TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings (The Minerals, Metals & Materials Series) 3031503481, 9783031503481

Citation preview

153 rd Annual Meeting & Exhibition

Supplemental Proceedings

The Minerals, Metals & Materials Series

The Minerals, Metals & Materials Society Editor

TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings

Editor The Minerals, Metals & Materials Society Pittsburgh, PA, USA

ISSN 2367-1181 ISSN 2367-1696 (electronic) The Minerals, Metals & Materials Series ISBN 978-3-031-50348-1 ISBN 978-3-031-50349-8 (eBook) https://doi.org/10.1007/978-3-031-50349-8 © The Minerals, Metals & Materials Society 2024 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.

This volume is a collection of papers from the TMS 2024 Annual Meeting & Exhibition, held March 3–7 in Orlando, Florida, USA. The contributions represent 53 symposia from the meeting. This volume, along with the other proceedings volumes published for the meeting, and TMS archival journals, represent the available written record of the over 90 symposia held at TMS2024.

Contents

Part I

2D Materials—Preparation, Properties, Modeling and Applications

A Novel Solid-Solution MXene with High Gravimetric Capacitance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wansen Ma, Zeming Qiu, Chaowen Tan, Chenzhen Hou, Xuewei Lv, Jinzhou Li, Liwen Hu, and Jie Dang An Overview of the Synthetic Route of Molybdenum Diselenide Nanoparticles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ita E. Uwidia, Esther U. Ikhuoria, Stanley O. Omorogbe, Ikhazuagbe H. Ifijen, Muniratu Maliki, and Aireguamen I. Aigbodion Exploring the Remarkable Gas Sensing Capability of Molybdenum Diselenide Nanoparticles . . . . . . . . . . . . . . . . . . . . . . . . . . . Asishana Paul Onivefu, Esther Uwidia Ikhuoria, Maliki Muniratu, and Ikhazuagbe Hilary Ifijen

3

12

30

Synthesis and Characterization of 2D WSe2 and Triple Cation Perovskite-Based Photoabsorbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Silvino P. Bastos, Sujan Aryal, and Anupama B. Kaul

47

Synthesis and Characterization of Selenides and Hybrid Halide Perovskites for Nanodevices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anupama B. Kaul

54

Two-Dimensional Solution-Processed Tungsten Diselenide’s Response to Nitrogen Gas Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ashique Zaman, Thomas Mather, and Anupama B. Kaul

62

vii

viii

Part II

Contents

Accelerated Testing to Understand the Long Term Performance of High Temperature Materials

Exploring the Service Life Extremes of 716 in Highly Corrosive Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tim Dunne, Lei Zhao, Jiaxiang Ren, Peng Cheng, Yu Liu, and Huailiang Liu

71

Part III Additive Manufacturing and Innovative Powder/Wire Processing of Multifunctional Materials Additive Manufacturing of Magnesium Alloys and Shape Memory Alloys for Biomedical Applications: Challenges and Opportunities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . F. Sayari and M. Yakout Functional and Mechanical Behavior of Ultra-Thin, Porous NiTi Fabricated via Laser Powder Bed Fusion . . . . . . . . . . . . . . . . . . . . . . . Londiwe Motibane, Lerato Tshabalala, Devon Hagedorn-Hansen, Silethelwe Chikosha, and Thorsten Becker Fused Filament Fabrication (FFF) Additive Manufacturing of Bronze-Based Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Simón Restrepo, Jaime Jaramillo, and Henry A. Colorado Influence of Temperature and Print Orientation on Anisotropic Sintering in Binder Jet SS316L . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Khadijeh Esmati, Apratim Chakraborty, Srinivas Pendurti, Arunkumar Natarajan, and Étienne Martin Mechanical Behavior of Tension of Multipolymers Through Fused Deposition Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Victor Paes Dias Gonçalves, Carlos Maurício Fontes Vieira, and Henry A. Colorado Preparation of Cu Powders with Electrical Explosion of Wires and Their Size-Dependent Mechanical Properties . . . . . . . . . . . . . . . . . . . Chenhui Wang, Luojia Zhang, Bingjia Wu, Kai Ding, Yulai Gao, and Bingge Zhao

85

96

105

113

122

132

Part IV Additive Manufacturing Fatigue and Fracture: Towards Rapid Qualification In-Situ Fatigue Life Prediction with Simulated Defects for Additive Manufacturing Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xueyong Qu, Leland Shimizu, and Jacob Rome

143

Contents

Part V

ix

Additive Manufacturing Materials in Energy Environments

Additive Manufacturing Nickel Base Alloy Characterization in Hydrogen Environment for Gas Turbine Applications . . . . . . . . . . . . . Iacopo Giovannetti, Massimiliano Buccioni, Angelo Donato, and Filippo Cappuccini Effects of Friction and Deformation Heating on Additively Manufactured M789 Steel During Hot Compression Tests . . . . . . . . . . . . Kudakwashe Nyamuchiwa, Ali Keshavarzkermani, and Clodualdo Aranas Performance of Laser Deposited Inconel 625 Coating During Heat Treatment and Carbonisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Monnamme Tlotleng, Paul Lekoadi, Reneilwe Kgoahla, Hosia Kgomo, Kgothatso Mokomele, Basebakhe Skhosane, Bathusile Masina, and Sisa Pityana Prototype Tooling for Bipolar Plates Challenges Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . P. Cyron, M. Beck, C. Karadogan, Nikola Nezic, and M. Liewald Part VI

159

172

181

190

Additive Manufacturing Modeling, Simulation and Machine Learning

Analyzing Micro-Macro Transitional Length Scale in 3D Printed Chopped Fiber Reinforced Polymer Materials . . . . . . . . . . . . . . . Indu Modala, Paromita Nath, and Nand Kishore Singh

205

Computational Modeling and Experimental Investigation of Additively Manufactured Fused Deposition Modeling Samples with In-Built Porosity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mosa Almutahhar, Khaled Al-Athel, Jafar Albinmousa, and Usman Ali

213

High-Strain Rate and High-Temperature Properties of Additively Manufactured Nickel-Based Alloy 718 . . . . . . . . . . . . . . . . . Anjali Sankar, Manjaiah Mallaiah, Thomas McCarthy, Jubert Pasco, Matthew Harding, and Clodualdo Aranas Numerical Analysis of Heat Accumulation During Wire Arc Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Ajay and Amber Shrivastava Softening Mechanisms in Additively Manufactured 420 Stainless Steel at Elevated Temperatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Harveen Bongao, Jubert Pasco, Thomas McCarthy, Kudakwashe Nyamuchiwa, and Clodualdo Aranas

224

235

244

x

Part VII

Contents

Additive Manufacturing: Materials Design and Alloy Development VI—Closed-Loop Alloy Design

Overcoming Challenges in Custom Powder Manufacturing—From Low-Melting and Reactive Materials to Refractories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ˙ Tomasz Choma, Łukasz Zrodowski, Jakub Ciftci, Bartosz Moro´nczyk, and Bartosz Kalicki

257

Part VIII Additive Manufacturing: Process-Induced Microstructures and Defects Effect of Laser Irradiation Mode on L-PBF Ti6Al4V Thin Sections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . John Daniel Arputharaj, Shahrooz Nafisi, and Reza Ghomashchi

273

Microstructural Evolution and Anisotropy in Stainless Steel 316L from Wire Arc Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . Neeraj K. Mishra, Jignesh Nakrani, V. Ajay, and Amber Shrivastava

290

Optimizing the DED 3D Printing Process for Improved Microstructure and Mechanical Performance . . . . . . . . . . . . . . . . . . . . . . . N. K. K. Arthur, C. W. Siyasiya, M. Tlotleng, and S. L. Pityana

299

Part IX Advanced Biomaterials for Biomedical Implants Bioactive Glasses for Bone Repair Application: A Review of Osteointegration and Controlled Ion Release Capabilities . . . . . . . . . . Casmir O. Okereke, Joshua Osaretin Onaifo, Stanley O. Omorogbe, Angela Ijioma Ogbu, and Ikhazuagbe Hilary Ifijen Corrosion Behavior of Ti-XCu Alloys for Dental Applications . . . . . . . . A. I. Alateyah, Marwa A. Abbas, Majed O. Alawad, Amal BaQais, H. Abd El-Hafez, Mohamed S. El-Asfoury, and W. H. El-Garaihy Part X

311

327

Advanced Functional and Structural Thin Films and Coatings

A Model of Particle Growth in Film Deposition . . . . . . . . . . . . . . . . . . . . . . Rahul Basu Functionalization Strategies for Rubber Seed Oil-Based Thin Films: A Critical Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aireguamen I. Aigbodion, Best Atoe, Ifeanyi J. Odiachi, Clinton A. Ehigie, and Ikhazuagbe H. Ifijen Influence of Alloying Agents on the Biodegradability of Zinc . . . . . . . . . Alejandra S. Román, Guadalupe M. Barrios Igoa, Edgar R. Ibañez, Natalia S. Zadorozne, Claudia M. Méndez, and Alicia E. Ares

341

350

366

Contents

xi

Tribological Behavior of a Hard TiB2 /TiC Multilayer Formed on M2 Steel Using a Duplex Process: Cathodic Arc Physical Vapor Deposition and Cathodic Reduction/Thermal Diffusion-Based Boriding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mehran Karimzadehkhoei, Erkan Kacar, Servet Timur, Mustafa Urgen, and Guldem Kartal Sireli Part XI

Advanced Materials for Energy Conversion and Storage 2024

Characterization of Black Mass After Different Pre-Treatment Processes for Optimized Metal Recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . Amalie My Olsen, Lars Arnberg, Sulalit Bandyopadhyay, and Ragnhild E. Aune Experimental Study on LaFeO3 /Nb2 O5 Oxygen Carrier in Chemical-Looping Partial Oxidation of Methane . . . . . . . . . . . . . . . . . . Yue Lai, Songming Zheng, Huamei Duan, Mujun Long, Dengfu Chen, Yandong Li, and Guoquan Zhang Methane Chemical Looping Partial Oxidation Over NiO/ Ce2 (SO4 )3 -MgO Oxygen Carrier to Produce High Purity Syngas . . . . . . Chengrui Wang, Songming Zheng, Mujun Long, Dengfu Chen, Huamei Duan, and Yandong Li Production and Characterization of Nickel Borides for Supercapacitor Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mehtap Arslan-Kaba, Servet Timur, and Guldem Kartal Sireli Part XII

377

389

409

420

435

Advanced Real Time Imaging

Formation Mechanism of Band Delta-Ferrite in 416 Stainless Steel and Its Relationship with MnS and M23 C6 . . . . . . . . . . . . . . . . . . . . . Yi Wang, Qianren Tian, Xiangyu Xu, and Jianxun Fu

443

Part XIII Advanced Soft Magnets and Magnetocaloric Materials: An FMD Symposium in Honor of Victorino Franco Entropy Change at a Demagnetization Broadened First Order Transition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Syed Q. A. Shah, Balamurugan Balasubramanian, and Christian Binek

457

xii

Contents

Part XIV Advances in Biomaterials for 3D Printing of Scaffolds and Tissues Biodegradable Polymers for 3D Printing of Tissue Engineering Scaffolds: Challenges and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . Eribe M. Jonathan, Osarumen E. Oghama, Ikhazuagbe Hilary Ifijen, and Gregory E. Onaiwu Bioink Formulations for 3D Printing of Tissue Scaffolds: A Review of Materials and Printability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Faithfulness O. Osazee, Andrew O. Ohifuemen, Jeffery I. Omoruyi, Ikhazuagbe Hilary Ifijen, and Godfrey Otabor Filaments Made of Magnesium-Incorporated Polymer for Potential Use in Bone Implants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sumama Nuthana Kalva and Muammer Koç Part XV

469

484

500

Advances in Ceramic Materials and Processing

Chemical Tempering of Soda Lime Silicate Glass by Electric Field Assisted Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Redae Fisseha Asfaw and Vincenzo M. Sglavo

509

Development and Characterization of Lightweight ZrB2 –B4 C Functionally Graded Composites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ajit Kumar Naik, D. K. V. D. Prasad, Tapas Laha, and Siddhartha Roy

522

Effect of Multi-axial Forging on Mechanical Properties and Microstructure of AA7075/TaC Composites . . . . . . . . . . . . . . . . . . . . . John Samson Khalkho and Dagarapu Benny Karunakar

530

Glass Waste Powders as Additives Based Ceramic Materials for Additive Manufacturing of Bricks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Carlos F. Revelo, G. B. Henrique Martins, Geovana C. G. Delaqua, Carlos M. F. Vieira, and Henry A. Colorado Hierarchically Porous, Diatomite-Based Absorbents Fabricated by Combining 3D-Printed Templating and Freeze Casting Techniques for Wastewater Treatments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Li-Chin Li, Haw-Kai Chang, Yu-Hsiang Lo, and Po-Yu Chen

547

559

Mass Spectrometric Investigation of Thermodynamic Properties of CaSiO3 Wollastonite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sergey Shornikov

568

Phase Transition Behavior of Rare Earth Oxide Ce2 O3 in CaO–SiO2 –5wt.% Al2 O3 System at 1673–1873 K . . . . . . . . . . . . . . . . . . Rensheng Li, Renyi Yang, Xu Gao, Wanlin Wang, and You Zhou

577

Contents

xiii

Production of Ceramic Tiles with Glass Waste and Kaolinitic Clay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L. A. dos Santos, G. C. G. Delaqua, and C. M. F. Vieira

590

The Thermophysical Properties of (Gd1-x Lax )2 Zr2 O7 Synthesized by the Molten Salt Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hao Chen, Yingqin Wang, Xin Lu, and Hao Bai

598

Thermodynamic Analysis of Fe2 AlB2 Prepared by Molten Salt Electrochemical Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ning Han, Hongyan Yan, Ju Meng, Enze Cui, Hui Li, and Jinglong Liang Thermodynamic Analysis of Fe3 Si Prepared from Steel Slag by Molten Salt Electrolytic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Enze Cui, Hongyan Yan, Ju Meng, Ning Han, Hui Li, and Jinglong Liang Part XVI

621

Advances in Magnetism and Magnetic Materials

Crystal Lattice Structure Prediction of Fe-Based Compounds by a Molecular Dynamics Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jianxin Zhu and Jian-Ping Wang Magnetic and Optical Study of Zinc Ferrite Produced by the Ceramic Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mery C. Gómez-Marroquín, Fernando Huamán-Pérez, Henry Colorado, Nilton Cárdenas-Falcón, José Carlos D’Abreu, Abraham J. Terrones-Ramirez, and Kim J. Phatti-Satto Part XVII

612

633

644

Advances in Multi-Principal Element Alloys III: Mechanical Behavior

Dependence on Their Mn and Cr Contents of the Microstructures, Melting Range, and High Temperature Creep Behaviors of Cantor’s Alloy and Versions Strengthened by MC Carbides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Corentin Gay, Pauline Spaeter, Nassima Chenikha, Lionel Aranda, and Patrice Berthod

659

Microstructural Analysis of MoNbZrTiV Refractory High-Entropy Alloy Developed via High-Energy Mechanical Alloying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marvin S. Tolentino, Aisa Grace D. Custodio, Gobinda C. Saha, and Clodualdo Aranas Jr.

669

Thermo-mechanical Behavior of HEA Alloys Containing Interdendritic MC Carbides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Patrice Berthod, Lionel Aranda, and Anne Verniere

679

xiv

Contents

Part XVIII

Advances in Surface Engineering VI

A Study on the Wear Behavior of Al2 Ce-p Reinforced Al Matrix Composite Layers at an Elevated Temperature . . . . . . . . . . . . . . . . . . . . . . Mertcan Kaba, Sezgin Cengiz, Faiz Muhaffel, and Hüseyin Çimeno˘glu Coating Development for High Temperature Dissolvable Rubber Element in Dissolvable Plug Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . Jiaxiang Ren, Peng Cheng, Lei Zhao, Yu Liu, Huailiang Liu, Xuefeng Cui, Bing Zhu, Qingjiang Wang, and Wei Ma

691

698

Electrodeposition Preparation and Performance Enhancement Mechanisms for Ni–Co–Fe Coatings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yizhe Du, Xuan Chen, Zhenyu Sun, and Dengfu Chen

706

Improving the Corrosion and Wear Behaviour of ECAP-Processed Biodegradable Mg-Zn-Ca Alloy for Bone Repair Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . W. H. El-Garaihy, A. I. Alateyah, A. Alrumayh, Amal BaQais, Majed O. Alawad, and Mohamed S. El-Asfoury

717

Part XIX Advances in the State-of-the-Art of High Temperature Alloys Thermodynamic Model-Guided Regulation of Self-propagating In-Situ Synthesis of Titanium–Aluminum Alloys . . . . . . . . . . . . . . . . . . . . Han Jiang, Zhihe Dou, and Ting’an Zhang Part XX

733

Advances in Titanium Technology

A New Low-Cost, Short-Flow, and Clean Preparation Process for Ti6Al4V Alloys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Daoguang Du, Jishen Yan, Zhihe Dou, and Ting’an Zhang

751

Insight into the Impacts of Heat Treatment on Microstructure and Mechanical Properties of TC11 Titanium Alloy . . . . . . . . . . . . . . . . . Zhen Yan and Jianfa Jing

763

Part XXI

AI/Data Informatics: Computational Model Development, Verification, Validation, and Uncertainty Quantification

A Dataset of CFD Simulated Industrial Furnace Images for Conditional Automatic Generation with GANs . . . . . . . . . . . . . . . . . . . Ricardo Calix, Orlando Ugarte, Hong Wang, and Tyamo Okosun

775

Contents

xv

Finding “Trigger Sites” of Reactions Among Heterogeneous Materials from X-ray Microscopic Big Data Using Persistent Homology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Masao Kimura, Ippei Obayashi, Daiki Kido, Yasuhiro Niwa, Xichan Gao, and Kazuto Akagi

784

Research on the Model of Matching Inventory Slab with Order Contracts of Steel Enterprises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cheng-hong Li, Ming-mei Zhu, Xian-wu Zhang, and Kun-chi Jiang

793

Simulating Castable Aluminum Alloy Microstructures with AlloyGAN Deep Learning Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Biao Yin and Yangyang Fan

804

Temperature Prediction of Continuous Casting Slab Based on Improved Extreme Learning Machine . . . . . . . . . . . . . . . . . . . . . . . . . . . Kun-chi Jiang, Ming-mei Zhu, Cheng-hong Li, Xian-Wu Zhang, Hong-yu Lin, Kai-tian Zhang, and Zhong Zheng Part XXII

Algorithm Development in Materials Science and Engineering

A Line-Free Discrete Dislocation Dynamics Method for Finite Domains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aitor Cruzado, Pilar Ariza, Alan Needleman, Michael Ortiz, and Amine Benzerga Capturing Hydrogen Embrittlement Effects with Hydrogen Diffusion Simulation and Crystal Plasticity . . . . . . . . . . . . . . . . . . . . . . . . . Junyan He, Anupam Neogi, Deepankar Pal, Ali Najafi, and Grama Bhashyam Inverse Problem Analysis of Phase Fraction Prediction in Aluminum Alloys Using Differentiable Deep Learning Models . . . . . . Yu Okano, Takeshi Kaneshita, Shimpei Takemoto, and Yoshishige Okuno Part XXIII

812

825

833

843

Bio-Nano Interfaces and Engineering Applications

Molecular Insights into Mineral Nanoparticle Interactions with Proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vadim G. Kessler Quantifying Surface Topographies on Antimicrobial Copper . . . . . . . . . Terry C. Lowe, Daniela P. Hirsch, Scott C. Dahl, Beatrice L. Lowe, Clinton L. Hawkins, Naveen S. Kailas, Máté Sz˝ucs, and Laszlo S. Toth

855 864

xvi

Contents

Part XXIV

Biological Materials Science

Challenges and Future Perspectives of Biomimetic Materials for Biomedical Applications: Bridging the Gap Between Nature and Medicine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Augustine Ighodaro, John A. Osarobo, Innocent C. Onuguh, Osahon K. Ogbeide, and Ikhazuagbe H. Ifijen

877

Physico-Chemical Evaluation of Compost and Inorganic Fertilizer for Environmental and Agricultural Management . . . . . . . . . . I. E. Uwidia, E. O. Oshodin, G. Bright, and P. A. Oham

897

Silk Biomaterials in Wound Healing: Navigating Challenges and Charting the Future of Regenerative Medicine . . . . . . . . . . . . . . . . . . Best Atoe, Ikhazuagbe H. Ifijen, Igbako Philip Okiemute, Okeke I. Emmanuel, and Muniratu Maliki Part XXV

904

Chemistry and Physics of Interfaces

Effect of the Welding Current on the Liquid Metal Embrittlement in the Resistance Spot Welded Galvanized DP1180 Advanced High Strength Steel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jiayi Zhou, Yu Sun, Bingjia Wu, Tianhan Hu, Ming Lei, Kai Ding, and Yulai Gao Part XXVI

Cold Spray Additive Manufacturing: Part Quality and Performance

Investigating the Bonding Types and Impact Modes in Cold Spray Deposition of AlCoCrFeNi HEA on Steel Substrate . . . . . . . . . . . . Aisa Grace D. Custodio, Marvin S. Tolentino, Gobinda C. Saha, and Clodualdo Aranas Jr. Part XXVII

933

Computational Thermodynamics and Kinetics

The Kinetic Study of Carbonation of BOF Slag at High Temperature: Impact of Particle Size Characteristics . . . . . . . . . . . . . . . . Zhenghao Wang, Songming Zheng, Yue Lai, Huamei Duan, Dengfu Chen, Mujun Long, and Yandong Li Thermodynamic Calculations of Precipitate Phases in FeCr17 Mn11 Mo3 Nx Powder Based on JMatPro . . . . . . . . . . . . . . . . . . . Dongjia Wang, Guolong Ni, Shuhuan Wang, and Jiawei Liu Part XXVIII

923

943

953

Defects and Interfaces: Modeling and Experiments

3D Discrete Dislocation Dynamics Simulations of Multiple Spiral Dislocation Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Luo Li and Tariq Khraishi

969

Contents

xvii

Atomistic Simulation of Hydrogen-Defect Interactions in Palladium Nanoparticles Across Multiple Time Scales . . . . . . . . . . . . . Xingsheng Sun and Youyun Xu

978

First Principles Study on the Segregation of Metallic Solutes and Non-metallic Impurities in Cu Grain Boundary . . . . . . . . . . . . . . . . . Vasileios Fotopoulos, Jack Strand, Manuel Petersmann, and Alexander L. Shluger

989

Hydrogen-Induced Transformation of Dislocation Core in Fe and Its Effect on Dislocation Mobility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1000 Md. Shahrier Hasan, Hadia Bayat, Colin Delaney, Christopher Foronda, and Wenwu Xu Void Nucleation in a Through Silicon Via (TSV): Unraveling the Role of Tilt Grain Boundaries Through Atomistic Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1008 Armin Shashaani and Panthea Sepehrband Part XXIX

Defects and Properties of Cast Metals

Avoiding the Cold Shut Defect by Introducing the Shape Factor Modifying Chvorinov’s Rule in Aluminum Gravity Die Casting . . . . . . . 1021 Fu-Yuan Hsu, Chi-Ming Hung, and Zhang-Yuan Luo Control of Surface Longitudinal Cracks During the Steel Continuous Casting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1031 Fengkang Wang, Jie Zeng, and Wanlin Wang Effect of RE Content on TiN Inclusions Formation in P110-Grade Casing Steel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1040 Jinwen Liu, Haiyan Tang, Gen Li, Kaimin Wang, Yuhang Wang, and Jiaquan Zhang How Various Inoculants and Their Amount Influence on the Metal Expansion Penetration in Grey Cast Iron Component . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1052 Izudin Dugic In-Suit Observation of the Formation of CeAlO3 Clusters on the Surface of an Al-Killed Molten Steel . . . . . . . . . . . . . . . . . . . . . . . . . 1067 Qiuyue Zhou and Lifeng Zhang Kinetic Evolution of the Composition of Desulfurizers in the Molten Steel During RH Refining Process . . . . . . . . . . . . . . . . . . . . . 1075 Jujin Wang and Lifeng Zhang Mold Simulator Study of Lubrication Behavior of High Carbon Steel Slag Film Inside Continuous Casting Mold . . . . . . . . . . . . . . . . . . . . . 1086 Zichao Wang, Wanlin Wang, Haihui Zhang, and Jie Zeng

xviii

Contents

Study of Tube/Pipe Cracking Induced by Casting Defects in Medium Carbon Steels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1095 Tihe Zhou, Youliang He, Peng Zhang, and Ryan Lu Study on Secondary Phase Precipitation Behavior of Ship Plate Steel Slab Under Different Cooling Rates in Continuous Casting Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1104 Huisheng Wang, Qing Liu, Biao Tao, Jun Wu, Ming Li, Min Guan, and Weili Huang Part XXX

Electrical Steels

Effect of Processing Methods on the Magnetic Properties of Non-oriented Electrical Steel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1119 Shengjie Wu, Wanlin Wang, Chongxiang Yue, and Hualong Li Effect of Melt Superheat on Interfacial Heat Transfer Behavior of Sub-Rapid Solidification Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1131 Lulu Song, Wanlin Wang, Xueying Lyu, Yunli Zhang, and Huihui Wang Influence of Hot Rolling Reduction Rate on the Microstructure and Texture of a Strip Cast Fe-2.5 wt.% Si Non-oriented Electrical Steel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1139 Huihui Wang, Wanlin Wang, Peisheng Lyu, Chenyang Zhu, Xueying Lyu, Lulu Song, and Yunli Zhang Interfacial Heat Transfer Behavior Between Liquid Steel and Mold of Non-oriented Electrical Steel Containing Manganese in Thin Strip Continuous Casting . . . . . . . . . . . . . . . . . . . . . . . 1146 Xueying Lyu, Wanlin Wang, Yunli Zhang, Lulu Song, and Huihui Wang Recrystallization of a 2.8 wt% Si Non-oriented Electrical Steel After Skew Cold Rolling at Different Angles to the Hot Rolling Direction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1156 Youliang He and Mehdi Sanjari Part XXXI

Electronic Packaging and Interconnection Materials

Numerical Modeling of Electromigration in Al(0.25 at. % Cu) Interconnects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1169 James Gordineer and Ping-Chuan Wang

Contents

Part XXXII

xix

Environmental Degradation of Multiple Principal Component Materials

Aloe Saponaria Gel as a Green Corrosion Inhibitor of Carbon Steel in an Acid Medium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1183 Flavia A. Schmidt, Alicia E. Ares, and Claudia M. Méndez Behavior in Cooling-Induced Oxide Scale Spallation of Original and Modified Cantor’s HEA Alloys Oxidized at High Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1194 Nassima Chenikha, Corentin Gay, Pauline Spaeter, Lionel Aranda, and Patrice Berthod Corrosion Resistance of 316L Stainless Steel in HCL and FeCl3 . . . . . . . 1205 ThankGod Nwokocha and T. David Burleigh Environmental Degradation of Polymer-Based Composite Materials: Challenges and Mitigation Strategies . . . . . . . . . . . . . . . . . . . . . 1218 Kate Mokobia, Eribe M. Jonathan, Glory Oyiborhoro, Muniratu Maliki, and Ikhazuagbe Hilary Ifijen Environmental Impact of Multi-component Fiber-Reinforced Composites: Challenges and Green Solutions . . . . . . . . . . . . . . . . . . . . . . . . 1237 Glory Oyiborhoro, Bala Anegbe, Ifeanyi J. Odiachi, Best Atoe, and Ikhazuagbe Hilary Ifijen Investigation of Mechanical Stress and B10 Exposure on FKM Polymer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1253 Qi An, Ralph Bäßler, Andreas Hertwig, Heike Strehlau, Gundula Hidde, and Frank Otremba Isothermal High Temperature Oxidation of Cantor’s-Based MC-Reinforced HEAs Versus Their Mn and Cr Contents . . . . . . . . . . . . 1262 Pauline Spaeter, Nassima Chenikha, Corentin Gay, Lionel Aranda, and Patrice Berthod Study of the Corrosive Effect of Enzymatic, Multi-enzymatic, and Sodium Hypochlorite Solutions on Surgical Grade Stainless Steel Instruments Used in the Operating Room Area of the Clinical Hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1273 Jhasmmany G. Lovera and Jaime A. Rocha Part XXXIII

Environmentally Assisted Cracking: Theory and Practice

Effect of Hydrogen Concentration and Residual Stress on the Delayed Cracking Performance of the 22MnB5 Hot Roll Bending Pipe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1285 Ping Zhu, Tianhan Hu, Jiayi Zhou, Yu Sun, Wufeng Dong, Kai Ding, and Yulai Gao

xx

Contents

Hydrogen Content and Charpy Toughness of Pipeline Steels with Different Hydrogen Charging Processes . . . . . . . . . . . . . . . . . . . . . . . . 1295 Xin Pang and Su Xu Part XXXIV

Fatigue in Materials: Fundamentals, Multiscale Characterizations and Computational Modeling

The Effect of Injection-Production Process Parameters on the Fatigue Life of High-Pressure Injection-Production String . . . . . 1307 Lihua Wan, Zhihuan Wang, Songyuan Ai, Haohao Zhang, Rundong Zhang, Mujun Long, Huamei Duan, and Dengfu Chen Part XXXV

Formability and Spring-Back Issues in Ultra-High Strength Steels and High Strength Aluminum Alloys

Influence of Yoshida-Uemori Model on Springback Prediction . . . . . . . . 1321 X. Lemoine and J. M. Devin Part XXXVI

Functional Nanomaterials 2024

Phytochemical-Mediated Green Synthesis of Silver Oxide Nanoparticles for Potential Cholera Treatment . . . . . . . . . . . . . . . . . . . . . . 1333 Rachel O. Okojie, Esther U. Ikhuoria, Ita E. Uwidia, Ikhazuagbe H. Ifijen, and Ikechukwu D. Chikaodili Prospects of Utilizing Environmentally Friendly Iron Oxide Nanoparticles Synthesized from Musa Paradisiaca Extract for Potential COVID-19 Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1344 Esther U. Ikhuoria, Ita E. Uwidia, Rachel O. Okojie, Ikhazuagbe H. Ifijen, and Ikechukwu D. Chikaodili Recent Advances in the Application of Manganese Oxide Nanoparticles for Remediation of Soil Contaminated with Organic Pollutants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1358 Bala Anegbe and Ikhazuagbe H. Ifijen Synthesis of Ternary Oxide Nanoparticles of Iron, Silver, and Vanadium from Blended Extracts for Potential Tuberculosis Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1375 Ita E. Uwidia, Esther U. Ikhuoria, Rachel O. Okojie, Ikhazuagbe H. Ifijen, and Ikechukwu D. Chikaodili Part XXXVII

High Performance Steels

Digital Design of a Lightweight and Low-Cost UHS Steel . . . . . . . . . . . . . 1389 Antonio Vazquez Prudencio, Unnur Lilja Þórðardóttir, Lu Meng, Robiul Haque Shaikh, and Qing Chen

Contents

xxi

Effect of Cerium on the Nucleation and Microstructure of High-Strength Low-Alloy Steel During Solidification . . . . . . . . . . . . . . 1400 Fei Huang and Jing Li Effect of Vanadium on the Mechanical and Microstructural Properties of Medium-Mn Steels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1412 Felisters Zvavamwe, Minkyu Paek, Kudakwashe Nyamuchiwa, and Clodualdo Aranas Jr. Formation and Decomposition Mechanism of Carbides in AISI M35 High-Speed Steel Produced by ESR . . . . . . . . . . . . . . . . . . . . . . . . . . . 1418 Wei Liang, Jing Li, and Jia-hao Li Phase Transformation, Microstructure, and Mechanical Properties on Nickel-Free High Chromium Weld Metal . . . . . . . . . . . . . . 1428 Fikret Kabakcı, Mustafa Acarer, and Nurcan Akduran Precipitation and Evolutionary Behavior of Eutectic Carbides in Electroslag Remelted 7Cr13N Steel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1439 Shouhui Li, Jing Li, and Shuang Zhu Part XXXVIII

High Temperature Electrochemistry: An FMD Symposium Honoring Uday B. Pal

Considerations for Measuring High Electrical Conductivity Molten Salts with Concentric Electrodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1451 Thomas Villalón Electrically-Enhanced Boron and Phosphorus Removal from Silicon by CaO–SiO2 –Al2 O3 /–MgO Slag Treatment . . . . . . . . . . . . . 1459 Andreas Diga Pratama Putera, Katri Avarmaa, Matthew Humbert, Himawan Tri Bayu Murti Petrus, Geoffrey Brooks, and M. Akbar Rhamdhani The Effect of Temperature on Electrodeposition Behavior of Cobalt from Cobalt Chloride Using 2:1 Urea/ChCl Ionic Liquid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1472 Rajyashree Lenka and Ramana G. Reddy Part XXXIX

Incorporating Additive Manufacturing in Material Science and Engineering Education (2024 Student-led Symposium)

Teaching Introductory Materials Engineering Via Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1483 Timothy Chambers

xxii

Contents

Using Additive Manufacturing and Active Methods for Teaching Materials and Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1490 Henry A. Colorado Part XL

Irradiation Testing: Facilities, Capabilities, and Experimental Designs

Challenges and Solutions for Fast Neutron Irradiation of Bulk Material Specimens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1499 N. Woolstenhulme, M. Worrall, and C. Downey Part XLI

Materials and Chemistry for Molten Salt Systems

Effect of Chloride Molten Salt on the Structural Characteristics of Deposited Carbon-Based Electrolysis Products . . . . . . . . . . . . . . . . . . . . 1517 Tao Rong, Haibin Zuo, Qingguo Xue, and Haoqing Yang Thermodynamic Analysis of Preparation of Fe-Si/Fe3 Si Intermetallic by Treating Valuable Elements in Red Mud with Molten Salt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1529 Geng Chen, Hui Li, and Jinglong Liang Thermodynamic Analysis of the Recovery of Metallic Mn from Waste Lithium Manganese Battery Using the Molten Salt Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1539 Ling Yue Song, Hui Li, and Jinglong Liang Part XLII Materials Processing and Kinetic Phenomena: From Thin Films and Micro/Nano Systems to Advanced Manufacturing Fabrication of Periodic Textures at Micron Level on Silicone Membrane Using Femtosecond Laser . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1551 S. Chatterjee, A. S. Cholkar, D. Kinahan, and D. Brabazon Part XLIII

Materials Science for Global Development— Health, Energy, and Environment: An SMD Symposium in Honor of Wole Soboyejo

Conjoint Influence of Thermal and Stress Cycling on Functional Fatigue Behavior of the NiTiZr Shape Memory Alloys . . . . . . . . . . . . . . . 1565 S. Santosh and T. S. Srivatsan Fatigue Crack Growth Rate Behaviour of an Additive Manufactured Nickel-Base Superalloy Inconel 718 . . . . . . . . . . . . . . . . . . . 1575 A. R. Anilchandra, B. Bharath, N. V. Sreekanth, J. Sharanabasavaraja, T. S. Srivatsan, and C. M. Manjunatha

Contents

xxiii

Recycled Wood-Geopolymer Concrete Blocks as Sustainable Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1585 Jong-Leng Liow, Amar Khennane, Firesenay Zerabruk Gigar, and Elmira Katoozi Part XLIV

Measurement and Control of High-Temperature Processes

A Complete Thermal Analysis of a Funnel-Type Mold Used in High-Speed Thin Slab Continuous Casting Through Three-Dimensional Inverse Heat Conduction Problem . . . . . . . . . . . . . . . 1599 Ce Liang, Haihui Zhang, and Wanlin Wang Advances in Magnetic Measurements and Externally Applied Magnetic Fields for Vacuum Arc Remelting Process Monitoring and Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1609 M. Cibula, J. Motley, N. Pettinger, D. McCulley, and P. King Fiber Optic Application in Metallurgical Processes’ External and Internal Temperature Monitoring of Metallurgical Furnaces with Distributed Temperature Sensor (DTS) . . . . . . . . . . . . . . . . . . . . . . . . 1623 Luis E. Gonzalez Gomez, Luis Chambi Viraca, Stefany Michelle Huanca Choque, and Carlos Acho Flexible Flame Staging Improving Copper Scrap Oxidation and Reduction Steps Toward Its Recovery at Recope Laminação . . . . . . 1642 Brenno Ferreira, William Mahoney, Joachim von Scheele, Edson Isihara, Brenno Silva, Eduardo Sarti, and Julio Bittencourt Linde’s Image Analysis System to Tune Burners for Lead Recovery from Automotive Batteries in Rotary Furnaces . . . . . . . . . . . . . 1654 Brenno Ferreira, Izaias Marques, Martin Adendorff, and Joachim von Scheele Metallurgical Production Process Improvement with Probes and Measuring Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1665 Jean-Francois Stumper, Marvin Schmidt, Filipe Rodrigues, Mark Kruessmann, and Marc Flammang Part XLV

Mechanical Response of Materials Investigated Through Novel In-situ Experiments and Modeling

In Situ Micro-computed Tomography of Re-entry Fabrics Under Tensile Loading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1681 Collin Foster, Cutler Phillippe, Laura Villafañe Roca, and Francesco Panerai Virtual XRD Method in Molecular Dynamics Simulation and a Case Study for Fe16 N2 and Fe8 N Thin Films . . . . . . . . . . . . . . . . . . . 1693 Jianxin Zhu and Jian-Ping Wang

xxiv

Part XLVI

Contents

Phase Stability in Extreme Environments II

Rhenium-Free Heat-Resistant Nickel Alloy for the Cast Blades Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1707 Evgeniy Milonin and Valeriy Naumyk Part XLVII

Phase Stability, Phase Transformations, and Reactive Phase Formation in Electronic Materials XXIII

Superplasticity Deformation of Sn-Bi-Based Solder Alloys . . . . . . . . . . . . 1715 Akira Yamauchi and Masashi Kurose Part XLVIII

Phase Transformations and Microstructural Evolution

Characteristics of Primary Carbide and Its Evolution During Hot Rolling in High-Carbon Chromium Bearing Steel . . . . . . . . . . . . . . . 1725 Zhuang Zhang, Hao Geng, Pu Wang, Peng Lan, Hai-yan Tang, and Jia-quan Zhang Effect of Interlayer Towards the Joint Properties Enhancement of Dissimilar Friction Welded SS321-AA2219 . . . . . . . . . . . . . . . . . . . . . . . 1734 Neeraj Kumar Mishra, S. G. K. Manikandan, N. Neethu, C. Jebasihamony, and Amber Shrivastava Effect of MgO on Mineral Phase and Structure of Vanadium Slag . . . . . 1745 Cancan Yu, Jinan Wang, Yiyu Qiu, Jiang Diao, Hongyi Li, and Bing Xie Effect of the Heating Rate on the Austenite Formation Kinetics by Isoconversion Method in Cr–Mo–V Steel . . . . . . . . . . . . . . . . . . . . . . . . . 1756 R. Guzman-Garfias, O. Vázquez-Gómez, P. Garnica-González, H. J. Vergara-Hernández, and J. A. Barrera-Godínez Impact of Aluminium and Cooling Conditions on Silicon Distribution in High Si-SGI by Performing 3D-Microstructure Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1765 Betto David Joseph, Björn Pustal, and A. Bührig-Polaczek Microstructural Evolution During Homogenization Heat Treatment of AA 6063 Alloy in Batch and Continuous Furnaces . . . . . . 1776 Akin Obali, Mertol Gökelma, Deniz Kavrar Ürk, Murat Do˘gan, and Gökçen Gökçe Optimization of Carbon Reduction and Efficiency Enhancement Process for Hot-Rolled Ribbed Steel Bars . . . . . . . . . . . . . . . . . . . . . . . . . . . 1783 Liu Yang and Gao Ming Phase Transformation upon Dissimilar Laser Welding of Al5083 and SS304 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1799 Parth Vaidya and Amber Shrivastava

Contents

xxv

Texture Preference and Variant Analysis of Martensite Formation in Laser Powder Bed Fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1808 Jubert Pasco, Youliang He, Ali Keshavarzkermani, and Clodualdo Aranas Part XLIX

Powder Materials Processing and Fundamental Understanding

An Atomistic Modeling Study of Electric Field Effect on Sintering Mechanisms of Zirconia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1819 Kyrel Polifrone, Colin Delaney, Md. Shahrier Hasan, Hadia Bayat, Christopher Foronda, Eugene Olevsky, and Wenwu Xu Preparation, Phase Structure, and Solubility of MnV2 O6 and Mn2 V2 O7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1827 Zhuoyang Li, Guishang Pei, Mengjiao Jiao, Yongda Li, Ningyu Zhang, and Xuewei Lv Preparation, Structure, and Characterization of SFCA-I . . . . . . . . . . . . . 1836 Yongda Li, Junjie Zeng, Ningyu Zhang, Yuxiao Xue, Yong Hou, and Xuewei Lv Part L

Process Metallurgy and Environmental Engineering: An EPD Symposium in Honor of Takashi Nakamura

Acidic and Ammonium Sulphate Leaching of Historic Copper Tailings from Copperbelt Province, Zambia . . . . . . . . . . . . . . . . . . . . . . . . . 1849 Misozi Makangila, Yotamu R. S. Hara, Kakoma Maseka, and Rainford Hara Application of the Thiocyanate-Thiourea System for the Leaching of Copper Present in Tailings from Pachuca, Hidalgo, Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1858 Erick Jesús Muñoz Hernández, Melissa Gordillo Salazar, Martin Reyes Pérez, Elia Guadalupe Palacios Beas, Aislinn Michelle Teja Ruiz, José Ángel Cobos Murcia, Ángel Ruiz Sánchez, and Julio Cesar Juárez Tapia Assessment of the Glycine Concentration for the Leaching of Cu, Zn, and Pb Contained in Tailings in the Presence of Thiourea . . . . . . . . . 1867 Erick Jesús Muñoz Hernández, Melissa Gordillo Salazar, and Ángel Ruiz Sánchez

xxvi

Contents

Characterization of Solid Mining Waste in the Urbanized Area of Zimapan, Hidalgo, for the Identification of Economically Valuable Elements and Trace Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1876 Aislinn Teja Ruiz, Julio Cesar Juárez-Tapia, Gabriel Cisneros-Flores, Jesús Iván Martínez-Soto, Martin Reyes-Pérez, Iván Alejandro Reyes-Domínguez, Hugo Garcia Ortiz, and Uriel Mizraim Flores Guerrero Correlation of the Initial Absorption Coefficient and the Compression Resistance of Concrete Blocks (Vibro-Compacted), with the Addition of Fly Ash and an Additive . . . . 1886 Hugo García Ortíz, Julio César Juárez Tapia, Martín Reyes Pérez, Miguel Pérez Labra, and Edgar Martínez Rojo DOWA Recycling Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1896 K. Miwa, H. Watanabe, T. Tokumoto, and S. Nakagawara Electro-Winning in Basic Medium, for the Recovery of Tin from By-Products Generated by the Harris I Process, at the Karachipampa Metallurgical Company . . . . . . . . . . . . . . . . . . . . . . . 1902 Quispe Ticona Maria Eugenia Investigation of Roast-Leach of High Sulphur Containing Slag from Luanshya, Zambia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1912 Yaki Chiyokoma Namiluko, Yotamu Rainford Stephen Hara, Agabu Shane, Brenda Chitewo, Rainford Hara, and Stephen Parirenyatwa LAREX-Tupy Process: Recycling of Li-Ion Batteries from Electric Vehicles by Hydrometallurgical Route Towards Circular Economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1920 Amilton Barbosa Botelho Junior, David Vasconcelos da Silva, Anastássia Mariáh Nunes de Oliveira Lima, Rafael Piumatti de Oliveira, Luciana Assis Gobo, Elio Augusto Kumoto, Andre Ferrarese, Jorge Alberto Soares Tenório, and Denise Crocce Romano Espinosa Pilot Trials on Zinc Fuming with Hydrogen Gas . . . . . . . . . . . . . . . . . . . . . 1928 Ida Heintz, Magnus Heintz, Magnus Ek, David Muren, and Jill Sundberg Recovery of Cobalt and Zinc from Metallurgical Wastewater Via a Selective Chelation Precipitation and Flotation Process . . . . . . . . . 1938 Yanfang Huang, Meimei Wang, Bingbing Liu, Guihong Han, and Hu Sun

Contents

xxvii

Recovery of Iron from Copper Tailings Using a Combined Direct Reduction–Magnetic Separation Process . . . . . . . . . . . . . . . . . . . . . 1946 Buxin Chen, Minghong Deng, Mengjun Hu, Mengyao Dong, and Meilong Hu Resource Utilization of Copper Slag with a Focus on Impoverishment and Reduction: A Review . . . . . . . . . . . . . . . . . . . . . . . 1957 Jun Hao, Zhi-he Dou, and Ting-an Zhang Selective Recovery of Zn and Mn from Waste Zinc–Manganese Batteries by Autocatalytic Reduction Roasting Followed by Leaching Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1965 Zijian Su, Bin Lei, and Wei Lv Solvent Extraction Process of Nickel Sulfate for Battery Materials . . . . 1974 Y. Yamaguchi, H. Nakagawa, and M. Suginohara Part LI

Solidification in External Fields

Industrial Trials of Permanent Magnet Stirring During Billet Continuous Casting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1985 Jianfei Peng, Shuaijie Yuan, Wanlin Wang, and Jie Zeng Part LII

The Future of Work in Materials Science

Leveraging Remote Work to Accelerate Material Informatics by Implementing Machine Learning Web Applications and Introducing Statistical Analysis Tools for Materials Scientists in a Chemical Corporation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1997 Yoshishige Okuno Remote Collaboration and Education in 3D Printing (3DP): Strategies for Engaging and Training Remote Learners . . . . . . . . . . . . . . 2006 Arslan Yousaf and Muammer Koç Part LIII Towards a Future of Sustainable Production and Processing of Metals and Alloys Melting Efficiently Rare Earth Steel by Whole Scrap Steel . . . . . . . . . . . 2023 Qian Long, Xu Gao, Jie Zeng, You Zhou, Zai-Xue Zheng, and Wanlin Wang Research on Pellet Hydrogen Reduction Followed by Melting Separation for Utilizing Oolitic High-Phosphorus Iron Ore . . . . . . . . . . . 2034 Hao Yu and Huiqing Tang Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2045 Subject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2053

Part I

2D Materials—Preparation, Properties, Modeling and Applications

A Novel Solid-Solution MXene with High Gravimetric Capacitance Wansen Ma, Zeming Qiu, Chaowen Tan, Chenzhen Hou, Xuewei Lv, Jinzhou Li, Liwen Hu, and Jie Dang

Abstract MXenes are a recently discovered family of two-dimensional (2D) early transition metal carbides or carbon-nitrides that have shown many attractive properties and hold great promise for energy storage and other applications. Although many MXenes have been synthesized, most studies have focused on Ti3 C2 Tx or other single-transition metal MXenes. In addition, studies on the electrochemical properties of solid-solution MXenes are scarce. Herein, a new vanadium-titanium double transition metal MAX phase and its corresponding MXene were successfully synthesized. By combining X-ray diffraction, X-ray photoelectron spectroscopy, energy dispersive X-ray spectroscopy, transmission electron microscopy, and scanning transmission electron microscopy, we determined the structure and phase purity of vanadium-titanium double transition metal MXene. In addition, this MXene exhibits excellent gravimetric capacitance and long-lasting stability when applied as an electrode for the supercapacitor. This work not only expands the MXenes family, but also provides a strategy for the preparation of solid-solution MXenes. Keywords MAX · MXene · Solid solution · Supercapacitor · Structure

Introduction The MXenes family has become colorful after more than a decade of development [1]. Since MXenes materials combine excellent conductivity, hydrophilicity, and scalability, they have been widely used in many scenarios such as energy storage, catalysis, and electromagnetic shielding [2, 3]. Top-down material preparation methods provide the opportunity to synthesize MXenes (generally denoted as Mn+1 Xn Tx ) by selectively etching the A atomic layer in the precursor MAX (generally denoted as W. Ma · Z. Qiu · C. Tan · C. Hou · X. Lv · J. Li · L. Hu (B) · J. Dang (B) College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China e-mail: [email protected] J. Dang e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_1

3

4

W. Ma et al.

Mn+1 AXn ), in which M denotes an early transition metal element; A denotes most III-A or IV-A elements; X denotes C and/or N; Tx denotes a functional group on the surface (generally –O, –OH, and halogen functional groups, etc.), and n may be taken as 1–4 [4, 5]. MXenes with two transition metals, the so-called dual transition metal (DTM) MXenes, become more prominent in the MXenes family. One of the two transition metals randomly occupies different M-layers, providing unique structures not found in single-transition-metal MXenes, such as out-of-plane ordered Mo2 TiC2 Tx or inplane ordered (Mo2/3 Y1/3 )2 CTx , as well as solid-solution MXene structures [6]. It has been shown that MXenes containing two transition metals have higher electrical conductivity, charge storage capacity, and catalytic capacity due to the fact that the DTM structure can change the electronic state of the metal and the specific properties of the outer transition metal layer [7, 8]. In particular, solid-solution MXenes allow unprecedented tunability and control of their properties, including electrical conductivity, by changing the M-site composition [9]. Because of this, the strategy of customizing solid-solution MXenes makes it more possible for MXene materials to have excellent electronic, mechanical, and other properties. However, there are fewer studies exploring the solid-solution system on the electrochemical properties of MXenes. Therefore, we designed and prepared solidsolution vanadium-titanium double transition metal MXene. The electrochemical performance of the prepared solid-solution MXene was investigated, and vanadiumtitanium double transition metal MXene showed excellent gravimetric capacitance and long-lasting stability when used as supercapacitor electrodes.

Experimental Synthesis of MAX Phase Powder The Ti (99.9%, 250 mesh), V (99.9%, 325 mesh), Al (99.95%, 325 mesh), and graphite (99.9%, 325 mesh) powders were purchased from Aladdin Reagent and used without further purification unless specified. The above powders were mixed in a molar ratio of 2:1:1.2:1.9. The excess Al is to compensate for evaporation during the synthesis of MAX at high temperatures. The well-mixed powder was transferred to an alumina crucible and then placed in a tube furnace for sintering under argon atmosphere. The sintering temperature was 1500 °C and held for four hours. After the samples were cooled to room temperature at the end of the holding period, the samples were removed and ground to 200 mesh.

A Novel Solid-Solution MXene with High Gravimetric Capacitance

5

Synthesis of MXene Powder 1 g of Ti2 VAlC2 MAX phase powder was slowly added to a reaction kettle containing 40 ml of 49% HF. The kettle was placed in a water bath, and the reaction was carried out for two days at 40 °C at 500 rpm. At the end of the water bath, the solution was centrifuged at 5000 rpm for 5 min. The supernatant was then removed and fresh deionized water was added. The whole process of centrifugation and washing was repeated several times until the pH of the supernatant was higher than 6. The resulting precipitate was dried overnight in a vacuum oven at 60 °C.

Electrochemical Characterization The CHI660E electrochemical workstation was used to carry out all electrochemical tests. The electrochemical tests were performed using a three-electrode system and were carried out at room temperature.

Results and Discussion The titanium-vanadium solid-solution MAX phase was synthesized using the previously described scheme [7, 10]. The X-ray diffraction (XRD) pattern of the Ti2 VAlC2 MAX phase is shown in Fig. 1a. The strong peak around 10° is the (002) peak of the Ti2 VAlC2 MAX phase, and the strong peak around 40° is the signature peak of the MAX phase material. When the Ti2 VAlC2 MAX phase reacted with hydrofluoric acid solution to selectively remove aluminum, the corresponding Ti2 VC2 Tx MXene was obtained. What can be clearly seen is that the (002) peak of Ti2 VC2 Tx MXene is obviously shifted to a lower angle, which implies that the interlayer spacing of the material has increased. This is due to the expansion of the interlayer caused by the removal of aluminum and the evaporation of water molecules during the drying process. In addition, the disappearance of the higher ordered peaks attributed to the MAX phase as well as the high intensity (002) peak of MXene confirm the complete removal of the Al layer. In order to determine the lattice parameters of the Ti2 VAlC2 MAX phase as well as the phase purity, the obtained XRD data were refined and the Rietveld refinement of the Ti2 VAlC2 MAX phase is shown in Fig. 1b. The sample contains 93.2 wt% of Ti2 VAlC2 MAX phase, and the impurities in the sample include 0.2 wt% TiAl3 , 4.1 wt% Ti2 C, 1.3 wt% VC, and 1.2 wt% Ti0.8 V0.2 C0.62 . The lattice parameters of Ti2 VAlC2 MAX phase obtained from the Rietveld refinement are a = 3.0293, b = 3.0409, and c = 18.2513 Å, which are close to the lattice parameters of the MAX phase of system 312 reported in other literature [11, 12].

6

W. Ma et al.

Fig. 1 a X-ray diffraction (XRD) patterns of Ti2 VAlC2 MAX phase and Ti2 VC2 Tx MXene. b Rietveld refinement for Ti2 VAlC2 MAX phase (Rwp = 5.0115)

Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were further employed to probe the morphology and structure of the double transition metal MAX phase and MXene. SEM images of the Ti2 VAlC2 MAX phase show that it has an obvious tightly stacked laminar structure (Fig. 2a), which is similar to a terraced structure. After reacting with hydrofluoric acid to remove the aluminum layer, the original dense layered structure of the Ti2 VAlC2 MAX phase was opened. The SEM image of the formed Ti2 VC2 Tx MXene is shown in Fig. 2b, and Ti2 VC2 Tx MXene has an obvious accordion-like microstructure. Similar to the SEM results, the TEM image of Ti2 VC2 Tx MXene shows a distinct lamellar structure (Fig. 2c). Figure 2d illustrates the SEM image of Ti2 VAlC2 MAX phase powders and the corresponding elemental distribution maps, which show the uniform distribution of Ti, V, Al and C elements. Next, we explored the morphology and elemental distribution of Ti2 VC2 Tx MXene using high-angle annular dark-field transmission electron microscopy (HAADF-STEM) and the corresponding elemental distribution maps (Fig. 2e). The HAADF-STEM image of Ti2 VC2 Tx MXene demonstrates a clear lamellar structure, which indicates that the MAX phase is successfully converted into MXene. In addition, the elemental distribution maps show that Ti, V, O, F, and C elements are present, where the presence of F and O elements indicates that MXene has abundant –F, –O, and –OH functional groups. Next, X-ray photoelectron spectroscopy (XPS) was further employed to probe the chemical bonding and functional groups on the surface of the synthesized MXene. The XPS spectra (Fig. 3a) of Ti2 VC2 Tx MXene show characteristic peaks of five elements, F, O, V, Ti, and C. The presence of F and O indicates the presence of –F, – O, and –OH functional groups. These functional groups originate from the reaction of the MAX phase with hydrofluoric acid solutions as well as aqueous solutions during the hydrofluoric acid etching process. The Ti 2p spectrum (Fig. 3b) of Ti2 VC2 Tx MXene can be fitted to six peaks, which can be assigned to Ti-C species at 454.8 and 461.2 eV binding energies. While the peaks located at 455.6, 456.8, 458.4, and 463.9 eV correspond to Ti2+ , Ti3+ , Ti–O–F, and Ti–O, which originate from Ti3 C2 (OH)x , Ti3 C2 Ox , TiO2-x Fx , and surface oxidation, respectively [13, 14]. The

A Novel Solid-Solution MXene with High Gravimetric Capacitance

7

Fig. 2 SEM images of a Ti2 VAlC2 MAX phase, b Ti2 VC2 Tx MXene. c TEM image of Ti2 VC2 Tx MXene. d SEM images of Ti2 VC2 Tx MXene and the corresponding elemental distribution maps. e HAADF-STEM image of Ti2 VC2 Tx MXene and the corresponding elemental distribution maps

XPS peaks of V 2p (Fig. 3c) can be fitted with five de-convoluted peaks, the peak at 513.7 eV is labeled as V-C, and the peaks at 515.4 and 523.8 eV are relevant to V4+ , while the remaining peaks are related to V3+ and V2+ . The multiple valence states of vanadium imply that Ti2 VC2 Tx MXene is a solid-solution structure [8, 15, 16]. The C 1 s spectrum (Fig. 3d) of Ti2 VC2 Tx MXene can be deconvoluted into five peaks. The peaks at 281.9 and 282.8 eV correspond to the bonding of C with the transition metals in MXene and are named C–Ti, C–V, respectively. The remaining peaks at 284.8, 285.7, and 286.3 eV correspond to C–C, C–H, and C–O, respectively [15]. For the O 1 s spectrum (Fig. 3e) of Ti2 VC2 Tx MXene, it can be decomposed into five de-convoluted peaks. The three peaks located at low binding energies are C–M–O, C–M–Ox , and C–M–OH, which originate from the bonding of early transition metals with surface functional groups in MXene. The remaining two peaks are related to C–O and H2 O, respectively [13]. There is only one strong peak in the high-resolution XPS spectrum of F 1 s (Fig. 3f), which can be attributed to the bonding of fluorine with the transition metal in MXene [16, 17]. In order to investigate the electrochemical properties of Ti2 VC2 Tx MXene electrode materials, working electrodes containing Ti2 VC2 Tx MXene were prepared by coating method. Cyclic voltammetry (CV) tests and galvanostatic charge–discharge (GCD) tests were performed in potassium hydroxide electrolyte solution. As shown in Fig. 4a, the cyclic voltammetry curve of Ti2 VC2 Tx MXene exhibits a rectangular-like

8

W. Ma et al.

Fig. 3 a XPS spectrum of Ti2 VC2 Tx MXene. b–f High-resolution XPS spectra of Ti 2p, V 2p, C 1 s, O 1 s, and F 1 s of Ti2 VC2 Tx MXene

shape, indicating that its capacitance contribution is mainly a double-layer capacitance. In addition, the cyclic voltammetry curves show no obvious shape change when the scan rate was increased from 2 to 200 mV s−1 , indicating that the Ti2 VC2 Tx MXene electrode material has excellent reversibility. The Ti2 VC2 Tx MXene has a gravimetric capacitance of 161 F g−1 when the scan rate is 2 mV s−1 . Next, the voltage versus time curve of Ti2 VC2 Tx MXene electrode material during charging and discharging was recorded using GCD test. As shown in Fig. 4b, the charge/ discharge duration of the electrode is inversely related to the current density. This is due to the fact that hydroxide ions in the potassium hydroxide electrolyte solution can be more fully embedded into the MXene interlayers at low current densities. At the same time, it can be observed that there is an insignificant voltage drop process at the tip of the charge–discharge curve. This small voltage drop can reflect the size of the electrode internal resistance. While the voltage drop in this paper is not very obvious, and it can be considered that the electrode internal resistance is low. In addition to capacitance, the stability of the electrode material is also very important. The Ti2 VC2 Tx MXene electrode also exhibits excellent cycling stability, retaining 96% of the capacitance after 5000 charges and discharges, as shown in Fig. 4c.

A Novel Solid-Solution MXene with High Gravimetric Capacitance

9

Fig. 4 a CV curves and b GCD curves of Ti2 VC2 Tx MXene electrode. c Capacitance retention test of Ti2 VC2 Tx MXene electrode

Conclusions In summary, we prepared the vanadium-titanium double transition metal MAX phase (Ti2 VAlC2 ) with solid-solution structure, and successfully prepared its derivative Ti2 VC2 Tx MXene by selectively etching the Al element in Ti2 VAlC2 using hydrofluoric acid. The HAADF-STEM image and its corresponding EDS images show that the elements in the prepared Ti2 VC2 Tx MXene are uniformly distributed without significant segregation. The XPS results verify that Ti2 VC2 Tx MXene is a solidsolution structure. When Ti2 VC2 Tx MXene is used as the electrode material for supercapacitors, it has a gravimetric capacitance of 161 F g−1 . In addition, it still has more than 96% capacitance after 5000 times of charging and discharging. This work not only adds a new member to the flourishing MXene family, but also provides insights into the preparation of a wide variety of MXenes by changing the M-site elements. Acknowledgements Thanks are given to the financial supports from the National Natural Science Foundation of China (52222408), MCC Changtian Scientific Research and Development Basic Research Fund (2022JCYJ04), and the Ministry of Education’s Industry School Cooperation

10

W. Ma et al.

Collaborative Education Project and Shandong Shandong Weiqiao Pioneering Group Co., Ltd (220506429071743).

References 1. Naguib M, Kurtoglu M, Presser V, Lu J, Niu J, Heon M, Hultman L, Gogotsi Y, Barsoum MW (2011) Two-dimensional nanocrystals produced by exfoliation of Ti3 AlC2 . Adv Mater 23(37):4248–4253 2. Vahid Mohammadi A, Rosen J, Gogotsi Y (2021) The world of two-dimensional carbides and nitrides (MXenes). Science 372:6547 3. Ma W, Qiu Z, Li J, Hu L, Li Q, Lv X, Dang J (2023) Interfacial electronic coupling of V-doped Co2 P with high-entropy MXene reduces kinetic energy barrier for efficient overall water splitting. J Energy Chem 85:301–309 4. Lukatskaya MR, Kota S, Lin Z, Zhao MQ, Shpigel N, Levi MD, Halim J, Taberna PL, Barsoum MW, Simon P, Gogotsi Y (2017) Ultra-high-rate pseudocapacitive energy storage in twodimensional transition metal carbides. Nat Energy 2(8):17105 5. Lian P, Dong Y, Wu ZS, Zheng S, Wang X, Sen W, Sun C, Qin J, Shi X, Bao X (2017) Alkalized Ti3 C2 MXene nanoribbons with expanded interlayer spacing for high-capacity sodium and potassium ion batteries. Nano Energy 40:1–8 6. Pang J, Mendes RG, Bachmatiuk A, Zhao L, Ta HQ, Gemming T, Liu H, Liu Z, Rummeli MH (2019) Applications of 2D MXenes in energy conversion and storage systems. Chem Soc Rev 48(1):72–133 7. Ma W, Wang M, Yi Q, Huang D, Dang J, Lv Z, Lv X, Zhang S (2022) A new Ti2 V0.9 Cr0.1 C2 Tx MXene with ultrahigh gravimetric capacitance. Nano Energy 96:107129 8. Han M, Maleski K, Shuck CE, Yang Y, Glazar JT, Foucher AC, Hantanasirisakul K, Sarycheva A, Frey NC, May SJ, Shenoy VB, Stach EA, Gogotsi Y (2020) Tailoring electronic and optical properties of MXenes through forming solid solutions. J Am Chem Soc 142(45):19110–19118 9. Wang L, Han M, Shuck CE, Wang X, Gogotsi Y (2021) Adjustable electrochemical properties of solid-solution MXenes. Nano Energy 88:106308 10. Ma W, Qiu Z, Wang M, Tan C, Hu L, Lv X, Li Q, Li J, Dang J (2023) A novel high-entropy MXene Ti1.1 V1.2 Cr0.8 Nb1.0 Mo0.9 C4 Tx for high-performance supercapacitor. Scripta Mater 235:115596 11. Meshkian R, Tao Q, Dahlqvist M, Lu J, Hultman L, Rosen J (2017) Theoretical stability and materials synthesis of a chemically ordered MAX phase, Mo2 ScAlC2 , and its two-dimensional derivate Mo2 ScC2 MXene. Acta Mater 125:476–480 12. Wang HW, Naguib M, Page K, Wesolowski DJ, Gogotsi Y (2015) Resolving the structure of Ti3 C2 Tx MXenes through multilevel structural modeling of the atomic pair distribution function. Chem Mater 28(1):349–359 13. Halim J, Cook KM, Naguib M, Eklund P, Gogotsi Y, Rosen J, Barsoum MW (2016) X-ray photoelectron spectroscopy of select multi-layered transition metal carbides (MXenes). Appl Surf Sci 362:406–417 14. Li J, Hou C, Chen C, Ma W, Li Q, Hu L, Lv X, Dang J (2023) Collaborative interface optimization strategy guided ultrafine RuCo and MXene heterostructure electrocatalysts for efficient overall water splitting. ACS Nano 17(11):10947–10957 15. Nemani SK, Zhang B, Wyatt BC, Hood ZD, Manna S, Khaledialidusti R, Hong W, Sternberg MG (2021) High-entropy 2D carbide MXenes: TiVNbMoC3 and TiVCrMoC3 . ACS Nano 15(8):12815–12825

A Novel Solid-Solution MXene with High Gravimetric Capacitance

11

16. Du Z, Wu C, Chen Y, Cao Z, Hu R, Zhang Y, Gu J, Cui Y, Chen H, Shi Y, Shang J, Li B, Yang S (2021) High-entropy atomic layers of transition-metal carbides (MXenes). Adv Mater 33(39):e2101473 17. Li J, Chen C, Lv Z, Ma W, Wang M, Li Q, Dang J (2023) Constructing heterostructures of ZIF67 derived C, N doped Co2 P and Ti2 VC2 Tx MXene for enhanced OER. J Mater Sci Technol 145:74–82

An Overview of the Synthetic Route of Molybdenum Diselenide Nanoparticles Ita E. Uwidia, Esther U. Ikhuoria, Stanley O. Omorogbe, Ikhazuagbe H. Ifijen, Muniratu Maliki, and Aireguamen I. Aigbodion

Abstract This study explores the diverse synthesis methods for molybdenum diselenide (MoSe2 ) nanoparticles, aiming to tailor their properties for an array of applications. Various techniques including hydrothermal, solvothermal, microwaveassisted, template-assisted, and sonochemical methods are discussed in terms of their principles, advantages, and disadvantages. Each method offers distinct control over nanoparticle size, morphology, and crystallinity, influencing their suitability for different applications. Comparative analysis of these methods reveals a range of factors, from scalability challenges to the need for specialized equipment. Researchers are driven to optimize synthesis conditions through comprehensive characterization techniques, aiming to tailor MoSe2 nanoparticles for specific applications. Despite existing challenges, the evolving landscape of MoSe2 nanoparticle research presents an exciting frontier, where interdisciplinary efforts and innovative synthesis approaches hold the potential to unlock multifunctional nanomaterials with tailored properties. Keywords Molybdenum diselenide · MoSe2 nanoparticles · Synthesis methods · Hydrothermal · Solvothermal · Microwave-assisted

I. E. Uwidia · E. U. Ikhuoria Faculty of Physical Sciences, Department of Chemistry, University of Benin, Benin City, Edo State, Nigeria S. O. Omorogbe · I. H. Ifijen (B) Rubber Research Institute of Nigeria, Benin City, Edo State, Nigeria e-mail: [email protected] M. Maliki Department of Chemistry, Edo State University, Iyamho, Nigeria A. I. Aigbodion Department of Physical Sciences, Benson Idahosa University, Benin City, Edo State, Nigeria © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_2

12

An Overview of the Synthetic Route of Molybdenum Diselenide …

13

Introduction Nanoparticles, materials with dimensions on the nanometer scale, have captivated researchers and industries alike due to their distinctive properties and potential applications across various domains [1, 2]. These tiny structures, often ranging from 1 to 100 nm in size, exhibit unique physical, chemical, and biological attributes that differ from their bulk counterparts [3–5]. As a result, nanoparticles have found their way into fields as diverse as electronics, medicine, energy, and environmental science [5–7]. One material of particular interest is molybdenum diselenide (MoSe2 ), a two-dimensional transition metal dichalcogenide (2D-TMD), which has garnered significant attention for its intriguing properties and potential applications. Nanoparticles hold immense promise due to their ability to be tailored at the atomic and molecular levels, offering unprecedented control over their properties [8–11]]. These properties often arise from the high surface area-to-volume ratio, quantum effects, and the dominance of surface phenomena in nanoparticles [12, 13]. Manipulating these characteristics can lead to enhanced catalytic activity, improved electrical conductivity, superior mechanical strength, and remarkable optical properties, making nanoparticles indispensable in a wide array of applications [14, 15]. Molybdenum diselenide (MoSe2 ), a member of the 2D-TMD family, has emerged as a prominent material for research and technological innovation [16–20]. Unlike bulk materials, the unique behavior of MoSe2 at the nanoscale has sparked intense interest for applications in electronics, optoelectronics, catalysis, and energy storage [21, 22]. Realizing the full potential of MoSe2 nanoparticles necessitates the development of precise and controlled synthesis methods that allow manipulation of their size, shape, and properties [23]. Various synthesis techniques, each with its own set of advantages and limitations, have been explored to achieve these goals [4]. In this context, this chapter delves into the significance of nanoparticles in modern research, elucidating the fundamental principles that underlie their exceptional properties. The subsequent sections of this chapter will provide a comprehensive overview of different synthesis methods for MoSe2 nanoparticles, including hydrothermal, solvothermal, microwave-assisted, template-assisted, and sonochemical approaches. The exploration of these methods will shed light on the challenges and opportunities that lie in the synthesis of MoSe2 nanoparticles, ultimately paving the way for their tailored applications in diverse fields.

Structure and Properties of Molybdenum Diselenide (MoSe2 ) Nanoparticles Molybdenum diselenide (MoSe2 ) nanoparticles exhibit diverse properties and structures that hold immense potential for a wide range of applications [16]. The synthesis technique employed plays a pivotal role in determining key process parameters that

14

I. E. Uwidia et al.

impact the properties of these nanostructures, making it crucial to tailor their characteristics for specific applications [17]. MoSe2 exhibits a combination of metallic and semiconductor properties, offering the flexibility of n- and p-type conductivity based on the synthesis method. This adaptability serves as a foundation for applications in catalysis, energy transformation, photodetectors, sensors, batteries, and even critical medical applications such as cancer therapy and precise drug delivery [18, 19]. The interaction of MoSe2 nanostructures with biologically active substances can modify their structural biocompatibility, facilitating novel biomedical applications [19]. For instance, ultrasonic exfoliation demonstrates how bulk MoSe2 material can be exfoliated into nanolayers (Fig. 1) [19]. Complex multicomponent nanoarchitectures further amplify their potential, blending the unique attributes of distinct materials to revolutionize fields like medicine, catalysis, and electronics [20]. While challenges remain in achieving high-throughput synthesis of multicomponent structures, progress has been witnessed in cancer therapy and targeted drug delivery [21]. External electric and magnetic fields can modify their behaviour in vivo, expanding their role in diagnostics, therapy, and tissue engineering. Beyond biology, they find applications in space technology, energy conversion materials, and electronics, owing to their mechanical stability, photochemical reactivity, and tuneable electric properties [22]. The versatility, cost-effectiveness, and varied synthesis methods of MoSe2 nanoparticles contribute to their attractiveness for catalysis, sensing, and medical applications, showcasing their potential to redefine various technological landscapes [23].

Fig. 1 MoS2 configurations a 2H and b 1 T, top and side views [4]

An Overview of the Synthetic Route of Molybdenum Diselenide …

15

Synthetic Methods for MoSe2 Nanoparticles Molybdenum diselenide (MoSe2 ) nanoparticles hold remarkable promise for a multitude of applications owing to their unique properties [22]. The synthesis of these nanoparticles involves several distinct methods, each contributing to the tunability of their characteristics [23]. Below, we delve into the principles, procedures, advantages, disadvantages, and resulting attributes associated with some prominent synthesis techniques.

Chemical Vapor Deposition (CVD) In CVD, precursor gases undergo thermal decomposition on a heated substrate to form MoSe2 . A Mo precursor and a Se precursor are introduced, and their reaction yields MoSe2 . The setup includes a quartz tube furnace where the precursor gases are introduced, and the substrate is heated [24]. MoSe2 forms on the substrate’s surface. This process allows fine control over size, shape, and thickness of the resulting nanoparticles. However, CVD requires carefully controlled conditions and can be complex to set up [25]. As an example, González and colleagues (2022) demonstrated a controlled chemical vapor deposition (CVD) synthesis to produce monolayer MoSe2 flakes of various shapes, including hexagons, triangles, sawtooth hexagons, dendrites, and fractals, deposited on SiO2 /Si substrates (see Fig. 2) [24]. This diverse array of morphologies stems from alterations in vapor composition due to the confinement of MoO3 and Se vapor, as well as variations in growth rates of MoSe2 crystals with distinct shapes. Moreover, the shape and size of these MoSe2 flakes significantly influence their photoluminescence (PL) response. These findings are poised to introduce novel opportunities for achieving morphology-controlled monolayer MoSe2 flakes tailored for applications in optoelectronics and energy harvesting systems. In a separate investigation, Wang and coresearchers (2020) undertook the synthesis of top-quality monolayer and bilayer MoSe2 triangular crystals, along with continuous thin films marked by precise nucleation density control, employing reverse-flow chemical vapor deposition (CVD) [25]. The team systematically explored and meticulously showcased the exceptional crystallinity and robust saturated absorption capabilities of MoSe2 . Attaining optimized nucleation and uniform morphology necessitated nuanced adjustments in reverse-flow switching time, growth duration, and temperature, thereby establishing associated growth kinetics. This endeavor introduces a fresh avenue for the controlled fabrication of monolayer transition metal dichalcogenides (TMDCs) crystals with elevated efficiency and dependability. In doing so, it advances the domain of surface/interface manipulation for 2D semiconductors, a pivotal stride toward the realization of van der Waals heterostructure device applications.

16

I. E. Uwidia et al.

Fig. 2 a–f SEM micrographs of MoSe2 microstructures for a total flow rate of a 50 sccm, b 60 sccm, c 70 sccm, d 80 sccm, e 100 sccm, and f 200 sccm, corresponding to samples 2–7, respectively. g–i AFM images of sample [24]

Hydrothermal Methods Hydrothermal synthesis involves mixing Mo and Se precursors in an aqueous solution within a high-pressure vessel [26]. The vessel is then heated to temperatures ranging from 150 to 200 °C. The precursors react under pressure, leading to MoSe2 nanoparticle formation. The resulting nanoparticles are collected, washed, and dried [27]. This method offers mild conditions, allowing uniform nanoparticle growth. Yet, the procedure can be time-consuming, and post-synthesis purification may be necessary. For instance, Siddiqui and colleagues (2018) conducted a study wherein micron-sized broom-shaped MoSe2 nanostructures were synthesized using the hydrothermal technique, as illustrated in Fig. 3 [26]. The scanning electron microscopy (SEM) analysis confirmed the broom-shaped morphology, revealing an average diameter of around 150 nm and a length of approximately 10 µm (as shown in Fig. 4). Through X-ray diffraction (XRD) investigations, the team validated the presence of a highly crystalline hexagonal phase within the MoSe2 nanostructures. The material’s band gap was assessed at 1.8 eV through Tauc’s plot. Remarkably, the broom shaped MoSe2 nanostructures exhibited notable efficiency as a photocatalytic material. This was substantiated by their performance in decomposing an organic pollutant, namely Methylene Blue (MB), with an impressive degradation efficiency of approximately

An Overview of the Synthetic Route of Molybdenum Diselenide …

17

Fig. 3 Synthesis of broom shaped MoSe2 nanostructures using hydrothermal technique [26] Fig. 4 SEM images of broom shaped MoSe2 nanostructure [26]

90% within the initial 20 min of experimentation. Moreover, the kinetics of the reaction were assessed and found to align effectively with the pseudo-second-order model. In a separate investigation, Burragoni and colleagues (2021) engaged in the synthesis of flower-like nanoflakes (NF) of molybdenum diselenide (MoSe2 ) using a one-pot hydrothermal approach [27]. The ensuing samples underwent comprehensive scrutiny via diverse analytical methods. Powder X-ray crystallography (XRD) corroborated the presence of the MoSe2 ’s hexagonal crystal phase, while scanning

18

I. E. Uwidia et al.

electron microscopy (SEM) images distinctly revealed the flower-like structures of the MoSe2 NF. The ensuing MoSe2 NF samples, along with Pt-supported MoSe2 NF catalysts, underwent assessment for both the methanol oxidation reaction (MOR) and photocatalytic hydrogen evolution. Remarkably, the electrocatalytic prowess of the Pt-supported MoSe2 NF surpassed that of the unadorned MoSe2 NF, attributed to the redox attributes intrinsic to the Pt material. Moreover, a comprehensive analysis of the photocatalytic hydrogen evolution was performed under varying light irradiation conditions. The catalyst’s resilience and longevity were meticulously gauged through recycling examinations and chronoamperometry measurements spanning 2400 s.

Solvothermal Methods Solvothermal techniques involve using organic solvents as reaction media in a similar fashion to hydrothermal methods [28]. The precursors are dissolved in the solvent, and the mixture is sealed in an autoclave and heated. The higher solubility of precursors in organic solvents facilitates controlled growth [28]. After the reaction, nanoparticles are separated, purified, and dried. Solvothermal methods offer advantages in terms of morphology control and crystallinity improvement. However, removing solvents can be challenging [29]. In a study carried out in the year 1999, Zhan et al. utilized a solvothermal method to fabricate nanocrystalline 2H–MoSe2 from MoO3 , N2 H4 · H2 O, and Se in pyridine at 300 °C for 12 h [28]. The resulting gray-black product underwent characterization via X-ray diffraction (XRD) and transmission electron microscopy (TEM) analysis. The XRD pattern confirmed the preparation of a phase-pure product, while TEM analysis depicted polycrystalline plate-shaped particles with a diameter of approximately 40 nm (Fig. 5). Under the pyridinethermal route and in the temperature range of 250–300 °C, MoO3 and Se underwent conversion to 2H–MoSe2 nanocrystallites in the presence of N2 H4 · H2 O. The solvothermal conversion route demonstrated the potential to synthesize nanometersized 2H–MoSe2 , with the conversion of MoO3 and Se to MoSe2 involving a twostep process via MoO2 . Notably, pyridine played a pivotal role in facilitating the conversion process by activating Se, providing reactive surfaces, and promoting the reaction. Ghritlahre et al. (2018) conducted MoSe2 synthesis through a solvothermal chemical route using two different precursor materials while varying the reaction temperature, and the resulting structural properties were investigated [29]. Figure 6a, b displays the X-ray diffraction (XRD) patterns of the samples obtained at different reaction temperatures and using distinct precursors. The diffraction peaks corresponding to (100), (105), and (110) crystallographic planes are clearly observed across all samples, with an additional peak attributed to the (040) plane of MoO3 . Notably, samples synthesized at a reaction temperature of 150 °C exhibit higher crystallinity. Alterations in microstructure are also apparent in samples prepared with different precursor materials. As shown in Fig. 6a, b, the field emission scanning electron microscopy (FESEM) images of the MoSe2 powder samples produced using

An Overview of the Synthetic Route of Molybdenum Diselenide …

19

Fig. 5 TEM image showing a the main morphology of the as-prepared sample and b the aggregation of the sample after annealing at 500 °C [28]

Fig. 6 a XRD spectra for MoSe2 sample prepared by sodium molybdate. b XRD spectra of the sample prepared by ammonium molybdate at different reaction temperature [29]

two different precursors at a reaction temperature of 200 °C reveal distinct particle morphologies. Specifically, needle or rod-shaped particles are observed when sodium molybdate is employed as the precursor, while spherical particles are formed when ammonium molybdate is utilized.

20

I. E. Uwidia et al.

Microwave-Assisted Synthesis Microwave-assisted synthesis involves the use of microwave irradiation to accelerate chemical reactions [30]. In the context of MoSe2 nanoparticles synthesis, this method offers several advantages. Firstly, microwave heating allows for rapid and uniform heating of the reaction mixture, leading to shorter reaction times compared to conventional heating methods [30]. This feature is particularly beneficial in reducing reaction durations and improving product yields [31]. Additionally, the ability to precisely control microwave power and duration facilitates the fine-tuning of reaction conditions to achieve desired nanoparticle sizes and morphologies [31]. Using this technique, Harpeness et al. (2003) employed a microwave-assisted reaction between Mo(CO)6 and Se to synthesize MoSe2 nanostructures. The resulting product mixture revealed the presence of nanorods of MoSe2 with lengths ranging from 45 to 55 nm [30]. Various characterization techniques, including X-ray powder diffraction, FTIR spectroscopy, photoacoustic spectroscopy (PAS), transmission electron microscopy (TEM), and high-resolution TEM (HRTEM), were employed to analyze the synthesized MoSe2 . The HRTEM images are presented in Fig. 7, depicting nanorods with lengths varying between 45 and 55 nm and widths ranging from 2.5 to 6.0 nm. Further insight is provided by the detailed structures shown in Fig. 7b and c. Figure 7b provides a close-up view of the nanorod structure, revealing fringes spaced around 0.65 nm apart, matching the (002) plane distance of hexagonal MoSe2 . Correspondingly, Nath and Rao17 had observed y0.64 nm spacing for the layers of the 002 planes in their MoSe2 nanotubes. Additionally, the images showcase partially crystallized or even amorphous MoSe2 at the edges. Figure 7c highlights elliptical particles around 10 nm in length, displaying fringes spaced by 0.25 nm, associated with the (103) planes of the hexagonal crystal. In a similar study, Reshmi and colleagues (2017) conducted a study in which they achieved the synthesis of MoS2 nanostructures through a straightforward method involving liquid phase exfoliation of MoS2 powder in organic solvents, followed by microwave treatment [31]. The combination of probe sonication and microwave treatment proved pivotal in inducing the rolling and curling of MoS2 nanosheets, leading to the formation of MoS2 spheres as well as rod and tube-like structures, exhibiting diameters of approximately 150–200 nm. Remarkably, the resulting MoS2

Fig. 7 High-resolution TEM images of MoSe2 nanorods [30]

An Overview of the Synthetic Route of Molybdenum Diselenide …

21

nanorods displayed a hollow interior with a wall thickness measuring 15–20 nm, while their lengths reached several micrometers. Notably, the fabrication of these tailored MoS2 nanorods via liquid phase exfoliation had not been previously reported. The study’s findings strongly indicate the preservation of the 2H phase of bulk MoS2 within the synthesized nanostructures, reflecting their high crystalline quality.

Sonochemical Methods Sonochemical synthesis involves the application of high-frequency ultrasound waves to drive chemical reactions [32]. In the context of MoSe2 nanoparticles synthesis, sonochemical methods offer distinct advantages. The ultrasonic cavitation phenomenon generates localized hotspots of high pressure and temperature, promoting rapid nucleation and growth of nanoparticles. This effect enhances mass transport and mixing, resulting in reduced reaction times compared to traditional methods. For instance, Kirubasankar et al. (2019) developed a facile and straightforward sonochemical method for synthesizing molybdenum selenide (MoSe2 ) nanosheets, as illustrated in Fig. 8 [32]. The optimization of the synthesis process involved varying sonication times (15, 30, and 45 min) while maintaining a constant power of 500 W. To enhance the electrochemical performance of the exfoliated MoSe2 nanosheets, a hybrid material was created by combining 2D-MoSe2 with 2D-graphene using a solvothermal approach. The field-emission scanning electron microscopy (FE-SEM) images of MoSe2 nanosheets (NS) and the MoSe2 /graphene (MoSe2 /G) nanohybrid are displayed in Fig. 9a–d. These images reveal sheet-like structures. The 15-min sonication produced exfoliated MoSe2 NS, with H2 O2 etching mainly affecting the basal edges and not

Fig. 8 Schematic illustration of the sonochemical process for the exfoliation of nanosheets containing a few layers of MoSe2 [32]

22

I. E. Uwidia et al.

Fig. 9 FE-SEM photographs of MoSe2 NS after various sonication times: a 15 min, b 30 min, and c 45 min. d FE-SEM photograph of the MoSe2 /G nanohybrid [32]

resulting in thin sheet-like structures. After 30 min of sonication (Fig. 9b), MoSe2 NS consisting of a few layers were observed, yielding 52%. Upon 45 min of sonication (Fig. 9c), very thin MoSe2 NS were formed, but with a low yield of 16%. This might be attributed to overoxidation of MoSe2 into MoO2 in the presence of H2 O2 , which can dissolve MoSe2 and promote an exothermic reaction. To achieve a few layers of MoSe2 NS, 30 min of sonication at a temperature below 25 °C was determined to be optimal. Furthermore, the MoSe2 /G hybrid was fabricated by orienting MoSe2 NS onto graphene nanosheets, resulting in a unique wrinkled nanostructure. The hybrid’s wrinkled morphology provides numerous electrochemically active edges, facilitating efficient electrolyte ion utilization and enhancing electrochemical properties. Energy dispersive X-ray analysis (EDX) confirmed the presence of Mo, Se, and C species in the MoSe2 /G nanohybrid. Transmission electron microscopy (TEM) images revealed that MoSe2 NS after 30 min of sonication exhibited very few stacked layers, while the MoSe2 /G nanohybrid displayed a thin, curled shape of MoSe2 NS oriented on graphene nanosheets. The presence of diffused halo rings in the selected area electron diffraction (SAED) pattern of the MoSe2 /G nanohybrid indicated its polycrystalline nature, consistent with XRD results. Moreover, BET surface area measurements showed surface areas of 68 m2 /g for exfoliated MoSe2 and 133 m2 /g

An Overview of the Synthetic Route of Molybdenum Diselenide …

23

for the nanohybrid, demonstrating the enhanced surface area provided by the hybrid structure. The exfoliated MoSe2 nanosheets are perpendicularly oriented on the surface of the graphene nanosheets. These MoSe2 nanosheet edges have a large number of electrochemically active sites, and the graphene sheets provide effective mass transportation of ions at the electrode–electrolyte interface.

Other Synthesis Methods for MoSe2 Nanoparticles Several other methods have been explored for synthesizing MoSe2 nanoparticles, expanding the range of available techniques beyond those previously mentioned [33]. One such approach involves the employment of chemical vapor transport (CVT) methods, where MoSe2 nanoparticles are produced by allowing vaporized reactants to transport to a cooler region and form nanoparticles through a reaction [33]. This method offers control over nucleation and growth, facilitated by creating a temperature gradient within a sealed ampoule. However, the process requires high temperatures and vacuum conditions, and the purity of the product may be influenced by residual carrier gases [34]. Another method that has gained attention is electrochemical exfoliation. This technique involves using an electrochemical cell to create nanosheets from layered materials like MoSe2 [35]. The layered material serves as an electrode and applying an electric potential lead to ion intercalation and exfoliation into nanosheets. Electrochemical exfoliation is advantageous due to its mild conditions and scalability, as it can be performed in solution [36]. However, precise electrochemical control is crucial to achieve the desired nanosheet characteristics, making the method dependent on meticulous experimental parameters [36]. In addition, template-assisted synthesis offers another avenue for producing MoSe2 nanoparticles. This technique relies on utilizing templates or matrices with well-defined structures to guide the growth of nanoparticles. By controlling the template’s properties, such as size, shape, and surface chemistry, researchers can tailor the resulting nanoparticles accordingly [37]. This method provides a versatile platform for achieving precise control over the final product’s characteristics. However, template-assisted synthesis requires the preparation of suitable templates, which can be a complex and time-consuming process. Additionally, template removal post-synthesis can pose challenges, potentially affecting the nanoparticle structure and properties [37]. Gas phase synthesis methods have also gained attention for creating MoSe2 nanoparticles. These methods involve vapor-phase reactions that lead to the formation of nanoparticles in a gas-phase environment [38]. Techniques such as laser ablation, chemical vapor deposition, and aerosol methods fall under this category. Gas phase

24

I. E. Uwidia et al.

synthesis enables the production of nanoparticles with controlled size and composition, and it is particularly suited for large-scale production [38]. However, maintaining precise control over nanoparticle properties and ensuring consistent quality can be challenging in gas phase synthesis, as it often involves intricate gas-phase reactions and nucleation processes. Understanding these synthesis procedures is vital for crafting MoSe2 nanoparticles with tailored properties for specific applications. From the meticulous peeling of layers to the controlled gas-phase reactions, each technique brings forth its set of capabilities and limitations. The resulting MoSe2 nanoparticles exhibit a spectrum of attributes such as size, morphology, crystallinity, and surface properties. By mastering these synthesis methodologies, researchers can fine-tune MoSe2 nanoparticles to suit diverse applications, propelling advancements in fields ranging from electronics to medicine and beyond. Table 1 presents the strengths and limitations of the diverse synthesis methods for MoSe2 nanoparticles that have been discussed in this study [25–33, 39, 40].

Challenges and Future Perspectives While various synthesis methods have shown promise in producing MoSe2 nanoparticles with tailored properties, there are several challenges that researchers need to address for the successful and widespread application of these materials. One significant challenge is achieving scalability and reproducibility [41]. Many synthesis methods, particularly those involving complex reaction conditions or specialized equipment, might encounter difficulties when attempting to scale up production while maintaining consistent nanoparticle quality [42]. This challenge is particularly pertinent when considering industrial applications that demand large quantities of nanoparticles. Another challenge lies in optimizing the properties of MoSe2 nanoparticles for specific applications [42]. The properties of MoSe2 nanoparticles, such as their size, shape, crystallinity, and doping, significantly influence their performance in various applications [42]. Achieving precise control over these properties requires a deep understanding of the synthesis parameters and their effects on the resulting nanoparticles. Furthermore, the optimization process may differ for each application, necessitating thorough research to determine the most suitable parameters [43]. Looking ahead, future research in MoSe2 nanoparticle synthesis should focus on addressing these challenges while also exploring new avenues for advancement. Novel synthesis approaches that offer improved scalability, reproducibility, and efficiency should be developed to enable the large-scale production of MoSe2 nanoparticles [44]. Moreover, enhancing the characterization techniques used to assess the properties of MoSe2 nanoparticles will be crucial for gaining a more comprehensive understanding of their structure, composition, and behavior at the nanoscale [44]. The integration of advanced characterization tools, such as high-resolution imaging

An Overview of the Synthetic Route of Molybdenum Diselenide …

25

Table 1 Advantages and disadvantages of different synthesis methods for MoSe2 nanoparticles Synthesis method

Advantages

Disadvantages

Hydrothermal method

– Relatively simple and cost-effective

– Limited control over size and morphology

– Mild reaction conditions

– Agglomeration of nanoparticles

– Suitable for large-scale production

– Long reaction times

– Reduced environmental impact

– Challenges in removing surfactants

Chemical vapor deposition

– Precise control over film thickness and size

– Complex and expensive equipment required

(CVD) method

– High-quality, large-area films can be grown

– High reaction temperatures may lead to defects

– Scalability for industrial applications

– Requires specialized substrates

– Low contamination risk due to closed system

– Precursor decomposition and by-products

– Morphology control and crystallinity control

– Removing solvents can be challenging

– Formation of various nanostructures

– Organic solvents can affect product properties

– Favorable for tailoring complex structures

– Reaction conditions need careful optimization

Solvothermal methods

Microwave-assisted synthesis – Rapid and energy-efficient synthesis

Template-assisted synthesis

Gas phase synthesis

– Limited control over morphology

– Homogeneous heating and reduced reaction time

– May require post-synthesis treatment

– Potential for scale-up and reproducibility

– Optimal microwave conditions need tuning

– Precise control over size and – Complex template morphology preparation process – Tailoring properties through templates

– Template removal can impact final properties

– Controlled size and composition

– Complex gas-phase reactions

– Suitable for large-scale production

– Maintaining precise control is challenging

– Potential for uniform and reproducible products

– Nucleation and growth dynamics can vary

26

I. E. Uwidia et al.

and spectroscopy techniques, will provide insights into the fundamental properties of MoSe2 nanoparticles. Emerging applications of MoSe2 nanoparticles in fields such as electronics, energy storage, catalysis, and biomedicine offer exciting prospects for future research. Exploring these applications and tailoring the properties of MoSe2 nanoparticles to meet specific requirements will be a key focus [45–47]. Additionally, investigating their performance within integrated systems, such as nanocomposites and heterostructures, could lead to breakthroughs in multifunctional materials and devices [46, 47]. Collaborative efforts between researchers from diverse disciplines will be essential to accelerate the development of MoSe2 nanoparticle-based technologies and their commercialization. In summary, while challenges exist, the field of MoSe2 nanoparticle synthesis holds great promise. Addressing scalability, reproducibility, and property optimization challenges, coupled with the exploration of innovative synthesis approaches and enhanced characterization techniques, will contribute to realizing the full potential of MoSe2 nanoparticles in various applications.

Conclusion The synthesis of MoSe2 nanoparticles presents a dynamic field where a multitude of innovative methods have been explored to tailor their properties for diverse applications. The versatility of MoSe2 nanoparticles, stemming from their tunable size, morphology, and composition, positions them as promising candidates for applications spanning electronics, energy storage, catalysis, and biomedicine. Through the careful selection of synthesis techniques, researchers can precisely engineer the structural and functional attributes of MoSe2 nanoparticles to meet the specific demands of these applications. Hydrothermal and solvothermal methods offer simplicity, scalability, and fine control over nanoparticle morphology, making them attractive options for producing MoSe2 nanostructures. Microwave-assisted synthesis capitalizes on rapid, energy-efficient reactions to generate nanocrystalline MoSe2 , while templateassisted methods provide additional control over structure and morphology. Each approach presents its own set of advantages and limitations, ranging from scalability challenges to the need for specialized equipment. Comparing these methods underscores the need for a holistic understanding of the synthesis parameters and their impact on the final product’s properties. Researchers should focus on advancing characterization techniques to gain precise insights into the structural, compositional, and electronic characteristics of MoSe2 nanoparticles. This knowledge will aid in fine-tuning the synthesis conditions and optimizing the resulting nanoparticles for targeted applications. While challenges like scalability, reproducibility, and property optimization persist, the horizon for MoSe2 nanoparticle research remains promising. Collaborative efforts between researchers across various disciplines will be essential to navigate these challenges and capitalize on the potential of MoSe2 nanoparticles. As the field advances, novel synthesis strategies and innovative applications will

An Overview of the Synthetic Route of Molybdenum Diselenide …

27

undoubtedly emerge, ushering in a new era of nanomaterials with tailored properties and multifunctional capabilities. The journey towards harnessing the full potential of MoSe2 nanoparticles continues, guided by the pursuit of scientific discovery and technological innovation.

References 1. Omorogbe SO, Aigbodion AI, Ifijen HI, Ogbeide-Ihama N, Simo A, Ikhuoria EU (2020) Low temperature synthesis of super paramagnetic Fe3 O4 morphologies tuned using oleic acid as crystal growth modifier. In: TMS 149th annual meeting & exhibition supplemental proceedings, pp 619–631 2. Ifijen IH, Ikhuoria EU, Maliki M, Otabor GO, Aigbodion AI (2022) Nanostructured materials: a review on its application in water treatment. In: The Minerals, Metals & Materials Society (eds) TMS 2022 151st annual meeting & exhibition supplemental proceedings. Springer, Cham, pp 1172–1180 3. Ifijen IH, Aghedo ON, Odiachi IJ, Omorogbe SO, Olu EL, Onuguh IC (2022) Nanostructured graphene thin films: a brief review of their fabrication techniques and corrosion protective performance. In: The Minerals, Metals & Materials Society (eds) TMS 2022 151st annual meeting & exhibition supplemental proceedings. Springer, Cham, pp 366–377 4. Ifijen IH, Maliki M, Omorogbe SO, Ibrahim SD (2022) Incorporation of metallic nanoparticles into alkyd resin: a review of their coating performance. In: The Minerals, Metals & Materials Society (eds) TMS 2022 151st annual meeting & exhibition supplemental proceedings. Springer, Cham, pp 338–349 5. Omorogbe SO, Ikhuoria SO, Ifijen IH, Simo A, Aigbodion AI, Maaza M (2019) Fabrication of monodispersed needle-sized hollow core polystyrene microspheres. In: The Minerals, Metals & Materials Society (eds) TMS 2019 148th annual meeting & exhibition supplemental proceedings, pp 155–164 6. Ifijen IH, Ikhuoria EU (2019) Generation of highly ordered 3D vivid monochromatic coloured photonic crystal films using evaporative induced technique. Tanzania J Sci 45(3):439–449 7. Ifijen IH, Ikhuoria EU (2020) Monodisperse polystyrene microspheres: studies on the effects of reaction parameters on particle diameter. Tanzania J Sci 46(1):19–30 8. Ifijen IH, Ikhuoria EU, Omorogbe SO (2018) Correlative studies on the fabrication of poly(styrene-methyl-methacrylate-acrylic acid) colloidal crystal films. J Dispersion Sci Technol 40(7):971–978 9. Ifijen IH, Ikhuoria EU, Omorogbe SO, Aigbodion AI (2019) Ordered colloidal crystals fabrication and studies on the properties of poly(styrene-butyl acrylate-acrylic acid) and polystyrene latexes. In: Srivatsan T, Gupta M (eds) Nanocomposites VI: nanoscience and nanotechnology in advanced composites. Springer, Cham, pp 155–164 10. Ifijen IH, Maliki M, Ovonramwen OB, Aigbodion AI, Ikhuoria EU (2019) Brilliant coloured monochromatic photonic crystals films generation from poly(styrene-butyl acrylate-acrylic acid) latex. J Appl Sci Environ Manag 23(9):1661–1664 11. Ifijen IH, Omorogbe SO, Maliki M, Odiachi IJ, Aigbodion AI, Ikhuoria EU (2020) Stabilizing capability of gum Arabic on the synthesis of poly(styrene-methylmethacrylate-acrylic acid) latex for the generation of colloidal crystal films. Tanzania J Sci 46(2):345–356 12. Omorogbe SO, Ikhuoria EU, Igiehon LI, Agbonlahor GO, Ifijen IH, Aigbodion AI (2017) Characterization of sulphated cellulose nanocrystals as stabilizer for magnetite nanoparticles synthesis with improved magnetic properties. Nigerian J Mater Sci Technol 7:21–30 13. Ifijen IH, Ikhuoria EU, Aigbodion AI, Omorogbe SO (2018) Impact of varying the concentration of tetraethyl-orthosilicate on the average particle diameter of monodisperse colloidal silica spheres. Chem Sci J 9(1):183–185

28

I. E. Uwidia et al.

14. Ikhuoria EU, Ifijen IH, Georgina OP, Ehigie AC, Omorogbe SO, Aigbodion AI (2020) The adsorption of heavy metals from aqueous solutions using silica microparticles synthesized from sodium silicate. In: Ni–Co 2021: the 5th international symposium on Ni and Co, pp 195–205 15. Ifijen IH, Ikhuoria EU (2020) A simple technique for the fabrication of P(St-BA-AA) colloidal crystal microdots on ink-jet paper. Heliyon 6(6):e04196. https://doi.org/10.1016/j.heliyon. 2020.e04196 16. Zhu W, Liu X, Tan L, Cui Z, Yang X, Liang Y, … & Wu S (2019) AgBr nanoparticles in situ growth on 2D MoS2 nanosheets for rapid bacteria-killing and photodisinfection. ACS Appl Mater Interfaces 11(37):34364–34375 17. Levchenko I, Bazaka K, Keidar M, Xu S, Fang J (2018) Hierarchical multicomponent inorganic metamaterials: intrinsically driven self-assembly at the nanoscale. Adv Mater 30(2):1702226 18. Yang H, Wei W, Mu C, Sun Q, Huang B, Dai Y (2018) Electronic structure and optical properties of Ag–MoS2 composite systems. J Phys D Appl Phys 51(8):085303 19. Mulu M, RamaDevi D, Basavaiah K (2021) Review on synthesis and applications of molybdenum disulfide (MoS2 ) nano material. Int J Creat Res Thoughts (IJCRT) 9(6):e215–e228. https://www.ijcrt.org/volume-9/issue-6/IJCRT2106485.pdf 20. Hung NT, Nugraha AR, Saito R (2018) Two-dimensional MoS2 electromechanical actuators. J Phys D Appl Phys 51(7):075306 21. Fang J, Aharonovich I, Levchenko I, Ostrikov K, Spizzirri PG, Rubanov S, Prawer S (2012) Plasma-enabled growth of single-crystalline SiC/AlSiC core–shell nanowires on porous alumina templates. Cryst Growth Des 12(6):2917–2922 22. Ramezani SM, Zarei-Hanzaki A, Abedi HR, Salandari-Rabori A, Minarik P (2019) Achievement of fine-grained bimodal microstructures and superior mechanical properties in a multi-axially forged GWZ magnesium alloy containing LPSO structures. J Alloy Compd 793:134–145 23. Huang Z, Qi Y, Yu D, Zhan J (2016) Radar-like MoS2 nanoparticles as a highly efficient 808 nm laser-induced photothermal agent for cancer therapy. RSC Adv 6(37):31031–31036 24. González C, Silva JPB, Viana AS, Gwozdz K, Conde O (2022) Shape-controlled monolayer MoSe2 flakes by chemical vapor deposition towards tuning the photoluminescence emission. Appl Surf Sci 605:154742. https://doi.org/10.1016/j.apsusc.2022.154742 25. Wang S, Wang G, Yang X, Yang H, Zhu M, Zhang S, Peng G, Li Z (2020) Synthesis of Monolayer MoSe2 with controlled nucleation via reverse-flow chemical vapor deposition. Nanomaterials 10:75. https://doi.org/10.3390/nano10010075 26. Siddiqui I, Mittal H, Kohli VK, Gautam P, Ali M, Khanuja M (2018) Hydrothermally synthesized micron sized, broom-shaped MoSe2 nanostructures for superior photocatalytic water purification. Mater Res Exp 5(12):125020. https://doi.org/10.1088/2053-1591/aae241 27. Burragoni SG, Koyyada G, Vattikuti SVP, Nam ND, Kim JH (2021) One-pot synthesis of flower-like MoSe2 nanoflakes for photocatalytic hydrogen evolution and methanol oxidation. Mater Lett 282:128678. https://doi.org/10.1016/j.matlet.2020.128678 28. Zhan JH, Zhang ZD, Qian XF, Wang C, Xie Y, Qian YT (1999) Synthesis of MoSe2 nanocrystallites by a solvothermal conversion from MoO3 . Mater Res Bull 34(4):497–501. https://doi. org/10.1016/S0025-5408(99)00048-3 29. Ghritlahre V, Kumari J, Agarwal P (2018) Synthesis and study of molybdenum diselenide (MoSe2 ) by solvo-thermal method. AIP Conf Proc 1953:050048. https://doi.org/10.1063/1. 5032703 30. Harpeness R, Gedanken A, Weiss AM, Slifkin MA (2003) Microwave-assisted synthesis of nanosized MoSe2 . J Mater Chem 13(10):2603–2611. https://doi.org/10.1039/b303740a 31. Reshmi S, Akshaya MV, Satpati B, Roy A, Basu PK, Bhattacharjee K (2017) Tailored MoS2 nanorods: a simple microwave-assisted synthesis. Mater Res Exp 4(11):115012. https://doi. org/10.1088/2053-1591/aa949c 32. Kirubasankar B, Vijayan S, Angaiah S (2019) Sonochemical synthesis of a 2D–2D MoSe2 / graphene nanohybrid electrode material for asymmetric supercapacitors. Sustain Energy Fuels 3:467–477. https://doi.org/10.1039/C8SE00446C

An Overview of the Synthetic Route of Molybdenum Diselenide …

29

33. Choi YH (2022) Molybdenum oxide nanoparticle aggregates grown by chemical vapor transport. Materials (Basel) 15(6):2182. https://doi.org/10.3390/ma15062182 34. Hu D, Xu G, Xing L, Yan X, Wang J, Zheng J, … Jiao L (2017) Two-dimensional semiconductors grown by chemical vapor transport. Angewandte Chemie Int Edn 56(13):3611–3615. https://doi.org/10.1002/anie.201700439 35. Li L, Zhang D, Gao Y, Deng J, Gou Y, Fang J (2021) Electric field driven exfoliation of MoS2 . J Alloy Compd 862:158551. https://doi.org/10.1016/j.jallcom.2020.158551 36. Zheng W, Lee LYS (2022) Beyond sonication: advanced exfoliation methods for scalable production of 2D materials. Matter 5(2):515–545. https://doi.org/10.1016/j.matt.2021.12.010 37. Patra JK, Baek K-H (2014) Green nanobiotechnology: factors affecting synthesis and characterization techniques. J Nanomater 2014:417305. https://doi.org/10.1155/2014/417305 38. Swihart MT (2003) Vapor-phase synthesis of nanoparticles. Curr Opin Colloid Interface Sci 8:127–133. https://doi.org/10.1016/S1359-0294(03)00007-4 39. Pantano MF, Kuljanishvili I (2020) Advances in mechanical characterization of 1D and 2D nanomaterials: progress and prospects. Nano Exp 1(2):022001. https://doi.org/10.1088/2632959X/abb43e 40. Shanmugam V, Mensah RA, Babu K, Gawusu S, Chanda A, Tu Y, Neisiany RE, Försth M, Sas G, Das O (2022) A review of the synthesis, properties, and applications of 2D materials. In: Particle & particle systems characterization. Advance Online Publication. https://doi.org/10. 1002/ppsc.202200031 41. Li Y, Zhang K, Wang F, Feng Y, Li Y, Han Y, Tang D, Zhang B (2017) Scalable synthesis of highly crystalline MoSe2 and its ambipolar behavior. ACS Appl Mater Interfaces 9(41):36009– 36016. https://doi.org/10.1021/acsami.7b10693 42. Lu X, Utama MIB, Lin J, Gong X, Zhang J, Zhao Y, … Xiong Q (2014) Large-area synthesis of monolayer and few-layer MoSe2 Films on SiO2 substrates. Nano Lett 14(5):2419–2425. https://doi.org/10.1021/nl5000906 43. Alam S, Chowdhury MA, Shahid A, Alam R, Rahim A (2021) Synthesis of emerging two-dimensional (2D) materials—advances, challenges and prospects. FlatChem 30:100305. https://doi.org/10.1016/j.flatc.2021.100305 44. Petri´c MM, Kremser M, Barbone M, Nolinder A, Lyamkina A, Stier AV, Kaniber M, Müller K, Finley JJ (2022) Tuning the optical properties of a MoSe2 monolayer using nanoscale plasmonic antennas. Nano Lett 22(2):561–569. https://doi.org/10.1021/acs.nanolett.1c02676 45. Xia D (D) Gong F, Pei X, Wang W, Li H, Zeng W, Wu M, Papavassiliou DV (2018) Molybdenum and tungsten disulfides-based nanocomposite films for energy storage and conversion: a review. Chem Eng J 348:519–542. https://doi.org/10.1016/j.cej.2018.04.207 46. Baig N (2023) Two-dimensional nanomaterials: a critical review of recent progress, properties, applications, and future directions. Compos A Appl Sci Manuf 165:107362. https://doi.org/10. 1016/j.compositesa.2022.107362 47. Eftekhari A (2017) Molybdenum diselenide (MoSe2 ) for energy storage, catalysis, and optoelectronics. Appl Mater Today 8:1–17. https://doi.org/10.1016/j.apmt.2017.01.006

Exploring the Remarkable Gas Sensing Capability of Molybdenum Diselenide Nanoparticles Asishana Paul Onivefu, Esther Uwidia Ikhuoria, Maliki Muniratu, and Ikhazuagbe Hilary Ifijen

Abstract Gas sensing is pivotal in numerous applications, from environmental monitoring to healthcare and industrial safety. Molybdenum Diselenide (MoSe2 ) nanoparticles have emerged as promising gas sensing materials due to their exceptional sensitivity and selectivity. This mini-review elucidates MoSe2 ’s gas sensing mechanism, encompassing surface adsorption and charge transfer processes, while highlighting the roles of defects and functionalization in enhancing sensing performance. Notably, MoSe2 -based sensors excel in sensitivity and selectivity for various gases. A compilation of key findings from several research studies emphasizes their impressive gas sensing capabilities. MoSe2 -based sensors operate efficiently at room temperature, outperforming traditional materials in terms of energy efficiency and sensitivity. Current applications span environmental monitoring, healthcare, and industrial safety, with future prospects centered on improving sensitivity, selectivity, and integration with emerging technologies such as wearables and the IoT. Although challenges exist, ongoing research endeavours aim to maximize MoSe2 ’s potential for revolutionizing gas sensing applications. Keywords Gas sensing · Molybdenum Diselenide · Nanoparticles

A. P. Onivefu Chemistry and Biochemistry, University of Delaware, Newark, DE, USA E. U. Ikhuoria Department of Chemistry, University of Benin, Benin City, Edo State, Nigeria M. Muniratu Department of Chemistry, Edo State University Uzairue, Auchi, Edo State, Nigeria I. H. Ifijen (B) Department of Research Outreach, Rubber Research Institute of Nigeria, Benin City, Edo State, Nigeria e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_3

30

Exploring the Remarkable Gas Sensing Capability of Molybdenum …

31

Introduction Nanoparticles have ushered in a new era of innovation across various scientific disciplines, revolutionizing fields from medicine to materials science [1–5]. Their remarkable properties, such as high surface area-to-volume ratios and tunable surface functionalities, have paved the way for groundbreaking advancements [6–10]. Nanoparticles, as minute as they are, offer immense potential to revolutionize gas sensing technologies [11–15]. This mini-review explores the fascinating realm of gas sensing, with a particular focus on the exceptional capabilities of Molybdenum Diselenide (MoSe2 ) nanoparticles. Gas sensors play a pivotal role in monitoring and detecting various gases, offering critical insights into environmental conditions, industrial safety, and healthcare diagnostics [16, 17]. They enable the real-time detection of hazardous gases, pollutant monitoring, and the early diagnosis of diseases through breath analysis [18–21]. The burgeoning interest in enhancing the sensitivity, selectivity, and response times of gas sensors has led to a quest for novel materials with superior sensing properties [22, 23]. MoSe2 nanoparticles have emerged as a promising candidate in this context, owing to their unique electronic and structural properties [22, 23]. This mini-review aims to elucidate the rise of MoSe2 as a potent gas sensing material, delving into the underlying mechanisms, synthesis methods, and remarkable sensing properties associated with these nanoparticles. It also discusses current applications and future prospects, all while shedding light on the challenges and limitations that researchers are actively addressing. In the subsequent sections, we will delve deeper into the synthesis techniques, gas sensing mechanisms, exceptional properties, applications, and future directions of MoSe2 nanoparticles in the gas sensing landscape.

Gas Sensing Mechanism of MoSe2 Adsorption of Gas Molecules The gas sensing process begins with the adsorption of gas molecules onto the surface of MoSe2 [24]. MoSe2 has a high surface-to-volume ratio due to its two-dimensional structure, making it an ideal candidate for gas sensing. Gas molecules are attracted to the exposed selenium (Se) atoms on the MoSe2 surface through weak van der Waals forces [25].

32

A. P. Onivefu et al.

Charge Transfer Upon adsorption, gas molecules interact with the selenium atoms on the MoSe2 surface. This interaction results in a charge transfer between the gas molecules and the MoSe2 material [26]. The nature and extent of this charge transfer depend on the type of gas and its chemical properties. Typically, when gas molecules adsorb onto the MoSe2 surface, they donate or accept electrons, leading to the formation of charge carriers [27].

Change in Electronic Structure The charge transfer induced by gas adsorption leads to a change in the electronic structure of MoSe2 . MoSe2 is usually a semiconductor with a finite bandgap in its pristine state [28]. However, the introduction of charge carriers due to gas adsorption effectively modulates its electronic properties. This can result in a shift in the material’s Fermi level, which is indicative of changes in the concentration of charge carriers [29].

Change in Conductivity One of the most critical effects of gas adsorption on MoSe2 is the alteration of its electrical conductivity [30]. The presence of charge carriers in the material changes its conductivity. Depending on the type and concentration of gas molecules, the conductivity of MoSe2 can increase or decrease [30]. This change in conductivity serves as the basis for gas detection.

Sensing Response The change in electrical conductivity of MoSe2 is directly related to the concentration of gas molecules in the surrounding environment [31]. By measuring the electrical resistance or conductance of the MoSe2 material, one can monitor the presence and concentration of the target gas [32]. A higher concentration of gas molecules leads to a more pronounced change in conductivity, resulting in a stronger sensing response.

Exploring the Remarkable Gas Sensing Capability of Molybdenum …

33

Role of Defects Defects in the MoSe2 lattice play a crucial role in gas sensing. Defects can act as active sites for gas adsorption, facilitating the interaction between gas molecules and the material [30]. Additionally, defects can influence the electronic structure of MoSe2 , making it more sensitive to gas molecules [31]. The presence of defects can enhance the gas sensing performance by increasing the surface area and providing more sites for gas adsorption [32].

Functionalization Functionalization involves the deliberate modification of MoSe2 nanoparticles with specific functional groups or materials to improve their gas sensing performance [25]. Functionalization can enhance gas adsorption and provide selectivity for specific gas molecules [26]. For example, the introduction of oxygen-containing functional groups can improve the sensitivity of MoSe2 to NO2 due to enhanced chemical reactivity [30].

Role of Temperature and Environment The gas sensing behaviour of MoSe2 nanoparticles can be temperature dependent [32]. At higher temperatures, the desorption of gas molecules from the surface may occur more rapidly, affecting the sensor response time and recovery time [32]. Additionally, the surrounding environment, including humidity and the presence of interfering gases, can influence the gas sensing performance. In summary, MoSe2 -based gas sensing involves a complex interplay of factors, from gas adsorption and charge transfer to changes in electronic structure and conductivity. The presence of defects, functionalization, and environmental conditions further affect the performance of MoSe2 gas sensors. Understanding these mechanisms is crucial for designing and optimizing MoSe2 -based gas sensing devices for various applications.

34

A. P. Onivefu et al.

Remarkable Sensing Properties Key Findings on MoSe2 ’s Exceptional Sensitivity and Selectivity to Different Gases Molybdenum Diselenide (MoSe2 ) has emerged as a material of great interest in the field of gas sensing due to its remarkable properties [18]. One of its most notable features is its exceptional sensitivity to various gases. MoSe2 -based sensors have demonstrated the ability to detect gases like nitrogen dioxide (NO2 ), ammonia (NH3 ), and volatile organic compounds (VOCs) with high sensitivity, even at low concentrations [17, 19]. This heightened sensitivity is attributed to MoSe2 ’s two-dimensional structure, which provides a large surface area for gas adsorption. When gas molecules interact with the exposed selenium (Se) atoms on the MoSe2 surface, they induce changes in the material’s electrical conductivity, enabling precise gas detection [23]. Moreover, MoSe2 exhibits remarkable selectivity towards specific gases. For example, it can selectively detect carbon monoxide (CO) amidst a mixture of gases, highlighting its potential for safety applications like CO detection in indoor environments [33]. This selectivity is a critical feature in gas sensing, as it ensures accurate and reliable detection, especially in scenarios where multiple gases may be present. MoSe2 ’s ability to differentiate between different gas species enhances its utility in various industrial, environmental, and healthcare settings [32]. MoSe2 ’s sensing properties are not limited to its sensitivity and selectivity alone; they also include fast response and recovery times [23]. These sensors can rapidly detect changes in gas concentrations and return to their baseline state once the gas is removed [23]. This real-time responsiveness is crucial for timely action in response to gas hazards, making MoSe2 -based sensors suitable for applications where quick detection and reaction are essential [33]. Furthermore, the ability to customize and tailor MoSe2 -based sensors for specific gases is a significant advantage [34]. Researchers can modify the material’s surface properties through techniques like functionalization and defect engineering, allowing for the optimization of sensitivity and selectivity towards gases [34]. This tunability makes MoSe2 an adaptable material for addressing various gas sensing challenges. Another noteworthy aspect of MoSe2 ’s gas sensing performance is its low detection limits. These sensors can detect trace amounts of gases, which is vital in applications requiring the early detection of gas leaks or environmental contaminants [28]. This capability enhances safety and environmental monitoring efforts, contributing to improved overall well-being [27]. In terms of energy efficiency, some MoSe2 sensors can operate at relatively low temperatures, reducing energy consumption. This is advantageous for batterypowered or portable gas sensing devices, where energy efficiency plays a crucial role in extending the device’s operational lifetime and usability [34]. MoSe2 ’s exceptional sensitivity, selectivity, responsiveness, tunability, low detection limits, and energy efficiency position it as a promising material for gas sensing applications. Its potential to detect a wide range of gases accurately and rapidly

Exploring the Remarkable Gas Sensing Capability of Molybdenum …

35

Fig. 1 a I–V characteristic of sensing device in temperature range 50–200 °C (inset: I–V characteristics for 50 and 100 °C), b variation of response with temperature in ambient environment, c dynamic sensing response and variation in current at T = 200 °C for H2 S concentration of 50 ppb–5.45 ppm in ambient environment, d dynamic sensing response and variation in current at T = 200 °C for H2 S concentration of 500 ppb–5.45 ppm in synthetic air [34]

makes it valuable in various fields, including environmental monitoring, industrial safety, healthcare, and beyond. As researchers continue to explore and optimize MoSe2 -based gas sensors, their potential impact on improving gas detection and safety measures is substantial. Here is a summary of several research studies focusing on MoSe2 nanoparticles that have demonstrated impressive gas sensing capabilities. Jha et al. [35] conducted a study on the fabrication of a liquid-exfoliated MoSe2 nanoflakes-based stable chemiresistive H2 S gas sensor operating at a moderate temperature of 200 °C (Fig. 1a) [34]. The results of their investigation revealed intriguing findings regarding the sensor’s performance characteristics. The p-type MoSe2 gas sensor exhibited a remarkable response to varying concentrations of H2 S gas when operated in an ambient environment. As depicted in Fig. 1b, the response ranged from 15.87 to 53.04% as the concentration of H2 S was varied between 50 ppb and 5.45 ppm. This wide range of response demonstrates the sensor’s sensitivity to different levels of H2 S gas. Figure 1c illustrates the dynamic transient response of the sensor, showing real-time current variations. The response of the sensor in the range of 53.04–18.57% (corresponding to H2 S concentrations of 5.45 ppm down to 50 ppb)

36

A. P. Onivefu et al.

was obtained when the sensor was allowed to recover in ambient conditions. However, a significant decrease in response was observed when the recovery was performed in a synthetic air environment. In the synthetic air environment (Fig. 1d), the sensor’s response ranged from 7.13 to 19.87% for H2 S concentrations spanning from 500 ppb to 5.45 ppm. This discrepancy in response between ambient and synthetic air environments suggests that the sensor performs more effectively in real-world conditions, highlighting its potential for practical applications. The sensor displayed rapid response and recovery times, with values of 15 and 43 s, respectively, for detecting 100 ppb of H2 S. The repeatability of the sensor’s performance was notably high, with a sensitivity of 5.57% per ppm of H2 S. Theoretical calculations led to the determination of the device’s limit of detection and limit of quantization, which were found to be 6.73 and 22.44 ppb, respectively. These values underscore the sensor’s ability to detect low concentrations of H2 S gas. Based on chemical analysis, the authors proposed a plausible mechanism for the sensor’s operation, suggesting that it relies on a charge transfer phenomenon. This mechanism elucidates the sensor’s sensitivity to H2 S gas and provides insights into its underlying operation. In a recent study conducted by Li et al. [36], a highly sensitive ethanol sensor was developed using Ag-doped MoSe2 nanomaterials that operate at room temperature [36]. The researchers employed a hydrothermal synthesis method to fabricate MoSe2 and Ag-modified MoSe2 nanoflowers, which exhibited exceptional purity and crystallinity. Various characterization techniques, including SEM, TEM, XRD, and XPS, were utilized to comprehensively analyze the micromorphology and microstructure of the Ag–MoSe2 nanomaterial. The resulting Ag-modified MoSe2 nanomaterial consisted of nanoflowers assembled from numerous nanosheets. Gas-sensing experiments were conducted, revealing that the Ag-modified MoSe2 -based sensor outperformed pristine MoSe2 , showcasing a low detection limit of 10 ppb and excellent response/recovery characteristics when exposed to ethanol at room temperature. This level of sensitivity holds great promise for applications in alcohol testing for individuals who have consumed alcoholic beverages. To gain further insights into the sensing mechanism, the researchers conducted simulations of adsorption configurations for both pristine and Ag-doped MoSe2 using density functional theory (DFT). Remarkably, the DFT simulations corroborated the experimental findings, demonstrating that the Ag–MoSe2 system exhibited superior ethanol sensing performance compared to pristine MoSe2 . This combination of experimental data and DFT simulations provides strong evidence that Ag-doped MoSe2 nanoflowers have significant potential as sensors for detecting low concentrations of ethanol at room temperature. In another study, Chen et al. [37] developed a simple and effective liquid-phase exfoliation method to convert bulk MoSe2 into nanosheets [37] (Fig. 2). They used anhydrous ethanol as a dispersant, which could be easily removed from the MoSe2 nanosheets without affecting their sensing abilities. The exfoliated MoSe2 nanosheets exhibited remarkable improvements in NO2 gas sensing. Figure 3a demonstrates that MoSe2 -2 had the highest response, reaching 1500% for 10 ppm NO2 , which was 18 times better than bulk MoSe2 . Figure 3b showed that MoSe2 -2 had a significantly faster response compared to bulk MoSe2 when exposed to 10 ppm NO2 . This indicated strong adhesion of gas molecules to the nanosheets, contributing to high

Exploring the Remarkable Gas Sensing Capability of Molybdenum …

37

Fig. 2 Schematic illustration of the preparation of MoSe2 nanosheets [37]

sensitivity. Figure 3c displayed the dynamic sensing curve of MoSe2 -2, indicating excellent sensitivity to NO2 concentrations as low as 50 ppb, with the response value increasing as the gas concentration rose. Figure 3d depicted the cycle stability of MoSe2 -2 with five consecutive cycles of exposure to 10 ppm NO2 . The response value increased during the cycles due to NO2 molecules remaining on the nanosheet surface after the recovery process, preventing complete recovery. In summary, Chen et al.’s study showcased the outstanding gas sensing capabilities of exfoliated MoSe2 nanosheets, providing a promising avenue for room temperature NO2 detection. Late et al. [38] explored the utility of single-layer MoSe2 as high-performance room temperature NH3 gas sensors, reporting promising results [38]. Their singlelayer MoSe2-based gas sensor demonstrated effective detection of NH3 gas down to 50 ppm. To validate gas sensing, Raman spectra were recorded before and after exposing the device to NH3 gas, revealing shifts indicative of charge transfer and analyte gas molecule adsorption on the surface of single-layer MoSe2 nanosheets. These findings suggest the potential use of single-layer and few-layer thick MoSe2 , as well as other transition metal dichalcogenides (TMDCs), as high-performance gas sensors. Figure 4a presents an optical photograph of the MoSe2 gas sensor device mounted on the chip carrier. Gas sensing performance was evaluated by subjecting the sensor device to various NH3 concentrations. In Fig. 4b, the NH3 gas sensing response, expressed as relative resistance variation, is depicted for concentrations ranging from 50 to 500 ppm. The data revealed increased sensitivity with higher gas concentrations, and the results were found to be comparable with recent reports on MoS2 sensor devices. The response time of the single-layer MoSe2 -based NH3 sensors was approximately 2.5 min, demonstrating faster response compared to single-layer MoS2 sensors, which typically range from 5 to 9 min. The recovery

38

A. P. Onivefu et al.

Fig. 3 a Response value of each sample to different concentrations of NO2 . b Response and recovery curves of bulk MoSe2 and MoSe2 -2–10 ppm NO2 . c Dynamic curves of MoSe2 -2 to different concentrations of NO2 . d Cyclic response curve of MoSe2 -2–10 ppm NO2 [38]

time, defined as the time required for the resistance to return below a 10% change of the overall range, was approximately 9 min, comparable to previous reports on MoS2 -based gas sensors. The slower recovery is attributed to the strong adhesion of gas molecules to the sensing material. Figure 3c illustrates the sensitivity versus NH3 concentration plot, showing increasing sensitivity as gas concentration rises. To elucidate the charge transfer mechanism responsible for the resistance changes in the presence of NH3 gas, Raman spectroscopy was employed. Figure 4d displays the A1g Raman peak of single-layer MoSe2 before and after exposure to 1000 ppm of NH3 . Clear shifts in the peak position and an increase in the full width at half maximum were observed, indicating n-doping in MoSe2 induced by NH3 exposure. This shift confirms the charge transfer mechanism as analyte gas molecules, such as NH3 , adsorb onto the surface of single-layer MoSe2 nanosheets, leading to substantial changes in carrier concentration, as observed in electrical measurements. In summary, Late et al.’s study demonstrates the potential of single-layer MoSe2 as an effective room temperature NH3 gas sensor. The study combines experimental findings with Raman spectroscopy to elucidate the charge transfer mechanism responsible for the

Exploring the Remarkable Gas Sensing Capability of Molybdenum …

39

Fig. 4 Sensing behavior of single-layer MoSe2 a optical image gas of sensor device fabricated using E-beam lithography, b NH3 sensing response as function of gas concentration, c linear plot of sensitivity of MoSe2 gas sensor device as a function of NH3 gas concentration (ppm), and d Raman spectrum of single-layer MoSe2 recorded at ambient, Ar environment and after exposure with 1000 ppm of NH3 [38]

sensor’s performance, highlighting the promise of MoSe2 and similar TMDCs for high-performance gas sensing applications.

Comparison with Traditional Materials When compared to traditional gas sensing materials, MoSe2 stands out in terms of its sensing performance [39]. Unlike conventional metal oxide-based sensors, which often require elevated operating temperatures for optimal performance, MoSe2 can operate effectively at room temperature. This not only reduces energy consumption but also makes MoSe2 -based sensors suitable for portable and low-power applications [40]. Moreover, MoSe2 ’s sensitivity and selectivity to specific gases surpass that of many traditional materials. Its ability to detect gases like NH3 at extremely low

40

A. P. Onivefu et al.

concentrations (parts per billion) sets it apart in applications such as air quality monitoring, where detecting trace amounts of pollutants is crucial [38].

Factors Influencing Sensing Performance Several factors influence MoSe2 ’s sensing performance. These include surface modification, defect engineering, operating temperature, and the surrounding environment [29]. Researchers can enhance sensitivity and selectivity by modifying the material’s surface through functionalization, which introduces specific functional groups to improve gas adsorption [25, 26]. Defects in the MoSe2 lattice play a crucial role in gas sensing. They can act as active sites for gas adsorption and influence the material’s electronic structure, making it more sensitive to gas molecules [30, 31]. Additionally, operating temperature can impact sensor response and recovery times. Higher temperatures can promote faster desorption of gas molecules from the material’s surface [32]. The surrounding environment, including humidity and the presence of interfering gases, can also influence the gas sensing performance of MoSe2 sensors. Understanding these factors and optimizing the sensor’s conditions is essential for achieving the desired sensing performance [34]. In a nutshell, MoSe2 ’s remarkable sensing properties, including sensitivity, selectivity, and room-temperature operation, position it as a promising material for gas sensors. Its advantages over traditional materials make it a valuable candidate for various gas sensing applications, from environmental monitoring to industrial safety and beyond.

Challenges Despite the promising capabilities of Molybdenum Diselenide (MoSe2 ) nanoparticles in gas sensing, several challenges need to be addressed for their widespread adoption and successful implementation in various applications [30–37]. 1. Specificity and Selectivity: Achieving high specificity and selectivity for target gases while minimizing false positives remains a significant challenge. Discriminating between different gas species, especially in complex environments with multiple gases, is a complex task that requires advanced sensor designs and recognition algorithms. 2. Interference from Environmental Factors: MoSe2 sensors can be sensitive to changes in environmental conditions, such as humidity, temperature, and the presence of other gases. Developing strategies to mitigate these environmental interferences and ensuring stable sensor performance under varying conditions is essential.

Exploring the Remarkable Gas Sensing Capability of Molybdenum …

41

3. Long-Term Stability: Maintaining the long-term stability of MoSe2 sensors is critical for practical applications. Over time, the material may degrade or undergo structural changes that affect its sensing performance. Ensuring sensor reliability and longevity is a persistent challenge. 4. Low Concentration Detection: While MoSe2 sensors exhibit remarkable sensitivity, detecting gases at ultra-low concentrations, especially in parts per billion (ppb) or lower, can be challenging. Achieving even greater sensitivity is essential for applications such as early disease detection or environmental monitoring. 5. Power Consumption: For portable and low-power applications, reducing the power consumption of MoSe2 -based sensors is crucial. Balancing sensor performance with energy efficiency remains a challenge, particularly in remote or battery-operated devices. 6. Scalability and Manufacturing: Transitioning from laboratory-scale synthesis to scalable and cost-effective manufacturing processes is a barrier to widespread adoption. Developing reliable and reproducible fabrication methods for MoSe2 sensors is essential to meet market demands. 7. Real-Time Response: Ensuring rapid response and recovery times, particularly in dynamic or emergency scenarios, presents a challenge. Reducing the sensor’s response and recovery times while maintaining accuracy is a complex engineering task. 8. Safety and Reliability: MoSe2 sensors may find applications in critical safety and security contexts. Ensuring their reliability and accuracy in such applications, such as gas leak detection or explosive gas sensing, is of utmost importance. 9. Environmental Impact: Consideration of the environmental impact of MoSe2 based sensors, including the materials used and disposal at the end of their lifecycle, is crucial for sustainable sensor technology. 10. Regulatory Compliance: Meeting regulatory standards and certifications for gas sensors in various industries can be challenging. Developing sensors that adhere to safety and quality standards is essential for market acceptance. Addressing these challenges requires interdisciplinary research efforts, including materials science, nanotechnology, sensor design, data analytics, and environmental science. Collaboration between academia, industry, and regulatory bodies is essential to drive innovations in MoSe2 -based gas sensing technology and unlock its full potential in diverse applications.

Future Directions Exploring the Remarkable Gas Sensing Capability of Molybdenum Diselenide (MoSe2 ) Nanoparticles opens up exciting avenues for future research and development in the field of gas sensing technology. Here are some potential future directions in this area [34–39]:

42

A. P. Onivefu et al.

1. Enhancing Sensitivity and Selectivity: Future research can focus on further enhancing the sensitivity and selectivity of MoSe2 -based gas sensors. This can be achieved through advanced material engineering, such as the creation of MoSe2 nanostructures with tailored properties, improved defect engineering, and innovative surface functionalization techniques. Developing strategies to selectively detect specific gases, even in the presence of interfering gases, will be a significant challenge. 2. Low-Power and Portable Devices: As the demand for low-power and portable gas sensors increases, future efforts can concentrate on developing MoSe2 based sensors that are highly energy-efficient. This may involve optimizing the sensor’s operational parameters to reduce power consumption, as well as integrating MoSe2 sensors into miniaturized and portable devices for real-time gas monitoring in various applications. 3. Integration with IoT and Smart Systems: The integration of MoSe2 gas sensors with the Internet of Things (IoT) and smart systems holds enormous potential. Future research can focus on developing wireless, networked sensor systems that can transmit real-time gas data to centralized databases or control systems. These integrated systems can find applications in smart cities, industrial automation, and environmental monitoring. 4. Environmental and Healthcare Applications: Future studies can explore the applicability of MoSe2 gas sensors in critical environmental monitoring, including air quality assessment, pollutant detection, and emissions control. Additionally, the healthcare sector could benefit from the development of MoSe2 -based sensors for medical diagnostics, such as breath analysis for disease detection. 5. Safety and Security: Gas sensors are essential for ensuring safety in various industries, including manufacturing, mining, and chemical processing. Future directions may involve optimizing MoSe2 sensors for industrial safety applications, such as early detection of gas leaks and hazardous substance monitoring. Security applications, such as detecting explosive or toxic gases, also represent an important area of research. 6. Real-Time and In Situ Sensing: Advances in in situ and real-time gas sensing techniques are crucial for timely responses to gas-related hazards. Future research can focus on developing MoSe2 sensors that offer rapid response and recovery times, making them suitable for real-time monitoring applications, including emergency response systems and leak detection. 7. Multimodal Sensing: Combining gas sensing capabilities with other sensing modalities, such as temperature, humidity, or light, can lead to the development of versatile and context-aware sensor systems. Future directions may involve integrating MoSe2 gas sensors into multifunctional platforms that provide a holistic view of environmental conditions. 8. Commercialization and Scalability: Transitioning from laboratory-scale research to scalable and cost-effective production of MoSe2 -based gas sensors will be a critical step. Future efforts can focus on manufacturing processes, production scalability, and cost optimization to facilitate the widespread adoption of this technology.

Exploring the Remarkable Gas Sensing Capability of Molybdenum …

43

In conclusion, the exploration of MoSe2 ’s remarkable gas sensing capability presents numerous exciting prospects for future research and applications. As researchers continue to innovate in materials science and sensor technology, MoSe2 based gas sensors are poised to play a pivotal role in addressing environmental, industrial, and healthcare challenges. The development of advanced, sensitive, and reliable gas sensors will contribute to safer and healthier living environments while supporting technological advancements in various sectors.

Conclusion Gas sensing technologies play a pivotal role in diverse fields, from ensuring environmental safety to enhancing healthcare and industrial processes. The emergence of Molybdenum Diselenide (MoSe2 ) as a promising gas sensing material has sparked significant interest due to its exceptional sensitivity and selectivity to various gases. Throughout this mini-review, we have delved into the intricate gas sensing mechanism of MoSe2 nanoparticles, shedding light on processes such as surface adsorption and charge transfer. We have also explored the pivotal roles of defects and functionalization in elevating MoSe2 ’s gas sensing performance, setting the stage for its future applications. The remarkable sensing properties of MoSe2 , including its room-temperature operation and its ability to distinguish between different gases, have positioned it as a leading candidate for gas sensing applications. Comparing MoSe2 -based gas sensors with traditional materials highlights its advantages, particularly in terms of energy efficiency and sensitivity. Examining current applications of MoSe2 -based gas sensors reveals their potential in environmental monitoring, industrial safety, and healthcare. Looking ahead, future directions in MoSe2 gas sensing research may encompass advancements in sensitivity, selectivity, and integration with emerging technologies, such as wearable devices and the Internet of Things (IoT). Nonetheless, we have also identified challenges and limitations, including the need for enhanced stability, long-term performance, and adaptability to varying environmental conditions. Ongoing research endeavours are actively addressing these issues, with the aim of further harnessing the potential of MoSe2 -based gas sensors. In closing, the journey of MoSe2 in gas sensing represents a compelling chapter in the evolving landscape of sensor technology. As researchers continue to unlock its capabilities and address its limitations, MoSe2 holds great promise in revolutionizing gas sensing applications and contributing to a safer and healthier future.

44

A. P. Onivefu et al.

References 1. Omorogbe SO, Aigbodion AI, Ifijen HI, Ogbeide-Ihama N, Simo A, Ikhuoria EU (2020) Low temperature synthesis of super paramagnetic Fe3 O4 morphologies tuned using oleic acid as crystal growth modifier. In: TMS 149th annual meeting & exhibition supplemental proceedings, pp 619–631 2. Ifijen IH, Ikhuoria EU, Maliki M, Otabor GO, Aigbodion, AI (2022) Nanostructured materials: a review on its application in water treatment. In: The Minerals, Metals & Materials Society (eds) TMS 2022 151st annual meeting & exhibition supplemental proceedings. Springer, Cham, pp 1172–1180 3. Ifijen IH, Aghedo ON, Odiachi IJ, Omorogbe SO, Olu EL, Onuguh IC (2022) Nanostructured graphene thin films: a brief review of their fabrication techniques and corrosion protective performance. In: The Minerals, Metals & Materials Society (eds) TMS 2022 151st annual meeting & exhibition supplemental proceedings. Springer, Cham, pp 366–377 4. Ifijen IH, Maliki M, Omorogbe SO, Ibrahim SD (2022) Incorporation of metallic nanoparticles into alkyd resin: a review of their coating performance. In: The Minerals, Metals & Materials Society (eds) TMS 2022 151st annual meeting & exhibition supplemental proceedings. Springer, Cham, pp 338–349 5. Omorogbe SO, Ikhuoria SO, Ifijen IH, Simo A, Aigbodion AI, Maaza M (2019) Fabrication of monodispersed needle-sized hollow core polystyrene microspheres. In: The Minerals, Metals & Mater Soc (eds) TMS 2019 148th annual meeting & exhibition supplemental proceedings, pp 155–164 6. Ifijen IH, Ikhuoria EU (2019) Generation of highly ordered 3D vivid monochromatic coloured photonic crystal films using evaporative induced technique. Tanzania J Sci 45(3):439–449 7. Ifijen IH, Ikhuoria EU (2020) Monodisperse polystyrene microspheres: Studies on the effects of reaction parameters on particle diameter. Tanzania J Sci 46(1):19–30 8. Ifijen IH, Ikhuoria EU, Omorogbe SO (2018) Correlative studies on the fabrication of poly(styrene-methyl-methacrylate-acrylic acid) colloidal crystal films. J Dispersion Sci Technol 40(7):971–978 9. Ifijen IH, Ikhuoria EU, Omorogbe SO, Aigbodion AI (2019) Ordered colloidal crystals fabrication and studies on the properties of poly(styrene-butyl acrylate-acrylic acid) and polystyrene latexes. In: Srivatsan T, Gupta M (eds) Nanocomposites VI: nanoscience and nanotechnology in advanced composites. Springer, Cham, pp 155–164 10. Ifijen IH, Maliki M, Ovonramwen OB, Aigbodion AI, Ikhuoria EU (2019) Brilliant coloured monochromatic photonic crystals films generation from poly(styrene-butyl acrylate-acrylic acid) latex. J Appl Sci Environ Manag 23(9):1661–1664 11. Ifijen IH, Omorogbe SO, Maliki M, Odiachi IJ, Aigbodion AI, Ikhuoria EU (2020) Stabilizing capability of gum Arabic on the synthesis of poly(styrene-methylmethacrylate-acrylic acid) latex for the generation of colloidal crystal films. Tanzania J Sci 46(2):345–356 12. Omorogbe SO, Ikhuoria EU, Igiehon LI, Agbonlahor GO, Ifijen IH, Aigbodion AI (2017) Characterization of sulphated cellulose nanocrystals as stabilizer for magnetite nanoparticles synthesis with improved magnetic properties. Niger J Mater Sci Technol 7:21–30 13. Ifijen IH, Ikhuoria EU, Aigbodion AI, Omorogbe SO (2018) Impact of varying the concentration of tetraethyl-orthosilicate on the average particle diameter of monodisperse colloidal silica spheres. Chem Sci J 9(1):183–185 14. Ikhuoria EU, Ifijen IH, Georgina OP, Ehigie AC, Omorogbe SO, Aigbodion AI (2020) The adsorption of heavy metals from aqueous solutions using silica microparticles synthesized from sodium silicate. In: Ni–Co 2021: the 5th international symposium on Ni and Co, pp 195–205 15. Ifijen IH, Ikhuoria EU (2020) A simple technique for the fabrication of P(St-BA-AA) colloidal crystal microdots on ink-jet paper. Heliyon 6(6):e04196. https://doi.org/10.1016/j.heliyon. 2020.e04196 16. Gomes JBA, Rodrigues JJPC, Rabêlo RAL, Kumar N, Kozlov S (2019) IoT-enabled gas sensors: technologies, applications, and opportunities. J Sens Actuator Netw 8:57. https://doi.org/10. 3390/jsan8040057

Exploring the Remarkable Gas Sensing Capability of Molybdenum …

45

17. Yaqoob U, Younis MI (2021) Chemical gas sensors: recent developments, challenges, and the potential of machine learning-a review. Sensors (Basel) 21(8):2877. https://doi.org/10.3390/ s21082877 18. Yi N, Shen M, Erdely D, Cheng H (2020) Stretchable gas sensors for detecting biomarkers from humans and exposed environments. Trends Anal Chem 133:116085. https://doi.org/10. 1016/j.trac.2020.116085 19. Ochoa-Muñoz YH, Mejía de Gutiérrez R, Rodríguez-Páez JE (2023) Metal oxide gas sensors to study acetone detection considering their potential in the diagnosis of diabetes: a review. Molecules 28(3):1150. https://doi.org/10.3390/molecules28031150 20. Li G, Zhu X, Liu J, Li S, Liu X (2023) Metal oxide semiconductor gas sensors for lung cancer diagnosis. Chemosensors 11:251. https://doi.org/10.3390/chemosensors11040251 21. Yi N, Shen M, Erdely D, Cheng H (2020) Stretchable gas sensors for detecting biomarkers from humans and exposed environments. TrAC Trends Anal Chem 133:116085. https://doi. org/10.1016/j.trac.2020.116085 22. Lun D, Xu K (2022) Recent progress in gas sensor based on nanomaterials. Micromachines (Basel) 13(6):919. https://doi.org/10.3390/mi13060919 23. Sun YF, Liu SB, Meng FL, Liu JY, Jin Z, Kong LT, Liu JH (2012) Metal oxide nanostructures and their gas sensing properties: a review. Sensors (Basel) 12(3):2610–2631. https://doi.org/ 10.3390/s120302610 24. Cao J, Zhou J, Chen J, Wang W, Zhang Y, Liu X (2020) Effects of phase selection on gassensing performance of MoS2 and WS2 substrates. ACS Omega 5(44):28823–28830. https:// doi.org/10.1021/acsomega.0c04176 25. Xiao C, Ma Z, Sa R, Cui Z, Gao S, Du W, Sun X, Li Q-H (2022) Adsorption behavior of environmental gas molecules on pristine and defective MoSi2 N4 : possible application as highly sensitive and reusable gas sensors. ACS Omega 7(10):8706–8716. https://doi.org/10.1021/acs omega.1c06860 26. Yue Q, Shao Z, Chang S, Li J (2013) Adsorption of gas molecules on monolayer MoS2 and effect of applied electric field. Nanoscale Res Lett 8(1):425. https://doi.org/10.1186/1556276X-8-425 27. González C, Biel B, Dappe YJ (2017) Adsorption of small inorganic molecules on a defective MoS2 monolayer. Phys Chem Chem Phys 19(14):9485–9499. https://doi.org/10.1039/C7CP00 544J 28. Ai W, Kou L, Hu X, Wang Y, Krasheninnikov AV, Sun L, Shen X (2019) Enhanced sensitivity of MoSe2 monolayer for gas adsorption induced by electric field. J Phys: Condens Matter 31(44):445301. https://doi.org/10.1088/1361-648X/ab29d8 29. Sharma M, Jamdagni P, Kumar A, Ahluwalia PK (2016) Interactions of gas molecules with monolayer MoSe2 : A first principle study. AIP Conf Proc 1731(1):140045. https://doi.org/10. 1063/1.4948211 30. Lin L, Feng Z, Dong Z, Tao H, Hu C (2023) Transition metal disulfide (MoTe2 , MoSe2 , and MoS2 ) were modified to improve NO2 gas sensitivity sensing. J Ind Eng Chem 118:533–543. https://doi.org/10.1016/j.jiec.2022.11.036 31. Donarelli M, Ottaviano L (2018) 2D materials for gas sensing applications: a review on graphene oxide, MoS2 , WS2 , and phosphorene. Sensors 18:3638. https://doi.org/10.3390/s18 113638 32. Singh S, Deb J, Sarkar U, Sharma S (2020) MoSe2 crystalline nanosheets for room-temperature ammonia sensing. ACS Appl Nano Mater 3(9):9375–9384. https://doi.org/10.1021/acsanm.0c0 2011 33. Fine GF, Cavanagh LM, Afonja A, Binions R (2010) Metal oxide semiconductor gas sensors in environmental monitoring. Sensors (Basel) 10(6):5469–5502. https://doi.org/10.3390/s10060 5469 34. Tian X, Wang S, Li H, Li M, Chen T, Xiao X, Wang Y (2023) Recent advances in MoS2 -based nanomaterial sensors for room-temperature gas detection: a review. Sens Diagn 2:361–381. https://doi.org/10.1039/D2SD00208F

46

A. P. Onivefu et al.

35. Jha RK, D’Costa JV, Sakhuja N, Bhat N (2019) MoSe2 nanoflakes based chemiresistive sensors for ppb-level hydrogen sulfide gas detection. Sens Actuators, B Chem 297:126687. https://doi. org/10.1016/j.snb.2019.126687 36. Li T, Yu S, Li Q, Chi M, Li P (2021) Room temperature ethanol gas-sensing properties based on Ag-doped MoSe2 nanoflowers: experimental and DFT investigation. New J Chem 45:21423– 21428. https://doi.org/10.1039/D1NJ04318H 37. Chen X, Chen X, Han Y, Su C, Zeng M, Hu N, Su Y, Zhou Z, Wei H, Yang Z (2019) Two-dimensional MoSe2 nanosheets via liquid-phase exfoliation for high-performance room temperature NO2 gas sensors. Nanotechnology 30(44):445503. https://doi.org/10.1088/13616528/ab35ec 38. Late DJ, Doneux T, Bougouma M (2014) Single-layer MoSe2 based NH3 gas sensor. Appl Phys Lett 105(23):233103. https://doi.org/10.1063/1.4903358 39. Pan W, Zhang Y, Yu S, Liu X, Zhang D (2021) Hydrogen sulfide gas sensing properties of metal organic framework-derived α-Fe2 O3 hollow nanospheres decorated with MoSe2 nanoflowers. Sens Actuators, B Chem 344:130221. https://doi.org/10.1016/j.snb.2021.130221 40. Parangusan H, Bhadra J, Al-Qudah RA, Elhadrami EC, Al-Thani NJ (2022) Comparative study on gas-sensing properties of 2D (MoS2 , WS2 )/PANI nanocomposites-based sensor. Nanomaterials (Basel) 12(24):4423. https://doi.org/10.3390/nano12244423

Synthesis and Characterization of 2D WSe2 and Triple Cation Perovskite-Based Photoabsorbers Silvino P. Bastos, Sujan Aryal, and Anupama B. Kaul

Abstract Transition metal dichalcogenides and perovskites have been gaining attention for their impressive optoelectronic performance towards photonics and renewable energy applications. In this work, optoelectronic devices were fabricated from a mechanically exfoliated WSe2 crystal and ink-based triple cation perovskites-based photoabsorber devices placed on oxidized silicon substrates. We conducted spectroscopy studies on both devices prior to the electrical characterization. We char1 and A1 g peaks for the WSe2 and the photoluminescence acterized the Raman E 2g peak for the perovskite occurred at 763.63 nm with an optical bandgap of around 1.635 eV, calculated through optical absorption spectroscopy. Photocurrent measurements were made for both devices using a broadband light source. This study provides insights into the performance of WSe2 photodetectors and cesium-based triple cation perovskites, contributing to their potential applications in various fields, including imaging, photonics, and optical communications. Keywords 2D materials · WSe2 · Perovskite · Photodetector · Photoresponsivity · Detectivity · Photocurrent

Introduction The development of high-performance photodetectors has been a topic of interest in the field of optoelectronics. Transition metal dichalcogenides (TMDCs) are a family of inorganic materials that possess a layered, two-dimensional structure. They also exhibit properties ranging from semiconducting, metallic to superconducting, S. P. Bastos · S. Aryal · A. B. Kaul (B) Department of Electrical Engineering, University of North Texas, Denton, TX, USA e-mail: [email protected] A. B. Kaul Department of Materials Science and Engineering, University of North Texas, Denton, TX 76207, USA © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_4

47

48

S. P. Bastos et al.

and given their large surface-to-volume ratio it enables effective light-matter interactions from enhanced light absorption and efficient charge transport, leading to improved photoabsorption performance [1]. Their high carrier mobility enables fast charge transport within the material, a crucial characteristic to achieve rapid response photodetectors, ensuring quick detection of incident light [2]. At the same time, we used cesium-based triple cation perovskites, which incidentally are also exceptional light absorbers, to characterize their interactions with light. These materials exhibit quantum confinement effect as they transition toward lowered dimensionality, which also contributes to their unique optoelectronic properties [3, 4]. Comparatively, triple cation perovskites exhibit improved stability and reproducibility compared to other perovskite compositions, ensuring consistent power output, particularly for photovoltaics, over extended periods of operation [4]. In this work, we report the synthesis and characterization of a WSe2 -based photodetector and compared the response to a triple cation absorber. Along the way we conducted material characterization studies on each type of absorber using techniques such as Scanning Electron Microscopy (SEM), Raman spectroscopy, and photoluminescence spectroscopy, as well as dc transport measurements at room temperature.

Results and Discussion Tungsten Diselenide (WSe2 ) Device Fabrication and Material Characterization The WSe2 -based device studied in this work was synthesized using the mechanical exfoliation (ME) method from a WSe2 bulk crystal using non-tac blue tape. We fabricated the photoabsorber using standard electron-beam lithography, followed by physical vapor deposition (PVD) for electrode deposition on top of the underlying WSe2 crystal. The WSe2 nanomembrane was characterized using Raman spectroscopy and photoluminescence spectroscopy and finally probed for the optoelectronic measurements. The specific process for the device fabrication of the ME WSe2 membranes started from a careful cleaning of the SiO2 /Si substrate using bath sonication sequentially with acetone, methanol, isopropanol, and deionized (DI) water. The ME crystal was then stamped onto the cleaned SiO2 /Si wafer, where e-beam lithography (EBL) was used with the JEOL JSM-7001F SEM and XENOS XPG-2 EBL pattern writer. For the interconnect layout, contact traces were written to expose the spin coated layer of poly (methyl methacrylate) (950-PMMA-A4), used as the e-beam resist, underneath which the WSe2 surface. These were defined by employing a 15 keV acceleration voltage, 240 pA emission current, and adjusting the dwell period to provide a constant dosage of ~300 C/cm2 for the PMMA to be exposed. After the sample was developed in MBK/IPA 1:3 for about 30 s, physical vapor deposition (PVD) process was then

Synthesis and Characterization of 2D WSe2 and Triple Cation …

49

Fig. 1 a Raman spectroscopy of WSe2 film which was mechanically exfoliated and in (b) PL spectroscopy results are shown. The peak position obtained was at 1.61 eV

used to deposit electrodes (100 nm Au) on the WSe2 crystal surface followed by the lift-off process that left the controlled Au thin film on top of the previously designed contact traces. The fabricated device was then placed under the spectroscopy system to validate the presence of the WSe2 , despite having undergone wet processing from the semiconductor processes. The Horiba HR Evolution confocal Raman microscope was used with a 532 nm excitation laser at to capture the Raman and photoluminescence (PL) spectra of the ME WSe2 devices. The spectrometer was calibrated using a Si calibration sample with its Raman fingerprint at ~520.7 cm−1 . Raman spectroscopy is a non-destructive technique that provides information about the vibrational modes, lattice properties, and inference of the layer thickness of materials in certain cases. The Raman spectra of 2D materials exhibit several characteristic peaks that can be used to identify the layer thickness and structural properties of the materials [5]. The peak position in the PL spectrum corresponds to the energy of the emitted photons 1 around 250 cm−1 , in the excitonic process [6]. The WSe2 device exhibiting the E 2g −1 while the A1 g peak appeared at around 255 cm . The data obtained on the ME WSe2 matches the spectra known for few layers of 2D WSe2 [7, 8]. Figure 1a exhibits the Raman, and Fig. 1b shows the PL spectra of the ME WSe2 device, with a peak position occurring at around 1.55 eV for a few layers of WSe2 [7–11]. The peak position and the full width at half maximum (FWHM) linewidth of the PL peak can be used to estimate the exciton binding energy. The WSe2 sample exhibited a FWHM of 69.7 meV.

Triple Cation Perovskite Device Fabrication For our perovskite absorber, we used a cesium-based triple cation perovskite to synthesize the film which was spin coated on an oxidized silicon substrate followed by PVD for electrode deposition using a shadow mask technique. The perovskite ink was

50

S. P. Bastos et al.

made from a solution of formamidinium iodide (FAI > 98%) (1M), methylammonium bromide (MABr) (0.2M), lead (II) iodide (PbI2 , 99.99%) (1.1M), lead (II) bromide PbBr2 (0.2M), dimethylformamide (DMF), and dimethylsulfoxide (DMSO) at a 4:1 ratio. The solution then was stirred at 65 °C for 2 h. A separate CsI solution was prepared from 1.5 M of cesium iodide (CsI) in 1 ml of DMSO. Thus, 50 µL of the CsI solution was added to the FAI solution, then stirred overnight at room temperature. The ink was then spin coated on top of a SiO2 /Si wafer via the one-step antisolvent spinning method. The spinning parameters involved: 1000 rpm for 10 s; 4000 rpm for 20 s where 100 µl of chlorobenzene was dripped as an antisolvent for last 6 s. This was followed by annealing at 100 °C for 1 h turning the nucleating perovskite film black. Finally, the electrodes were deposited on top of the perovskite layer using a shadow mask in a PVD system, consisting of 10 nm of Ti and 100 nm of Au. Figure 2 exhibits the morphology of the triple cation perovskite taken from a scanning electron microscope (SEM). The film appears dense and continuous and is uniform over large areas, although the individual grains are clearly evident. We then characterized the perovskite film using PL and optical absorption spectroscopy. By analyzing the peak positions and intensities in the PL spectra of triple cation perovskites, the peak position in the PL spectrum corresponds to the energy of the emitted photons, as shown by the spectra in Fig. 3a through PL and optical absorption spectroscopy of the triple cation perovskite film where the peak occurred at 763.63 nm and Fig. 3b exhibits the Tauc-plot for determination of the optical bandgap of the triple cation perovskite film, revealing an optical bandgap E g ~ 1.63 eV. Fig. 2 Picture of the triple cation perovskite photoabsorber taken from SEM

Synthesis and Characterization of 2D WSe2 and Triple Cation …

51

Fig. 3 a PL spectroscopy and optical absorption of the triple cation perovskite device. Peak was found at 763.63 nm. b Tauc-plot for determination of the optical bandgap of the triple cation perovskite film, revealing an E g ~ 1.63 eV

Optoelectronic Analysis on WSe2 and Perovskite Devices Photodetectors by definition are devices that can absorb incident light by converting incident light energy into an electrical signal. They play a crucial role in various applications, including imaging, sensing, and communication systems [12]. The performance of photodetectors is characterized by several figures of merit, including the photocurrent, which is the difference from the current measured under illumination, ILight and the dark current IDark , as described in the Eq. (1). I ph = ILight − IDark

(1)

From the photocurrent I ph it is possible to quickly evaluate if any material is a potential candidate for a photodetector since the proportionality between electrical current and light absorption is expected. Figure 4a exhibits I Light and I dark as a function of V ds for the WSe2, and Fig. 4b displays the same analysis for the perovskite device. The plot that corresponds to light on both figures considers when both devices were exposed to 220 mW/cm2 of incident light. The I ph is shown in Fig. 4c for the WSe2 device, while the equivalent data for the perovskite device is presented in Fig. 4d, for measurements conducted at room temperature. Both photodetectors exhibited relevant increase in conductivity as a function of light exposure, indicating their photo absorption characteristics [13]. However, in this particular case the WSe2 device exhibited photocurrent values that are responsive in the negative bias regime rather than in the forward polarity. On the other hand, the perovskite device exhibited symmetric photocurrents for similar voltage biases. These results suggest our devices

52

S. P. Bastos et al.

Fig. 4 a I dark and I light curves from WSe2 device in respect of source-drain voltage. b Idark and Ilight curves from perovskite device in respect of source-drain voltage. c Photocurrent at room temperature of the WSe2 device. It exhibits around 8.2 µA for 25 V drain-source. d Photocurrent for the perovskite device, which exhibits approximately 180 nA at 25 V drain-source

with both photoabsorbers are interesting candidates for further analysis in future studies.

Conclusions In summary, we have validated the light absorbing features in an inorganic TMDC semiconductor, specifically a selenide-based two-dimensional material, and compared the results with a hybrid organo-halide perovskite which also exhibited a photoresponse. This preliminary data will help us build more complex devices with the two types of photoabsorbers for future applications in imaging and sensing. Acknowledgements We thank the Office of Naval Research (grant number ONR N00014-20-12597 and grant number ONR N00014-19-1-2142) and the Air Force Office of Scientific Research (grant number FA9550-21-1-0404) that enabled us to pursue this work.

Synthesis and Characterization of 2D WSe2 and Triple Cation …

53

References 1. Omkaram I, Hong YK, Kim S (2018) Transition metal dichalcogenide photodetectors. Twodimension Mater Photodetector. https://doi.org/10.5772/intechopen.72295 2. Askari MB et al (2023) Transition-metal dichalcogenides in electrochemical batteries and solar cells. Micromachines (Basel) 14(3). https://doi.org/10.3390/mi14030691 3. Eftekhari A (2017) Tungsten dichalcogenides (WS2 , WSe2 , and WTe2 ): materials chemistry and applications. J Mater Chem A Mater 5(35):18299–18325. https://doi.org/10.1039/c7ta04 268j 4. Saliba M et al (2016) Cesium-containing triple cation perovskite solar cells: improved stability, reproducibility and high efficiency. Energy Environ Sci 9(6):1989–1997. https://doi.org/10. 1039/c5ee03874j 5. McCreary A et al (2016) Distinct photoluminescence and Raman spectroscopy signatures for identifying highly crystalline WS2 monolayers produced by different growth methods. J Mater Res 31(7):931–944. https://doi.org/10.1557/jmr.2016.47 6. Konar R et al (2020) Scalable synthesis of few-layered 2D Tungsten diselenide (2H-WSe2 ) nanosheets directly grown on Tungsten (W) foil using ambient-pressure chemical vapor deposition for reversible Li-Ion storage. ACS Omega 5(31):19409–19421. https://doi.org/10.1021/ acsomega.0c01155 7. Terrones H et al (2014) New first order Raman-active modes in few layered transition metal dichalcogenides. Sci Rep 4(February). https://doi.org/10.1038/srep04215 8. Jayanand K, Kaul AB (2022) Plexcitonic interactions in spherical and bi-pyramidical Au nanoparticles with monolayer WSe2 . Appl Phys Lett 121(20). https://doi.org/10.1063/5.012 0636 9. Zhang S et al (2018) Controllable, wide-ranging n-Doping and p-Doping of Monolayer Group 6 transition-metal disulfides and diselenides. Adv Mater 30(36). https://doi.org/10.1002/adma. 201802991 10. De Luca M et al (2020) New insights in the lattice dynamics of monolayers, bilayers, and trilayers of WSe2 and unambiguous determination of few-layer-flakes’ thickness. 2d Mater 7(2). https://doi.org/10.1088/2053-1583/ab5dec 11. Hu C et al (2017) Synergistic effect of hybrid PbS quantum dots/2D-WSe2 toward high performance and broadband phototransistors. Adv Funct Mater 27(2). https://doi.org/10.1002/adfm. 201603605 12. Ren H, De Chen J, Li YQ, Tang JX (2021) Recent progress in organic photodetectors and their applications. Adv Sci 8(1):1–23. https://doi.org/10.1002/advs.202002418 13. Zou Y et al (2022) High-temperature flexible WSe2 photodetectors with ultrahigh photoresponsivity. Nat Commun 13(1). https://doi.org/10.1038/s41467-022-32062-0

Synthesis and Characterization of Selenides and Hybrid Halide Perovskites for Nanodevices Anupama B. Kaul

Abstract Semiconducting two-dimensional (2D) crystallites offer a rich playground to tune electronic and optoelectronic properties through synthesis routes. Here we discuss the synthesis of two such classes of 2D crystallites. The first is based on tungsten diselenide (WSe2 ) which is synthesized using a chemical vapor deposition route through salt-assisted deposition. Besides these binary compositions of 2D layered materials, more complex material systems also exist that exhibit a form of van der Waals bonding in low-dimensionality hybrid organo-halides at their headgroups. Through this work, we delineate the synthesis and optical characterization of WSe2 and 2D perovskites, where the latter has a composition specifically of ((CH3 (CH2 )3 NH3 )2 (CH3 NH3 )3 Pb4 I13 ). Both such material systems are finding use as photoabsorbers in sensors and solar cells. Keywords Tungsten diselenide · Molybdenum disulfide · Raman spectroscopy · Photoluminescence spectroscopy

Introduction The family of two-dimensional (2D) [1, 2] materials comprising of graphene and transition metal dichalcogenides (TMDCs) has gained phenomenal interest in electronics, optoelectronic devices, and sensors. Among the various TMDCs, WSe2 is a promising material with a band gap in the bulk of ~1.3 eV. When the bulk crystals are thinned down to monolayers through various exfoliation means, the bandgap rises to ~1.6 eV from quantum confinement effects. The intriguing properties of WSe2 have garnered its potential consideration towards next generation field-effect transistors (FETs), photodetectors, and flexible optoelectronics. Unlike WSe2 where the optical transitions are direct only in the monolayer configuration, A. B. Kaul (B) Department of Electrical Engineering, Department of Materials Science and Engineering, University of North Texas, Denton, TX 76207, USA e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_5

54

Synthesis and Characterization of Selenides and Hybrid Halide …

55

more complex material systems exist within the van der Waals family, such as the low-dimensionality 2D organo-halide perovskites, which are a subset of the broader class of three-dimensional (3D) perovskites [3, 4], exhibit direct band gaps even in bulk crystals. In this work, we discuss the synthesis and optical properties of these two classes of 2D layered materials which have potential applications in sensors and other types of nanodevices, where their strong light-matter interactions are at the heart of the device functionality.

Results and Discussion Material Preparation The WSe2 nanosheets employed in this work were nucleated on ~270 nm SiO2 /Si substrates using the halide-assisted (HA) low-pressure-(LP) chemical vapor deposition (CVD) route [5, 6]. The incorporation of a halide in the form of a salt is known to aid in the reduction of the WO2.9 precursor to lower synthesis temperatures below 1000 °C. Prior to HA-LPCD growth, the 75 mm SiO2 /Si substrate was diced to ~25 mm squares and sonicated for 15 min in acetone, methanol, isopropanol, and deionized (DI) water. The SiO2 /Si substrates were then dehydrated on a hot plate at 200 °C for 30 min which was followed with a UV ozone treatment at room temperature for 15 min. Following this protocol, the precursors were then weighed in the following quantities: 22 mg of WO2.9 (Alfa Aesar, 99.99% purity), 4 mg of anhydrous NaCl (Sigma-Aldrich 99.999% purity), and 33 mg of Se (Alfa Aesar, 99.999% purity). On the other hand for the 2D perovskites, specifically (CH3 (CH2 )3 NH3 )2 (CH3 NH3 )n-1 Pbn I3n+1 (n = 2, 3, and 4), we used the following precursors: PbO (part #:402,982), HI (part #:210,021), H3 PO2 (part #:214,906), CH3 NH3 Cl (part #:8,060,200,250), and n-CH3 (CH2 )3 NH2 (part #:471,305), which were all purchased from Sigma-Aldrich. The PbO powder was dissolved in a mixture of 57% w/w aqueous HI solution and 50% aqueous H3 PO2 by heating and subsequent boiling under constant magnetic stirring for about 5 min, that led to the formation of a bright yellow solution. Subsequent addition of solid CH3 NH3 I to the hot yellow solution initially caused the precipitation of a black powder that rapidly re-dissolved under stirring; this yielded a clear bright-yellow solution. Additionally, the n-CH3 (CH2 )3 NH3 I was then added dropwise under vigorous stirring over a period of 5 min; this did not result in any visible changes to the solution. We then stopped stirring and left the solution to cool to room temperature during which time deep red, rectangular-shaped platelets started to crystallize. The precipitation was deemed complete after ∼2 h. The crystals then were isolated by suction filtration and thoroughly dried under reduced pressure.

56

A. B. Kaul

Characterization of Inorganic TMDCs: WSe2 The tungsten trioxide precursor, WO2.9 and the halide, NaCl, were thoroughly mixed based on the mass ratio provided, before being transferred to the Al2 O3 crucibles. The precursors in the Al2 O3 crucibles were then placed in a quartz tube and arranged spatially as illustrated in Fig. 1a-Left. To ensure reactivity of the gas phase Se precursors, the SiO2 /Si substrates were placed facing down. The WO2.9 /NaCl mixture was then placed about10 mm away from the edge of the Al2 O3 crucible, as shown in the bottom-inset. The entire assembly was placed within the center of the heating zone where the growth temperature was set to 900 °C, as shown in Fig. 1a-Left. The flow rates of the carrier and reducing gasses, Ar and H2 , respectively, were 120 and 30 sccm, and the process pressure was adjusted to 6 Torr using a pressure control valve hooked to the chamber. Using this single zone furnace in a semi-multi-zone configuration, the spatially-controlled thermal gradient profile allowed us to place the Se boat at ~270 °C verified using a thermocouple to calibrate the thermal profile. This temperature happened to arise at a position of 15.5 cm upstream from the centre of the heating zone. Figure 1a-Right illustrates the temperature–time profile segmented into Regions I–VII, where the temperature was taken at the nominal centre of the heating zone. Region I corresponds to a ramping stage from 25 to 600 °C at a rate of 10 °C/min. On the other hand, Region II represents the sublimation of Se conducted at a reduced ramp rate of 5 °C/min. The growth zone, i.e. Region III at ~900 °C, signifies the onset of the high-density nucleation and growth of WSe2 crystallites, whereas in Region IV, after the predominant growth step, the thermal ramp down from 900 °C to 700 °C was started at a ramp rate of ~10 °C/min. Region V corresponds to the annealing isotherm at 700 °C for 60 min. Here, the Ar and H2 carrier gases at the aforementioned flow rates were kept constant throughout Regions I and V. We have connected the presence of H2 in Region V to its role in etching and thinning the multilayer WSe2 crystallites, as well as preventing redeposition of oxide precursors on the substrate. A controlled ramp down was then conducted in Region VI from 700 to 400 °C at 10 °C/min, in pure Ar at a flow rate of 180 sccm without the presence of H2 . At the last step, in Region VII, a rapid cooling is noted as the furnace cover was lifted. Raman and PL spectroscopy were performed using a Raman laser excitation wavelength of 532 nm on three spatially uniform Sections designated as monolayer or single layer (1L), multi-layer (M)L, and bulk WSe2 . For a fixed laser power (P = 1 and A1g 3.35 mW) and room temperature (T = 298 K), the two Raman-active E 2g −1 modes were found at ~247 and ~256 cm , (Fig. 2a) for 1L WSe2 . As the thickness of 1 and A1g modes shifted in opposite frequency directions. the WSe2 increased, the E 2g 1 Specifically, the E 2g mode underwent a red-shift, while the A1g mode blue-shifted as thickness increased (Fig. 2a). The blue-shift in the A1g mode as thickness increased is explained on the basis of the interlayer interaction of the Se atoms in the neighboring planes. From the nearest-neighbor interaction model it is expected, to first-order, that as film thickness increases, a greater restoring force from overlying layers will be present, where the equilibrium average lattice vibrational amplitude is reduced.

Synthesis and Characterization of Selenides and Hybrid Halide …

57

Fig. 1 a-Left. A schematic representation of our HA-LPCVD growth process to synthesize 1L WSe2 , where the temperature gradient in the furnace is shown from the center of the heating zone for the single zone furnace which is used in a quasi multi-zone fashion. The Se precursor is placed on an alumina (Al2 O3 ) crucible positioned 15.5 cm away from the center of the heating zone, where the temperature was measured to be ~270 °C using a thermocouple. The WO2.9 /NaCl mixture was placed in another Al2 O3 crucible shown in magnified view at the bottom inset and placed at the center of the heating zone with the SiO2 /Si substrates facing downward. b-Right. The temperature profile at the centre of the heating zone showing the various growth regimes in Regions I–VII, where the annealing isotherm in Region V, results in the conversion of multilayer WSe2 into 1L WSe2

1 and A modes for mechanically exfoliated Fig. 2 a The variation of the Raman spectra for the E2g 1g 1 WSe2 for 1L, ML, and bulk. The E2g mode exhibits a red-shift /ω ~ 0.47 cm-1 while the A1g mode reveals a blue-shift /ω ~ 1.4 cm-1 with increasing layer number. b The PL spectra for 1L, ML, and bulk WSe2 nanomembranes, where the excitonic A-peak represents direct-gap optical transitions, while the I-peak is characteristic of indirect band gap optical transitions

Thus, the frequencies of the modes here in the out-of-plane direction will blue-shift as thickness increases. 1 The red-shift of the E 2g mode as thickness increases is attributed to dielectric screening effects of the long-range Coulomb interaction, where the effective charges resulting from the relative displacement between the W and Se atoms is reduced. This causes the coulombic force to decrease, and hence the energy also decreases. We note from Fig. 1a that the blue-shift /ω(A1g )~ 1.4 cm−1 is more than 3 times 1 )~ 0.47 cm−1 when the sample thickness larger compared to the red-shift /ω(E 2g

58

A. B. Kaul

increased from 1L to bulk. Another important observation from Fig. 1a is the increase in intensity of the A1g peak as the number of layers increases, which is likely due to positive reinforcement arising from interference effects for the out-of-plane modes. It was found from the data in Fig. 1a that the /ω was 7.5, 8.4, and 9.1 cm−1 for 1L, ML, and bulk WSe2 , respectively. Thus, the Raman peaks exhibit a larger separation as thickness increases. Monolayer WSe2 undergoes a transition from direct-to-indirect bandgap (E g ) as the number of layers increases. We corroborate this here as well, with our PL analysis of WSe2 for 1L, ML, and bulk samples, where Fig. 2b depicts a single excitonic Apeak at 1.61 eV for 1L. As the number of layers increases, an indirect peak I emerges which is clearly seen from the PL spectra of the ML and bulk samples. In contrast, the I peak is absent in the 1L PL spectra, demonstrating that E g undergoes an indirectto-direct evolution for the ML to 1L case, respectively. It should also be noted that the I peak undergoes a red-shift from the ML to the bulk and consequently E g was found to be 1.42 and 1.37 eV, respectively, for the two cases.

Characterization of Direct Bandgap 2D Perovskites While 2D WSe2 exhibits strong light-matter interactions, its binary composition is quite unlike some of the more complex 2D layered compounds based on perovskites, which are a family of layered compounds with tunable semiconducting properties. Reducing dimensionality of the 3D perovskites to the 2D perovskites, including in the 2D Ruddlesden-Popper phase, is gaining momentum, particularly for their use in solar cells [7–10]. However, the power conversion efficiencies (PCEs) of the 2D perovskites are typically lower than the 3D perovskites. The 2D perovskites provide significant relief from the restricted compositional variety present within the 3D perovskites. Single (or many) inorganic sheets are sandwiched between organic spacers which are held together by Coulombic forces. The standard formula for 2D perovskites can be represented as (A' )m (A)n−1 Bn X 3n+1 , where A' is a bulky organic cation (such as an aliphatic or aromatic alkylammonium) that functions as a spacer between the inorganic sheets, and n is the number of inorganic layers held together. The layered structure reduces the Goldschmidt tolerance factor’s limitations on cation size and unlike 3D perovskites, allows bulky A' cations to be accommodated via van der Waals interactions between the inorganic sheets. Here, we have examined the optoelectronic properties of 2D Ruddlesden-Popper crystals, specifically ((CH3 (CH2 )3 NH3 )2 (CH3 NH3 )3 Pb4 I13 ). After the synthesis, the powder was examined using atomic force microscopy (AFM), x-ray diffraction (XRD), and optical absorption spectroscopy. The Bruker Multimode 8 system for AFM analysis showed that the surface morphology for n = 2 (Fig. 3a) was distinct from the n = 3 and 4 perovskite films (Fig. 3b–c). The root mean square (RMS) surface roughness of ~5.60 nm was found to be highest for the n = 2 sample, while the n = 3 and 4 perovskite films were smoother with RMS roughness of ~3.04 and ~1.80 nm, respectively. The n = 3 and 4 perovskite films appeared dense, whereas the

Synthesis and Characterization of Selenides and Hybrid Halide …

59

n = 2 exhibited pockets of agglomerated grains with voids and the largest topography height profile. Figure 3d shows the XRD spectra of 2D perovskite films with n = 2, 3, and 4, where the measurements were carried out using the Rigaku Ultima III diffractometer. The separation of the inorganic layers results in an increase in the lattice constants as the incorporation of the BA bilayer requires a gap of ~15.6 Å between the inorganic layers. The ordered stacking of the Pb4 I13 layers leads to a large repeating distance of ~25.11 Å and for the simplest case of n = 1 this repeat distance is ~6.4 Å, for the inorganic moiety within the unit cell along the stacking direction. These changes in the unit cell can be monitored by XRD, which characteristically reveals unique reflections for the n = 2, 3, and 4 perovskite films. The XRD spectra for the 2D perovskite film displays the typical peaks, which occur at 2θ = 14.08°, 14.09°,

Fig. 3 The AFM surface topology maps of spin-coated 2D perovskite films on SiO2 /Si substrates, where RMS roughness was determined to be ~5.60, 3.04, and 1.80 nm for a n = 2, b n = 3, and c n = 4, respectively. d The XRD spectra of spin-coated 2D perovskite films for n = 2, 3, and 4 formulations on SiO2 /Si substrates. The 2θ peaks at 14.08°, 14.09°, and 14.20° are assigned to the (BA)2 (MA)n−1 Pbn I3n+1 (111) crystallographic planes, respectively. The top-right inset with 2θ peaks at 28.30°, 28.35°, and 28.39° are assigned to the (202) crystallographic planes for n = 2, 3, and 4 perovskite films, respectively. e The UV-vis optical absorption spectra for spin-coated 2D perovskite films for n = 2, 3, and 4 on glass substrates at room T. The right inset displays the synthesized perovskite powders for n = 2, 3, and 4, where the reddish-brown color of the n = 2 formulation is attributed to its higher E g , where the higher energy photons in the blue-end of visible spectrum are absorbed and the red-end is reflected. The optical absorption spectra show the peak light absorption wavelengths occurring at λ ~ 568.3 nm (E g ~ 2.18 eV), 601.4 nm (E g ~ 2.08 eV), and 609.4 nm (E g ~ 2.03 eV) corresponding to n = 2, 3, and 4 perovskite compositions, respectively

60

A. B. Kaul

and 14.20° assigned to the (CH3 (CH2 )3 NH3 )2 (CH3 NH3 )n-1 Pbn I3n+1 (111) crystallographic planes, as shown in Fig. 2d. The inset in Fig. 2d validates the 2θ peaks at ~28.30°, 28.35°, and 28.39° are assigned to the (202) crystallographic planes for n = 2, 3, and 4 perovskite films, respectively. For the n = 2 perovskite film, the 2θ peak at 27.23° assigned to the (0k0) reflection is prominent and shifted to the left when compared to n = 3 and 4 cases, while the (111) and (202) reflections for the three formulations reveal the vertical growth morphology of the 2D perovskite with respect to the substrate plane. The UV–vis optical absorption spectra of 2D perovskite films for n = 2, 3, and 4 layers are shown in Fig. 3e, where measurements were conducted with the CARY 5000 spectrophotometer. As the number of layers increases in the crystal structure, the optical E g decreases, as is evident from the red-shift of the absorption peak, where λmax ~ 568.3, 601.4, 609.4 nm are assigned to the n = 2, 3, and 4 crystal structures, respectively. The direct optical E g increases as n decreases from ~2.03 eV (for n = 4) to 2.18 eV (for n = 2) due to quantum confinement effects from the dimensional reduction of the perovskite chromophores. However, in contrast to conventional 2D inorganic semiconducting transition metal dichalcogenides, such as WSe2 or MoS2 that show a direct E g only for monolayers, the 2D perovskites remarkably point toward a direct E g in all compound formulations. The right-most inset in Fig. 3e exhibits the optical images of the powders for the n = 2, 3, and 4 compositions, with the reddish color of the n = 2 formulation consistent with its higher E g , where the blue component of the spectrum is absorbed. Acknowledgements We thank the Office of Naval Research (grant number ONR N00014-20-12597 and grant number ONR N00014-19-1-2142) and the Air Force Office of Scientific Research (grant number FA9550-21-1-0404) that enabled us to pursue this work.

References 1. Novoselov KS (2005) Proc Natl Acad Sci USA 102:10451 2. Tao L, Cinquanta E, Chiappe D, Grazianetti C, Fanciulli M, Dubey M, Molle A, Akinwande D (2015) Nat Nanotechnol 10:227–231 3. Kim JY, Lee J-W, Jung HS, Shin H, Park N-G (2020) High-efficiency Perovskite solar cells. Chem Rev 120(15):7867–7918 4. Green M, Dunlop E, Hohl-Ebinger J, Yoshita M, Kopidakis N, Hao X (2021) Solar cell efficiency tables (version 57). Prog photovoltaics Res Appl 29(1):3–15 5. Wu W, Morales-Acosta MD, Wang Y, Pettes MT (2019) Nano Lett 19:1527–1533 6. Bandyopadhyay AS, Biswas C, Kaul AB (2020) Light-matter interactions in two dimensional layered WSe2 for gauging evolution of phonon dynamics. Belstein J. Nanotechnol. 11:782–797 7. Kojima A, Teshima K, Miyasaka, T, Shirai Y (2006) Novel photoelectrochemical cell with mesoscopic electrodes sensitized by lead-halide compounds. J Electrochem Soc 397 8. Stranks SD, Snaith HJ (2015) Metal-halide perovskites for photovoltaic and light-emitting devices. Nat Nanotechnol 10(5):391 9. Liu J, Xue Y, Wang Z et al (2016) Two-dimensional CH3 NH3 PbI3 perovskite: synthesis and optoelectronic application. ACS Nano 10(3):3536–3542

Synthesis and Characterization of Selenides and Hybrid Halide …

61

10. Min M, Hossain RF, Adhikari N, Kaul AB (2020) Inkjet printed organo-halide 2D layered perovskites for high-speed photodetectors on flexible polyimide substrates. ACS Appl Mater Interfaces 12:10809

Two-Dimensional Solution-Processed Tungsten Diselenide’s Response to Nitrogen Gas Flow Ashique Zaman, Thomas Mather, and Anupama B. Kaul

Abstract Currently, there are limited reports on the use of two-dimensional WSe2 in gas sensors. In this work, we fabricated a chemically exfoliated WSe2 device, contacted with gold (Au) electrodes where a response to incoming gas flow, specifically Nitrogen (N2 ) is evident. The films were formed using solution processing and electrically contacted in a two-terminal configuration. The structural properties of the films were examined using various microscopy and spectroscopy tools such as Raman spectroscopy and optical microscopy. This allowed us to validate the morphology and chemical fingerprints of the films and correlate this to our electronic transport data with N2 as the incoming gas. This work is a stepping-stone towards further analysis of WSe2 as a gas sensing media for low-power and miniaturized sensors using additive manufacturing approaches. Keywords Response to pressure · Inkjet printing · Chemical exfoliation · Tungsten diselenide

Introduction Gas sensors play a vital role in endless applications across diverse fields, including environmental monitoring, industrial safety, healthcare, to name a few. In environmental contexts, gas sensors contribute to assessing and managing air quality, monitoring pollutants, and ensuring compliance with emission standards, thereby safeguarding public health and the environment [1, 2]. Within the commercial sector, these sensors are essential for process control, detecting hazardous gas leaks, and ensuring workplace safety [3, 4]. In healthcare, gas sensors are instrumental in A. Zaman · A. B. Kaul (B) Department of Materials Science and Engineering, University of North Texas, Denton, TX 76203, USA e-mail: [email protected] T. Mather · A. B. Kaul Department of Electrical Engineering, University of North Texas, Denton, TX 76203, USA © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_6

62

Two-Dimensional Solution-Processed Tungsten Diselenide’s Response …

63

diagnosing diseases through breath analysis and maintaining safe anaesthesia levels during surgical operations [5, 6]. Besides environmental emissions, contributing to public safety and health [7, 8], their significance extends to agriculture, automotive, space exploration, and energy production [9]. In each of these domains, gas sensors serve as indispensable tools for real-time gas detection, monitoring, and control. Conventional metal oxide sensors have low selectivity and high operating temperature requirements [10]. For polymeric materials, they generally tend to be extremely sensitive to moisture and degrade rapidly [11]. On the other hand, recent activity with two-dimensional (2D) layered materials shows their immense prospects in a wide variety of fields, including in the area of sensors. Their unique structural attributes make them interesting candidates towards gas sensing applications given their high surface area-to-volume ratio, availability of active sites, ease of surface functionalization, and simplicity of integration into 3D device designs. Tungsten diselenide (WSe2 ), a prominent 2D material, boasts unique features making it an attractive choice for sensor applications. Its layered atomic structure, akin to other 2D materials, serves as a versatile platform for various electronic devices [12]. Notably, WSe2 exhibits a direct bandgap property when pushed to the limit of monolayers, making it proficient in light emission and detection, and rendering it suitable for photodetectors and photovoltaic devices [12]. Its chemical stability, substantial surface area due to atomic thinness, and compatibility with traditional semiconductor processes further bolsters its promise in sensor technologies [13]. These attributes, coupled with its adaptability to flexible and hybrid electronics, make WSe2 a compelling material for advanced sensor applications [14]. The mechanisms for gas sensing include detectable changes in electrical conductance where sensors have demonstrated exceptional sensitivity and selectivity towards gases such as N2 , CO2 , NO2 , NH3 , and H2 [15]. The stability and tuneable bandgap adjusted through layer manipulation enhances the versatility of WSe2 in crafting sensors for specific gas detection requirements [12]. Additionally, WSe2 is compatible with microfabrication processes which facilitates its seamless integration into practical devices. In this study, we have employed electrical transport measurements to assess the current levels in solution processed inkjet printed WSe2 . Bulk powder was chemically exfoliated under controlled conditions. Upon completion of the device fabrication steps, gas flow was supplied from the inlet of a vacuum chamber and the electrical conductance was then measured. Raman spectroscopy and optical microscopy measurements were used to analyze the WSe2 based inkjet printed 2D film contacted on either end with metal electrodes.

64

A. Zaman et al.

Results and Discussion Process to Formulate Inks and Film Characterization The WSe2 ink was formulated by dispersing 21 ml of cyclohexanone in 9 ml of terpineol with the help of a micropipette to which ethyl cellulose (EC) and WSe2 powder was then added in a vial. The chemical exfoliation of the solution was done by using two approaches, bath sonication (Fig. 1a) and horn-tip sonication (Fig. 1b). For bath sonication, the solution was sonicated overnight under slightly elevated conditions above room temperature, and then WSe2 powder was added to the solution and again bath sonicated overnight. After that, some of the solution, and more WSe2 was added and then horn-tip sonication was used to ensure proper chemical exfoliation of the solution, and a representative image of the final solution is shown in Fig. 1c. To remove bulk and unexfoliated layers, the solution was centrifuged for 10 min at 1000 rpm. After preparing the solution, we then proceed to characterize the material properties of the ink-jet printed films which were cast on oxidized silicon substrates. First, shown in Fig. 2 below is the Raman spectra of a region on the printed film where the A1g peak resides at ~247.19 cm−1 and the E2g peak is found at ~241.78 cm−1 . In comparison, we also conducted similar analysis on mechanically exfoliated WSe2 , where the Raman spectra is shown in Fig. 3 where the respective A1g and E2g peaks were found at ~255.45 and ~246.46 cm−1 . Given the full-width-half-maximum which is more narrowly defined in the mechanically exfoliated WSe2 , we infer the presence of defects in the WSe2 as a result of the chemical exfoliation process.

Fig. 1 a Bath sonication set-up and b horn-tip sonication. c The solution processed WSe2 in a typical conical tube

Two-Dimensional Solution-Processed Tungsten Diselenide’s Response …

65

Fig. 2 Raman spectra of chemically exfoliated bulk WSe2

Fig. 3 Raman spectra of mechanically exfoliated WSe2

Device Fabrication The devices were fabricated using inkjet printing, where the printer cartridge was filled with the chemically exfoliated solution. Inkjet printing was done on the Si/SiO2

66

A. Zaman et al.

Fig. 4 a Printed WSe2 pattern on the gold electrode, b the WSe2 device on LCC, c optical microscopic image in 5x Fig. 5 Optical microscopic image of WSe2 device in 50x in Horiba System

substrate with pre-patterned metal electrodes which were 3 mm apart from each other. The drop spacing was set at 45 µm, and inkjet printing was done over the surface of the electrodes by using 40 passes and subsequently annealed. After annealing, the device was mounted on a leadless chip carrier (LCC) using double sided adhesive carbon dots, and connected electrically with the LCC via wire bonding, as shown in Fig. 4. Shown in Fig. 5 is the optical microscopy image of the film, revealing its continuous microstructure.

Device Measurements The WSe2 device with LCC was inserted inside the sensing chamber, as shown in Fig. 6, and then the chamber lid was closed with a Cu-gasket to reach the base pressure with the aid of a turbo pump backed with a mechanical roughing pump.

Two-Dimensional Solution-Processed Tungsten Diselenide’s Response …

67

Fig. 6 a WSe2 device mounted on the mechanical support connected with a socket. b WSe2 device inside the sensing chamber

The flow rate of N2 gas was controlled by mass flow controllers (MFCs) where the maximal flow could reach up to 200 sccm. The sensing chamber was pumped down until it reached a pressure of ~1.6 × 10–5 Torr. The pump was then turned-off and N2 gas was flowed into the chamber at 200 sccm to expose the device to the incoming gas. As shown by the data in Fig. 7a, the current in vacuum was higher than at ambient. In Fig. 7b, we see there was a gradual decrease of conductivity with time, due to increasing pressure inside the gas chamber arising from the presence of N2 , which indicates an initial response of the device to the flow of N2 gas.

Fig. 7 a is the I versus V characteristic curve of the WSe2 device in a vacuum and ambient pressure, and b is the change of conductivity of current with respect to the increase in pressure over a certain period of time

68

A. Zaman et al.

Conclusion We have demonstrated the simple and scalable technique for fabricating gas sensing devices using inkjet printed 2D materials with a primary focus on WSe2 . Upon flowing N2 gas into the chamber, we noticed an increase in the resistance of the device in conjunction with the increasing pressure caused by the flowing gas. These preliminary findings suggest that further tests on inkjet printed WSe2 may reveal its promise in gas sensing applications, including on flexible substrates. Acknowledgements We thank the Office of Naval Research (grant number ONR N00014-20-12597 and grant number ONR N00014-19-1-2142) that enabled us to pursue this work.

References 1. Vyas A, Kothari DP, Pathak N (2014) Wireless gas leakage detection system and methodology. In: 2014 international conference on advanced robotics and intelligent systems (ARIS). IEEE, pp 1–6 2. Guo X, Zhang Z, Zhang L, Jiang B, Li X, Guan X (2019) An intelligent gas leakage detection device for environmental monitoring. In: 2019 9th international conference on information science and technology (ICIST). IEEE, pp 19–23 3. Kumar R, Kim JS, Bansal V, Bhatia R (2017) Gas leak detection by wireless sensor networks and RF communication. Procedia Comput Sci 132:553–559 4. Veltzé S, Martinelli M, Genova V, Cella UM (2018) A Zigbee wireless gas sensor network for indoor air quality monitoring applications. IEEE Sens J 18(23):9719–9726 5. Dweik RA, Amann A (2007) Exhaled breath analysis: the new frontier in medical testing. J Breath Res 1(1):014001 6. Amann A, Corradi M, Mazzone P (2014) A critical review of breath analysis techniques in clinical diagnostics. Trends Anal Chem 61:2–19 7. Zhang S, Xu K, Palchik O et al (2009) A wearable and wireless gas sensor array for real-time monitoring of human gaseous bio marker. Biomed Microdevices 11:1175–1187 8. Wang Z, Ballerini DR, Gadgil AJ (2008) Development of a low-cost particulate matter monitor. J Air Waste Manag Assoc 58(12):1479–1486 9. Lemmon M, Koehler J, Johnson R (2007) Measurement of the thermodynamic properties of single-phase organic compounds. J Phys Chem Ref Data 36(2):1287–1300 10. Rajkumar K, Kumar RR (2019) Fundamentals and sensing applications of 2D materials. Woodhead Publishing, pp 205–258 11. Liu X, Cheng S, Liu H, Hu S, Zhang D, Ning H (2012) A survey on gas sensing technology. Sensors 12(7):9635–9665 12. Wang QH, Kalantar-Zadeh K, Kis A, Coleman JN, Strano MS (2012) Electronics and optoelectronics of two-dimensional transition metal dichalcogenides. Nat Nanotechnol 7(11):699–712 13. Wilson NR, Nguyen PV, Seyler KL, Rivera P, Marsden AJ, Laker ZP, … Cobden DH (2013) Determination of band offsets, hybridization, and exciton binding in 2D semiconductor heterostructures. Nano Lett 13(2):543–548 14. Gong Y, Lin J, Wang X, Shi G, Lei S, Lin Z, … Pantelides ST (2014) Vertical and in-plane heterostructures from WS2 /MoS2 monolayers. Nat Mater 13(12):1135–1142 15. Choudhary N, Choi W, Choudhary A, Harzandi AM, Lee SH, Hong SS, Lee YH (2019) Twodimensional materials for gas sensing applications: a review. ACS Nano 13(11):11736–11756

Part II

Accelerated Testing to Understand the Long Term Performance of High Temperature Materials

Exploring the Service Life Extremes of 716 in Highly Corrosive Environments Tim Dunne, Lei Zhao, Jiaxiang Ren, Peng Cheng, Yu Liu, and Huailiang Liu

Abstract 716 (UNS N07716) is a commonly selected alloy for multi-decade oilfield applications with established environmental guidance from NACE MR-0175. Based on thermodynamic calculations, the historical limit determined using low-pressure rated equipment could be extended by 3x by accounting for non-ideal H2 S phase behavior effects. Slow strain rate testing at 204 °C with increasing H2 S concentration determined a potential traditional ideal 800 psi H2 S limit and non-ideal 1100 psi H2 S limit. TM0177 c-ring testing was conducted at these concentrations with 1200–1360 psi CO2 , 20–25% NaCl, with elemental sulfur at pressures of 2300 and 15,000 psi total pressure for 90 days. One 15,000 psi sample of nine unexpectedly cracked in a lower stress area outside of the highest stress apex area. Further microstructural analysis was conducted. The highest ever reported H2 S 716 testing simultaneously proved multi-decade use at least 200 psi H2 S over the standard and the new revision allowing elemental sulfur is problematic. Keywords UNS N07716 · 716 · NACE MR0175 · Elemental sulfur · HPHT environmental testing · Stress Corrosion cracking

Introduction Global energy needs will increase 50% by 2050 as emerging markets collectively boost consumption. Even in a 2050 net zero carbon scenario, hydrocarbons will be significant energy resources, still supplying around 50% of world energy [1]. Giant oil fields, defined as those fields with >500 million recoverable barrels, are of immense importance to global energy supplies. The world’s 20 largest fields produce 25% of all oil. Despite recent discoveries of giant oilfields, the rate of discovery peaked in the 1970s [2]. Unconventional resources have increasingly been exploited in recent T. Dunne (B) · L. Zhao · J. Ren · P. Cheng · Y. Liu · H. Liu CNPC USA Corporation, 2901 Wilcrest Dr, Houston, TX 77042, USA e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_7

71

72

T. Dunne et al.

decades to meet levels of demand conventional hydrocarbon reservoirs are increasingly unable to do. Global demand have pushed hydrocarbon exploration and extraction towards high pressure and high temperature (HPHT) reservoirs. Improvements in technology and technique have pushed the envelope upwards to temperatures exceeding 350 °F (175 °C) and pressures exceeding 15,000 psi (105 MPa) [3]. Many of these HPHT reservoirs will co-produce significant amounts of chlorides, H2 S, and CO2 in a high chloride environment [4, 5]. High temperatures in combination with high H2 S and CO2 concentration will accelerate metallic corrosion, necessitating materials selection with manageable corrosion rates [6]. Chinese National Petroleum Company (CNPC) forecasts vigorous Chinese oil demand up to a peak in 2030. Boosting energy supply is being accomplished by developing challenging resources like that of the Tarim or Sichuan Basin, some of the largest oil and gas bearing areas in China [7]. Wells in the Tarim Basin have pressures exceeding 15,000 psi, temperatures exceeding 400 °F (204°), and H2 S partial pressures surpassing 200 psi (1.4 MPa) [8]. The general material selection philosophy is to select the least expensive option that exceeds the minimum mechanical properties and has a low probability of corrosion related failure for the lifetime of the well [9, 10]. Such extreme environmental combinations require the use of high-cost nickel-based corrosion resistant alloys (CRA). These alloys are variably sensitive to high chloride concentrations, elemental sulfur, and high H2 S at high temperatures. A degree of conservatism is applied to material selection to minimize risk, ensure reliability, and safeguard personnel. Coincidentally, giant oil field discoveries peaked with the introduction of NACE MR0175 in 1975, which was published to provide material selection guidelines in H2 S containing environments. The document, now known as NACE MR0175/ISO 15156, contains industry accepted safe use limits for specific alloys based on testing and experience with combinations of CO2 , H2 S, chlorides, temperature, hardness, and yield strength [11]. Unsurprisingly, there is a threshold between the recommended upper limit and the probabilistic failure limit. It is of economic advantage to explore beyond the published limits of an alloy to compress the differential between recommended and actual failure. Savings of $1MM to $4MM per 10,000 feet of tubing string are possible if high strength martensitic stainless steel can be reliably installed rather than duplex stainless steel or a nickel-based alloy. Recent changes to NACE MR0175/ISO 15156 were driven by criticisms of the document’s conservatism of strictly considering the partial pressure of H2 S (PH2 S ). PH2 S is based on the ideal gas law, linearly increasing the predicted sour severity with increasing total pressure. Cracking will only occur when H2 S and CO2 are dissolved in water; dry sour gas will not cause corrosion at downhole conditions. Assessing sour severity from PH2 S will overpredict the measurable H2 S concentration in the fluid (CH2 S ), where CH2 S has a near constant severity with increasing total pressure at high pressure range, unnecessarily restricting alloy selection in some cases, as the gaseous H2 S does not contribute to cracking. A fugacity (fH2 S ) based approach will fall in between PH2 S and CH2 S with a pseudo-parabolic increase in severity with increasing pressure [12]. Sherar et al. demonstrate the modelled real gas behavior is

Exploring the Service Life Extremes of 716 in Highly Corrosive …

73

in very good agreement with physical testing [13]. Despite these changes, adoption is hampered by a lack of validation through qualification testing. UNS N07718 is often used in extreme downhole conditions but is restricted by MR0175–200 psi (1.4 MPa) H2 S partial pressure at 401 °F (205 °C). UNS N07716, 716, is commonly used in environments above 718’s limit, as MR0175 allows a 600 psi (4.1 MPa) H2 S partial pressure at the same temperature with any combination of chloride concentration and in situ pH in the presence of elemental sulfur (S0 ) [14]. The high chromium content controls the pit initiation, and the relatively high molybdenum content enhances surface passivation. However, at 401 °F, the material is not necessarily resistant to S0 . S0 solubility increases in H2 S containing aqueous environments, potentially damaging components [15]. It is unclear what hardness limit is acceptable for 716 at this temperature to ensure functionality over the life cycle of a project. Field cases exist of component failure of 716 due to the presence of S0 [16]. The ambiguity on the limits set with H2 S, chloride concentration, and the presence of S0 warrants more research. The objective of this work is to clarify and expand the SCC safe use limit of 716 at 15,229 psi (105 MPa) based on equivalent dissolved H2 S concentration of the MR0175 published sour service limit determined historically at low total pressure.

Material Testing Approach In this work, SCC susceptibility of triplicate heats of precipitation hardened nickelbased alloy 716 was evaluated by performing NACE TM0177 Method C SCC testing and TM0198 Slow Strain Rate Testing (SSRT). MR0175 is complemented by standard TM0177, the only recognized method for certification therein. TM0177 outlines laboratory testing of metals for resistance to stress corrosion cracking (SCC) and sulfide stress cracking (SSC) in H2 S containing environments [17]. Method C, the C-ring test, is the most used method outline in the standard for tubular goods. C-rings are statically loaded specimens that are frequently used in evaluation of tubing, pipes, and forgings. Circumferential stress is of principle interest, and it varies around the circumference from zero at each bolt hole to a maximum at the outer surface of the middle of the arc opposite the stressing bolt. Testing is expensive in part due to the laborious preparation and long, 90-day duration. TM0198 outlines SSRT for screening corrosion resistant alloys for SCC in sour service. The test consists of a dynamic strain applied at a constant extension rate, commonly in the range of 1.0 × 10–5 s−1 to 1.0 × 10–7 s−1 , immersed in a fluid of interest. Cracking is accelerated in susceptible materials, typically over the course of 1 to 3 days, lending it usefulness as a screening tool to determine likely upper limits before committing to a long duration C-ring test [18]. However, the downsides are threefold: a lack of pass/fail criteria, poor direct correlation with Method C testing, and aggressive corrosion compared to real environments [19]. Using SSRT and C-ring testing in tandem is an excellent method for exploring the upper limits of SCC susceptibility of 716 in a sour environment. SSRT is first used

74

T. Dunne et al.

Fig. 1 OLI simulation results showing the effect of total pressure on dissolved H2 S concentrations at a fixed H2 S partial pressure of 600 psi (4.13 MPa)

to screen several sour environments of increasing H2 S partial pressure starting at the nominal sour service limits defined by MR0175/ISO15156-3:2020 for 716. Once a clear boundary is established by SSRT, a sour environment under the discovered cracking boundary is selected for performing the 90-day high pressure SCC qualification testing using C-rings at typical lab conditions (400°F (205 °C) and 1250 psi) for NACE Level VII environmental conditions. Concurrently, SCC qualificationring testing of a very high pressure autoclave will simulate potential field conditions with a pressure of 15,229 psi (105 MPa) by matching the CH2 S to the standard high pressure test. Thermodynamic modeling points towards evaluating sour severity through CH2 S . A simulation from OLI Analyzer software in Fig. 1 demonstrates the usefulness in applying this metric to sour environments by modeling the baseline MR0175 conditions to a HPHT sour well with 1300 psi (8.96 MPa) CO2 , 19% wt. % NaCl, and 15 ksi (103 MPa) pressure. In the baseline case, the H2S partial pressure is held constant at 600 psi (1.4 MPa) with the overpressure varied by increasing CH4 at 400 °F (205 °C), demonstrating the inverse relationship between pressure and CH2 S .

Experimental Procedure Three random heats of 716 (140 ksi minimum yield strength) were procured from Foroni, with hardness ranging from 37 to 43 HRC. Five SSRT specimens conforming to TM0198 were machined from the mid-radius, longitudinal orientation from each heat. Five C-rings conforming to TM0177 were machined with the apex at the mid-radius location from each heat. One specimen was used for strain-deflection calibration, three in the high pressure testing, and one in the very high pressure test.

Exploring the Service Life Extremes of 716 in Highly Corrosive …

75

NACE TM0198 SSRT Screening A baseline 401 °F (205 °C) test was performed, after which the NACE Level VII condition (600 psi (4.1. MPa) PH2 S , 1218 psia (8.40 MPa) PCO2 , 180,000 mg/L Cl− , S0 at 1 g/L) was tested by Honeywell, both at a rate of 4.0 × 10–6 in/sec (1.01 × 10–4 mm/ s). Upon completion of the test, the samples were cleaned with acetone, visually examined for secondary cracks, calculated the reduction in area (RA) by measuring the diameter to the nearest 0.001 inch (0.025 mm), and calculating the elongation by measuring the total length (EL). The time to failure (TTF) is also recorded. The sour test results were compared to the baseline air measurements to determine the ductility performance ratio. Ductility ratio indicates the susceptibility of the alloy in the environment, with a ratio Fe(8h) > Fe(4e). The magnetic moment of Fe is also expected to be consistent with the same ranking as the Fe–C or Fe–N hybridization becomes weaker when interatomic distance is further apart. (5) Lattice paramters a, c, and c/a ratio of the relaxed crystal lattice of Fe16 Cx N2−x , both for C-doped α'' -Fe16 N2 and N-doped α'' -Fe16 C2 , are shown in Fig. 6. The lattice parameters vary with the C-dopant compositions. The formation energies for each atomic composition of Fe16 Cx N2−x for both C-doped Fe16 N2 “Minnealloy” and N-doped in α'' -Fe16 C2 are plotted in Fig. 7. Although lattice parameters show a large difference, there is only a small difference between the two sets of energy at the same C composition. With higher C%, the crystal structure becomes more stable except at 100% C. Instead, Fe16 C1.78 N0.22 is shown to have the most stable structure with the lowest energy at −6.45 eV/atom. Carbon-doped Fe16 C0.475 N1.525 (with C composition at 0.475) has the highest c/a ratio.

Crystal Lattice Structure Prediction of Fe-Based Compounds …

641

Fig. 5 Crystal structure comparison in a proposed “Atom + Cluster” Fe6 X (X = C, N) sublattice formation in relaxed a α'' -Fe16 N2 and b α'' -Fe16 C2 . In Fe(4e), Fe(8h) and Fe(4d) to C(2a) distance. In α'' -Fe16 C2 , compared to α'' -Fe16 N2 , Fe(4d) to C(2a) distance reduced by about 1.6% while Fe(4e) to C(2a) distance increased by 1.9%

Fig. 6 Lattice constants a (top), c (middle), and c/a ratio (bottom) of the relaxed crystal lattice for Fe16 Cx N2−x , both C-doped α'' -Fe16 N2 and N-doped α'' -Fe16 C2

642

J. Zhu and J.-P. Wang

Fig. 7 Lattice formation energy versus X in alloy Fe16 Cx N2−x . The most stable composition identified is Fe16 C1.78 N0.22

Conclusions The crystal structures of α'' -Fe16 N2 , α'' -Fe16 C2 , and Fe16 Cx N2−x (x ∈ (0,2)) alloys were studied using MD-based energy minimization using SA-DVS method with high computational efficiency. The obtained lowest energy state of γ' -Fe4 N, α'' -Fe16 N2 , and α'' -Fe16 C2 resulted in the lattice parameters and formation energies that are reasonably comparable to the literature values. Although the lattice of α'' -Fe16 C2 exhibited lower formation energy therefore a better stability than α'' -Fe16 N2 . The significantly reduced c/a ratio ~1.06 in α'' -Fe16 C2 suggests the degraded magnetic anisotropy as shown by DFT study [23]. In Fe16 Cx N2−x Minnealloy, the most stable structure was found in Fe16 C1.78 N0.22 with better stability than α'' -Fe16 C2 , while Fe16 C1.12 N0.88 exhibited the highest c/a ratio at 1.14.

References 1. Wang J-P (2020) Environment-friendly bulk Fe16 N2 permanent magnet: review and prospective. J Magn Magn Mater 497:165962 2. Jack KH (1994) The synthesis, structure, and characterization of a-Fe16 N2 . J Appl Phys 76:6620 3. Hang X et al (2020) Magnetic structure of Fe16 N2 determined by polarized neutron diffraction on thin-film samples. Phys Rev B 102:104402

Crystal Lattice Structure Prediction of Fe-Based Compounds …

643

4. Ji N, Liu X, Wang J-P (2010) Cluster + atom model: theory of giant saturation magnetization in α'' -Fe16N2: role of partial localization in ferromagnetism of 3d transition metals. New J Phys 12:063032 5. Tanaka H et al (2000) Electronic band structure and magnetism of Fe16 N2 calculated by the FLAPW method. Phys Rev B 62(22) 6. Sinclair CW et al (2010) Molecular dynamics study of the ordering of carbon in highly supersaturated a-Fe. Phys Rev B 81:224204 7. Kandasklov D, Maugis P (2017) A first-principles study of the structural, elastic, lattice dynamical and thermodynamic properties of a-Fe16 C2 and a-Fe16 N2 phases. Comput Mater Sci 128:278–286 8. Fang CM et al (2012) Stability and crystal structures of iron carbides: a comparison between the semi-empirical modified embedded atom method and quantum mechanical DFT calculations. Phys Rev B 85:054116 9. Eren Y et al (2017) Chapter 2 Introduction to optimization. In: Optimization in renewable energy systems. Butterworth-Heinemann, pp 27–74 10. Leineweber et al (2017) Crystal structures of Fe4 C vs. Fe4 N analyzed by DFT calculations: Fcc-based interstitial superstructure explored. Acta Mater 140:433–442 11. Zener (1948) Theory of strain interaction of solute atoms. Phys Rev 74:639 12. Md Mehedi et al (2017) Minnealloy: a new magnetic material with high saturation flux density and low magnetic anisotropy. J Phys D Appl Phys 50:37LT01 13. Guo G et al (2020) Carbon and microstructure effects on the magnetic properties of Fe–CN soft magnetic materials (minnealloy). TMS 2020 149th annual meeting and exhibition supplemental proceedings. The minerals, metals and materials series. Springer, Cham, pp 1841–1852 14. Lee B-J et al (2006) A modified embedded-atom method interatomic potential for the Fe–N system: a comparative study with the Fe–C system. Acta Mater 54(17):4597–4607 15. Lee B-J (2006) A modified embedded-atom method interatomic potential for the Fe–C system. Acta Mater 54(3):701–711 16. Liyanage L (2014) Structural, elastic, and thermal properties of cementite (Fe3 C) calculated using a modified embedded atom method. Phys Rev B 89:094102 17. Kinaci et al (2012) Thermal conductivity of BN-C nanostructures. Phys Rev B 86:115410 18. Thompson P et al (2022) LAMMPS—a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Comput Phys Commun 271:108171 19. Mi WB et al (2013) Reactively sputtered epitaxial g-Fe4 N films: surface morphology, microstructure, magnetic and electrical transport properties. Acta Mater 61:6387–6395 20. Zhu J, Wang J-P (2023) Simulation of thermal decomposition of g-Fe4 N using molecular dynamics method. AIP Adv 13:025234 21. Stoeckl P et al (2021) Magnetocrystalline anisotropy of α'' -Fe16 N2 under various DFT approaches. AIP Adv 11:015039 22. Ochirkhuyag T et al (2021) First principles prediction of enhanced magnetic anisotropy of α'' -phase Fe16 N2 with B and C impurities. IEEE Trans Magn 57(2):1–3 23. Uchida S et al (2007) Magnetocrystalline anisotropy energies of Fe16 N2 and Fe16 C2 . J Magn Magn Mater 310

Magnetic and Optical Study of Zinc Ferrite Produced by the Ceramic Method Mery C. Gómez-Marroquín, Fernando Huamán-Pérez, Henry Colorado, Nilton Cárdenas-Falcón, José Carlos D’Abreu, Abraham J. Terrones-Ramirez, and Kim J. Phatti-Satto

Abstract A solid–solid reaction took place at 1000 °C during 4 h, using a mixture of pure iron oxideFe2 O3 and pure zinc oxide—ZnO in order to synthesize zinc ferrite— ZF of different compositions: (S1) Fe2 O3 /ZnO:3/2, (S2) Fe2 O3 /ZnO:1/1, (S3) Fe2 O3 / ZnO:4/1, and (S4) Fe2 O3 /ZnO:2/1. Each of these mixtures were milled during 24 h before the thermic treatment was carried out. S1, S2, S3, and S4 samples were become to M1, M2, M3, and M4 samples, respectively, which after that were thermally characterized using DSC, DTA, and TG techniques. In sequence the ZF produced were examined using XRD, optical, and magnetic techniques, SEM and TEM. XRD analysis shows up contains of equimolar ZF: M3 (73.20%), M4 (28.00%), and M2 (2.10%) as non-stoichiometric phases of ZF: 31.80% of Zn0.95 Fe1.78 O3.71 and 30.40% of Zn1.08 Fe1.92 O4 in M4; Zn0.97 Fe2.02 O4 in M3 and 35.30% of Zn0.54 Fe2.46 O4 in M1. Previous studies of magnetic characterization observed a little hysteresis of M. C. Gómez-Marroquín (B) · F. Huamán-Pérez · A. J. Terrones-Ramirez · K. J. Phatti-Satto Steelmaking and Ironmaking Research Group, National University of Engineering, 210 Túpac Amaru Ave, Rímac, Lima 15333, Peru e-mail: [email protected] F. Huamán-Pérez e-mail: [email protected] A. J. Terrones-Ramirez e-mail: [email protected] K. J. Phatti-Satto e-mail: [email protected] H. Colorado University of Antioquia, 67 St, 52-21, 1226 Medellín, Antioquia, Colombia e-mail: [email protected] N. Cárdenas-Falcón Pontifical Catholic University of Perú, Universitaria Ave, 1801, San Miguel, Lima 15088, Peru e-mail: [email protected] J. C. D’Abreu Pontifical Catholic University of Rio de Janeiro, Marquês de São Vicente St, 225 Gávea, Rio de Janeiro, RJ 22522451-900, Brazil e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_55

644

Magnetic and Optical Study of Zinc Ferrite Produced by the Ceramic …

645

this equimolar ZF. The results of estimation of the bandgap energy (Eg) via the manipulation of the Kubelka–Munk theory allowed to determine that the samples M1, M2, M3, and M4 are considered semiconductors (3.66 and 3.76 eV). Keywords Ceramic method · Magnetic materials · Zinc ferrite—ZF · Optical characterization · Magnetic characterization · Modified Kubelka–Munk function

Introduction As is known, zinc ferrite is a spinelium compound that belongs to the franklinite family. Spinelias are constituted as a group of minerals that crystallize in the cubic system, with an octahedral habit. Its general formula is (X)(Y)2 O4 , where X represents the cations that occupy tetrahedral positions and Y the octahedral ones. Some divalent, trivalent and tetravalent cations can occupy the X and Y positions, including elements such as: Mg, Zn, Fe, Al, Cr, Ti, and Si [1]. Zinc ferrites can be normal (when Zn atoms occupy tetrahedral sites and Fe atoms occupy octahedral sites) or inverse (when Zn atoms partially occupy the octahedral sites, while Fe atoms occupy half of the octahedral sites) [2, 3]. There are different methods for synthesizing zinc ferrites, including conventional ceramic, mechanochemical, sol–gel synthesis, combustion technique, hydrothermal processing, etc. [3, 4], but the ceramic route has allowed the formation of either stoichiometric or equimolar zinc ferrites, defined mainly at high synthesis times and temperatures, 4 h and 1000 °C, respectively [5]. These materials are considered ferromagnetic, and due to their good magnetic and optical properties, they can be used in electronic applications mainly, magnetic recording and fluids, catalysis, sensors, magnetically guided drug delivery, pigments, microwave technology, catalytic and biomedical fields [6]. On the other hand, optical analysis (UV-Vis and PL) of zinc ferrites nanoparticles had been studied demonstrating their absorption edge properties in the visible region which is legitimated to the excitation of electron from O-2p state to Fe-3d state [7]. Various zinc ferrite characterization techniques were used to determine the crystallinity, crystallite size, lattice parameter, morphology, elemental composition, energy bandgap, emission, saturated magnetization, and coercivity of the synthesized nanoparticles [8]. This work is aimed to understand the relationship between the magnetic and optical study of zinc ferrite samples produced by the ceramic method but using non-stoichiometric and stoichiometric mixtures [9].

646

M. C. Gómez-Marroquín et al.

Table 1 Molar and weight ratios of raw materials for preparation of stoichiometric and nonstoichiometric mixtures Samples

Molar ratio

Weight ratio

Heat treatment product names

Fe2 O3

ZnO

Fe2 O3

ZnO

S1

3

2

3.23

1

M1, M' 1

S2

1

1

2.16

1

M2, M' 2

S3

4

1

8.63

1

M3, M' 3

S4

2

1

4.32

1

M4, M' 4

ZF pure

1

1

2.00

1

M5

Hematite

1

–

1.00

–

HM

Experimental Procedures Mechanical Preparation of Stoichiometric and Non-stoichiometric Mixtures The raw materials, zinc oxide and iron(III) oxide, were prepared mechanically through simultaneous grinding and homogenization using 500 g ceramic mortars and 25 g agate mortars, simulating grinding in a ball mill.

Thermogravimetric Analysis via DTG and TGA For this purpose, a Perkin Elmer TGA 4000 analyzer with S/N: 522A17110904 was used. For this reason, we proceeded to take approximately 10 mg by weight of each of the stoichiometric oxide mixtures: Fe2 O3 /ZnO:1/1 (S2) and non-stoichiometric Fe2 O3 /ZnO:3/2 (S1), Fe2 O3 /ZnO:4/1 (S3), and Fe2 O3 /ZnO:2/1 (S4) previously homogenized and ground in mortars (Table 1). This test took place via programming a heating ramp of the thermogravimetric analysis equipment under the following operating conditions: Heating rate of 10 °C/ min, initial temperature of 30 °C to final temperature of 900 °C, isothermal period 5 min at 900 °C, and inert gas flow (N2 ) of 50 mL/min.

Heat Treatment of Oxide Mixtures Samples of 100–150 g of stoichiometric mixtures were then weighed: Fe2 O3 /ZnO:1/ 1 (S2) and non-stoichiometric mixtures: Fe2 O3 /ZnO:3/2 (S1), Fe2 O3 /ZnO:4/1 (S3), and Fe2 O3 /ZnO:2/1 (S4) which were weighed, homogenized, and ground for 24 and 48 h. Four porcelain crucibles with a maximum capacity of 125 g were preheated

Magnetic and Optical Study of Zinc Ferrite Produced by the Ceramic …

647

Fig. 1 Mechanical preparation and mortar grinding of raw materials and heat treatment or synthesis of zinc ferrites followed by their mechanical preparation for complete characterization

at a temperature of 300 °C for a period of 8–12 h, before subjecting them to a heat treatment at 1000 °C for 4 h, together with the 4 prepared mixes. These thermal treatments were carried out in a FUNDINORT S.A.C brand electric muffle furnace of 1100 °C maximum temperature previously calibrated and which showed a heating rate of approximately 1.5 °C/min. The samples weighed in the proportions S1, S2, S3, and S4, which were ground and mixed for about 24 h, became M1, M2, M3, and M4, and those of 48 h became M' 1, M' 2, M' 3, and M' 4; after heat treatment. The molar and weight proportions of these mixtures, as well as the names of the products obtained after heat treatment, are presented in Table 1. The samples called thermal treatment products (M1, M2, M3, M4, and M5) were used to carry out the structural characterization, via XRD, magnetic-VSM, and optical-UV vis. Figure 1 shows the mechanical mixing and grinding of the raw materials carried out in ceramic mortars, before heat treatment, and the heat treatment or synthesis of zinc ferrites followed by their mechanical preparation for their complete characterization of the samples. Only samples M' 1, M' 2, M' 3, and M' 4 were analyzed by XRD.

X-Ray Diffraction Analysis—XRD XRD of raw materials (mixtures treated thermally) was performed in an ADVANCE D8 X-ray diffractometer, BRUKER. This equipment is scanned with a goniometer (radius 240 mm). XRD patterns were collected in the 2θ range of 5°–90° with 0.02° increment and a divergence slit size of 0.6°. The diffractometer has copper anodes (λ = 1.5406 Å, Cu K-α; λ = 1.39 225 Å, Cu K-β), and operates with a 40 kV voltage and a 30 mA current. We analyze the crystalline phases and/or inorganic compounds in the tested samples qualitatively (by comparison with the ICSD database) and quantitatively (using the Rietveld method).

648

M. C. Gómez-Marroquín et al.

Magnetic Characterization—VSM These tests for determination of magnetic properties were carried out in a Vibrating Sample Magnetometer (VSM) brand GLOBALMAG and model TMAG-V2, which has a Gaussian magnetic field of 1 T/V ≈ 10 Oe/mV sensitivity and passage speed of 16.8 Oe/s. This equipment operated with a Stanford Research System Locking Amplifier, Model SR830 with a generator configuration of [−8 A, 8 A] and [−50 V, 50 V].

Optical Characterization—UV Vis The optical characterization was carried out using a Shimadzu UV-2600 spectrophotometer (A11665704761) coupled to UVProbe software version 2.7 that measured absorbance and reflectance in a wavelength range of 300–700 nm, average scanning speed, interval of sampling of 0.05 nm, absorbance and reflectance slit width of 5.0 nm, accumulation time of 2.0 s, light source switching wavelength: 370.0 nm detector unit: external (2 detectors) detector wavelength switching: 900.0 nm S/R exchange.

Results and Discussion TGA-DTG Thermogravimetric Analysis Figure 2a shows the TGA thermogram of the weight loss tests of the samples: S1, S2, S3, and S4 while Fig. 2b shows the behavior of the samples S1, S2, S3, and S4 against to the heating time and temperature in the thermogravimetric equipment, where St1, St2, St3, and St4 are the programmed temperatures and ST1, ST2, ST3, and ST4 are the temperatures observed by the corresponding samples S1, S2, S3, and S4. As expected, all treated samples showed a weight loss during treatment at 1000 °C for 4 h due to the evaporation of zinc that was part of its corresponding oxide. Knowing that both samples S2 and S3 showed both the minimum and maximum weight loss of the four samples tested, respectively. However, the DTA-DTG test of the four samples showed that all of these lost almost the same weight from the temperature of the environment to approximately 100 °C, possibly due to the humidity gained during its preparation and grinding. Sample S4 showed a very close weight loss compared to sample S3. The stoichiometric sample, S2 showed a weight loss of approximately 0.02%. Because the weight losses of the tested samples are negligible, it can be considered that they are stable against heat treatment at high temperatures.

Magnetic and Optical Study of Zinc Ferrite Produced by the Ceramic …

(a)

649

(b) 0

20

40

60

80 900 720 540 360 180

900

S1t S1T S2t S2T S3t S3T S4t S4T

°C

720

atu

re ,

540

mp

er

360

Te

180 0

20

40

60

80

time, min

Fig. 2 a Weight loss thermogram of samples S1, S2, S3, and S4, and b 3D behavior of samples S1, S2, S3, and S4 versus heating time and temperature in the thermogravimetric equipment

See Fig. 3. Next, Table 3 shows the weight losses of the DTA-DTG assay and the main endothermic peaks of the samples: S1, S2, S3, and S4. Using the main endothermic peaks obtained during the TGA-DTG test of the samples: S1, S2, S3, and S4, and the quantification of crystalline phases carried out by the XRD analysis, the formation of the main spinels of the zinc ferrites can be verified, both stoichiometric and non-stoichiometric (mixed). It has also been observed that both samples S1 and S2 showed a very insignificant weight loss between 0.02 and 0.25% and samples S3 and S4 a significant weight loss between 100 and 1.10%.

Fig. 3 TGA and DTG curves of the decomposition of the sample a S1 (T = 117.6 °C), b S2 (T = 114.3 °C), c S3 (T = 117.60 °C), and d S4 (T = 121.4 °C)

650

M. C. Gómez-Marroquín et al.

Table 3 Weight losses of the DTA-DTG test and the main endothermic peaks of the samples: S1, S2, S3, and S4 Samples

% Weight loss—TGA

Endothermic peaks of probable appearance of the spinel phase of zinc ferrite—DTG (°C)

S1

0.05

117.60, 278.41, 489.19, and 819.60

S2

0.02

114.30, 273.10, 468.49, 491.29, 544.86, 645.71, 713.62, and 833.30

S3

1.10

117.60, 261.08, 305.89, 330.46, 413.70, 488.14, 613.97, 664.17, 728.80, 793.46, and 822.30

S4

1.00

121.47, 271.45, 441.60, 596.83, 666.53, 732.23, and 847.00

Likewise, samples S1 and S3 show in common a first and only endothermic peak or coincident decomposition temperature equal to 117.60 °C.

Characterization via X-Ray Diffraction-XRD Figure 4 shows (a) the diffractogram of the XRD analysis of M4, and (b) the diffraction patterns of samples M1, M2, M3, and M4, as well as, Tables 4 and 5 the main crystalline phases identified and quantified by the Rietveld method of the XRD of the samples: M1, M2, M3, and M4, as well as, the samples M' 1, M' 2, M' 3, and M' 4, respectively. Certainly, the spinel phases present in both Tables 4 and 5 obey the formula: [A1−x Bx ]t[Ax B1−x B]oO4 . As can be seen, the four samples tested after 24 h of grinding: M1, M2, M3, and M4 show the presence of the main inverse spinel phases both in the stoichiometric form: ZnFe2 O4 in M3 (73.20%), M4 (28.00%), and M2 (a)

(b) 3.0x108

M4

2.3x108 1.5x108 7.5x107 0.0 9.6x107

M3

7.2x107 7

4.8x10

M2

1.0x108

counts

2.4x107 1.5x108

7

5.1x10

0.0 2.2x108

M1

1.6x108 1.1x108 5.5x107 0.0 0

2x105

4x105

6x105

8x105

2 theta, Bragg angle

Fig. 4 a XRD diffraction patterns of sample M4 and b the four samples simultaneously

1x106

8.00

8.10

M3

M4

1.70

7.40

64.70

Fe3 O4

61.80

20.70

Fe2.96 O4

M2

Fe2 O3

M1

Samples

28.00

73.20

2.10

ZnFe2 O4 35.30

Zn0.54 Fe2.46 O4

11.40

Zn0.97 Fe2.02 O4

30.40

Zn1.08 Fe1.92 O4

Table 4 Main spinel phases shown in samples M1, M2, M3, and M4 identified and quantified by XRD

31.80

Zn0.95 Fe1.78 O3.71

15.50

Zn2 (SiO4 )

Magnetic and Optical Study of Zinc Ferrite Produced by the Ceramic … 651

652

M. C. Gómez-Marroquín et al.

Table 5 Main spinel phases shown in samples M' 1, M' 2, M' 3, and M' 4 identified and quantified by XRD Samples

Quartz low

Fe3 O4

ZnFe2 O4

SiO2 -coesita

Fe2 O3

Zn2 (SiO4 )

Icsd 16331

Icsd 85806

Icsd 91827

Icsd 18112

Icsd 82902

Icsd 20093

18.00

M’1

6.00

10.10

64.20

1.70

M’2

5.60

24.20

51.10

1.40

M’3

5.60

21.60

71.10

1.70

M’4

6.40

3.70

36.40

1.70

17.7 51.80

Rwp

gof

4.14

1.23

4.72

1.44

4.42

1.40

4.35

1.30

(2.10%) as non-stoichiometric or mixed spinels: 31.80% Zn0.95 Fe1.78 O3.71 (M4); 30.40% Zn1.08 Fe1.92 O4 (M4); Zn0.97 Fe2.02 O4 (M3); and 35.30% Zn0.54 Fe2.46 O4 (M1). Samples M3 and M4 observed a total of 84.60 and 90.20% of spinel phases, respectively. The interesting thing is that other magnetic phases were also observed such as: hematite Fe2 O3 , non-stoichiometric magnetite Fe2.96 O4 , stoichiometric magnetite Fe3 O4 . However, only in the case of M3 and M4 the hematite content is very similar. While samples M' 1, M' 2, M' 3, and M' 4 did not show the presence of nonstoichiometric zinc ferrites or spinel phases and a lot of SiO2 contamination, possibly due to the excessive blow of the pistil on a porcelain crucible during the 48 h of grinding. It is notable that the fit between the experimental diffractograms and those adjusted by the Rietveld “gof” (Goodness of Fit) method of all tests are quite close to one (1).

Magnetic Characterization—VSM The estimation results of the saturation magnetization (M) using Vibrating Sample Magnetometer—VSM or as a function of the applied magnetic field (H) carried out on the samples M1, M2, M3, M4, and M5, are shown in Table 6. From Table 6, the highest saturation magnetization (M) observed, M5, was 0.68 emu/g, a value much lower than that observed for nanoparticles synthesized by green methods (12.81 emu/g) [10]. In Fig. 5a, the clearly marked magnetization Table 6 Saturation magnetization (M) results of samples M1, M2, M3, M4, and M5

Muestras

Magnetización de saturación (emu/g)

Masa (g)

M1

0.20

0.04

M2

0.15

0.08

M3

0.15

0.05

M4

0.20

0.02

M5

0.68

0.09

Magnetic and Optical Study of Zinc Ferrite Produced by the Ceramic …

(a) 0

2

4

653

(b) 6

8

10 10

0.8

1.2 Hematita

0.6

0.8

8

0.2

6

0.0 4

M1 M2 M3 M4 M5

-0.2 -0.4 -0.6

0

1000

0.0

-0.4

Ferrita de Zinc

-0.8

0 -1000

0.4

2

-0.8 -2000

M (Normalizado)

M (emu/g)

0.4

2000

H (Oe)

-1.2 -2000

-1000

0

1000

2000

H (Oe)

Fig. 5 Magnetization (M) as a function of the applied magnetic field (H) for samples M1, M2, M3, M4, and M5, and b normalized hysteresis curve as a function of the applied magnetic field of the equimolar zinc ferrite (M5) and hematite

hysteresis curve could only be observed in sample M5 because it is the standard sample M5. In Fig. 5b, the hysteresis of the sample of pure hematite (HM) and zinc ferrite (ZF) can be observed. As can be seen in Fig. 5b, the magnetization observed in this zinc ferrite sample with spinel structure is due to the contribution of Fe2+ cations. As is known, these ions tend to occupy the tetrahedral gaps or interstices as occurs in normal spinel, thus forcing some Fe3+ to leave their tetrahedral positions towards the octahedral sites, but when it is the case of the occurrence of inverse spinels, these cations aligned and contribute to increasing the magnetization of the material, as it is the case with sample M5, but not with samples M1, M2, M3, and M4. A very weak paramagnetic behavior was observed in the magnetic characterization of M1, M2, M3, and M4 except in the case of M5 which is slightly magnetic.

Optical Characterization-UV Vis Figure 6 shows both the (a) absorbance and (b) reflectance as a function of wavelength, in the range of 300 and 700 nm, of the four samples under study (M1, M2, M3, and M4). In Fig. 6a, it is clearly observed that both samples M1 and M2 have almost the same behavior regarding the absorbance of the electrons emitted by the spectrophotometer, only sample M3 absorbed more energy than sample M4 and this, at its time, adsorbed more photon energy than M1 and M2 from the electron beam in a range between 450 and 700 nm while Fig. 6b shows the reflectance as a function of wavelength, in the range of 300 and 700 nm, for samples M1, M2, M3, and M4.

654

M. C. Gómez-Marroquín et al. (a)

(b) M1 M2 M3 M4

2.5

M1 M2 M3 M4

35 30

Reflectance %

Absorbance (a.u.)

40

2.0

1.5

1.0

25 20 15 10 5

0.5 300

400

500

600

0 300

700

400

500

600

700

Wavelength (nm)

Wavelength (nm)

Fig. 6 a Absorbance and b reflectance spectra of samples M1, M2, M3, and M4 as a function of wavelength

(a)

3.5x10 5

(b) Magnetic and Optical properties

Kubelka-Munk´s Function modified

Analogously to the previous case, it is observed that both samples M1 and M2 have almost the same behavior regarding the reflectance of the electrons emitted by the spectrophotometer, in turn, these showed a higher % of reflectance, compared to sample M4 and this consequently with sample M3 in the visible spectrum range between 450 and 700 nm. From the results in Fig. 6 and using a spreadsheet to make the fundamental adjustments of the Kubelka–Munk function, the bandgap energies (Eg) of samples M1, M2, M3, and M4 could be estimated. Figure 7a shows the graph of the modified Kubelka– Munk function as a function of the photon energy in Ev, of the four samples under study (M1, M2, M3, and M4) and Fig. 7b a summary of the magnetic and optical properties of samples M1, M2, M3, and M4.

3.0x10 5 2.5x10 5

M1 M2 M3 M4

2.0x10 5 1.5x10 5 1.0x10 5 5.0x10 4 0.0 -5.0x10 4

10

Fe2O3/ZnO M (emu/g) Eg (eV)

8

6

4

2

0

1.5

2.0

2.5

3.0

Energy (eV)

3.5

4.0

4.5

M1

M2

M3

M4

samples

Fig. 7 a Estimation of the Kubelka–Munk Function as a function of the photon energy and b a summary of the magnetic and optical properties of samples M1, M2, M3, and M4 as a function of the Fe2 O3 / “ratio” ZnO

Magnetic and Optical Study of Zinc Ferrite Produced by the Ceramic … Table 7 Bandgap energy values (Eg) of samples M1, M2, M3, and M4

655

Samples

Eg (eV)

Type of material

Eg (eV)

M1

3.66

Conductors

0.0

M2

3.76

Semiconductors

0.5–4.0

M3

3.73

Insulators

5.0–10.0

M4

3.74

The UV–visible spectral analysis revealed interesting optical properties of samples M1, M2, M3, and M4: absorbance and reflectance, and above all it was possible to estimate an almost constant bandgap range (Eg), which indicates that these samples have a large amount of photon energy possible, classifying as “moderately semiconducting” according to the classification tables already widely disseminated (See Table 7). UV–visible reflectance spectrometry analyses showed a bandgap variation of the samples M1, M2, M3, and M4 that presented values between 3.66 and 3.76 eV that are very high compared to other zinc ferrite nanoparticles produced using the green synthesis method via honey-mediated sol–gel combustion method [8]. UV–visible spectral analysis revealed optical properties and therefore the optical bandgap could be found using the Kubelka–Munk function diagram [9]. Photoluminescence studies exhibited the excitation wavelength, which showed a recombination of holes and electrons [10].

Conclusions The large number of peaks or temperatures of probable decomposition, rearrangement or nucleation of new grains of zinc ferrites within the samples tested by TGA: S1, S2, S3, and S4 are due to the variety of spinel phases observed and quantified via XRD in samples M1, M2, M3, and M4. The weight loss observed via DTG was minimal. XRD of samples M1, M2, M3, and M4 showed the presence of the main inverse spinel phases, both the stoichiometric: ZnFe2 O4 in M3 (73.20%), M4 (28.00%), and M2 (2.10%) and the non-stoichiometric or mixed spinels: 31.80% Zn0.95 Fe1.78 O3.71 (M4); 30.40% Zn1.08 Fe1.92 O4 (M4); Zn0.97 Fe2.02 O4 (M3); and 35.30% Zn0.54 Fe2.46 O4 (M1). Samples M3 and M4 observed a total of 84.60 and 90.20% of spinel phases, respectively. Other magnetic phases such as: hematite Fe2 O3 , non-stoichiometric magnetite Fe2.96 O4 , stoichiometric magnetite Fe3 O4 were also observed. However, only in the case of M3 and M4 the hematite content is very similar. Additionally, samples M' 1, M' 2, M' 3, and M' 4 did not exhibit non-stoichiometric zinc ferrites or spinel phases, but they did exhibit a lot of SiO2 contamination, possibly due to the excessive blow of the pistil on the porcelain crucible during the 48 h of grinding. It is notable that the fit between the experimental diffractograms and those adjusted by the Rietveld “gof” (Goodness of Fit) method of all tests are quite close to one (1). On the other hand, samples M1, M2, M3,

656

M. C. Gómez-Marroquín et al.

and M4 observed a weakly paramagnetic behavior against the saturation magnetization of the VMS (between 0.5 and 1.0 eum/g), except in the case of M5 (0.68 eum/ g) which observed a well-established hysteresis curve. The estimation results of the bandgap energy (Eg) via the manipulation of the Kubelka–Munk theory (modified Kubelka–Munk function) allowed us to determine that samples M1, M2, M3, and M4 are considered semiconductors (3.66 and 3.76 eV). Acknowledgements Authors would like to thank the Research Vice Rectorate and the College of Geological Mining and Metallurgical Engineering Research Institute of the National University of Engineering for the financial assistance granted, without which these programmed experiences could not have been carried out.

References 1. Sugi S, Radhika S, Padma CM (2022) Co-precipitation of zinc ferrite nanoparticles in the presence and absence of polyvinyl alcohol with other constant parameters and the analysis of polyvinyl alcohol mediated zinc ferrite nanoparticles. Mater Chem Phys 292:126799 2. Mouhib Y, Belaiche M, Elansary M, Ferdi CA (2022) Effect of heating temperature on structural and magnetic properties of zinc ferrite nanoparticles synthesized for the first time in presence of Moroccan reagents. J Alloy Compd 895:162634 3. Cobos MA, de la Presa P, Llorente I, García-Escorial A, Hernando A, Jiménez JA (2020) Effect of preparation methods on magnetic properties of stoichiometric zinc ferrite. J Alloy Compd 849:156353 4. Afkhami A, Sayari S, Moosavi R, Madrakian T (2015) Magnetic nickel zinc ferrite nanocomposite as an efficient adsorbent for the removal of organic dyes from aqueous solutions. J Ind Eng Chem 21:920–924 5. Gómez-Marroquín MC (2004) Contribution to the study of the formation and reduction of Zinc Ferrite. Thesis dissertation, Department of Science of the Materials and Metallurgy, Pontifical Catholic University of Rio de Janeiro. DCMM - PUC-Rio, 2004, 179 p. Adviser: Prof. D’Abreu, José Carlos 6. Naik MM, Naik HB, Nagaraju G, Vinuth M, Naika HR, Vinu K (2019) Green synthesis of zinc ferrite nanoparticles in Limonia acidissima juice: characterization and their application as photocatalytic and antibacterial activities. Microchem J 146:1227–1235 7. Singh NB, Agarwal A (2018) Preparation, characterization, properties and applications of nano zinc ferrite. Mater Today Proc 5(3):9148–9155 8. Yadav RS, Kuˇritka I, Vilcakova J, Urbánek P, Machovsky M, Masaˇr M, Holek M (2017) Structural, magnetic, optical, dielectric, electrical and modulus spectroscopic characteristics of ZnFe2 O4 spinel ferrite nanoparticles synthesized via honey-mediated sol-gel combustion method. J Phys Chem Solids 110:87–99 9. Kombaiah K, Vijaya JJ, Kennedy LJ, Bououdina M, Al-Lohedan HA, Ramalingam RJ (2017) Studies on Opuntia dilenii haw mediated multifunctional ZnFe2 O4 nanoparticles: optical, magnetic and catalytic applications. Mater Chem Phys 194:153–164 10. Vinosha PA, Mely LA, Jeronsia JE, Krishnan S, Das SJ (2017) Synthesis and properties of spinel ZnFe2 O4 nanoparticles by facile co-precipitation route. Optik 134:99–108

Part XVII

Advances in Multi-Principal Element Alloys III: Mechanical Behavior

Dependence on Their Mn and Cr Contents of the Microstructures, Melting Range, and High Temperature Creep Behaviors of Cantor’s Alloy and Versions Strengthened by MC Carbides Corentin Gay, Pauline Spaeter, Nassima Chenikha, Lionel Aranda, and Patrice Berthod

Abstract Decreasing Mn and increasing Cr in the cast Cantor’s alloys and in their MC–strengthened versions may have consequences on the refractoriness and on the high temperature mechanical properties. Differential thermal analysis (DTA) was run to specify the temperatures of starts and stops of melting and solidification. 3 points flexural creep tests were carried out at several temperatures in the [1000–1100 °C] range for several values of the induced maximal tensile stress varying between 10 and 20 MPa. It appears that, at constant contents in Mn and Cr, the solidus temperature of the MC–containing alloys is lowered by regards to the MC–free ones, and also that, for the MC–free alloys as well as for the MC–containing ones, the solidus temperature increases when the Mn content decreases and the Cr content increases. The creep tests evidence that no systematic effect of the Mn/Cr ratio on the creep resistance exists, neither for the MC–free alloys, nor for the MC–containing ones. In contrast, the MC–strengthened alloys are indisputably stronger against creep deformation than the MC–free alloys, regardless the Mn and Cr contents. Keywords High entropy alloys · CoNiFeMnCr–based HEAs · Melting range · Creep behavior · Mn and Cr influence · TaC and HfC influence

C. Gay · P. Spaeter · N. Chenikha · P. Berthod (B) Université de Lorraine, Campus Victor Grignard, 54500 Vandoeuvre-Lès-Nancy, France e-mail: [email protected] L. Aranda · P. Berthod Institut Jean Lamour, 2 Allée André Guinier, Campus ARTEM, 54000 Nancy, France © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_56

659

660

C. Gay et al.

Introduction Among the famous high entropy alloys (HEAs), the Cantor’s alloy appears in good place. It contains, generally in equal molar quantities, metallic elements the melting points of which are rather high: Co (1495 °C), Ni (1455 °C), Fe (1538 °C), Cr (1907 °C), and Mn, the less refractory of the five ones, with only 1246 °C [1, 2]. The melting point of the Cantor’s alloy [3] is considered to belong to the 1350–1400 °C range [4–6]. This is much less the Refractory High Entropy Alloys (RHEAs) [7], but this is compatible with elaboration by classical foundry for obtaining structural alloys which, furthermore, can possibly compete with superalloys [8]. However, in absence of grain and intergrain strengthening particles, the mechanical properties of this type of alloy are possibly not as interesting at temperatures near 1000 °C as at ambient and cryogenic temperatures. Recent tests of introducing carbon and MC– former elements in the Cantor’s chemical composition to promote in situ–forming MC carbides led to interesting interdendritic and intergranular population of TaC [9] and HfC [10] carbides. The script–like morphologies of these carbides, inherited from the solidification mechanisms inducing the re–distribution, between the two phases of the growing {MC + matrix} eutectic compound, of the different elements of the liquid, remarkably improved the creep resistance of the Cantor’s alloy at temperatures of the 1000 °C level [11] for moderate applied stresses (10 MPa). Unfortunately, the low resistance of these alloys to oxidation at these high temperatures was a threat for their sustainability on long times [12]. The responsibility of manganese was pointed out, as well as the chromium content too close to the critical value of 20 wt%. New versions with less Mn and more Cr were thus considered. In the present work, the consequences of these changes of chemical composition of the MC–free and MC–containing carbides alloys, on the refractoriness and on the creep resistance, were considered and investigated with thermal analysis and bending creep tests.

Experimental Six alloys were elaborated by high frequency induction melting (CELES furnace, France), from pure elements (Alfa Aesar, purity > 99.9 wt%), in an atmosphere made of 300 millibars of pure Ar to prevent oxidation and loss of the most oxidable ones of these elements. Three alloys, with as targeted compositions CoNiFeMn0.5 Cr1.5 , {96 wt% CoNiFeMn0.5 Cr1.5 , 3.7 wt%Ta, 0.25 wt%C} and {96 wt% CoNiFeMn0.5 Cr1.5 , 3.7 wt%Hf, 0.25 wt%C}, respectively named “Mn0.5Cr1.5”, “Mn0.5Cr1.5TaC”, and “Mn0.5Cr1.5HfC”, were obtained as ovoid ingots weighing about 40 g. The three initial alloys with equimolarity between Co, Ni, Fe, Mn, and Cr were also elaborated: CoNiFeMnCr, {96 wt% CoNiFeMnCr, 3.7 wt%Ta, 0.25 wt%C}, and {96 wt% CoNiFeMnCr, 3.7 wt%Hf, 0.25 wt%C}, respectively named “1Cr1”, “Mn1Cr1TaC”, and “Mn1Cr1HfC”, for enhancing the

Dependence on Their Mn and Cr Contents of the Microstructures …

661

effects of Mn and Cr on the studied properties, by playing the role of references for comparisons. The six alloys were cut using a metallographic saw to obtain samples for metallography control, {≈2 mm × ≈2 mm × ≈7 mm} parallelepipeds for the thermal analysis tests, and {≈16 mm × ≈1.5–2 mm × ≈1–1.5 mm} (length × width × thickness) parallelepipeds for the creep tests. The parts for metallography control were classically prepared (embedding, grinding, polishing) to obtain mirror–like samples. There microstructures were examined by electron microscopy (JSM6010LA scanning electron microscope (SEM) from JEOL (Japan), acceleration voltage for the electrons beam: 15–20 kV). Imaging was carried out using the back scattered electron mode (BSE), and the chemical composition control was done using Energy Dispersion Spectrometry (EDS) with the spectrometer attached to the SEM. The thermal analyses were carried out using a TG/ATD 92-16.12 analyzer from SETARAM (France). For each alloy, the {2 mm × 2 mm × 7 mm} sample was placed in an alumina crucible. Under a pure Ar flow (2 L/h), the sample was heated at +20 K min−1 to 1100 °C, then at +5K min−1 to 1450 °C (melting), cooled at − 5 K min−1 to 1100 °C (solidification as solid with a more homogeneous chemical composition), heated again +5 K min−1 to 1450 °C (determination of the melting range), cooled at −5 K min−1 to 1100 °C (determination of the solidification range), and finally cooled −20 K min−1 to ambient temperature. The creep tests were carried out using a thermo–dilatometer (TMA 92–16.18) especially equipped to allow performing centered three points flexural creep tests. For each test the {16 mm × 1.5–2 mm × 1–1.5 mm} sample was placed on two alumina rods separated from on another by 12 mm; a third alumina rod—connected to a displacement sensor—was place on the middle of the top face. The tests were performed under a pure Ar flow (2 L/h), with application of the constant load—calculated to produce a maximal tensile stress equal to the wished value (e.g. 20 MPa) in the middle of the bottom face of the sample—using the third rod (the one connected to the sensor). The maximal duration of the test was 150 h. When the sample deformed rapidly and entered in contact with the alumina support (after 1–1.2 mm of deformation), the tests’ duration was shortened.

Results and Discussion Chemical Compositions and Microstructures of the Studied Alloys The obtained chemical compositions of the six alloys are presented in Table 1. The wished contents in all elements were rather well obtained in all cases. Their microstructures in the as-cast states are shown in Fig. 1, only in the case of the carbides–containing alloys (the single–phased “Mn1 Cr1 ” and “Mn0.5 Cr1.5 ” alloys appears as uniformly gray). These SEM/BSE micrographs allow evidencing, as other phase than the dendritic austenitic matrix, the presence of only TaC carbides

662

C. Gay et al.

Table 1 Chemical compositions of the six alloys (average ± standard deviation calculated from five full frame EDS results obtained on five ×250 randomly selected areas) Co

Ni

Fe

Mn

Cr

Ta

Hf

C

Mn1Cr1

20.0 ±0.5

21.5 ±0.5

19.5 ±0.5

19.5 ±0.5

20.5 ±0.5

/

/

/

Mn0.5Cr1.5

20.0 ±0.1

20.5 ±0.3

19.8 ±0.2

8.3 ±0.5

31.3 ±0.4

/

/

/

Mn1Cr1TaC

19.3 ±0.2

20.1 ±0.5

18.6 ±0.5

18.3 ±0.3

19.2 ±0.3

4.5 ±0.4

/

0.25

Mn0.5Cr1.5TaC

19.5 ±0.2

20 ±0.5

19.1 ±0.3

8.4 ±0.2

28.5 ±0.3

4.6 ±0.2

/

0.25

Mn1Cr1HfC

19.9 ±0.3

20.2 ±0.6

18.4 ±0.4

18.2 ±0.2

19.3 ±0.5

/

4 ±1.9

0.25

Mn0.5Cr1.5HfC

19.7 ±0.4

20.1 ±0.3

19.1 ±0.3

8.8 ±0.3

27.8 ±0.7

/

4.5 ±0.6

0.25

Alloys

in the Ta–containing alloys (“Mn1 Cr1 TaC” and “Mn0.5 Cr1.5 TaC”) and of only HfC carbides in the Hf–containing alloys (“Mn1 Cr1 HfC” and “Mn0.5 Cr1.5 HfC”). No other phase is obviously present (notably: no chromium carbides).

Results of the Thermal Analyses The obtained curves are plotted in Fig. 2 for the “Mn1 Cr1 ” and “Mn0.5 Cr1.5 ” alloys, in Fig. 3 for the “Mn1 Cr1 TaC” and “Mn0.5 Cr1.5 TaC” alloys, and in Fig. 4 for the “Mn1 Cr1 HfC” and “Mn0.5 Cr1.5 HfC” alloys. Their exploitation for specifying the temperatures of start of melting and end of melting (heating parts, red) and the temperatures of start of solidification and end of solidification (cooling parts, blue) led to the values presented in Table 2. Obviously, the estimated solidus temperatures (average values of melting start and solidification end) range over the 1267–1331 °C interval while the estimated liquidus temperatures (average values of melting end and solidification start) are between 1302 and 1378 °C. It appears that the solidus temperatures of the carbide– containing alloys (1267–1314 °C) are lower than the ones of the carbide–free alloys (1321–1331 °C), and also that the solidus temperatures of the three “Mn0.5 Cr1.5 ”– type alloys are higher than the “Mn1 Cr1 ”–type. Thus, lower Mn content simultaneous with higher Cr content increases the refractoriness of the alloys while the presence of carbides lowers the refractoriness. The first observation can be explained, in a somewhat simplistic way, by the relatively low melting point of Mn compared to the other elements. The second observation can be more seriously interpreted by the presence of a eutectic compound in the case of the carbides–containing alloys. In addition one can remark that, for the Cantor’s alloy, the melting starts at 1321 °C, that is at a lower temperature than said in earlier studies [4–6].

Dependence on Their Mn and Cr Contents of the Microstructures …

663

Fig. 1 Microstructures of the four alloys containing carbides, in their as-cast condition

First, by reasoning only on the simple criterion relating to the solidus temperature, the carbide–free alloys would be more creep–resistant than the carbide–containing ones, and the “Mn0.5 Cr1.5 ”–type alloys would be each more creep resistant than the “Mn0.5 Cr1.5 ”–type ones. The first assumption is logically certainly false (structural hardening generally predominates over the difference of refractoriness). The second assumption needs to be further investigated.

Some Creep Results Some creep tests were thus performed according to the centered three points flexural method, for some of these alloys, for several conditions of temperatures and stresses. Taking into account the solidus temperatures presented above, the temperatures for these tests were limited to 1100 °C (about 150–200 °C below the lowest

664

C. Gay et al.

Fig. 2 Heat flow versus temperature plotted versus temperature for the two carbide-free alloys

Fig. 3 Heat flow versus temperature plotted versus temperature for the two TaC-containing alloys

Dependence on Their Mn and Cr Contents of the Microstructures …

665

Fig. 4 Heat flow versus temperature plotted versus temperature for the two HfC-containing alloys

Table 2 Temperatures of start (Tms) and end (Tme) of melting and temperatures of start (Tss) and end (Tse) of solidification; calculated values of the estimated values of the solidus and liquidus temperatures

Alloys

Tms (°C)

Tse (°C)

Tme (°C)

Tss (°C)

T solidus (°C) (Tms+Tse)/2

T liquidus (°C) (Tme+Tss)/2

Mn1Cr1

1320

1321

1361

1360

1321

1361

Mn0.5Cr1.5

1344

1317

1382

1374

1331

1378

Mn1Cr1TaC

1268

1266

1325

1278

1267

1302

Mn0.5Cr1.5TaC

1278

1264

1384

1343

1271

1364

Mn1Cr1HfC

1283

1266

1335

1283

1275

1309

Mn0.5Cr1.5HfC

1321

1307

1380

1373

1314

1377

solidus values). In Fig. 5 which concerns only the carbide–free alloys, it seems, for 10 MPa and 1000 °C, that the most refractory alloy among the “Mn1 Cr1 ” alloy and the “Mn0.5 Cr1.5 ” alloy effectively behaves the best. The creep resistance of the “Mn0.5 Cr1.5 ” is thus rather interesting, but it becomes not satisfactory for 20 MPa at the same temperature. MC–strengthened alloys are certainly to be preferred for this higher level of stress. Three of them are tested under 20 MPa, at a higher temperature (1100 °C). In Fig. 6 where the deformation curves are plotted together, this is obviously the “Mn1 Cr1 TaC alloy” which demonstrates the best resistance against

666

C. Gay et al.

Fig. 5 Creep behaviors at 1000 °C of the carbide-free alloys for two levels of constant stress (centered three points flexural mode)

Fig. 6 Creep behaviors under 20 MPa at 1100 °C of some carbide-containing alloys (centered three points flexural mode)

creep. However, its creep performance becomes disappointing at the same temperature when the stress increase beyond 25 MPa (Fig. 7): after 25 h the steady state is progressively replaced by the tertiary creep stage and deformation accelerates until contact of the bottom of the sample with the alumina base after only 40 h (deformation curve now horizontal).

Dependence on Their Mn and Cr Contents of the Microstructures …

667

Fig. 7 Creep behavior under 26 MPa at 1100 °C of the “Mn1 Cr1 TaC” alloy (centered three points flexural mode)

Commentaries Clearly, the contents in Mn (the less refractory element in the Cantor’s composition) and in Cr (the most refractory one) have both an influence of the melting range of the three types of alloys: the carbide–free ones, the TaC–containing ones, and the HfC– containing ones. Decreasing the Mn content and increasing the Cr one at the same time induce an increase in solidus temperature, with possible favorable consequence on the creep resistance. An increase in liquidus temperature can be also noted, and this may influence the castability of the alloys. Concerning the creep resistance, no certain effect was proven with the creep tests which were performed. This is much more the presence or not of TaC or HfC carbides which plays an important role for the creep resistance. The presence of these carbides is compulsory to ensure suitable creep behavior.

Conclusions For uses at high temperatures of the 1000 °C level under stresses the Cantor’s alloy elaborated by classical foundry must be significantly strengthened. The addition carbon and Ta or Hf by targeting contents allowing the development of an interdendritic MC skeleton dense enough is a relevant solution. Some of these alloys seems able to resist more than 100 h for moderate applied stresses, even at temperature as high as 1100 °C. In contrast, the Mn and Cr contents, which influence the melting

668

C. Gay et al.

range, and the solidus temperature in particular, did not show clear effect on the creep behavior. Modifying their contents can be done for improving the oxidation resistance without significant change on the creep resistance.

References 1. Shaffer PTB (1964) High temperature materials. N°1: materials index. Plenum Press Handbooks, New York, USA 2. Samsonov GV (1964) High temperature materials. N°2: properties index. Plenum Press Handbooks, New York, USA 3. Cantor B (2021) Multicomponent high-entropy Cantor alloys. Prog Mater Sci 120:100754. https://doi.org/10.1016/j.pmatsci.2020.100754 4. Glowka K, Zubko M, Swiec P, Prusik K, Albrecht R, Dercz G, Loskot J, Witala B, Stróz D (2020) Microstructure and mechanical properties of Co-Cr-Mo-Si-Y-Zr high entropy alloy. Metals 10:1456. https://doi.org/10.3390/met10111456 5. Campari EG, Casagrande A, Colombini E, Gualtieri ML, Veronesi P (2021) The effect of Zr addition on melting temperature, microstructure, recrystallization and mechanical properties of a Cantor high entropy alloy. Materials 14:5994. https://doi.org/10.3390/ma14205994 6. Straumal BB, Kulagin R, Baretzky B, Anisimova NY, Kiselevskiy MV, Klinger L, Straumal PB, Kogtenkova OA, Valiev RZ (2022) Severe plastic deformation and phase transformations in high entropy alloys: a review.Crystals 12:54. https://doi.org/10.3390/cryst12010054 7. Chen S, Qi C, Liu J, Zhang J, Wu Y (2022) Recent advances in W-containing refractory high-entropy alloys—an overview. Entropy 24:1553. https://doi.org/10.3390/e24111553 8. Donachie MS, Donachie SJ (2002) Superalloys: a technical guide, 2nd edn. ASM International, Materials Park, USA 9. Berthod P (2022) As-cast microstructures of high entropy alloys designed to be TaCstrengthened. J Metall Mater Res 5:1–10. https://doi.org/10.30564/jmmr.v5i2.4685 10. Berthod P (2022) As-cast microstructures of HEA designed to be strengthened by HfC. J Eng Sci Innov C Chem Eng Mater Sci Eng 7:305–314. https://jesi.astr.ro/wp-content/uploads/2023/ 03/3_Patrice-Berthod.pdf 11. Berthod P (2023) Strengthening against creep at elevated temperature of HEA alloys of the CoNiFeMnCr type using MC-carbides. In: TMS 2023 152nd annual meeting and exhibition supplemental proceedings, pp 1103–1111. https://doi.org/10.1007/978-3-031-22524-6_102 12. Berthod P (2023) High temperature oxidation of CoNiFeMnCr high entropy alloys reinforced by MC-carbides. In: TMS 2023 152nd annual meeting and exhibition supplemental proceedings, pp 933–941. https://doi.org/10.1007/978-3-031-22524-6_86

Microstructural Analysis of MoNbZrTiV Refractory High-Entropy Alloy Developed via High-Energy Mechanical Alloying Marvin S. Tolentino, Aisa Grace D. Custodio, Gobinda C. Saha, and Clodualdo Aranas Jr.

Abstract Refractory high-entropy alloys (RHEAs) are an emerging group of materials exhibiting interesting functional and structural properties under hightemperature operations. In this work, MoNbZrTiV RHEA particles were developed via high-energy mechanical alloying, employing sequential and conventional milling approaches. Microstructural analysis was done through scanning electron microscopy, and the corresponding energy-dispersive X-ray spectroscopy confirmed the successful formation of the alloy. Results showed that as the milling progressed, dissolution of the elements and homogenization of the alloy were greatly governed by the physical properties of the elements. Thermodynamic calculations predicted the formation of a solid solution with a body-centered cubic (BCC) crystal structure. The reduced particle size after 24 h of milling was mainly due to the brittle nature of the elements having BCC and hexagonal close-packed (HCP) crystal structures, in addition to strain hardening and the frequent tendency of fracturing than cold welding during milling. Keywords Refractory · High-entropy alloys · Mechanical alloying · MoNbZrTiV

M. S. Tolentino (B) · A. G. D. Custodio · G. C. Saha Nanocomposites and Mechanics Laboratory, Mechanical Engineering, University of New Brunswick, Fredericton, NB E3B 5A3, Canada e-mail: [email protected] A. G. D. Custodio e-mail: [email protected] G. C. Saha e-mail: [email protected] M. S. Tolentino · A. G. D. Custodio · C. Aranas Jr. Alloy Design Research Laboratory, Mechanical Engineering, University of New Brunswick, Fredericton, NB E3B 5A3, Canada e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_57

669

670

M. S. Tolentino et al.

Introduction With the advent of metals research, the alloying process has been widely used with the aim of meeting the demand for metallic materials for high-performance and complex function applications. This led to several significant research breakthroughs that eventually gave rise to the development of Ni- and W-based, and refractory superalloys with outstanding mechanical properties and functionalities that overcome those of conventional metals and alloys [1]. In the past twenty (20) years, multiple alloys have been studied and various element combinations have been exploited which pioneered the discovery of high-entropy alloys (HEAs) with promising properties that can even surpass the properties of previously known superalloys [2–4]. Contrary to the conventional alloys in which the alloying element/s are introduced to the principal alloying matrix in small quantities, HEAs consist of at least five (5) principal elements with concentrations varying from 5 to 35 atomic % [3]. The potential of HEAs has been extended to high-temperature aerospace applications and refractory elements, known for their high melting points, have been introduced. Senkov et al. [5] were able to develop refractory high-entropy alloys (RHEAs) consisting of WNbMoTa and WNbMoTaV that exhibited a single-phase body-centered cubic (BCC) crystal structure and a notable increase in Vickers microhardness with the addition of V. RHEAs comprising mainly of ZrTiHfVNb and ZrTiHfNbMoTa with remarkable strength and plasticity had been developed by Chen et al. [6] by accounting for the resulting valence electron concentrations (VEC) of the alloys. In the study conducted by Juan et al. [7], they were able to observe the simultaneous improvement of strength and ductility of HfNbTaTiZr as a result of grain refinement at varying annealing conditions. Among other fabrication routes to produce RHEAs, the solid-state route of powder metallurgy (PM) has been identified to control the microstructure and hinder phase segregation which contributes to the alloy’s compositional accuracy [8, 9]. Initially, PM involves feedstock powder preparation such as mechanical alloying (MA), followed by a consolidation process. In MA, blending or mixing of the alloying elements on the atomic level is induced by repeated cold welding and fracturing during high-energy ball milling. Hence, various milling parameters can be used to attain RHEA powders with homogeneous microstructures and refined grains [1, 10]. Vaidya et al. [11] explored a sequential MA method in which the alloying elements are milled in a stepwise approach. They were able to prove the path dependency of phase formation in MA. The main objective of this research is to develop MoNbZrTiV RHEA powder via sequential and conventional MA and to conduct preliminary qualitative and quantitative microstructural investigation of the powders produced. Sequential MA focused on the stepwise addition of Ti and V due to their potential to improve mechanical properties [12, 13]. Thermodynamic calculations were also done as an initial analysis of the phase formation involved in the MA of MoNbZrTiV.

Microstructural Analysis of MoNbZrTiV Refractory High-Entropy …

671

Experimental Methods The starting elemental powders consisting of Mo, Nb, Zr, Ti, and V (each having > 99% purity) with morphologies and average size presented in Fig. 1 were purchased from NanoChemazone Inc., Canada, and used as received. The elemental powders (all at equiatomic concentrations) were pre-mixed and milled according to the design of experiment (DoE) presented in Table 1. The progression of milling time was based on a similar study conducted by Kang et al. [14] from which they found that after 6 h of milling WNbMoTaV RHEA, a single-phase BCC was obtained with refinement in average particle and crystallite sizes, and a homogenized chemical composition was observed. For each of the sequential and conventional MA processes, 100.0 g of samples were prepared in 304 stainless steel vial with grinding balls (6.0 mm diameter), maintaining a 10:1 ball-to-powder ratio (BPR). The samples were milled using a planetary ball mill (PQ-N04 series Gear-Drive 0.4L) at 580 rpm for 24 h, with 6-h interval. 5.0 g of samples were obtained every 6 h for analysis. Further, stearic acid (3.0 wt. %) was used as a process control agent (PCA) during milling to prevent agglomeration. The particle morphology of the samples was investigated using a scanning electron microscope (SEM) (JEOL JSM-6010LA) and the energy-dispersive spectroscopy (EDS) analysis was done to assess the elemental homogenization during milling.

Fig. 1 a Micrographs of the elemental powders, and b schematic diagram of MA

672

M. S. Tolentino et al.

Table 1 Design of experiment (DoE) for the MA of MoNbZrTiV RHEA Milling process

Composition

Designation

Sequential

MoNbZr (as received)

S0

Conventional

Milling time, [h] 0

MoNbZr

S6

6

MoNbZr + Ti

S12

12

MoNbZrTi + V

S18

18 24

MoNbZrTiV

S24

MoNbZrTiV (as received)

C0

0

MoNbZrTiV

C6

6

C12

12

C18

18

C24

24

Results and Discussion During milling, the individual powders of Mo, Nb, Zr, Ti, and V (Fig. 1) are subjected to repeated deformation and fracture events, which break down the larger particles into smaller ones as seen in Fig. 2. It is observed from the SEM images that irregular shape particles at the start of milling became finer particles with near-spherical shapes after 6 h of conventional mechanical alloying. On the other hand, this change in particle morphology was observed after 12 h of sequential milling when Ti was added. MA can result in finer grain size, increased homogeneity, and improved distribution of alloying elements within the particle. The process of homogenizing alloying elements involves the mutual diffusion of atoms from various elements [15]. This diffusion requires overcoming two distinct energy barriers: (1) for atoms to vacate their original lattice positions and (2) for these atoms to occupy new lattice sites. The initial barrier primarily depends on the binding energy or bond strength between the lattice’s original atoms, which is highly influenced by the material’s melting temperature. Those with low melting temperatures diffuse away more easily from the original lattice sites than those with higher melting temperatures. The second barrier primarily relies on the compatibility between the elements involved in the diffusion process. The compatibility of the different materials can be predicted by the thermodynamic parameters and other factors based on the Hume-Rothery rules—mixing entropy (Smix ), mixing enthalpy (Hmix ), atomic size mismatch (δ), and valence electron concentration (VEC). Table 2 shows the calculated values of the said parameters for the developed MoNbZrTiV RHEA based on the equations in the literature [16–18]. Moreover, accounting for the criteria presented in Table 3 for each parameter, it is suggested that S6, comprising of MoNbZr, would form a body-centered would form a BCC solution but incomplete dissolution of the elements is expected due to lower Smix . All other compositions involving four (4) to (5) elements (S12 to S24, C6 to C24) are predicted to form a BCC solid solution.

673

Fig. 2 Particle morphology with milling time progression

Microstructural Analysis of MoNbZrTiV Refractory High-Entropy …

674

M. S. Tolentino et al.

Table 2 Calculated parameters for the phase prediction of the MoNbZrTiV   kJ   Designation Smix , molJ K Hmix , mol Composition MoNbZr

S6

9.13

− 3.56

δ

VEC

6.91

5.00

MoNbZrTi

S12

11.53

− 2.50

5.99

4.75

MoNbZrTiV

S18, S24 C6, C12, C18, C24

13.38

− 2.72

6.85

4.80

Table 3 Criteria for the phase prediction based on the calculated parameters Parameter

Criteria

Reference/s

Smix

11 ≤ Smix ≤ 19.5 J/mol K, solid solution

[17]

Hmi x

− 22 ≤ Hmix ≤ 7 kJ/mol, solid solution Hmix < 0 (negative), formation of intermetallic compounds Hmix > 0 (positive), elemental segregation

[17, 18]

δ

0 ≤ δ ≤ 8.5, solid solution

[18]

VEC

VEC ≥ 8, FCC solid solution VEC < 6.87, BCC solid solution

[19]

Figure 3 shows the SEM–EDS results for mapping (Fig. 3a) and spectrum (Fig. 3b, c) analyses for both sequential and conventional milling processes every 6 h of milling. The elemental powders were milled at equiatomic concentrations and based on Fig. 3a, the homogeneous distribution of the individual elements was observed as the milling progressed. Table 4 presents the physical properties of the elements that influenced their dissolution during MA. Quantitatively, it can be seen from Fig. 3b, c that the dissolution of the individual elements to attain microscale homogenization was greatly affected by their melting points and crystal structure. Mo, Nb, and V with BCC crystal structures and high melting points exhibited slow diffusion compared to Zr and Ti with hexagonal close-packed (HCP) crystal structures and relatively lower melting points. Stronger atomic bonds were expected for the elements with high melting points [15, 20], which was the reason for their slow solid-state diffusion even after 24 h of milling. After 24 h of milling, the average particle size for both sequential and conventional milling had decreased to 10.805 µm and 4.57 µm, respectively, indicating that extended milling of RHEA can result in a surface morphology similar to that of clusters/agglomerates of submicron particles. Due to the brittle nature of the elements (BCC and HCP crystal structures), and the work hardening phenomenon that occurred during MA, increased milling time resulted in higher tendency for fragmentation and fracturing [14, 15]. Figure 4 shows the morphologies of the particle after 24 h of sequential and conventional MA.

Fig. 3 a EDS analysis mapping and chemical composition of b sequentially and c conventionally milled MoNbZrTiV with milling time progression

Microstructural Analysis of MoNbZrTiV Refractory High-Entropy … 675

676

M. S. Tolentino et al.

Table 4 Physical properties of the elements of MoNbZrTiV RHEA Component element

Atomic radius, [Å]

Crystal type

Melting point, [°C]

Mo

1.363

BCC

2616

Nb

1.429

BCC

2467

Zr

1.603

HCP

1851

Ti

1.462

HCP

1659

V

1.316

BCC

1901

Fig. 4 Micrographs of MoNbZrTiV particles after 24 h of sequential (S24) and conventional (C24) milling, respectively

Conclusions The MoNbZrTiV RHEA was successfully fabricated via sequential and conventional MA approaches. The dissolution of the elements was qualitatively observed with the results of SEM–EDS mapping. The homogenization of the elements was quantitatively determined with the spectrum analysis and was found to be highly dependent on the melting points and crystal structures of the elements. Thermodynamic parameters such as the mixing entropy (Smix ), mixing enthalpy (Hmix ), atomic size mismatch (δ), and valence electron concentration (VEC) were calculated, and predicted the formation of BCC solid solution. Continuous milling for up to 24 h resulted into the decrease in particle size for both sequential and conventional milling, exhibiting cluster/agglomerated-like morphology.

Microstructural Analysis of MoNbZrTiV Refractory High-Entropy …

677

Acknowledgements The authors would like to acknowledge with gratitude the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Foundation for Innovation (CFI), Transport Canada, the Atlantic Canada Opportunities Agency (ACOA), and the New Brunswick Innovation Foundation (NBIF) for funding this research endeavor.

References 1. Senkov ON, Miracle DB, Chaput KJ, Couzinie JP (2018) Development and exploration of refractory high entropy alloys—a review. J Mater Res 33(19):3092–3128. https://doi.org/10. 1557/jmr.2018.153 2. Cantor B, Chang ITH, Knight P, Vincent AJB (2004) Microstructural development in equiatomic multicomponent alloys. Mater Sci Eng A 375–377(1–2):213–218. https://doi.org/ 10.1016/j.msea.2003.10.257 3. Yeh JW et al (2004) Nanostructured high-entropy alloys with multiple principal elements: Novel alloy design concepts and outcomes. Adv Eng Mater 6(5):299–303. https://doi.org/10. 1002/adem.200300567 4. Miracle DB, Miller JD, Senkov ON, Woodward C, Uchic MD, Tiley J (2014) Exploration and development of high entropy alloys for structural applications. Entropy 16(1):494–525. https:// doi.org/10.3390/e16010494 5. Senkov ON, Wilks GB, Miracle DB, Chuang CP, Liaw PK (2010) Refractory high-entropy alloys. Intermetallics 18(9):1758–1765. https://doi.org/10.1016/j.intermet.2010.05.014 6. Chen Y, Li Y, Cheng X, Wu C, Cheng B, Xu Z (2018) The microstructure and mechanical properties of refractory high-entropy alloys with high plasticity. Materials (Basel) 11(2). https:// doi.org/10.3390/ma11020208 7. Juan CC et al (2016) Simultaneously increasing the strength and ductility of a refractory high-entropy alloy via grain refining. Mater Lett 184:200–203. https://doi.org/10.1016/j.mat let.2016.08.060 8. Torralba JM, Alvaredo P, García-Junceda A (2020) Powder metallurgy and high-entropy alloys: update on new opportunities. Powder Metall 63(4):227–236. https://doi.org/10.1080/ 00325899.2020.1807713 9. Manogar B, Yang F, Bolzoni L (2022) Correlation between microstructure and tensile properties of powder metallurgy Ti-6Nb-x(Fe or Mn) alloys. J Alloys Compd 926:166805. https://doi. org/10.1016/j.jallcom.2022.166805 10. Gao MC, Liaw PK, Yeh JW, Zhang Y (2016) High-entropy alloys: fundamentals and applications. High-Entropy Alloy Fundam Appl 1–516. https://doi.org/10.1007/978-3-319-270 13-5 11. Vaidya M, Prasad A, Parakh A, Murty BS (2017) Influence of sequence of elemental addition on phase evolution in nanocrystalline AlCoCrFeNi: Novel approach to alloy synthesis using mechanical alloying. Mater Des 126:37–46. https://doi.org/10.1016/j.matdes.2017.04.027 12. Han ZD et al (2017) Effect of Ti additions on mechanical properties of NbMoTaW and VNbMoTaW refractory high entropy alloys. Intermetallics 84:153–157. https://doi.org/10. 1016/j.intermet.2017.01.007 13. Wang M, Ma ZL, Xu ZQ, Cheng XW (2021) Effects of vanadium concentration on mechanical properties of VxNbMoTa refractory high-entropy alloys. Mater Sci Eng A 808. https://doi.org/ 10.1016/j.msea.2021.140848 14. Kang B, Lee J, Ryu HJ, Hong SH (2018) Ultra-high strength WNbMoTaV high-entropy alloys with fine grain structure fabricated by powder metallurgical process. Mater Sci Eng A 712:616– 624. https://doi.org/10.1016/j.msea.2017.12.021 15. Qiao Y et al (2020) Preparation of TiZrNbTa refractory high-entropy alloy powder by mechanical alloying with liquid process control agents. Intermetallics 126:106900. https://doi.org/10. 1016/j.intermet.2020.106900

678

M. S. Tolentino et al.

16. Zhang Y, Zhou YJ, Lin JP, Chen GL, Liaw PK (2008) Solid-solution phase formation rules for multi-component alloys. Adv Eng Mater 10(6):534–538. https://doi.org/10.1002/adem.200 700240 17. Guo S, Liu CT (2011) Phase stability in high entropy alloys: Formation of solid-solution phase or amorphous phase. Prog Nat Sci Mater Int 21(6):433–446. https://doi.org/10.1016/S10020071(12)60080-X 18. Martin P, Madrid-Cortes CE, Cáceres C, Araya N, Aguilar C, Cabrera JM (2022) HEAPS: a user-friendly tool for the design and exploration of high-entropy alloys based on semi-empirical parameters. Comput Phys Commun 278:108398. https://doi.org/10.1016/j.cpc.2022.108398 19. Guo S, Ng C, Lu J, Liu CT (2011) Effect of valence electron concentration on stability of fcc or bcc phase in high entropy alloys. J Appl Phys 109(10). https://doi.org/10.1063/1.3587228 20. Huang M, Jiang J, Wang Y, Liu Y, Zhang Y (2022) Effects of milling process parameters and PCAs on the synthesis of Al0.8 Co0.5 Cr1.5 CuFeNi high entropy alloy powder by mechanical alloying. Mater Des 217:110637. https://doi.org/10.1016/j.matdes.2022.110637

Thermo-mechanical Behavior of HEA Alloys Containing Interdendritic MC Carbides Patrice Berthod, Lionel Aranda, and Anne Verniere

Abstract Casting allows obtaining in situ composites associating a HEA matrix and refractory carbides. The presence of MC carbides allows benefiting simultaneously from the intrinsic good creep resistance of the HEA matrix, and from the delayed {steady state to tertiary} transition of the creep deformation given by the good cohesion between neighbor dendrites. However, the difference in thermal expansion behavior between matrix and carbides may induce curious geometrical behavior of the whole alloy at high temperature, as earlier found for cobalt-based alloys, for instance. This work aims to investigate the dimensional behavior of MC-strengthened HEA alloys at high temperature during heating and an isothermal stage, in order to observe the consequences of the internal interaction between matrix and carbides, such as visco-plastic deformations. Effectively, in contrast with the carbides-free quinary HEA alloys based on Co, Ni, Fe, Mn and Cr, the alloys with the same compositions as these later ones but containing TaC or HfC carbides behave curiously during heating and during the 1200 °C isothermal stage. Indeed, contraction occurs when arriving to 1200 °C and continues isothermally but slowing down. In parallel, it was also noticed that a decrease in Mn content and an increase in Cr content lowers a little thermal expansion coefficient. Keywords High entropy alloys · CoNiFeMnCr-based HEAs · Thermal dilatometry · Dimensional behavior · TaC and HfC influence

P. Berthod (B) · A. Verniere Université de Lorraine, Campus Victor Grignard, 54500 Vandoeuvre-lès-Nancy, France e-mail: [email protected] P. Berthod · L. Aranda · A. Verniere Institut Jean Lamour, 2 Allée André Guinier, Campus ARTEM, 54000 Nancy, France © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_58

679

680

P. Berthod et al.

Introduction In the wide family of high entropy alloys, there are numerous ones which can apply to work at high temperatures in parallel with, or possibly in substitution to, classical superalloys [1] with which they share the same elements. For the hot conditions of service, in addition to the mechanical [2] and chemical [3] resistances it can be asked to these high temperature alloys to demonstrate acceptable dimensional behavior in thermal cycling conditions. This can first concern the thermal expansion coefficient (α), generally wished the smallest possible but which stays not far from the ones of pure Ni, Co, and Fe (their base elements) which are about 15–20 × 10–6 K−1 [4, 5]. But particular dimensional behavior can also take place when hard ceramic particles with low α values are present in significant quantities mixed with a metallic matrix the α of which is higher. This was, for example, observed in cobalt-based or nickel/ iron-based alloys containing well interconnected TaC carbides closely mixed with matrix [6, 7]. Recently a new concept was explored by adding TaC or HfC carbides to a Cantor’s base [8] using foundry. Thanks to solidification, the obtained alloys were composed of a dendritic CoNiFeMnCr equimolar matrix closely mixed with script-like eutectic TaC or HfC carbides [9, 10]. These carbides, the in situ formation of which took place at the end of solidification according to the liquid → {additional matrix + MC} eutectic reaction, exhibit a script-like morphology resulting from the conditions required by the redistribution of all the elements during the growth of the interdendritic eutectic compound [11]. The presence and the particular morphology of these hard particles strategically located in the grain boundaries and interdendritic spaces allowed spectacularly enhancing the creep resistance of the polycrystalline cast Cantor’s alloy [12], similarly to what one obtained earlier with these eutectic carbides in the cases of Co-based and Ni-based superalloys [13]. Thus, efficient for mechanically strengthen alloys at high temperature, these script TaC and HfC carbides may also induce inappropriate dimensional evolutions. This is this point which will be studied here for cast MC–reinforced {Co, Ni, Fe, Mn Cr}-based HEAs.

Experimental The alloys considered for this work are two MC–reinforced equimolar CoNiFeMnCr (Cantor’s) high entropy alloys (MC = either TaC or HfC) and two MC–reinforced Mn–poor Cr–enriched CoNiFeMnCr (modified Cantor’s) alloys. As references for comparison of results, one also considered their carbide-free versions. They are named “Mn1Cr1TaC”, “Mn1Cr1HfC”, “Mn0.5Cr1.5TaC”, “Mn0.5Cr1.5HfC”, “Mn1Cr1”, and “Mn0.5Cr1.5” respectively. All were elaborated by melting pure elements together under an inert atmosphere, using a high frequency induction furnace (HFIF; manufacturer: CELES, France). The obtained ingots, egg-shaped and weighing close to 40 g, were cut to obtain parts for metallography control after embedding, grinding, and polishing until obtaining a

Thermo-mechanical Behavior of HEA Alloys Containing Interdendritic …

681

mirror-like state, as well as small flat parts with two main faces parallel to one another for the dilatometry tests. The first parts (metallography) were observed using a scanning electron microscope (SEM; manufacturer: JEOL/Japan, JSM 2010LA model) in the back scattered electrons mode (BSE) to control the obtained microstructures, and their obtained chemical compositions were checked by Energy Dispersion Spectrometry (EDS) using the device attached to the SEM. The second parts were placed between two alumina disks in the high temperature thermos-dilatometer (manufacturer: SETARAM, France) in which they were subjected to the following thermal cycle: heating from room temperature up to 1200 °C at 10°C min−1 , 1 h-stage at 1200 °C, cooling down to room temperature at − 10°C min−1 . A sensor continuously measured the evolution of the thickness of the sample.

Results and Discussion Chemical Compositions the Studied Alloys The chemical compositions measured by EDS are communicated in Table 1. The three “Mn1Cr1(TaC or HfC)” alloys have the same weight contents in Co, in Ni, in Fe, in Mn, and in Cr and consequently, due to the similar molar masses of these elements, it is the same for their atomic contents. The Co, Ni, and Fe weight contents of the “Mn0.5Cr1.5” are also similar to one another, while the Mn content is divided by 2 and the Cr content is multiplied by 1.5. The “Mn1Cr1TaC” and “Mn0.5Cr1.5TaC” alloys contain about 4.5 wt% Ta while, similarly, the “Mn1Cr1HfC” and “Mn0.5Cr1.5HfC” alloys contain also about 4.5 wt% Hf. These contents in Ta and in Hf are a little exaggerated since Ta and Hf were introduced for targeting 3.7 wt%. This overestimation is classical for these types of microstructures in which the carbides-former elements are more exposed to the electron beam during the EDS measurements because of their high hardness and their prominence after final polishing. Carbon was not controlled by EDS (too light element present in too low quantity in the chemical composition), but it was considered as well respected (equal to the targeted value 0.25 wt% C) after other deduction.

The As-Cast Microstructures of the Studied Alloys The as-cast microstructures are illustrated by SEM/BSE micrographs in Fig. 1, but only of the MC-containing alloys). Indeed, in absence of any second phase (no carbides) the micrographs taken on the “Mn1Cr1” and “Mn0.5Cr1.5” alloys are uniformly gray. One can clearly distinguish the script-like TaC and HfC carbides which are located in the inderdendritic spaces as the white phase in the eutectic compounds.

Ni

21.5 ± 0.5

20.5 ± 0.3

20.1 ± 0.5

20 ± 0.5

20.2 ± 0.6

20.1 ± 0.3

Co

20.0 ± 0.5

20.0 ± 0.1

19.3 ± 0.2

19.5 ± 0.2

19.9 ± 0.3

19.7 ± 0.4

Alloys ↓

MnlCrl

Mn0.5Cr1.5

MnlCr1TaC

Mn0.5Cr1.5TaC

MnlCrlHfC

Mn0.5Cr1.5HfC

19.1 ± 0.3

18.4 ± 0.4

19.1 ± 0.3

18.6 ± 0.5

19.8 ± 0.2

19.5 ± 0.5

Fe

8.8 ± 0.3

18.2 ± 0.2

8.4 ± 0.2

18.3 ± 0.3

8.3 ± 0.5

19.5 ± 0.5

Mn

27.8 ± 0.7

19.3 ± 0.5

28.5 ± 0.3

19.2 ± 0.3

31.3 ± 0.4

20.5 ± 0.5

Cr

–

–

4.6 ± 0.2

4.5 ± 0.4

–

–

Ta

4.5 ± 0.6

4 ± 1.9

–

–

–

–

Hf

0.25

0.25

0.25

0.25

–

–

C

Table 1 Chemical compositions (weight contents) of the studied alloys (average and standard deviation calculated from five full frame EDS results obtained on five × 250 randomly chosen areas)

682 P. Berthod et al.

Thermo-mechanical Behavior of HEA Alloys Containing Interdendritic …

683

Fig. 1 As-cast microstructures of the four carbides—containing alloys (SEM/BSE micrographs)

Thermal Expansion Behavior During Heating The thermal expansion curves plotted as deformation versus temperature are presented in Fig. 2 for the “Mn1Cr1”, “Mn1Cr1TaC”, and “Mn1Cr1HfC” alloys, and in Fig. 3 for the “Mn0.5Cr1.5”, “Mn0.5Cr1.5TaC”, and “Mn0.5Cr1.5HfC” alloys, with the same scales on the ordinate axis. The two quinary alloys dilated rather linearly with the increase in temperature, reaching about 2.5 % of relative deformation when arriving at 1200 °C for the “Mn1Cr1” alloy, more than the final value of about 2% of relative deformation for the “Mn0.5Cr1.5” alloy. Expansion during heating was also linear for the “Mn1Cr1TaC” alloy. In contrast, the curves obtained for the three other alloys, “Mn1Cr1HfC”, “Mn0.5Cr1.5TaC”, and “Mn0.5Cr1.5HfC”, were linear only up to 850 or 950 °C and their end was affected by a decrease in expansion rate, and even an inversion of expansion (i.e. contraction) even if temperature was still increasing.

684

P. Berthod et al.

Fig. 2 Thermal expansion curves of the “Mn1Cr1”-type alloys

Fig. 3 Thermal expansion curves of the “Mn0.5Cr1.5”-type alloys

Dimensional Behavior During the Isothermal Stage The result of thickness monitoring during the 1200 °C isothermal stage is presented in Fig. 4 for the “Mn1Cr1”, “Mn1Cr1TaC”, and “Mn1Cr1HfC” alloys, and in Fig. 5 for the “Mn0.5Cr1.5”, “Mn0.5Cr1.5TaC”, and “Mn0.5Cr1.5HfC” alloys, with the same scales on the ordinate axis. Obviously, the three alloys (“Mn1Cr1”, “Mn0.5Cr1.5”, and “Mn1Cr1TaC”) for which the expansion was quite linear from room temperature up to 1200 °C did not know thereafter particular dimensional behavior. For the three other alloys (“Mn1Cr1HfC”, “Mn0.5Cr1.5TaC”, and “Mn0.5Cr1.5HfC”) the decrease in thickness continued during the isothermal stage, more (“Mn1Cr1HfC” and “Mn0.5Cr1.5TaC”) or less (“Mn0.5Cr1.5HfC”).

Thermo-mechanical Behavior of HEA Alloys Containing Interdendritic …

685

Fig. 4 Dimensional evolution of the “Mn1Cr1”-type alloys during the 1 h-stage at 1200 °C

Fig. 5 Dimensional evolution of the “Mn0.5Cr1.5”-type alloys during the 1 h-stage at 1200 °C

Commentaries The carbide-free alloys regularly extended during the heating and stayed rather stable during the isothermal stage preceding the cooling return from 1200 °C to room temperature. No particular event was to be noted for these single-phased austenitic alloys. This was not the same for the alloys in which carbides were present in quantity high enough to allow MC forming a more or less interconnected rigid skeleton: thermal expansion started slowing down when temperature had become high enough (around 900 °C) and an inversion of thickness evolution occurred before reaching 1200 °C. This inversion continued during the isothermal stage but slower and slower, tending obviously to a stabilization. This phenomenon, which was earlier encountered and explained for Co-, Ni-, and/ or Fe-based cast alloys containing also interdendritic script-like MC carbides, can be described as follows (illustration in Fig. 6).

686

P. Berthod et al.

Fig. 6 Scheme illustrating the internal stresses development with the increase in temperature and of the resulting dimensional changes for the whole alloy

1–2/ during a first part of heating both matrix and carbides extend but with more and more mechanical interaction between them since the average thermal expansion coefficient (TCE) of the matrix is twice the carbides one (approximately: 20 × 10−6 K−1 against 10 × 10−6 K−1 ); the global expansion of the alloy (and of matrix and carbides) is intermediate of the natural one of the matrix (which should be faster if alone) and the natural one of the carbides (which should be slower if alone); 2–3/ the interaction of matrix and carbides intensifies with the increase in temperature and the carbides skeleton is subjected to more and more traction under the influence of matrix while matrix is subjected to more and more compression under the effect of carbides; the global expansion of the whole alloy continues; 3–4/ near 900 °C and beyond, matrix starts being weak while carbides are still rigid; consequently carbides force matrix to deform plastically in compression, this allowing carbides to be less stressed in traction; the global expansion of the alloy is replaced by a global contraction; 4–5/ during the stage at the maximal temperature (1200 °C) the tensile constrains known by the carbide skeleton continues their relaxation, taking benefit from the visco-plastic compressive deformation of the matrix; the global contraction of the whole alloy slows down tending to an equilibrium; One must notice that no such inversion to contraction occurred for the MCcontaining “Mn1Cr1TaC” alloy. This stay to be understand. Another interesting observation concern the thermal expansion coefficient values of all the alloys during heating or only the first part of heating (Table 2). Obviously, the TCE of the “Mn0.5Cr1.5”-type alloys is all lower than the ones of the “Mn1Cr1”type alloys. It seems that decreasing the Mn content and increasing the Cr one, what

Thermo-mechanical Behavior of HEA Alloys Containing Interdendritic …

687

Table 2 Synthesis of the exploitation of the thermal expansion curves and of the curves of isothermal thickness evolution Alloys ↓

Average a on the linear part

Contraction near the end of heating?

Isothermal contraction?

Mn1Cr1

23.8 × 10–6 K−1

No

No

Mn0.5Cr1.5

l8.2 × 10–6 K−1

No

No

Mn1Cr1TaC

22.6 ×

K−1

No

No

Mn0.5Cr1.5TaC

20.9 × 10–6 K−1

Yes

Yes

Mn1Cr1HfC

23.8 ×

K−1

Yes

Yes

Mn0.5Cr1.5HfC

16.1 × 10–6 K−1

Yes

Yes

10–6 10–6

was done to improve the oxidation in high temperature of these alloys [14], has this second beneficial effect. If confirmed, this stay to understand.

Conclusions MC carbides, very useful for the creep resistance at high temperature of cast Cantor’s alloys and derivatives, may cause dimensional stability problems when temperature varies. Among the HEA alloys studied here, the ones containing MC, extrapolated from some cobalt-based or nickel-based alloys designed according to the same {matrix + MC} concept, present similarities of behavior with these previous alloys. This concerns the creep resistance improvement, but also the matrix–MC internal interaction problem, both earlier encountered with the Co-based and Ni8based alloys. A possible solution can be to strengthen matrix by solid solution or by precipitation of reinforcing particles, to allow it resisting more efficiently to the compressive action of the carbides.

References 1. Sims CT, Hagel WC (1972) The superalloys. Wiley, New York 2. Donachie MS, Donachie SJ (2002) Superalloys: a technical guide, 2nd edn. ASM International, Materials Park 3. Young DJ (2008) High temperature oxidation and corrosion of metals. Elsevier Corrosion Series, Amsterdam, The Netherlands 4. Shaffer PTB (1964) High temperature materials. N°1: materials index. Plenum Press Handbooks, New York 5. Samsonov GV (1964) High temperature materials. N°2: Properties Index. Plenum Press Handbooks, New York 6. Berthod P, Heil C, Aranda L (2010) Influence of the morphologic evolution of the eutectic carbides at high temperature on the thermal expansion behavior of refractory cast alloys. J Alloys Compd 504(1):243–250

688

P. Berthod et al.

7. Berthod P, Aranda L, Hamini Y (2011) Thermal expansion of chromium–rich iron–based or iron/nickel-based alloys reinforced by tantalum carbides. Physicochemical Mechanics of Materials 3:46–52 8. Cantor B (2021) Multicomponent high-entropy Cantor alloys. Prog Mater Sci 120:100754 9. Berthod P (2022) As-cast microstructures of high entropy alloys designed to be TaC–strengthened. J Metal Mater Res 5:1–10 10. Berthod P (2022) As–cast microstructures of HEA designed to be strengthened by HfC. J Eng Sci Innov C. Chem Eng Mater Sci Eng 7:305–314 11. Kurz W, Fisher DJ (1989) Fundamentals of solidification, 3rd edn. Trans Tech Publications, Aedermannsdorf 12. Berthod P (2023) Strengthening against creep at elevated temperature of HEA alloys of the CoNiFeMnCr type using MC-Carbides. In: TMS 2023 152nd Annual Meeting & Exhibition Supplemental Proceedings pp 1103–1111. 13. Berthod P, Conrath E (2014) Mechanical and chemical properties at high temperature of {M-25Cr}-based alloys containing hafnium carbides (M=Co, Ni or Fe): creep behavior and oxidation at 1200°C. J Mater Sci Technol Res 1:7–14 14. Spaeter P, Gay C, Chenikha N, Medjahdi G, Vernière A, Rapin C, Aranda L, Berthod P (2023) Oxidation behavior at 1000°C of low-Mn high–Cr {Cantor’s HEA}-based alloys strengthened or not by MC carbides. Preprints 2023, 2023071329. https://doi.org/10.20944/preprints202 307.1329.v1

Part XVIII

Advances in Surface Engineering VI

A Study on the Wear Behavior of Al2 Ce-p Reinforced Al Matrix Composite Layers at an Elevated Temperature Mertcan Kaba, Sezgin Cengiz, Faiz Muhaffel, and Hüseyin Çimeno˘glu

Abstract This study focuses on fabricating Al matrix composite layers on commercially pure Al and 7075 alloy by hot pressing to improve wear resistance at elevated temperatures. As a reinforcement particle, Al2 Ce intermetallic particles synthesized by vacuum arc melting was chosen for its better chemical compatibility with Al matrix. Structural characterizations revealed the good binding between Al2 Ce-p and Al matrix and the success of Al2 Ce-p in increasing hardness of Al and 7075 alloy. Results of the wear tests conducted at 200 °C against alumina balls under the load of 2 N showed 2.6- and 6.0-times lower wear rate for the Al matrix composite layer covered and 7075 matrix composite layer covered samples as compared to their monolithic states, respectively. Keywords Al · 7075 · Composite · Al2 Ce intermetallic · Elevated temperature wear

Introduction Considering the poor wear resistance of Al and alloys, which restricts their use for engineering components operating under harsh sliding contact conditions such as engine pistons, Al matrix composites (AMC) reinforced with oxide-, boride-, and carbide-based ceramic particles have been developed [1, 2]. However, ceramic particle reinforced AMCs may face with brittle phase formation and de-bonding at the particle/matrix interface, which deteriorates their mechanical properties, mostly due to the poor wettability and high thermal expansion coefficient difference between the matrix and the reinforcement particles [3, 4]. M. Kaba · F. Muhaffel · H. Çimeno˘glu (B) Department of Metallurgy and Materials Engineering, Istanbul Technical University, Istanbul, Turkey e-mail: [email protected] S. Cengiz Department of Materials Science and Engineering, Gebze Technical University, Kocaeli, Turkey © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_59

691

692

M. Kaba et al.

In the open literature, researchers have tried to overcome this problem by coating ceramic particles with metals such as Ni, Zr, and Cu in order to improve wettability [5–7]. The other solution has been reported as using intermetallic particles with high melting point and low density and coefficient of thermal expansion, enabling formation of a chemical bond between Al matrix and reinforcing intermetallic particles. In this regard, Al-rich intermetallic compounds such as Al3 Ni, Al3 Ti, Al3 Mg2 , Al3 Zr, Al3 Fe, and Al2 Cu are preferred as a reinforcement particle for the production of AMCs [8–12]. Apart from the other intermetallic compounds, Al2 Ce was chosen as a reinforcing particle due to its high melting point (1480 °C) and hardness (~850 HV) in order to fabricate AMCs having a good matrix/reinforcing particle binding in the recent study of the authors [13]. In this respect, the effectiveness of the Al2 Ce particle reinforcement on improvement in room temperature wear performance of Al was reported. However, elevated temperature wear behavior of the Al2 Ce particle reinforced AMCs have not been studied yet, to the best knowledge of the authors. In the present study, it is aimed to investigate elevated temperature (at 200 °C) wear behavior of the Al2 Ce particle reinforced Al and 7075 alloy matrix composite layers fabricated on the surface of Al and 7075 alloy by hot pressing. Results of this study may extend the usage of Al and its alloys for wear-related engineering applications operating at elevated temperatures.

Experimental Procedure Monolithic pure Al and 7075 alloy and 40 wt% Al2 Ce containing composite layers were prepared by hot pressing method. In order to obtain Al matrix composite layers on the surface of monolithic Al and 7075 alloy, mixture of spherical Al (99.5% pure, −325 mesh) and 7075 (5.6–6.1% Zn, 2.1–2.5% Mg, 1.2–1.6% Cu, 99.5% pure, − 325 mesh) powders and irregular shaped Al2 Ce (~10 μm) powder were poured over the monolithic Al and 7075 alloy, where the composite powder: monolithic powder ratio is 1:6. Disc shaped (Ø20 mm) monolithic and composite layer covered samples were produced after compacting in a 200 bar (Hidro Mode) hydraulic press under a uniaxial pressure of 110 bar at 220–230 °C. Light optical microscope (LOM) and scanning electron microscope (SEM) equipped with and energy dispersive spectroscopy (EDS) analyses were conducted on the surface of Al and 7075 alloy matrix 40 wt% Al2 Ce reinforced composite layer covered samples. Hardness measurements were conducted by using a Vickers microhardness tester under the load of 1 kg. The elevated temperature tribological properties of the monolithic and composite layer covered samples were determined by dry sliding wear tests using a ball-ondisc type tribometer (CSM Instruments) at 200 °C against an alumina ball (Ø6 mm). Test load, linear speed of the rotating disc, radius of the wear track, and total sliding distance was set as 2 N, 2 cm/s, 3 mm, and 50 m, respectively. Wear tracks developed on the surface of the samples were examined by a 2-D stylus profilometer (Veeco

A Study on the Wear Behavior of Al2 Ce-p Reinforced Al Matrix …

693

Dektak 6M) and an SEM (Hitachi TM 1000). Furthermore, contact surface of the counterface alumina balls were investigated by LOM.

Results and Discussion In Fig. 1, LOM and high magnification SEM images taken from the surface of 40 wt% Al2 Ce reinforced Al matrix composite layer covered sample are presented. From the LOM image (Fig. 1a), the volume fraction of the reinforcement particles (grey colored), which were homogenously distributed in the matrix, were quantified as 43 ± 1 and 34 ± 1% for Al and 7075 matrix composite layers (figure not given), respectively. High magnification SEM image (Fig. 1b) and elemental EDS-mapping images of Al and Ce (Fig. 1c) revealed the crack- and discontinuity-free nature of the Al2 Ce reinforcing particle/Al matrix interface. This observation indicated the good binding between Al2 Ce particle and Al matrix. Accordingly, addition of 40 wt% Al2 Ce into the Al and 7075 alloy matrixes caused an increase in the hardness from 56 ± 2 to 88 ± 9 HV1 and from 113 ± 2 to 124 ± 2 HV1 , respectively. Friction curves and representative 2-D profiles of the wear tracks formed on the surfaces of monolithic and composite layer covered samples after testing at 200 °C are shown in Fig. 2. In general, composite layer covered samples had a remarkably lower coefficient of friction values as compared to the monolithic samples while the friction curves of the monolithic samples fluctuated in a wider range than that of the composite layer covered samples. It should be noted that wear test conducted on the monolithic Al sample was cut about the sliding distance of 15 m because of the exceeding the tangential force limits of the tribometer. 2-D profilometric analyses revealed that deeper and wider wear tracks were formed on the monolithic alloys as compared to the composite layer covered samples. Figure 3 depicts the wear rate of the examined samples calculated from 2-D profilometric analyses by dividing wear track volume (mm3 ) with test load (N) and total sliding distance (m). At the first glance, 40 wt% Al2 Ce reinforced Al and 7075

Fig. 1 a LOM and b high magnification SEM image taken from the surface of Al matrix composite layer covered sample along with c EDS-mapping images for Al and Ce

694

M. Kaba et al.

Fig. 2 Friction curves and representative 2-D profiles of the wear tracks formed on the surfaces of the examined samples after testing at 200 °C

alloy matrix composite layer covered samples exhibited 2.6 and 6.0 times lower wear rate than that of their monolithic states, respectively. It is worth mentioning that steady state coefficient of friction values and wear rates of the 7075 sample were lower as compared to the Al sample whether 40 wt% Al2 Ce reinforced composite layer covered or not. Worn surface SEM images taken from the monolithic and composite layer covered samples and contact surface LOM images of the counterface balls are given in Figs. 4 and 5, respectively. Protuberances and delamination zones were observed on the worn surface of the monolithic Al and 7075 samples, indicating heavy plastic deformation on the contact surface. In accordance with this observation contact surfaces of the counterface alumina balls were darkened as the evidence of material transfer. Even though worn surfaces of the composite layer covered samples exhibited similar characteristics with that of the monolithic ones, intensities of plastic deformation, and delamination zones as well as the material transfer to the counterface ball were remarkably lower for the composite layer covered samples. These observations agreed well with the lower coefficient of friction values (Fig. 2) and wear rate (Fig. 3) of the composite layer covered samples. The dominant wear mechanism for the monolithic and composite layer covered samples was determined as plastic deformation induced adhesive wear. But, Al2 Ce reinforcement successfully

A Study on the Wear Behavior of Al2 Ce-p Reinforced Al Matrix …

Fig. 3 Wear rates of the examined samples at 200 °C

Fig. 4 Worn surface SEM images of the examined samples tested at 200 °C

695

696

M. Kaba et al.

Fig. 5 LOM images of the wear scars formed on the counterface balls after testing at 200 °C

suppressed plastic deformation by acting as a mechanical restraint during sliding contact [2] and provided superior wear resistance at 200 °C. It should be notified that higher hardness of the 7075 alloy matrix composite layer as compared to Al matrix composite layer resulted in formation of less amount of delamination (Fig. 4) and material transfer to the counterface (Fig. 5), and therefore higher wear resistance at 200 °C (Fig. 3).

Conclusion Elevated temperature wear performance of the monolithic and 40 wt% Al2 Ce reinforced composite layer covered Al and 7075 samples were examined by dry sliding wear tests at 200 °C. Results of the wear tests revealed the effectiveness of the Al2 Ce intermetallic particle reinforcement in increasing wear resistances of both Al and 7075 alloy via suppressing progress of plastic deformation dominated adhesive wear. 7075 alloy matrix composite layer covered sample exhibited the highest hardness and wear resistance as compared to Al matrix composite layer covered sample. Acknowledgements This study was funded by Istanbul Technical University Scientific Research Projects (ITU-BAP) with a project number MGA-2019-42222.

A Study on the Wear Behavior of Al2 Ce-p Reinforced Al Matrix …

697

References 1. Ramnath BV, Elanchezhian C, Annamalai RM, Aravind S, Atreya TSA, Vignesh V, Subramanian C (2014) Aluminium metal matrix composites—a review. Rev Adv Mater Sci 38:55–60 2. Bhattacharya S, Alpas AT (2017) Tribology of aluminum and aluminum matrix composite materials for automotive components. Light Sustain Mater Automot Appl 303–328. https:// doi.org/10.1201/9781315152967 3. Shorowordi KM, Laoui T, Haseeb ASMA, Celis JP, Froyen L (2003) Microstructure and interface characteristics of B4 C, SiC and Al2 O3 reinforced Al matrix composites: a comparative study. J Mater Process Technol 142:738–743. https://doi.org/10.1016/S0924-0136(03)00815-X 4. Sadhu KK, Mandal N, Sahoo RR (2023) SiC/graphene reinforced aluminum metal matrix composites prepared by powder metallurgy: a review. J Manuf Process 91:10–43. https://doi. org/10.1016/j.jmapro.2023.02.026 5. Ramesh CS, Keshavamurthy R, Channabasappa BH, Ahmed A (2009) Microstructure and mechanical properties of Ni-P coated Si3 N4 reinforced Al6061 composites. Mater Sci Eng A 502:99–106. https://doi.org/10.1016/j.msea.2008.10.012 6. Sun P, Dong Z, Chen Y, Yan H, Luo C, Song H, Hu Z (2020) Characterization of Ni coating layer of Al2 O3 particles and their wettability behavior in Al2 O3 @Ni/Al-10Si composites. Appl Surf Sci 526:146660. https://doi.org/10.1016/j.apsusc.2020.146660 7. Sha JJ, Lü ZZ, Sha RY, Zu YF, Dai JX, Xian YQ, Zhang W, Cui D, Yan CL (2021) Improved wettability and mechanical properties of metal coated carbon fiber-reinforced aluminum matrix composites by squeeze melt infiltration technique. Trans Nonferrous Met Soc China (Engl Ed) 31:317–330. https://doi.org/10.1016/S1003-6326(21)65498-5 8. Scudino S, Liu G, Sakaliyska M, Surreddi KB, Eckert J (2009) Powder metallurgy of Albased metal matrix composites reinforced with β-Al3 Mg2 intermetallic particles: analysis and modeling of mechanical properties. Acta Mater 57:4529–4538. https://doi.org/10.1016/j.act amat.2009.06.017 9. Qian J, Li J, Xiong J, Zhang F, Lin X (2012) In situ synthesizing Al3 Ni for fabrication of intermetallic-reinforced aluminum alloy composites by friction stir processing. Mater Sci Eng A 550:279–285. https://doi.org/10.1016/j.msea.2012.04.070 10. Dinaharan I, Ashok Kumar G, Vijay SJ, Murugan N (2014) Development of Al3 Ti and Al3 Zr intermetallic particulate reinforced aluminum alloy AA6061 in situ composites using friction stir processing. Mater Des 63:213–222. https://doi.org/10.1016/j.matdes.2014.06.008 11. Xue Y, Shen R, Ni S, Song M, Xiao D (2015) Fabrication, microstructure and mechanical properties of Al-Fe intermetallic particle reinforced Al-based composites. J Alloys Compd 618:537–544. https://doi.org/10.1016/j.jallcom.2014.09.009 12. Liu Y, Jia L, Wang W, Jin Z, Zhang H (2023) Reinforcing Al matrix composites by novel intermetallic/SiC interface and transition structure. J Mater Res Technol 26:164–175. https:// doi.org/10.1016/j.jmrt.2023.07.166 13. Cengiz S, Kaba M, Çetiner D, Çimeno˘glu H (2019) Production of Al2 Ce intermetallic reinforced Al matrix composites and investigation of wear performance. In: International conference on materials science, mechanical and automotive engineering and technology

Coating Development for High Temperature Dissolvable Rubber Element in Dissolvable Plug Applications Jiaxiang Ren, Peng Cheng, Lei Zhao, Yu Liu, Huailiang Liu, Xuefeng Cui, Bing Zhu, Qingjiang Wang, and Wei Ma

Abstract Dissolvable tools have been used more in unconventional oil and gas operations in recent years. Currently, more and more wells in Southwest of China requires high temperature (HT) dissolvable plug. The HT dissolvable plug needs to hold 70 Mpa pressure differential in water at 150 °C for 24 h. On the other hand, after the pressure holding test, the dissolvable plug needs to be dissolved in 1% KCl at 95 °C in less than 15 days. These requirements put big challenges on dissolvable rubber sealing materials. To meet the industrial challenges, several special HT coatings were developed to delay the dissolution time of the HT dissolvable rubbers. Two coatings delayed the dissolution time of dissolvable rubber coupons from 16 h to 14 days. Two dissolvable plugs with coating B coated dissolvable rubber element passed the testing requirements. Based on our knowledge, this is the first time in the industry a HT dissolvable plug with dissolvable rubber sealing element passed the requirements. Keywords Coating · Dissolvable rubber · High temperature · Dissolvable plug

Introduction The multistage hydraulic fracturing has been proven as one of the most effective stimulation technologies for exploiting unconventional oil and gas wells. Plug and Perf operation is the primary method for stimulating multistage wells [1]. The frac plug has been used extensively in the Plug and Perf operations in the past 70 years. The plug has been evolved from the cast ion plug (1950s–1990s) to the composite plug (1990s to today) and the dissolvable plug (2010s to today) [2, 3]. Dissolvable plugs have been used extensively for unconventional oil and gas production to replace J. Ren (B) · P. Cheng · L. Zhao · Y. Liu · H. Liu CNPC-USA Corp, 2901 Wilcrest Dr, Houston, TX 77042, USA e-mail: [email protected] X. Cui · B. Zhu · Q. Wang · W. Ma Daqing Oilfield Company Limited, CNPC, Daqing, China © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_60

698

Coating Development for High Temperature Dissolvable Rubber …

699

millable composite plugs in China during recent years. After the fracturing, the dissolvable plug could be dissolved in the downhole fluids. Therefore, the milling operation time and cost were saved. The dissolvable elastomer was an essential component of the dissolvable plug. There are more and more HT wells in Southwest of China, which requires high temperature dissolvable plugs in recent years. To meet the Southwest Oilfield Company lab test requirements, the HT dissolvable plug needs to hold 70 Mpa pressure in differential at 150 °C for 24 h. On the other hand, the dissolvable plug needs to be dissolved in 1% KCl at 95 °C in less than 15 days. These requirements place seemingly mutually exclusive challenges on dissolvable materials. Norman et al. [4] developed dissolvable metal and dissolvable elastomer for high temperature formation in Middle Eastern basin. However, the typical high temperature was only 121 °C. As far as we know, there is no report for dissolvable plugs with dissolvable rubber elements meeting the requirements of Southwest Oilfield Company yet. The metal-metal seal dissolvable plugs were reported to be used in Southwest of China. However, the metal seal could not make good seal due to its limited elasticity, especially in Southwest Oilfield of China. Casing deformation wells are very common in the Southwest Oilfield wells. Significant erosion of the casing has been reported for the location connected with metal seal of the plug during fracturing. To meet the industrial challenges, HT dissolvable rubbers were successfully developed at CNPC-USA for the HT dissolvable plug applications [5]. Various coating technologies have been developed to delay the dissolution of dissolvable metals [6, 7]. However, there is no publication regarding to effective coating to delay the dissolution of dissolvable rubber elements. In the work, two coatings were developed for delaying the dissolution of dissolvable rubber elements at high temperature at CNPCUSA. The dissolvable plug with the element coated with coating B passed Southwest Oilfield Company pressure holding testing and dissolution testing requirements. This is the first time in the industry based on our knowledge a HT dissolvable plug with dissolvable rubber sealing element passed 150 °C, 70 Mpa 24 h pressure holding test in water and then dissolved in brine at 95 °C in less than 15 days.

Materials and Experimental Methods Several grades of HT elastomers were developed for the HT dissolvable plug sealing element at CNPC-USA. The tensile testing was performed on the dissolvable rubbers at ambient temperature and 150 °C based on ASTM D412 [5]. Different HT coating methods have been developed to coat on the dissolvable rubber elements. Two of them have been proven more efficient. The dissolution testing of the dissolvable rubber coupons was performed in brine at 140 °C for 1 day and then at 95 °C to simulate the dissolvable plug testing procedure. On the other hand, the dissolvable rubber coupons and elements were also aged in 1% KCl at 95 °C to test the dissolution rate at the condition. The weight loss, hardness,

700

J. Ren et al.

dimension of the coupons, and the pH value of the fluid were measured at various durations. Two HT dissolvable plugs were developed with the dissolvable rubber element made of DR-127 coated with coating B. During the pressure holding testing, the dissolvable plug was soaked in water at 150 °C with 20–30 Mpa pressure differential for 12 h and then 70 Mpa pressure differential for 12 h. Afterwards, the dissolution testing was performed on the dissolvable plugs in 1% KCl at 95 °C for 15 days. To pass the HT dissolvable plug lab testing requirements, the dissolvable plug needs to hold 70 Mpa pressure stable at 150 °C during pressure holding testing. After dissolution testing, the dissolvable plug residue needs to be less than 5 wt.% of the plug before testing and the maximum dimension of the residue needs to be less than 2 cm.

Results and Discussion Coating Development for Dissolvable Rubbers It is very challenging to develop a coating for the HT dissolvable rubbers as the coating needs to meet the following requirements. 1. Coating needs to have a strong bonding with dissolvable rubber substrate. 2. The coating needs to be chemically and thermally stable in brine at 150 °C for > 24 h. 3. The coating needs to be easily applied with industrial coating manufacturing process. Several coatings were developed and tested at CNPC-USA. Two of them, i.e., Coating A and B displayed good results. Coating A is a silicone-based spray coating. Before coating, the surface of the rubber elements is cleaned with isopropanol alcohol to remove the dusts and oil residues. Afterwards, the silicone coating was sprayed to the surface of the dissolvable rubber elements. The coating is cured at room temperature overnight. Coating B is a poly(para-xylene), which is coated on the surface of dissolvable rubber element by vapor deposition (VDP) coating process. The thickness of the poly (para-xylene) coating needs to be designed to balance the properties of delaying the dissolvable rubber dissolution and dissolution rate of dissolvable rubbers. The high thickness coating could help to improve the barrier properties but sacrifices the sealing properties. Figure 1 displays the cross-section of DR-127 dissolvable rubber coupon with coating B. It was clearly observed that the coating has very good conformability with the sealing element substrate surface.

Coating Development for High Temperature Dissolvable Rubber …

701

Fig. 1 Optical microscopic cross-section image of DR-127 dissolvable rubber coupon coated with coating B

Dissolution Testing Results for Dissolvable Rubbers Figure 2 displays the dissolution progress of a dissolvable rubber DR-127 coupon without coating, with coating A 5 µm, and with coating B 12 µm at 140 °C, 0.3% KCl, 24 h and then at 95 °C, 0.3% KCl for 15 days. The observed results are as following.

Fig. 2 Dissolution progress of a dissolvable rubber DR-127 non-coated, DR-127 with coating A 5 µm, DR-127 with coating B 12 µm at 140 °C, 0.3% KCl, 24 h and then at 95 °C, 0.3% KCl for 15 days

702

J. Ren et al.

Fig. 3 Weight loss of dissolvable rubber DR-127 non-coated, DR-127 with coating A 5 µm, DR-127 with coating B 12 µm at 140 °C, 0.3% KCl, 24 h and then at 95 °C, 0.3% KCl for 15 days

. DR-127 coupon without coating was fractured after aging at 140 °C for 24 h, and was broken to pieces after aging at 95 °C for 1 day. . DR-127 coupon coated with coating A was broken to pieces after aging at 95 °C for 1 day, and was broken to pieces after aging at 95 °C for 3 days. . DR-127 coupon coated with coating B was broken to pieces after aging at 95 °C for 10 days, was broken to pieces after aging at 95 °C for 15 days. The results suggest that coating A delayed the dissolution of the DR-127 coupon for 2 days, while coating B delayed the dissoltuion of the DR-127 coupon for 14 days. Figure 3 shows the weight loss versus time for the three DR-127 coupons. The weight loss of DR-127 coated with coating A was less than that of DR-127 without coating in 24 h at 140 °C. Afterwards, the weight loss of the coating A coated coupon was comparable to that of DR-127 coupon without coating. It was observed that coating A was debonded from rubber substrate after soaking in the brine solution at 140 °C for 24 h. The results suggest coating A could temporarily delay the dissolution of the dissolvable rubber material in short time. On the other hand, the weight loss rate of coating B coated DR-127 coupon was obviously slower than that of DR-127 coupon without coating. The results suggest the coating B could delay the dissolution rate of DR-127 element in a longer time. The results are likely attributed to the hydrophobicity of coating B, a stronger bonding strength of the coating with the elastomer substrate, and the low permeation rate of the fluid through the coating. The study of the effect of coating thickness on the dissolution rate of dissolvable rubber materials is in progress at CNPC-USA.

Dissolvable Plug Testing Results Two HT plugs were designed with dissolvable rubber sealing element made of DR127 coated with coating B 12 µm. During the pressure holding test, the plug was set

Coating Development for High Temperature Dissolvable Rubber …

703

Fig. 4 Pressure holding test results of the dissolvable plug with coating B 12 µm coated DR-127 element

first at ambient temperature, then soaked in water at 150 °C for 12 h with ~ 20 Mpa pressure differential. Afterwards, a 70 Mpa (10,000 psi) pressure hold was performed on the plug for 12 h. The pressure remained stable for a total of 24 h. The plug only lost 2.76 Mpa (400 psi) during the 12 h 70 Mpa holding time. The testing results meet the HT dissolvable plug pressure holding testing requirements, as shown in Fig. 4. Figure 5 shows the dissolution progress of one HT dissolvable plug with coating B 12 µm coated DR-127 element at 95 °C in 1% KCl after pressure holding test. The metal parts were completely dissolved in 72 h. The dissolvable rubber element broke to pieces less than 2 cm after 336 h (14 days). The total weight loss of the plug was 95.5%. The dissolution testing results meet the HT dissolvable plug dissolution testing requirements.

Conclusions Two types of high temperature coatings were successfully developed to delay the dissolution process of dissolvable rubber element for HT dissolvable plug applications at CNPC-USA. Coating A and coating B delayed the dissolution of a dissolvable rubber coupon for 2 days and 14 days, respectively. The coatings for dissolvable rubbers provide a good method to delay and control the dissolution time of the dissolvable rubber elements. Different coatings could be used based on the actual application requirements. The high temperature plug based on the dissolvable rubber element DR-127 with coating B 12 µm passed both HT dissolvable plug pressure holding and dissolution testing requirements. This is the first time in the industry based on our knowledge a HT dissolvable plug with dissolvable rubber sealing element passed

704

Before Dissolution testing

After 288 hrs

J. Ren et al.

After 24 hrs

After 48 hrs

After 336 hrs

Fig. 5 Dissolution testing results of HT dissolvable plug with coating B 12 µm coated DR-127 element at 95 °C, 1% KCl

150 °C, 70 Mpa 24 h pressure holding test in water and then dissolved in brine at 95 °C in less than 15 days. The coatings could be applied in many other oil and gas applications. Acknowledgements The authors would like to thank the management of CNPC-USA for granting permission to publish this work.

References 1. Aviles I, Dardis M, Jacob G (2015) Dissolvable plug and perf system eliminates mill-outs in multistage simulations. JPT, June 2015 2. Xu ZY, Zhang ZH (2019) The art of disintegration–ten years in review of disintegrable metals and downhole tools. Paper presented at offshore technology conference. Houston, USA, May 2019 3. Walton Z, Michael F, Jesse P, Greg V (2019) Evolution of frac plug technologies. SPE-194802MS. Paper presented at SPE middle east oil and gas show and conference. Manama, Bahrain, March 18–21, 2019 4. Norman T, Walton Z, Fripp M (2018) Full dissolvable frac plug for high-temperature wellbore. OTC-28939-MS. Paper presented at the offshore technology conference. Houston, 30 April–3 May 2018 5. Yue W, Ren J, Yue J, Cheng P, Dunne T, Zhao L, Patsy M, Nettles D, Liu Y, Liu H (2022) High temperature dissolvable materials development for high temperature dissolvable plug applications. SPE-210238-MS. Paper presented at Annual technical conference and exhibition. Houston, TX, Oct 2022

Coating Development for High Temperature Dissolvable Rubber …

705

6. Zhao L, Yue W, Ren J, Dunne T, Cheng P, Liu H (2022) Flexible surface treatment technology to enable temporary SCC prevention for Mg dissolvable Alloys. Paper presented at TMS annual meeting & exhibition. Anaheim, USA, March 2022 7. Hartley RA (1971) Coating and corrosion. OTC 1466. Paper presented at Offshore technology conference. Houston, USA, April 1971

Electrodeposition Preparation and Performance Enhancement Mechanisms for Ni–Co–Fe Coatings Yizhe Du, Xuan Chen, Zhenyu Sun, and Dengfu Chen

Abstract A coating with superior properties is essential to prolong the life of the mold. In this contribution, a high-performance Ni-Co-Fe ternary alloy coating is prepared by electrodeposition, the parameters of the electrodeposition process are optimized, and first-principles calculations clarify the strengthening mechanism of Fe atoms. The results show that as the FeSO4 content in the deposition solution increases, the surface morphology of the coating gradually transitions from cellular to granular, and the hardness continuously decreases. Through comprehensive comparative analysis of coating quality and performance, the optimal preparation process for Ni Co Fe ternary alloy coating was obtained as follows: FeSO4 content of 2g/L, current density of 4A/dm2 , and temperature of 45 °C. The thickness of the coating sample obtained at this time is approximately 70–80 µm, the surface is bright and has good uniformity, and the hardness has increased by 24% compared to binary alloys. Furthermore, the introduction of Fe atoms can effectively enhance the properties of NiCo alloys, such as elasticity and hardness, and reduce the degree of anisotropy of the alloy. Electronic properties were investigated and showed that the improvement of the mechanical properties of the alloy can be attributed to the strong local covalent interaction after doping with Fe atoms. Keywords Ni–Co–Fe coatings · Electrodeposition · Elastic properties · Hardness · Electronic properties

Introduction As a key component of continuous casting machines, mold carries core functions such as initial solidification of molten steel and stable molding of billet shells. The addition of a coating to the inner surface of the mold facilitates the improvement of Y. Du · X. Chen · Z. Sun · D. Chen (B) Laboratory of Materials and Metallurgy, College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_61

706

Electrodeposition Preparation and Performance Enhancement …

707

its key properties such as hardness and wear resistance, and can effectively improve the surface quality of the billet, which is crucial for the continuous casting process. Since the 1970s, mold coatings have undergone a transition from metals (Ni, Cr et al.) to binary alloys (Ni–Fe, Ni–Co et al.). In particular, the application rate of Ni–Co alloy coatings alleviates the defects of poor stability and bonding properties of previous generations of coatings, but problems such as low hardness and poor wear resistance remain. At present, with the development of high-speed continuous casting and the demand for high-quality continuous casting slabs, it is necessary to further improve the comprehensive performance of the mold. Alloying has received a lot of attention as one of the effective strengthening methods. At present, theoretical studies and fabrication of a third element (including metal elements W, Mo, etc. and non-metal elements C, B, N, P, etc. [1]) doped Ni-Co alloy have been carried out by several scholars with the aim of further improving the mechanical properties of the alloy. For example, Farzaneh et al. [2] found that W element can significantly improve the hardness of Ni–Co alloy, especially when the W content exceeds 44 wt.%, the coating structure changes from crystal to amorphous state, which further improves the hardness. Bekish et al. [3] successfully prepared a Ni–Co–B ternary alloy coating by electrodeposition, and studied the effect of B content on the mechanical properties of the coating, and optimized the composition of the electrolyte. In addition, as a transition group metal element, Fe element is in the same period as Ni and Co, and has a good solid solution strengthening effect. The introduction of Fe element into NiCo alloy is expected to obtain coating materials with better comprehensive properties. At present, there are few studies on Fe element-doped Ni–Co alloy coatings, especially the change of alloy properties after Fe element doping and other key issues are still unclear. These unresolved problems restrict the development and application of high-performance Ni–Co–Fe ternary alloy coatings, and research on this is urgently needed. In this contribution, we have successfully fabricated Ni–Co–Fe ternary alloy coatings with excellent properties by electrodeposition and optimized the parameters of the electrodeposition process by comparing the quality and performance of the coatings. In addition, the effect of Fe atom doping on the elastic properties of NiCo alloys has been analyzed by first-principles calculations, and the nature of the strengthening effect brought by Fe atoms has been clarified from the electronic level. The results can provide some valuable information for the development and application of high-performance Ni–Co–Fe triplet alloy coatings.

Experimental and Computational Methods Ni–Co–Fe ternary alloy coatings were prepared by electrodeposition method, and the specific plating solution system and experimental process parameters are listed in Table 1. Among them, FeSO4 ·7H2 O serves as the source of Fe element in the coating, and together with temperature and current density, it serves as a variable

708

Y. Du et al.

Table 1 Deposition solution composition and electrodeposition process parameters Sedimentation fluid composition

Contents (g/ L)

Electrodeposition process parameters

NiSO4 ·6H2 O

100

Current density (A/dm2 )

Variable

CoSO4 ·7H2 O

10

Bath temperature (°C)

Variable

FeSO4 ·7H2 O

Variable

Stirring method

Magnetic stirring

Sodium dodecyl sulfate (SDS)

0.2

pH

4–5

Saccharin

0.4

Anode material

Ru-Ir alloy plated titanium plate

Boric acid

30

Heating method

Water bath

parameter. In addition, dilute sulfuric acid or NaOH solutions are used to maintain the pH of the bath solution within a certain range. The first-principles calculations were performed using the Cambridge Serial Total Energy Package (CASTEP) package based on density functional theory. Among them, the exchange correlation can be carried out by generalized gradient approximation (GGA) and Perdew–Burke–Ernzerhof (PBE) functional [4], and the ion– electron interaction described by the plane-wave ultrasoft pseudopotential method [5]. In the structural optimization, the Monkhorst–Pack type k-points grid is used for the integral calculation in the first Brillouin zone [6]. In order to ensure good convergence, the cut-off energy is selected as 450 eV, and the K point is selected as 15 × 15 × 11. The BFGS method was used to optimize the locally stable structure of the crystal [7]. The convergence conditions were that the total energy deviation was less than 5 × 10–6 eV/atom, the energy deviation was less than 0.01 eV/Å, the stress deviation was less than 0.02 G Pa, and the displacement deviation was less than 5 × 10–4 Å. All calculations take into account spin polarization. The computational models are shown in Fig. 1. The L10 NiCo binary alloy model was established, and 2 × 2 × 2 cell expansion treatment was carried out. In, the doping cases of Ni and Co atoms replaced by Fe atoms were considered separately and subsequent calculations were performed.

Results and Discussion Electrodeposition Preparation and Process Optimization of Ni–Co-Fe Alloy Coatings Experimentally, the effect of the FeSO4 content in the bath solution on the coating morphology was first investigated and its composition was characterized, as shown in Fig. 2. The results show that the coating is composed of three elements, Ni, Co, and Fe, with a uniform distribution. Furthermore, we find that the FeSO4 content has a

Electrodeposition Preparation and Performance Enhancement …

709

Fig. 1 Crystal structure of Ni–Co and Fe-doped Ni–Co alloys. a Ni–Co; b Ni–Co (2 × 2 × 2 supercell); c Ni replaced by Fe; d Fe substitution of Co. Among them, the gray is Ni atoms, the blue is Co atoms, and the yellow is Fe atoms

significant effect on the coating surface. Specifically, when the FeSO4 content is low (2g/L), the grains are tightly bonded without gaps, which is conducive to improving the mechanical properties of the coating. As the Fe content increases, the coating morphology gradually transitions from cellular to granular. When the FeSO4 content is high (≥15 g/L), the surface of the coating is obviously granular, the grains are fine, but not dense, and the gaps between the grains are large, which may lead to poor coating performance. Figure 3a is the corresponding relationship between the Fe elements content in the coating and the FeSO4 content (1, 2, 5, 15, 30, 45, 60 g/L) in the bath solution. As the FeSO4 content increases, the composition of the coating changes dramatically, with a gradual transition from Ni and Co dominated to Fe-dominated. The electrode potential of Fe is more positive than that of Ni and Co, and it deposits more readily on the

Fig. 2 a–d: Surface morphology of coatings with different FeSO4 contents a 2 g/L; b 15 g/L; c 30 g/L; d 45 g/L; e–g surface scanning analysis of the coating

710

Y. Du et al.

Fig. 3 a Relationship between FeSO4 content in deposition solution and Fe content in coating; b effect of FeSO4 content in deposition solution on coating hardness; c effect of temperature on coating hardness; d effect of current density on coating hardness

cathode copper plate, suppressing deposition of other metallic elements. Therefore, the amount of FeSO4 in the bath solution should not be too large. In addition, the effect of FeSO4 content on the hardness of the coating was also studied, as shown in Fig. 3b. The results show that with the increase of FeSO4 content, the coating hardness first increases and then decreases. The Fe elements content in the coating is 8.2 wt.% for a FeSO4 content of 2 g/L. At this time, the hardness of the coating is the highest, reaching 688.2 HV, which is 24.7% higher than that of the binary Ni–Co alloy (552HV). Therefore, we adopt the FeSO4 content of the bath solution as 2 g/L in subsequent studies of other process parameters. The temperature of the plating solution during electrodeposition can affect the deposition rate, surface quality, and crystallization properties of the coating, which in turn can affect its performance. We have studied the surface quality and hardness of the coating under different temperature conditions (25, 35, 45, 55, 65 °C) when the FeSO4 in the plating solution is 2 g/L and the current density is 4A/dm2 . Among them, the hardness results are shown in Fig. 3c. The results showed that when the temperature was 25 and 35 °C, the surface of the coating appeared partial peeling phenomenon, the surface was darker, and the hardness was lower. When the temperature of the plating solution is high, the surface of the coating will be wrinkled and scorched, and a small number of pores will be created. When the temperature of the plating solution is 45 °C, the surface of the coating is bright, without defects such as

Electrodeposition Preparation and Performance Enhancement …

711

cracks and pores, and has the highest hardness. Therefore, the best bath temperature is 45 °C. The current density is also one of the important parameters affecting the surface quality and performance of the coating. Therefore, we analyzed the effect of current density changes (2, 3, 4, 5, 6 A/dm2 ) on the hardness of coating under the condition that other experimental conditions remained unchanged (the content of FeSO4 in the bath was 2 g/L, and the temperature was 45 °C), as Fig. 3d shown. The results show that the coating hardness first increases and then decreases with the increase of current density. Increasing the current density increases the cathodic polarizability, which favors crystallization refinement and the acquisition of a homogeneous and dense coating structure. However, when the current density is too high, this leads to an increase in the concentration polarization, causing the coating to burn and blacken, the coating to become loose and the hardness to decrease. Experimental studies have shown that at current densities of 4 A/dm2 , the coating has the highest hardness and the surface is bright with no significant defects. Thus, the optimal current density is chosen to be 4 A/dm2 . In summary, the quality, morphology, and performance of the coatings have been comprehensively judged through one-factor variational experimental studies, the optimal preparation process of the Ni-Co-Fe coating is: the content of FeSO4 is 2 g/L, the temperature of the bath solution and the current density is 4 A/dm2 at 45 °C.

Effect of Fe Atom Doping on Elastic and Electronic Properties of Alloys Elastic Properties and Anisotropy Based on the above experimental studies, in order to clarify the strengthening mechanism of Fe atoms, we first performed preliminary calculations on the elastic properties of Ni–Co–Fe alloys. The enthalpy of formation [8] is used to judge the site preference of Fe atoms in NiCo alloy. The formula for the calculation is: Ni Co y X z

H f = (E totalx Ni Co X

Ni Co − x E bulk − y E bulk − z E 0X )/(x + y + z)

(1)

Ni where E totalx y z is the total energy per unit cell of the compound Nix Coy Xz ; E bulk , Co E bulk is the average energy per atom in the solid elemental Ni and Co, respectively, and the equilibrium energy per metal atom in its stable structure, with x, y, z denoting the corresponding number of atoms in the unit cell. The calculated enthalpy of formation of Ni8 Co7 Fe (Fe replacing Co) is − 0.009, while the formation enthalpy of Ni7 Co8 Fe (Fe replacing Co) is 0.002, indicating that Fe in the alloy tends to occupy the position of Co atoms.

712

Y. Du et al.

Elastic constants can be used to evaluate the mechanical properties of solid materials, and they can provide important information about technological and industrial applications of materials. There are six independent elastic constants for the tetragonal crystal structure, which are C 11 , C 12 , C 13 , C 33 , C 44 , and C 66 . The elastic constants of different systems are calculated by the stress–strain method [9], and the calculation results are listed in Table 2. In order to analyze the elastic properties of the alloy more comprehensively, we calculated the bulk modulus B, shear modulus G, and Young’s modulus of different alloys Elastic performance parameters such as E and Poisson’s ratio v. Among them, B and G of different crystal structures can be obtained by the Voigt-Reuss-Hill (VRH) approximation method [10], and the calculation methods of other parameters have been detailed in our previous research [11]. In general, the larger the bulk modulus B, the stronger the resistance to bulk deformations. According to the calculations, the inclusion of Fe atoms results in a slight reduction of the bulk modulus of NiCo alloy. In addition, the shear modulus G and Young’s modulus E respectively reflect the ability of the material to resist shear deformation and the stiffness of the material [12]. Usually, the larger G and E, the higher the strength and hardness of the material, and the better its wear resistance. After the addition of Fe atoms, the shear modulus and Young’s modulus of the alloy have been improved to varying degrees, especially the improvement is more significant when Fe atoms replace Co atoms. Currently, the G and E of the alloy are as high as 105 GPa and 268 GPa, respectively. Therefore, we speculate that Fe atoms are beneficial for improving the comprehensive mechanical properties of the alloy. On the other hand, the parameter B/G proposed by Pugh [13] was used to characterize the toughness and brittleness properties of the alloy. When B/G > 1.75 and the larger it is, the better the toughness or ductility of the alloy. Similarly, when the Poisson’s ratio (v) is greater than 0.26, it can be determined that the material is a plastic phase, otherwise it is a brittle phase. From the combined results, on the one hand, the B/G and ν of the alloy are larger than the above critical values regardless of whether the Fe atoms replace Ni or Co atoms, indicating good plasticity. On the other hand, it also reflects that the Fe atoms doping not only bring a strengthening effect compared to NiCo alloy, but also sacrifices a certain degree of toughness. Furthermore, microhardness is also a critical parameter that directly reflects the mechanical properties of the material [14]. The vickers hardness of different systems was calculated using the classic formula proposed by Chen et al. [9], that is: HV = 2(K 2 G)0.585 − 3

(2)

Table 2 Elastic constants and related mechanical properties parameters of varying systems, (GPa) Alloy

C 11

C 12

C 13

C 33

C 44

C 66

B

G

E

v

B/G

HV

NiCo

388

80

155

306

140

50

206

103

264

0.287

2.02

10.2

Ni8 Co7 Fe

378

75

146

311

143

51

200

105

268

0.277

1.91

11.3

Ni7 Co8 Fe

378

83

156

288

142

58

204

104

265

0.283

1.97

10.6

Electrodeposition Preparation and Performance Enhancement …

713

In Eq. 2, K = G/B, where G and B are the shear and bulk modulus, respectively. It can be seen from the table that Fe atoms can effectively increase the hardness of NiCo alloy, especially when Fe replaces Co, the hardness increases by 10.8%, reflecting its typical solid solution strengthening characteristics, which is in good agreement with the detection results of the electrodeposition experiments described above. Elastic anisotropy is also one of the important properties of materials, which is related to behaviors such as the initiation of microcracks in materials [15]. The study of elastic anisotropy is beneficial for more comprehensive improvement and design of material properties. The anisotropy index Au proposed by Ranganathan et al. [16] is usually used to describe the degree of anisotropy of the material, namely Au = 5(G V /G R ) + BV /B R − 6

(3)

Here, BV and GV are the bulk modulus and shear modulus of the Voigt equation, respectively; BR and GR are the Reuss equation. Calculated Au (NiCo) = 1.04, Au (NiCo) = 1.04, Au (NiCo) = 1.04. It is shown that the addition of Fe atoms reduces the anisotropy of the NiCo alloy. Based on the results on elastic properties and hardness, the mechanical properties of alloys are basically positively correlated with the anisotropy index. Moreover, in order to provide a more intuitive understanding of the elastic anisotropy of different systems, we calculated the uniaxial Young’s modulus in different directions using parameters such as elastic compliance constant and directional cosines [17], and plotted a three-dimensional Young’s modulus diagram of NiCo alloy and the projection of Young’s modulus of different systems on the (100) plane, as shown in Fig. 4. If the crystal is isotropic, the 3D modulus map should be spherical, so the degree of deviation from the sphere can be used to measure differences in anisotropy between different systems. Each system is anisotropic, and the addition of Fe atoms reduces the degree of anisotropy in NiCo alloys. The effect of replacing the Co atoms with Fe atoms is more significant, in agreement with the analytical structure of Au .

Electronic Structure Analysis In order to further clarify the strengthening mechanism of Fe atoms, taking Ni8 Co7 Fe as a representative, the partial density of states (PDOS) of different atoms in the alloy was calculated, and the overlapping of the density of states near the Fermi level was analyzed, as shown in Fig. 5. The bonding characteristics between atoms are essentially determined by the valence electrons (s, p, d), and will affect the plastic deformation behavior or the brittle behavior of bulk amorphous alloys. From the density of states distribution, the DOS shapes of the three atoms are similar, with the energies of the bound electrons mainly between − 10 and 10 eV. At the Fermi level with an energy of 0 eV, the band gaps of the three atoms are all 0, showing typical metallic characteristics. Furthermore, the d orbitals of the three atoms near the Fermi level have a large area

714

Y. Du et al.

Fig.4 a 3D Young’s modulus diagram of NiCo alloy, b projection of young’s modulus of varying systems on the (100) plane

Fig. 5 Partial density of state (PDOS) diagram of different atoms in NiCoFe alloy. a Ni; b Co; c Fe

of overlap, indicating that there is obvious hybridization, which means that there will be local strong covalent interactions in the system, which will be beneficial to the improvement of the overall mechanical properties of the alloy.

Conclusions In this contribution, we have successfully prepared Ni–Co–Fe ternary alloy coatings with excellent properties by electrodeposition and optimized the process parameters. Moreover, the effect of Fe atom doping on the elastic properties and hardness of alloys was calculated using first-principles calculations, and the strengthening mechanism brought by Fe atoms was analyzed from the point of view of electronic properties. The results show that as the FeSO4 content in the deposition solution increases, the surface morphology of the coating gradually transitions from cellular to granular, and the hardness continuously decreases. Through comprehensive comparative analysis of coating quality and performance, the optimal preparation process for Ni Co Fe

Electrodeposition Preparation and Performance Enhancement …

715

ternary alloy coating was obtained as follows: FeSO4 content of 2 g/L, current density of 4 A/dm2 , and temperature of 45 °C. The thickness of the coating sample obtained at this time is approximately 70–80 µm, the surface is bright and has good uniformity, and the hardness has increased by 24% compared to binary alloys. Additionally, first-principles calculations show that Fe atoms tend to occupy the positions of Co atoms in the alloy, that the elastic modulus and hardness parameters of the alloy are significantly enhanced, and the strengthening effect is closely related to the degree of anisotropy. Furthermore, the electronic structure analysis shows the strengthening effect due to the Fe atoms can be attributed to their strong covalent interaction with the Ni and Co atoms localized in the alloy. Acknowledgements The authors gratefully acknowledge the financial support provided by the National Natural Science Foundation of China, project No.52274320 and 52074053.

References 1. Du Y, Chen Y, Yuan X, Liu P, Long M, Chen D (2023) Potential mechanisms of interstitial atomic enhancement and interface failure behavior in Ni3 Co/Cu systems. Appl Surf Sci 629:157388 2. Farzaneh MA, Raeissi K, Golozar MA (2010) Effect of current density on deposition process and properties of nanocrystalline Ni–Co–W alloy coatings. J Alloy Compd 489(2):488–492 3. Bekish YN, Poznyak SK, Tsybulskaya LS, Gaevskaya TV, Kukareko VA, Mazanik AV (2014) Electrodeposited Ni–Co–B alloy coatings: preparation and properties. J Electrochem Soc 161(12):D620 4. Perdew JP, Burke K, Ernzerhof M (1996) Generalized gradient approximation made simple. Phys Rev Lett 77(18):3865 5. Laasonen K, Pasquarello A, Car R, Lee C, Vanderbilt D (1993) Car-Parrinello molecular dynamics with Vanderbilt ultrasoft pseudopotentials. Phys Rev B 47(16):10142 6. Monkhorst HJ, Pack JD (1976) Special points for Brillouin-zone integrations. Phys Rev B 13(12):5188 7. Fischer TH, Almlof J (1992) General methods for geometry and wave function optimization. J Phys Chem 96(24):9768–9774 8. Pfrommer BG, Côté M, Louie SG, Cohen ML (1997) Relaxation of crystals with the quasiNewton method. J Comput Phys 131(1):233–240 9. Ji ZW, Hu CH, Wang DH, Zhong Y, Yang J, Zhang WQ, Zhou HY (2012) Mechanical properties and chemical bonding of the Os–B system: a first-principles study. Acta Mater 60(10):4208– 4217 10. Hill R (1952) The elastic behaviour of a crystalline aggregate. Proc Phys Soc. Sect A 65(5):349 11. Liu P, Chen D, Wang Q, Xu P, Long M, Duan H (2020) Crystal structure and mechanical properties of nickel–cobalt alloys with different compositions: a first-principles study. J Phys Chem Solids 137:109194 12. Gerk AP (1977) The effect of work-hardening upon the hardness of solids: minimum hardness. J Mater Sci 12:735–738 13. Pugh SF (1954) XCII. Relations between the elastic moduli and the plastic properties of polycrystalline pure metals. The London, Edinburgh, Dublin Philos Mag J Sci 45(367):823–843 14. Du Y, Yuan X, Liu P, Long M, Chen D (2023) Uncovering the influence mechanism of nonmetallic atoms on the mechanical properties of Ni3 Co alloy. J Mater Res Technol 25:4396–4408

716

Y. Du et al.

15. Hasegawa M, Yagi T (2005) Systematic study of formation and crystal structure of 3d-transition metal nitrides synthesized in a supercritical nitrogen fluid under 10 GPa and 1800 K using diamond anvil cell and YAG laser heating. J Alloy Compd 403(1–2):131–142 16. Ranganathan SI, Ostoja-Starzewski M (2008) Universal elastic anisotropy index. Phys Rev Lett 101(5):055504 17. Liu P, Du Y, Ai S, Xu P, Yang J, Duan H, Chen D (2020) The effect of the elements Cr, Os, Ir, and Y additions on the mechanical and electronic properties of L12 Ni3 Co alloys. J APPL PHYS 128(18)

Improving the Corrosion and Wear Behaviour of ECAP-Processed Biodegradable Mg-Zn-Ca Alloy for Bone Repair Applications W. H. El-Garaihy, A. I. Alateyah, A. Alrumayh, Amal BaQais, Majed O. Alawad, and Mohamed S. El-Asfoury

Abstract In this work, biodegradable Mg–3Zn–0.4Ca (ZX30) alloy was processed using equal channel angular pressing for up to 4-passes of route Bc. Microstructural evolution and crystallographic texture of the billets were studied using the scanning electron microscope-based electron back scatter diffraction technique. The corrosion behaviour of the alloy was investigated using potentiodynamic polarization and electrochemical impedance spectroscopy, set in a body simulated fluid. Wear tests were conducted for ZX30 billets as functions of load, velocity, and distance. The microstructure of the 4-passes samples was dominated by fine equiaxed grains, which W. H. El-Garaihy (B) · A. I. Alateyah · A. Alrumayh Department of Mechanical Engineering, College of Engineering, Qassim University, Unaizah 56452, Saudi Arabia e-mail: [email protected] A. I. Alateyah e-mail: [email protected] A. Alrumayh e-mail: [email protected] W. H. El-Garaihy Mechanical Engineering Department, Faculty of Engineering, Suez Canal University, Ismailia 41522, Egypt A. BaQais Department of Chemistry, College of Science, Princess Nourah Bint Abdulrahman University, Riyadh 11671, Saudi Arabia e-mail: [email protected] M. O. Alawad Center of Excellence for Nanomaterials for Clean Energy Applications, King Abdulaziz City for Science and Technology (KACST), Riyadh 12354, Saudi Arabia e-mail: [email protected] M. S. El-Asfoury Production Engineering and Mechanical Design Department, Faculty of Engineering, Port-Said University, Port- Said 42523, Egypt e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_62

717

718

W. H. El-Garaihy et al.

indicates that the deformation process was homogeneous and had caused continuous dynamic recrystallization. The average grain size of the 4-pass ZX30 alloy was reduced by 91.6% compared to its as-annealed counterpart. A 93.4% corrosion rate reduction, and a 254% corrosion resistance improvement was achieved in the 4passes condition. Furthermore, ECAP processing yielded significant improvements in wear behavior, compared to as-annealed counterpart. Keywords Equal channel angular pressing · Microstructural evolution · Crystallographic texture · Corrosion behaviour · Wear behaviour · ZX30 alloy

Introduction The development of biomaterials plays a crucial role in contemporary orthopaedic surgery, facilitating the repair of fractures, and the substitution of joints [1]. In the context of biodegradable implants, eliminating the need for implant removal postrecovery from bone fractures brings significant benefits for patients and healthcare systems. Unlike permanent implants, Magnesium (Mg) alloys degrade completely in vivo, obviating the need for subsequent surgical interventions. This feature suits them for temporary support applications in bone repair [2, 3]. However, their rapid degradation necessitates corrosion control aligned with bone healing processes to prevent mechanical property loss and toxic by-product accumulation [4–6]. Hence, enhancing the corrosion resistance of Mg alloys is crucial to mitigate implications for medical costs and patient well-being, ensuring the success of these biodegradable metal implants in bone repair applications. Alloying is one of the main techniques to enhance the corrosion resistance of Mg alloy. Research by Witte [1, 7], Xu et al. [8], and Staiger et al. [9] has pioneered the investigation of biodegradable Mg alloys for implants. Particularly, Mg alloys with aluminum and zinc (AZ) have garnered attention due to their commercial availability. These alloys exhibit in vivo degradation dependent on alloy composition, leading to the production of low corrosion rate alloys by introducing alloying elements like rare earths [1]. Early studies use of Mg-Al alloy demonstrated implant disappearance after bone grafting [10]. Stroganov et al. employed Mg alloys with rare earth and other elements, observing slow degradation over 5–10 months [11]. Witte et al. studied AZ and rare earth alloy degradation, noting slower corrosion for Mg–Li–Al alloy and the presence of alloying elements in the corrosion layer but not in adjacent bone tissue [12]. Wang’s work with Mg–Zn–Zr implants revealed corrosion and increased bone density around implants [13]. Pan et al. introduced high-strength Mg–Sn–Ca alloys, attributing strength to nano phase density and ultrafine granulation [14]. It worth to mention that eliminating the toxic consequence of alloying elements is essential (e.g., Al caused Alzheimer, Zr has associations with lung, liver, and breast cancers) [4]. However, using elements present in the human body that slow Mg

Improving the Corrosion and Wear Behaviour of ECAP-Processed …

719

alloy biodegradation holds promise and mitigate toxic effects. Zn and Ca represent the most effective elements satisfy this characteristic [15, 16]. Zn can enhance age hardening and solid solution strengthening, overcoming corrosion effects of Fe and Ni impurities [17, 18]. Calcium benefits bone healing as the primary bone component, and both can improve corrosion potential and reduce degradation rate [14, 19]. In addition, ultrafine grain structure of Mg alloys has shown enhanced mechanical and biological responses compared to their coarser counterparts [20]. Severe plastic deformation (SPD) represents a successful approach to synthesis bulk nanostructured metallic materials [21–23]. Recent years have witnessed extensive efforts in devising and investigating diverse SPD methods. Foremost among these techniques is the equal channel angular pressing (ECAP) [24, 25]. ECAP process decline the corrosion rate of ZE41 Mg alloy, though raising dislocation density [26]. Zhang et al. observed improved corrosion resistance after one ECAP pass of WE43 Mg alloy, which was further enhanced through subsequent aging at 200 °C for 24 h [27]. This tendency was confirmed in ZK30, ZK60, and AZ31 Mg alloys, likely due to stress relief, enhanced film protection, and second phase redistribution [28–30]. Hence, the utilization of ECAP holds significant promise in enhancing the texture and distribution of second phases within Mg alloys. However, careful investigation into the resulting characteristics is essential, particularly in the context of wear properties. This intricate interplay between alloying with biocompatible materials and ECAP process necessitates comprehensive exploration to strike the optimal balance for developing advanced Mg alloys for biomedical applications. This study investigates the effect of SPD, namely ECAP on Mg–Zn–Ca alloy (ZX30). A four-passes ECAP approach is employed to refine the grain structure and enhance crystallographic texture, through an in-depth exploration of microstructural evolution, corrosion, and wear properties. This research sheds light on potential processing pathways for enhancing the properties of Mg alloys for bone repair applications.

Material and Method Commercial cylindrical billet of ZX30 (Mg–3 Zn–0.4 Ca, wt%) alloy as the subject material is employed for this study. The initial step involved sectioning the samples into 60 mm long billets with a diameter of 20 mm. Prior to ECAP processing, annealing was carried out for 16 h at 430 °C to dissolve second phase particles (labelled as annealing sample (AA)). The processing was facilitated using a die featuring an angle of 90° and an outer arc of curvature of 20°, and a ram at a speed of 10 mm/min. The hot processing took place at 250 °C for varying passes: 1-pass (1P), 4-passes of route Bc (4Bc).

720

W. H. El-Garaihy et al.

To comprehensively characterize the microstructural evolution, both the AA samples and the ECAP-processed samples underwent a detailed preparation process. Subsequent grinding and polishing were performed through a series of grits and diamond suspensions, etching and ion milling were employed to further refine the samples. Characterization was executed via scanning electron microscopy (SEM) with electron back scattered diffraction (EBSD) accessory for microstructure and crystallographic texture analysis. EBSD measurements were taken from the top ED surface with a SEM. Crystallographic data was processed with software to generate inverse pole figure (IPF) maps. For corrosion characteristics, a 3-electrode flat corrosion cell was used, and procedures were carried out with a Potentiostat, using a simulated body fluid as corrosive agents. The cell comprised a counter electrode (platinum mesh), a reference electrode (saturated calomel electrode), and the working electrode (AA or ECAP-processed ZK30 samples). Linear potentiodynamic polarization scans and Electrochemical Impedance Spectroscopy (EIS) were performed to assess the corrosion behaviour of the extruded samples. Wear behaviour of the magnesium alloy was investigated using ball-on-flat (Bruker’s universal mechanical tester, USA) apparatus. Before wear tests all Mg alloy samples were grinded and polished to a mirror-like finish. Different wear parameters were selected for performing wear test. Three speeds of 64.5, 125, and 250 mm/s were selected at a different applied load of 1, 3, and 5 N for time duration of 110, 210, and 410 s.

Results and Discussion Microstructure Evolution The inverse pole figures (IPF) map relative to the extrusion direction (ED) coupled with the band contrast maps (BC) with low angle grain boundaries (LAGBs) in red and high angle grain boundaries (HAGBs) in black and the (0001) pole figures (PF) for ZX30 alloy before and after processing are shown in Fig. 1. The grain size distribution and misorientation angle distribution for the ZX30 alloy were found in Fig. 2. Figure 1a revealed relatively equiaxed coarse grains ranged between 7 up to 74.7 μm with average grain size of 26 μm. Furthermore, AA condition exhibited many twins as shown in Fig. 1a. The BC map (Fig. 1b) displayed that for the AA condition, the HAGBs was dominates the structure. Figure 1c showed that the AA exhibited fairly strong texture with texture intensity 10.8 times random. A simple shear texture component was revealed and the poles of {0001} were aligned parallel to the transverse direction (TD) as shown in Fig. 1c.

Improving the Corrosion and Wear Behaviour of ECAP-Processed …

721

Fig. 1 Inverse pole figure coloring maps a, d, g and their corresponding grain boundary maps with grain boundaries of misorientation angles > 15° in black lines, 5°–15° in red lines b, e, h and (0001) pole figures for the AA a, b, c and the ECAP-processed samples for d, e, f 1P, g, h, i 4Bc

Fig. 2 The grain size distribution (a) and misorientation angle distribution (b) of the ZX30 billets before and after ECAP processing

ECAP processing through 1P revealed a severely elongated grain coexisted with ultrafine equiaxed grains which indicated that a partial dynamic recrystallization (DRX) was occur as shown in Fig. 1d. The existence of the coarse elongated grains confirmed that 1P is not sufficient to perform a complete DRX process. The grain size of 1P condition was ranged between 1.2 up to 48.7 μm with average grain size

722

W. H. El-Garaihy et al.

of 3.5 μm. The BC map (Fig. 1e) demonstrated that a considerable fraction of the LAGBs which confirmed the occurrence of a continuous dynamic recrystallization (cDRX). Concerning the crystallographic texture, the PF of (0001) displayed a strong texture with texture intensity of 11 times random while the basal plane was aligned at an angle of about 10º relative to the TD. Accumulation of the plastic straining up to 4Bc displayed that the ultrafine grained structure (UFG) was dominated the whole structure which was distributed uniformly throughout the structure which confirmed that the cDRX process was take place across the whole structure as shown in Fig. 1g. Straining via 4Bc resulted in refining the average grain size to 2.18 μm which indicated that 4Bc resulted in a significant refinement of the average grain size by 91.6% compared to the AA condition. On the other hand, the BC map shown in Fig. 1h showed that the HAGBs were dominated the grain boundary map while a few fractions of LAGBs was depicted (Fig. 2b). In terms of the crystallographic texture, 4Bc displayed a fairly strong simple shear texture with texture intensity of 10.4 times random (Fig. 1i). Furthermore, Fig. 1i confirmed that 4Bc resulted in rotating the poles of (0001) as it aligned at 45º relative to the TD. Figure 2a confirmed that ECAP processing through 1P and 4Bc exhibeted a significant grain refinment compared to the AA counterpart while it can be concluded that accumlation the staring up to 4Bc resulted in further refinment compared to 1P counterpart. The microstractural evolution and crystallographic texture are in a good agreement with previous studies for ZK30 [25], pure magnesium [31], and Mg–Zn–Ca alloy [32–34].

Corrosion Behavior The electrochemical behavior of ZX30 alloy in its AA and ECAPed samples are shown in Fig. The potentiodynamic polarization curves (Tafel plots) of the AA, 1P, and 4Bc conditions was shown in Fig. 3a while Nyquist plots coupled with the equivalent circuit was shown in Fig. 3b. The electrochemical parameters of the tafel’s plots included the corrosion potential (Ecorr), the corrosion current density (Icorr), anodic and cathodic constants (βa and βc), and corrosion rate in millimeter per year (mmpy) were tabulated in Table 1. Furthermore, the electrical component (shown in Fig. 3b) of the equivalent circuit used to fit the EIS findings were found in Table 2 where Rs referred to the solution resistance, Rp is referred to pitting corrosion resistance, and CPE is referred to the oxide film capacitance, while the capacitance is measured in terms of an empirical exponent N. From Fig. 3a it can revealed that ECAP processing resulted in shifting the Icorr towards the nobler values compared to the AA condition. In addition, increasing the plastic strain up to 4Bc exhibited further shifting of Icorr towards the nobler behavior compared to 1P counter parts. Similar trend was attained for the corrosion rate as shown in Table 1. Processing via 1P revealed a significant decrease in the corrosion rate of 70.1% compared to the AA condition. Further straining via 4Bc exhibited a significant reduction in the corrosion rate of 93.5% compared to the AA condition. The aforementioned Tafel’s findings confirmed

Improving the Corrosion and Wear Behaviour of ECAP-Processed …

723

that the obtained UFG structure (Fig. 1) after ECAP processing resulted in improving the corrosion behavior of ZX30 alloy. Furthermore, processing via multiple passes displayed higher refinement which led to further improvement in corrosion rate which can be attributed to increasing the grain boundaries areas. Accordingly, increasing the grain boundaries area resulted in formation of oxide/hydroxide protective layer with greater thickness and enhanced stability and coherency and hence enhanced corrosion rate was achieved [35, 36]. The Nequist plots shown in Fig. 3b revealed that all ZX30 samples displayed a capacitive semicircle in which the ECAPed samples showed much bigger radius compared to the AA condition which indicated higher corrosion resistance. Furthermore, it was clear that 4Bc sample revealed much bigger semicircle radius compared to 1P counterpart, hence better corrosion resistance. The pitting corrosion resistance was improved by 99.9% compared to the coarse-grained sample (AA) after 1P processing as displayed in Table 2. Increasing the processing passes up to 4Bc

Fig. 3 Corrosion measurements a potentiodynamic polarization curves and b Nyquist plot for the AA and ECAP-processed ZX30 billets

Table 1 Electrochemical parameters of Tafel’s plots for different conditions of ZX30 Mg Condition

βa (V/dec)

− βc (V/dec)

Ecorr (V)

Icorr (A)

Corrosion rate (mmpy)

AA

0.082772

0.22653

− 1.4598

1.9626 × 10–6

0.15576

1P

0.026152

0.072864

− 1.4806

5.8672 × 10–7

0.046564

0.12885

− 1.4719

1.2819 ×

0.010174

4Bc

0.15377

10–7

Table 2 The electrical parameters of the EIS equivalent circuit Condition

Rs ( .cm2 )

Rp ( .cm2 )

CPE (F)

N

AA

155.3

232.8

4.8623 ×

1P

168.2

465.5

9.2171 × 10–06

0.96856

4Bc

178.6

824.4

5.6815 × 10–06

0.80122

10–06

0.909

724

W. H. El-Garaihy et al.

resulted in significant enhancement of 254.4% in the pitting corrosion resistance compared to the AA counterpart. Accordingly, the Nequist plots finding agreed with Tafel’s plot perfectly. Processing through ECAP via multiple passes resulted not only refining the α-matrix grains but it leads to refining the secondary phases as well as redistributing it uniformly along the grain boundaries [30, 35]. The uniform distribution of the secondary phases along the grain boundaries resist and reduce the activity of both micro galvanic and pitting corrosion which agreed with previous studies [15, 37].

Wear Performance Figure 4 shows the volume loss for the AA, 1P, and 4Bc conditions processed under a load of 1, 3, and 5 N. In addition, the volume loss as a function of time for ZX30 processed through (a) 0-pass, (b) 1P, and (c) 4Bc coupled the IPF along the TD, ED, and normal direction (ND) is shown in Fig. 5. For all the applied loads, the AA exhibited higher volume loss compared to the ECAPed counterparts. In addition, from Fig. 4 it can revealed that the test speed introduced insignificant effect on the volume loss. The AA sample displayed a volume loss of 2.178 × 10–6 m3 as shown in Fig. 4a. ECAP processing through 1P experienced a significant reduction in the volume loss by 56% compared to the AA counterpart. Similar trend was observed for the sample tested under a load of 3 N and 5 N as shown in Fig. 4b and c, respectively. The reduction in the volume loss of the ECAP-processed samples can be attributed to the significant grain refinement (Fig. 1) which resulted in enhancing the hardness and hence, improving the wear behavior of the alloy [15]. Refining and redistributing of the secondary phases along the grain boundaries also assisted in improving the wear performance of the ECAP-processed samples. Furthermore, improving the wear behavior after ECAP processing can also explained by the formation of an oxide protective layer which resulted that protect the surface from adhesion to the counter surface and hence improve the wear resistance of the sample [38]. On the other hand, further processing through 4Bc resulted in improving the volume loss by 28.5% compared to the AA counterpart. Despite of decreasing the average grain size compared to the 1P condition, 4Bc revealed increasing the volume loss compared to 1P condition which indicated that the effect of texture strengthening mechanism dominated the effect of grain refinement mechanism. As displayed in IPF shown in Fig. 5, the AA sample displayed max texture intensity of 5.2 times random whereas the ECAP-processed samples via 1P and 4Bc revealed max texture intensity of 2.8 and 1.5 times random, respectively. Comparing the texture intensity of the ECAP-processed sample with the texture intensity of the AA sample it can revealed that ECAPed sample experienced lower texture intensity in the TD, ED,

Improving the Corrosion and Wear Behaviour of ECAP-Processed …

725

Fig. 4 Volume loss of ZX30 alloy under applied load of a 1 N, b N, and c 5 N

and ND despite of showing lower volume loss which can be attributed to the effect of grain refinement. Inspecting the effect of the applied load shown in Fig. 5 it can revealed that for all ZX30 samples the applied load in range of from 1 up to 5 N at all testing speeds exhibited insignificant effect on the volume loss of the ZX30 billets as the volume loss was ranged from 2.164 × 10–6 to 2.178 × 10–6 m3 , and from 9.481 × 10–7 to 9.594 × 10–6 m3 and from 1.549 × 10–6 to 1.558 × 10–6 m3 for the AA, 1P, and 4Bc, respectively. On the other hand, it can be revealed that for all ZX30 samples increasing the applied load in the range of 1–5 N showed decreasing in the volume loss as shown in Fig. 5. The coefficient of friction (COF) versus wear time for the applied load 1, 3, and 5 N was depicted in Fig. 6. From Fig. 6 it can be revealed that the COP curves were fluctuated which indicated the friction was not steady for all the ZX30 samples. The large fluctuating of the COP can be attributed to the smaller applied load on the surface of the sample. The average COP was also displayed in Fig. 6. For the AA sample, at lower speed the applied load of 1 N displayed the lowest COP whereas at higher speed the applied load of 3 N displayed the lowest COP as shown in Fig. 3a, b. For 1P condition, the applied load of 5 N displayed the lowest COP at lower

726

W. H. El-Garaihy et al.

Fig. 5 Volume loss as a function of time for ZX30 processed through a 0-pass, b 1P, and c 4Bc coupled the IPF along the TD, ED, and ND

and intermediate speeds whereas the applied load 3 N displayed the lowest COP at higher speed (Fig. 6c, d). On the other hand, the applied load of 5 N displayed the lowest COP at lower speed whereas at both intermediate and high speed the 3 N load displayed the lowest COP as shown in Fig. 6e, f.

Conclusions ZX30 alloy was processed through ECAP via 1P and 4Bc at 250 ºC. The microstructural evolution and crystallographic texture were studied through EBSD. Both the corrosion behaviour and the wear performance were investigated. The following conclusion can be drawn: 1. Processing through ECAP via 4Bc resulted in reducing the average grain size by 91.6% compared to the AA counterpart.

Improving the Corrosion and Wear Behaviour of ECAP-Processed …

727

Fig. 6 Coefficient of friction a, c and e and average coefficient of friction b, d and f for the AA billets a, b and ECAPed ZX30 alloy processed through c, d 1P and e, f 4Bc

2. 4Bc experienced a significant improve of 93.4% in the corrosion rate coupled with 254% increase of the corrosion resistance compared to the AA condition. 3. ECAP processing through 1P exhibited the highest reduction of the volume loss by 56% compared to the AA condition.

References 1. Witte F, Kaese V, Haferkamp H, Switzer E, Meyer-Lindenberg A, Wirth CJ, Windhagen H (2005) In vivo corrosion of four magnesium alloys and the associated bone response. Biomaterials 26:3557–3563. https://doi.org/10.1016/j.biomaterials.2004.09.049 2. Wolf F (2003) Chemistry and biochemistry of magnesium. Mol Aspects Med 24:3–9. https:// doi.org/10.1016/S0098-2997(02)00087-0

728

W. H. El-Garaihy et al.

3. Saris NEL, Mervaala E, Karppanen H, Khawaja JA, Lewenstam A (2000) Magnesium: an update on physiological, clinical and analytical aspects. Clin Chim Acta 294:1–26. https://doi. org/10.1016/S0009-8981(99)00258-2 4. Chen Y, Dou J, Yu H, Chen C (2019) Degradable magnesium-based alloys for biomedical applications: the role of critical alloying elements. J Biomater Appl 33:1348–1372. https://doi. org/10.1177/0885328219834656 5. Chiu KY, Wong MH, Cheng FT, Man HC (2007) Characterization and corrosion studies of fluoride conversion coating on degradable Mg implants. Surf Coatings Technol 202:590–598. https://doi.org/10.1016/j.surfcoat.2007.06.035 6. Alateyah AI, Aljohani TA, Alawad MO, Elkatatny S, El-Garaihy WH (2021) Improving the corrosion behavior of biodegradable am60 alloy through plasma electrolytic oxidation. Metals (Basel) 11:953. https://doi.org/10.3390/met11060953 7. Witte F (2010) The history of biodegradable magnesium implants: a review✩. Acta Biomater 6:1680–1692. https://doi.org/10.1016/j.actbio.2010.02.028 8. Xu L, Pan F, Yu G, Yang L, Zhang E, Yang K (2009) In vitro and in vivo evaluation of the surface bioactivity of a calcium phosphate coated magnesium alloy. Biomaterials 30:1512– 1523. https://doi.org/10.1016/j.biomaterials.2008.12.001 9. Staiger MP, Pietak AM, Huadmai J, Dias G (2006) Magnesium and its alloys as orthopedic biomaterials: a review. Biomaterials 27:1728–1734. https://doi.org/10.1016/j.biomateri als.2005.10.003 10. Uppal G, Thakur A, Chauhan A, Bala S (2022) Magnesium based implants for functional bone tissue regeneration—a review. J Magnes Alloy 10:356–386. https://doi.org/10.1016/j. jma.2021.08.017 11. Stroganov GB, Savitsky EM, Tikhova NM, Terekhova VF, Volkov MV, Sivash KM, Borodkin VS (1972) Magnesium-base alloy for use in bone surgery 12. Witte F (2015) Reprint of: the history of biodegradable magnesium implants: a review. Acta Biomater 23:S28–S40. https://doi.org/10.1016/j.actbio.2015.07.017 13. Wang J, Jiang H, Bi Y, e Sun J, Chen M, Liu D (2015) Effects of gas produced by degradation of Mg–Zn–Zr Alloy on cancellous bone tissue. Mater Sci Eng C 55:556–561. https://doi.org/ 10.1016/j.msec.2015.05.082 14. Pan H, Fu H, Song B, Ren Y, Zhao C, Qin G (2016) Formation of profuse dislocations in deformed calcium-containing magnesium alloys. Philos Mag Lett 96:249–255. https://doi. org/10.1080/09500839.2016.1192296 15. Alateyah AI, Alawad MO, Aljohani TA, El-Garaihy WH (2022) Influence of ultrafine-grained microstructure and texture evolution of ECAPed ZK30 magnesium alloy on the corrosion behavior in different corrosive agents. Materials (Basel) 15:5515. https://doi.org/10.3390/ma1 5165515 16. Sun Y, Zhang B, Wang Y, Geng L, Jiao X (2012) Preparation and characterization of a new biomedical Mg–Zn–Ca alloy. Mater Des 34:58–64. https://doi.org/10.1016/j.matdes.2011. 07.058 17. Zhang S, Zhang X, Zhao C, Li J, Song Y, Xie C, Tao H, Zhang Y, He Y, Jiang Y, Bian Y (2010) Research on an Mg–Zn alloy as a degradable biomaterial. Acta Biomater 6:626–640. https:// doi.org/10.1016/j.actbio.2009.06.028 18. Zhao D, Witte F, Lu F, Wang J, Li J, Qin L (2017) Current status on clinical applications of magnesium-based orthopaedic implants: a review from clinical translational perspective. Biomaterials 112:287–302. https://doi.org/10.1016/j.biomaterials.2016.10.017 19. Hofstetter J, Becker M, Martinelli E, Weinberg AM, Mingler B, Kilian H, Pogatscher S, Uggowitzer PJ, Löffler JF (2014) High-strength low-alloy (HSLA) Mg–Zn–Ca alloys with excellent biodegradation performance. JOM 66:566–572. https://doi.org/10.1007/s11837-014-0875-5 20. Kasaeian-Naeini M, Sedighi M, Hashemi R (2022) Severe plastic deformation (SPD) of biodegradable magnesium alloys and composites: a review of developments and prospects. J Magnes Alloy 10:938–955. https://doi.org/10.1016/j.jma.2021.11.006 21. Fouad DM, El-Garaihy WH, Ahmed MMZ, Albaijan I, Seleman MME-S, Salem HG (2021) Grain structure evolution and mechanical properties of multi-channel spiral twist extruded AA5083. Metals (Basel) 11:1276. https://doi.org/10.3390/met11081276

Improving the Corrosion and Wear Behaviour of ECAP-Processed …

729

22. Fouad DM, El-Garaihy WH, Ahmed MMZ, El-Sayed Seleman MM, Salem HG (2018) Influence of multi-channel spiral twist extrusion (MCSTE) processing on structural evolution, crystallographic texture and mechanical properties of AA1100. Mater Sci Eng A 737:166–175. https://doi.org/10.1016/j.msea.2018.09.039 23. Almenaif O, Alhumaydan Y, Alnafisah M, Aldhalaan M, Alateyah AI, El-Garaihy WH (2020) A computational investigation into the effect of equal channel angular processing on the mechanical properties of severely deformed ZK 60 alloy validated by experiments. Am J Eng Appl Sci 13:296–310. https://doi.org/10.3844/ajeassp.2020.296.310 24. Alawad MO, Alateyah AI, El-Garaihy WH, BaQais A, Elkatatny S, Kouta H, Kamel M, ElSanabary S (2022) Optimizing the ECAP parameters of biodegradable Mg-Zn-Zr alloy based on experimental, mathematical empirical, and response surface methodology. Materials (Basel) 15:7719. https://doi.org/10.3390/ma15217719 25. Shaban M, Alateyah AI, Alsharekh MF, Alawad MO, BaQais A, Kamel M, Alsunaydih FN, El-Garaihy WH, Salem HG (2023) Influence of ECAP parameters on the structural, electrochemical and mechanical behavior of ZK30: a combination of experimental and machine learning approaches. J Manuf Mater Process 7:52. https://doi.org/10.3390/jmmp7020052 26. Sekar P, Sanna N, Desai V (2020) Enhancement of resistance to galvanic corrosion of ZE41 Mg alloy by equal channel angular pressing. Mater Corros 71:571–584. https://doi.org/10.1002/ maco.201911337 27. Zhang Y, Gao M, Etim IP, Tan L, Yang K (2020) Optimising the torsional properties and corrosion resistance of biodegradable WE43 Mg alloy by ECAP and subsequent ageing. Mater Technol 35:402–410. https://doi.org/10.1080/10667857.2019.1688539 28. Shahar IA, Hosaka T, Yoshihara S, MacDonald BJ (2017) Mechanical and corrosion properties of AZ31 Mg alloy processed by equal-channel angular pressing and aging. Proc Eng 184:423– 431. https://doi.org/10.1016/j.proeng.2017.04.113 29. Mostaed E, Hashempour M, Fabrizi A, Dellasega D, Bestetti M, Bonollo F, Vedani M (2014) Microstructure, texture evolution, mechanical properties and corrosion behavior of ECAP processed ZK60 magnesium alloy for biodegradable applications. J Mech Behav Biomed Mater 37:307–322. https://doi.org/10.1016/j.jmbbm.2014.05.024 30. Alateyah AI, Alawad MO, Aljohani TA, El-Garaihy WH (2022) Effect of ECAP route type on the microstructural evolution, crystallographic texture, electrochemical behavior and mechanical properties of ZK30 biodegradable magnesium alloy. Materials (Basel) 15:6088. https:// doi.org/10.3390/ma15176088 31. Alateyah AII, Ahmed MMZ, Alawad MO, Elkatatny S, Zedan Y, Nassef A, El-Garaihy WHH (2022) Effect of ECAP die angle on the strain homogeneity, microstructural evolution, crystallographic texture and mechanical properties of pure magnesium: numerical simulation and experimental approach. J Mater Res Technol 17:1491–1511. https://doi.org/10.1016/j.jmrt. 2022.01.088 32. Ying T, Yu M, Chen Y, Zhang H, Wang J, Zeng X (2022) Dominant deformation mechanisms in Mg–Zn–Ca Alloy. Acta Metall Sin (English Lett) 35:1973–1982. https://doi.org/10.1007/ s40195-022-01437-z 33. Tong LB, Zheng MY, Chang H, Hu XS, Wu K, Xu SW, Kamado S, Kojima Y (2009) Microstructure and mechanical properties of Mg-Zn-Ca alloy processed by equal channel angular pressing. Mater Sci Eng A 523:289–294. https://doi.org/10.1016/j.msea.2009.06.021 34. Horky J, Bryła K, Krystian M, Mozdzen G, Mingler B, Sajti L (2021) Improving mechanical properties of lean Mg–Zn–Ca alloy for absorbable implants via double equal channel angular pressing (D-ECAP), Mater Sci Eng A 826. https://doi.org/10.1016/j.msea.2021.142002 35. Alateyah AI, Aljohani TA, Alawad MO, El-Hafez HA, Almutairi AN, Alharbi ES, Alhamada R, El-Garaihy BW, El-Garaihy WH (2021) Improved corrosion behavior of AZ31 Alloy through ECAP processing. Metals 11(2):363. https://doi.org/10.3390/met11020363 36. Orlov D, Ralston KD, Birbilis N, Estrin Y (2011) Enhanced corrosion resistance of Mg alloy ZK60 after processing by integrated extrusion and equal channel angular pressing. Acta Mater 59:6176–6186. https://doi.org/10.1016/j.actamat.2011.06.033

730

W. H. El-Garaihy et al.

37. Zohrevand M, Mohammadi-Zerankeshi M, Nobakht-Farin F, Alizadeh R, Mahmudi R (2022) Degradation behavior of the as-extruded and ECAP-processed Mg–4Zn alloy by Ca addition and hydrothermal coating. J Mater Res Technol 20:1204–1215. https://doi.org/10.1016/j.jmrt. 2022.07.072 38. Divya SP, Nagaraj M, Kesavamoorthy M, Srinivasan SA, Ravisankar B (2018) Investigation on the effect of ECAP routes on the wear behavior of AA2014. Trans Indian Inst Met 71(1):67–77. https://doi.org/10.1007/s12666-017-1141-7

Part XIX

Advances in the State-of-the-Art of High Temperature Alloys

Thermodynamic Model-Guided Regulation of Self-propagating In-Situ Synthesis of Titanium–Aluminum Alloys Han Jiang, Zhihe Dou, and Ting’an Zhang

Abstract This study investigates the controlled fabrication of Ti45Al8Nb alloy using self-propagating in-situ synthesis guided by thermodynamic modeling. It explores the impact of the Al stoichiometric ratio on alloy and slag composition, microstructural morphology, and inclusion distribution. Findings demonstrate the thermodynamic model’s effectiveness in governing desired alloy composition, guiding titanium-aluminum alloy composition tailoring. Under specific conditions (Al stoichiometric coefficient 0.8, system’s specific reaction enthalpy 3250 J/g), a titanium-aluminum alloy with Ti, Al, Nb, O, and N mass fractions of 51.8, 29.5, 17.4, 1.2, and 0.0016 wt% is achieved. The primary phases are TiAl and TiAl3 /NbAl3 . Increasing aluminum content reduces inclusion content and size. This study proposes an efficient, scalable method for producing high-quality titanium-aluminum alloys at a reduced cost by leveraging the thermodynamic model to predict and regulate self-propagating synthesis. Keywords Mass action concentration model · Thermite reduction · Superalloy · Titanium–Aluminum Alloy

Introduction Titanium–aluminum alloys are lightweight high-temperature alloys with excellent comprehensive properties, including low density, high strength, outstanding hightemperature mechanical performance, corrosion resistance, and non-magnetic properties. They find wide applications in aerospace, marine, medical devices, and other fields, with promising prospects [1, 2]. However, challenges such as poor roomtemperature formability and inadequate oxidation resistance above 800 °C have H. Jiang · Z. Dou · T. Zhang (B) Key Laboratory of Ecological Metallurgy of Multi-metal Intergrown Ores of Ministry of Education, Special Metallurgy and Process Engineering Institute, Northeastern University, Shenyang 110819, China e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_63

733

734

H. Jiang et al.

long hindered the further development of titanium-aluminum alloys. The addition of niobium has proven to be an effective method for mitigating these performance deficiencies, thereby enhancing their utility and application range. Professor Guoliang Chen from China [3] pioneered the incorporation of niobium into titanium-aluminum alloys, raising their operating temperature by 100 °C. Researchers at Beijing University of Science and Technology’s national key laboratory studied the fabrication process of high-niobium TiAl-based alloys. They used self-consumable melting to produce high-niobium TiAl-based alloys, which raised their melting point by 600 °C. By optimizing the alloy’s properties with carbon, tungsten, and boron elements, and comparing with induction skull melting, they concluded that alloy yield can be regulated by reducing alloy skull weight. Harbin Institute of Technology’s key laboratory utilized the electromagnetic cold crucible continuous casting method to fabricate titanium-aluminum-niobium alloys, resulting in Ti44Al(Nb) alloys with improved strength, albeit with lower preparation efficiency and brittle fracture modes. Currently, the mainstream methods for preparing titanium–aluminium–niobium alloys include powder metallurgy, molten salt electrolysis, external aluminum thermal reduction, and electro-aluminothermic methods [2, 4, 5]. Among these, the electro-aluminothermic method is favoured by researchers due to its low cost. However, it suffers from low current efficiency and instability, preventing largescale continuous production. Directly synthesizing titanium–aluminium–niobium alloys from pure metal powders yields relatively pure products, but the high cost of producing titanium via the Kroll process results in elevated prices for powder metallurgy-prepared alloys. Therefore, there is a need for a low-cost, stable, and efficient method for preparing titanium–aluminium–niobium alloys, which is the main focus of this study. In this study, titanium dioxide (TiO2 ) and niobium pentoxide (Nb2 O5 ) were used as raw materials, with aluminum as the reducing agent and alloying element, calcium oxide (CaO) as the slagging agent, and potassium chlorate (KClO3 ) added to enhance the reaction heat. A chemically compliant titanium-aluminum-niobium alloy was successfully synthesized using a self-propagating high-temperature synthesis method. Thermodynamic design was carried out using a mass action concentration model to obtain a theoretically reasonable material ratio, allowing for the adjustment of the proportions of various raw materials to ensure a stable and continuous reaction. Characterization of the reaction products through X-ray diffraction, scanning electron microscopy, full spectrum spectroscopy, and oxygen-nitrogen analysis yielded insights into the phase composition, microstructure, and chemical composition of the products, leading to the determination of the optimal experimental conditions.

Thermodynamic Model-Guided Regulation of Self-propagating In-Situ …

735

Experiment Experiment Materials and Methods The materials involved in the experiment are presented in Table 1. The experimental procedure includes the following steps: drying, batching, and mixing of materials. Subsequently, the thoroughly mixed materials are placed in a self-propagating reaction vessel and ignited using magnesium powder. The reduction process is rapid and intense. After the reaction is complete, the reaction products are extracted. The bottom part consists of a metal ingot, while the top part is slag. Samples are taken from each part for testing and analysis. The schematic diagram of the experimental process is shown in Fig. 1.

Thermodynamic Model Design The reaction equations for the aluminum thermite self-propagating in-situ reduction smelting process discussed in this paper are as follows: TiO2 + 0.085Nb2 O5 + 2.574Al = Ti + 0.957Al + 0.17Nb + 0.809Al2 O3

(1)

The adiabatic temperature of Eq. (1) has been determined to be 2103 K through calculations. Soviet scholar A. G. Mcrzhanov suggested that the reaction can only Table 1 Raw material for self-propagating preparation of titanium–aluminum–niobium alloy

Fig. 1 Schematic diagram of self-propagating in-situ synthesis equipment

Ingredient

Granularity

Purity

TiO2

0.1–0.3 µm

99.5

Nb2 O5

0.1–0.2 µm

99.9

Al

≤ 3 mm

99.5

KClO3

≤ 2 mm

99.5

CaO

≤ 2.5 mm

99.5

736

H. Jiang et al.

proceed spontaneously and sustain itself when the system’s adiabatic temperature (Tad) exceeds 1800 K. Therefore, it can be inferred that this reaction can occur spontaneously. Subsequently, a mass action concentration model will be employed to predict and analyze the composition of equilibrium phases. Utilizing the Factsage8.1 database in conjunction with binary phase diagrams of Ti–Al, Ti–O, Ti–Nb, Al–Nb, Al–O, and Nb–O, the phase composition (structural units) in the molten state can be determined as follows: Simple atoms: Ti, Al, O, Nb. Complex compounds: NbO, Nb2 O5 , NbO2 , TiO, TiO2 , Ti9 O17 , Ti8 O15 , Ti7 O13 , Ti6 O11 , Ti5 O9 , Ti4 O7 , Ti3 O5 , Ti2 O3 , Ti20 O39 , Ti10 O19 , Al2 O3 , AlO2 , AlO, Ti3 Al, TiAl, TiAl2 , TiAl3 , Ti2 Al5 . Ni (1 ≤ i ≤ 23 and i is an integer) represents the activity concentration of each substance in the metallurgical melt, following the law of mass action, i.e., the equilibrium normalized molar fraction. xi denotes the total molar fraction of a specific ∑ substance in the metallurgical melt after the reaction reaches equilibrium, and X represents the total molar fraction at equilibrium. In accordance with the law of conservation, the calculation formula for the mass action concentration model of the Ti–Al–O–Nb melt is obtained as follows: a · (N2 + 2 · N20 + N21 + N22 + N23 + N24 + 2 · N25 + 3 · N26 + 5 · N27 ) = b(N1 + N8 + N9 + 9 · N10 + 8 · N11 + 7 · N12 + 6 · N13 + 5 · N14 + 4 · N15 + 3 · N16 + 2 · N17 + 20 · N18 + 10 · N19 + 3 · N23 + N24 + N25 + 2 · N27 );

(2)

a · (N3 + N5 + 5 · N6 + 2 · N7 + N8 + 2 · N9 + 17 · N10 + 15 · N11 + 13 · N12 + 11 · N13 + 9 · N14 + 7 · N15 + 5 · N16 + 3 · N17 + 39 · N18 +19 · N19 + 3 · N20 + 2 · N21 + N22 ) = c · (N1 + N8 + N9 + 9 · N10 + 8 · N11 + 7 · N12 + 6 · N13 + 5 · N14 + 4 · N15 + 3 · N16 + 2 · N17 + 20 · N18 + 10 · N19 + 3 · N23 + N24 + N25 + 2 · N27 );

(3)

a · (N4 + N5 + 2 · N6 + N7 ) = d · (N1 + N8 + N9 + 9 · N10 + 8 · N11 + 7 · N12 + 6 · N13 + 5 · N14 + 4 · N15 + 3 · N16 + 2 · N17 + 20 · N18 + 10 · N19 + 3 · N23 + N24 + N25 + 2 · N27 ) (4) N1 + N2 + N3 + N4 + N5 + N6 + N7 + N8 + N9 + N10 + N11 + N12 + N13 + N14 + N15 + N16 + N17 + N18 + N19 + N20 + N21 + N22 + N23 + N24 + N25 + N26 + N27 = 1

(5)

Through calculations, the equilibrium concentrations of various components at 2100 K have been obtained. In order to visually investigate the impact of aluminum content variation on key components, components with mass fractions exceeding 0.1% have been retained, while excluding the three elements Ti, Al, and Nb. The changing trends of the remaining components are depicted in Fig. 2.

Thermodynamic Model-Guided Regulation of Self-propagating In-Situ … 30

TiO Al2O3 chemical composition/(wt%)

Fig. 2 Relationship and the mass fraction of each component under equilibrium state

737

TiO2 TiAl

Ti2O3 TiAl2

25

20

15

0 0.5

0.6

0.7

0.8

0.9

1.0

Allocation coefficient/(g/g)

As the aluminum composition ratio increases, the proportional content of metallic elements at equilibrium gradually rises, while the proportion of low-valence titanium oxides such as TiO and Ti2 O3 decreases. In the equilibrium system, metallic oxides devoid of Nb exist, indicating that their Gibbs free energy is lower than that of TiO2 , making them prone to reduction reactions with Al, thus entering the molten metal system. With an increase in the reducing agent ratio, the formation of metal intermetallic compounds such as TiAl and TiAl2 is promoted. This behavior simultaneously facilitates the reduction reactions of low-valence titanium oxides, further reducing the TiO content in the system. To determine the theoretical optimal aluminum composition ratio, the equilibrium concentrations of the Ti, Al, and Nb alloy phases are analyzed individually (Fig. 3). As the aluminum composition ratio increases, the content of Al and Nb elements shows a negative correlation, with the Ti content reaching its peak at around 0.8. At lower aluminum composition ratios (0.5–0.7), insufficient Al preferentially reacts with Nb2 O5 to produce Nb, while the unreacted Ti oxide further reacts as the aluminum composition ratio increases until it begins to decline when Al is in excess. Considering the significant influence of kinetic factors under practical conditions, the reduction rate of Ti is greatly affected. Therefore, when considering the equilibrium states of Al and Nb separately, relatively effective composition parameters can be theoretically obtained. A linear regression of the ratio of the equilibrium concentrations of Al and Nb to the aluminum composition ratio is shown in Fig. 4. The linear regression equation is y = 3.9263x − 1.4791

(6)

At equilibrium, with Ti content stabilized, the desired mass ratio of Al to Nb metals is 29/17, equal to 1.705 (y = Al/Nb). Substituting this value into the regression equation with x as the aluminum composition ratio, we obtain the theoretical optimal

738

H. Jiang et al.

Fig. 3 Relationship between aluminum coefficient and mass fraction of metal components in equilibrium state

Fig. 4 Relationship between aluminum coefficient and Al/ Nb ratio

aluminum composition ratio as 0.8119. This calculation serves as the theoretical basis for the composition ratio in the subsequent experimental section.

Thermodynamic Model-Guided Regulation of Self-propagating In-Situ …

739

Results and Discussion Effect of Per Unit Mass Unit mass heat effect, a crucial factor in self-propagating reactions, exhibits increased intensity as its numerical value rises. Examining the influence of unit mass heat effect in the range of 2900–3300 J/g on alloy yield and chemical composition trends, the results are depicted in Figs. 5 and 6. With increasing reaction heat, the metal yield initially rises and then declines. When the unit mass heat effect increases (from 2900 to 3200 J/g), the stable temperature at which the reaction system reaches equilibrium rises, and the high-temperature state persists longer. This is conducive to the separation of metals from slag, resulting in a clear slag-metal interface and an increase in metal yield. However, when the unit mass heat effect is excessively high (at 3300 J/g), there is a significant instantaneous

Fig. 5 Alloy yield under different unit mass heating effect

Fig. 6 Change graph of alloy composition under different unit mass reaction heat

740

H. Jiang et al.

temperature increase, causing an overly vigorous reaction and material loss due to molten metal splattering. Consequently, the alloy yield decreases. In summary, under the condition of a unit mass reaction heat of 3200 J/g, the overall reaction is stable, efficient, and controllable. At this point, the alloy yield can reach 46.6%. The reduction of metal oxides in the raw materials occurs spontaneously at high temperatures. The temperature mainly influences the reaction by increasing the effective duration of the high-temperature molten state to enhance the metal reduction rate. As shown in Fig. 6, with an increase in the unit mass reaction heat, the relative time that the high-temperature molten slag-metal exists in a liquid form increases. This extended duration allows denser metals more time to separate from the lower-density slag, promoting the forward progression of the reduction reaction and increasing the reduction rate of Ti. Consequently, the Ti content in the alloy composition increases with the rising unit mass heat effect. Simultaneously, the improved slag-metal separation reduces impurities remaining in the metal, resulting in a decrease in O content in the alloy. However, in the case of the 3300 J/g experimental group, splattering occurs, leading to the loss of surface slag layer protection. This causes a noticeable increase in O and N content in the alloy melt. In summary, considering both yield and alloy chemical composition, under the condition of a stable reaction system without splattering, higher heat generation is more favorable for the aluminum thermite reduction reaction, as well as for the composition and yield of alloy products. In this experimental group, the condition with a unit mass reaction heat of 3200 J/g performs the best.

Effect of Slag Mixing Coefficient The slag system for the Ti, Al, Nb, and O system is the CaO–Al2 O3 binary slag system. To facilitate the upward floatation of the high-melting product Al2 O3 generated in the reaction into the slag, it is crucial to incorporate CaO in a reasonable proportion. The combination of CaO with Al2 O3 forms calcium aluminate with a lower melting point, which enhances the fluidity of the slag and facilitates slag-metal separation. In accordance with the binary phase diagram, the experiment investigated the changes in slag composition when the slag coefficient was set to 0.2, 0.25, 0.3, 0.35, and 0.4. The results are shown in Fig. 7. Within the range of slag coefficients from 0.2 to 0.4, the primary phases in the slag system are composed of CaAl2 O4 , Ca3 Al2 O6 , and CaAl4 O7 . The composite slag’s melting point in this range varies between 1580 and 1750 °C. As the slag coefficient increases, the diffraction peak intensity of CaAl2 O4 and Ca3 Al2 O6 initially increases and then decreases. When the slag coefficient reaches 0.3, a low-melting CaAl4 O7 phase appears, and its diffraction peak intensity increases with an increase in the slag coefficient.

Thermodynamic Model-Guided Regulation of Self-propagating In-Situ …

741

Fig. 7 Phase analysis diagram of slag under different slag mixing coefficients

Taking into account the CaO–Al2 O3 binary phase diagram, theoretically, lower slag melting points, and smaller total slag quantities would result in better slag-metal separation effects. However, within the range of 0.2–0.4, these two factors exhibit a negative correlation. When the total slag quantity is lower, the slag system has a higher melting point, while a lower-melting slag system has a higher total slag quantity. Therefore, it is necessary to further compare alloy compositions to find the optimal point. Figure 8 illustrates the trends in alloy composition under different slag coefficients. As the slag coefficient increases, the Nb content in the alloy remains relatively constant, while the Ti content initially increases and then decreases, accompanied by a decrease and subsequent increase in Al content. Fig. 8 The relationship between different slag distribution coefficients and alloy composition

742

H. Jiang et al.

The increase in Ti content suggests better slag-metal separation at this point, with the reduction-generated Ti forming metal intermetallic compounds that sink to the bottom of the system. This promotes the forward progression of the reduction reaction and accelerates the settling of metal components. With a further increase in the slag coefficient, the slag quantity in the system increases, and the duration of the settling process for the metal becomes longer. This results in some metal products not separating from the slag system in a timely manner, thereby affecting the reduction of Ti. From the perspective of alloy composition, a slag coefficient of 0.3 relatively aligns with the desired composition. Starting from a slag coefficient of 0.2, the Ti content in the alloy initially increases (from 0.2 to 0.3). The primary factor limiting slag-metal separation is the slag’s melting point at lower slag coefficients, which is around 1750 °C. This leads to enhanced reduction, an increase in Ti reduction rate, and alignment with the calculations from the mass action concentration model in the previous section. As the slag coefficient continues to rise (from 0.3 to 0.4), the slag’s melting point decreases further. However, at this point, the limiting factor for slag-metal separation gradually becomes the thickness of the slag layer. The increased distance and longer residence time during the settling of the reduced metal result in poorer separation at the slag-metal interface. This, in turn, hinders the further reduction of Ti’s low-valence oxides, leading to a decrease in Ti content in the alloy. Figure 9 displays SEM images of the alloy under different slag coefficients, along with the SEM image of the slag at a slag coefficient of 0.3. Energy spectrum analyses at the indicated positions are presented in Table 2. Combining the information from both sources, the alloy’s matrix phase is identified as TiAl, with the presence of Nbrich phases and dendritic Ti3 Al phases of varying grain sizes. The primary component of inclusions in the alloy is Al2 O3 .

Fig. 9 SEM images of alloy and slag under different slag mixing coefficients a 0.2, b 0.25, c 0.3, d 0.35, e 0.4, f 0.3 slag sem

Thermodynamic Model-Guided Regulation of Self-propagating In-Situ …

743

Table 2 Phase composition of alloy with different slag coefficient(wt%) Ti

Al

Nb

O

C

Si

2.6

52.8

0

45.5

0

0

2

0.9

49.5

46.5

0

3.1

0

3

56.7

17.5

1.3

0

9

16.5

4

17.2

58.2

24.7

0

0

0

5

52.4

27.1

20.6

0

0

0

6

43.2

53.2

3.7

0

0

0

7

47.6

21.1

14.4

0

16.9

0

8

29.6

52

7.3

0

11.1

0

9

32.4

27.4

15.3

0

21.1

3.7

10

13.4

45.3

28.7

0

12.5

0

No a b c d e

1

The inclusion patterns observed in the microstructure of the alloy align with the predictions from the previous section. At lower slag coefficients (a), inclusions in the alloy have sizes ranging from 10 to 20 µm and are widely distributed, often near the dendritic Ti3 Al regions. The higher melting point of the slag system (around 1750 °C) results in shorter settling times for slag-metal separation, preventing the timely separation of reduction-generated Al2 O3 from the alloy. This corresponds with the findings in Fig. 8, where Ti exhibits lower reduction rates at lower slag coefficients, and Al content is relatively high, favoring the formation of smallergrained AlX Nb intermetallic compounds (point 2). With a further increase in the slag coefficient (d, e), defects start to proliferate in the alloy. Under high slag coefficient conditions, a large amount of slag is present, and the settling distance of alloy phases becomes longer. During this process, some Al2 O3 may be carried into the final alloy product. The matrix phase remains TiAl, with irregular grains composed of a titanium-rich phase containing Nb. Nb content fluctuates irregularly. When the slag coefficient is raised to 0.4, defects in the alloy become more pronounced, with increased cracks and inclusions compared to other conditions. This indicates poor slag-metal separation under high slag coefficient conditions. The alloy phase shows increased shrinkage cracks, a higher defect rate during the cooling process, and a noticeable increase in carbon (C) element content under high slag coefficient conditions. In summary, excessively high or low slag coefficients not only have a negative impact on the chemical composition of the alloy but also significantly increase microstructural inclusions and alloy defect rates. A slag coefficient of 0.3 appears to be the most suitable for practical processes.

744

H. Jiang et al.

Fig. 10 XRD diagrams of alloys with different aluminum coefficients

Effect of Aluminum Addition Coefficient Aluminum serves as both a reducing and alloying agent in the aluminum thermite reduction process. Controlling the amount of aluminum added is crucial to achieve the desired chemical composition in the alloy. To maintain the desired aluminum content within a specific range, it is essential to reduce the aluminum addition coefficient. This reduction decreases the proportion of aluminum in the alloy while increasing the reduction rates of other metal oxides. The experiment explores the impact of aluminum addition coefficients ranging from 0.6 to 1.0 on the alloy products, as shown in Fig. 10, using X-ray diffraction patterns. The alloy primarily consists of TiAl, Al3 Ti, and Al5 Ti2 phases. With an increase in the aluminum addition coefficient, Al3 Ti and Al5 Ti2 phases gradually appear. SEM images and chemical analysis reveal that the matrix consists mainly of TiAl, Al3 Nb, and Al3 Nb phases. Dendritic grains, primarily Ti3Al, protrude from the matrix. Lower aluminum addition coefficients result in a higher Ti content in the matrix and a reduction in Al2 O3 inclusions. As the aluminum addition coefficient exceeds 0.7, the alloy mainly comprises dual-phase matrices of TiAl and Al3 Ti, with some dendritic Ti3 Al. At a coefficient of 1.0, higher Al content results in an Al3 Ti matrix phase, with some dendritic Ti3 Al. This shift occurs due to increased Al content, causing a transition from TiAl to Al3 Ti intermetallic compounds (Fig. 11). At an aluminum addition coefficient of 0.8, SEM images at 2000 × magnification show TiAl as the matrix phase. Energy spectrum analysis identifies dendritic Ti3 Al grains with higher Ti content and irregular Nbx Al phases with higher niobium content. Niobium is dissolved within the TiAl phase and coexists in the alloy (Table 3). The trend of alloy composition with varying aluminum addition coefficients is shown in Fig. 12. As the aluminum addition coefficient increases, the Ti content in the alloy first rises and then decreases, while the Nb content decreases, and the Al content

Thermodynamic Model-Guided Regulation of Self-propagating In-Situ …

745

Fig. 11 SEM images of the alloy obtained under different aluminum distribution coefficient conditions

Table 3 Phase composition of alloys under different aluminum distribution coefficients (wt%) No a b

Ti

Al

Nb

O

Si

1

49.8

26.2

8.1

6.4

9.5

2

38.1

42.7

13.0

6.2

0

3

0.4

52.2

0

47.4

0

4

41.1

37.5

21.4

0

0

c

5

16.4

50.7

32.9

0

0

6

52.4

27.1

20.6

0

0

d

7

42.3

51.8

4.8

0

0

8

56.4

19.2

12.6

8.8

3.0

e

9

43.9

37.7

18.4

0

0

10

70.4

18.0

11.5

0

0

shows an increasing trend. The O and N contents both decrease. When the oxidation of Ti is not complete, increasing the aluminum addition effectively promotes the progress of the reduction reaction. Additionally, increasing the aluminum content as a reducing agent can make the reduction reaction more thorough and rapid, effectively reducing the O and N contents in the alloy. In conclusion, an aluminum addition coefficient of 0.8 is the optimal value in practice. This aligns closely with the theoretical value obtained from the mass action concentration model, confirming the feasibility of using the concentration action model for predicting alloy composition.

746

H. Jiang et al.

Fig. 12 Relationship between different aluminum coefficient and alloy composition

Conclusions In this study, the mass action concentration model was utilized for predicting the composition of in-situ reduced titanium-aluminum alloys. The significance of the material ratio process in the self-propagating synthesis was emphasized. Three parameters, namely, the unit mass reaction heat, slagging coefficient, and aluminum addition coefficient, were examined for their influence on the process, thereby validating the accuracy and scientific validity of the theoretical model. The conclusions are as follows: (1) By establishing a mass action concentration model for thermodynamic design, the theoretical optimal aluminum addition coefficient in the Ti–Al–Nb–O system at an adiabatic temperature of 2100 K was determined to be 0.8119. (2) Through changes in the initial composition ratios of materials, it is possible to achieve stable self-propagating high-temperature synthesis of titaniumaluminum-niobium alloy. The optimal experimental parameters obtained were a unit mass reaction heat of 3200 J/g, a slagging coefficient of 0.3, and an aluminum addition coefficient of 0.8. At these conditions, the main phases in the alloy are TiAl, Al3Ti, and Ti2Al5. The mass fractions of Ti, Al, Nb, O, and N in the alloy are 51.8%, 29.5%, 17.5%, 1.2%, and 0.0016%, respectively. (3) This process uses metal oxides as raw materials to produce titanium-aluminumniobium alloys, avoiding the high energy consumption and lengthy processes associated with the Kroll method for producing sponge titanium as raw material. It is an efficient and controllable manufacturing process with broad prospects and industrial potential.

Thermodynamic Model-Guided Regulation of Self-propagating In-Situ …

747

References 1. Clemens H, Mayer S (2013) Design, processing, microstructure, properties, and applications of advanced intermetallic TiAl alloys. Adv Eng Mater 15(4):191 2. Kothari K, Radhakrishnan R, Wereley NM (2012) Advances in gammatitanium aluminides and their manufacturing techniques. Prog Aerosp Sci 55:1 3. Li D, Wang B, Luo L, Li X (2022) In-situ synthesis of Al2O3-reinforced high Nb–TiAl laminated composite with an enhanced strength-toughness performance. Ceramics Int 48(2):1589–1602 4. Lu X, He XB, Zhang B, Zhang L, Qu XH, Guo ZX (2009) Microstructure and mechanical properties of a spark plasmasintered Ti–45Al–8.5Nb–0.2W–0.2B–0.1Y alloy. Intermetallics 17(10):840 5. Stroosnijder MF, Zheng N, Quadakkers WJ, Hofman R, Gil A, Lanza F (1996) The effect of niobium ion implantation on the oxida-tion behavior of a c-TiAl-based intermetallic. Oxid Met 46(1):19

Part XX

Advances in Titanium Technology

A New Low-Cost, Short-Flow, and Clean Preparation Process for Ti6Al4V Alloys Daoguang Du, Jishen Yan, Zhihe Dou, and Ting’an Zhang

Abstract Ti6Al4V alloy has many advantages such as high specific strength, good corrosion resistance and biocompatibility, and is the most widely used titanium alloy. At present, the industrial production of titanium must use titanium sponge (Kroll method) as raw material, and the production cycle is long, high cost, cannot meet the requirements of the development of circular economy and environmental protection, which greatly limits the large-scale application of titanium. We have designed and developed the “high-performance titanium/titanium alloy thermoelectric coupling low-cost short-flow preparation of a series of new process system”. We have designed and developed a new method to prepare Ti6Al4V alloy powder by self-propagating multistage reduction and one-step in-situ reduction using Ti6Al4V alloy as the representative titanium alloy. The method has completed semi-industrial tests and established the world’s first demonstration production line for the low-cost, short-flow, clean production of Ti6Al4V powder and Ti powder by this method, which can reduce the cost of titanium production by more than 30%, and is expected to boost the further development of the titanium and titanium alloy industry. Keywords Ti · Ti6Al4V · Self-propagating · Low-cost · Short-flow

D. Du · Z. Dou (B) · T. Zhang (B) Key Laboratory of Ecological Metallurgy of Multi-metal Intergrown Ores of Ministry of Education, Northeastern University, Shenyang 110819, China e-mail: [email protected] T. Zhang e-mail: [email protected] School of Metallurgy, Northeastern University, Shenyang 110819, China J. Yan School of Intelligent Manufacturing, Nanyang Institute of Technology, Nanyang 473004, China © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_64

751

752

D. Du et al.

Introduction Titanium and titanium alloys are characterized by high specific strength, corrosion resistance, non-magnetism, low damping, good biocompatibility, and unique properties, such as superconductivity, shape memory, and hydrogen storage, and are known as “all-purpose metal”, “space metal”, “ocean metal”, and so on [1, 2]. It is also classified as a strategic metal by countries around the world and is widely used in aerospace, marine engineering, medical industry, nuclear industry, chemical industry, and energy [3–5]. The Ti6Al4V alloy, developed in 1953 by H.D. Kessler and M. Hansen, is one of the most widely used titanium alloys today. At present, the industrial production of titanium not only requires titanium sponge (Kroll method) as raw material, but also has a long production cycle and high cost, which cannot meet the requirements of the development of recycling economy and environmental protection, and greatly limits the large-scale application of titanium materials. Scholars have proposed many new methods to replace the Kroll process. For example, the electrochemical methods such as FFC [6, 7], OS [8], and USTB [9] with TiO2 as raw material, but these methods need to solve the technical problems such as unstable current efficiency, difficulty in deoxidizing titanium oxide and control of trace impurities. In addition to electrolytic preparation of titanium, metalthermal reduction (MRC) is another promising low-cost method for the preparation of titanium. The MRC method aims to reduce titanium oxide or titanium chloride with alkali sodium salts or alkaline-earth metals such as magnesium and calcium to obtain titanium and titanium-alloy powders. Yamamoto [10] and Weil [11], among others, used TiCl4 , AlCl3 , and VCl4 as the raw materials, and sprayed these materials into molten Na or Mg for reduction to obtain Ti6Al4V powders. However, this method requires the preparation of TiCl4 by the Kroll method first. Self-propagating high-temperature synthesis (SHS) is an attractive method for extracting titanium powders due to its short process, simple system, and low cost. Since 1980, combustion synthesis has been proposed for the preparation of titanium powders [12]. Northeastern University, Ting’an Zhang, Zhihe Dou, et al. proposed the “high-performance titanium/titanium alloy thermoelectric coupling low-cost shortflow preparation of a series of new process system” using metal oxides and reducing metals as raw materials, using the SHS method or coupling the SHS method with the material/metallurgical thermoelectric method of low-cost short-flow preparation of titanium/titanium alloys, including multistage. The method of preparing titanium and titanium alloy powders by multistage reduction [13–16] and so on. The new process system avoids the trouble caused by using TiCl4 as intermediate product in Kroll method, avoids the problem that the molten salt cannot be recycled in electrolysis method and traditional thermal reduction method, improves the utilization rate of reductant relative to the traditional metal thermal reduction, has the outstanding characteristics of low cost, short process and clean, realizes the theoretical breakthroughs

A New Low-Cost, Short-Flow, and Clean Preparation Process …

753

and technological innovations in the integration of the material metallurgy and preparation, and successfully prepares Ti6Al4V powder [17, 18], titanium powder [19– 21], titanium-aluminum alloy ingots [22–24], high-titanium ferroalloys [25, 26], Ti5Al2.5Fe [27], and so on. This paper focuses on the progress related to the new process system in the preparation of Ti6Al4V alloy. In order to meet the growing market demand for Ti6A4V alloy powders, we propose a multistage deep reduction new method with magnesiothermic self-propagation primary reduction and calciothermic deep reduction, as well as a new method of calciothermic self-propagating one-step in-situ synthesis, and successfully prepared Ti6A4V alloy powder. We have developed the core equipment of the method, completed semi-industrialization experiments, and established the world’s first demonstration production line for the low-cost and clean preparation of Ti6Al4V and Ti powders by the method. In order to further explore the potential of the process, we are also carrying out research on “One-step in-situ preparation of Ti6Al4V alloy ingots by self-propagation protected by raw slag shells” and other related studies.

Experiment TiO2 , V2 O5, and Al provide the alloying elements and Mg and Ca participate in the reaction as reducing agents, respectively, and these are the five most important raw materials in the experimental process. Hydrochloric acid is involved in the removal of acid-soluble substances in the pickling process. Argon was used as a protective gas and participated in regulating the initial reaction pressure. TiO2 and V2 O5 were dried in a desiccator using a temperature of 393 K for 24 h prior to the experiment to remove possible moisture and some volatile impurities.

Multistage Deep Reduction Experiments Multistage deep reduction new method with magnesiothermic self-propagation primary reduction and calciothermic deep reduction is shown in Fig. 1. The raw materials (TiO2 , V2 O5 , Al, and Mg) were firstly mixed uniformly in a mixer, and then placed in a self-propagating furnace, relying on the ignition electrode to ignite the materials in the kettle for the magnesiothermic self-propagating reaction, and then the reduction products were washed and dried using dilute hydrochloric acid. Next, the dried product was mixed with Ca grains for calciothermic deep reduction. Finally, the deep reduction product was washed with dilute hydrochloric acid and dried to obtain Ti6Al4V alloy powder.

754

D. Du et al.

Fig. 1 Process of preparing Ti6Al4V alloy powder by multistage deep reduction

One-Step In-Situ Reduction Experiments The process of calciothermic self-propagation one-step in-situ synthesis of nearspherical Ti6Al4V alloy powders is shown in Fig. 2. The raw materials (TiO2 , V2 O5 , Al and Ca) were firstly mixed uniformly in a mixer and then placed in a high temperature self-propagating furnace for reaction. The reacted materials were washed with dilute hydrochloric acid and dried to obtain nearly spherical Ti6Al4V alloy powders.

Fig. 2 In-situ preparation of Ti6Al4V alloy powders by calciothermic self-propagation one-step process

A New Low-Cost, Short-Flow, and Clean Preparation Process …

755

Preparation of Ti6Al4V Alloy Powder by Multistage Deep Reduction In this part, the magnesiothermic self-propagation unfolding mechanism for the preparation of Ti6Al4V alloy powders by multistage deep reduction was investigated by comparing the TiO2 –Mg, TiO2 –V2 O5 –Mg, TiO2 –Al–Mg, and TiO2 – Al–V2 O5 –Mg systems, and the magnesiothermic self-propagation primary reduction process was investigated experimentally by using one-factor-variable method [13, 14, 17, 28]. The self-propagating primary reduction leads to porous Ti–Al–V–O precursors with oxygen contents ranging from 6.174 to 16.4 wt %, which creates favorable thermodynamic and kinetic conditions for calorimetric deep reduction. The deep calcium-thermal deoxidation of the precursor at a temperature of 1173 K also further reduced the Mg content in the product, which in turn resulted in a high-purity Ti6Al4V alloy powder. The new method proposed in this part mainly consists of four production steps: magnesiothermic self-propagating primary reduction process (5–6 h), calciothermic deep reduction process (15 h), and two acid leaching and drying processes (12 h). The magnesiothermic self-propagating primary reduction stage requires only a small amount of electrical energy to start the reaction, and the deep reduction stage consumes electrical energy but not much energy. Therefore, this new method can complete a production cycle in 48 h, which has a great potential for industrial production and a huge advantage over the Kroll process.

Preparation of Ti6Al4V Alloy Near-Spherical Powders by One-Step In-Situ Reduction The process study of multistage deep reduction revealed that it is difficult to reduce the oxygen content in titanium and titanium alloy products to very low levels only by the magnesiothermic self-propagating primary reduction process. The use of Mg as a reducing agent could not reduce the mass percent of O in TiO2 to less than 0.3% due to unbreakable thermodynamic limitations. In contrast, the mass percent of O in the product obtained by calciothermic reduction can be less than 0.3%. The conventional metal thermal reduction process has a slow mass transfer rate and often requires a long holding time with the assistance of an external heat source to reduce the oxygen content in TiO2 powder to a certain level [14]. In order to further explore the potential of the process system, a new breakthrough is realized on the basis of the multistage deep reduction method. In this chapter, the conventional calciothermic reduction process is discarded, and a calciothermic selfpropagating one-step in-situ reduction is realized to directly prepare Ti6Al4V alloy near-spherical powders.

756

D. Du et al.

We carried out a thermodynamic theoretical study of the TiO2 –V2 O5 –Al–Ca system and used the one-factor-variable method to experimentally investigate the evolution patterns of the physical phase, composition, morphology, and particle size of the products during the calciothermic self-propagation process, which in turn led to the determination of the optimal process conditions, and the successful preparation of near-spherical Ti6Al4V alloy powders. Meanwhile, we further investigated the sphericalization process of the reduced products, and found two necessary conditions for the system to produce near-spherical product particles: (1) the adiabatic temperature of the self-propagating system is higher than the melting point of the products, and (2) there is an excess of liquid calcium metal in the reaction process. The product spheroidization process can be described as the four stages of “sintering - reduction - spheroidization - solidification”.

Industrial Expansion Test Experimental Investigations Through the amplified experimental study, and the examination of the additives, the amount of calcium reductant, argon pressure, the particle size of calcium reductant, the processing temperature of TiO2 and the ratio of raw materials, and other factors, the “one-step in-situ reduction” as the optimal process for semi-industrial experiments was determined. The Ti6Al4V alloy powder has been successfully prepared, and the mass content of Al and V meets the requirements of the Chinese national standard “GB/T 34,486-2017”, and the product has a uniform particle size distribution and a certain degree of safety in the air. The world’s first demonstration production line of Ti6Al4V powder and Ti powder by this method was established, and the whole line was put into production in December 2019 [16]. The process can reduce the production cost of titanium and titanium alloys by more than 30%, laying an industrialized foundation for low-cost, short process, clean production of titanium, and titanium alloys.

Comparison of Two New Processes A comparison of the production and product characterization of the two new processes is shown in Table 1. The “multistage deep reduction method” uses more equipment and has a longer production cycle than the “one-step in-situ reduction method” because of the additional deep reduction process. It can be seen from the characterization of the products prepared by these two methods that there is little difference in the oxygen content of the two products. However, the product prepared by the “multistage deep reduction method” has a higher number of impurities, a larger particle size, and a smaller vibration density and bulk density. Therefore, the “one-step in-situ reduction method” was selected as the best process for scale-up experiments.

A New Low-Cost, Short-Flow, and Clean Preparation Process …

757

Table 1 Comparison between the production process and the products of the two new processes Factor

Multistage deep reduction method

One-step in-situ reduction method

Process cycle time

Approx. 33 h

Approx. 12 h

Alloying element content (wt%)

Al: 5.5–6.75, V: 4.5–5.5

Al: 5.5–6, V: 4.5–5.5

Product description

Porous networked

Subglobular

Oxygen content (wt%)

0.2–0

0.18–0.3

Mg, Ca elemental content (wt%)

Mg < 0.1 Ca: 0.1–0.2

Ca < 0.1

Particle size (D50) (µm)

30–70

10–20

0.4–0.5

0.25–0.6

Specific surface area

(m2 /g)

Exploration of Semi-industrialized Experiments The maximum pressure that can be reached by the reaction is one of the first technical parameters to be examined. The maximum pressure that can be reached by the reaction is not only related to the selection of equipment, but also can predict the state of the reaction. Therefore, the maximum atmospheric pressure reached during the reaction was calculated for different charging volumes. The results of the calculation are shown in Fig. 3 (taking 120 L reactor as an example). As can be seen from Fig. 3, when the initial argon pressure in the reactor is certain, with the increase in the amount of charge in the reactor, the maximum pressure that can be reached by the reaction first increases sharply and then increases slowly. When the amount of material in the reactor is the same, with the increase of the initial argon pressure, the maximum pressure reached by the reaction also increases. When the charge amount was increased to 40 kg, the maximum pressures of the system corresponding to the four different initial argon pressures increased to 0.6, 3.35, 6.64, and 13.05 MPa, respectively. This is because when the amount of charge is small, a large number of argon gas acts as a diluent, so that the overall Fig. 3 Maximum pressure in the system for different charge volumes

758

D. Du et al.

temperature of the system is reduced, due to the argon gas at this time accounted for a large percentage, so with the increase in the amount of charge reaction can reach the maximum pressure increased significantly. But when the amount of material to reach a certain weight, argon as a diluent role is significantly weakened, so the reaction of the highest temperature can be reached gradually converge to the theoretical adiabatic temperature. Figure 4 shows the actual pressure–time variation curves during the scaled-up experiments. The highest reaction pressure is 2.08 MPa in Fig. 4a, 1.17 MPa in Fig. 4b, and 1.16 MPa in Fig. 4c, and the highest reaction pressures are lower than the calculated values in Fig. 3. The pressure–time variation curves can be divided into three parts: the rapid ramp-up phase, the slow ramp-up phase, and the ramp-down phase. The rapid pressurization stage occurs at the beginning of the ignition, which is due to the use of “powder” as the ignition agent can quickly ignite the reaction, often within a few seconds can make the kettle pressure rises sharply. In the reaction process, no rapid ignition of the block material can only be through the energy transfer between the other blocks to trigger the self-propagating reaction, at this time the self-propagating reaction occurs per unit of time of the material is reduced, showing a slow pressure stage. After the end of the self-propagating reaction, the heat in the system is decreasing, showing a depressurization stage. The average oxygen contents of the products in Fig. 4a–c were 0.716 wt%, 0.202 wt%, and 0.223 wt%, respectively. Since a charge of 20 kg has basically reached the maximum carrying capacity of the 120 L self-propagating furnace, a charge of 20 kg and a starting argon pressure of 0.5 MPa were used as the reaction conditions. Table 2 shows the chemical composition of the samples during the experiment, it can be seen that the oxygen content of the samples is 0.093 wt%, and the content of Al and V is in accordance with the requirements of the Chinese national standard “GB/T 34,486-2017”. Figure 5 shows the microscopic morphology pictures of the products during the actual production process. The morphology of the final product can be seen through Fig. 5a, b as irregular lumps, which are interspersed with some near-spherical particles; no defects, such as holes, can be seen inside the product through the TEM picture shown in Fig. 5c. Figure 6 shows the EDS-TEM analysis results of the product, which shows that the distribution of alloying elements in the product is relatively uniform, and the oxygen content is always at a low level. Figure 7 shows the particle size distribution curve of the product during the actual production process. It can be seen from Fig. 7 that the particle size distribution of the final product is more concentrated, in which the values of D10, D50, and D90 are 15.03 µm, 30.79 µm, and 56.72 µm, respectively. Figure 8 shows the TGA and DTG curves of the product with a heating rate of 10 K/min. It is obvious from the DTG curves that the rate of increase in the mass of the product increases significantly when the temperature exceeds 908 K, reaches a maximum at 1219 K, and the mass remains almost unchanged when the temperature exceeds 1373 K. This indicates that the product is also safe for use in air. Therefore, it shows that the product is also safe in air. In addition, the theoretical mass gain of Ti6Al4V when fully oxidized is 66.36%, which is very close to the test result

A New Low-Cost, Short-Flow, and Clean Preparation Process …

759

Fig. 4 Pressure–time curves during the actual reaction: a 10 kg charge, starting argon pressure 1 MPa; b 10 kg charge, starting argon pressure 0.5 MPa; c 20 kg charge, starting argon pressure 0.5 MPa

Table 2 Composition of a batch of the product of industrial experiments Element

O

V

Al

Ca

Ti

wt%

0.093

4.14

6.21

0.03

Bal

Fig. 5 Microstructure of the product

(66.136%), indicating that the design of the alloy composition for direct reduction and in-situ synthesis is feasible.

760

D. Du et al.

Fig. 6 EDS-TEM analysis Fig. 7 Particle size distribution of products

Fig. 8 Experimental analysis of the oxidation of the products

Conclusions (1) The research and development of the “high-performance titanium / titanium alloy thermoelectric coupling low-cost short-flow preparation of a series of new process system”, using the SHS method or SHS method and materials /

A New Low-Cost, Short-Flow, and Clean Preparation Process …

761

metallurgy thermoelectric method coupled with low-cost short-flow preparation of titanium/titanium alloys, successfully prepared Ti6Al4V powder, Ti powder, titanium-aluminum alloy ingots, high-titanium ferroalloys, Ti5Al2.5Fe, and so on. (2) In the preparation of Ti6Al4V alloy, a new multistage deep reduction process of magnesiothermic self-propagation primary reduction and calciothermic deep reduction has been developed. To further explore the potential of the process, we have developed a new process of one-step in-situ synthesis by calciothermic self-propagation, and are now carrying out related research on “one-step in-situ preparation of Ti6Al4V alloy ingots by self-propagation with protection of slag shells” and so on. (3) The core equipment of the relevant process has been developed, realizing the theoretical breakthrough and technological innovation in the integration of material and metallurgical preparation, and establishing the world’s first demonstration production line for low-cost, short-flow, and clean production of Ti6Al4V powder and Ti powder of the method, which can reduce the production cost of titanium material by more than 30%, and is expected to boost further development of titanium and titanium alloy industry.

References 1. 2. 3. 4. 5. 6. 7. 8. 9.

10.

11.

12.

13.

Deng GZ (2010) Titanium metallurgy. Metallurgical Industry Press, Bei Jing Mo W (2006) Titanium metallurgy, 2nd edn. Metallurgical Industry Press, Bei Jing Ma HJ (1982) Titanium metallurgy. Metallurgical Industry Press, Bei Jing Zhou ZW (2012) Titanium Handbook. Chemical Industry Press, Bei Jing Zhang XY, Zhao YQ, Bai CG et al (2005) Titanium alloys and applications. Chemical Industry Press, Bei Jing Chen GZ, Fray DJ, Farthing TW (2000) Direct electrochemical reduction of titanium dioxide to titanium in molten calcium chloride. Nature 407:361–364. https://doi.org/10.1038/35030069 Chen GZ (2020) Interactions of molten salts with cathode products in the FFC cambridge process. Int J Miner Metall Mater 27:1572–1587. https://doi.org/10.1007/s12613-020-2202-1 Suzuki RO, Inoue S (2003) Calciothermic reduction of titanium oxide in molten CaCl2 . Metall Mater Trans B 34:277–285. https://doi.org/10.1007/s11663-003-0073-2 Wang QY, Song JX, Wu JY, Jiao SQ, Hou JG, Zhu HM (2014) A new consumable anode material of titanium oxycarbonitride for the USTB titanium process. Phys Chem Chem Phys 16:8086–8091. https://doi.org/10.1039/C4CP00185K Chen W, Yamamoto Y, Peter WH et al (2012) The investigation of die-pressing and sintering behavior of ITP CP-Ti and Ti-6Al-4V powders. Powder Technol 541:440–447. https://doi.org/ 10.1016/j.jallcom.2012.06.131 Weil KS, Hovanski Y, Lavender CA (2009) Effects of TiCl4 purity on the sinterability of Armstrong-processed Ti powder. J Alloy Compd 473(1–2):L39–L43. https://doi.org/10.1016/ j.jallcom.2008.06.097 Frolov JV, Fetzoy VP (1984) Synthesis of submicron titanium powder under the combustion mode. Paper presented at the first all-union symposium on macroscopic kinetics and chemical gasodynamics. Chernogolovka Zhang TA, Dou ZH, Liu Y et al (2019) A method of preparing reduced titanium powder by multistage deep reduction. CN. CN107236869B. 26 Feb 2019

762

D. Du et al.

14. Yan JS, Dou ZH, Zhang TA et al (2021) A new process of preparing Ti6Al4V powder by a multistage depth reduction process. Rare Metal Mater Eng 50(9):3094–3101 15. Fan SG, Dou ZH, Zhang TA et al (2019) Deoxidation mechanism in reduced titanium powder prepared by multistage deep reduction of TiO2. Metall Mater Trans B 50:282–289. https://doi. org/10.1007/s11663-018-1466-6 16. Zhang TA, Dou ZH (2020) Novel multi-stage deep thermal reduction technology for titanium and titanium alloys. Titan Ind Prog 37(2):43–48 17. Yan JS, Dou ZH, Zhang TA, Niu LP (2021) Preparation of Ti6Al4V alloy powder by multistage depth reduction process. Rare Metal Mater Eng 50(8):2973–2978 18. Cheng C, Dou ZH, Zhang TA, Zhang HJ, Yi X, Su JM (2017) Synthesis of as-cast Ti-Al-V alloy from titanium-rich material by thermite reduction. JOM 10:1818–1823. https://doi.org/ 10.1007/s11837-017-2467-7 19. Fan SG (2016) Basic research on the preparation of titanium powder by multistage deep reduction method. M.A. thesis, Northeastern University (China) 20. Fan SG, Dou ZH, Zhang TA, Zhang BW, Niu LP (2020) Direct preparation of Titnium powder bu multistage deep reduction. Rare Metal Mater Eng 49(3):1020–1023 21. Zhou XY, Dou ZH, Zhang TA, Yan JS, Yan JP (2022) Preparation of low-oxygen Ti powder from TiO2 through combining self-propagating high temperature synthesis and electrodeoxidation. Trans Nonferrous Metals Soc China 32(10):3469–3477. https://doi.org/10.1016/S1003-632 6(22)66033-3 22. Song YL, Dou ZH, Zhang TA, Liu Y (2019) A novel continuous and controllable method for fabrication of as-cast TiAl alloy. J Alloy Compd 789:266–275. https://doi.org/10.1016/j.jal lcom.2019.03.050 23. Song YL, Dou ZH, Zhang TA, Liu Y, Niu LP (2020) Preparation of TiAl master alloy by metallothermic reduction. Rare Metal Mater Eng 49(3):1015–1019 24. Song YL, Dou ZH, Zhang TA, Liu Y, Wang GC (2019) Firstprinciples calculation on the structural, elastic and thermodynamic properties of TiAl intermetallics. Materi Res Express 6(10):1065a4. https://doi.org/10.1088/2053-1591/ab3e11 25. Cheng C, Dou ZH, Zhang TA, Su JM, Zhang HJ, Liu Y, Niu LP (2018) Sulfur distribution in preparation of high titanium ferroalloy by thermite method with different CaO addition. Rare Met 38:793–799. https://doi.org/10.1007/s12598-018-1170-3 26. Cheng C, Dou ZH, Zhang TA, Su JM, Zhang HJ, Liu Y, Niu LP (2018) Oxygen content of high ferrotitanium prepared by thermite method with different melt separation temperature. Rare Met 38:892–898. https://doi.org/10.1007/s12598-019-01218-1 27. Zhang BW (2018) Basic study on the preparation of Ti-5Al-2.5Fe alloy powder by multistage deep reduction method. M.A. thesis, Northeastern University (China) 28. Yan JS, Dou ZH, Zhang TA (2022) Magnesium thermal self-propagation mechanism during the preparation of Ti6Al4V alloy powders by multistage deep reduction method. Rare Metal Mater Eng 51(8):2892–2898

Insight into the Impacts of Heat Treatment on Microstructure and Mechanical Properties of TC11 Titanium Alloy Zhen Yan and Jianfa Jing

Abstract The effect of heat treatment on the microstructure and mechanical properties of TC11 titanium alloy were investigated. The α phase begins to transform to the β phase at 950 °C, and the α phase has almost completely transformed to the β phase at 1100 °C. After the alloy aging tread, the fine secondary alpha phase becomes more abundant. The cycle heat treatment results show that the strength of the alloy decreases, and its plasticity and toughness increase as the number of cycle heat treatments increases. This is due to the gradual increase in the number of needle-like secondary α phases interspersed at the α phase interface impedes slip. The ultra-high circumferential fatigue results show that the ultra-high fatigue strength at 109 cycles for a failure probability of 50% (σ9 (10)) was calculated as 690 Mpa. In summary, the fatigue life of the TC11 alloy can exceed 109 . Keywords Titanium · Phase transformation · High-temperature materials · Cycle heat treatments · Ultra-high circumferential fatigue

Introduction TC11 titanium alloy belongs to α + β titanium alloy, which possesses a high strength below 500 °C and is used widely in aerospace, marine, and chemical industries [1−2]. Compared with the traditional Ti-6Al-4 V alloy, the TC11 titanium alloy provides the distinct advantages of higher strength and better thermal stability [3, 4]. This outstanding characteristic is attributed to adding the beta isomorphous element Mo, neutral element Zr, and beta eutectoid elements Si into the Ti-6Al base, with a nominal composition Ti-6.3Al-1.6Zr-3.4Mo-0.3Si [5, 6]. Hot forming processing of TC11 alloy often involves steps from coging the as-cast ingot to the final part forming with a specific microstructure as the goal [1, 7]. Therefore, to improve the Z. Yan · J. Jing (B) School of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_65

763

764

Z. Yan and J. Jing

overall performance of titanium alloys with fixed alloy composition, we have to start with their processing. Various efforts have been reported on the processing. Li [8] reported the deformation behavior of TC11 titanium alloy with beta microstructure between 750 °C and 1100 °C under the strain rate ranging from 0.001 s−1 to 10 s−1 by the THERMECMASTOR-Z simulator. The results showed that in the α + β region, the spheroidization fraction of α lamellar decreased with increasing temperature. In contrast, in near-β and β phase regions, dynamic recrystallization fraction increased with increasing temperature in all strain rates except at the strain rate of 0.001 s−1 . Based on this, Li [9] studied the grain size, and the volume fraction of prior α in hightemperature deformation appears highly nonlinear and fuzzy. The results showed that the grain size decreases sharply after a slight increase in deformation temperature. The volume fraction decreases at the deformation temperature of more than 1123 K; their predicted results were consistent with the experimental results in the isothermal compression of TC11 alloy. Zhang [10] also conducted the isothermal compression of TC11 alloy by using a Gleebe-1500 hot-simulator with the deformation temperatures ranging from 1023 to 1323 K. The strain rates ranged from 0.001 to 10 s−1 , and the height reductions ranged from 50 to 70%. The results indicated that the apparent activation energy for deformation in isothermal compression of the TC11 titanium alloy decreases with the increase of strain. Moreover, the apparent activation energy for deformation in the α + β two-phase region of the TC11 titanium alloy increases with the increasing deformation temperature and decreases with the increasing strain rate. Furthermore, the processing map has been used to represent the dynamics of metals and alloys in hot forming [11]. Seshacharyulu et al. [12] developed a processing map for hot working commercial-grade Ti–6Al–4 V alloy with a lamellar structure. The microstructural mechanisms were investigated at different deformation temperatures and strain rates using different strain rates on the map. The various domains in the map corresponding to different dissipative characteristics were identified as follows: grain boundary sliding, dynamic recrystallization, and dynamic recovery, the TC11 alloy with the same properties. All of these studies have been devoted to analyzing the deformation behavior of TC11 alloy during thermal processing. However, the previous evolutionary pattern of the finished titanium alloy’s corresponding thermodynamic and microstructural structure remains unclear. In this study, the effect of heat treatment on the microstructure and mechanical properties of TC11 titanium alloy was investigated. For this purpose, FactSage 8.0 was used to predict the phase transformation behavior. As confirmed in our previous research paper, this software can accurately predict phase changes in alloy properties [13]. The XRD results and microstructure further confirm the veracity of the software predictions. In addition, the tensile properties of the TC11 alloy under different heat treatment conditions were tested and analyzed, the changes in microstructure during the heat treatment process were analyzed, and the correspondence between microstructure and tensile properties was finally established. The final test analyzed the ultra-high circumferential fatigue life of the alloy. This provided theoretical and technical guidance for the later heat treatment of TC11 alloys.

Insight into the Impacts of Heat Treatment on Microstructure …

765

Experimental Details The TC11 alloy used in the present work is an α + β titanium alloy as hot-rolled bars with a diameter of 40 mm. The TC11 titanium alloy had the following chemical composition (wt%): 6.64 Al, 3.46 Mo, 1.74 Zr, 0.26 Si, and balance Ti. The tensile test was conducted by an Instron-4507 electronic tensile testing machine with a 3 mm/min constant strain rate. After tensile tests, the samples were processed into a size of 10 mm × 10 mm × 10 mm by wire-electrode cutting. And then, the samples were polished with progressively finer grades (from 80# to 2000#) of silicon carbide-impregnated emery paper to remove all the surface irregularities and machining marks. The samples were etched using 10%HF + 30%HNO3 + 60%H2 O for 5 s. The corroded samples were utilized for microstructure analysis. An electromagnetic resonant testing machine (QBG-100) with a high-temperature furnace (Max. temperature: 1200 °C) conducted the axial loading fatigue tests at elevated temperatures. According to the service environment of components, the fully reversed loading and pulsating loading, i.e., the stress ratios R of − 1 and 0, are adopted. The related environment temperatures are 25 °C, 150 °C, and 250 °C, respectively, corresponding to the service temperature of aero-engine parts. The testing cycles were about 104 –1010 cycles, and the defined failure criterion is the complete fracture of the specimen. The microstructure and crystal structure of the samples were investigated through light microscopy (OM, Lecia MeF3A), X-ray diffraction (XRD, PANalytical, Empyrean, 45 kV, 40 mA, Cukα, 2°/min), and analytical scanning electron microscopy (SEM, TESCAN, MIRA3, LMH with Ulti max20), respectively. The alloy phase change prediction was analyzed by the “Equilib” and “Phase Diagram” modules of FactSage 8.0 with the databases “Fssteel”.

Results and Discussion Effect of Solid Solution Temperature on Phase Transformation Behavior The equilibrium diagram of different phases in TC11 alloy at different temperatures, calculated by FactSage 8.0 and the module of “Equilib” with the databases “Fssteel.“, as shown in Fig. 1. It indicated that the content of the α phase and β phase remained unchanged when the temperature was below 950 °C. As the temperature increases, the content of the α phase decreases quickly, while the β phase increases. When the temperature was above 1100 °C, the α phase almost completely disappeared; only the β phase is present in the TC11 alloy. To prove the effect of the solid solution temperature on the microstructure evolution. The TC11 alloys are heat-treated at 925 °C/1 h, AC; 950 °C/1 h, AC; 975 °C/1 h, AC; 1000 °C/1 h, AC; and 1025 °C/1 h, AC, respectively. The XRD patterns of the treated specimens at different temperatures

766

Z. Yan and J. Jing

Fig. 1 Equilibrium diagram of different phases in TC11 alloy at different temperatures (calculated by FactSage 8.0 and the module of “Equilib” with the databases “Fssteel”)

were shown in Fig. 2. The specimens showed the diffraction peaks corresponding to the α-Ti (hcp) and β-Ti (bcc) phases. No additional phase was generated, and the peak positions of the α and β phases did not change after heat treatment when the temperatures were below 950 °C. However, the intensities of the α (002), α (101), and β (110) peaks changed, indicating that the grain orientation of the specimen had been transformed. The intensities α (002) peak gradually decreases when the temperature was over 950 °C and then disappears at 1000 °C. The morphologies of the initial sample and the heat-treated samples were examined by light microscopy, and the results are shown in Figure. The α phase in the initial sample almost equiaxed crystal form in Fig. 3a. As the temperature increases, the equiaxed crystal α phase began gradually transformed into the platelet α phase when the heat treatment temperature is 925–950 °C (Fig. 3b–c). It is worth noting that both the equiaxed α phase and the platelet α phase tend to dissolve at 975 °C (Fig. 3d). When the heat treatment temperature is increased to 1000 °C, the majority of the α phase is dissolved, and the β phase is exposed (Fig. 3e). Figure 3f showed that all α phases dissolve, and only the β phase is present in the alloy. The TC11 alloy needs to have an ideal microstructure to obtain more desirable mechanical properties. Therefore, the perfect solid solution treatment temperature for TC11 alloy is 950 °C.

Tensile Properties Under Different Cycle Heat Treatment Conditions According to the tensile properties corresponding to the solution heat treatment of TC11 alloy, 950 °C/1 h, AC + 540/6 h, AC was selected as the optimum heat treatment condition. The tensile properties corresponding to the cycle heat treatment were studied, and the results are shown in Fig. 4. The tensile strength decreased as the number of heat treatment cycles increased (Fig. 4a). It is noteworthy that the

Insight into the Impacts of Heat Treatment on Microstructure …

767

Fig. 2 The XRD patterns of the TC11 alloy at different conditions Fig. 3 Initial microstructure of the TC11 alloy and microstructures heat-treated at a different temperature, a initial microstructure; b 925 °C/1 h, AC; c 950/1 h, AC; d 975 °C/1 h, AC; e 1000 °C/1 h, AC; f 1025 °C/1 h, AC

tensile strength is only reduced from 1094 to 1087 MPa, which can be considered almost unchanged. The yield strength and reduction of the area also decreased with the number of heat treatment cycles increased (Fig. 4b, d). However, the elongation of TC11 alloy rises significantly with the number of heat treatment cycles. The elongation reaches 19% (Fig. 4c) when the sample is heat-treated at 950 °C/1 h, AC + 540/6 h, AC + 950 °C/1 h, AC + 540/6 h, AC + 950 °C/1 h, AC + 540/6 h, AC + 950 °C/1 h, AC + 540/6 h, AC. The corresponding SEM images are shown in Fig. 5. The tissue consists mainly of a white equiaxed spherical primary alpha

768

Z. Yan and J. Jing

(a) 960

(b)

1090 940 R P0.2 /MPa

R M /MPa

1080 1070

920 900 880

1060

860 1050 1

3

1

4

Cycle/times

(c)

55

20 18 16 14 12 10 8 6 4 2 0

(d)

2

3

4

Cycle/times

50 45 Z/%

A/%

2

40 35 30 25 20

1

2

3

4

1

Cycle/times

2

3

4

Cycle/times

Fig. 4 The tensile properties of TC11 alloy under different cycle heat treatment conditions; a tensile strength; b yield strength; c elongation; d reduction of area

phase. A small amount of β-transformed tissue is distributed with a few fine needlelike secondary alpha phases (Fig. 5a). Contrasting Fig. 5a, b, it can be found that the number of equiaxed primary α phases in the solution-aged state is significantly less than in the double-annealed state and is more prominent in size. In contrast, the content of needle-like secondary alpha phases is substantially more than in the double-annealed state. As the number of heat treatment cycles increased, the gradual increase in the number of needle-like secondary α phases interspersed at the α phase interface impedes slip (Fig. 5b, d). This reasonably revealed that the strength of the alloy decreases, and its plasticity and toughness increase as the number of cycle heat treatments increases.

TC11 Ultra-High Circumferential Fatigue Study The conventional fatigue tests at loading frequencies < 150 Hz and 109 ultra-high circumferential fatigue tests under continuous operating conditions take 77 days,

Insight into the Impacts of Heat Treatment on Microstructure …

769

Fig. 5 SEM images of TC11 alloy under different cycle heat treatment conditions; a 950 °C/1 h, AC + 540/6 h, AC; b 950 °C/1 h, AC + 540/6 h, AC + 950 °C/1 h, AC + 540/6 h, AC; c 950 °C/1 h, AC + 540/ 6 h, AC + 950 °C/1 h, AC + 540/6 h, AC + 950 °C/1 h, AC + 540/6 h, AC; d 950 °C/1 h, AC + 540/6 h, AC + 950 °C/1 h, AC + 540/ 6 h, AC + 950 °C/1 h, AC + 540/6 h, AC + 950 °C/1 h, AC + 540/6 h, AC

while 1010 ultra-high circumferential fatigue test takes 2 years. It is proposed that fatigue limits corresponding to many cycles above 108 should be obtained, and it is difficult to carry out research by applying conventional fatigue test machines. Ultrahigh cycle fatigue is an evaluation of the material’s own fractured life in the case of zero defects, different from the crack sprouting and initial expansion mechanism of conventional fatigue, higher fatigue limit, and longer fatigue life than traditional testing of fatigue, the lower the number of cycles the more obvious, suitable for ultra-high cycle fatigue testing under intense stress [14]. The ultra-high fatigue test technique can significantly reduce the test time, which is ideal for testing the fatigue properties of materials at ultra-high circumferences. With a loading frequency of 20,000 Hz, the 109 UHP fatigue test takes 14 h, while the 1010 UHP fatigue test takes only 5.8 days [15]. The ultra-high circumferential fatigue tests of TC11alloy are presented in the S–N plot with a logarithmic scale for the number of cycles to the failure axis, as shown in Fig. 6. The ultra-high circumferential fatigue of the alloy can be classified into surface crack initiation, mechanical crack initiation, and interior crack initiation. According to Fig. 6, the ultra-high fatigue strength at 109 cycles for a failure probability of 50% (σ9 (10)) was calculated as 690 Mpa. In summary, the fatigue life of TC11 alloy can exceed 109 .

770

Z. Yan and J. Jing

Fig. 6 S–N plot of the ultra-high circumferential fatigue test data for the studied TC11 alloy

Conclusions (1) The phase transformation behavior of titanium alloy, which was predicted by FactSage 8.0, shows that the α phase begins to transform to the β phase at 950 °C, and the α phase has almost completely transformed to the β phase at 1100 °C. The XRD results show that the intensities α (002) peak decreases when the temperature is over 950 °C and then disappears at 1000 °C. (2) The cycle heat treatment results show that the strength of the alloy decreases, and its plasticity and toughness increase as the number of cycle heat treatments increases. This is due to the gradual increase in the number of needle-like secondary α phases interspersed at the α phase interface impedes slip. (3) The ultra-high circumferential fatigue results show that the ultra-high fatigue strength at 109 cycles for a failure probability of 50% (σ9 (10)) was calculated as 690 Mpa. In summary, the fatigue life of the TC11 alloy can exceed 109 .

References 1. Qiu ZK, Zhang PZ, Wei DB et al (2015) Mechanical and electrochemical properties of Zr and Zr-Er alloyed layers deposited on titanium alloy (TC11). Surf Coat Technol 280:301–307 2. Zhou Y, Wang SQ, Huang KZ et al (2017) Improvement of tribological performance of TC11 alloy via formation of a double-layer tribo-layer containing graphene/Fe2 O3 nanocomposite. Tribol Int 109:485–495 3. Zhan ZX (2018) Fatigue life calculation for TC4-TC11 titanium alloy specimens fabricated by laser melting deposition. Theoret Appl Fract Mech 96:114–122 4. Gupta A, Khatirkar R, Singh J (2022) A review of microstructure and texture evolution during plastic deformation and heat treatment of β-Ti alloys. J Alloys Comp 899:163242

Insight into the Impacts of Heat Treatment on Microstructure …

771

5. Ding CY, Liu C, Zhang LG, et al. (2022) Microstructure and tensile properties of a costaffordable and ultrahigh-strength metastable β titanium alloy with a composition of Ti-6Al1Mo-1Fe-6.9Cr. J Alloys Comp 901:163476 6. Song ZM, Lei LM, Zhang B, et al. (2012) Microstructure dependent fatigue cracking resistance of Ti-6.5Al-3.5Mo-1.5Zr-0.3Si alloy. J Mater Sci Technol 28:614–621 7. Song HW, Zhang SH, Cheng M (2014) Dynamic globularization prediction during cogging process of large size TC11 titanium alloy billet with lamellar structure. Def Technol 10:40–46 8. Lei L, Huang X, Wang M et al (2011) Effect of temperature on deformation behavior and microstructures of TC11 titanium alloy. Mater Sci Eng, A 528:8236–8243 9. Li MQ, Zhang XY (2011) Modeling of the microstructure variables in the isothermal compression of TC11 alloy using fuzzy neural networks. Mater Sci Eng, A 528:2265–2270 10. Zhang XY, Li MQ, Li H et al (2010) Deformation behavior in isothermal compression of the TC11 titanium alloy. Mater Des 31:2851–2857 11. Álvarez I, Font-Muñoz JS, Hernández-Carrasco I et al (2021) Using self organizing maps to analyze larval fish assemblage vertical dynamics through environmental-ontogenetic gradients. Coastal Shelf Sci 258:107410 12. Seshacharyulu SCMT, Frazier WG et al (2002) Microstructural mechanisms during hot working of commercial grade Ti-6Al-4V with lamellar starting structure. Mater Sci Eng, A 305:112–125 13. Jing JF, Zheng FQ, Guo YF, et al. (2022) Solidification behavior and microstructure of the main phases in a Ni–Fe–Cr based GH2150A alloy during melting and heat treatment process Jom 74 14. Li C, Li W, Cai L et al (2022) Microstructure based cracking behavior and life assessment of titanium alloy under very-high-cycle fatigue with elevated temperatures. Int J Fatigue 161:106914 15. Gao T, Xue H, Sun Z et al (2020) Investigation of crack initiation mechanism of a precipitation hardened TC11 titanium alloy under very high cycle fatigue loading. Mater Sci Eng, A 776:138989

Part XXI

AI/Data Informatics: Computational Model Development, Verification, Validation, and Uncertainty Quantification

A Dataset of CFD Simulated Industrial Furnace Images for Conditional Automatic Generation with GANs Ricardo Calix, Orlando Ugarte, Hong Wang, and Tyamo Okosun

Abstract The steel industry is constantly looking for ways to automate processes and improve efficiency. A standard practice in industry is to simulate how complex systems will operate before they are actually used. Some complex systems, including steel industry processes such as blast furnaces, require complex physics-based simulations utilizing computational fluid dynamics (CFD). These CFD physics-based simulations are very accurate but can take significant time and computational resources to process, resulting in challenges for the implementation of the models in real-world operational environments. In recent years, deep learning (DL) has been considered as a substitute for these CFD models. DL models can be trained on validated CFD simulation data and then used for industrial process inference. Previous DL-based solutions have made great contributions for industrial automation but are currently missing the additional visualization component that CFD simulations also provide. In this paper, we propose a dataset for simple DL generative approaches that can help to address this issue. The dataset and methodology under development to approach this prediction are discussed in this work. Keywords CFD · Generative AI · KNN · GANs

R. Calix · O. Ugarte · T. Okosun (B) Purdue University Northwest, 2200 169th Street, Hammond, IN 46323, USA e-mail: [email protected] R. Calix e-mail: [email protected] O. Ugarte e-mail: [email protected] H. Wang Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37830, USA e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_66

775

776

R. Calix et al.

Introduction Industrial plants are constantly looking for ways of automating processes to improve efficiency and reduce costs. Knowing how an expensive-to-operate system will perform under a range of operating conditions before making any process changes can be crucial. A standard practice in industry is to simulate how complex systems will operate under these changing conditions before making modifications to the process itself. Complex systems in manufacturing, aerospace, and other fields involving fluid flow, turbulence, chemical reactions, and heat transfer can employ physics-based Computational Fluid Dynamics (CFD) simulations to predict how changes to operation will influence the process. These simulations can be validated against experimental or real-world industrial measurements, and are generally quite accurate. However, the process of generating data with this approach can require significant time and computational resources. Existing CFD modeling techniques have been employed to predict the operation of the ironmaking blast furnace, including providing a window to observe the blast furnace’s internal state. CFD modeling of the blast furnace has been broadly applied and validated against operational data, and with modern computing technology, the simulation of combustion, heat transfer, multi-phase flow, and other phenomena are possible [1–4]. Key simulation models have been developed to explore conditions within various reaction regions of the blast furnace including the tuyere, raceway, and shaft, capturing solid and gas combustion, gas-solid reduction reactions, melting, turbulence, and other physics occurring within the furnace environment [5, 6]. In recent years, deep learning (DL) has been considered as a substitute for these CFD models. DL models can be trained on highly accurate CFD simulated data and then be used for industrial process inference. These previous solutions have made great contributions to their respective industries but are missing the additional visualization component that CFD simulations also provide. In this paper, we propose a dataset and simple generative approaches that can help to address this issue. The dataset consists of images that reflect the different temperatures inside a steel furnace based on various input conditions. All images have the same size, and the furnace outline properly aligns in all the images. Therefore, the only thing that changes in the images is the temperature colors within the outline of the furnace. The input conditions are correlated with the images. As an example, using a car engine analogy, the coloring of the wall of a car engine could be simulated to become more red as more gasoline is injected into the combustion chamber. Similarly, the CFD generated images in our dataset reflect these relationships for an industrial steel furnace and its related inputs. Details of the dataset as well as potential methodologies to generate the images are presented and discussed. Finally, while GANs are interesting and very powerful, we also propose a very simple yet very effective way to generate conditional images we call Conditional KNN Averaging.

A Dataset of CFD Simulated Industrial Furnace Images …

777

Literature Review Generative Adversarial Networks (GANs) show great promise for many applications. The authors in [7] provide a great survey type introduction to this topic as it relates to image synthesis with generative models. There are 2 main deep learning algorithms that have been used to create generative models. These are Transformers and GANs. GANs have been used extensively for image synthesis and Transformers have been used extensively for natural language generation. However, these algorithms are still very new, and it is possible that these in the future may be used for many other applications or may be combined. In the field of natural language processing, there are many successful examples of text generative models such as GPT-3 and ChatGPT [8] as of this writing. These are transformer-based generative models and are currently mostly used for text generation. In the field of image processing, similar progress has been made such as with Stable Diffusion as discussed in [9, 10]. Stable Diffusion focuses on generating images from inputs such as text descriptions. Image generative models in general have used GANs. While GANs have in general been used for image generation, and Transformers have been used for language generation, it is possible that in the future these models can be used in other mediums or that they could be combined. For the research presented in this paper, we will focus on simple generative methodologies. Figure 1 presents a diagram summarizing the general ideas of GANs. Basically, a GAN consists of 2 deep learning models in a sense playing against each other. Both models have different objectives and goals. The models are called a generator and a discriminator. The generator takes a vector or matrix as input, runs it through its deep neural network which can be an autoencoder, and produces and output which for our purposes can be an image. The images that come out of the generator can be labelled as fake images. The discriminator is a standard classifier. The discriminator takes in images and classifies them as either real or fake. To train this discriminator,

Fig. 1 GAN diagram

778

R. Calix et al.

you need some real images such as our provided CFD furnace images and also the fake images from the generator. In this paper, we provide a dataset to train GAN models. A further extension of GAN models are conditional GAN models as described in [11, 12]. These models allow for the GAN to provide additional knowledge or context to the generator. In Fig. 1, it can be seen that, in general, the input to the generator is a noise matrix or vector. However, another vector or matrix with additional information (context) can be concatenated to the generator input, and this combined input (noise + context) makes regular GANs become conditional GANs. The images of the dataset discussed in this paper also include this conditional information represented as a small vector of initial system inputs that produced each respective image. The use of GANs for industrial applications has been shown in several studies such as in [13]. In their work, the authors applied GANs to generate simulated time series data for their industrial application with promising results.

Dataset Specification and Methods The dataset consists of 615 images of an industrial blast furnace generated via Computational Fluid Dynamics simulation of the process under a range of operating conditions. The images also include certain normalized parameters and their values that led to the output images. These input parameters are what can be used as conditional vectors to train the Conditional Generative models. From a physics point of view, the output images represent, for the given input conditions, the respective temperature characteristics of the internal solid burden and gas material within the furnace represented by color changes and gradients. The following figure shows examples of the dataset images for the furnace (Fig. 2). The following table provides further simple statistics about the dataset such as image dimensions and number of samples. The images are of size 1400 .× 390, and are 2D (Table 1). Each image is associated with a vector of regression values representing input conditions to the furnace that led to the temperature colorization of the images. These regression features are inputs to a furnace such as natural gas, oxygen, iron ore, and other chemicals. Two generative conditional GAN scripts are also made available with the dataset. These handle image loading to DataLoaders and basic GAN training and inference using pre-trained models. Finally, Table 2 provides a list of the DL frameworks used for this work.

Conditional KNN Averaging While GANs are the state of the art for generative models, in this work we also propose a simple yet effective technique to generate furnace images called Conditional KNN

A Dataset of CFD Simulated Industrial Furnace Images …

Fig. 2 Image data

779

780 Table 1 Dataset characteristics Characteristic N images Height Width Features

R. Calix et al.

Value 615 1400 390 5–11

Table 2 Tools used Tool Fastai PyTorch Nvidia GPUs Sklearn PIL TorchVision

Averaging. Each image in the dataset was generated using 6–8 input conditions. Different combinations of values for these input conditions resulted in different output images. Our proposed technique was very effective in generating new images via averaging. The simple idea is that we use the input conditions as axes in a vector space so that every image is a point in this vector space. Then, given a new sample of input conditions we can use KNN to find the 3 closest other sets of conditions in the vector space. Once those 3 closest are located, the corresponding images for these 3 cases are averaged (element-wise) to produce a new image. The Conditional KNN Averaging algorithm is described below. Algorithm 1 Conditional KNN Averaging Require: Data = {(x1 , y1 ), (x2 , y2 ), ..., (xn , yn )}; x j ⊆ R m ; y j ⊆ I mages 1: for j,...,n do 2: Calculate Dist (x [ j] , x [q] ) and select k closest corresponding y j into Y 3: end for 4: Gen_I mage = Y¯

In the algorithm, .x [q] is a target set of conditions to be compared to the dataset. The value .k is the number of closest samples that will be selected. For this study k was set to 3. There are several distance functions that can be used. The Euclidean distance function was used for the proposed approach (see equation below):

A Dataset of CFD Simulated Industrial Furnace Images … Table 3 Losses for conditional GAN (Mirza) Epoch D loss 195/200 196/200 197/200 198/200 199/200

781

G loss

30,187.40 16,262.09 7,650.90 6,626.24 980.08

13.29 12.28 6.03 10.02 5.09

┌ | m |∑ [a] [b] . Dist (x , x ) = | (xi[a] − xi[b] )2

(1)

i=1

where .x [a] and .x [b] represent points .a and .b which exist in . R m and .m is the dimensionality of the input condition vector space.

Characteristics and Results The created dataset and scripts were used and tested, and results are discussed in this section. In general, the GAN models seemed to have learned with our data. This can be seen below as evidenced by the loss value improvements during training (Table 3). As a proof of concept, we performed generative inference using our trained GAN models. While the results are not the greatest, they showed that the model does begin to change the image colorization schemes (Fig. 3). Further work will focus on improving these initial experiments. In particular, 2 scripts are provided for GAN modeling with our data. One script is a standard GAN-based colorization approach where the conditional input is the gray-scale image of the furnace. The second script provides a GAN-based framework to add the input regression values as conditional inputs to the model. Since this is a dataset paper, the main effort was not on perfecting the performance of the generative models.

Results of Conditional KNN Averaging The results of the Conditional KNN Averaging can be seen below. Human expert evaluations indicated that the results were accurate and useful (Fig. 4).

782

R. Calix et al.

(a) original

(b) original

(c) Generated

Fig. 3 Image inference: a Original color, b original black and white, and c generated image Fig. 4 Results of conditional KNN averaging

A Dataset of CFD Simulated Industrial Furnace Images …

783

Conclusion In this work, a dataset of CFD simulated industrial furnace images for use in conditional automatic generation with generative models is presented and discussed. A proof of a concept DL-based pipeline for automatic image colorization and generation was presented and discussed. Additionally, a simple yet effective approach called Conditional KNN Averaging was proposed and evaluated. In general, the dataset and approaches look promising. Future work will focus on improving the methodologies and increasing the number of samples. The dataset and code can be accessed from [14]. Acknowledgements This work was supported in part by DOE.

References 1. Guo B, Zulli P, Rogers H, Mathieson JG, Yu A (2005) Three-dimensional simulation of the combustion behavior of pulverized coal injection. In: Proceedings of 5th international symposium on multiphase flow, heat mass transfer and energy conversion, Xi’an, China 2. Yeh C-P, Du S-W, Tsai C-H, Yang R-J (2012) Du: numerical analysis of flow and combustion behavior in tuyere and raceway of blast furnace fueled with pulverized coal and recycled top gas. Energy 42:33–240 3. Babich A, Senk D, Gudenau HW (2016) An outline of the process. Ironmaking, 180–185 4. Okosun T, Silaen AK, Zhou CQ (2019) Review on computational modeling and visualization of the ironmaking blast furnace at purdue university northwest. Steel Res Int’l 90 5. Fu D (2014) Numerical simulation of ironmaking blast furnace shaft. PhD dissertation, Purdue University, West Lafayette, IN 6. Okosun T (2018) Numerical simulation of combustion in the ironmaking blast furnace raceway. PhD dissertation, Purdue University, West Lafayette, IN 7. Huang H, Yu PS, Wang C (2018) An introduction to image synthesis with generative adversarial nets. arXiv:1803.04469 8. Susnjak T (2022) Chatgpt: the end of online exam integrity? arXiv:abs/2212.09292 9. Ramesh A, Dhariwal P, Nichol A, Chu C, Chen M (2022) Hierarchical text-conditional image generation with clip latents. arXiv:abs/2204.06125 10. Rombach R, Blattmann A, Lorenz D, Esser P, Ommer B (2021) High-resolution image synthesis with latent diffusion models 11. Mirza M, Osindero S (2014) Conditional generative adversarial nets. arXiv:abs/1411.1784 12. Isola P, Zhu J-Y, Zhou T, Efros AA (2016) Image-to-image translation with conditional adversarial networks. In: 2017 IEEE conference on computer vision and pattern recognition (CVPR), pp 5967–5976 13. Huang H, Xu C, Yoo S (2021) Interpretable temporal gans for industrial imbalanced multivariate time series simulation and classification. In: Proceedings of the 36th annual ACM symposium on applied computing. SAC ’21, pp 924–933. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3412841.3441967 14. Calix RA. GANs for industrial image generation. https://github.com/rcalix1/ ProbabilityDensityFunctionsFromNeuralNets/tree/main/experiments/2023/january2023/ GANs

Finding “Trigger Sites” of Reactions Among Heterogeneous Materials from X-ray Microscopic Big Data Using Persistent Homology Masao Kimura, Ippei Obayashi, Daiki Kido, Yasuhiro Niwa, Xichan Gao, and Kazuto Akagi

Abstract Material properties are typically determined by specific features such as the heterogeneity (or “trigger sites”) of phases and chemical states. Trigger sites have been investigated in systems such as structural materials and batteries by using multiscale X-ray microscopy (XRM). However, identifying trigger sites manually or via computers has been challenging because the data involved are large and multidimensional. In this study, we developed a new approach to determine trigger sites on the basis of shapes of heterogeneity in XRM data by using persistent homology (PH) analysis. Our results revealed the following two aspects: (1) the trigger sites for the heterogeneous reduction of iron ore sinters, the complex of Ca–Fe–O oxides, and pores; and (2) the crack initiation sites at the nanoscale in carbon-fiber-reinforced plastics (CFRPs) under load. We could “non-empirically” identify trigger sites from the big data obtained by XRM. This approach can be applied to identify trigger sites in various materials. Keywords X-ray microscopy · Persistent homology · Iron ore sinter · CFRP · Synchrotron radiation

M. Kimura (B) · D. Kido · Y. Niwa High Energy Accelerator Research Organization (KEK), 1-1 Oho, Tsukuba 305-0801, Ibaraki, Japan e-mail: [email protected] SOKENDAI (The Graduate Univ. for Advanced Studies), 1-1 Oho, Tsukuba 305-0801, Ibaraki, Japan I. Obayashi Okayama Univ, 3-1-1 Tsushimanaka, Kita-Ku, Okayama 700-8530, Okayama, Japan X. Gao · K. Akagi Tohoku Univ, 2-1-1 Katahira, Aoba-Ku, Sendai 980-8577, Miyagi, Japan © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_67

784

Finding “Trigger Sites” of Reactions Among Heterogeneous Materials …

785

Introduction X-ray microscopy (XRM) can be used to reveal the internal two-dimensional or three-dimensional structures of materials through nondestructive and in situ observations. By combining XRM and diffraction, information other than microstructures, including the type and amount of elements, electronic structures, and atomicconfiguration structures, can be obtained. Recent advances in X-ray optics has helped sequentially address the most significant disadvantage of XRM, namely, low magnification because of difficulties associated with fabricating X-ray “lenses.” XRM has been widely used for in situ and operando observations of various systems, such as catalysis, batteries, and structural materials [1]. However, a remarkably challenging task concerns analyzing the multidimensional big data obtained via XRM. X-ray computed tomography (X-CT) has been performed by varying X-ray energies so as to determine the electrochemical states for each volume in the field of view (“voxel”). Performing these measurements during the progress of the reactions yields five-dimensional data (5D = space (3D) + energy + time). The 5D data typically result in a size on the order of terabytes. Therefore, identifying trigger sites where critical reactions that determine the macroscopic properties are initiated and propagated is a challenging but inevitable task (Fig. 1). However, identifying trigger sites manually or by using computers has been challenging because of the large and multidimensional data involved. In the XRM data, the reaction evolution is often accompanied by changes in the microstructure and/ or chemical-state heterogeneity. In this study, we focused on the changes in their “shapes” and developed a new approach for determining trigger sites on the basis of the shapes of heterogeneity in XRM data by using persistent homology (PH) analysis.

Experiments Using Multiscale and Multimodal XRM In microscopy, the size of a detector is usually fixed. Thus, owing to the underlying physical principle, a high magnification of a microscope is usually irreconcilable with a large field of view. Thus, we used multiscale and multimodal XRM (Fig. 2) to observe the following reactions: (1) the heterogeneous reduction of iron ore sinters composed of the complex of Ca–Fe–O oxides and pores; and (2) crack initiation at the nanoscale in carbon-fiber-reinforced plastics (CFRPs) under load. The details of the XRM are described elsewhere [1, 2].

786

M. Kimura et al.

Fig. 1 Schematic of the five-dimensional big data obtained via XRM

Fig. 2 Multiscale and multimodal X-ray microscopes used in this study

Heterogeneous Reduction of Iron Ore Sinters Iron ore sinter is the starting material for ironmaking processes (Fig. 3) and is used in blast furnaces in most countries. The properties required for iron ore sinter are high reducibility and low mechanical degradation during the reduction process in a blast furnace. Sinter is formed via liquid sintering at T > 1500 K, at which iron oxide grains (mainly α-Fe2 O3 ) are sintered with bonding layers composed of various types

Finding “Trigger Sites” of Reactions Among Heterogeneous Materials …

787

Fig. 3 Process of steel making from iron ore, wherein iron ore sinter is reduced to pig iron

of calcium ferrites. Porous networks are formed during the solidification of molten calcium ferrites [3]. It was observed that reduction was more likely to occur in areas with low calcium concentrations; this can be explained on the basis of the experimental results obtained from the powder specimens of individual phases, in which iron oxides were more easily reduced than calcium ferrites. However, the reduction progressed heterogeneously within the same calcium ferrite or iron oxide phase (Fig. 3, lower right panel). This indicates that the heterogeneous reduction was not only the result of the different reduction rates of the individual phases but was also aided by other factors, such as the pore networks or porous structure of the calcium ferrite phase, which affected the flow of the reductive gas. Because the gas flow is more effective in the porous regions, the reduction is accelerated. Each voxel in the 3D X-CT data was segmented into (a) calcium ferrite phase, (b) iron oxide, (c) initial pore, and (d) microcracks formed during reduction. Then, the image data corresponding to the regions (a) and (b) were transformed into a persistence diagram wherein the topological features of the images were represented by point clouds of two parameters—“birth” and “death” (Fig. 4b). They denote the step numbers of birth and death of “holes” when the image data are transformed larger or smaller step by step according to a specific rule in the computer [3–5]. The persistence diagrams were converted into a vector representation, a so-called persistence image, and the relationship between the vectors and the macroscopic properties such as the crack amount was investigated using principal component analysis (PCA). Finally, four types of crucial birth–death pairs were identified: two for calcium ferrites (TS CF1 and TS CF2 ) and two for iron oxides (TS IO1 and TS IO2 ), which are highly correlated with cracks (Fig. 4c). Notably, four types of trigger sites were identified on the basis of PH without any prior knowledge of the materials and processes involved. The locations of the four types of trigger sites were consistent with the locations where the cracks were formed, as determined via X-CT (Fig. 4d). This approach can be applied to complete the 3D data obtained by X-CT, and the

788

M. Kimura et al.

Fig. 4 Outline of the proposed approach for finding “trigger sites.” a An XRM image is analyzed using b PH analysis; c triggers sites are predicted non-empirically. d Predictions agree with the trigger sites (i.e., cracks) that are revealed by macroscopic X-CT measurements

topological features of trigger sites in 3D can be determined in the 3D microstructures [5]. This study demonstrated the efficacy of the proposed method in analyzing a heterogeneous reaction without requiring specific data concerning the reaction mechanism involved. In this process, only the image data depicting the heterogeneity of a material, such as a map of the chemical states and coexisting phases and their relationship with a macroscopic property, are required; these data are analyzed using PH and machine learning.

Crack Initiation Sites at Nanoscale in Carbon-Fiber Reinforced Plastics (CFRP) Carbon-fiber-reinforced plastic (CFRP) composites, which exhibit high specific strength and stiffness, are widely used as weight-reducing structural materials in aerospace, automobile, and other applications [6]. CFRPs have multiple components: strong but brittle anisotropic carbon fibers as well as ductile and isotropic plastics, held together by adhesive bonding. They also feature a multiscale (nm to m) hierarchical structure. The carbon fibers are usually aligned in the same direction and pre-impregnated with plastic to form “prepreg” sheets, which are stacked in different directions and are formed in various shapes as structural parts (Fig. 5). However, crack formation remains unelucidated owing to experimental difficulties. We performed multiscale, nondestructive, and three-dimensional (3D) observations of crack initiation and propagation under an applied stress. Considering anisotropic mechanical properties of CFRP, X-CT measurements were performed at various scales with fields of view ranging from 100 micrometers to 10 millimeters (Figs. 2 and 5). In situ loading cell was utilized for X-CT observations using an in-house X-CT apparatus at the macroscopic scale (macroscopic X-CT) and using transmission X-ray microscopy (TXM) X-CT using synchrotron radiation at the nanoscopic scale (nanoscopic SR X-CT) [7–9].

Finding “Trigger Sites” of Reactions Among Heterogeneous Materials …

789

Fig. 5 Hierarchical structure of CFRPs at various scales and their examination using macroscopic X-CT and nanoscopic synchrotron radiation X-CT (nanoscopic SR X-CT)

Figure 6 depicts the results of the initiation and propagation of cracks and voids when the sample was pressed with a wedge indenter (Fig. 6a), corresponding to deformation under opening stress (partially mode I tensile loading). To the best of our knowledge, this is the first in situ nondestructive observation of crack initiation and propagation in CFRP at a high resolution of ~50 nm. The 3D images obtained in this study indicated cracks inside the bulk specimen, which was free of surface effects. (Fig. 6 exhibits only the interior part of a specimen.) The segmented 3D images show that the mechanisms of crack initiation and propagation depend largely on the spacing between the carbon fibers, which is equivalent to the thickness of the epoxy separating the carbon fibers. The crack shape in the “thin” region was much sharper than that in the “thick” region, and the resin around the cracks showed negligible deformation. In other words, the cracks in the thin epoxy region propagated along the carbon fiber/plastic interface in a brittle manner, that is, fiber/plastic interface debonding. In contrast, the cracks in the “thick” epoxy region initiated at the fiber/epoxy interfaces but propagated not only along the interface but also into the epoxy resin (in-resin crack initiation). Crack propagation accompanied the plastic deformation of the epoxy, resulting in the formation of blunt cracks with shapes different from those at the interface boundary where the cracks initiated. These observations revealed that crack initiation and propagation do not simply result from local stresses but are also primarily affected by two competing nanoscale

790

M. Kimura et al.

Fig. 6 Change of reconstructed 3D volume data obtained via the nanoscopic SR X-CT, as the opening stress in the X-direction was increased (b–d). Carbon fibers, plastic resin, and cracks (air) are shown in black, dark yellow, and red, respectively

mechanisms, namely, fiber/plastic interface debonding and in-plastic crack initiation. The fiber alignment and plastic thickness among the fibers significantly influence the competition among these mechanisms [7, 8]. Therefore, the carbon-fiber alignment of the CFRP observed using macroscopic X-CT was analyzed using PH (Fig. 7). First, the positions of the carbon fibers were determined via image analysis (equalization and Gaussian Blur) and by setting the super-level of death as PD1. The carbon-fiber positions were successfully determined beyond the instrumental spatial resolution. Then, persistence diagrams, quantitatively representing the carbon-fiber alignments, were obtained for “thin,” “thick,” and crack regions. The persistence diagrams clearly indicate the differences in carbon-fiber alignments among these regions. Once the topological features of the carbon-fiber alignment are converted into persistence diagrams, various analyses can be performed to relate them to the crack initiation mechanism. This affords indispensable information for determining the trigger sites in CFRP, where cracks initiate and propagate at multiple scales from nanoscale to macroscale [10].

Fig. 7 a Macroscopic X-CT three-dimensional data were analyzed, and b carbon-fiber positions were determined. c Then, the topological features of carbon-fiber alignment are converted into persistence diagrams

Finding “Trigger Sites” of Reactions Among Heterogeneous Materials …

791

Conclusion This study demonstrated that information on trigger sites can be extracted from the multidimensional big data obtained via XRM by focusing on the changes in the topological features of microstructure and chemical-state heterogeneities. The proposed approach can be implemented using PH and informatic techniques such as machine learning. We demonstrated the efficacy of the proposed approach on the basis of the following two results: (1) the trigger sites for the heterogeneous reduction of iron ore sinters composed of the complex of Ca–Fe–O oxides and pores; and (2) the nanoscale crack initiation sites in CFRP under load. This approach can be applied to identify trigger sites from XRM data in various systems, such as batteries, catalysts, and geological reactions, wherein the reactions progress heterogeneously in heterogeneous complexes of microstructures, phases, and chemical states. Acknowledgements The following funds supported this work: (1) Grant-in-Aid for Transformative Research Areas (A) 22H05109 by JSPS; (2) JST-Mirai Program JPMJMI20C2 and JPMJMI22C1; and (3) KAKENHI JP19H00834 and JP20H02028. The experiments using synchrotron radiation were performed with the approval of the Photon Factory Program Advisory Committee (Proposal Nos. 2015S2-002, 2016S2-001, 2019S2-002, and 2022S2-001).

References 1. Kimura M, Takeichi Y, Watanabe T, Niwa Y, Kimijima K (2019) Finding degradation trigger sites of structural materials for airplanes using X-Ray microscopy. Chem Rec 19:1462–1468. https://doi.org/10.1002/tcr.201800203 2. Niwa Y, Takeichi Y, Watanabe T, Kimura M (2019) Development of spectromicroscopes for multiscale observation of heterogeneity in materials at photon factory, IMSS. KEK AIP Conf Procds 2054:050003. https://doi.org/10.1063/1.5084621 3. Kimura M, Obayashi I, Takeichi Y, Murao R, Hiraoka Y (2019) Non-empirical identification of trigger sites in heterogeneous processes using persistent homology. Sci Rep 8:3553. https:// doi.org/10.1038/s41598-018-21867-z 4. Obayashi I, Hiraoka Y, Kimura M (2018) Persistence diagrams with linear machine learning models. J Appl Comput Topol 1:421–449. https://doi.org/10.1007/s41468-018-0013-5 5. Obayashi I, Kimura M (2022) Persistent homology analysis with nonnegative matrix factorization for 3D voxel data of iron ore sinters. JSIAM Lett 14:151–154. https://doi.org/10.14495/ jsiaml.14.151 6. Potter K (2017) ‘But how can we make something useful out of black string?’ the development of carbon fibre composites manufacturing (1965–2015). In: Beaumont PWR, Soutis C, Hodzic A (eds) The structural integrity of carbon fiber composites: fifty years of progress and achievement of the science, development, and applications 2017. Springer International Publishing, Cham, pp 29–57 7. Kimura M, Watanabe T, Takeichi Y, Niwa Y (2019) Nanoscopic origin of cracks in carbon fibre-reinforced plastic composites. Sci Rep 9:19300. https://doi.org/10.1038/s41598-019-559 04-2 8. Watanabe T, Takeichi Y, Niwa Y, Hojo M, Kimura M (2020) Nanoscale in situ observations of crack initiation and propagation in carbon fiber/epoxy composites using synchrotron radiation

792

M. Kimura et al.

X-ray computed tomography. Compos Sci Technol 197:108244. https://doi.org/10.1016/j.com pscitech.2020.108244 9. Kimura M, Watanabe T, Oshima S, Takeichi Y, Niwa Y, Seryo Y, Hojo M (2022) Nanoscale in situ observation of damage formation in carbon fiber/epoxy composites under mixedmode loading using synchrotron radiation X-ray computed tomography. Compos Sci Technol 230:109332. https://doi.org/10.1016/j.compscitech.2022.109332 10. Gao S, Kido D, Akagi K, Kimura M (2023) (in preparation)

Research on the Model of Matching Inventory Slab with Order Contracts of Steel Enterprises Cheng-hong Li, Ming-mei Zhu, Xian-wu Zhang, and Kun-chi Jiang

Abstract This paper studies the matching problem between inventory board and customer order. On the basis of objective analysis and constraint analysis of inventory board and order combination process, a nonlinear integer programming model with minimum surplus material ratio as objective function is established, and the model is solved based on particle swarm optimization algorithm. Adaptive weight and adaptive mutation are introduced to improve the algorithm, which improves the global search ability of the algorithm and quickly obtains the global optimal solution. The improved particle swarm optimization algorithm is used to solve the mathematical model, and the results show that the model can describe the practical problems well. Compared with manual experience, the efficiency of the combined process is faster, the residual material rate is lower, the average residual material rate is controlled below 1% and even can be controlled at 0.2% in large-scale application, and the combined process is optimized. Keywords Slab allocation · Combination optimization · Intelligent optimization algorithm · Mathematical model · Particle swarm optimization

Introduction Research Background The traditional planned production mode of iron and steel enterprises has been challenging to adapt to the actual production needs of iron and steel enterprises. Faced with the demand for small batches, numerous varieties, jumbled specifications, customization, and other production orders, the scale efficiency pursued by iron and steel enterprises is facing significant challenges; that is, there is a sharp C. Li · M. Zhu (B) · X. Zhang · K. Jiang College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_68

793

794

C. Li et al.

contradiction between the large-scale production mode and the satisfaction of order requirements such as quick response, flexible customization, and timely delivery, which leads to a large number of stock slab and occupies the storage resources of warehouses and the liquidity of enterprises. Therefore, iron and steel enterprises urgently need an efficient laminate assembly model to reduce the surplus materials produced in the laminate assembly process, to achieve the purpose of reducing capital inventory and waste.

Research Status At present, relevant scholars at home and abroad have researched the matching between stock slab and customer order and related issues from two aspects of theory and application. Vesko and others [1] first proposed to cut the slabs to be matched in inventory. They combined the slabs into two parts separately, established a research model, and aimed at spending the least matching cost. They also added virtual contracts and slabs into the model and then transformed the matching between the stock slab and customer order problem into a transportation problem. The model was calculated by using Betkesi’s network nodes. The experimental results show that this method can quickly combine many stock slabs and contract orders. Denton et al. [2] developed a decision support system that optimizes the stock slab’s quality by studying the stock slab’s design problem and establishing a mathematical model. In practical application, the system dramatically improves enterprises’ production efficiency and reduces the contracts’ delivery period. Forrest and Kalagnanam [5] regarded the matching between the stock slab and customer order problem in [3, 4] as a Multiple knapsack problem with color contracts (MKCP). Forrest designed a column generation algorithm to solve the model; the results are better than those in [3]. Song [5] thought that the problem of matching the remaining slabs allocated in the inventory motherslab with the contract order could be approximated as a multi-stage and multi-knapsack problem and established a model to simulate it, using a column generation algorithm to calculate. The goal of the model is to reduce the production cost and improve customer satisfaction, which embodies the concept of multi-objective development [6–8]. The established mathematical programming model gradually changes from static to dynamic models [9, 10]. It has been proved that matching between the stock slab and the customer order problem is a typical NP-Hard problem. The above scholars have different ways to solve this problem, from intelligent and accurate algorithms to heuristic algorithms. However, the control of surplus material rate could be more satisfactory.

Research on the Model of Matching Inventory Slab with Order Contracts …

795

Fig. 1 Sketch of matching between the stock slab and customer order process

Problem Description and Mathematical Model Description of Matching Between the Stock Slab and Customer Order The main content of matching between the stock slab and customer order problem research is to combine the order sub-boards of different specifications to the stock master board and make the remaining material’s minimum after the stock master board is rolled into sub-boards, as shown in Fig. 1.

Establish a Mathematical Model (1) Symbol description of order sub-slab I: Number of orders. I: Order number, I ε {1, 2, … I}. Li,m : The length of the m-th sub-board in the i-th order, mm. Gi : The number of order sub-boards. m: The sub-board number in order i, M ε {1, 2, … M}.

796

C. Li et al.

K i : Order sub-board width, mm. Pi : The steelmaking grade of the order sub-plate. (2) Description of stock motherslab symbols S: Number of motherslabs in stock. S: The stock motherslab number, S ε {1, 2, … S}. Ls : Length of stock motherslab s, mm. K s : Width of stock motherslab, mm. Gi,s : The number of sub-boards of order i matched to stock motherslab s. Ps : Steel-making grade of stock motherslab. μi,s,m : The decision variable, if the m slab of the i order matches the s slab; otherwise, it is 0. (3) Matching between the stock slab and customer order optimization constraints The following constraints need to be considered when solving matching between stock slab and customer order problems: 1) Consistency constraint of steelmaking grade: The steelmaking grade of the stock motherslab and the order slab should be consistent. 2) Section size constraint: The section size and length of the matched order slab and the stock slab should meet the requirements of the rolling process, and the rolled length of the stock slab should be larger than the total length of the order slab matched with the stock slab. Equations (1) and (2) are satisfied.

L=

(A + α) × (B + β) × (C + γ + δ) b×c×ε L => m × a

(1) (2)

where A is the length of stock motherslab, mm; B is the width of stock motherslab, mm; C is the thickness of stock motherslab, mm; A is the order sub-board length, mm; b is the order sub-board width, mm; c is the order sub-board thickness, mm; α is the length margin, mm; β is the width margin, mm; γ is the thickness margin, mm; δ is the lower limit of negative tolerance of thickness, mm; ε is the burning loss rate,%; m is the number of sub-plates matched to the stock motherslab, and L is the length of the slab to be rolled, mm. 3) Length constraint: The length of the stock motherslab should not be less than the sum of the order motherslab lengths matched to the motherslab. 4) Order quantity constraint: The total number of matching order sub-boards should be no less than the total demand of the order.

Research on the Model of Matching Inventory Slab with Order Contracts …

797

(4) Mathematical model In this paper, the mathematical model for matching between the stock slab and customer order problem has the following steps: 1) According to the consistency constraint of steelmaking grade, the order sub-plate and the inventory sub-plate are grouped according to the steelmaking grade to match the inventory sub-plate and the order sub-plate with the same steelmaking grade. 2) According to the section size constraint, based on the above grouping conditions, the order sub-boards are grouped according to the section size, and the width and thickness of each group of order sub-boards are the same so that the section size of different order sub-boards matched to the same stock motherslab is the same. 3) According to the length constraint, ensure that the length of the motherslab is greater than or equal to the total length of the matched daughter board. 4) According to the order quantity constraint, the model should ensure that the total quantity of all order sub-boards matched to the inventory motherslab should meet the requirements of all order contracts. Objective function: min f =

S 

 Ls −

s=1

I  M 

 μi,s,m ∗ L i,m

(3)

i=1 m=1

Constraints: S 

G i,s ≥ G i

(4)

G i,s ∗ L i ≤ L s

(5)

s=1 I  i=1

G i.s ∈ {1, 2, . . . , G i }  

S  I  s=1 i=1

(6)

K i ≤ K s , μi,s,m = 1 K i > K s , μi,s,m = 0

(7)

Pi = Ps , μi,s,m = 1 Pi = Ps , μi,s,m = 0

(8)

μi,s,m ≤ 1, m ∈ {1, 2, . . . , Gi }

(9)

798

C. Li et al.

The objective function formula (3) is to minimize the waste of surplus materials after the order is completed, the constraint condition formula (4) indicates that the total number of all order sub-boards matched to the inventory motherslab is not less than the demand of the order contract, the bundle condition formula (5) indicates that the length of the inventory motherslab is not less than the total length of the order sub-boards matched to the motherslab, the constraint condition formula (6) indicates that the number of order sub-boards matched by each inventory motherslab is constrained, the constraint condition formula (7) suggests that the width of the order sub-board is less than the width of the matched inventory motherslab, the constraint condition formula (8) indicates that the steelmaking grade of the matched order sub-board is consistent with that of the inventory motherslab, and the formula (9) suggests that the inventory motherboard and the order motherboard belong to a one-to-many combination mode.

Algorithm Design Improved Particle Swarm Optimization Algorithm Adaptive Weight The inertia weight of particles with lower fitness should be appropriately increased to find the global optimal solution more quickly and accurately. In comparison, the inertia weight of particles with higher fitness should be appropriately reduced. To sum up, this paper adopts the strategy of adjusting inertia weight according to the distance between particles and the position of global optimum, as shown in Eq. (10).  w=

f + f −

( f − f min ) , f avg − f min ( f − f min ) , f avg − f min

f ≤ f avg f ≥ f avg

(10)

where f represents the fitness of each particle after each update, f avg represents the average fitness of all particles after the update, and f min represents the minimum fitness of all particles after the update.

Adaptive Mutation To escape from the local optimum to the greatest extent, this paper gives each particle the ability of adaptive mutation. The adaptive mutation is similar to the mutation operation in the genetic algorithm. Every particle has the probability to mutate. A threshold will be set in the algorithm. When the fitness of particles reaches this threshold, the mutation mechanism will start so that the position of particles has a certain probability of mutating according to Eq. (11):

Research on the Model of Matching Inventory Slab with Order Contracts …

pi, j = pi j (t) + ( plimit−max − plimit−min ) ∗ ε

799

(11)

Then, the position is revised according to the upper and lower limits of the position set before.

Model-Solving Steps (1) Obtain information and preprocess it Read the specifications of the stock board and order board from the database, classify the board, and preprocess the board. (2) Encoding The identity code of each particle is an n-dimensional vector X(x1 , x2 , …, xn ), and the dimension is determined by the number of sub-boards. Each element xi in the vector represents the matching situation between the block sub-board and the motherslab of the i-th order if r block sub-boards in the i-th order match the corresponding motherslab, xi = r . (3) Random initialization of population According to the model established in the second section, the independent variable is defined as an n-dimensional vector X(x1 , x2 ,…, xn ), and xi represents the number of the i-th order sub-boards matched with it on a specific motherslab, that is to say, the feasible solution space is n-dimensional. At the beginning of the algorithm, Q particles are randomly generated in this n-dimensional feasible solution space, and the population composed of these Q particles is taken as the initial solution. The position of the i-th particle is set asPi = ( pi,1 , pi,2 , . . . , pi,n ), and its velocity is set asVi = (xi,1 , xi,2 , . . . , xi,n ). (4) Fitness evaluation and storage of individual and population extremum According to the model’s objective function, each particle’s fitness is evaluated, and iteration is carried out. According to individual experience and group experience, particles will pursue the optimal position (gbest) found by themselves and the position (zbest) of the particle with the shortest distance from the optimal solution in the whole particle swarm, that is, individual maximum value (Pi,g ) and global maximum value (Pz ). (5) Update speed and location After tracking the individual extremum (Pi,g ) and the global extremum (Pz ), the particle will update its speed and position according to Eqs. (12) and (13), that is, update the different combinations of inventory motherslab and order motherslab.   vi, j (t + 1) = wvi, j + c1 ∗ rand 1 ∗ Pz − pi, j (t) + c2 ∗ rand 2 ∗ [Pi,g − pi, j (t)] (12)

800

C. Li et al.

pi, j (t + 1) = pi, j (t) + vi, j (t + 1)

(13)

c1 and c2 are learning factors.w is inertia weight; rand 1 , rand 2 are random numbers between 0 and 1, respectively. (6) Adaptive mutation Each particle’s current position has a certain probability of mutation, and the specific variation rules are described in section “Improved Particle Swarm Optimization Algorithm”. (7) Adaptive weight updating The weight of each particle is updated according to its position, and the update rules are described in section “Research Background”. (8) Renewal fitness The fitness of the particles after iteration is recalculated and their new fitness is compared with the individual’s historical optimal wellness. If the new fitness is better, it replaces the latter. (9) Optimal renewal population Compare the best positions of all the new generation particles and update the group’s best positions. (10) Output If the preset condition is met, the iteration is stopped, and the matching result is output; otherwise, (4) will be returned.

Case Analysis To verify the model’s and algorithm’s performance, the data of 2618 contracts of 665 pieces of steel stored in a particular month in a specific steel plant are used for calculation. Three groups of calculation results are selected for analysis. At the initial stage, the parameters are set as 20 different orders, population sizepop = 500, maximum iteration times ger = 200, maximum inertia weight wmax = 0.9, minimum inertia weight wmin = 0.4, learning factor c1 = 2, and learning factor c2 = 2. The above stock slab and order sub-board are combined using the mathematical model established in this paper and the developed algorithm. The output is shown in Fig. 2. At this time, the timber rate is high, reaching 0.9% at the highest, and it also keeps running at a high level in the later period. When the parameters are set as population sizepop = 5000, maximum iteration times ger = 1000, maximum inertia weight wmax = 0.9, minimum inertia weight wmin = 0.4, learning factor c1 = 2, learning factor c2 = 2, and the threshold of adaptive

Research on the Model of Matching Inventory Slab with Order Contracts …

801

Fig. 2 Surplus material rate1

mutation is set as 0.9, the output result is shown in Fig. 3, and the residual timber rate is reduced. It runs stably at a low position in the later period. Then, the number of orders of different specifications is increased to 50, and the output result is shown in Fig. 4. The overall surplus rate is further reduced, reaching below 0.2% and stable below 0.1% in the later period. Finally, the experimental results show that the mathematical model and the improved particle swarm optimization algorithm can reduce the average matching residue ratio between the stock slab and customer order problem to less than 1%. The Fig. 3 Surplus material rate2

Fig. 4 Surplus material rate

802

C. Li et al.

more the number of matching order sub-boards and the types of external dimensions, the better the residue ratio can be controlled, even less than 0.2%, fully proving the feasibility and excellent performance of the model and algorithm.

Conclusion In this paper, an integer programming model is established to solve the problem of surplus material in steel enterprises, and a particle swarm optimization algorithm is designed to solve the model to reduce the excess material rate. The main research work of this paper can be summarized as follows: (1) Establishing the matching model of hot rolled coil residue. Based on the literature investigation of matching between the stock slab and customer order problem, the optimization objective and constraint conditions of hot rolled coil residue matching are analyzed, and a nonlinear 0–1 integer programming model is established by taking the minimization of residue ratio as the objective function. (2) Solving the model. A particle swarm optimization algorithm solves the model. An improved weighted particle swarm optimization algorithm-adaptive weighted particle swarm optimization algorithm is introduced, and the adaptive mutation of particles is added to the algorithm to improve the ability of global search and quickly obtain the global optimal solution. (3) The calculation results of the model show that the matching surplus ratio between the stock slab and customer order problem can be reduced to less than 1% on average by using the mathematical model and solution algorithm established in this paper. The more matching sub-boards and external dimensions, the better the surplus ratio is controlled, and even the excess ratio can be controlled below 0.2%.

References 1. Vasko FJ, Cregger ML, Stott KL et al (1994) Assigning slabs to orders: an example of appropriate model formulation. Comput Ind Eng 26(4):797–800 2. Denton B, Gupta D, Jawahir K (2003) Managing increasing product variety at integrated steel mills. Informs J Appl Anal 33(2):41–53 3. Kun-yuan H, Chun-guang C, Bin-lin Z (2004) The model and algorithm for joint optimization of inventory matching and production planning in steel plant. Inf Control 33(02):177–180 4. Forrest JJH, Kalagnanam J, Ladanyi L (2006) A column-generation approach to the multiple knapsack problem with color constraints. INFORMS J Comput 18(1):129–134 5. Song SH (2010) A nested column generation algorithm to the meta slab allocation problem in the steel making industry. Int J Prod Res 47(13):3625–3638

Research on the Model of Matching Inventory Slab with Order Contracts …

803

6. Azrag MAK, Kadir TAA (2019) Empirical study of segment particle swarm optimization and particle swarm optimization algorithms. Int J Adv Comput Sci Appl (IJACSA) 10(8):1118– 1123 7. Harrison KR, Ombuki-Berman BM, Engelbrecht AP (2019) A parameter-free particle swarm optimization algorithm using performance classifiers. Inf Sci 503:156–160 8. Abdul-Adheem, Wameedh, Riyadh (2019) An enhanced particle swarm optimization algorithm. Int J Electr Comput Eng (IJECE) 9(6):228–232 9. Rahman IU, Wang Z, Liu W, Ye B, Zakarya M, Liu X (2020) An N-state markovian jumping particle swarm optimization algorithm. IEEE Trans Syst Man Cybern Syst 51(11):949–955 10. Raß A (2020) High precision particle swarm optimization algorithm (HiPPSO). J Open Res Softw 8(1):666–671

Simulating Castable Aluminum Alloy Microstructures with AlloyGAN Deep Learning Model Biao Yin and Yangyang Fan

Abstract Material scientists have made progress in controlling alloy performance through microstructure quantification. However, attempts at numerically modeling microstructures have failed due to the complex nature of the solidification process. In this research, we present the AlloyGAN deep learning model to generate microstructures for castable aluminum alloys. This innovative model demonstrates its capacity to simulate the evolution of aluminum alloy microstructures in response to variations in composition and cooling rates. Specifically, it is successful to simulate various effects on castable aluminum, including: (1) the influence of Si and other elements on microstructures, (2) the relationship between cooling rate and Secondary Dendritic Arm Spacing, and (3) the impact of P/Sr elements on microstructures. Our model delivers results that match the accuracy and robustness of traditional computational materials science methods, yet significantly reduces computation time. Keywords Deep learning · Aluminum alloys · Microstructure · Generative Adversarial Network

Introduction The global metal market, crucial for industries like construction and aerospace, hinges on alloys for their reliable properties. With a projected worth of $18.5 trillion by 2030, alloy manufacturing is a key market driver [1]. Aluminum alloy casting and novel alloy development are crucial yet expensive, with a high rate of product rejections, which must be re-melted and re-cast due to various defects. Annually, the industry sees tens of millions of tons of metal casting products fall into this cycle B. Yin Data Science Program, Worcester Polytechnic Institute, Worcester, MA, USA e-mail: [email protected] Y. Fan (B) DeepAlloy, Portland, OR, USA e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_69

804

Simulating Castable Aluminum Alloy Microstructures with AlloyGAN …

805

[2]. Thus, efficient and reliable simulation models for accelerating scientific alloy discovery and reducing costs of manufacturing will bring immense economic and environmental benefits. Traditional numerical methods have struggled with the complex solidification process in alloy formation, characterized by vast nonlinear chemical and physical interactions [3–7]. These models are intricate, computationally demanding, and require specific knowledge of material science, limiting their accessibility to the broader research community [8–13]. The problem thus is the urgent need for more efficient and accurate methods to generate microstructure images of metal alloys, based on initial conditions like chemical composition and manufacturing setting. Training from limited data, these methods should accurately model complicated chemical reactions while ensuring scientific validity and less computational complexity for practical application. Deep learning techniques like VAEs, GANs, and Diffusions are being explored for microstructural analysis of materials in an early stage [14–18]. Their application remains limited, however, particularly in generating scientifically valid images based on basic alloy compositions. The existing deep learning methods haven’t fully addressed the complexities inherent in material science [19–22]. This void emphasizes the need for innovative solutions capable of dealing with the complex nonlinear dynamics of the alloy microstructure formation and delivering robust generation capabilities to accelerate scientific alloy discovery. To bridge this gap, we propose AlloyGAN, a ground-breaking approach leveraging the power of deep learning to create scientifically valid alloy microstructure images from basic alloy compositions (see Fig. 1). By integrating materials database, domain knowledge, and deep learning approach, AlloyGAN is thereby successfully simulating the microstructure of alloys with complex compositions and casting parameters. This innovative method seamlessly integrates materials databases, domain knowledge, and deep learning techniques, thereby enabling the accurate simulation of alloy microstructures with intricate compositions and casting parameters. The AlloyGAN model comprises three key components: a reliable materials database, a robust neural network, and domain expertise in materials science. By inputting alloy compositions and casting parameters, the model can produce corresponding microstructures. These generated micrographs closely resemble real-world microstructures, empowering materials engineers and scientists to assess material performance effectively.

Alloy Microstructure Database Datasets play a crucial role in the training of deep learning models. Our dataset comprises 21,000 microstructure images, encompassing nine distinct alloys subjected to various manufacturing conditions, as detailed in Table 1. Each row within the table corresponds to a specific alloy type with unique chemical compositions. Furthermore, each alloy undergoes diverse cooling rates and modification

806

B. Yin and Y. Fan

Fig. 1 Workflow of the AlloyGAN model. The model consists of three integral components: a materials database, a neural network, and materials knowledge. When alloy compositions and other relevant parameters are provided as input, the model proceeds to generate corresponding micrographs that closely mimic real-world microstructures

Table 1 Summary of the alloys employed in training the AlloyGAN deep learning model. It encompasses micrographs of nine distinct alloys, each subjected to varying cooling rates and modification conditions, all of which are integral to the training process Alloy

Si

Fe

Cu

Mn

Mg

Ni

Cooling rate (K/s)

Modification

A356

7

0.5

0.25

0.35

0.3

0

2.5, 10, 57, 143

Yes, No

A360

9.5

0.6

0.1

0.05

0.5

0

2.5, 10, 57, 143

No

A369

11.5

1

0.5

0.25

0.4

0.05

2.5, 10, 57, 143

Yes, No

A339

12

1.2

2

0.5

1

1

2.5, 10, 57, 143

No

A393

22

1.3

0.9

0.1

1

2.3

2.5, 10, 57, 143

Yes, No

A355

5

0.65

1.25

0.55

0.5

0

2.5, 10, 57, 143

No

A308

5.5

0.8

4.5

0.5

0.1

0

2.5, 10, 57, 143

No

A319

6

1

4

0.4

0.55

0.35

2.5, 10, 57, 143

No

A332

9.5

0.9

3

0.5

2.1

0.5

2.5, 10, 57, 143

No

processes. These alloys were prepared using both sand and permanent mold techniques, resulting in cooling rates ranging from 1 to 100 K/s. Notably, alloys A356, A369, and A393 were modified by the addition of minute quantities of Strontium or Phosphorus (Sr/P), inducing significant alterations in the microstructures of these Si-based aluminum alloys through complex chemical reactions.

AlloyGAN Deep Learning Model AlloyGAN builds upon the foundational principles of conditional Generative Adversarial Networks (cGANs) and incorporates unique adaptations that leverage prior knowledge of solidification reactions to generate scientifically valid alloy microstructure images. Similar to other Generative Adversarial Networks, AlloyGAN

Simulating Castable Aluminum Alloy Microstructures with AlloyGAN …

807

comprises two major components: the Generative Network and the Discriminative Network. The role of the Generative Network is to produce synthetic microstructure images, while the Discriminative Network acts as a classifier, attempting to distinguish between real and generated data. Through numerous training epochs, typically numbering in the hundreds or thousands, the Generative Network undergoes training loops to generate virtual micrographs that closely resemble real ones. Simultaneously, the Discriminative Network is trained to become progressively more proficient at discerning whether a given micrograph is genuine or generated (‘fake’). The ultimate objective is for the Generative Network to produce micrographs so authentic that even experts would struggle to distinguish them from real ones. Meanwhile, the Discriminative Network should reach a point where it has a 50–50 chance of correctly identifying whether an image originates from the Generative Network.

Results and Discussion As training epochs progress, these micrographs increasingly resemble real castable aluminum alloy structures. We assess the quality of the generated micrographs using three key metrics: (1) the model’s capacity to accurately depict the influence of Si content on microstructures. (2) Its ability to demonstrate the relationship between Secondary Dendritic Arm Spacing and cooling rates. (3) Its effectiveness in revealing the effects of Sr/P modifications on microstructures. Figure 2 displays representative micrographs of model-generated images featuring varying Si contents. In these images, white pixels represent Al phases, while black/ gray pixels represent Si or Si compounds. As the Si content increases, the AlloyGAN model accurately depicts the rising presence of Si or Si compounds in the generated micrographs. Figure 3 provides a quantitative representation of the increasing area fractions of Si phases in relation to Si content within the AlloyGAN-generated micrographs. These results serve as compelling evidence that the AlloyGAN model has effectively learned how Si contents influence aluminum microstructures. The Secondary Dendritic Arm Spacing (SDAS) in the AlloyGAN-generated micrographs is assessed across various alloy compositions and cooling rates. It is a well-established fact that in the solidification process of metals, SDAS decreases with increasing cooling rates. This relationship can be quantified as follows [23]: λ = k(C R)−n (n > 0)

(1)

whereas λ represents SDAS, CR represents the cooling rate, k is a constant, and n is a positive number. We have measured the data for A356, A319, and A355 alloys, fitted it into Eq. 1, and plotted the results in Fig. 4. The outcomes demonstrate a strong fit to Eq. 1, indicating that the images generated by AlloyGAN align well with real-world

808

B. Yin and Y. Fan

Fig. 2 AlloyGAN generated micrographs of A356, A332, A339, and A393 alloys which have Si contents of 7, 9.5, 12, and 22%, respectively. The black/gray pixels correspond to Si or Si compound phases 60.00% Measured Si Area Fraction in Generated Images

Area Fraction of Si

50.00% 40.00% 30.00% 20.00% 10.00% 0.00% 0%

5%

10%

15%

20%

25%

Si wt Content Fig. 3 Quantitative analysis of the relationship between Si contents and the area fractions of Si phases in AlloyGAN-generated micrographs

Simulating Castable Aluminum Alloy Microstructures with AlloyGAN …

SDRS(um)

A356

A319

A355 n = 0.1 R² = 0.9775

45 40 35 30 25 20 15 10 5 0

n = 0.03 R² = 0.8756

n = 1.1 R² = 0.9878

0

0.2

0.4

809

0.6

0.8

1

1.2

(CR)-n Fig. 4 Measurement of SDRS with cooling rate in AlloyGAN-generated micrographs

solidification phenomena. It underscores that the model has effectively captured how cooling rates influence SDAS in castable aluminum alloys. Strontium and Phosphorus are frequently employed to modify the microstructure of castable aluminum alloys. The modified microstructures typically exhibit increased branching of eutectic Si phases, resulting in a smoother and more rounded appearance. This transformation occurs by enhancing twin density through a phenomenon known as impurity-induced twinning, as well as facilitating smoother eutectic growth during solidification [24]. In Fig. 5a–c, we observe AlloyGAN-generated micrographs of A356, A369, and A393 under unmodified conditions, while Fig. 5e, f display the corresponding generated images under modification conditions. These images distinctly reveal that the Si phases (depicted by dark pixels) are significantly finer and dispersed in the presence of Sr/P modifications. This evidence underscores that AlloyGAN has effectively learned how modification elements impact the microstructure of castable aluminum alloys.

AlloyGAN Website We have made AlloyGAN accessible via a website (http://deepalloy.com). Users can create scientifically valid images given their text prompt to determining expected Alloy compositions within only 1 s. Enhancements of AlloyGAN to support different types of materials will continue to drive up its value to the material science community and customers.

810

B. Yin and Y. Fan

Fig. 5 a–c A356 alloy, A369, and A393 alloys with cooling rate = 2.5 K/s, unmodified. d–f A356 alloy, A369, and A393 alloys with cooling rate = 2.5 K/s, modified

Conclusion AlloyGAN successfully generates microstructures of aluminum alloys under an array of promptable conditions, taking into account various chemical elements, manufacturing environments, as well as fundamental materials domain knowledge. AlloyGAN achieves results rivaling traditional computational material science methods in accuracy, while significantly reducing time and dependency on complex domain knowledge. With the launch of AlloyGAN, we unlock a path to remarkably efficient and ground-breaking applications in both material verification and scientific discovery in the field.

References 1. Allied Market Research (2022) Metal & metal manufactured products market 2021–2030. https://www.alliedmarketresearch.com. Accessed April 2022 2. Anderson MP, Grest GS, Srolovitz DJ (1985) Grain growth in three dimensions: a lattice model. Scr Metall (United States) 19(2) 3. Azimi SM, Britz D, Engstler M, Fritz M, Mücklich F (2018) Advanced steel microstructural classification by deep learning methods. Sci Rep 8(1):2128

Simulating Castable Aluminum Alloy Microstructures with AlloyGAN …

811

4. Conti M, Di Pietro R, Mancini LV, Mei A (2009) Distributed data source verification in wireless sensor networks. Information Fusion 10(4):342–353 5. Eiken J (2009) Dendritic growth texture evolution in Mg-based alloys investigated by phasefield simulation. Int J Cast Met Res 22(1–4):86–89 6. Ferreira I, Ochoa L, Koeshidayatullah A (2022) On the generation of realistic synthetic petrographic datasets using a style-based GAN. Sci Rep 12(1):12845 7. Holm EA, Cohn R, Gao N, Kitahara AR, Matson TP, Lei B, Yarasi SR (2020) Overview: computer vision and machine learning for microstructural characterization and analysis. Metall and Mater Trans A 51:5985–5999 8. Iyer A, Dey B, Dasgupta A, Chen W, Chakraborty A (2019) A conditional generative model for predicting material microstructures from processing methods. arXiv preprint arXiv:1910. 02133 9. Jung J, Na J, Park HK, Park JM, Kim G, Lee S, Kim HS (2021) Super-resolving material microstructure image via deep learning for microstructure characterization and mechanical behavior analysis. npj Comput Mater 7(1):96 10. Jung J, Yoon JI, Park HK, Jo H, Kim HS (2020) Microstructure design using machine learning generated low dimensional and continuous design space. Materialia 11:100690 11. Kim Y, Park HK, Jung J, Asghari-Rad P, Lee S, Kim JY, Kim HS (2021) Exploration of optimal microstructure and mechanical properties in continuous microstructure space using a variational autoencoder. Mater Des 202:109544 12. Kobayashi R (1993) Modeling and numerical simulations of dendritic crystal growth. Phys D 63(3–4):410–423 13. Lee JW, Goo NH, Park WB, Pyo M, Sohn KS (2021) Virtual microstructure design for steels using generative adversarial networks. Eng Rep 3(1):e12274 14. Lee KH, Yun GJ (2023) Microstructure reconstruction using diffusion-based generative models. Mech Adv Mater Struct 1–19 15. Li X, Zhang Y, Zhao H, Burkhart C, Brinson LC, Chen W (2018) A transfer learning approach for microstructure reconstruction and structure-property predictions. Sci Rep 8(1):13461 16. Li YL, Chen LQ (2006) Temperature-strain phase diagram for BaTiO3 thin films. Appl Phys Lett 88(7) 17. Ma W, Kautz EJ, Baskaran A, Chowdhury A, Joshi V, Yener B, Lewis DJ (2020) Image-driven discriminative and generative machine learning algorithms for establishing microstructure– processing relationships. J Appl Phys 128(13) 18. Makhlouf ASH, Aliofkhazraei M (2015) Handbook of materials failure analysis with case studies from the aerospace and automotive industries. Butterworth-Heinemann 19. Moon IY, Lee HW, Kim SJ, Oh YS, Jung J, Kang SH (2021) Analysis of the region of interest according to CNN structure in hierarchical pattern surface inspection using CAM. Materials 14(9):2095 20. Na J, Kim G, Kang SH, Kim SJ, Lee S (2021) Deep learning-based discriminative refocusing of scanning electron microscopy images for materials science. Acta Mater 214:116987 21. Ning L, Cai Z, Liu Y, Wang W (2021) Conditional generative adversarial network driven approach for direct prediction of thermal stress based on two-phase material SEM images. Ceram Int 47(24):34115–34126 22. Oh S, Kim HK, Jeong TE, Kam DH, Ki H (2020) Deep-learning-based predictive architectures for self-piercing riveting process. IEEE Access 8:116254–116267 23. Fisher D, Kurz W (1998) Fundamentals of solidification. Fundam Solidi 1–316 24. Lu SZ, Hellawell A (1987) The mechanism of silicon modification in aluminum-silicon alloys: Impurity induced twinning. Metall Trans A 18:1721–1733

Temperature Prediction of Continuous Casting Slab Based on Improved Extreme Learning Machine Kun-chi Jiang, Ming-mei Zhu, Cheng-hong Li, Xian-Wu Zhang, Hong-yu Lin, Kai-tian Zhang, and Zhong Zheng

Abstract A fusion ELM model based on ensemble learning was proposed to predict slab temperature. Combined with the actual production data of a steel mill, the integrated ELM, ELM, ANN, BP networks are designed and the comparison test proves that the integrated ELM model has more advantages in the aspects of running time and prediction accuracy. The number of base models for integrating ELM model is determined to be 3, the number of hidden layer nodes is 20, and the neuron activation function Hardlim is the most suitable for steel mill data set. The results show that the average hit rate of the predicted temperature is 88.89% within ±5 °C, and the MAE and RMSE of the predicted results are 2.46 and 2.85 °C, respectively, indicating that the model has high accuracy and stability, and can be used to predict the casting slab temperature. Keywords Continuous casting slab · Extreme learning machine · Temperature prediction model · Optimization algorithm

Introduction Continuous casting is an important process for slab forming and quality assurance, and it is also the core of long process steelmaking to promote dynamic—orderly, coordinated—continuous operation of the whole process. The determination of the surface temperature of the slab in the secondary cooling zone is very important for the formulation of a reasonable cooling system and a pressing system, and the improvement of the production of the casting machine and the quality of the slab. Based on mechanism analysis, many scholars at home and abroad have established temperature prediction models for continuous casting slab [1, 2]. Wang et al. [3] established a two-dimensional mathematical model of slab heat transfer to predict K. Jiang · M. Zhu (B) · C. Li · X.-W. Zhang · H. Lin · K. Zhang · Z. Zheng College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_70

812

Temperature Prediction of Continuous Casting Slab Based on Improved …

813

slab temperature distribution and slab shell thickness. Bryan Petrus et al. [4] established a one-dimensional finite difference model for predicting slab temperature and solidification state during continuous casting. S. Mosayebidorcheh et al. [5] conducted steady-state analysis of slab temperature and phase transition in the continuous casting process and established the two-dimensional heat transfer equation in the continuous casting process. In recent years, with the development of computer and related technologies, more and more researchers have established a temperature prediction model of continuous casting slab based on statistical data [6, 7]. Based on the experimental study, Fupingyuan et al. [8] established a prediction model of continuous casting slab surface temperature by using artificial neural network, and the prediction error of the model was 5–10 °C. Zhan Xianhui [9] used BP neural network to identify the mathematical model of solidification heat transfer in continuous casting and realized the prediction of casting slab temperature. Tian Shanshan [10] adopted particle swarm optimization and genetic hybrid algorithm to optimize the parameters of support vector machine and established the temperature prediction model of each stage of continuous casting secondary cooling based on the optimized support vector machine. The test results show that the model error can meet the requirements of dynamic control of secondary cooling. The data model has the characteristics of simple modeling, fast influence speed, and high prediction accuracy. However, the model parameters in the data model are complex and changeable, and in order to achieve the advantages of high prediction accuracy, a large number of simulation tests need to be carried out. Therefore, this paper intends to establish a data model for the temperature prediction of continuous casting slab, and adopt the method based on the improved extreme learning machine to predict the temperature of continuous casting slab. In this paper, the real data of steel mills are preprocessed and the characteristic parameters are selected. Then, the reasonable model parameters are determined through the comparison test of the number of base models, the integrated ELM model under different activation functions, and the number of hidden nodes. Finally, the actual effect of the algorithm is tested with the actual production data of a factory, and the test results show that the method has high stability and improves the prediction accuracy.

Continuous Casting Slab Temperature Prediction Model Data Preprocessing and Feature Parameter Selection By analyzing the composition and characteristics of steel mill data, it is found that the actual data has various problems due to the system or human reasons, such as the existence of outliers, redundant values, or missing values, and different data structures, dimensions, and orders of magnitude, so it cannot be directly used for modeling. Therefore, it is necessary to process the data first, ensure the quality

814

K. Jiang et al.

and quantity of the data set, and provide support for further data law analysis and modeling. According to the analysis of the actual production data and the calculation results, this paper selected the steel grade, steel casting temperature, cooling water, drawing speed, and specifications as the characteristics of the prediction model. There are two main purposes for feature selection: one is to simplify the input parameters of the data model to ensure the calculation speed of the data model; the other is to eliminate the factors that have no significant impact on the energy conversion of the continuous casting process (that is, irrelevant attributes) to avoid the impact of irrelevant factors on the accuracy of the model, increase the effectiveness of the analysis task, thereby improving the accuracy of the model and reducing the running time [11].

Establishment of Temperature Prediction Model for Continuous Casting Slab The slab temperature prediction model is a data model based on historical data training, which can reproduce the historical production process, help production personnel review the production process, find the cause of failure, and analyze the improvement space. Moreover, when the real-time database is connected, the temperature of the slab can be predicted quickly according to the real-time parameters of molten steel, the parameters of continuous casting process, and the production target. The prediction model of casting slab temperature mainly consists of the following three parts: feature selection and data processing, ELM training based on sub-data set, and integration of prediction results. Feature selection and data processing mainly simplify the original data and re-sample the simplified data set to obtain multiple sub-data sets. Through mechanism analysis, it is found that the relevant factors that significantly affect the energy conversion of continuous casting units include casting temperature, drawing speed, secondary cooling water distribution, and specifications. ELM training based on sub-data sets uses the same algorithm to train on different data sets and obtains several different base models. The test data set is input into each trained sub-model to obtain the corresponding prediction results, and then the prediction results of each sub-model are linearly integrated and the final prediction results are obtained. The implementation process of the model is as follows: 1. Initialization: Each sub-model randomly initializes its network weight and bias and obtains the Moore–Penrose generalized inverse matrix for calculating the output weight of neurons. 2. Data preparation: Based on the selected features, the data is simplified and resamples to obtain n sub-data sets. 3. Model training: Input n sub-data sets to the ELM model, and obtain n trained base models.

Temperature Prediction of Continuous Casting Slab Based on Improved …

815

4. Prediction result integration: Input the test data into the trained ELM model to obtain n prediction results, and use the linear weighted average method to obtain the final output results.

Improved Extreme Learning Machine Method In this paper, Extreme Learning Machine (Extreme Learning Machine) is used to model the continuous casting process. ELM is a simple and effective Single Hidden Layer Feedforward Neural Network (SLFN) learning algorithm. The biggest feature of ELM is that compared with traditional neural networks, especially SLFN, it is faster than traditional learning methods on the premise of ensuring learning accuracy [12]. ELM can still maintain SLFN’s interpolation ability [13], general approximation ability [12], and classification ability [4] even when the hidden layer neuron parameters are randomly generated. Ensemble learning is an important data mining method, which combines multiple weak learners to form a new strong learning model to reduce model variance, bias, or improve prediction, and can improve the generalization ability of learning system. According to the generation strategy of base learners, ensemble learning methods can currently be classified into two categories: Bagging algorithm and Boosting algorithm. When a single prediction model is more unstable, Bagging method can improve the effect of fusion model [8]. ELM can improve the operation efficiency of neurons by randomly initializing network input weights and bias. Random initialization makes different ELM models which differ greatly and have strong diversity, and the prediction effect is unstable, but it is suitable for Bagging method for fusion enhancement. Therefore, this study will use Bagging method for fusion enhancement of ELM model. Re-sampling of the original data set was conducted to obtain n new sub-data sets, and then n different ELM models were trained based on the n sub-data sets. Finally, n ELM models were fused by linear average integration to obtain an integrated ELM model, as shown in Fig. 1. The output of the final integrated model is shown in Formula (1). Y (x) =

n 1∑ yi (x) n i=1

(1)

Result Analysis This paper uses the Combined Cycle Power Plant Data Set of UCI data set to test the algorithm and compares it with ANN and BP neural network. The performance test of integrated ELM model under different sampling times and the comparison

816

K. Jiang et al.

Fig. 1 Ensemble ELM based on bagging

test between ELM hidden layer node and activation function are designed to determine reasonable model parameters. Finally, using the actual production data of slab continuous casting machine in a factory as data set, the actual effect of the algorithm is tested.

Algorithm Performance Test UCI Data Set is a commonly used standard test data set for machine learning. The Combined Cycle Power Plant Data Set (CCPPDS) is a data set in UCI that includes four input variables and one output variable, which is consistent with the number of input and output variables of continuous casting unit in this study. The CCPPDS data set contains 9568 sets of valid data, which are normalized and tested in MATLAB R2017a environment. The ANN and BP neural networks are deployed by using MATLAB’s own toolbox, which are neural networks containing 3 layers and 20 hidden layer nodes, respectively. ANN and BP networks adopt the default configuration of MATLAB, and ELM adopts sin activation function. In the experiment, 9000 sets of data in the data set were used as the training set, and the remaining 568 sets of data were used as the test set, which were respectively input into ANN, BP network, and ELM. The test performance indexes included algorithm time, Mean Absolute Error (MAE), and root mean square error (RMSE) of the test set. Root Mean Squared Error). MAE and RMSE can reflect the deviation degree and accuracy of the predicted data. Generally, the smaller MAE and RSEM are, the higher the accuracy of the model is. They are common performance indicators to measure the prediction algorithm, and the calculation methods are shown in Formulas (2) and (3), respectively. n | 1 ∑ || yi − yi | n i=1 ┌ | n |1 ∑( )2 yi − yi RMSE = | n i=1

MAE =

∆

(2)

∆

(3)

Temperature Prediction of Continuous Casting Slab Based on Improved … Table 1 Performance comparison results of various algorithms

817

Algorithm

CPU time (s)

MAE

ANN

4.3438

0.0365

RMSE 0.048

BP neural network

0.6719

0.0437

0.2209

ELM

0.4115

0.0424

0.0528

Integrated ELM

0.6511

0.0417

0.0519

This paper compares the performance of ANN, BP network, single ELM algorithm, and integrated ELM algorithm in the same environment and data set, and the results are shown in Table 1. Three basic ELM models are trained in integrated ELM, and then, the three basic ELM models are grouped together by linear average. It can be seen from Table 1 that the overall performance of ELM is better than that of ANN and BP networks. The accuracy and stability of ELM can be improved on the basis of slightly reducing the running time of the algorithm with appropriate integration of ELM model. Therefore, the integration of ELM model can obtain smaller errors and more stable results.

Analysis of Prediction Results of Casting Slab Temperature Based on the production data of slab continuous casting machine in a factory, the effect of the integrated ELM model proposed in this paper is tested in practice. About 178 sets of valid data were selected, and the attributes of the data set included molten steel temperature (°C), drawing speed, water distribution of secondary cooling (L/ min), specification (m2 ), and slab temperature of straightening point (°C). The data of molten steel temperature, drawing speed, and specification came from the actual data of the steel mill. The water distribution of secondary cooling per flow of the casting machine was calculated by Eq. (4) [14]. The slab temperature at the straightening point was calculated according to the data in reference [15]. Q a = 1000 × W R × Fm × vc × ρb

(4)

Among them, WR is Specific water, desirable for air–water cooling WR = 1.5 L/ kg; F m is the selected section of the slab, m2 ; vc is the drawing speed corresponding to the current slab section, m/min; ρ b is the density of cold slab, ρ b = 7.8 t/m3 .

Comparative Test of ANN-BP-ELM Data Set in Steel Mills In order to analyze whether ELM is still effective on the steel mill data set pair, the same parameters are used to test on the steel mill data set. The test results are shown in Table 2. It can be found that the performance of ELM in CPU Time, MAE, and RSME is better than that of ANN and BP network, which proves that ELM still has a good performance on this data set.

818 Table 2 Test results of ELM-ANN-BP under the steel plant data set

K. Jiang et al.

Algorithm

CPU time (s)

MAE

ANN

0.8021

0.1429

RMSE 0.1669

BP neural network

0.7665

0.1398

0.1634

ELM

0.4792

0.1287

0.1528

Table 3 Ensemble ELM test results under different sampling times Base model quantity

CPU time (s)

MAE (°C)

RMSE (°C)

±5 °C (%)

1

0.2917

2.9095

3.5368

81.48

3

0.4323

2.484

3.0057

88.89

5

0.5261

2.1547

2.6798

94.44

Base Model Number Comparison Test Different number of base models have a great impact on the performance of the integrated ELM model. Comparison tests of 1, 3, and 5 base models were set respectively to compare the performance indicators of each integrated ELM model under different number of base models. The tests were carried out under the same activation function Hardlim. Three tests were carried out in each case, and the average values of the three test results were taken, as shown in Table 3. It can be seen from Table 3 that with the increase of the number of base models, the running time of the integrated ELM method increases significantly, while MAE and RSME both show a downward trend, indicating that the training time of the integrated model is longer, but more stable and accurate results can be obtained. The average hit rates of prediction results and original values under 1, 3, and 5 base models at ±5°C are 81.48, 88.89, and 94.44%, respectively, indicating that the prediction accuracy of fusion model can be significantly improved by integrating more base models. Based on the above test results and analysis, after considering the model effect and calculation time comprehensively, it is decided to obtain an integrated ELM model by fusing three basic ELM models.

Comparative Experiment of Integrated ELM Model Under Different Activation Functions Under the condition of the same 20 hidden layer nodes, the classic Sig, Sin, Hardlim, and Tbibas functions are selected as test objects, and three tests are conducted under each activation function condition to observe the impact of model differences caused by ELM random initial hidden layer network weight and bias on the actual data. First, the data is normalized, and then the model is input for training and testing. The amount of data used for training and testing respectively is shown in Table 4.

Temperature Prediction of Continuous Casting Slab Based on Improved …

819

Table 4 Training data and test data distribution 1#ELM

2#ELM

3#ELM

TEXT

40

50

70

18

Table 5 Comparison of the results of ensemble ELM under different activation functions Activation function

CPU time (s)

MAE (°C)

RMSE (°C)

±5 °C (%)

Sin

0.3698

4.2059

5.2714

72.22

Sig

0.3073

4.514

5.8877

68.52

Hardlim

0.2604

2.4865

2.9781

94.44

Tribas

0.2656

3.7355

5.2178

79.63

The test results are shown in Table 5, where ±5 °C represents the percentage of deviation between the predicted value and the true value within ±5 °C. It can be seen that Hardlim and Tribas of the integrated ELM model have the shortest running time under each activation function. From the two indexes of MAE and RSME, it can be found that the integrated ELM model using Hardlim function as the activation function has smaller prediction accuracy and deviation. Judging from the prediction accuracy in the range of ±5 °C, Hardlim has the best average hit rate of three tests under each activation function. Therefore, Hardlim was selected as the network parameter for subsequent research.

Comparison Test of the Number of Nodes in Hidden Layer In order to determine reasonable hidden layer node data, a comparison test of the number of hidden layer nodes was designed, and the performance of integrated ELM under the number of 5, 10, and 20 hidden layer nodes was tested, respectively. The training data set was divided as shown in Table 4, and the simulation results are shown in Table 6. It can be seen from Table 4 that the number of nodes in the hidden layer has little impact on the running time of the integrated ELM model. Compared with the MAE and RMSE diagrams, it can be seen that when the number of hidden layer nodes is larger, the prediction results of the model are more stable, and the fluctuation and error are reduced. When the number of nodes in the hidden layer is n = 5, 10, 20, the average hit rate of the predicted values of the three tests within the range of ±5 °C is 81.48, 83.33, 94.44%, respectively. With the increase of the number of nodes in the hidden layer, the prediction accuracy of the model has an increasing trend. Therefore, the subsequent experiments in this paper used 20 hidden layer nodes to initialize the network.

820

K. Jiang et al.

Table 6 Test results of different hidden layer nodes Number of hidden layer nodes

CPU time (s)

MAE (°C)

RMSE (°C)

±5 °C (%)

5

0.3073

2.6675

3.4287

81.48

10

0.2865

2.8132

3.5887

83.33

20

0.2604

2.4865

2.9781

94.44

Table 7 Performance results of slab temperature prediction model

CPU Time/s

MAE/°C

RMSE/°C

±5 °C

0.2188

2.46

2.85

88.89%

Slab Temperature Prediction Test Through the sample sampling times test and the integrated ELM model comparison test under different activation functions, the optimal neuron activation function Hardlim was determined to train three basic ELM nodes, 20 hidden layer nodes and SDC04 steel data set in the fusion model. The prediction model of casting slab temperature based on integrated ELM method was simulated, and the data set was divided as shown in Table 4. The simulation results are shown in Table 7 and Figs. 2 and 3. The calculation period of the predicted model is 0.2188 s, which can quickly give the slab temperature at the straightening point under the current production conditions. The mean absolute deviation (MAE) and root mean square error (RMSE) of the prediction results of the 18 groups were 2.46 and 2.85 °C, respectively, both within 5 °C. It can be concluded that the predicted value of the model has a small deviation from the actual value, and the prediction accuracy of the model is good. In the range of ±5 °C, the hit rate between the predicted result and the original value is 88.89%, and a good effect is obtained.

Conclusions (1) In this paper, a fusion ELM model based on ensemble learning was established to predict the casting slab temperature, and the integrated ELM, ELM, ANN, and BP networks were designed and compared to prove that the integrated ELM model has more advantages in terms of running time and prediction accuracy. (2) Through experiments, the number of integrated ELM model is determined to be 3, the number of hidden layer nodes is 20, and the neuron activation function Hardlim is the most suitable for steel mill data set. (3) The results show that the average hit rate between the predicted temperature and the actual temperature is 88.89% within the range of ±5 °C, and the MAE and RMSE of the predicted results are 2.46 and 2.85 °C, respectively, indicating that the model has high accuracy and stability and can be used to predict the casting slab temperature.

Temperature Prediction of Continuous Casting Slab Based on Improved …

Fig. 2 Distribution of actual and predicted values of slab temperature

Fig. 3 Actual value and prediction result of slab temperature

821

822

K. Jiang et al.

References 1. Qiu S, Liu H, Gan Y, Liu H, Gan Y (2003) Numerical simulation of solidification process of slab continuous casting based on Continuous model. J Iron Steel Res (06):16–20 2. Alizadeh M, Edris H, Shafyei A (2006) Mathematical modeling of heat transfer for steel continuous casting process. Int J Iron Steel Soc Iran 3(2):7–16 3. Wang H, Li G, Lei Y, Zhao Y, Dai Q, Wang J (2005) Mathematical heat transfer model research for the improvement of continuous casting slab temperature. ISIJ Int 45(9):1291–1296 4. Petrus B, Zheng K, Zhou X, Thomas BG, Bentsman J (2011) Real-time, model-based spraycooling control system for steel continuous casting. Metall Mater Trans B-Process Metall Mater Process Sci 42(1):87–103 5. Mosayebidorcheh S (2017) Gorji-Bandpy M. Local and averaged-area analysis of steel slab heat transfer and phase change in continuous casting process. Appl Therm Eng 118:724–733 6. Zhang L, Cai C (2008) Secondary cooling control of continuous casting based on BP network. Comput Modern (10):66–69 7. Gao F, Changsong W, Ke X, Xiuyong W (2009) Intelligent control model for secondary cooling of slab continuous casting. J Univ Sci Technol Beijing 31(10):1322–1327. 8. Pingyuan F, Langjie Y, Weiqing C (1999) Prediction of slab surface temperature by neural network. Continuous Cast 06:21–23 9. Xianhui Z (2007) Study on dynamic control model of secondary cold water for slab continuous casting based on BP-GA algorithm. Chongqing University 10. Shanshan T (2018) Study on adaptive dynamic control algorithm for secondary cooling of continuous casting. Shenyang Polytechnic University 11. Yan H (2005) Study and application of mathematical model of heat transfer in solidification of continuous casting slab. Chongqing University 12. Su W, Wang W-L, Luo S, Jiang D-B, Zhu M-Y (2014) Heat transfer and central segregation of continuously cast high carbon steel slab. J Iron Steel Res Int 21(6):565–574 13. Ma J, Xie Z, Jia G (2008) Applying of real-time heat transfer and solidification model on the dynamic control system of lab continuous casting. ISIJ Int 48(12):1722–1727 14. Ladao Y, Jinchun H, Shuxian L et al (2017) Straight arc slab continuous casting equipment. Metallurgical Industry Press 15. Fuhua S, Jiangang D (2009) Prediction of continuous casting slab surface temperature based on support vector machine. Steelmaking 25(01):55–59

Part XXII

Algorithm Development in Materials Science and Engineering

A Line-Free Discrete Dislocation Dynamics Method for Finite Domains Aitor Cruzado, Pilar Ariza, Alan Needleman, Michael Ortiz, and Amine Benzerga

Abstract A method for solving general boundary-value problems involving discrete dislocations is introduced. Plastic flow emerges from the motion of dislocations in an incremental fashion. At each increment, the displacement, strain and stress fields in the body are obtained by superposition of the infinite medium fields associated with individual dislocations and an image field that enforces boundary conditions. Dislocations are represented as monopoles and dislocation events are treated as a transportation map problem. Long-range interactions are accounted for through linear elasticity with a core regularization procedure. At the current state of development of the method, no ad hoc short-range interactions are included. An approximate loop nucleation model is used for large-scale computations. The image problem is solved using a finite element formulation with the following features: (i) a single Cholesky decomposition of the global stiffness matrix, (ii) a consistent enforcement of traction and displacement boundary conditions, and (iii) image force interpolation using an efficient BB-tree algorithm. To ensure accuracy, we explore stable time steps and employ monopole splitting techniques. Special attention is given to the interaction of curved dislocations with arbitrary domain boundaries and free surfaces. The capabilities of the framework are illustrated through a wire torsion problem. Keywords DDD · Line free method · Free surfaces · Finite elements

A. Cruzado (B) · A. Benzerga Department of Aerospace Engineering, Texas A&M University, College Station, TX 77843, USA e-mail: [email protected] P. Ariza Escuela Técnica Superior de Ingeniería, Universidad de Sevilla, 41092 Sevilla, Spain A. Needleman · A. Benzerga Department of Materials Science & Engineering, Texas A&M University, College Station, TX 77843, USA M. Ortiz Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125, USA © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_71

825

826

A. Cruzado et al.

Introduction Nearly three decades ago, discrete dislocation plasticity [1] emerged as a powerful framework for dealing with a range of problems where microstructural and dimensional length scales strongly interact. Phenomena analyzed within this framework include size effects [2, 3], fatigue [4], strain hardening [5], grain-size strengthening [6] creep [7, 8], and elastodynamics [9]. The framework is, however, limited to edge dislocations within a plane strain two-dimensional setting. Alternatively, three-dimensional dislocation dynamics methods have been developed with increasing sophistication [10–13], but for the most part have remained limited to infinite domains, e.g. under the assumption of periodicity. Methods that have been developed for finite domains [14–17] involve computationally inefficient coupling with finite elements and tedious constraints for maintaining linear connectivity among dislocation segments due to the line-based character of the methods. Recently, a line-free method has been developed which is based on the notion of monopoles [18]. Its simplicity resides in the point-like character of monopoles, which does not require keeping track of connectivity. A monopole represents a discrete element of line dislocations, each carrying a Burgers vector. Monopoles exhibit mobility kinetics driven by a synergy of elastic interactions and externally applied forces, allowing them to replicate the dynamic behavior of dislocations. The method has recently been used to investigate hardening in nano-crystals [19]. The purpose of this paper is to expand upon this method and develop a fully consistent coupling with finite elements to solve boundary value problems in arbitrary domains for small deformations.

Formulation A finite body occupying domain .Ω is subjected to boundary tractions .T0 and boundary displacements .U0 on boundary parts .∂Ωt and .∂Ωu , respectively. The body contains dislocation loops each being discretely represented by a set of monopoles M .a = 1 · · · M with coordinates .{xa }a=1 . Following the line-free method of monopoles for 3D dislocation dynamics [18, 19] each monopole concentrates a dislocation line M M and element of line .{ξa }a=1 . density and carries a Burgers vector .{ba }a=1 At time .t the body is in equilibrium and the position of each monopole in the body ˙ strain, .ε, is known. Superposition is used as in [1] to write the displacement rate .u, and stress, .σ, fields as: ˜˙ ˆ˙ ˙ u(x) = u(x) + u(x) ; ε = ε˜ + εˆ ; σ = σ˜ + σ, ˆ

.

(1)

˜ fields are obtained by superposition of the infinite medium fields of indiwhere the.(·) ˆ fields are image fields that enforce the boundary vidual dislocation loops and the .(·) conditions. Formally, one may write:

A Line-Free Discrete Dislocation Dynamics …

σ(x) ˜ =

827 M ∑

.

σ a (x)

(2)

a=1

where .σ a (x) is a term arising from using an appropriate Green’s function and Mura’s formula [20] for a general loop in a homogeneous unbounded medium. Details on stress calculations will be given elsewhere. For example, the time- and monopolediscretized infinite medium displacements read: u

. v+1

(x) − uv (x) =

M ∑

σ ϵ (x − xa,v+1/2 ) · ba,v+1/2 ⊗ ξa,v+1/2 × (xa,v+1 − xa,v )

a=1

(3) where .Σiϵjk is the stress corresponding to a regularized Green’s function .G iϵj . For isotropic elasticity with Lamé constants .λ and .μ, ϵ σ iϵjk = λG iϵp, p δ jk + μ(G iϵj,k + G ik, j)

.

(4)

ˆ fields are governed by a linear elastic boundary value On the other hand, the .(·) problem: .∇ · σ ˆ = 0 ; εˆ = ∇ ⊗ uˆ ; σˆ = L : εˆ for x ∈ Ω, (5) ˜ for x ∈ ∂Ωu n · σˆ = T0 − n · σ˜ for x ∈ ∂Ωt ; uˆ = U0 − U

.

(6)

with .L the isotropic tensor of elastic moduli and .n the outer normal. The method employed here does not require direct (and costly) traction calculations on the surface. Instead, if .F0,n denote the imposed nodal forces on a set .Γf of ˆ and .(·) ˜ problems, boundary nodes, .fˆn and .f˜n the corresponding nodal forces for the .(·) respectively, i.e. .fˆn = F0,n − f˜n , n ∈ Γf , (7) then the tilde forces are assembled over all elements that share a boundary surface node (total number . Nel ): Nel ∑ f˜e .f˜n = n ∈ Γf (8) e=1

where .f˜e is determined through consistent per element integration of the infinitemedium stresses (number of integration points . Nip ): .f˜e =

Nip ∑

B T (ξi , ηi , ζi )σ(ξ ˜ i , ηi , ζi ) | J i | wi

(9)

i=1

Here,. B T are the shape function “derivatives” evaluated at integration point.(ξi , ηi , ζi ), | J i | is the determinant of the Jacobian and .wi the weight of .i.

.

828

A. Cruzado et al.

The motion of a monopole is driven by the Peach-Koehler force: f = σ(x ˆ a ) · ba × ξa +

M ∑

. a

σ b (xa ) · ba × ξa

(10)

b/=a

The first term corresponds to the externally applied force, denoted .faext in [19]. The second term is replaced with .faϵ , which accounts for core regularization. The complete expression can be found in [18, 19]. Here, only the glide component is considered. The current position of monopole .a is obtained by solving the implicit Euler-Lagrange equation: .

| | Dψ(va (t)) |ξa (t)| + faϵ (x(t)) + faext (x(t)) = 0,

(11)

where .va is the monopole velocity, . Dψ(va (t)) denotes partial differentiation of the kinetic potential, here defined by a linear mobility law of the form: ψ (va (t)) =

.

1 |va (t)|2 , 2M

(12)

with . M the mobility. The elements of line are updated explicitly by the local gradient of the incremental transport map: ξ˙ (t) =

M ∑

. a

(∇ Nb (xa , t) · ξa (t))vb (t),

(13)

b=1

where the mesh-free scheme for the interpolation of the velocity is specified using the Max-ent shape functions: ) ( βa 1 2 exp − |x − xa (t)| , . Na (x, t) = Z 2

) ( βa 2 Z= exp − |x − xa (t)| , 2 a=1 (14) These shape functions “connect” the monopoles through an effective interaction √ distance of .1/ β. Time integration of Eqs. (11) and (13) is accomplished using an explicit two-stage Runge–Kutta method [19] or the Polak–Ribière iterative solver [18]. Determining the first term in Eq. (10), .faext , requires evaluating the image stress, determined by solving Eqs. (5) and (6), at the location of monopole .a. This is accomplished by interpolating the .σˆ field. In the course of a simulation, monopoles change elements. An efficient BB-tree element locator is used, given monopole coordinates .xa . Since the.σ ˆ field is discontinuous across element boundaries, it is first extrapolated to element nodes through the shape functions. Then the nodal values are averaged over all elements sharing the same node, before interpolation to the monopoles. M ∑

A Line-Free Discrete Dislocation Dynamics …

829

Next, the interaction of monopoles with free surfaces is treated as follows. The infinite medium analytical expression for .σ˜ is only valid for a dislocation loop. If part of the loop exits the body spurious stresses may be evaluated on the surface. To address this, a method of virtual monopoles is introduced, which mimics virtual segments in line-based methods. Thus, the monopoles that now lie outside of .Ω are detected (using a BB-tree) and removed. The two monopoles that are closest to the surface are identified and virtual monopoles are introduced to close the loop for subsequent stress calculations. The evolution problem is approached incrementally, demanding an efficient code coupling strategy. The MonoDis code [18, 19] is fully integrated within the finite element software Z-set [21] through a plug-in interface. Inversion of the global stiffness matrix is executed once, resulting in minimal computational burden in FEM. The methodology involves the following steps: 1. At time .t the body is in equilibrium and the position of each monopole in the body is known. The surface nodal forces .f˜ derived from .σ˜ and displacements .u˜ are computed. 2. The boundary-value problem defined by Eqs. (5) and (6) for the .σˆ field is solved. 3. The .σˆ field is interpolated to monopole locations in order to evaluate the PeachKoehler forces. 4. The mobility problem, Eq. (11), is solved to determine new monopole positions at time .t + Δt. 5. Monopoles that lie outside the body are flagged and removed. Virtual monopoles are added to close the dislocation loop for stress calculations. 6. Go to 1: .t .← .t + Δt. In this process, a distinctive rule involves modeling loop nucleation by introducing circular general loops. Locations of initial potential sources are randomly distributed in the body. At a given source location, a loop of radius .ρ nucleates when ext ϵ ϵ .||fa || > ||fa || where .a = arg max(||fn )|| is the monopole that presents the maximum n

regularized linear elastic PK force.

Results We first explore the optimal element of line .ξ that reproduces the non-singular solution for prismatic loops [18] and general loops [22]. For a core regularization parameter of .ϵ = b, we find that a value .ξ = 0.43b is needed to recover the analytical solution of the prismatic loop, Fig. 1a. A scalability relation between .ξ and .ϵ is also determined, which enables calculations with larger elements of lines without sacrificing accuracy. The relationship only holds for sufficiently large loops. To illustrate free surface effects, we consider, √ as in [14], a circular loop with radius .r = 4000a and Burgers vector .b = a(100)/ 2 placed at the center of a cube

830

A. Cruzado et al.

(a) 1.5

(b) 1.5

1

1

0.5

0.5

0

0

50

100

150

0

200

400

600

800

1000

Fig. 1 Peach-Koehler force (per unit length) normalized by .μb2 /(8π(1 − ν)ϵ) versus loop radius for: a prismatic loops and b general loops

(a)

(b)

0.9

0.2

0.8

0.15

0.7

0.1

0.6

0.05

0.5 0

0.4 -0.05

0.3 -0.1

0.2

5

10

15

20

25

30

0

1000

2000

3000

4000

5000

Fig. 2 a Glide PK force around the loop for various FE mesh discretizations. b Image shear stress, versus distance from center of loop

.τˆ ,

with traction free boundary conditions and parallel to (010) face. The cube has side length . L = 10000a and Cu material properties: lattice parameter .a = 0.3614 nm, shear modulus .μ = 45 GPa, mobility . M = 5.56 × 1021 nm.2 /Ns. Figure 2a shows both the analytically known infinite medium PK force (blue) and the FE computed image force for two types of finite elements and various mesh densities. Using quadratic elements, convergence is attained for a mesh density of .163 elements (element size of 441.b). Furthermore, we verify that the hat component of the resolved shear stress, .τˆ = −n i σˆ i j b j /b, corresponds to the numerical solution obtained in [14] using a line-based method, Fig. 2b. Next, consider the nucleation criterion. If the loop radius at nucleation is taken to coincide with the annihilation radius .ρ0 = 2.25ϵ (from maximum PK force in Fig. 2), then the corresponding equilibrium resolved shear stress is .τnuc = f ϵ ρ0 /(ξb). Stable growth of dislocation loops occurs when they nucleate at .τ = 1.5τnuc , as depicted in

A Line-Free Discrete Dislocation Dynamics …

831

Fig. 3 Analysis of stable growth of nucleated loops for an applied stress a.τ = τnuc , b.τ = 1.25τnuc and c .τ = 1.5τnuc

Fig. 4 Dislocation network evolution in a Cu wire measuring 500 nm in diameter and 1750 nm in length subjected to a twist of: a 1.◦ , b 1.5.◦ and c 2.◦

Fig. 3c. However, stable simulations require time increments .Δt ≈ 10−14 . If loops with a radius of operation of Frank–Read sources, say .ρ > 100b and .ϵ ≈ 20b, are nucleated, stable simulations are possible with .Δt ≈ 10−10 − 10−9 s. Finally, we illustrate the dislocation network evolution in a wire under torsion oriented for single slip and initially containing 50 sources each with a nucleation radius .ρ = 30nm, Fig. 4. The wire’s diameter is .d = 500 nm with aspect ratio .l/d = 3.5. We verify the early activation of sources located near the surface due to higher shear stresses, Fig. 4a. As the twist increases, the dislocation network evolves with dislocation loops enlarging and parts exiting the wire, Fig. 4b. At a 2.◦ twist, Fig. 4c, monopoles are notably trapped near the wire’s center, as expected. An analysis of size effects is underway.

Concluding Remarks A 3D discrete dislocation plasticity framework is under development, enabling dislocation dynamics in diverse domains for small deformations. This framework employs

832

A. Cruzado et al.

the MonoDis code as a basis for treating dislocation dynamics using monopoles, while the Z-set software employs finite elements to solve the image problem. Notable features include a single Cholesky decomposition of the global stiffness matrix, a consistent enforcement of boundary conditions, a virtual monopole technique for dislocation-free surface interactions, and an approximate nucleation model for efficient large-scale computations at a reasonable time step (.>0.1 ns). Acknowledgements AAB acknowledges support from NSF under grant CMMI-1950027. AC and AAB thank Vincent Chiaruttini and Jean-Didier Garaud from ONERA for assistance with the plugin interface of Z-set.

References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22.

Van der Giessen E, Needleman A (1995) Modell Simul Mater Sci Eng 3:689–735 Nicola L, Van der Giessen E, Needleman A (2003) J Appl Phys 93:5920–5928 Guruprasad PJ, Benzerga AA (2008) J Mech Phys Solids 56:132–156 Deshpande VS, Needleman A, Van der Giessen E (2001) Acta Mater 49:3189 Benzerga AA, Bréchet Y, Needleman A, Van der Giessen E (2004) Modell Simul Mater Sci Eng 12:159–196 Balint DS, Deshpande VS, Needleman A, Van der Giessen E (2008) Int J Plast 24:2149–2172 Keralavarma SM, Cagin T, Arsenlis A, Benzerga AA (2012) Phys Rev Lett 109:265504 Shishvan SS, McMeeking RM, Pollock TM, Deshpande VS (2017) Acta Mater 135:188–200 Gurrutxaga-Lerma B, Balint DS, Dini D, Sutton AP (2015) Proc R Soc A 471:20150433 Devincre B, Kubin L (1997) Mater Sci Eng 8(14):234–236 Zbib H, Rhee M, Hirth JP (1998) Int J Mech Sci 40:113–127 Ghoniem NM, Sun LZ (1999) Phys Rev B 60:128–140 Arsenlis A, Cai W, Tang M, Rhee M, Oppelstrup T, Hommes G, Pierce TG, Bulatov VV (2007) Modell Simul Mater Sci Eng 15(6):553–595 Weygand D, Friedman LH, Van der Giessen E, Needleman A (2002) Modell Simul Mater Sci Eng 10:437–468 Crone JC, Chung PW, Leiter KW, Knap J, Aubry S, Hommes G, Arsenlis A (2014) Modell Simul Mater Sci Eng 22(3):035014 Mar Vattré A, Devincre B, Feyel F, Gatti R, Groh S, Jamond O, Roos A (2014) J Mech Phys Solids 63:491–505 Ryu Ill, Gravell JD, Cai W, Nix WD, Gao H (2020) Extreme Mech Lett 40:100901 Deffo A, Ariza MP, Ortiz M (2019) J Mech Phys Solids 122:566–589 Ariza MP, Ortiz M (2021) Extreme Mech Lett 45:101267 Mura T (1982) Micromechanics of defects in solids. Martinus Nijhoff Publishers Z-set 9.1 package (2020) Non-linear material & structure analysis suite Cai W, Arsenlis A, Weinberger CR, Bulatov V (2006) J Mech Phys Solids 54(3):561–587

Capturing Hydrogen Embrittlement Effects with Hydrogen Diffusion Simulation and Crystal Plasticity Junyan He, Anupam Neogi, Deepankar Pal, Ali Najafi, and Grama Bhashyam

Abstract Hydrogen is a promising clean energy source, but its safe storage is challenging, as hydrogen has severe embrittling effects on metals. The extent of hydrogen embrittlement depends on the local hydrogen concentration and how it couples with the thermal and structural counterparts. This work presents a framework for hydrogen diffusion and embrittlement effects considering underlying microstructure. A hydrogen diffusion simulation is conducted on a microstructure with grain boundary trapping effect and trapping site saturation effect explicitly considered. The simulation provides a time history of hydrogen concentration in the microstructure. The grain boundary decohesion and softening effects of hydrogen are described phenomenologically by a nonuniform initial slip resistance degradation, which is computed based on the hydrogen concentration profile. This initial distribution is then used in crystal plasticity simulations to predict how the hydrogen exposure affects the mechanical properties such as initial yield stress and subsequent flow behavior. The results show that the diffusion model can capture the trapping effects of hydrogen as well as the gradual saturation of trapping sites with increased hydrogen concentration. The phenomenological model for hydrogen-based slip resistance degradation is able to capture the increased softening with longer hydrogen exposure times. The current framework provides a simple yet effective framework to connect microstructure-informed diffusion simulation with crystal plasticity to quantitatively study hydrogen embrittlement. Keywords Hydrogen embrittlement · Diffusion · Grain boundary trapping · Crystal plasticity

J. He (B) · A. Neogi · D. Pal · A. Najafi · G. Bhashyam Ansys Inc., Canonsburg, PA 15317, USA e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_72

833

834

J. He et al.

Introduction Hydrogen is a promising source of clean energy and has been used in fuel cells [1], hydrogen-powered engines [2], and rocket fuel [3]. However, it is well-known that hydrogen can significantly degrade fracture resistance and yield strength of metals [4, 5], rendering the engineering structures more prone to time-delayed fracture. These hydrogen embrittlement effects begin with the material’s absorption of hydrogen. The absorption process happens at external surfaces exposed to hydrogen sources such as water vapor, electrolytic solutions and gaseous environments [6], and is affected by plastic strain, residual stress and boundary conditions [7]. It is also understood that hydrogen diffusion in metals can be obstructed by various lattice defects and imperfections such as grain boundaries, precipitates and dislocations [8, 9]. These defects can bind to hydrogen atoms and reduce its mobility in diffusion, which is known as trapping. As such, the underlying microstructure of the metal plays a significant role in the hydrogen diffusion behavior. Therefore, a micro-scale diffusion model that explicitly accounts for the effects of the microstructure on the hydrogen diffusion process is warranted, whose development is the first objective of this work. Since hydrogen embrittlement leads to significant adverse effects on engineering structures, it is of practical importance to develop and implement theoretical and computational models to quantitatively predict the effect of hydrogen on mechanical properties. Since the various hydrogen embrittlement mechanisms, such as hydrogen enhanced decohesion and hydrogen enhanced localized plasticity, are closely related to the underlying microstructure, hydrogen embrittlement effects have been studied using crystal plasticity simulations [10–12]. These simulations couple the mechanical deformation process to the hydrogen diffusion process, accounting for the generation of dislocations during plastic loading and the trapping of hydrogen atoms at the grain boundaries and dislocations. These models provide important physics-based insights into how the microstructure affects hydrogen embrittlement and provides potential road maps to how to design a microstructure of the material for best hydrogen erosion resistance. Given the application values of these models, the second objective of our current work is to construct a simplified but efficient framework connecting microstructure-informed hydrogen diffusion model with crystal plasticity simulations via a phenomenological degradation model. As a proof of concept, we demonstrate the diffusion model on a synthetically generated microstructure and performs crystal plasticity simulations at different hydrogen exposure times to quantify the effect of hydrogen concentration profiles on the mechanical properties of the material.

Capturing Hydrogen Embrittlement Effects with Hydrogen …

835

Methods Hydrogen Diffusion and Grain Boundary Trapping In the absence of any grain boundaries, dislocations and defects, the transport of hydrogen within a pristine single crystal can be described by the classical Fick’s law of diffusion: .

∂C = D∇ 2 C, ∂t

(1)

where .C, .t and . D denotes the molar hydrogen concentration, time and diffusion constant, respectively. The main focus on the current work is to focus on the effect of grain boundary trapping in polycrystals. Therefore, an isotropic and uniform diffusion constant is assumed for all grains inside the microstructure. However, when hydrogen diffuse through realistic polycrystal microstructures, it interacts with interstitial lattice sites, vacancies, dislocations as well as grain boundaries, thus complicating the mass transport behavior. In this work, we focus on capturing the role of the grain boundaries in hydrogen transport, especially its role to act as potential trapping sites for hydrogen atoms [13]. McNabb and Foster [14] proposed a modification to the Fick’s law and a kinetics model to account for the trapping and release of hydrogen at the trapping sites: ∂θocc ∂C +N = D∇ 2 C, ∂t ∂t

(2)

∂θocc = Ck(1 − θocc ) − pθG B , ∂t

(3)

.

.

Where . N is the density of the trapping sites (in this work, grain boundaries), .θocc is the fraction of occupied trapping sites, .k is the kinetic constant for trapping and . p is the kinetic constant for escaping. These equations describe the trapping effect of the grain boundaries in a homogenized manner via scalar measures such as grain boundary density . N and fraction of occupied trapping sites .θocc . When the locations of grain boundaries are available in a microstructure representative volume element (RVE), we would like to leverage the location of the grain boundaries to capture a spatial distribution of hydrogen concentration and the grain boundary trapping effects instead of a simple homogenized measure. We also limit ourselves to the worst-case scenario where no hydrogen atoms can escape once trapped, thus we only capture the saturation of the trapping sites and set the escape kinetic constant . p = 0. For simplicity, we introduce .θuno = 1 − θocc as the fraction of unoccupied trapping sites. Substituting Eq. (3) (with . p = 0) into Eq. (2) and using the location of the grain boundary in place of its density . N , we have: .

∂C + IG B Ckθuno = D∇ 2 C, ∂t

(4)

836

J. He et al.

where . IG B is a grain boundary indicator function, . IG B = 1 for all material points on the grain boundaries, and equals to 0 otherwise. The evolution law for .θuno can be obtained from a simple change of variable: .

∂θuno = −Ckθuno . ∂t

(5)

This ordinary differential equation can be evolved from the initial condition .θuno = 1 at all grain boundaries (i.e., all grain boundaries are initially unoccupied trapping sites). Equations (4) and (5) lend themselves well to a finite-difference discretization since microstructures information are often expressed in rectangular pixels (in 2D) and voxels (in 3D). The two equations are solved sequentially in each time step. The implicit backward Euler scheme is used for time integration for stability. The diffusion and trapping equations are solved before and are not coupled with the structural problem, so the effect of hydrostatic pressure on hydrogen diffusion is ignored and the diffusion is assumed to occurred at a stress-free state.

Hydrogen Embrittlement and Crystal Plasticity The crystal plasticity (CP) model is used to model the mechanical deformation of a polycrystal RVE. A finite-deformation formulation is used, assuming a multiplicative decomposition of the total mechanical deformation gradient [15]: .

F=

∂u + I = Fe F p , ∂X

(6)

where . F e and . F p denote the elastic and plastic parts of the deformation gradient, respectively. Following Schmid’s law, the plastic velocity gradient . L p can be related to the slip rates on slip systems as [16]:

.

L p = F˙ p (F p )−1 =

Nss ∑

γ˙ α P α ,

(7)

α=1 .

Nss denotes the number of available slip systems. The slip rate .γ˙ is related to the activation energy .∆F and resolved shear stress .τ α as: γ˙ α = γ˙0 exp

.

{

) ]q } [ ( α |τ | − ga p −∆F sgn(1 + sgn(τ α )), 1− kB T g α − ga

(8)

Capturing Hydrogen Embrittlement Effects with Hydrogen …

837

where .γ˙0 is a reference slip rate, .k B is the Boltzmann constant, .T is the temperature, and.g α denotes the slip resistance of slip system.α.. p,.q and.ga are material parameters to be calibrated. During active plastic loading, the slip resistance evolve according to a hardening law: .g ˙ α = q αβ h β |γ˙ β |, (9) where .q αβ is a matrix relating the self- and latent-hardening of different slip systems [17] and.h β is the hardening modulus. The slip resistance evolves with an user-defined initial condition .g α (t = 0) = g0 (X), where .g0 (X) denotes a (potentially) spatially nonuniform field of initial slip resistance. A nonuniform distribution of .g0 (X) can be leveraged to capture grain boundary strengthening (Hall-Petch effect) in crystal plasticity [18, 19]. In this work, we leverage a nonuniform initial slip resistance to capture hydrogen embrittlement, especially hydrogen-induced softening. The hydrogen-induced softening is approximated by a reduction of the slip resistance of the material near the grain boundaries. The extend of weakening depends on the local hydrogen concentration. Solving Eqs. (4) and (5) yields an evolution history of the hydrogen concentration field .C. The amount of slip resistance and hardening modulus degradation due to hydrogen damage is assumed to be related to the maximum norm of the Laplacian of the concentration profile over time: ( ) 1 2 ∗ . g0 (X) = g0 − exp − (10) max |∇ C(X, t)| ∆gmax , L 0≤t≤tf where .g0∗ is the initial slip resistance without any hydrogen damage, .∆gmax is the maximum degradation and . L is a scaling factor.

Results Hydrogen Diffusion The diffusion problem is solved in a 2D square polycrystal domain with an edge length of 1 mm. The microstructure contains 35 grains, and is shown in the first column of Fig. 1. A .101 × 101 uniform grid is used to discretize the domain in the finite-difference method. The four edges of the domain are subject to a constant and mol uniform hydrogen concentration of 0.01 . mm 3 . The diffusion constant . D is taken to mm 2 be 0.01 . s and the trapping kinetic constant .k is taken to be 2000 . 1s . The system is evolved for 100s with a time step size of 0.5s. Contour plots of the hydrogen concentration .C and the fraction of unoccupied trapping sites (grain boundaries) at different time points are shown in Fig. 1.

838

J. He et al.

(a) Initial condition

(b) t=25s

(c) t=50s

(d) t=100s

Fig. 1 Simulated hydrogen diffusion process in a microstructure RVE. The first column shows the microstructure colored by grain ID, and the identified grain boundaries. In all other columns, the top row shows the hydrogen concentration .C and bottom row shows the fraction of unoccupied trapping sites .θuno

Crystal Plasticity Simulations Once the hydrogen diffusion simulation is completed, the hydrogen concentration at t=0s (before hydrogen exposure), 25s, 50s and 100s are extracted and a initial slip resistance field .g0 (X) is computed according to Eq. 10 for each time value and is used in a crystal plasticity simulation. The initial distributions at different hydrogen exposure times are shown in Fig. 2. We assumed a plane-strain condition in the thickness direction since the microstructure is 2D, and the microstructure RVE is loaded to 1% nominal strain along the Y direction in a duration of 1s. The material is 2024-T3 aluminium alloy, whose true stress–strain curve was provided in the work of Esmaeili et al. [20]. Its elastic behavior is assumed to be isotropic (characterized by Young’s modulus . E and Poisson ratio .ν). The material properties for the crystal plasticity model were calibrated to the experimental data and are listed in the Table 1.

(a) No hydrogen exposure

(b) t=25s

(c) t=50s

(d) t=100s

Fig. 2 Initial slip resistance distribution .g0 (X) at different hydrogen exposure levels

Capturing Hydrogen Embrittlement Effects with Hydrogen …

839

Table 1 Material properties used in the crystal plasticity simulation E [MPa]

.ν

.p

.q

.h β [MPa]

.γ˙0 [.s −1 ]

.∆F [J]

.g0∗ [MPa]

.∆gmax . L

70000

0.38

0.131

1.1

1750

1.732.×106

2.5.×10−19

220

150

[MPa] 0.0007

Fig. 3 Final von Mises stress distribution at different hydrogen exposure levels

Fig. 4 Final equivalent plastic strain distribution at different hydrogen exposure levels

The distributions of the von Mises stress at 1% nominal strain for different hydrogen exposure times are displayed in Fig. 3, and the equivalent plastic strain distributions in Fig. 4. The simulated stress–strain curves at different hydrogen exposure levels are compared in Fig. 5.

Discussion From the contour plots of the hydrogen concentration, we can clearly see the trapping effect of the grain boundaries on hydrogen diffusion. Diffusion is slower near the grain boundary and faster at the grain interior, a pattern that is obvious at t=25s when most of the grain boundary trapping sites remains occupied (hence not saturated). As hydrogen diffusion progresses, more and more grain boundaries (trapping sites) become saturated, as can be seen from the bottom row of Fig. 1. Once saturated, those grain boundaries no longer act as barrier to continued hydrogen diffusion. Therefore, the hydrogen concentration in those regions appear closer to that of a diffusion in an isotropic medium with no trapping (see last column of Fig. 1). In short, the model used in this research is able to capture the trapping effects of grain boundaries during

840

J. He et al.

Fig. 5 Comparison of stress–strain curves at different hydrogen exposure levels

hydrogen diffusion, and captures the gradual saturation of those trapping sites as the local hydrogen concentration increases. The degradation effects of hydrogen on the initial slip resistance is clearly visible in Fig. 2, we see that as hydrogen diffusion continues, more an more grain boundaries become eroded by the hydrogen content, and the decohesion and softening effects are phenomenologically represented by the reduced slip resistance near the hydrogenaffected grain boundaries. Hydrogen concentration significantly affects the stress contour in the microstructure RVE, as evidenced in Fig. 3. The hydrogen-induced weakening of the grain boundaries leads to lower stress levels near the affected grain boundaries. Meanwhile, new stress hot spots are created at grain interior. When inspecting the distribution of plastic strains, we observed noticeable concentration of plastic straining near the affected grain boundaries as a direct result of hydrogen erosion of the material. The effect of hydrogen on the overall stress–strain curve is seen in Fig. 5. The crystal plasticity simulations are able to predict more profound softening effects represented by decreased initial yield stress and subsequent flow stress as the hydrogen exposure time increases. However, since the current crystal plasticity material model is for plasticity only and does not include any damage effects, the effect on hydrogen on the fracture strain of the material is not captured. It is also worth noting that although some of the crystal plasticity parameters (with no hydrogen exposure) were calibrated with experimental data, the parameters related to hydrogen diffusion and the degradation of initial slip resistance with hydrogen concentration were randomly chosen in this work due to the lack of relevant experimental data. Further material calibration is needed to obtain physically-meaningful values for those parameters.

Capturing Hydrogen Embrittlement Effects with Hydrogen …

841

Conclusions This work introduces a sequential framework for connecting microstructureinformed hydrogen diffusion and crystal plasticity to quantitatively study hydrogen embrittlement on a microstructure RVE. First, a diffusion model is solved on the polycrystal using the finite-difference method, which explicitly considers the hydrogen trapping effect of the grain boundaries. The saturation of grain boundary trapping sites is also considered via an evolution equation for trapping site occupancy fraction. The simulated hydrogen concentration is then used to compute a spatially nonuniform distribution of initial slip resistance, which is adopted in this work as a simple phenomenological method to represent the grain boundary decohesion and softening effects in crystal plasticity simulations. A crystal plasticity simulation is then conducted to predict the initial yield stress and subsequent flow behavior of the RVE at different hydrogen exposure levels. The results show that the diffusion model can capture the trapping effect of the grain boundaries and the progressive saturation of trapping site is clearly visible in the simulation as well. With the initial slip resistance degradation computed from hydrogen concentrations, the crystal plasticity model is able to capture increased degradation of mechanical properties in terms of yield stress as the hydrogen exposure time increases, which is in qualitative agreement with experimental observations. These observation prove that the current framework is a simple yet effective approach to capture hydrogen softening effects on microstructure RVEs. Key limitations of the current work are: (1) some material properties related to hydrogen diffusion and slip resistance degradation were not calibrated to experimental data, thus preventing further quantitative validation of the current model; (2) the diffusion simulation is uncoupled from the crystal plasticity simulation, so the interaction of the two (e.g., the effect of pressure-induced hydrogen diffusion and hydrogen trapping at dislocations introduced by plastic deformation), are completely ignored in the current framework; (3) hydrogen diffusion is assumed to take place before any mechanical loading, and is assumed constant during mechanical loading; and (4) temperature effects on hydrogen diffusion are not accounted for. In future works, we aim to resolve those limitations by calibrating the material constants to experimental data, and to develop a fully-coupled diffusion-crystal plasticity model to capture the interactions.

References 1. Singla MK, Nijhawan P, Oberoi AS (2021) Hydrogen fuel and fuel cell technology for cleaner future: a review. Environ Sci Pollut Res 28:15607–15626 2. White C, Steeper R, Lutz A (2006) The hydrogen-fueled internal combustion engine: a technical review. Int J Hydrog Energy 31(10):1292–1305 3. Peschka W (2012) Liquid hydrogen: fuel of the future. Springer

842

J. He et al.

4. Vinogradov A, Ishida T, Kitagawa K, Kopylov V (2005) Effect of strain path on structure and mechanical behavior of ultra-fine grain Cu-Cr alloy produced by equal-channel angular pressing. Acta Mater 53(8):2181–2192 5. Depover T, Escobar DP, Wallaert E, Zermout Z, Verbeken K (2014) Effect of hydrogen charging on the mechanical properties of advanced high strength steels. Int J Hydrog Energy 39(9):4647– 4656 6. Fernández-Sousa R, Betegón C, Martínez-Pañeda E (2020) Analysis of the influence of microstructural traps on hydrogen assisted fatigue. Acta Mater 199:253–263 7. Drexler A, Bergmann C, Manke G, Kokotin V, Mraczek K, Pohl M, Ecker W (2021) On the local evaluation of the hydrogen susceptibility of cold-formed and heat treated advanced high strength steel (ahss) sheets. Mater Sci Eng A 800:140276 8. Song EJ, Suh D-W, Bhadeshia H (2013) Theory for hydrogen desorption in ferritic steel. Comput Mater Sci 79:36–44 9. Darken LS, Smith RP (1949) Behavior of hydrogen in steel during and after immersion in acid. Corrosion 5(1):1–16 10. Hassan Hu, Govind K, Hartmaier A (2019) Micromechanical modelling of coupled crystal plasticity and hydrogen diffusion. Philos Mag 99(1):92–115 11. Ogosi E, Siddiq A, Asim UB, Kartal ME (2020) Crystal plasticity based study to understand the interaction of hydrogen, defects and loading in austenitic stainless-steel single crystals. Int J Hydrog Energy 45(56):32632–32647 12. Yuan S, Zhu Y, Huang M, Liang S, Li Z (2020) Dislocation-density based crystal plasticity model with hydrogen-enhanced localized plasticity in polycrystalline face-centered cubic metals. Mech Mater 148:103472 13. Hurley C, Martin F, Marchetti L, Chêne J, Blanc C, Andrieu E (2016) Role of grain boundaries in the diffusion of hydrogen in nickel base alloy 600: study coupling thermal desorption mass spectroscopy with numerical simulation. Int J Hydrog Energy 41(38):17145–17153 14. McNabb A, Foster P (1963) A new analysis of diffusion of hydrogen in iron and ferritic steels. Trans Metall Soc AIME 227(3):618 15. Reina C, Conti S (2014) Kinematic description of crystal plasticity in the finite kinematic framework: a micromechanical understanding of f= fefp. J Mech Phys Solids 67:40–61 16. Clayton JD (2010) Nonlinear mechanics of crystals, vol 177 17. Bronkhorst CA, Kalidindi S, Anand L (1992) Polycrystalline plasticity and the evolution of crystallographic texture in fcc metals. Philos Trans R Soc Lond Ser A: Phys Eng Sci 341(1662):443–477 18. Herriott C, Li X, Kouraytem N, Tari V, Tan W, Anglin B, Rollett AD, Spear AD (2019) A multi-scale, multi-physics modeling framework to predict spatial variation of properties in additive-manufactured metals. Modell Simul Mater Sci Eng 27(2):025009 19. Zhang Y, He J (2023) Additive manufacturing material behavior prediction-a simulation based icme approach. In: AIAA SCITECH 2023 forum, p 2080 20. Esmaeili F, Zehsaz M, Chakherlou T, Barzegar S (2015) Fatigue life estimation of double lap simple bolted and hybrid (bolted/bonded) joints using several multiaxial fatigue criteria. Mater & Des 67:583–595

Inverse Problem Analysis of Phase Fraction Prediction in Aluminum Alloys Using Differentiable Deep Learning Models Yu Okano, Takeshi Kaneshita, Shimpei Takemoto, and Yoshishige Okuno

Abstract In recent years, there has been an increasing demand for the optimization of alloy properties, driven by the growing complexity of end products and the need to reduce development costs. In general, Thermo-Calc based on the CALPHAD method, which calculates the thermodynamic state of an alloy, is widely used for efficient alloy development. However, a challenge in alloy exploration using Thermo-Calc is the need for specialized computational skills and the significant computational effort required due to the extensive range of calculation conditions for numerous alloys. Consequently, we have developed a deep learning model that rapidly and accurately predicts the temperature-dependent changes in equilibrium phase fractions for 6000-series aluminum alloys (Al–Mg–Si-based alloys), which are widely used in industry, using calculations from Thermo-Calc. We developed the architecture of the deep learning model based on the Transformer, which is commonly used in natural language processing tasks. The model is capable of performing calculations more than 100 times faster than Thermo-Calc. Furthermore, by leveraging backpropagation of errors in the trained model, we developed a method to estimate the alloy composition for the phase fraction results calculated based on Thermo-Calc. Keywords Deep learning · Inverse problem · CALPHAD · Transformer

Introduction As products become increasingly complex and there is a growing demand for cost reduction in development, the need for optimizing the properties of alloys that make up these products is also escalating. For instance, aluminum alloys are garnering attention as essential metal materials for lightweighting final products. It is widely recognized that the various phases that form within these aluminum alloys have a direct correlation with their mechanical properties. Therefore, by utilizing phase Y. Okano · T. Kaneshita · S. Takemoto · Y. Okuno (B) Resonac Corporation, 8, Ebisu-Cho, Kanagawa-Ku, Yokohama 2210024, Japan e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_73

843

844

Y. Okano et al.

diagrams to calculate phase fractions and to identify the compositional and thermal ranges where these phases are stable, it becomes possible to optimally control the mechanical properties of the alloys. Currently, in the realm of alloy design through computational methods, Thermo-Calc [1], based on the CALPHAD (Calculation of Phase Diagrams, Computer Coupling of Phase Diagrams and Thermochemistry) approach, is widely utilized. In aluminum alloys, a forward problem approach is commonly adopted, where the alloy composition and manufacturing processes are controlled to optimize the metal’s microstructure, using CALPHAD methods for property optimization. On the other hand, from the perspective of efficient materials exploration, adopting an inverse problem approach can rapidly identify the alloy composition best suited for targeted properties, such as strength, heat resistance, and corrosion resistance. This has the potential to significantly accelerate the material development cycle. Therefore, we have developed a deep learning model based on the Transformer [2] architecture that can calculate phase fractions in the industrially prevalent 6000-series aluminum alloys at a much faster rate than the CALPHAD method. Additionally, utilizing the deep learning model we developed, we have also created an algorithm for inverse problem-solving that can estimate the composition of additive elements in an alloy when phase fractions calculated by the CALPHAD method are provided. This approach aims to significantly increase the efficiency of material exploration.

Formulation of Inverse Problems in Deep Learning Let θ denote the parameters of the deep learning model, the process by which the model outputs y from an input x can be formulated as shown in Eq. (1). In this context, training the model involves minimizing the loss function J (θ ), which corresponds to the average error between the predicted values ypred and the true values ytrue across the entire dataset, as defined in Eq. (2). The optimal model parameters θ ∗ are identified by minimizing J (θ ), as described in Eq. (3). The optimal parameters θ ∗ can be determined through iterative updates using gradient descent, as outlined in Eq. (4). The gradient of the loss function can be efficiently computed using the backpropagation algorithm. y = f θ (x) J (θ ) =

N  1   i i L ypred , ytrue N i=1

θ ∗ = arg min θ

N 1    i i  L f θ x , ytrue N i=1

(1)

(2)

(3)

Inverse Problem Analysis of Phase Fraction Prediction in Aluminum …

θ = θ − α∇θ J (θ )

845

(4)

In this paper, the inverse problem, given a trained model, is defined as follows: when a particular output y ∗ is provided, the objective is to find a specific input x ∗ that results in the model outputting y ∗ . This is formulated as Eq. (6), where the goal is to find. x ∗ that minimizes the loss function between the given y ∗ and f θ (x), as defined in Eq. (5). The value of x ∗ can be determined through iterative updates using gradient descent and backpropagation, in a manner similar to that described in Eq. (4), as outlined in Eq. (7). During the model training phase, the gradient of θ is calculated with respect to the loss function for the entire dataset, as described in Eq. (3) and outlined in Eq. (4). However, in solving the specific inverse problem of finding x ∗ , the gradient is calculated with respect to a loss function that depends on x as defined in Eq. (5). This represents a key difference between the two approaches. In the initial stages of iterative updates for x, the value of J (x) decreases as x is updated. However, as the updates continue, J (x) eventually converges to a specific value. If the converged value of J (x) is sufficiently small, then the model’s output f θ (x ∗ ) and y ∗ can be considered to be essentially identical, implying that the desired x ∗ has been successfully determined.   J (x) = L y ∗ , f θ (x)

(5)

  x ∗ = arg min L y ∗ , f θ (x)

(6)

x = x − α∇x J (x)

(7)

x

Training Data To calculate the phase fractions of 6000-series aluminum alloys based on the CALPHAD method, Thermo-Calc was used. When calculating phase fractions, we defined 11 phases consisting of Liquid (Al), Al, Al9 Fe2 Si2 , Al8 Fe2 Si2 , Al15 (Mn, Fe)3 Si2 , Mg2 (Si, Sn), (Al, Si)3 Ti(Lt), (Al, Si)11 Cr4 , DO23 –Al3 (Ti, Zr), Liquid (Solder), and Pb. Based on these phases, we generated a total of 841,689 training data points. In the Japanese Industrial Standards (JIS), which set the typical alloy standards in Japan, specific series are designated for the 6000 series of aluminum alloys. These include the 6010, 6013, 6060, 6061, 6063, 6066, 6070, 6101, 6181, and 6351 series. For each of these series, the upper and lower limits for the values of the alloying elements are specified, as shown in Table 1. The alloying elements include 12 types: Si, Fe, Cu, Mn, Mg, Cr, Zn, Ti, Zr, B, Bi, and Pb. To generate the training data, we first randomly selected alloys that meet the standard specifications. For each selected alloy, we randomly determined the composition of each alloying

846

Y. Okano et al.

Table 1 Upper and lower composition limits of JIS standard 6013 series aluminum alloy Elements Si

Fe

Cu

Mn

Mg

Cr

Zn

Ti

Zr

B

Bi

Pb

Al

Min

0.60 0.00 0.60 0.20 0.80 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Bal

Max

1.00 0.50 1.10 0.80 1.20 0.15 0.25 0.10 0.05 0.05 0.05 0.05 Bal

Fig. 1 Example of phase fraction calculation

element within the specified upper and lower limits. The composition of Al was set so that the sum of all alloying elements equaled 1. Using this set of 13 values to define the alloy composition, we then calculated the phase fractions using Thermo-Calc. Using this established set of 13 values to define the alloy composition, we calculated the phase fractions using Thermo-Calc. For 70 temperature points ranging from 100 to 790 °C in 10 °C increments, we used the phase fraction values from the 11 predefined phases as the training data. The reason for obtaining values at 10 °C intervals is to optimize memory usage and reduce computation time during inference with the trained model. Note that when visualizing the phase fractions as shown in Fig. 1, we display values at 1 °C intervals, which have been interpolated linearly.

Model Architecture The Transformer is a deep learning model that has been employed for various tasks, including natural language processing and image recognition [3], as illustrated in Fig. 2. We utilized the architecture of the Transformer to predict phase fractions from the alloy compositions of aluminum alloys. Modifications specific to phase fraction prediction were made solely to the Input Embeddings of both the Encoder and Decoder.

Inverse Problem Analysis of Phase Fraction Prediction in Aluminum …

847

Fig. 2 Transformer architecture

As shown in Table 1, the alloy composition consists of a set of 13 values. We directly fed this 13-value set into the Input Embedding of the Encoder. In the Encoder’s Input Embedding, a fully connected layer combined with an activation function was used to transform each of the 13 alloy composition values into a 1536dimensional embedding vector. The parameters of this fully connected layer are subjected to optimization during training. The Decoder is designed to output phase fractions; thus, it generates 11dimensional vectors for each of 70 temperature points, ranging from 100 to 790 °C in 10 °C increments. Each value in the 11-dimensional vector represents the phase fraction of one of the 11 pre-defined phases used in the phase fraction calculations, and the sum of phase fractions at each temperature point is constrained to be 1. In the Transformer architecture, it is necessary to maintain a consistent dimensionality for the embedding vectors between the Encoder and Decoder to perform Attention calculations. Therefore, in the Decoder’s Input Embedding, we employed a combination of a fully connected layer and an activation function to transform the 11-dimensional vector into a 1536-dimensional embedding vector. The parameters of this fully connected layer are subjected to learning, similar to those in the Encoder. The Transformer architecture involves multiple hyperparameters. In the model used for this study, the hyperparameters are as follows: • Number of Heads in Multi-Head Attention: 24. • Number of Encoder Stacks: 2. • Number of Decoder Stacks: 3.

848

Y. Okano et al.

Model Training In the context of phase fraction prediction, the range of phase fractions that are practically relevant extends from ~ 10−3 to 1. Consequently, to learn phase fractions accurately, it is essential to efficiently propagate the error gradient over this broad range. Additionally, the graph of the phase fractions exhibits complex behavior around 600 °C, the approximate melting point of aluminum alloys, due to phase transitions occurring in this temperature range. Therefore, when calculating the loss function, we divided the temperature range of interest into three segments: (a) the low-temperature region from 100 to 300 °C, (b) the high-temperature region from 490 to 700 °C, and (c) the full temperature range from 100 to 790 °C. For the loss function related to the phase fraction error, we employed three different types: (1) Mean Squared Logarithmic Error, (2) Cross-Entropy Loss, and (3) Mean Absolute Error. Additionally, to ensure the continuity of the predicted phase fractions with respect to temperature, we also included the Mean Absolute Error of the temperature-dependent differences in phase fractions as a fourth component of the loss function. Training was conducted by applying these four loss functions to each of the three temperature segments (a), (b), and (c).

Model Prediction Result Table 2 presents the loss values for 17,980 validation data points for the deep learning models. For comparison, the table includes prediction results from three types of deep learning models: Transformer, Seq2Seq [4], and a network composed solely of fully connected layers. In Fig. 3, we present the calculated results from Thermo-Calc alongside the predictive outcomes from deep learning models. We found that the Transformer model exhibited the highest prediction accuracy, providing forecasts nearly equivalent to the results obtained from Thermo-Calc. Based on the results from Table 3, we confirmed that when using a GPU, the Transformer model can calculate phase fractions more than 100 times faster than Thermo-Calc. Table 2 Comparison of loss on validation data

Model

Mean squared logarithmic error

Dense network

3.79 × 10−4

Seq2Seq

5.1 × 10−5

Transformer

2.45 × 10−5

Inverse Problem Analysis of Phase Fraction Prediction in Aluminum …

849

Fig. 3 Comparisons between CALPHAD method and model predictions

Table 3 Comparison of calculation time Model

Calculation time using GPU

Calculation time using CPU

CALPHAD

51 s

51 s

Transformer

0.49 s

4.0 s

Inverse Problem Result We validated whether it is possible to estimate x ∗ , corresponding to the alloy composition under computational conditions, from y ∗ , which corresponds to phase fractions calculated by Thermo-Calc, based on Eq. (7). However, as per Eq. (7), updating the alloy composition values could result in negative figures depending on the learning rate set. Therefore, a constraint was added to ensure that each component of the alloy composition is greater than or equal to 0 during the update. Additionally, constraints were imposed to ensure that the upper limit for each alloy composition also falls within the range specified for 6000-series alloys by the JIS standards. If these constraints were not applied during the value update step, the model’s input values would deviate from the range of the training data, resulting in decreased predictive accuracy and preventing the loss function from converging. Furthermore, due to the constraint that the sum of all alloy compositions must equal 1, the composition of Al was not updated using Eq. (7). Instead, after updating the values of the other alloying elements, it was set such that the sum of all alloying elements’ compositions equals 1.

850

Y. Okano et al.

Fig. 4 Comparison of phase fraction changes due to alloy composition updates

Table 4 Final alloy composition after update Elements

Si

Initial alloy 1.0 composition

Fe

Cu

Mn

Mg

Cr

Zn

Ti

0.5

1.1

0.8

1.2

0.1

0.25 0.1

Zr

B

Bi

Pb

Al

0.00 0.00 0.00 0.00 Bal

Final alloy 0.21 0.62 0.61 1.10 1.00 0.12 0.06 0.01 0.00 0.00 0.00 0.00 Bal composition Ground truth

0.20 0.63 0.66 1.17 0.81 0.26 0.36 0.18 0.00 0.00 0.00 0.00 Bal

Multiple initial values of x were selected within the compositional range of 6000series alloys according to JIS standards for the application of inverse problem analysis. It is desirable for the phase fractions corresponding to these initial values to resemble the shape of y ∗ . Among these initial values, the one yielding the lowest final loss function value was adopted. As illustrated in Fig. 4, we confirmed that an alloy composition capable of replicating the given phase fractions could be determined. Although the initial phase fractions differ significantly in shape from the target phase fractions, it was confirmed that they eventually converge to a shape largely identical to the target phase fractions. The initial and final alloy compositions corresponding to Fig. 4, along with their comparison to the Ground Truth (GT), are listed in Table 4. It is observed that the estimated values for the key elements are generally close to those of the GT.

Conclusion In this study, we explored methods for predicting phase fractions in aluminum alloys and solving inverse problems using deep learning models. By employing the Transformer architecture for prediction, we achieved comparable accuracy to the CALPHAD method while being ~ 100 times faster. Furthermore, by utilizing the model trained through inverse problem analysis, we were able to estimate the alloy composition conditions for the phase fraction results calculated based on the CALPHAD method.

Inverse Problem Analysis of Phase Fraction Prediction in Aluminum …

851

References 1. Sundman B, Jansson B, Andersson J-O (1985) The thermo-calc databank system. Calphad 9(2):153–190 2. Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser L, Polosukhin I (2017) Attention is all you need. In: Advances in neural information processing systems, pp 5998–6008. Author F, Author S, Author T (1999) Book title, 2nd ed. Publisher, Location 3. Dosovitskiy A, Beyer L, Kolesnikov A, Weissenborn D, Zhai X, Unterthiner T, Dehghani M, Minderer M, Heigold G, Gelly S, et al (2020) An image is worth 16x16 words: transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 4. Sutskever I, Vinyals O, Le QV (2014) Sequence to sequence learning with neural networks. Adv Neural Inform Process Syst 27:128

Part XXIII

Bio-Nano Interfaces and Engineering Applications

Molecular Insights into Mineral Nanoparticle Interactions with Proteins Vadim G. Kessler

Abstract Mineral nanoparticles (NPs) are recognized as important actors in biointeractions in soil and in living organisms. Their reactivity is often ascribed to their photo catalytical properties, but more specific enzyme-like activity in oxidation or hydrolysis of proteins, the “nanozyme” behavior is attracting an increasing attention. In the search for possibility to visualize NP interactions on molecular level, we develop approaches to isolation and characterization of protein and peptide complexes with smallest possible NP—the Poly-Oxo-Metalate (POM) species. Structural and theoretical investigation of POM complexes with peptide molecules has permitted to highlight the role of such factors as polarity of metal–oxygen bond, hydrophilicity and hydrophobicity of the peptide ligand, acidity of the medium and its salinity. Using single crystal models and 2D correlation NMR approaches has permitted to get insight into bigger nanoparticles interaction modes with larger proteins, in particular, with those essential for the SARS-CoV-2 virus metabolism. Keywords Mineral nanoparticles · NP-protein interaction · Poly-Oxo-Metalate (POM) · Molecular models · X-ray single crystal studies

Introduction Mineral nanoparticles (NPs) have been continuously produced through weathering of ground minerals both in the oceans and in the ground waters since the beginning of time. The mechanisms of these processes are well investigated, involving, in the first hand, the hydrolysis of silicates on action of acidity, provided by carbon dioxide and in situ generated sulfuric acid, and, in part by redox reactions on action of dissolved oxygen [1]. The life has emerged in the oceans and thus should be well accustomed and compatible with these NP, while the mechanisms of their chemical reactivity V. G. Kessler (B) Department of Molecular Sciences, BioCenter, Swedish University of Agricultural Sciences, Almas allé 5, Box 7015, 75007 Uppsala, Sweden e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_74

855

856

V. G. Kessler

can in fact be of important for the development of life itself. The redox reactivity of NP has been highlighted as the origin of their nanozyme action, crucial for in particular, plant stress resistance [2], while complexation with blood proteins has a strong beneficial effect in wound healing [3, 4]. In order to get insight into the molecular mechanisms of protein interactions with NP, an effort has been set on, in particular, the investigation of different spectroscopic characteristics of the so-called “protein corona” [5–7], as well as on modeling of the possible attachment mode with the help of means of theoretical chemistry [8]. The most insightful approach in revealing the molecular structure and interactions is of course the X-ray diffraction, but application of this approach has been impeded by not fully uniform size of NP and huge difference in X-ray reflectivity between the solid inorganic matter and the much less electron-rich amino acid or protein/peptide molecules. It has been observed that the particles essentially were forming the common dense packing motives, but how the molecules in question were attached to them remained an enigma [9]. In our studies, we proposed an innovative approach based on using the smallest “mineral” metal oxide NP—the Poly-Oxo-Metalate species (POMs). Their size is most often exceeding 1 nm, being in the range 1.03–1.05 for the Keggin POM that is spherical chemically individual species with the composition EM12 O40 , E = P, As, Sb, Si; M = Mo, W (V). POMs are charged, most often negatively and stable in more-or-less acidic medium, or, sometimes, positively, displaying then stability in basic medium (such as Al13 and Fe13 aggregates). The POM charge is generally high—up to about 1 atomic unit per nm2 , but is still representative for visualizing the nature of chemical bonding on the surface. In the present study, we proceeded varying key parameters for the NP-peptide bonding such as the polarity of the M–O bond, hydrophilicity/hydrophobicity of the peptide, the acidity and salinity of the medium. We have also imported the POMs as structural models for explaining the nature of NP interaction with some crucial virus proteins.

Role Metal–Oxygen Bond Polarity In the starting point of our studies, we compared complexation between the phosphomolybdic and phosphotungstic acid and a simple peptide bis-glycine, GlyGly. It turned out that if taken in POM: peptide = 1:3 ratio, corresponding to the formal charge balance, the structures of the resulting complexes, possessing exactly the same composition, are considerably different. The reason of the difference was apparently the nature of the interactions between the POM and the peptide, resulting from the difference in polarity of the metal–oxygen bonds. In case of [PMo12 O40 ]3− species, the dominating force was apparently the electrostatic interaction of the protonated peptide as cation with the POM anion displaying high and apparently uniform negative charge density. The hydrogen bonding was established mostly between the peptide molecules themselves or was complementing the charge interaction between the ammonium and NH+ fragments with POM. For the [PW12 O40 ]3− species, the charge interaction could also be traced but was strongly complemented by hydrogen

Molecular Insights into Mineral Nanoparticle Interactions with Proteins

857

Fig. 1 Building units and packing in the structures (on top) (HGlyGly)3 [PMo12 O40 ](H2 O)4 and (bottom) (HGlyGly)3 [PW12 O40 ](H2 O)4 . Reprinted with permission from [10]

bonding, due, supposedly, to higher polarity of the W–O, readily accepting interaction with the amide protons (see Fig. 1) [10]. The difference is especially visible in the packing: while for Mo-POM, we observe pairs of protonated peptides H-bound with each other, in that of the W-POM, the single protonated peptide cations are H-bound to the POM anions.

Effects of Thermal Pre-history of Solutions It turned out that while all crystallizations occurred at room temperature, the structure of the products was distinctly dependent on the thermal pre-history of the solutions. Intermediate heating was leading to a less dense structure incorporating more of the water molecules per structural unit. Composition of the resulting materials was (HGlyGly)3 [PMo12 O40 ](H2 O)10 and (HGlyGly)3 [PW12 O40 ](H2 O)6 , respectively (Fig. 2). In the packing, which gains higher symmetry, monoclinic instead of triclinic, we can clearly see the persistent trend for hydrogen bonding between peptide cations in the Mo-POM and more pronounced H-bonding to POM anions in the W-POM. The reason of gaining more water and higher symmetry is apparently that higher mobility

858

V. G. Kessler

Fig. 2 Structures of the (HGlyGly)3 [PMo12 O40 ](H2 O)10 (left) and (HGlyGly)3 [PW12 O40 ](H2 O)6 (right)

of the POMs in the intermediate heated up medium results in gaining a secondary solvation sphere that is then preserved on cooling and kept on transition into the solid crystal structure.

Role of Hydrophilicity/Hydrophobicity of Peptide Molecule or Protein Fragment In order to get inside into the effects of hydrophilicity/hydrophobicity on the POMpeptide interactions, we attempted the synthesis of both Mo-POM and W-POM complexes with oligopeptides of different lengths, such as GlyGlyGly and GlyGlyGlyGly. The general effect was that it was necessary to increase the acidity of the medium (lower pH to below 1.0 by addition of a strong acid) to achieve formation of the complexes, as the peptide was otherwise too poorly soluble. The structures generally turned to be more directed by hydrogen bonding, both for Mo-POM and W-POM, but the number of H-bonds per POM unit was distinctly higher for the W-POM, see Fig. 3 [11]. It is important to note that for the more hydrophobic GlyGlyGlyGly peptide, the composition of the complexes was quite different between the Mo-POM and the WPOM, (HGly4 )2 (H3 O)PMo12 O40 (H2 O)9 , and (HGly4 )1.33 (H3 O)1.67 PW12 O40 (H2 O), respectively. The Mo-POM complex was much more hydrated and less H-bound between the peptide and the POM, while the W-POM one has only minor amounts

Molecular Insights into Mineral Nanoparticle Interactions with Proteins

Fig. 3 Molecular structures of the (HGly4 )2 (H3 O)PMo12 O40 (H2 O)9 (HGly4 )1.33 (H3 O)1.67 PW12 O40 (H2 O) (right). Reprinted with permission from [11]

859

(left)

and

of crystal water and very strong H-bonding between the POM and the peptide. The latter was essentially “wrapped” around the POM with strong NH-POM hydrogen bond interactions [11].

Influence of Acidity and Salinity Conditions The entrance of NP into a body can proceed, either via the respiratory, or via the gastro-intestinal tract. For the latter both increased acidity and appreciable salinity are typical. We investigated therefore the effects of both these factors on the formation of the complexes between POMs and the GlyGly peptide. Our first experiment was focused on testing the effects of POM: peptide ratio in the view of high acidity of the POMs themselves being strong acids. For W-POM, the only product that could be isolated was the earlier described (HGlyGly)3 [PW12 O40 ](H2 O)4 complex. In case of Mo-POM, we observed at the ratios POM: peptide higher than 1.0, crystallization of a new phase of (HGlyGly)3 [PMo12 O40 ](H2 O)4 complex with the structure analogous to the W-POM one. It appeared then, quite logically, that increased acidity was promoting formation of the hydrogen bonds, permitting to build the phase analogous to the more H-bond-based W-POM one. Keeping POM: peptide ratio at 1: 3 and increasing acidity and content of Na+ (aq) and also higher charged cations resulted in formation of complexes with lower peptide content and with inclusion of the sodium cations into the structures. The latter were directing the structure formation as they formed fragments, where Na+ (aq) was solvated by the peptide species (see Figs. 4 and 5) [12]. It was possible to summarize the effects of both acidity and salinity in the form of a diagram, showing the observed correlations, see Fig. 6 [12].

860 Fig. 4 Molecular (a) and crystal (b) structures of the compound Na(HGlyGly)2 [PMo12 O40 ]·8H2 O

Fig. 5 Molecular (a) and crystal (b) structures of compound Na(HGlyGly)(H3 O)[PMo12 O40 ]·3H2 O

V. G. Kessler

Molecular Insights into Mineral Nanoparticle Interactions with Proteins

861

Fig. 6 Summary of the acidity and salinity effects on the composition and structure of POM-peptide complexes. Reprinted with permission from [12]

Modeling NP Interaction Using NMR Data and Crystallographic Insights from POM Studies The development of SARS-CoV-2 pandemic has ignited the interest in anti-viral activity of the NP. Having access to fully isotope labelled nsp1 protein, our research group investigated complexation between this molecule responsible for depressing immune response in the attacked cells and surface-capped TiO2 NP. It turned out that titania capped by chelating carboxylate lactate ligands was not forming any complexes with nsp1, while the TiO2 NP capped with easily desorbed triethanolammonium ligands was distinctly forming a complex with 1:1 = NP:nsp1 composition. This was indicated by well-visible shifts of several NMR signals corresponding to changes of bonding for distinct side chain groups in the nsp1 ordered α-helix fragment. In order to bring molecular understanding into the interaction process, we used the literature data on the structure of a Ti-POM, H6 [Ti42 (μ3 -O)60 (Oi Pr)42 (OH)12 ], replacing all iso-propoxide functions with OH ones [13]. The matching between the POM and nsp1 structure was carried out using Chimera program [14]. It proved that the curved anatase-like surface of the Ti-POM was binding to the protein via an inner-sphere carboxylate complex supported by several strong hydrogen bonds as displayed in the model presented in Fig. 7 [15]. Strong binding to viral proteins might be a contributing factor to the anti-viral activity of NP.

862

V. G. Kessler

Fig. 7 Model showing the docking of the metal–oxygen core of H6 [Ti42 (μ3 -O)60 (Oi Pr)42 (OH)12 )] with the structure of nsp1 taken from 7K7P [16]. The possible interactions are show in cyan: carboxylate of D48 with titanium, forming an inner sphere complex, and green: hydrogen bonding of OH-groups from the nanoparticle to E41, Q44, and H45. The amino acids of the other amides showing chemical shift perturbation are marked. Reprinted with permission from [15]

Conclusions The results of our studies demonstrate that the use of POM models can deliver important insights into the interaction between NP and proteins and highlight the effects of several crucial factors influencing this interaction such as polarity of the M– O bonds, hydrophilicity/hydrophobicity of the peptide fragment, acidity and salinity of the medium. Use of X-ray single crystal structure data provide also valuable starting points for interpretation of the data provided by the NMR spectroscopic studies of NP-protein complexes.

References 1. Hochella MF Jr, Lower SK, Maurice PA, Penn RL, Sahai N, Sparks DL, Twining BS (2008) Science 319:1631–1635 2. Wang H, Wan KW, Shi XH (2019) Adv Mater 31:1805368 3. Seisenbaeva GA, Fromell K, Vinogradov VV, Terekhov AN, Pakhomov AV, Nilsson B, Ekdahl K, Vinogradov VV, Kessler VG (2017) Sci Rep 7:15448 4. Svensson FG, Manivel VA, Seisenbaeva GA, Kessler VG, Nilsson B, Ekdahl KN, Fromell K (2021) Hemocompatibility of nanotitania-nanocellulose hybrid materials. Nanomaterials 11:1100

Molecular Insights into Mineral Nanoparticle Interactions with Proteins

863

5. Bashiri G, Padilla MS, Swingle KL, Shepherd SJ, Mitchell MJ, Wang K (2023) Lab Chip 23:1432–1466 6. Costa D, Savio L, Pradier CM (2016) J Phys Chem B 120:7039–7052 7. Joshi S, Ghosh I, Pokhrel S, Mädler L, Nau WM (2012) ACS Nano 6:5668–5679 8. Lee H (2021) Pharmaceutics 13:637 9. Kostiainen MA, Hiekkataipale P, Laiho A, Lemieux V, Seitsonen J, Ruokolainen J, Ceci P (2013) Nature Nanotechnol 8:52–56 10. Rominger KM, Nestor G, Eriksson JE, Seisenbaeva GA, Kessler VG (2019) Eur J Inorg Chem 4297–4305 11. Greijer B, De Donder T, Nestor G, Eriksson JE, Seisenbaeva GA, Kessler VG (2021) Eur J Inorg Chem 54–61 12. Greijer BH, Nestor G, Eriksson JE, Seisenbaeva GA, Kessler VG (2022) Dalton Trans 51:9511– 9521 13. Gao MY, Wang F, Gu ZG, Zhang DX, Zhang L, Zhang JJ (2016) Am Chem Soc 138:2556–2559 14. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE (2004) J Comput Chem 13:1605–1612 15. Agback P, Agback T, Dominguez F, Frolova E, Seisenbaeva GA, Kessler VG (2022) Nanoscale Adv 4:1527–1532 16. Clark LK, Green TJ, Petit CM (2021) J Virol 95:e02019

Quantifying Surface Topographies on Antimicrobial Copper Terry C. Lowe, Daniela P. Hirsch, Scott C. Dahl, Beatrice L. Lowe, Clinton L. Hawkins, Naveen S. Kailas, Máté Szucs, ˝ and Laszlo S. Toth

Abstract Specific angular topographies on metal surfaces can create non-uniform charge distributions that can disrupt biochemical processes and structures of nearby microbes. A new method has been developed to assess the density and asperity of topographical features designed to neutralize viral and bacterial pathogens. Coarse grain and ultrafine grain high-purity copper surfaces were chemically treated to impart microscale and nanoscale architectures. Images from Scanning Electron Microscopy and topographical data from Atomic Force Microscopy were analyzed using algorithms to quantify the electrostatic potential of the surfaces. We found that treated surfaces of coarse grain copper produced by conventional rolling and T. C. Lowe (B) · D. P. Hirsch · S. C. Dahl · B. L. Lowe · C. L. Hawkins Colorado School of Mines, Golden, CO 80401, USA e-mail: [email protected] D. P. Hirsch e-mail: [email protected] S. C. Dahl e-mail: [email protected] B. L. Lowe e-mail: [email protected] C. L. Hawkins e-mail: [email protected] T. C. Lowe · N. S. Kailas · M. Sz˝ucs · L. S. Toth LEM3 Laboratory and Laboratory of Excellence On Design of Alloy Metals for Low-Mass Structures, University of Lorraine, 57070 Metz, France e-mail: [email protected] M. Sz˝ucs e-mail: [email protected] L. S. Toth e-mail: [email protected] M. Sz˝ucs · L. S. Toth Institute of Physical Metallurgy, Metal-Forming and Nanotechnology, University of Miskolc, Miskolc 3515, Hungary © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_75

864

Quantifying Surface Topographies on Antimicrobial Copper

865

annealing and ultrafine-grained copper made using a new High Shear Deformation process, Friction-Assisted Lateral Extrusion Process both resulted in average asperity spacings smaller than the size of pathogens. However, the ultrafine grain copper had a Surface Asperity Charge Density that was 4.5 times greater than the coarse grain copper. Means to further enhance the computation of a quantitative measure of Surface Asperity Charge Density were identified. The analysis algorithms provide the basis for developing machine learning methods to optimize the antimicrobial effectiveness of copper surfaces. Keywords Copper · Ultrafine grains · Surface topography · Antimicrobial

Introduction Pathogen-induced diseases are currently mitigated by a wide range of methods, including the use of antibiotics, sanitization, and sterilization [1]. Nevertheless, data published by the Global Research on Antimicrobial Resistance (GRAM) Project in 2022 showed that one in eight deaths worldwide is still linked to bacterial infections [2]. One forefront in mitigating infection is the introduction of antimicrobial surfaces, often based on copper or silver, that are capable of contact killing [3]. The mechanisms through which metal-containing compounds deactivate microbes have been discussed in depth [4]. Proposed mechanisms by which copper neutralizes microorganisms are based on chemical effects such as the formation of radicals that disrupt or disorder biological structures such as DNA, messenger RNA, enzymes, proteins, hydrogen bonds, and membranes [5]. These mechanisms have been shown to be effective against a wide range of pathogens, but they operate on time scales of minutes [6] to hours [7]. Many natural and man-made surface topographies that have bactericidal effects have been identified and analyzed [8]. The mechanisms by which these surfaces impact microbes have been most thoroughly reviewed by Tripathy et al. [9]. Naturally occurring and artificially formed surface features include nanoneedles, hair spinules, nanograss, nanocones, nanocylinders, nanopillars, nanospikes, nanopores, nanorings, nanonuggets, and nanopatterned arrays. The proposed mechanisms by which these features influence the viability of pathogens include altering surface wettability, stretching of bacterial cell walls, altering microbe adhesion, and rupture through penetration of microbe membranes. Absent from these explanations is the consideration of the electrostatics of conductive solids. Yet to be addressed sufficiently are the electronic properties of metal/metal oxide systems and the roles of surface features with very small radii that can stimulate charge transfer to disrupt proteins, membranes, and nucleic acids in microbes. This work considers a novel approach to neutralize pathogens in seconds to a few minutes by adding specific surface topographies to copper that can deactivate microbes by rapid charge transfer. Our central hypothesis is that small radii surface features will create non-uniform charge distributions. This hypothesis is supported

866

T. C. Lowe et al.

by the work of Bhattacharya, who developed a relation for the charge density on a conducting cone-shaped asperity with a cone half-angle α [10]. He proposed that the charge density σ at the tip of the cone depends on the geometric angularity as: [ ( ( α ))[−1 σ ∝ R · Sin(α) · ln Tan 2

(1)

From Eq. 1, the degree of charge amplification for a cone angle 2α is significant, for example, ranging from a factor of 1.6–21.1 for cone angles of 90°–1°, respectively. Thus, spike-like features will exhibit multi-fold increases in charge concentration. Even for cone angles of 90°, there is a 60% higher charge than a planar surface. Bhattacharya applied the theory to additional conducting surface shapes, including ellipsoids and hyperboloids of two sheets, both of which possess multiple radii of curvature. Additional characteristics of conductive substrate material influence charge transfer. The substrate must possess specific electronic structures with a high electron density near the Fermi level, high electron transmission probability, and exhibit a topography-dependent work function to impart antimicrobial effects. The full theoretical basis for designing such surfaces will be presented in a separate manuscript. The theme underlying this work is to establish a method to quantify the density and angularity of nanoscale asperities on conductive surfaces. We first created nanoscale channels, ridges, and asperities on pure copper with two different grain sizes to achieve different densities and types of asperities. Then, we measured and analyzed the profiles of these two types of surfaces and implemented numerical algorithms to compute a Surface Asperity Charge Density (SACD) to provide a single parameter to represent the areal degree of charge amplification, which in later work we will correlate with measurements of antimicrobial efficacy. Each of these steps is described in the next section.

Materials and Methods Experimental Preparation of Two Copper Surfaces Nominally pure copper with two distinctly different starting microstructures was prepared for surface modification and subsequent quantitative topographical analyses. Sheets of annealed C110 99.90% copper 0.127 mm thick were obtained from McMaster-Carr (product code 8944K25) and sectioned into 10 mm × 10 mm samples that we will designate herein as coarse grained (CG). Comparable samples with 10 mm × 10 mm areas were produced via a new High Shear Deformation (HSD) process called Friction-Assisted Lateral Extrusion Processing (FALEP) that creates ultrafine-grained (UFG) microstructures. FALEP induces large amounts of shear in metals and alloys in a single operation to reduce the grain size to produce submicron

Quantifying Surface Topographies on Antimicrobial Copper

867

grains. The UFG samples were fabricated from rectangular 20 mm × 20 mm OFHC 99.95% copper bar from Goodfellow (product code CS00-BR-000120). Details of the experimental setup for FALEP have been published by Vu et al. [11]. In our experiments, FALEP was applied to 20 mm × 20 mm × 20 mm cubes of copper. The cubes were confined in an entry channel under a normal load of 120 kN to press the copper at room temperature through the FALEP tooling. Concurrently, a driving load of 130 kN was applied to the plunger to translate it in the orthogonal channel to induce shear within the workpiece to produce a 2.23 mm thick outgoing strip. The planar surfaces of 10 mm × 10 mm CG and UFG samples were cleaned by immersion in 50 mL acetic acid agitated at 60 rpm for 90 s on a digital orbital shaker (ONiLAB, Model 2 kg). After air drying, the samples were immersed in a proprietary hydrochloric acid-based solution and agitated for 130 s at 60 rpm to modify the surface topography. After the surface treatment, the samples were rinsed in an isopropanol bath on the orbital shaker for 90 s, also agitated at 60 rpm. After rinsing, the samples were dried in an ambient pressure recirculating air dehydrator (Colzer, 800W) for 120 s.

Characterization of Copper Substrate Microstructures and Topography The average grain size and other microstructural characteristics of the CG and UFG copper were determined by backscatter electron imaging using a JEOL JSM7000F Field Emission Scanning Electron Microscope (JEOL, Tokyo) with an EDAX HikariPro Electron Backscatter Detector (Ametek EDAX, Berwyn, PA, USA). Samples were prepared for Scanning Electron Microscopy by electropolishing using an electrolyte of two parts phosphoric acid to one part deionized water. A DC voltage of 1.5 V with a corresponding current of 0.25 amps was applied for 20 min using a copper cathode and an Adjustable DC Switching Variable Voltage Power Supply (Flycow, USA). Additional polishing for EBSD-quality surfaces was performed for 3 h using a Buehler Vibromet 2 (Buehler, Lake Bluff, IL, USA) with a 20 nm colloidal suspension of SiO2 . The surfaces of samples were imaged using a Tescan S8252G Scanning Electron Microscope (Brno, Czech Republic), a Helios NanoLab600i Scanning Electron Microscope (ThermoFisher Scientific, Waltham, MA, USA), and an Oxford Instruments (Abingdon, Oxfordshire, England) Asylum MFP-3D Atomic Force Microscope (AFM). AFM scans were collected over square surface regions ranging from 1 μm × 1 μm to 80 μm × 80 μm to quantify the surface topographies. The AFM scans were conducted using an aluminum-coated silicon TAP300AL-G tip (Ted Pella, Redding, CA, USA) with a tip radius less than 10 nm and operated at 300 kHz resonant frequency with a force constant of 40 N/m. The in-plane sampling resolution used in the AFM scans was as small as 4 nm, with a height resolution of 0.020 nm

868

T. C. Lowe et al.

in all measurements. In this work, we report topographical data only from the AFM for scan areas of 20 μm × 20 μm.

Numerical Analysis Methods The numerical analyses developed here were designed anticipating the long-term goal of developing learning models able to adaptively analyze surfaces with widely varying topographies. At this initial stage of algorithm development, we focused on two objectives: to quantify the density of peaks and the angularity of these peaks. We deliberatively neglected the characteristics of surface minima, even though we expect a significant influence of concave surface topographies on charge uniformity. Topographical data from the AFM were exported into a Jupyter Notebook (Python3) code environment for analysis. Height data from AFM output files were parsed along 20 equidistant scan lines out of the 256 AFM scan lines in each image data set. Maxima along each scan line were indexed, and the corresponding peaks were transferred into arrays to identify peaks for geometric analyses. For each maximum, cone angles were computed by sampling the lateral and height coordinates of symmetric pairs of measured positions, up to +5 and −5 sampling distances away from the maxima. Note that AFM scans were performed with in-plane sampling distances between 3.9 nm and 313.7 nm, varying with the scan area. For this work, we report results only for 20 μm scans, which had a sampling spacing of 78.3 nm. For each asperity, the peak angle, height, width, and spacing were computed. For each of the 20 scan lines, the average peak angle and the minimum peak angle corresponding to the sharpest peak were computed. Considering that the size range of most pathogens is between 0.5 and 8 μm, a suitable measure to quantify the density of asperities is the number of asperities per micrometer. When the spacing of asperities is less than 0.5 μm, the probability of any pathogenic bacterium near the surface of the substrate having proximity to an asperity is essentially 100%. The peak angle near each maxima determines the degree of local charge amplification that will affect the electron transfer kinetics. Angles smaller than 110° provide greater than 50% amplification compared to nearby planar regions. For each of the 20 scan lines, the average and minimum peak angles were computed. Then, the average peak angle characteristic of the entire surface and the average minimum over the 20 scan lines were computed. When these two metrics are equal in magnitude, the degree of variability across the sampled region is negligible. In contrast, when the average minimum peak angle is significantly smaller than the overall average peak angle, one expects some degree of heterogeneity in the surface angularity and, therefore, in the uniformity of the prospective charge transfer.

Quantifying Surface Topographies on Antimicrobial Copper

869

Results and Discussion Scanning electron micrographs from electropolished surfaces of the CG and UFG copper prior to surface treatment are shown in Fig. 1. The average grain sizes for the CG and UFG copper were 6.77 and 0.28 μm, respectively. The CG copper grain structure is typical of annealed copper; grains are largely equiaxed, and many exhibit annealing twins. Because of the higher energy of some of the twin boundaries in the CG copper, one expects interaction of the annealing twins with the chemical surface treatment. In contrast, the UFG copper made by FALEP provides grains with 24-fold smaller average grain size with mostly submicron size grains with virtually no twins. Figure 2 compares the angular features of the treated CG and UFG surfaces. For the CG surface, shown in Fig. 2a, the chemical treatment reveals intragranular crystallographic features with submicron spacings. Angular ridges appear at the intersection of facets of crystallographic planes on a size scale finer than the grain size. It is likely that higher energy microstructural defects, such as twinned regions, provided sites for the chemical etching to expose these intragranular crystallographic features. The presence of annealing twins effectively increases the density of planar surfaces. Block-like surface steps with intraplanar angles near 90° appear in Fig. 2a. We expect higher energy crystallographic planes such as the {210} and {310} planes to etch more readily. These planes both form 90° angles with {100} cube planes and with each other. Smaller interplanar angles should also form, with 36° 52' , 53° 8' , 66° 25' , and 78° 0' angles between the highest energy {210} planes. Similarly, 25° 51' , 36° 52' , 53° 8' , 72° 3' , and 84° 16' angles may exist between the second highest energy {310} planes. Surface planes with obtuse angles are also possible and appear in the micrograph.

Fig. 1 EBSD unique grain maps of a CG copper at 1000× magnification and b UFG copper at 20,000× magnification

870

T. C. Lowe et al.

Fig. 2 SEM images of a CG and b UFG copper after surface treatment to form surface asperities

The etched UFG surface shown in Fig. 2b exhibits angular features but with some significant differences from the CG surface. The facets created by the etching have a more flake-like appearance, suggesting the presence of more acute interplanar angles. Feather-like ridges extend to varying degrees from the substrate, exhibiting evidence of partial etching along the length of the ridges. One expects some degree of spatial variation in the chemical etching response in the UFG copper because of the high density of intragrain dislocations with non-uniform distributions. Three-dimensional surface height maps obtained from CG and UFG samples are shown in Fig. 3. Note that the areas imaged by SEM and AFM do not correspond to each other. The height variation across the 20 μm × 20 μm scan areas was on the order of a few micrometers, as is typical for industrially machined or rolled surfaces. Neither the rolled and annealed sheet from which the CG samples were produced nor the FALEP samples was polished or otherwise modified prior to surface treatment. Figure 3 shows asperities and ridges of various size scales present on both surfaces. These features were analyzed from line profiles extracted from the AFM data and imported into the Jupyter computing environment. The AFM scans measured a 256 × 256 array of heights to provide 65,536 data points. For visual simplicity, only five equally spaced profiles of the 256 scan lines are shown in Fig. 4. Round symbols denote the maxima. Statistics on the heights of the peaks, their spacing, and angularity for each surface are presented in Table 1. Note that the scale of the height axis is larger than the in-plane dimensional scale in Figs. 3 and 4 so that peaks appear more pronounced. However, the numerical algorithms that compute surface angularity are not influenced by this factor. The first surface parameter of interest is the spacing between asperities. The density of maxima varied widely between the various samples, with ranges of 0.52 ± 0.06–5.86 ± 1.96 per μm for CG substrates and 1.18 ± 0.23–3.07 ± 1.57 per μm for the UFG surfaces. The more significant degree of variation in the density of surface peaks for the CG copper can be attributed to the wide range of grain sizes, including many grains larger than 10 μm, as seen in Fig. 1a. For example, a large asperity-free region can be seen on the CG sample surface on the left edge of Fig. 2a. The AFM measurements suggest that the measured peaks are surrounded

Quantifying Surface Topographies on Antimicrobial Copper

871

Fig. 3 About 20 μm × 20 μm AFM scan surface height profiles of a CG and b UFG copper after surface treatment

(a)

(b)

Fig. 4 Height profiles for five of 256 AFM scan lines. Solid circular symbols identify the maxima for a CG and b UFG copper Table 1 Summary of topological parameters for treated copper surfaces Topological parameter

CG copper

UFG copper

Average number maxima per μm, ±SD

1.32 ± 0.27 #/μm

1.18 ± 0.23 #/μm

Average local height of asperities, ±SD

52.2 nm ± 13.7 nm 83.8 nm ± 15.0 nm

Average angle at maxima, ±SD

153.3° ± 4.5°

154.4° ± 6.1°

Average minimum angle per scan line, ±SD

126.1° + −12.7°

100.9° ± 15.5°

Percent of AFM scan lines with peak angles 0.999) between ln[1/(1 − x)]·t −1 and x·t −1 . Additionally, it was found that both the self-impeding coefficient and reaction ratio constant increased as the particle size decreased. Notably, particles smaller than 61 µm exhibited the highest reaction ratio constant and lowest selfimpeding coefficient, reaching values of 0.0022 and 0.9894, respectively. According to previous studies [17, 18], the small particle size of BOF slag results in a larger surface area, which provides more contact areas with CO2 and facilitates the carbonation process and leads to higher CO2 sequestration and f-CaO consumption. However, compared to other alkaline constituents in BOF slag, the content of f-CaO was relatively low, approximately 5% by mass in this study. Therefore, the differences in particle size had limited influence on it.

The Kinetic Study of Carbonation Process In this study, the carbonation kinetics of BOF slag were investigated using the shrinking core model, which has been previously validated for the carbonation process of BOF slag [19]. If the rate-limiting step is determined by the diffusion

The Kinetic Study of Carbonation of BOF Slag at High Temperature …

949

Fig. 3 Relationship between ln[1/(1 − x)]·t −1 and x·t −1 for various particle sizes in the CO2 sequestration process

Table 1 Detailed information of fitting results Particle size (µm) Reaction ratio constant Self-impeding coefficient Correlation coefficient i

xi x j (



ivj (xi − x j )v )

(6)

v

Pt = xa Pa + xβ Pβ + PI I I Fs

(7)

where Pi0 represents the relevant property for group element i. xi is the molar fraction of component i. ivj is the interaction coefficient between components i and j. Pa is the relevant property of the α phase. PIII is the property associated with the material’s topology structure. F s is the dispersity of the material. According to Fig. 4, nitrogen content divides the solidification paths into two types: L → L + α → L + α + γ and L → L + γ → L + γ + α. At a nitrogen content of 0.703 wt%, the alloy’s liquidus temperature is 1415.67 °C, and the ferrite phase begins to precipitate rapidly. The austenite phase forms at a temperature of 1409.58 °C. When the solidus temperature is 1375.0 °C, the content of the austenite phase and σ phase reaches its maximum. In Fig. 4b–d, as the nitrogen content increases, there is minimal change in the liquidus and solidus temperatures of the powder. When the nitrogen content exceeds 0.832 wt%, the initiation temperature of austenite precipitation increases, and the precipitation rate also rises. However, the amount of ferrite phase precipitation becomes significantly reduced. Therefore, adjustments in nitrogen content lead to variations in the sequence and quantity of phase formations, which will enhance the material’s performance.

Analysis of TTT and CCT Curves To identify the sensitive temperature range and incubation period for the precipitated phase, it is necessary to calculate the minimum cooling rate. The isothermal transformation curve (TTT) and continuous cooling transformation curve (CCT) during the phase transition process are depicted in Figs. 5 and 6.

Thermodynamic Calculations of Precipitate Phases …

959

Fig. 4 Solidification paths for different nitrogen contents. a 0.703 wt%, b 0.836wt%, c 0.932 wt%, d 1.010 wt%

Fig. 5 The variation pattern of TTT curves. a TTT curve for 0.703 wt% nitrogen content, b M2 (C, N) phases in different nitrogen contents

960

D. Wang et al.

Fig. 6 The variation pattern of CCT curves. a 0.703 wt%, b 0.836 wt%, c 0.932 wt%, d 1.010 wt%

Figure 5a illustrates the TTT curve of high-nitrogen stainless steel melt with a nitrogen content of 0.703 wt%. The curve exhibits an overall "C" shape, with nose temperatures of the σ phase, CHI phase, LAVES phase, and M2 (C, N) phase being 700, 740, 760, and 900 °C, respectively. The starting transition temperatures are 750, 790, 800, and 960 °C, with the shortest incubation time observed for the M2 (C, N) phase at 803.05 s. In Fig. 5b, as the nitrogen content increases, the TTT curve for the M2 (C, N) phase shifts towards the upper left, indicating shorter transformation times and faster cooling rates. Combined with the analysis in Fig. 1, undergoing phase transformation at lower temperatures can reduce the formation of harmful LAVES and σ phases, ultimately optimizing the material’s properties. Figure 6 presents CCT curves of the high-nitrogen stainless steel melt, reflecting the relationship between phases, temperature, and time during the continuous cooling transformation process. As the nitrogen content increases from 0.703 wt% to 1.010 wt%, based on the calculations, critical cooling rates for the M2 (C, N) phase are calculated to be 0.39, 0.67, 0.88, and 1.07 °C/s, respectively. This implies that during solution treatment of the alloy, the supersaturated solid solution will decompose when the cooling rate falls below this critical rate. Therefore, if the cooling rates is higher than this critical rate for cooling media, it is beneficial to obtain a supersaturated solid solution and facilitate the precipitation of second phase particles.

Thermodynamic Calculations of Precipitate Phases …

961

Impact of Nitrogen Content on Pitting Corrosion Resistance Pitting is a type of corrosion that can result in the deterioration of stainless steel. It is often quantified using the pitting resistance equivalent number (PREN), with higher PREN values indicating superior pitting corrosion resistance, and PREN primarily depends on the lower values [15]. As reflected in Fig. 1, alterations in temperature can cause variations in the proportions of austenite and ferrite phases, subsequently affecting the PREN value. Selecting formula (8) to calculate the PREN: P R E N = Cr + 3.3%Mo + 30%N − 1%Mn

(8)

From formula (8), the PREN value is primarily governed by the concentrations of Cr, Mo, N, and Mn. Within the temperature range of 1260–1420 °C, as depicted in Fig. 7a, the content of Cr and Mo in the ferrite phase decreases, while Mn content rises and then decreases. The levels of N, C, and O remain constant. Consequently, the PREN value of the ferrite phase decreases, with a trend similar to Cr. In Fig. 7b, spanning from 600 °C to 1400 °C, the austenite phase exhibits a noticeable increase in Cr, Mo, and nitrogen content, along with a decreasing trend in Mn content. C and O content remain unchanged. Since the sensitivity coefficient of Mn to the PREN value is lower than that of N, the PREN value continues to increase. As presented in Fig. 8, for a nitrogen content of 0.703 wt%, within the range of 1280–1410 °C, the pitting corrosion resistance is determined by the ferrite phase with a lower PREN value. When the nitrogen content increases to 0.836 wt%, the temperature range associated with the ferrite phase’s PREN value narrows down to 1360–1400 °C. Within the nitrogen content range of 0.932 wt% to 1.010 wt%, the pitting corrosion resistance of high-nitrogen stainless steel becomes contingent on the PREN value of the austenite phase.

Fig. 7 Ferrite and austenite variation curves for N content of 0.703 wt%

962

D. Wang et al.

Fig. 8 Variation curves of PREN values with temperature at different nitrogen contents. a 0.703 wt%, b 0.836 wt%, c 0.932 wt%, d 1.010 wt%

Influence of Nitrogen Content on the Linear Expansion Coefficient To better control the dimensions of stainless steel in different temperatures, the coefficient of the linear expansion-temperature curve is depicted in Fig. 9. If the material has a small linear expansion coefficient, it will reduce the strain in the temperature gradient, reduce the modulus of elasticity, and reduce the stresses generated by thermal strains, resulting in good heat resistance of the material. Since the nitrogen element occupies a large space in the lattice, and increased nitrogen loosens the lattice structure. Simultaneously, the thermal motion of atoms increases the distance between them, which will lead to a change in the linear expansion coefficient. As depicted in (a)–(f), under heat treatment conditions from 25 °C to 1420 °C, the material with a nitrogen content of 1.010 wt% exhibits the lowest linear expansion coefficient. In (g)–(h), when the temperature range is 420–1500 °C, the material with a nitrogen content of 0.703 wt% demonstrates the lowest coefficient of linear expansion.

Fig. 9 Curve of linear expansion coefficient-temperature

Thermodynamic Calculations of Precipitate Phases … 963

964

D. Wang et al.

Considering the application range of high-nitrogen stainless steel is mainly focused on room temperature to moderate temperatures, which can add a higher N content of Fe-17.11Cr-11.1Mn-2.91Mo-1.010N powder for sintering molding.

Influence of Nitrogen Content on the Linear Expansion Coefficient Grain size of high-nitrogen stainless steel powders has an important effect on material properties. Grain boundaries as interfaces of adjacent grains can enhance the material’s resistance to plastic deformation. The relationship between tensile strength, yield strength, hardness of high-nitrogen stainless steel, and grain size can be described by Hall–Petch formula: σ y = σ0 + kden λ−0.5

(9)

where σ 0 is the resistance to intragranular deformation, k den is the extent of the grain boundary’s influence on strength. λ is the grain size. As illustrated in Fig. 10, because of the refining effect for grain structure, smaller grain sizes have larger adjacent grain boundary areas, which hinder plastic deformation. Meanwhile, with the grain size increasing, the strength and hardness of the material decreased in different nitrogen contents. When the grain size is 1 μm, with the nitrogen content increasing, the yield strength, tensile strength, and hardness of the material are increased. This is mainly because nitrogen atoms and iron atoms form a solid solution, which can produce a strengthening effect in the lattice and impede dislocation movement, increasing the material’s strength. Additionally, nitrogen introduction will alter the lattice parameter and affect crystal structure, leading to an enhancement in the material’s hardness. Taking all factors into account, selecting FeCr17 Mn11 Mo3 Nx powder with a nitrogen content of 1.010 wt% is helpful in optimizing the material’s performance.

Conclusions (1) When nitrogen content increases from 0.703 wt% to 1.010 wt%, the M2 (C, N) phase precipitation will increase from 6.09 wt% to 8.82 wt%. (2) The cooling rate should exceed the critical cooling rate for the absence of M2 (C, N) phase precipitation, which is beneficial for obtaining supersaturated solid solutions. Furthermore, the precipitation of secondary phase particles can be promoted.

Thermodynamic Calculations of Precipitate Phases …

965

Fig. 10 Effect of grain size on strength and hardness. a 0.703 wt%, b 0.836 wt%, c 0.932 wt%, d 1.010 wt%

(3) When the nitrogen content ranges from 0.703 wt% to 0.836 wt%, pitting corrosion resistance depends on the PREN value of ferrite. Otherwise, the pitting resistance depends on the PREN value of austenite. (4) Based on the analysis of linear expansion coefficient, strength, and hardness, selecting FeCr17 Mn11 Mo3 Nx powder with a nitrogen content of 1.010 wt% is more conducive for optimizing material performance. Acknowledgements The authors are grateful for the support from the National Natural Science Foundation of China (No. 52304351), Natural Science Foundation of Hebei Province, China (No. E2022209136 and No. E2021209146), Science and Technology Project of Hebei Education Department, China (No. BJK2023073), Tangshan Science and Technology Plan Project (No. 22130202G).

966

D. Wang et al.

References 1. Li S, Zhang C, Lu J et al (2021) A review of progress on high nitrogen austenitic stainless-steel research. J Mater Express 11(12):1901–1925 2. Talha M, Behera CK, Sinha OP (2013) A review on nickel-free nitrogen containing austenitic stainless steels for biomedical applications. J Mat Sci Eng R, C 33(7):3563–3575 3. Cheng B, Wei F, Teh W, et al (2022) Ambient pressure fabrication of Ni-free high nitrogen austenitic stainless steel using laser powder bed fusion method. J Addit Manuf 55 4. Sumita M, Hanawa T, Teoh SH (2004) Development of nitrogen-containing nickel-free austenitic stainless steels for metallic biomaterials—review. J Mat Sci Eng C-Mater 24(6– 8):753–760 5. Amuth S, Sasidhar KN, Meka SR (2021) High nitrogen alloying of AISI 316 L stainless steel powder by nitriding. J Powder Technol 390(693) 6. Liu Y, Wang MQ, Liu GQ (2014) Effect of hydrogen on ductility of high strength 3Ni-Cr-Mo-V steels. Mat Sci Eng 594:40–47 7. Liu T, Cui Y, Zheng K, et al (2023) Synergistic effect of grain size and second-phase particle on the oxidation behaviour of a high-manganese austenitic heat-resistant steel. Corros Sc. 215 8. Wang H, Li Y, Detemple E et al (2020) Revealing the two-step nucleation and growth mechanism of vanadium carbonitrides in microalloyed steels. J Scripta Mate. 187:350–354 9. Aminorroaya S (2020) Influence of microalloying elements (Ti, Nb) and nitrogen concentrations on precipitation of pipeline steels—a thermodynamic approach. J Eng. https://doi.org/10. 1002/eng2.12337 10. Liu JT, Zhang YA, Li XW et al (2014) Thermodynamic calculation of high zinc-containing Al-Zn-Mg-Cu alloy. J T Nonferr Metal Soc 24(5):1481–1487 11. Zhu S, Shittu J, Perron A, et al (2023) Probing phase stability in CrMoNbV using cluster expansion method, CALPHAD calculations and experiments. J Acta Mater 255 12. Liu Y, Jiang DM, Li WJ (2016) Composition optimization of Al-Zn-Mg-Cu alloy via thermodynamic calculation. J J Optoelectron Adv M 18:868–872 13. Liu Z, Fan CL, Yang CL et al (2023) Investigation of the weldability of dissimilar joint between high nitrogen steel and low alloy steel by comparing filler metals. J Mater Today Commun 2023:35 14. Okugawa M, Izumikawa D, Koizumi Y (2020) Simulations of non-equilibrium and equilibrium segregation in nickel-based superalloy using modified Scheil–Gulliver and phase-field methods. J Mater Trans (11) 15. Yang C, Feng H, Chen X et al (2023) Enhanced pitting corrosion resistance of CoCrFeMnNi high entropy alloy in the presence of Desulfovibrio vulgaris via nitrogen doping. J J Mater Sci Technol 139:92–102

Part XXVIII

Defects and Interfaces: Modeling and Experiments

3D Discrete Dislocation Dynamics Simulations of Multiple Spiral Dislocation Sources Luo Li and Tariq Khraishi

Abstract A spiral dislocation source is a dislocation with one end fixed on the slip plane, while the other end of the spiral dislocation source is at a grain boundary or a free surface. In the current study, 3D dislocation discrete dynamics (DDD) simulations, which is a simulation method that can emulate the collective motion of dislocations and predict the constitutive behavior of a crystalline material, is used to simulate, and capture the interaction between the spiral dislocation sources. The simulation results show that the flow stress in the computational domain is dependent of the number of spiral sources. Another important simulation result from the current study is that an edge FR source can be produced from two screw spiral dislocations that are moving in the same direction on the same slip plane. Keywords DDD simulations · Spiral dislocation · Multipoles

Introduction Dislocations, extra half planes or shifted half planes in the crystal, are 1D or line defects that exist in the crystalline materials. Usually, the formation of dislocations is due to the environmental effects and manufacturing processes. Besides, dislocations can be generated from dislocation sources during plastic deformation under loading. Traditional Frank-Read (FR) sources and spiral dislocation sources are the two main dislocation sources in a crystal. Unlike the FR source which has two ends pinned on the slip plane, only one end of the spiral dislocation source is fixed, and its other end is at a free surface or a grain boundary [1, 2], as Fig. 1 shows. L. Li · T. Khraishi (B) Department of Mechanical Engineering, University of New Mexico, Albuquerque, NM 87131, USA e-mail: [email protected] L. Li e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_83

969

970

L. Li and T. Khraishi

Fig. 1 a Initial configuration of the spiral dislocation source; b Initial configuration of the FR dislocation source. The pinned point of the dislocation is shown with a dot or sphere. Here, the xy-plane is the slip plane which contains both the dislocation and the Burgers vector

Early on, configuration of the spiral dislocation source was captured utilizing 3D X-ray projection topographs, by Authier et al. and G’sell and associates [3, 4]. Later, more and more research regarding spiral dislocations were carried out by researchers. Plastic behavior of single-crystal micropillars caused by the operation of spiral dislocation sources was investigated by Tang et al. [5]. Maia and Bakke studied the behavior of a 2D harmonic oscillator in an elastic material with an edge spiral dislocation [6]. Moreover, dislocation dynamics was employed to emulate the size/scale effects of the thin films on the strength of the material using spiral dislocation sources [7]. In a recent study, Li et al. investigated the size/scale effect on the operation of a spiral dislocation source using DDD simulations [8]. Discrete dislocation dynamics (DD) is a numerical simulation methodology that can mimic the plastic behavior of crystalline materials and predicts the constitutive behavior of the material based on its loading and micro-constituents. In the current study, 3D DDD, which can emulate long-/short-range interactions and cross slip in crystals after the innovation by Zbib and associates [9, 10], is used to investigate the operation of multiple spiral dislocations and the interaction between them.

Method In DDD simulations, curved dislocation lines are discretized into linked straight dislocation segments. To obtain the self-stress of the curved dislocation lines, selfstresses of the dislocation segments are summed up. The stress field of a dislocation segment, which is the main term for calculating the Peach-Koehler (PK) force felt at any point on a dislocation, has been developed by other researchers [2, 11], and the equation for the PK force at a point (say the midpoint of a segment), which can

3D Discrete Dislocation Dynamics Simulations of Multiple Spiral …

971

capture the mutual interaction of discrete straight dislocation segments is presented as follows [9]:   F i = σ i total · bi × ξ i + F i f orwar d + F i backwar d

(1)

where “×” represents the cross product, “·” stands for multiplication, bi is the Burgers vector, ξ i is the line sense, F i f orwar d and F i backwar d are self-forces from immediate neighboring dislocation segments. (Note that vectors are represented by bolded parameters in this paper). σ i total is the total stress felt by the center of the dislocation segment, which includes the sum of the stresses from dislocation segments except for the two immediate neighboring segments, the external applied stress, and the stress from other sources (particles, surface effects, etc.). Knowing the PK and with material properties (e.g. stiffness, the dislocation mobility, etc.), velocities of dislocation segments, the plastic strain rate, and the stress increment on the computational domain/box can be calculated given an externally applied strain rate. Equations for these parameters have been presented in detail in other research work [9, 10] and hence are not elaborated here for brevity.

Results and Discussion Simulations for the Spiral Dislocation Source and the Traditional FR Source For the simulation of the spiral dislocation, a simulation box (S1 × S2 × S3 = 60,000b × 60,000b × 40,000b) is centered on the coordinate origin as Fig. 1a shows. The spiral dislocation source is sitting along the x-axis with one end fixed at the coordinate-system origin, while the other end of the spiral dislocation is at the free surface (30,000b, 0, 0), which means that the length of the spiral dislocation source is 30,000b (where b is the magnitude of the Burgers vector, which is equal to 0.286 [nm], and the direction of the Burgers vector is (0, 1, 0)). Other simulation parameters are chosen as follows: The shear modulus (G) and Poisson’s ratio (υ) are 26.32 [GPa] and 0.33, respectively. The dislocation mobility is 10,000 [(Pa •s)−1 ]. The minimum segment length is 300b. The minimum time step is 10–12 [s]. The applied strain rate ε˙ yz is 10 [s−1 ]. Under the effect of the applied load, the spiral dislocation source bows and generates dislocation glide on the slip plane, as presented in Fig. 2. Authors also compare the simulation data of a spiral dislocation source with one for a traditional FR source. For the simulation of the FR source, the FR source is placed along the x-axis. Two ends of the FR source are fixed at the nodal points (−15,000b, 0, 0) and (15,000b, 0, 0), which means that the length of the spiral dislocation source is also 30,000b. Other simulation parameters are the same as the ones for the spiral dislocation. It can be seen in Fig. 3 that the stress–strain curve for

972

L. Li and T. Khraishi

Fig. 2 Multiplication of a single edge spiral source (different color lines represent the single spiral source at different time steps)

Fig. 3 Simulation results for the traditional edge FR source and the edge spiral dislocation source (source lengths of these two dislocation sources are the same: 30,000b)

the spiral dislocation (red) and the one for the traditional FR source are basically on top of each other. One expects the flow stress (a measure of material strength) obtained from the simulation of the spiral dislocation source would be lower compared to the FR source, as one end of the spiral dislocation is free, i.e. has more degrees of freedom. However, the surfaces of the simulation box also constrain the operation of the spiral dislocation, meaning the spiral cannot move as easily as one expects. Therefore, the similar simulation results for these two sources imply that the surfaces of the simulation box play a similar role in constraining the dislocation operation as the fixed or pinned points, at least under the conditions simulated herein.

3D Discrete Dislocation Dynamics Simulations of Multiple Spiral …

973

Simulations for a Pair of Co-Planer Spiral Dislocations In this subsection, interaction of two spiral dislocations gliding on the same slip plane has been investigated. The two spiral dislocations are placed on the slip plane, the xy-plane in our simulation box. For the first spiral dislocation, one end is fixed at the nodal point (−5000b, 0, 0) and the other end is free at the free surface (−5000b, 30,000b, 0). For the second spiral dislocation, the nodal coordinate of the free end is at (5000b, −30,000b, 0) and the fixed point is at (5000b, 0, 0). The rest of the simulation parameters are the same as the ones mentioned in section Simulations for the Spiral Dislocation Source and the Traditional FR Source. Note that the Burgers vector direction (0, 1, 0) of these two spiral dislocations is the same. The line sense directions of the spiral dislocations, which are parallel to the Burgers vector direction, are the same. Hence, these two spiral dislocations are screw dislocations of the same sign, and they move in the same direction when they are subjected to an external stress (see Fig. 4a–b). Then at one point, two spiral sources annihilate each other at a point which has two edge dislocations of opposite signs and form a traditional edge FR source after that. Under the effect of the external applied load, the operation of the FR source continues (see Fig. 4c–d). In Fig. 5, one compares the stress–strain curve for the screw spiral dipole to the one of the edge FR source (recall two screw spiral dislocations with the same Burgers vector and line sense can form an edge FR source). For the simulation of the edge FR source, the dislocation is pinned at nodal points (−5000b, 0, 0) and (5000b, 0, 0) and other simulation parameters remain unchanged. According to Fig. 5, the stress– strain curve for the screw spiral dipole reaches a steady or stable state of plasticity generation slower than the edge FR source. Before the spiral dipole reaches the steady state, it takes time for these two dislocations to annihilate and form the edge FR source, and then the newly formed FR source can continuously generate plasticity afterwards. For the initially-single FR source, it can generate continuous plastic flow in the simulation domain once it passes the semicircular equilibrium state, i.e. once it transitions into an instability with fast dislocation generation ensuing in terms of dislocation looping. Hence, the transient states of these two scenarios are not the same as their dynamics are different. But their steady states or the flow stress values are the same as their dynamics or their continuous plasticity generation is the same after the initial transient stage. So, one can see that the steady stable states of the stress–strain curves in Fig. 5 overlap.

DDD Simulations for Multiple Spiral Dislocation Sources To investigate the plastic behavior of multiple spiral dislocation sources, simulations of a multipole composed of edge spiral dislocation sources are performed here. As can be seen in Fig. 6, spiral dislocation sources are sitting on parallel slip planes (xy-plane or parallel to it) with a separation of Lz along the z-axis between any

974

L. Li and T. Khraishi

Fig. 4 a Initial configuration of two screw spiral dislocations; b operation of the spiral dislocations subjected to the external load; c formation of an edge FR source; d edge FR source operation/ looping

spiral source and its neighbors. For the tripole, the two nodal coordinates for the top, center, and bottom dislocation sources are (0, 0, Lz) and (30,000b, 0, Lz), (0, 0, 0) and (30,000b, 0, 0), (0, 0, −Lz) and (30,000b, 0, −Lz), respectively. Other simulation parameters are the same as the ones mentioned in section Simulations for the Spiral Dislocation Source and the Traditional FR Source. As shown in Fig. 7, the three spiral dislocations form a continuous fan-shaped action after the critical bow from the initial configuration. This continuous fan-shaped action contributes to continuous plastic flow and plasticity generation. With more spiral dislocation sources, the fan-shaped action is more continuous as the spiral sources tend to help each other, or push each other, into sustaining the plastic flow; meaning with the same amount of applied load, more plasticity is generated in the

3D Discrete Dislocation Dynamics Simulations of Multiple Spiral …

975

Fig. 5 Stress–strain curves for single edge FR source and screw spiral dislocation dipole

Fig. 6 Initial configuration of edge spiral dislocation sources (tripole), each separated by Lz distance

simulation cell, which indicates a lower flow stress needed in the simulation domain to sustain this plastic flow. As Fig. 8 shows, the flow stress in the simulation domain decreases with increasing number of spiral dislocation sources. In this subsection, the authors also investigate the effect of the separation Lz on the plasticity generation by varying Lz and examining the effect on the flow stress. Simulation results for different values of Lz are presented in Fig. 8. As can be seen, there is no significant difference in the data curves (flow stress versus number of spiral dislocation sources), which implies that the plasticity generation in the simulation domain is independent of the studied separation distances between the spiral sources. A similar study for traditional FR sources forming multipoles was done by Siddique et al. [12]. In their work, it shows that the separation between the traditional FR sources can affect the operation of the sources. As presented in their paper, the FR sources keep trying to attract each other back to the equilibrium state if they are

976

L. Li and T. Khraishi

Fig. 7 Operation of initially-edge spiral dislocation sources—a tripole (spiral sources separated along the z-axis are represented by different color lines to distinguish them)

Fig. 8 Stress–strain curves for multipoles of spiral dislocations with different separation distance Lz between sources along the z-axis

placed too close to each other along the z-axis, and this continuous attraction hinders plasticity flow. Also, the FR sources are fixed at both ends, meaning they have less degrees of freedom to get rid of this attraction, and they cannot form the fan-shaped action like the case of multipole spiral dislocation sources; i.e., they cannot separate like the spirals and end-up forming dynamic dipoles during the applied straining process. For the scenario of multiple spiral sources here, these sources have more freedom to move and separate, and the continuous fan-shaped action can help the sources maintain the plasticity generation. Hence, the plasticity generation for the spiral dislocation sources is independent of the separation distance between them.

3D Discrete Dislocation Dynamics Simulations of Multiple Spiral …

977

Conclusion In the current study, 3D DDD simulations are carried out to investigate multiple spiral dislocations. From the simulations for a pair of co-planer spiral dislocations, it is observed that two screw spiral dislocations that are moving in the same direction on the same slip plane can form an edge FR source. For the simulations for multipoles of spiral dislocations with a separation of Lz along the z-axis, a lower flow stress is obtained in the simulation domain as the number of spiral dislocation sources increases. With more spiral dislocation sources, the fan-shaped action is more continuous as the spiral sources tend to help each other, or push each other, into sustaining the plastic flow; meaning with the same amount of applied load, more plasticity is generated in the simulation cell, which indicates a lower flow stress needed in the simulation domain to sustain this plastic flow. Also, spiral dislocation sources have more freedom to move and separate compared to the FR sources, and the continuous fan-shaped action can help the sources maintain the plasticity generation. Hence, the plasticity generation for the spiral dislocation sources is independent of the separation distance between them.

References 1. Hull D, Bacon DJ (2011) Introduction to dislocations, 5th edn. New York, NY, USA, Butterworth-Heinemann 2. Hirth JP, Lothe J (1982) Theory of dislocations, 2nd edn. Malabar, FL, USA, Krieger 3. Authier A, Lang AR (1964) Three-dimensional X-ray topographic studies of internal dislocation sources in silicon. J Appl Phys 35:1956–4959. https://doi.org/10.1063/1.1713778 4. G’sell C, Champier G (1976) X-ray topographic examination of loops and spiral dislocations in cadmium single crystals. Philos Mag: J Theor Exp Appl Phys 34:733–751. https://doi.org/ 10.1080/14786437608222046 5. Tang H, Schwarz W, Espinosa HD (2008) Dislocation-source shutdown and the plastic behavior of single crystal micropillars. Phys Rev Lett 100:185503. https://doi.org/10.1103/PhysRevLett. 100.185503 6. Maia AVDM, Bakke K (2018) Harmonic oscillator in an elastic medium with a spiral dislocation. Phys B Condens Matter 531:213–215. https://doi.org/10.1016/j.physb.2017.12.045 7. Zhou C, LeSar R (2012) Dislocation dynamics simulations of plasticity in polycrystalline thin films. Int J Plast 30–31:185–201. https://doi.org/10.1016/j.ijplas.2011.10.001 8. Li L, Khraishi TA (2023) An investigation of spiral dislocation sources using Discrete Dislocation Dynamics (DDD) simulations. Metals 13:1408. https://doi.org/10.3390/met130 81408 9. Zbib HM, Rubia TD (2002) A multiscale model of plasticity. Int J Plast 18:1133–1163 10. Rhee M, Zbib HM, Hirth JP, Huang H, de la Rubia T (1998) Models for long-/short-range interactions and cross slip in 3D dislocation simulation of BCC single crystals. Model Simul Mater Sci Eng 6:467–492 11. Devincre B (1995) Three dimensional stress field expressions for straight dislocation segments. Solid State Commun 93:875–878 12. Siddique AB, Lim H, Khraishi TA (2022) The effect of multipoles on the elasto-plastic properties of a crystal: theory and three-dimensional dislocation dynamics modeling. J Eng Mater Technol 144:011016. https://doi.org/10.1115/1.4052168

Atomistic Simulation of Hydrogen-Defect Interactions in Palladium Nanoparticles Across Multiple Time Scales Xingsheng Sun and Youyun Xu

Abstract This paper aims to explore solute-defect interactions in nanosized palladium-hydrogen (Pd-H) systems across multiple time scales through two atomistic methods. The first method, namely Diffusive Molecular Dynamics (DMD), is capable of capturing the mass transport of H atoms and the dynamics of soluteinduced lattice defects over a long diffusive time scale. The second one, Molecular Dynamics (MD), aims to provide more detailed information into instantaneous atomic movements and hopping over the time scale of thermal vibrations. These two methods are connected by initializing MD simulations with statistical measures of microscopic variables that are obtained from DMD at different H/Pd ratios. Our simulation results show that DMD is able to capture the motion of an atomistically sharp hydride phase boundary as well as the initialization and dynamics of soluteinduced lattice defects, i.e., misfit dislocations and stacking faults. While the H-rich phase leads to an increase in the vibrational standard deviation of Pd and H atoms, the existence of stacking faults locally reduces it. Furthermore, the MD simulation results match well with DMD ones in terms of the equilibrium potential energy, the preservation of hydride phase boundary, and the spatial distribution of stacking faults. Keywords Solute-defect interactions · Palladium hydrides · Atomistic simulations · Multiple time scales · Diffusive molecular dynamics · Molecular dynamics

Introduction Palladium hydride (.PdHx ) has served as a prototypical system for the study of soluteinduced phase transformations and solute-defect interactions in both fundamental and applied research fields for several decades [1, 2]. Pd and its nanomaterials are X. Sun (B) · Y. Xu Department of Mechanical and Aerospace Engineering, University of Kentucky, Lexington, KY 40506, USA e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_84

978

Atomistic Simulation of Hydrogen-Defect Interactions …

979

particularly noteworthy due to their exceptional ability to absorb a significant amount of hydrogen at readily achievable temperatures and pressures, with hydrogen atoms exhibiting high mobility within the Pd lattice. The phase diagram of .PdHx reveals a dilute .α phase (.x < 0.015 at room temperature) and a concentrated .β phase (.x > 0.6 at room temperature). While the face-centered cubic (FCC) structure is maintained by the Pd lattice in both phases, the .α to .β phase transformation is accompanied by a .4% increase in the lattice constant, potentially leading to the formation of lattice defects such as misfit dislocations and stacking faults. The dynamics of H atoms in nanostructured Pd have been extensively studied using experimental methods. For instance, under gas-phase conditions, the hydrogenation of Pd nanoparticles involves three steps [3]: (1) the dissociation of H2 into H atoms on the surface of the Pd nanoparticles (i.e., adsorption), (2) the saturation of H atoms into a subsurface layer, and (3) the diffusion of H atoms into the interior, occupying the octahedral interstitial sites of the FCC lattice and forming an H-rich .β phase (i.e., absorption). A few recent experiments have suggested that in individual nanosized particles, the absorption is characterized by the propagation of a hydride phase boundary with a thickness of several atomic layers [1, 2, 4, 5]. Due to the ratelimiting nature of subsurface saturation [6], the speed of phase boundary movement can be as low as .1 nm/s, resulting in long time scales for the completion of the hydrogenation process. As a result, the convergence of atomistic length scales and long time scales presents a significant challenge for modeling and simulation. In this work, we employ a recently developed computational method, referred to as Diffusive Molecular Dynamics (DMD), to investigate the intricate dynamics of hydride phase transformation in Pd nanoparticles. DMD represents a novel approach for simulating long-term diffusive mass transport and heat transfer while maintaining atomic-level resolution [7–11]. We synergistically combine Diffusive Molecular Dynamics (DMD) with classical Molecular Dynamics (MD) to investigate interactions between H solutes and lattice defects in Pd nanoparticles, achieving atomic resolution across multiple time scales. The broad time window of DMD allows us to effectively study hydride phase transformation and the evolution of solute-induced lattice defects over diffusive time scales. On the other hand, classical MD provides more detailed insights into atomic movements and lattice relaxation on the timescale of thermal vibrations. The remainder of this paper is structured as follows. Section “Methodology” presents a concise overview of the theory, model equations, and setup for both DMD and MD simulations. Subsequently, in section “Results and Discussions”, we discuss the results of our numerical experiments, encompassing the motion of the hydride phase boundary, the dynamics of H-induced stacking faults, and the comparisons between MD and DMD simulations. Finally, in section “Concluding Remarks”, we provide a summary of our findings.

980

X. Sun and Y. Xu

Methodology Diffusive Molecular Dynamics We focus our attention on a three-dimensional Pd-H system which comprises two types of sites, i.e., host and interstitial sites. Each host lattice site is always occupied by a Pd atom, whereas each interstitial site can be either occupied by an H atom or vacant. We denote the sets of host and interstitial sites by . IPd and . IH , respectively. The number of host and interstitial sites are denoted by . NPd and . NH , respectively, i.e., . NPd = |IPd | and . NH = |IH |. At each interstitial site .i ∈ IH , we define an occupancy function .n i as [12] { n =

. i

1 if the site i is occupied by an H atom, 0 if the site i is vacant.

(1)

By contrast, the occupancy of the host sites is always .1, i.e., .n i = 1, i ∈ IPd . It follows from the definition Eq. (1) that the occupancy array .{n} takes values in a set consisting of the elements of .{0, 1}. We refer to this set as .O, defined by N .O = {0, 1} H . We denote the instantaneous position and momentum of the site .i by .q i and . pi , respectively. When viewed on time scales much longer than that of atomic vibrations, these microscopic state variables can be regarded as random variables ( that have )a joint probability distribution characterized by density function.ρ {q}, { p}, {n} , where.{q} = {q i : i ∈ IPd ∪ IH },.{ p} = { pi : i ∈ IPd ∪ IH } and .{n} = {n i : i ∈ IH } [12]. Then we can define the expectation or macroscopic value ( ) of any quantity . A {q}, { p}, {n} via the widely used phase average in the classical statistical mechanics [7] =

∑

.

{n}∈O

( ) ( ) || A {q}, { p}, {n} ρ {q}, { p}, {n}

1 h 3(NPd +NH )

dq i d pi ,

(2)

i∈IPd ∪IH

where .h is the Planck’s constant. Following the Gaussian density clouds of atomic positions [9], we further assume that .q i and . pi of each host and interstitial sites are characterized by the normal distribution, whereas .n i of each interstitial site follows Bernoulli distribution. Then the probability density function .ρ can be shown as [10]

.ρ =

1

( exp

−

∑ i∈IPd ∪IH

(

) ∑ ) 1 xi 2+ 2 + ¯ ¯ , |q − q | | p − p | n log i i i i 2kB Ti m i i 1 − xi 2σ 2 1

i

i∈IH

(3) with the partition function

.

√ || ( σi kB Ti m i )3 || 1 , = h 1 − xi i∈I ∪I i∈I Pd

H

H

(4)

Atomistic Simulation of Hydrogen-Defect Interactions …

981

where .kB is the Boltzmann constant and .h is the reduced Planck’s constant. .m i and T are the atomic mass and absolute local temperature, respectively. .q¯ i , .σi , . p¯ i , and . x i are parameters characterizing the probability density function. Moreover, one can derive that √ .q¯ i and .σi are the mean and standard deviation (SD) of .q i , respectively. ¯ i and . kB Ti m i are the mean and SD of . pi , respectively. .xi , referred to as atomic .p faction, is the mean of .n i . The statistics of microscopic variables can be determined using mean field approximation for the free energy of the system. After straightforward deviations according to Ref. [10], we have . p¯ i = 0, and .q¯ i and .σi can be solved by minimizing the variational Gaussian Helmholtz energy . i

( ( ) ) h2 h2 3 ∑ 3 ∑ log kB Ti log − 1 + k T + x − 2 B i i 2 2 kB Ti m i σi2 kB Ti m i σi2 i∈IPd i∈IH ∑ ( ) kB Ti xi log xi + (1 − xi ) log (1 − xi ) , +

min F = +

¯ {q},{σ } .

i∈IH

(5) ) where .V {q}, {n} represents the interatomic potential energy. In this work, we assume that the heat transfer is much faster than the mass transport. As a result, the temperature .Ti , becomes uniform over all the sites and is equal to a constant value .T . Then we can formulate the exchange chemical potential at one interstitial site .i by differentiating Eq. (5) with respect to .xi , i.e., (

μi =

.

∂F 3 xi ∂ = kB T + kB T log + , i ∈ IH . ∂ xi 2 1 − xi ∂ xi

(6)

In this work, a linear discrete kinetic law is employed to govern slow mass transport at the atomistic length scale. At any time step, it enforces the balance of mass at each interstitial site, i.e., x˙ =

. i

∑ B0 xi + x j (μ j − μi ), i, j ∈ IH , T 2 j/=i

(7)

where . B0 denotes the bondwise diffusion coefficient, and it can be calibrated to fit some experimental measures such as the speed of diffusion. We simulate the absorption of H by a spherical Pd nanoparticle at the room temperature (i.e., .T = 300 K). The nanosphere, with a diameter of .20 nm, consists of .261, 563 host sites and .261, 742 octahedral interstitial sites. The host lattice sites are fully occupied by Pd atoms, so the atomic fraction is always.1 throughout simulations. The interstitial sites are either occupied by H atoms or vacant, so the atomic faction varies within the range.(0, 1). Following previous studies [10, 12, 13], we assume that the interstitial sites located within an outermost layer of the particle have already been in equilibrium with the surrounding H environment. The thickness of this layer is set to .0.5 nm, based on the value provided by an equilibrium Monte Carlo method [14]. We also fix .xi = 1 at all interstitial sites within this layer. The H fractions of other

982

X. Sun and Y. Xu

interstitial sites are initialized with .10−3 , corresponding to dilute .α hydride phase. The lattice parameter of the particle is set to .aL = 3.885 Åfor the initial relaxation of the system. Then we employ the DMD model to predict the inward diffusion of H atoms from the outermost layer. An embedded atom method (EAM) potential [15] is employed to capture the interactions between atoms. The diffusive parameter of the kinetic law is set to . B0 = 500.0 K/(eV · s), in line with previous studies [10, 12, 13]. The time step size for integrating the discrete kinetic equation is .2.0 × 10−3 s. The total simulation time of H diffusion is .80.0 s, which is sufficient for the complete phase transformation in the nanoparticle.

Molecular Dynamics Large-scale molecular dynamics (MD) simulations are initialized by the DMD simulation results that aim to provide an energetically stable atomic configuration of both Pd and H atoms. Specifically, we use the DMD results at multiple time points with a broad range of H/Pd ratios. The DMD method states that, over a sufficiently long time scale, the instantaneous position and the occupancy of each site can be regarded as random variables following the normal and Bernoulli distributions, respectively. As a result, we use the normal distributions with the mean and SD calculated by the DMD simulation to randomly generate the initial positions of Pd atoms for the MD simulation. We further adopt the Bernoulli distributions with the mean also provided by DMD to randomly generate the initial occupancies of interstitial sites. If an interstitial site is occupied by an H atom, the initial position is then randomly generated based on the corresponding normal distribution. The MD simulations are performed using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) solver [16]. We use the same EAM potential [15] as employed in the DMD simulation. The temperature is fixed at .300 K, using a Nosé-Hoover thermostat. The time step size for solving Newton’s equations of motion is .0.1 fs, and the total simulation time for all simulations is .1.0 ns. The total number of both Pd and H atoms are kept constant throughout the MD simulations. We find that the H-concentrated phase can lead to the large variances of atomic positions. As a result, we employ the time-averaged atomic positions of Pd and H atoms over .0.01 ns to identify the types of lattice structures and interstitial sites. In addition, the simulation results are visualized using OVITO [17]. The lattice structural types are identified by Common Neighbor Analysis [18].

Atomistic Simulation of Hydrogen-Defect Interactions …

983

t=0.5 s, H/Pd=0.127

t=4.5s, H/Pd=0.245

t=10.5s, H/Pd=0.387

t=17.5s, H/Pd=0.531

t=27.5s, H/Pd=0.695

t=53.0s, H/Pd=0.866

[001] [100]

[010]

2 nm

H atomic fraction 0

1

Fig. 1 Snapshots of H atomic fraction at the interstitial sites. Half of the nanosphere is shown

Results and Discussion Evolution of Statistics of Microscopic Variables We initiate our investigation by analyzing H diffusion during the absorption process. To achieve this, we extract statistical information on microscopic variables at six distinct steps from the DMD simulation. Figure 1 presents the evolution of H atomic fraction at interstitial sites. As may be seen, H gradually intercalated along the radial direction of the Pd nanosphere, from a spherical shell with high H concentration (close to .1) to a core with low H concentration (close to .0). The shell and core can be interpreted as H-concentrated .β and H-dilute .α phase, respectively. Notably, they are separated by an abrupt boundary consisting of only a few layers of atomic sites. Therefore, the phase transformation process is governed by the slow propagation of this atomistically sharp, hydride phase boundary. This mechanism is the same as experimental observations in the hydrogenation of individual Pd nanoparticles [1, 5]. A time sequence of vibrational standard deviation (SD) of Pd and H atoms is depicted in Figs. 2 and 3, respectively, where sites are placed based on their mean atomic positions. Similar to the hydride phase boundary, there is also a distinct and abrupt transition of SD from .α to .β phase. As anticipated, the SD of Pd atoms is

984

X. Sun and Y. Xu

t=0.5 s, H/Pd=0.127

t=4.5s, H/Pd=0.245

t=10.5s, H/Pd=0.387

t=17.5s, H/Pd=0.531

t=27.5s, H/Pd=0.695

t=53.0s, H/Pd=0.866

[001] [100]

[010]

2 nm

Standard deviation (Å) 0.07 0.12

Fig. 2 Snapshots of SD of Pd atoms at host sites. Half of the nanosphere is shown

t=0.5 s, H/Pd=0.127

t=4.5s, H/Pd=0.245

t=10.5s, H/Pd=0.387

t=17.5s, H/Pd=0.531

t=27.5s, H/Pd=0.695

t=53.0s, H/Pd=0.866

[001] [100]

[010]

Standard deviation (Å) 0.11 0.18

Fig. 3 Snapshots of SD of H atoms at interstitial sites. Half of the nanosphere is shown

2 nm

Atomistic Simulation of Hydrogen-Defect Interactions …

985

significantly lower than that of H atoms in both .α and .β phases. In addition, the SD in .β phase is larger than that in .α phase for both Pd and H atoms, owing to the stronger interactions caused by additional H atoms in the H-rich phase. Specifically, the vibrational SD of Pd atoms increases by .41% from .α to .β phase, whereas this raise is .16% for H atoms. Figures 2 and 3 also reveal that certain atoms in the .β phase exhibit lower SDs, forming a strip-shaped pattern parallel to the .{111} slip planes of FCC structures. We find that the regions where stacking faults (SFs) are observed coincide with the regions where atoms have lower SDs. The reduction in SD can be more than .25%. Thus, solute-induced SFs lead to a decrease in SD of both Pd and H atoms.

Comparisons Between DMD and MD Simulations

-3.00

H/Pd 0.127 0.245 0.387 0.531 0.695 0.866

-3.20

-3.40

-3.60 0.00

0.25

0.50

Time (ns)

(a)

0.75

1.00

Potential energy (eV/atom)

Potential energy (eV/atom)

We now proceed with the results from MD simulations. We employ the statistics at the same six time steps as shown in Figs. 1, 2 and 3. Consequently, a total of six MD simulations are performed. To compare the macroscopic states obtained from the DMD and MD simulations, we focus on the potential energy per atom computed by these two methods. Figure 4(a) illustrates the time history of the potential energy per atom as obtained from the MD simulations. It is evident that the potential energy quickly reaches equilibrium, typically within less than 0.1 ns, for all cases examined. This indicates that the DMD simulations have successfully provided energetically stable configurations of Pd and H atoms across a wide range of H/Pd ratios. Furthermore, Fig. 4b compares the time-averaged potential energy between the DMD and MD simulations. Notably, the results obtained from both methods closely align with each other, demonstrating that the averaged potential energy increases with increasing H/Pd ratio. Therefore, the atomic configurations obtained by the two methods are statistically equivalent.

-3.00

-3.20

-3.40

-3.60 0.00

DMD MD

0.25

0.50

0.75

1.00

H/Pd

(b)

Fig. 4 a Time history of potential energy in MD simulations. b Comparison of potential energy between DMD and MD simulations

986

X. Sun and Y. Xu

DMD

MD (t = 0.6 ns)

MD (t = 1.0 ns)

(a)

(b)

[001] [100]

[010]

2 nm

Fig. 5 Spatial distributions of H atoms: a.H/Pd = 0.531; b.H/Pd = 0.866. In these subfigures, only half of the nanosphere is shown. The DMD results are generated by removing interstitial sites with . x i < 0.05

Figures 5 and 6 compare the spatial distributions of H atoms and SFs between DMD and MD simulations at two representative H/Pd ratios, receptively. As shown in Fig. 5, MD simulations reveal that during the time window of .1.0 ns, the equilibrium positions of most H atoms only vary slightly. As a result, the sharpness of the phase boundary is preserved and the position coincides with that obtained from DMD simulations. This again confirms that the DMD method has provided an energetically stable configuration of atoms. Additionally, we have observed the presence of H-induced misfit dislocations and SFs, as shown in Fig. 6. Most of the SFs take place within the .β phase and phase boundary. They grow inwards along with the propagation of the sharp phase boundary. The formation and dynamics of SFs in the nanoparticle can be attributed to their role in alleviating the residual stress induced by the atomistically sharp boundary and the lattice mismatch between the .α and .β phases, as previously reported by Ref. [12] through an elastic core-shell model. In addition to the SFs revealed by the DMD simulation, the MD simulation also confirms their existence and persistence in the same locations within the short time span of .1.0 ns. It is evident that some differences arise in spatial distribution of lattice defects between DMD and MD simulations, as expected. It can be attributed to the fact that the MD tracks the displacive thermal vibrations of Pd and H atoms, allowing it to identify other energetically stable atomic configurations that further relax the system. On the other hand, the solution obtained from DMD represents an averaged configuration.

Atomistic Simulation of Hydrogen-Defect Interactions …

DMD

MD (t = 0.6 ns)

987

MD (t = 1.0 ns)

(a)

(b)

[001] [100]

[010]

Structure type HCP Other

2 nm

Fig. 6 Spatial distributions of extracted lattice defects: a .H/Pd = 0.531; b .H/Pd = 0.866. In these subfigures, only half of the nanosphere is shown and the atoms with perfect FCC structure are removed for the sake of clarity

Concluding Remarks We have conducted an analysis of hydrogen (H) absorption by a palladium (Pd) nanosphere with a diameter of .20 nm, utilizing both Diffusive Molecular Dynamics (DMD) and classical Molecular Dynamics (MD) simulations. Several significant findings from our calculations deserve attention. Firstly, the hydride phase transformation in Pd nanoparticles is primarily driven by the propagation of an atomically sharp .α/.β phase boundary. Stacking faults are observed within the .β phase and the phase boundary, effectively relieving the elastic stress arising from the lattice misfit between the .α and .β phases. The .β phase contributes to an increase in vibrational standard deviation of atomic positions. Notably, the DMD results align closely with the MD solution in terms of time-averaged potential energy, indicating that DMD can provide energetically stable configurations of Pd and H atoms across a wide range of H/Pd ratios. Furthermore, the MD simulations confirm the stability of the hydride phase boundary and the spatial distribution of stacking faults on a timescale of nanoseconds. Acknowledgements This work is supported by the University of Kentucky through the faculty startup fund.

988

X. Sun and Y. Xu

References 1. Narayan TC, Hayee F, Baldi A, Leen Koh A, Sinclair R, Dionne JA (2017) Direct visualization of hydrogen absorption dynamics in individual palladium nanoparticles. Nat Commun 8:14020 2. Ulvestad A, Welland MJ, Collins SSE, Harder R, Maxey E, Wingert J, Singer A, Hy S, Mulvaney P, Zapol P et al (2015) Avalanching strain dynamics during the hydriding phase transformation in individual palladium nanoparticles. Nat Commun 6:1–8 3. Zalineeva A, Baranton S, Coutanceau C, Jerkiewicz G (2017) Octahedral palladium nanoparticles as excellent hosts for electrochemically adsorbed and absorbed hydrogen. Sci Adv 3(2):e1600542 4. Ulvestad A, Welland MJ, Cha W, Liu Y, Kim JW, Harder R, Maxey E, Clark JN, Highland MJ, You H et al (2017) Three-dimensional imaging of dislocation dynamics during the hydriding phase transformation. Nat Mater 16(5):565–571 5. Sytwu K, Hayee F, Narayan TC, Koh AL, Sinclair R, Dionne JA (2018) Visualizing facet-dependent hydrogenation dynamics in individual palladium nanoparticles. Nano Lett 18(9):5357–5363 6. Wilde M, Fukutani K (2008) Penetration mechanisms of surface-adsorbed hydrogen atoms into bulk metals: experiment and model. Phys Rev B 78(11):115411 7. Kulkarni Y, Knap J, Ortiz M (2008) A variational approach to coarse graining of equilibrium and non-equilibrium atomistic description at finite temperature. J Mech Phys Solids 56(4):1417– 1449 8. Venturini G, Wang K, Romero I, Ariza MP, Ortiz M (2014) Atomistic long-term simulation of heat and mass transport. J Mech Phys Solids 73:242–268 9. Li J, Sarkar S, Cox WT, Lenosky TJ, Bitzek E, Wang Y (2011) Diffusive molecular dynamics and its application to nanoindentation and sintering. Phys Rev B 84(5):054103 10. Sun X, Ariza MP, Ortiz M, Wang K (2017) Acceleration of diffusive molecular dynamics simulations through mean field approximation and subcycling time integration. J Comput Phys 350:470–492 11. Sun X, Ariza MP, Wang K (2016) Deformation-diffusion coupled analysis of long-term hydrogen diffusion in nanofilms. In: Proceedings of VII European congress on computational methods in applied sciences and engineering, vol 1, pp 197–208. ECCOMAS 12. Sun X, Ariza MP, Ortiz M, Wang KG (2019) Atomistic modeling and analysis of hydride phase transformation in palladium nanoparticles. J Mech Phys Solids 125:360–383 13. Sun X, Ariza P, Ortiz M, Wang KG (2018) Long-term atomistic simulation of hydrogen absorption in palladium nanocubes using a diffusive molecular dynamics method. Int J Hydrogen Energy 43(11):5657–5667 14. Ruda M, Crespo EA, Ramos S, de Debiaggi. (2010) Atomistic modeling of h absorption in pd nanoparticles. J Alloys Compounds 495(2):471–475 15. Zhou X, Zimmerman JA, Wong BM, Hoyt JJ (2008) An embedded-atom method interatomic potential for pd–h alloys. J Mater Res, 23(03):704–718 16. Plimpton S (1995) Fast parallel algorithms for short-range molecular dynamics. J Comput Phys 117(1):1–19 17. Stukowski A (2010) Visualization and analysis of atomistic simulation data with ovito-the open visualization tool. Modell Simul Mater Sci Eng 18(1):015012 18. Stukowski A (2012) Structure identification methods for atomistic simulations of crystalline materials. Modell Simul Mater Sci Eng 20(4):045021

First Principles Study on the Segregation of Metallic Solutes and Non-metallic Impurities in Cu Grain Boundary Vasileios Fotopoulos, Jack Strand, Manuel Petersmann, and Alexander L. Shluger

Abstract Metallic dopants have the potential to increase the mechanical strength of polycrystalline metals. These elements are expected to aggregate in regions of lower coordination, such as grain boundaries. At the grain boundaries, they can have a beneficial (toughening) or detrimental effect (e.g. grain boundary embrittlement). In this study, we employ Density Functional Theory (DFT) to compute the segregation energies of various metallic and non-metallic elements to determine their effect when introduced in a symmetric Cu grain boundary. The results may be used to qualitatively rank the beneficial effect of certain metallic elements, such as V, Zr, and Ag, as well as the strong weakening effect of non-metallic impurities like O, S, F, and P. Furthermore, the induced local distortion is found to be correlated with the weakening effect of the elements. Keywords DFT · Segregation · Grain boundaries · Metals · Non-metallic impurities · Metallic dopants

Introduction Degradation phenomena in metals have been reported to initiate at certain microstructural features, such as grain boundaries (GBs) [1–4]. Experimental results have illustrated how the level of corrosion and degradation of metals under high-stress conditions depends on the concentration of certain elements [5]. Impurity-induced V. Fotopoulos (B) · J. Strand · A. L. Shluger Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK e-mail: [email protected] M. Petersmann KAI—Kompetenzzentrum Automobil- und Industrieelektronik GmbH, Europastrasse 8, Villach 9524, Austria J. Strand Nanolayers Research Computing Ltd., London, UK © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_85

989

990

V. Fotopoulos et al.

embrittlement accounts for many cases of brittle failure of polycrystalline metals [6– 8]. Impurity-induced embrittlement is commonly attributed to a chemical effect of the segregation of solutes, which is believed to change the bonding strength at GBs [6, 9], or to a size (strain) effect that is associated with the size mismatch between the solute and host atoms [10, 11]. The segregation of metallic dopants and non-metallic impurity elements at GBs in metals plays a key role in the design of novel materials [12]. However, a clear correlation between the properties of solutes and the strengthening or weakening effect that they can have when introduced in the GBs of metals is still missing. In light of recent experimental studies in bicrystalline Fe, solutes that decorate grain boundaries significantly affect their chemical composition, charge distribution, structural properties, and therefore their mechanical stability [13]. GBs in polycrystalline metals can be engineered and decorated with certain elements to increase their resistance against corrosion effects. Thus, identifying the elements that could potentially be employed as GB decorative solutes is of great interest. First principles simulations on 3d transition metal solutes in Fe [14, 15], Au [12], Mo [16], and Ni [17] illustrated that their presence at GBs can significantly increase their tensile strength and resistance against embrittlement phenomena. Cu, a metal used in a wide range of applications, including electronic devices, showed prominent degradation effects under thermal cycling [1, 18]. Such phenomena often initiate at crystal grain boundaries and can have devastating effects on the performance of these devices. Doping of grain boundaries with metallic elements can be an efficient solution to this problem [19]. However, although several properties have been proposed to play a critical role in the weakening or strengthening effect that these elements can have, a correlation between the above-mentioned effects and the elements’ induced local distortion into the lattice hasn’t been established. This work complements previous theoretical studies of metallic segregants in Cu GBs. Density Functional Theory (DFT) simulations are conducted to determine the most favorable segregation sites of 3d transition and other metals in a symmetric Cu GB, along with their local strengthening or weakening effect. We highlight the beneficial effects of V, Zr, and Ag. Finally, we show how the computed segregation energies are linked with the solutes’ induced lattice relaxation. Metallic solutes with low GB segregation energies induce small relaxation. On the other hand, non-metallic impurities with a high computed strengthening energy, such as O, S, F, and P, cause severe local displacements of Cu atoms. Such findings highlight the possibility of decorating Cu GBs with specific metallic elements to reduce the degradation effects in Cu.

Methods DFT calculations are performed using the Vienna Ab Initio Simulation Package (VASP) [20–22], with the GGA exchange-correlation functional Perdew-BurkeErnzerhof (PBE) [23]. For the investigation of grain boundaries and bulk properties

First Principles Study on the Segregation of Metallic Solutes …

991

Fig. 1 a Examined substitutional and interstitial sites of dopants/impurities in (210)[100].∑5 Cu grain boundaries. b Schematics illustrating (top) the segregation and (bottom) strengthening energies of substitutional impurities/dopants in the grain boundaries

of copper, 76-atom and 108-atom periodic cells are utilized, respectively. The specific grain boundary chosen for examination is the (210)[100].∑5 twin boundary (shown in Fig. 1a), due to its high symmetry and low-energy characteristics [24]. Consistent with previous studies [25, 26], the calculations employed converged 5.×4.×1 and 4.×4.×4 k-point grids for the 76 and 108-atom simulation cells, respectively. An energy cut-off of 450 eV is used, as established in previous Cu simulations [27]. Segregation energies were calculated using the formula: .

E seg = (E G B+X − E G B ) − (E Bulk+X − E Bulk ),

(1)

where . E G B+X and . E G B are the energies of GB cells with and without segregants (X) and . E Bulk+X , . E Bulk the energies of bulk cells with and without segregants, respectively. Negative and positive segregation energies illustrate favorable GB segregation and antisegregation, respectively. For the determination of the segregation energies related to interstitial impurities, octahedral and tetrahedral interstitial sites are considered in the bulk. Figure 1a presents the four interstitial and substitutional positions considered at the GB for each segregant.

992

V. Fotopoulos et al.

The effect of impurities on the strength of the grain boundary can be derived from the strengthening energy. This parameter provides insight into whether the solutes exhibit a preference for locating themselves at grain boundaries as opposed to surface positions. The calculation of DFT strengthening energies is carried out according to the following expression: .

E str = (E G B+X − E G B ) − (E Sur +X − E Sur ),

(2)

where . E Sur and . E Sur +X symbolize the energies associated with the pure Cu surface and the Cu surface simulation cells containing one solute atom, respectively. For the surface simulations, 108-atom simulation (100) slab models are used with a thickness of 10.86 Å. The strengthening energy, when negative, indicates an enhancement of the grain boundary strength due to the impurity, while a positive value implies a weakening effect. Schematic representations of the segregation and strengthening energies are shown in Fig. 1b.

Results Segregation Energies To determine the most favorable sites, as shown in Fig. 1a, of the impurities examined, the segregation energies of all elements are calculated. Figure 2a includes all the computed segregation energies for the various sites. The plots are divided into colored regions on the basis of the group of elements on the periodic table. As seen in the

Fig. 2 Computed segregation energies for a metallic and b non-metallic elements for different sites. Different colored areas correspond to elements of different groups. Negative energies correspond to favorable segregation at the GB, whereas positive energies correspond to antisegregation. The int represents interstitial atoms, whereas the rest of the elements correspond to substitutional atoms

First Principles Study on the Segregation of Metallic Solutes …

993

figure, most of the metallic dopants are found to occupy most preferably substitutional sites 1 and 3. Fe and Co dopants show segregation energies close to 0 eV, indicating that these elements do not show an energetic preference to be at the GB instead of the bulk region. For non-metallic impurities, our results show that all substitutional elements will occupy site 2. Also, non-metallic elements show a significantly stronger tendency to segregate at the GB compared to metallic solutes, with F, S, O, and P resulting in the lowest segregation energies. C is the only element that shows a strong preference to segregate as an interstitial atom. On the basis of these results, elements such as C, O, F, P, S, and Se, when introduced in polycrystalline Cu, are expected to strongly segregate at the GBs of the crystal. Table 1 includes the comparison between the segregation energies calculated in the current work and previous studies. For non-metallic impurities, the computed segregation energies are within 0.2 eV compared to previous studies. The only exceptions are seen in the case where a different .∑5 GB ((310)[001].∑5 GB [30, 34]), or a different .∑ symmetry ((221)[110].∑9 [31]) is used. For the segregation energies of

Table 1 Segregation energies comparison between the results from the current work and previous DFT studies for metallic and non-metallic elements. Values with.∗ and.∗∗ correspond to segregation energies computed in (221)[110].∑9 and (310)[001].∑5 GB, respectively. The rest of the values, including our results, were obtained using (210)[100].∑5 GB simulation cells Element Reference E.seg (eV) E.seg (eV) [Our work] C (int) C (int) O (int) O Si Si P P S S S S Ge Se Mg V Co Ag Ag Zr

Wurmshuber [28] Huang (2018) [19] Bodlos [29] Bodlos [29] Huang (2018) [19] Li [30] Li [30] Lousada [31] Bodlos [29] Wang [32] Li [30] Lousada [31] Razumovskiyy [33] Razumovskiyy [33] Huang (2020) [34] Huang (2020) [34] Razumovskiyy [33] Razumovskiyy [33] Huang (2019) [35] Huang (2018) [19]

.−0.8

.−0.85

.−0.9

.−0.85

.−1.2

.−1.27

.−1.15

.−1.26

.−0.3

.−0.36

∗∗

.−0.58.

.−0.36

.−0.95

.−0.9

∗

.−0.65.

.−0.9

.−1.2

.−1.14

.−1

.−1.14

∗∗ .−1.15. ∗

.−1.14

.−0.75.

.−1.14

.−0.3

.−0.42

.−0.8

.−0.98

∗∗

.−0.57

.−1.

∗∗

.−0.2.

.−0.34

0 .−0.6 .−0.8 .−1.65

.−0.04 .−0.5 .−0.5 .−1.23

994

V. Fotopoulos et al.

the metallic dopants, our results agree well with the results of ref. [33], while the study ref. [19] showed lower energies by 0.3 and 0.42 eV for Ag and Zr, respectively. In general, the table shows that there is a clear trend for certain non-metallic (C, O, P, S, Se) and metallic elements (Zr) to strongly segregate at the grain boundaries. The rest of the elements show small to close to no preference for being at the grain boundaries instead of the bulk of Cu.

Strengthening Energies In Fig. 3, the effect of the studied elements on the strength of the GB is shown when introduced at various sites. Negative strengthening energies correspond to a toughening effect, whereas positive energies correspond to a weakening effect. On the basis of these results, one can deduce that most of the metallic solutes show negative strengthening energies (strengthening effect), whereas all non-metallic elements show positive strengthening energies (weakening effect). The latter shows that our findings support previous studies and highlight the differences between metals and non-metals when it comes to their impact on GBs [19, 33, 35]. Table 2 summarizes the main conclusions of our investigation so far. One can see that all of the examined non-metallic elements are expected to have a weakening effect when they are introduced into the GB of Cu. From the metallic dopants, excluding Mg and Cd, all of the rest showed a strengthening effect. The weakening effect of Mg and Cd can be attributed to their small atomic radii. The grain boundary energy is expected to decrease as the atomic radius of the metallic dopants increases [35].

Fig. 3 Computed strengthening energies for a metallic and b non-metallic elements for different sites. Different colored areas correspond to elements of different groups. Negative strengthening energies correspond to a strengthening effect, whereas positive strengthening energies correspond to a weakening effect

First Principles Study on the Segregation of Metallic Solutes …

995

Table 2 Properties of the examined non-metallic impurities and metallic solutes along with the identified most favorable sites and their effect. W and S correspond to weakening and strengthening effects, respectively Group Mass (amu) Radius (pm) Site Effect (S/W) Element C O O F Si P S Ge Se Mg V Fe Co Zr Ag Cd Pt

2 2 2 2 3 3 3 4 4 3 4 4 4 5 5 5 6

12.01 15.99 15.99 18.99 28.09 30.97 32.07 72.64 78.96 24.31 50.94 55.85 58.93 91.22 107.87 112.41 175

170 152 152 147 210 195 180 211 190 173 179 126 200 206 172 158 195.08

3 (int) 4 (int) 2 2 2 2 2 3 2 1 4 4 4 3 1/3 1 1

W W W W W W W W W W S S S S S W S

These results agree with the conclusions drawn in ref.[33], where metallic dopants with energies close to zero, in our case Co and Fe, are expected to strengthen the GB. Also, in agreement with the aforementioned study, non-metallic impurities relaxing to the site next to the GB plane (site 2) weaken the GB. Furthermore, as highlighted in previous theoretical works [34], non-metallic solutes with larger atomic radius segregate more easily at the grain boundary but cause more significant grain boundary embrittlement.

Lattice Distortion Effects In the previous sections, the segregation and strengthening energies were computed, and the most favorable segregation sites were identified. The computed energetic parameters follow the pattern already identified by previous studies [19, 33, 35]. We now move on to examine the effect of impurities/dopants on local lattice distortions. Figure 4a includes the fully relaxed configurations for some of the tested metallic dopants along with non-metallic elements at their most favorable sites. In addition, displacements are also included, both in the form of colored atoms and as displacement vectors. Relaxed configurations for O, Si, P, Zr, and Pt are shown in

996

V. Fotopoulos et al.

Fig. 4 a Fully relaxed configurations along with their displacement magnitudes (bottom) for O, Si, P, Zr, and Pt. Yellow arrows correspond to the displacement vectors. For displacements, the configuration prior to relaxation is used as a reference. b Bond analysis for the aforementioned elements. Bond analysis illustrates the distribution of distances between the dopants/impurities and nearby Cu atoms within a cut-off distance of 3 Å. The y-axis corresponds to the number of Cu atoms at a certain distance from the dopant/impurity

Fig. 4a. As can be deduced, substitutional metallic solutes cause minimal relaxation. Non-metallic elements, either substitutional or interstitial, induce significant local relaxation, which could explain the weakening effect that these elements have. Nonmetallic impurities with a small preference to segregate at the GB, like Si, caused negligible local distortion. Figure 4b includes the results of the bond analysis. Bond analysis illustrates the distribution of distances between the dopants/impurities and nearby Cu atoms within a cut-off distance of 3 Å. Any distances beyond the mentioned cut-off are ignored. All metallic dopants showed distances from the adjacent Cu atoms of approximately 2.6 Å, which is the same as the Cu-Cu distance in the perfect lattice. The latter highlights the minimal distortion that the metallic dopants introduced. On the other hand, non-metallic impurities show peaks at lower than 2.5 Å.

Conclusions We employed DFT to investigate the energetic properties of metallic dopants and nonmetallic impurities introduced into the grain boundaries of Cu. Among the metallic dopants, such as Mg, V, Fe, Co, Ag, and Zr, a clear trend towards segregation within the grain boundaries rather than the bulk was found. The aforementioned elements also showed negative strengthening energies, indicating that they are expected to locally increase the resistance of the crystal against decohesion. Furthermore, the results highlighted a preference for non-metallic impurities, like O, P, F, S, and Se, to

First Principles Study on the Segregation of Metallic Solutes …

997

segregate at the grain boundaries as opposed to the bulk of Cu. This enhanced affinity of impurities to grain boundaries, along with the predicted local weakening effect of these elements, could potentially explain experimental findings that point to the initiation of degradation phenomena in these regions. A link was determined between the segregation energies and the induced relaxation effects. Metallic solutes with segregation energies close to zero were shown to induce minimal distortion, whereas non-metallic elements that strongly segregate at the GB caused severe displacement of nearby Cu atoms. Grain boundaries are known to play an important role in the properties of metals. On the basis of our findings, the incorporation of metallic dopants such as V, Zr, and Ag at the grain boundaries of Cu has the potential to improve the mechanical properties of these regions and enhance their resistance against degradation. Further studies are needed to understand the behavior of these impurities when introduced into polycrystalline Cu. Acknowledgements A. L. S. acknowledges funding by EPSRC (grant EP/P013503/1). V. F. would like to acknowledge funding by EPSRC (grant EP/L015862/1) as part of the CDT in molecular modeling and materials science. Computational resources on ARCHER2 (http://www.archer2.ac. uk) were provided via our membership in the UK’s HPC Materials Chemistry Consortium, which is funded by EPSRC (EP/L000202, EP/R029431). V. F. and A. L. S. would like to thank Rishi Bodlos, Lorenz Romaner, and Ernst Kozeschnik for useful comments and help with calculations.

References 1. Moser S, Kleinbichler M, Kubicek S, Zechner J, Cordill MJ (2021) Electropolishing-a practical method for accessing voids in metal films for analyses. Appl Sci 11(15):7009 2. Konishi S, Moriyama M, Murakami M (2002) Effect of annealing atmosphere on void formation in copper interconnects. Mater Trans 43(7):1624–1628 3. Hallberg H, Ås SK, Skallerud B (2018) Crystal plasticity modeling of microstructure influence on fatigue crack initiation in extruded Al6082-T6 with surface irregularities. Int J Fatigue 111:16–32 4. Stopka KS, McDowell DL (2020) Microstructure-sensitive computational multiaxial fatigue of Al 7075-T6 and duplex Ti-6Al-4V. Int J Fatigue 133:105,460 (2020) 5. Hu T, Yang S, Zhou N, Zhang Y, Luo J (2018) Role of disordered bipolar complexions on the sulfur embrittlement of nickel general grain boundaries. Nat Commun 9(1):2764 6. Duscher G, Chisholm MF, Alber U, Rühle M (2004) Bismuth-induced embrittlement of copper grain boundaries. Nat Mater 3(9):621–626 7. Ludwig W, Pereiro-López E, Bellet D (2005) In situ investigation of liquid Ga penetration in Al bicrystal grain boundaries: Grain boundary wetting or liquid metal embrittlement? Acta Mater 53(1):151–162 8. Laporte V, Mortensen A (2009) Intermediate temperature embrittlement of copper alloys. Int Mater Rev 54(2):94–116 9. Kang J, Glatzmaier GC, Wei SH (2013) Origin of the bismuth-induced decohesion of nickel and copper grain boundaries. Phys Rev Lett 111(5):055,502 10. Schweinfest R, Paxton AT, Finnis MW (2004) Bismuth embrittlement of copper is an atomic size effect. Nature 432(7020):1008–1011

998

V. Fotopoulos et al.

11. Lozovoi A, Paxton A, Finnis M (2006) Structural and chemical embrittlement of grain boundaries by impurities: A general theory and first-principles calculations for copper. Phys Rev 74(15):155,416 12. Scheiber D (2021) Segregation and embrittlement of gold grain boundaries. Comput Mater Sci 187:110,110 13. Zhou X, Ahmadian A, Gault B, Ophus C, Liebscher CH, Dehm G, Raabe D (2023) Atomic motifs govern the decoration of grain boundaries by interstitial solutes. Nat Commun 14(1):3535 14. Xu Z, Tanaka S, Kohyama M (2019) Grain-boundary segregation of 3d-transition metal solutes in bcc fe: Ab initio local-energy and d-electron behavior analysis. J Phys: Condens Matter 31(11):115,001 15. Mai HL, Cui XY, Scheiber D, Romaner L, Ringer SP (2022) The segregation of transition metals to iron grain boundaries and their effects on cohesion. Acta materialia 231:117,902 16. Scheiber D, Romaner L, Pippan R, Puschnig P (2018) Impact of solute-solute interactions on grain boundary segregation and cohesion in molybdenum. Phys Rev Mater 2(9):093,609 17. Razumovskiy VI, Lozovoi A, Razumovskii I (2015) First-principles-aided design of a new Ni-base superalloy: Influence of transition metal alloying elements on grain boundary and bulk cohesion. Acta Mater 82:369–377 18. Moser S, Zernatto G, Kleinbichler M, Nelhiebel M, Zechner J, Cordill MJ, Pippan R (2019) A novel setup for in situ monitoring of thermomechanically cycled thin film metallizations. JOM 71:3399–3406 19. Huang Z, Chen F, Shen Q, Zhang L, Rupert TJ (2018) Uncovering the influence of common nonmetallic impurities on the stability and strength of a .∑5 (310) grain boundary in Cu. Acta Mater 148:110–122 20. Kresse G, Hafner J (1993) Ab initio molecular dynamics for open-shell transition metals. Phys Rev B 48(17):13,115 21. Kresse G, Furthmüller J (1996) Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys Rev B 54(16):11,169 22. Kresse G, Furthmüller J (1996) Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput Mater Sci 6(1):15–50 23. Perdew JP, Burke K, Ernzerhof M (1996) Generalized gradient approximation made simple. Phys Rev Lett 77(18):3865 24. Wu X, You YW, Kong XS, Chen JL, Luo GN, Lu GH, Liu C, Wang Z (2016) First-principles determination of grain boundary strengthening in tungsten: Dependence on grain boundary structure and metallic radius of solute. Acta Mater 120:315–326 25. Nazarov R, Hickel T, Neugebauer J (2012) Vacancy formation energies in fcc metals: Influence of exchange-correlation functionals and correction schemes. Phys Rev B 85(14):144,118 26. Nazarov R, Hickel T, Neugebauer J (2014) Ab initio study of H-vacancy interactions in fcc metals: Implications for the formation of superabundant vacancies. Phys Rev B 89(14):144,108 27. Fotopoulos V, Grau-Crespo R, Shluger AL (2023) Thermodynamic analysis of the interaction between metal vacancies and hydrogen in bulk Cu. Phys Chem Chem Phys 25(13):9168–9175 28. Wurmshuber M, Burtscher M, Doppermann S, Bodlos R, Scheiber D, Romaner L, Kiener D (2022) Mechanical performance of doped W–Cu nanocomposites. Mater Sci Eng: A 857:144,102 29. Bodlos R, Scheiber D, Spitaler J, Romaner L (2023) Modification of the Cu/W interface cohesion by segregation. Metals 13(2):346 30. Li Y, Korzhavyi PA, Sandström R, Lilja C (2017) Impurity effects on the grain boundary cohesion in copper. Phys Rev Mater 1(7):070,602 31. Lousada CM, Korzhavyi PA (2020) Segregation of P and S impurities to a .∑9 grain boundary in Cu. Metals 10(10):1362 32. Wang X, Benabou L (2018) First-principles investigation of intergranular fracture in copper by grain boundary segregation of sulfur. J Eng Mater Technol 140(1):011,008 33. Razumovskiy V, Divinski S, Romaner L (2018) Solute segregation in Cu: DFT vs. experiment. Acta Mater 147:122–132

First Principles Study on the Segregation of Metallic Solutes …

999

34. Huang Z, Wang P, Chen F, Shen Q, Zhang L (2020) Understanding solute effect on grain boundary strength based on atomic size and electronic interaction. Sci Rep 10(1):16,856 35. Huang Z, Chen F, Shen Q, Zhang L, Rupert TJ (2019) Combined effects of nonmetallic impurities and planned metallic dopants on grain boundary energy and strength. Acta Mater 166:113– 125

Hydrogen-Induced Transformation of Dislocation Core in Fe and Its Effect on Dislocation Mobility Md. Shahrier Hasan, Hadia Bayat, Colin Delaney, Christopher Foronda, and Wenwu Xu

Abstract In this research, we employ atomistic simulations to scrutinize the impact of hydrogen (H) on dislocation mobility in iron (Fe). Our study uncovers two critical aspects: Firstly, hydrogen atoms serve to stabilize the edge dislocation core, thereby elevating the shear stress threshold needed for dislocation mobilization. Secondly, hydrogen’s influence on dislocation mobility is velocity-dependent; it enhances mobility at low velocities by diminishing lattice resistance but hampers it at high velocities due to increased viscous drag. These nuanced findings illuminate the multifaceted relationship between hydrogen atoms and dislocation mechanisms. They offer valuable insights for the development of materials with enhanced mechanical properties and contribute to strategies for mitigating hydrogen-induced material degradation. Keywords Hydrogen embrittlement · Dislocation mobility · Atomistic modeling

Introduction Metals and alloys are indispensable structural materials as they have the desirable combination of strength and ductility required for structural applications [1–4]. Moreover, metals and alloys allow for substantial plastic deformation before failure, making them ideal for manufacturing. This essential property of metals and alloys, however, can be negatively impacted by a phenomenon: hydrogen (H) embrittlement [5–7]. Hydrogen embrittlement is a phenomenon where metals and alloys crack or fail before reaching their fracture strength after being exposed to H. Since H atoms are much smaller than most metallic atoms, H atoms permeate through the metallic systems and can occupy interstitial and defective regions. Despite extensive research, Md. S. Hasan · H. Bayat · C. Delaney · C. Foronda · W. Xu (B) Department of Mechanical Engineering, San Diego State University, San Diego, CA 92182, USA e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_86

1000

Hydrogen-Induced Transformation of Dislocation Core in Fe and Its …

1001

the mechanism behind H’s detrimental effect on metals remains debated. A cohesionbased theory, the H-enabled decohesion (HEDE), posits that H facilitates crack formation and growth in polycrystalline metals by promoting decohesion at crack tips. Another explanation about HEDE suggests that H accelerates formation of vacancies, weakening the metal [8]. It is worth noting that while HEDE is theoretically robust, experimental evidence is inconclusive. The above mechanisms explain brittle fractures, they do not account for ductile fractures, the primary failure mode in metals and alloys. Ductile failure begins with the microvoid formation near the second phase particle or precipitate in metals and alloys, followed by void coalescence and growth culminating in ductile failure. The hydrogen-enabled localized plasticity (HELP) mechanism proposes that H affects plastic deformation in metals. According to the HELP mechanism, the presence of hydrogen eases dislocation motion, reduces dislocation–dislocation interaction known as hydrogen shielding and promotes dislocation nucleation locally softening the material. This theory gains support from observation showing reduced dislocation pile-up distances in metals like steels and aluminum with higher H concentration. Atomistic modeling is an effective tool to investigate a variety of phenomena where atomistic description of the material has a significant effect [9–13]. This research aims to examine how varying H concentrations influence dislocation core velocity in single crystal iron under shear loads. The following sections outline our Methodology, Results, and Discussions, and finally, Conclusions are drawn from the results to further our understanding of the atomistic mechanism responsible for H embrittlement.

Methodology Periodic array of dislocation (PAD) [14] model is used to model edge dislocation inside of a single crystal BCC Fe model. Periodic boundary condition (PBC) was used in the boundary along X- and Z-directions, and shrink-wrapped boundary condition was used along the Y-direction to be used as a traction boundary. A convergence analysis with energy minimization is performed to find the minimum dimensions of the PAD model with no significant periodic effect. The dimension for the PAD model was determined to be 61[111] × 40[−110] × 12[−1–12] with 9480 atoms in pure Fe model. An edge dislocation with 1/2[111] burger vector is introduced at the center of the XZ plane by adding the upper half plane above the dislocation line with the Atomsk software tool [15]. The schematic diagram of this PAD model with the edge dislocation is shown in Fig. 1a. The widely used Large-Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) software is then used to perform a series of molecular dynamic simulations [16]. In the PAD model, at the traction boundary along Y-direction, atoms that are six atomistic layers deep from the upper and lower regions were marked to be frozen from thermal activation. For pure metal Fe, EAM potential is used by Proville et al. that is specifically developed for simulating thermally activated glide

1002

Md. S. Hasan et al.

Fig. 1 Schematic diagram and atomistic PAD model of pure metal Fe: a and b show schematic diagram of dislocation in PAD model at rest and under shear, respectively. c shows the atomistic PAD model where blue and white atoms represent matrix and dislocation core atoms, respectively. d shows line representation of the dislocation

of dislocations [17]. The PAD model is then equilibrated at 300 K temperature for 10 picoseconds (PS) which was found to be sufficient to relax the pure Fe model. Care is taken not to include the frozen atoms in the equilibration process. After the equilibrated configuration is obtained, a shear stress is applied on the upper traction boundary along Y. Total shear force is equally distributed among the upper frozen atoms. Shear stress varies from 0.1 GPa to 1.5 GPa for the PAD model keeping the temperature fixed at 300 K and shear simulation time at 150 PS. Open Visualization Tool (OVITO) is used to analyze the time-series data from molecular dynamic simulation [18]. To identify the local crystal structure, OVITO has two different tools based on distinct algorithms, namely Common Neighbor Analysis (CNA) [19] and Polyhedral Template Matching (PTM) [20]. In the presence of strong thermal fluctuations and strain, the PTM method is determined to be a more reliable tool for structural identification. With the help of PTM, the atoms with native BCC crystal structure can be distinguished from dislocation core atoms with unmatched crystal structure as can be seen from Fig. 1c. The atoms that make up the dislocation core are marked and average position of the collection of dislocation core atoms is

Hydrogen-Induced Transformation of Dislocation Core in Fe and Its …

1003

recorded at each time step. This average position of dislocation core atoms is plotted against time to calculate the edge dislocation velocity in pure Fe. To investigate the H effect on edge dislocation velocity, the PAD model is randomly incorporated with varying number of H atoms. After creating models with varying concentration of H, the simulation process of equilibration, shear, and dislocation velocity calculation is performed on each model.

Results and Discussion The effect of H on the edge dislocation core at zero temperature is previously reported by Wang et al. where Peierls stress, shear modulus, and dislocation core energy are computed at various H concentrations [21]. Edge dislocation core energy is reported to show a steady decrease with the increase of H concentration from 0 to 0.08 at%. In the present work, the effect of edge dislocation core configuration is computed at room temperature (300 K). Furthermore, to model H effect on Fe, the EAM potential developed by Wen [22] is used here as opposed to the Mendelev [23] potential as the former takes H–H interaction into account in addition to H-Fe interaction. In the atomistic model, dislocation core atoms are identified using the PTM method. The dislocation core energy then can be computed as the model is allowed to be equilibrated for 100 ps. Dislocation core atoms are at a higher energy compared to the rest due to the lattice mismatch. Figure 2a, b shows that the addition of H affects the energy distribution of the core, and Fig. 2c shows that H atoms also affect the average energy of the core atoms. During equilibration, the average dislocation core energy of pure Fe remains constant but for the models with H atoms, dislocation core energy progressively reduces. This result shows the H atoms stabilize the dislocation core of Fe and the rate of stabilization directly correlates to the H concentration. Atomistic visualization reveals that the H atoms occupy the dislocation core interstitial position, reducing the lattice mismatch at the edge dislocation core which explains the reduction in core energy. The continuous reduction in core energy also confirms the progressive accumulation of H atom at the dislocation core. The effect of this H induced stabilization of dislocation core on the mobility of dislocation is studied by analyzing the MD simulation result of application of shear load on the equilibrated models. The applied shear stress in the simulation varied from 500 to 1500 MPa, whereas the H concentration varied from 0.25 to 1.00%. Table 1 shows the shear stress and H concentration at which the edge dislocation was able to mobilize. In pure Fe, the dislocation was observed to be able to move at 50 MPa shear stress. However, with as little as 0.25% presence of H, the dislocation is rendered immobile below 900 MPa shear stress. At 1.00% H concentration, edge dislocation can only move at and above 1200 MPa applied shear. At the applied shear and H concentration where dislocation can move, dislocation velocity is calculated from the slope of average dislocation core position against time curve. Figure 3 shows how dislocation velocity changes with the increasing applied shear in pure Fe model. It can be noted that at lower applied shear stress, the

1004

Md. S. Hasan et al.

Fig. 2 H effect on dislocation core. a and b show the relative energy distribution in the edge dislocation core with and without H atoms respectively. The average energy of the dislocation core with increasing H concentration is shown in (c)

Table 1 Effect of H concentration on the mobility of the Fe edge dislocation Atom% H

50 MPa

100 MPa

300 MPa

600 MPa

900 MPa

1200 MPa

1500 MPa

0.00

m

m

m

m

m

m

m

0.25

s

s

s

s

m

m

m

0.50

s

s

s

s

m

m

m

0.75

s

s

s

s

m

m

m

1.00

s

s

s

s

s

m

m

dislocation core movement is non-linear but as with the increase of applied shear, core movement becomes nearly linear. At low applied shear, atomistic lattices resist the core movement which becomes insignificant with the increase of applied shear. This observation justifies the linear approximation to calculate dislocation velocity. Even a small concentration of H dramatically modifies the dislocation core behavior as observed from Table 1. Figure 4 shows the effect of H concentration on dislocation velocity. While increase of H concentration increases the shear stress level required to mobilize an edge dislocation core, it also eases the initial lattice resistance, enhancing the dislocation velocity compared to dislocation core in pure

Hydrogen-Induced Transformation of Dislocation Core in Fe and Its …

1005

Fig. 3 Dislocation velocity with varying applied shear stress in pure Fe

Fe. However, since at higher shear stress level (>900 MPa) lattice resistance does not play a significant part, this enhancement also becomes insignificant. Above 900 MPa shear stress, increasing H concentration starts to impede dislocation velocity. This can be explained by the fact that under high shear and larger dislocation velocity,

1006

Md. S. Hasan et al.

Fig. 4 Effect of H concentration on Fe dislocation velocity

lattice resistance is already small, and thus, H atoms only add to the viscous drag of the dislocation movement.

Conclusions In conclusion, this study delves into the nuanced effects of hydrogen (H) on dislocation mobility within iron (Fe). Our key findings reveal a dual role for hydrogen atoms in influencing this process. First, H atoms serve to stabilize the edge dislocation core in Fe, thereby elevating the level of shear stress necessary to mobilize the dislocation. Secondly, H atoms exhibit a velocity-dependent impact on dislocation mobility: They facilitate it at low velocities by reducing lattice resistance but act as an impediment at high velocities by increasing viscous drag. These insights offer a deeper understanding of the complex interactions between hydrogen and dislocation behaviors, setting the stage for future research in this critical area. Acknowledgements This research was made possible through the generous support of the US National Science Foundation, Division of Materials Research (Award No. 1900876), as well as the US Department of Energy, Office of Basic Energy Sciences (Award No. SC0022244). We extend our heartfelt appreciation to the High-Performance Computing Cluster (HPCC) at SDSU for supplying the essential computational resources for this project. Data Availability The raw/processed data required to reproduce these findings cannot be shared at this time as the data also forms part of an ongoing study.

Hydrogen-Induced Transformation of Dislocation Core in Fe and Its …

1007

References 1. Lu K (2010) The future of metals. Science 328(5976):319–320 2. Xu WW et al (2015) In situ synchrotron radiography of ultrasound cavitation in a molten Al-10Cu alloy. In: TMS2015 supplemental proceedings. pp 61–66 3. Xu WW, Song XY, Li ED, Wei J, Zhang JX (2009) Thermodynamic study on phase stability in nanocrystalline Sm–Co alloy system. J Appl Phys 105(10):104310 4. Williams JC, Starke EA (2003) Progress in structural materials for aerospace systems. Acta Mater 51(19):5775–5799 5. Pradhan A, Vishwakarma M, Dwivedi SK (2020) A review: the impact of hydrogen embrittlement on the fatigue strength of high strength steel. Mater Today Proc 26:3015–3019 6. Dwivedi SK, Vishwakarma M (2018) Hydrogen embrittlement in different materials: a review. Int J Hydrogen Energy 43(46):21603–21616 7. Robertson IM et al (2015) Hydrogen embrittlement understood. Metall Mater Trans A Phys Metall Mater Sci 46(6), 2323–2341 8. Sanchez J, Ridruejo A, de Andres PL (2020) Diffusion and trapping of hydrogen in carbon steel at different temperatures. Theor Appl Fract Mech 110:102803 9. Xu W, Maksymenko A, Hasan S, Meléndez JJ, Olevsky E (2021) Effect of external electric field on diffusivity and flash sintering of 8YSZ: a molecular dynamics study. Acta Mater 206:116596 10. Xu W, Ramirez K, Gomez S, Lee R, Hasan S (2019) A bimodal microstructure for fatigue resistant metals by molecular dynamics simulations. Comput Mater Sci 160:352–359 11. Hasan MS, Lee R, Xu W (2020) Deformation nanomechanics and dislocation quantification at the atomic scale in nanocrystalline magnesium. J Magnes Alloy 8(4):1296–1303 12. Hasan MS, Berkeley G, Polifrone K, Xu W (2022) An atomistic study of deformation mechanisms in metal matrix nanocomposite materials. Mater Today Commun 33:104658 13. Xu W, Horsfield AP, Wearing D, Lee PD (2018) Classical and quantum calculations of the temperature dependence of the free energy of argon. Comput Mater Sci 144:36–41 14. Bacon DJ, Osetsky YN, Rodney D (2009) Chapter 88 dislocation{\textendash}obstacle interactions at the atomic level. In: Dislocations in solids. Elsevier, pp 1–90 15. Hirel P (2015) Atomsk: a tool for manipulating and converting atomic data files. Comput Phys Commun 197:212–219 16. Thompson AP et al (2022) LAMMPS—a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Comput Phys Commun 271:108171 17. Proville L, Rodney D, Marinica M-C (2012) Quantum effect on thermally activated glide of dislocations. Nat Mater 11(10):845–849 18. Stukowski A (2010) Visualization and analysis of atomistic simulation data with OVITO the open visualization tool. Model Simul Mater Sci Eng 18(1):015012 19. Honeycutt JD, Andersen HC (1987) Molecular dynamics study of melting and freezing of small Lennard-Jones clusters. J Phys Chem 91(19):4950–4963 20. Larsen PM, Schmidt S, SchiØtz J (2016) Robust structural identification via polyhedral template matching. Model Simul Mater Sci Eng 24(5):0–18 21. Wang S, Hashimoto N, Ohnuki S (2013) Hydrogen-induced change in core structures of $\lbrace$110$\rbrace$[111] edge and $\lbrace$110$\rbrace$[111] screw dislocations in iron. Sci Rep 3(1) 22. Wen M (2021) A new interatomic potential describing Fe-H and H-H interactions in bcc iron. Comput Mater Sci 197:110640 23. Mendelev MI, Han S, Srolovitz DJ, Ackland GJ, Sun DY, Asta M (2003) Development of new interatomic potentials appropriate for crystalline and liquid iron. Philos Mag 83(35):3977–3994

Void Nucleation in a Through Silicon Via (TSV): Unraveling the Role of Tilt Grain Boundaries Through Atomistic Investigation Armin Shashaani and Panthea Sepehrband

Abstract Through Silicon Via (TSV) is a technique used in three-dimensional (3D) integrated circuit (IC) packaging to vertically stack layers for the purpose of establishing electrical and mechanical connections. Nevertheless, TSV faces certain challenges that pose risks to its reliability, many of them originated from void formation. Despite its importance, considering the challenges for experimental analysis of the phenomenon, there are a lot of uncertainties about the mechanism of void nucleation. An important parameter affecting void nucleation under stress is the grain type and orientation. This study aims to understand this effect through a systematical analysis, using molecular dynamics simulations. Void formation during tension in the tilt grain boundary and within the grain of a face-centered cubic (FCC) Cu bicrystal is examined. Three misorientation axes— < 100> , < 110> , and < 111 >—with various tilt angles are explored. This study suggests that the level of strain that leads to void nucleation depends on the dislocation network that exists at the grain boundary. Dislocation evolutions throughout loading are examined to define the mechanism of void formation. Keywords TSV · Tilt grain boundary · MD · Void nucleation · Grain orientation · Copper

Introduction Three-dimensional (3D) integrated circuit (IC) packaging is considered as one of the most promising solutions for surpassing Moore’s law limitations and addressing the need for improved performance, smaller sizes, and reduced power usage [1]. This technique involves stacking chips using Through Silicon Vias (TSV) to create both vertical mechanical and electrical connections [1]. In recent years, there has been a A. Shashaani (B) · P. Sepehrband Mechanical Engineering Department, Santa Clara University, 500 El Camino Real, Santa Clara, CA 95053, USA e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_87

1008

Void Nucleation in a Through Silicon Via (TSV): Unraveling the Role …

1009

pronounced surge in the adoption of the Through Silicon Vias (TSV) technique. This is primarily attributed to its numerous advantages, including increased bandwidth, reduced signal propagation delay, improved power management, and a more compact form factor [2]. Due to its low electrical resistance and strong endurance against electromigration, copper has become a preferred choice as the interconnect metal in integrated circuits [3]. Reliability is a primary concern regarding Cu TSVs, which includes stress-induced void formation and the related challenges that could shorten their operational lifespan. The key source of these concerns is the mismatch in thermal expansion coefficients between copper TSVs and silicon wafers. This mismatch can result in concentrated stress areas at weak points within the copper TSVs, leading to the generation of voids [4, 5]. Void formation leads to higher electrical resistance, reduced mechanical strength, device failure, and ultimately a shorter lifetime for the Cu TSVs [6]. The presence of texture and grain structure within the Cu TSVs can intensify localized stress concentration, thereby creating potential sites for void nucleation [7]. Some investigations have been performed on the influence of microstructure on void susceptibility within Cu TSVs [3, 8–11]. Nevertheless, the precise comprehension of the impact of crystallographic texture on void formation remains unclear, and contradicting perspectives exit regarding which texture leads to the highest resistance against void initiation. In some studies, the (111) texture is proposed to show increased resistance against void nucleation [10–12]. On the other hand, it has been shown that Cu TSVs frequently adopt a {111} texture, leading to distinctive [322] twin boundaries that exhibit pronounced susceptibility to void formation [8]. The (100) crystallographic texture has been proposed at a different study as a strong case against void formation, while the (111) texture is reported to exhibit comparatively weaker resistance towards void initiation [9]. Furthermore, films with a (111) found to display higher thermal stress, and as a result higher potential for void formation, when compared to those with a (100) texture [3]. The discrepancy in the literature regarding the impact of grain boundary orientation on void nucleation arises from the absence of systematic investigations into this phenomenon. This includes lack of analysis on how grain boundaries with different tilt angles on identical grain boundary planes behave concerning void nucleation. The experimental preparation of grain boundaries with precisely defined angles involves significant challenges, making experimental analysis of such cases extremely difficult. Molecular dynamics simulation provides an appropriate framework for generating such grain boundaries and analyzing their response to void nucleation, enabling investigation of the underlying mechanisms that govern void nucleation. In our previous work in this area, exclusive attention was given to void nucleation within the < 100 > misorientation axes, covering angles from 0 to 90 degrees [13]. The present study signifies a more extensive investigation of this subject matter. This paper aims to describe how crystallographic orientation affects void nucleation, identify the tilt grain boundary characteristics that offer optimal resistance against void formation, and define the physics that controls void formation. To achieve these goals, molecular dynamics (MD) simulations are employed to detect the onset

1010

A. Shashaani and P. Sepehrband

of void nucleation and analyze the evolution of dislocations under tensile loading in copper bicrystals containing various tilt grain boundaries.

Methodology Molecular dynamics (MD) simulations are conducted using Large-scale Atomic/ Molecular Massively Parallel Simulator (LAMMPS) Simulation package [14]. These simulations are employed to investigate the intricate characteristics of copper utilizing the embedded atom method (EAM) interatomic potential [15]. The investigation focuses on tilt grain boundaries, with crystallographic misorientation axes < 100 > , < 110 > , and < 111 > at varying tilt angles [16]. Each MD simulation includes a configuration comprising two grain boundaries. As shown graphically in Fig. 1, one of these boundaries is located at the simulation box’s y-axis edge. The employment of periodic boundary conditions ensures the correct representation of the system’s repetitive behavior. The dimensions of the simulation box are adjusted in accordance with the specific angle of the tilt grain boundary. Once the state of the lowest energy is established for each individual grain boundary, the simulation box is duplicated in both x- and z-directions to eliminate any unwanted image effects. The overall number of atoms, however, stays the same in every simulation, staying within the range of 350,000 and 900,000 atoms. To ensure the integrity of the simulation results, a thermalization process is carried out on the simulation box. This process involves subjecting the system to isobaric conditions with zero pressure and an isothermal state at 300K temperature. This pre-equilibrium phase, governed by specific thermodynamic conditions, readies the Fig. 1 Schematic of the simulation box

Void Nucleation in a Through Silicon Via (TSV): Unraveling the Role …

1011

system for subsequent analysis. Following the achievement of a state with minimal energy, the simulation is subjected to uniaxial tension applied along the y-direction, with a strain rate of 109 s−1 and at the temperature of 300 K. Notably, the other spatial directions retain a zero-strain status. The simulation timestep is set to 1 fs. Simulation results are analyzed using the OVITO open visualization application [17]. A collection of methods, including construct surface mesh [18], polyhedral template matching (PTM) [19], and common neighbor analysis (CAN) [20] are used to investigate the details of crystallographic defects. The "construct surface mesh" technique is used in each case to identify the initiation of voids. For the comprehensive investigation of dislocations, including the calculation of Burgers vectors and dislocation types, the dislocation extraction algorithm (DXA) [21] integrated within OVITO is utilized.

Results and Discussion MD simulations are employed to study the effect of tilt grain boundary characteristics on void nucleation during tensile loading. Specifically, tilt grain boundaries with grain boundary axes oriented along < 100 > , < 110 > , and < 111 > , with tilt angles spanning from 0 to 180 degrees are investigated. The strain at which void nucleation occurs are computed for all grain boundaries, and these results are presented in the form of a box plot in Fig. 2a and categorized by the grain boundary axis. For each misorientation axis, the box plot illustrates the void nucleation strain ranges, along with median, lower, and upper quartile values. It is noteworthy that the < 111 > case displays the lowest median value for void nucleation strain, while the median values for < 100 > and < 110 > are found to be quite similar. Interestingly, in the case of < 110 > , a substantial variation in void nucleation strain is detected across different tilt angles. This observation suggests that grain boundary axis < 110 > is particularly sensitive to the magnitude of the tilt angle, making it the most susceptible among the studied grain boundary axes. Considering that the strain concentration in the Cu TSV due to the thermal mismatch between Cu and Si can reach as high as 8% [22], in this study, we have defined any void nucleation incident at a strain level less than 9% as detrimental. Similarly, grain boundaries exhibiting greater resistance than this specified threshold are considered as favorable conditions. This threshold value is shown by a red dashed line in Fig. 2a. As an overall observation, it is evident that the < 100 > misorientation axis demonstrates the highest void nucleation resistance compared to the threshold value. This is attributed to the fact that over 80% of the angles exceed the specified threshold. In contrast, the < 111 > misorientation axis displays the lowest resistance, with approximately 50% of the data points falling below the threshold. Furthermore, the < 110 > misorientation axis emerges as a potential candidate for specific applications that demand enhanced strength. This conclusion is drawn from the observation that the distribution of void nucleation strain is notably higher in comparison with the other two misorientation axes.

1012

A. Shashaani and P. Sepehrband

Fig. 2 Box plot for comparing a void formation strain and b grain boundary energy for different misorientation axes

Grain boundary energies for all cases are calculated and shown in a separate box plot in Fig. 2b. While the overall grain boundary energy for the < 110 > grain boundary axis is found to be the lowest, the general trend in distribution of grain boundary energy appears to be different than the void nucleation strain. Such discrepancy suggests that the resistance to void nucleation cannot be directly and solely related to the changes in the grain boundary energy. To understand the effect of grain boundary characteristics on void nucleation, each misorientation axis needs to be analyzed individually.

Void Nucleation in Tilt Grain Boundary with < 100 > Misorientation Axis The plot in Fig. 3 illustrates the relationship between void nucleation strain and the tilt angle for the < 100 > misorientation axis. For most angles, the resistance against void nucleation is found to be within an acceptable range compared to the threshold value. However, certain grain boundary conditions exhibit notably high levels of resistance to void nucleation, while a few angles indicate relatively lower levels of resistance. To understand the mechanism of void nucleation in critical conditions, tilt angles that lead to the highest and lowest resistance to void nucleation are selected for analysis, as highlighted in the Figure. Since the main purpose is to understand the effect of the type and distribution of defects at the grain boundary on void nucleation, special grain boundaries, which feature unique atomic arrangements and are marked by SG in the figure, are excluded from the analysis. Without considering special grain boundaries, tilt angles of 28.07 and 126.87 degrees exhibit the highest resistance to void nucleation. The evolution of dislocations during loading of these two grain boundaries is shown in Fig. 4. In the case of the 28.07-degree misorientation angle, as shown in Fig. 4a–c, a network of

Void Nucleation in a Through Silicon Via (TSV): Unraveling the Role …

1013

Fig. 3 Void nucleation strain versus tilt angle for < 100 > misorientation axes. “HR” as high resistance, “LR” as low resistance, and “SG” as special grain boundary

dislocation initially exists at the grain boundary before straining the system. During loading, the density of dislocations at the grain boundary increases. In such configurations, the proximity between dislocations within the grain boundary region is significantly decreased, creating an environment favorable to dislocation entanglement. This characteristic contributes to the high level of the resistance against void nucleation. However, it’s important to note that under sufficient tension stress that leads to plastic deformation, void nucleation occurs within the grain boundary at dislocation sites which have high energy levels. Conversely, when examining the 126.87-degree tilt angle, a different behavior is observed. Initially, the grain boundary appears free of dislocations, as evident in Fig. 4d–f. This absence of dislocations results from the inability of a dislocation network to compensate for the misorientation between the two grains. As a result, the grain boundary region is occupied by disordered atoms. In this case, void formation is found to occur at dislocations that are generated as a result of plastic deformation. In this context, the presence of dislocations plays a crucial role, providing a path through which vacancies diffuse. While examining grain boundaries with high resistance against void nucleation is crucial, it is equally important to analyze those that exhibit low resistance: grain boundaries with the tilt angles of 11.421, 82.37, and 170.85 degrees. The dislocation networks for these cases are presented in Fig. 5. For all three cases, a characteristic feature of low-angle grain boundaries is observed where prior to deformation, a sparse network of dislocation is present without any evidence of dislocation entanglement (Fig. 5a, d, and g). Essentially, the structural configuration of these tilt grain boundaries at the mentioned angles comprises only a few isolated dislocations. The lack of dislocation entanglement results in a weakened system susceptible to rapid plastic deformation. Consequently, the onset of void nucleation is accelerated, stemming

1014

A. Shashaani and P. Sepehrband

Fig. 4 Various timesteps for the tilt angles of (a–c) 28.07 and (d–f) 126.87 in < 100 > misorientation axes. Dislocations are color-coded: green for Shockley and red for “Other.” Atom types are coded: red for HCP and grey for “Other” structures

from a dislocation within the grain boundary. This sequence of events is effectively illustrated in Fig. 5.

Void Nucleation in Tilt Grain Boundary with < 110 > Misorientation Axis The relationship between void nucleation strain and tilt angle for the < 110 > misorientation axis is illustrated in Fig. 6. An overall examination reveals a wide range of resistance levels against nucleation across various misorientation angles. Notably, certain instances, such as those at 31.59 and 121.01 degrees, exhibit significant resistance, while others, specifically at 53.59 and 102.11 degrees, demonstrate lower resistance. Additionally, a few special grain boundaries exist. Similar to Fig. 3, the special grain boundaries are marked by “SG” and the angles with the high (HL) and low resistance (LR) are highlighted in the figure. Upon analyzing the 31.59-degree angle, no dislocations, but a high level of disordered atoms, are detected prior to deformation and void nucleation found to occur within the grain boundary following subsequent plastic deformation. This behavior mirrors what has been observed for 126.87-degree angle in the < 100 > misorientation axis. In contrast, a different scenario is observed for the grain boundary angle of 121.01 degrees. In this case, a high level of dislocation entanglement within the boundary is observed prior to deformation. Similar to what has been noted in

Void Nucleation in a Through Silicon Via (TSV): Unraveling the Role …

1015

Fig. 5 Various timesteps for the angles of (a–c) 11.421, (d–f) 82.37, and (g–i) 170.85 in < 100 > misorientation axes. Dislocations are color-coded as follows: blue for perfect, green for Shockley, and red for other

Fig. 6 Void nucleation strain versus tilt angle for < 110 > misorientation axes. “HR” as high resistance, “LR” as low resistance, and “SG” as special grain boundary

1016

A. Shashaani and P. Sepehrband

28.07-degree angle in < 100 > misorientation axis, this entanglement strengthens the system, requiring more force and strain for void nucleation. The low resistance observed in both cases of the 53.59 and 102.11-degree angles is attributed to the presences of untangled dislocations at the grain boundaries. Continuous strain application fails to induce entanglement within the system, resulting in premature plastic deformation at lower strain levels. This situation creates favorable conditions for void nucleation, occurring at the intersection of multiple dislocations within the grain boundary.

Void Nucleation in Tilt Grain Boundary with < 111 > Misorientation Axis The relationship between void nucleation strain and tilt angle for the < 111 > misorientation axis is illustrated in Fig. 7. In general, when compared to the two other axes studied, grain boundaries with misorientation axis of < 111 > demonstrate lower resistance to void nucleation. Special grain boundaries, indicated on the figure as “SG,” show notable resistance against void nucleation, particularly in comparison with other boundaries. Excluding the special boundaries, specific angles, such as 118.03 and 130.42 degrees, display significant resistance, while others, including 65.36 and 158.21 degrees, show reduced resistance. Similar behaviors to those observed previously are noted in this condition. In cases characterized by misorientation angles of 118.03 and 130.42 degrees, the high resistance is attributed to the presence of dislocation entanglement within the system. Conversely, angles associated with low resistance, such as 65.36 and 158.21 degrees, lack entanglement, leading to system weakening and void nucleation at low levels of strain.

Void Nucleation Across Grain Boundaries The analysis reveals the importance of plastic deformation and dislocation dynamics in controlling void nucleation. It is seen than when dislocation entanglement occurs at the grain boundary, the strength of the system is increased, plastic deformation is delayed, and a noticeable amount of deformation can be supported prior to void nucleation. On the other hand, when the grain boundary is composed of dispersedly arranged dislocations, the likelihood of dislocation entanglement decreases, leading to early void nucleation as a consequence of prematurely initiated plastic deformation. It is found that any mechanism that can delay plastic deformation can postpone void nucleation as well. Therefore, one of the reasons for observing varying response to void nucleation in the studied grain boundary axes may be linked to the fact that in specific crystallographic directions, the activation of slip systems occurs relatively

Void Nucleation in a Through Silicon Via (TSV): Unraveling the Role …

1017

Fig. 7 Void nucleation strain versus tilt angle for < 111 > misorientation axes. “HR” as high resistance, “LR” as low resistance, and “SG” as special grain boundary

early in comparison to alternative directions. Therefore, plastic deformation starts sooner, thereby creating favorable conditions for void nucleation within the system. The observed critical role of dislocations in void nucleation suggests that the mechanism of void nucleation is likely controlled through vacancy agglomeration, which needs vacancy diffusion that is significantly enhanced by dislocations.

Conclusion This MD simulation study explores how tilt grain boundary characteristics influence void nucleation during tensile loading. Three misorientation axes, < 100 > , < 110 > , and < 111 > , spanning a range of tilt angles, are investigated. Notably, < 111 > grain boundaries exhibited the lowest resistance to void nucleation, while < 100 > and < 110 > showed similar resistance levels. The < 110 > axis displays significant variation in void nucleation strain across different misorientation angles, indicating sensitivity to tilt angle magnitude. The network of dislocations prior and throughout loading is studied. This analysis highlights the importance of plastic deformation and dislocation dynamics in void nucleation control. When dislocations entangle at grain boundaries, they strengthen the system, delaying plastic deformation, and allowing for more deformation before void nucleation. Conversely, dispersed dislocations at grain boundaries trigger early void nucleation as a result of prematurely initiated plastic deformation. Acknowledgements The support for this research was made possible through the SoE 2022 Faculty Research Excellence Grant from Santa Clara University. Computing resources were provided by the Wiegand Advanced Visualization Environment (WAVE) at Santa Clara University.

1018

A. Shashaani and P. Sepehrband

References 1. Kaushik BK, Kumar VR, Majumder MK, Alam A (2016) Through silicon vias : materials, models, design, and performance. Silicon Vias 2. Burkett SL, Jordan MB, Schmitt RP, Menk LA, Hollowell AE (2020) Tutorial on forming through-silicon vias. J Vac Sci Technol Vac Surf Films 38(3):031202 3. Basavalingappa A, Shen MY, Lloyd JR (2017) Effect of texture and elastic anisotropy of copper microstructure on reliability. Proc 2016 IEEE Int Integr Reliab Workshop IIRW 2016:57–60 4. Frank T, Moreau S, Chappaz C, Leduc P, Arnaud L, Thuaire A, Chery E, Lorut F, Anghel L, Poupon G (2013) Reliability of TSV interconnects: electromigration, thermal cycling, and impact on above metal level dielectric. Microelectron Reliab 53(1):17–29 5. Gambino JP, Adderly SA, Knickerbocker JU (2015) An overview of through-silicon-via technology and manufacturing challenges. Microelectron Eng 135:73–106 6. Wang J, Duan F, Lv Z, Chen S, Yang X, Chen H, Liu J (2023) A short review of through-silicon via (TSV) interconnects: metrology and analysis. Appl Sci 13(14):8301 7. Kumar P, Lee TK, Dutta I, Huang Z, Conway P (2021) Microstructure and mechanical reliability issues of TSV. Springer Ser Adv Microelectron 64:71–105 8. Sekiguchi A, Koike J, Kamiya S, Saka M, Maruyama K (2001) Void formation by thermal stress concentration at twin interfaces in Cu thin films. Appl Phys Lett 79(9):1264–1266 9. Koike J, Wada M, Sanada M, Maruyama K (2002) Effects of crystallographic texture on stress-migration resistance in copper thin films. Appl Phys Lett 81(6):1017 10. Feng HP, Cheng MY, Wang YL, Chang SC, Wang YY, Wan CC (2006) Mechanism for Cu void defect on various electroplated film conditions. Thin Solid Films 498(1–2):56–59 11. Ryu C, Kwon KW, Loke ALS, Lee H, Nogami T, Dubin VM, Kavari RA, Ray GW, Wong SS (1999) Microstructure and reliability of copper interconnects. IEEE Trans Electron Devices 46(6):1113–1120 12. Gupta T (2010) Copper interconnect technology. Springer Science & Business Media 13. Shashaani A, Sepehrband P (2023) The effect of grain boundary type on void formation in a through silicon via (TSV). In: TMS 2023 152nd Annual Meeting & Exhibition Supplemental Proceedings. Springer Nature Switzerland, Cham, pp 921–929 14. Plimpton S (1995) Fast parallel algorithms for short-range molecular dynamics. J Comput Phys 117(1):1–19 15. Mishin Y, Mehl MJ, Papaconstantopoulos DA, Voter AF, Kress JD (2001) Structural stability and lattice defects in copper: Ab Initio, tight-binding, and embedded-atom calculations. Phys Rev B 63(22):224106 16. Tschopp MA, Coleman SP, McDowell DL (2015) Symmetric and asymmetric tilt grain boundary structure and energy in Cu and Al (and transferability to other Fcc metals). Integrating Mater Manuf Innov 4(1):176–189 17. Yang L, Ma Z, Stukowski A (2009) Visualization and analysis of atomistic simulation data with OVITO–the open visualization tool. Model Simul Mater Sci Eng 18(1):015012 18. Stukowski A (2014) Computational analysis methods in atomistic modeling of crystals. JOM 66(3):399–407 19. Larsen PM, Schmidt S, Schiøtz J (2016) Robust structural identification via polyhedral template matching. Model Simul Mater Sci Eng 24(5):055007 20. Faken D, Jónsson H (1994) Systematic analysis of local atomic structure combined with 3D computer graphics. Comput Mater Sci 2(2):279–286 21. Stukowski A, Albe K (2010) Extracting dislocations and non-dislocation crystal defects from atomistic simulation data. Model Simul Mater Sci Eng 18(8):085001 22. Liu J, Huang Z, Conway PP, Liu Y (2019) Processing-structure-protrusion relationship of 3-D Cu TSVs: control at the atomic scale. IEEE J Electron Devices Soc 7:1270–1276

Part XXIX

Defects and Properties of Cast Metals

Avoiding the Cold Shut Defect by Introducing the Shape Factor Modifying Chvorinov’s Rule in Aluminum Gravity Die Casting Fu-Yuan Hsu, Chi-Ming Hung, and Zhang-Yuan Luo

Abstract To avoid the so-called cold-shut defect, the relationships among the proposed factors, such as shape factor, mold constant, and critical flow rate, were built up to construct the designing rules for the bottom ingate. An aluminum knuckle casting was cast in various initial mold temperatures to obtain the critical filling flow rate controlled by the cross-sectional area of the bottom ingates with a constant velocity. Using the computational fluid dynamic package, the various magnifying sizes with the same shape as the knuckle castings were modeled, and the maximum critical filling time could be found. Based on the proposed shape factor modifying Chvorinov’s rule, the so-called critical mold constant (Bcold ) and the shape factor (Spcold ) were introduced in this study. From the proposed relationship, the rule of designing the critical bottom ingate size with the minimizing flow rate could be achieved to avoid cold-shut defects. Keywords Aluminum gravity die casting · Cold-shut · Chvorinov’s rule · Mold constant · Shape factor · Critical ingate flow rate

Introduction This study investigates the cold-shut defect of aluminum die casting influenced by the mold constant (B) and the casting shape factor (Sp). Based on the mold constant of the Chvorinov rule and the shape factor proposed by Hsu et al. [1], the critical ingate size to provide a critical minimum flow rate (Qc) required by an arbitrary shape casting for avoiding the formation of the filling defect, so-called the cold-shut defect, is predicted by the innovation equation modified from the Chvorinov rule. F.-Y. Hsu (B) Department of Materials Science and Engineering, National United University, Miaoli City, Taiwan e-mail: [email protected] C.-M. Hung · Z.-Y. Luo Prototyping Centre, Metal Industry Research and Development Centre, Kaohsiung City, Taiwan © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_88

1021

1022

F.-Y. Hsu et al.

In the metal liquid filling process, the liquid metal loses heat into mold material as it contacts the wall of a mold cavity. If the mold filling time is too long (i.e., the flow rate is too little), the phenomenon of the cold-shut defect is inevitably formed during the filling process. Considering heat released into mold material is constant in the Chvorinov rule [2]. The solidification time (t s ) of liquid metal within the mold cavity could be derived from the solidification modulus (M), which is the volume (V ) of casting geometry divided by its surface area (As ). Therefore, the rule is stated as the following equations: 

V ts = B As M≡

n ≈ BM 2

V = B × ts0.5 As

(1a) (1b)

where the unit of the M, solidification modulus or shape modulus, is distant (i.e., m or mm), the B is the mold constant dependent on mold materials and its unit is (m2 / s)0.5 , and the n is the modulus exponent (i.e., 2 in the study of Chvorinov [2]). Hsu et al. [1] used commercial 3D CAD software to measure the volume and surface area of the nine shapes of castings, such as open feeder, sphere, blind feeder, cylinder, cube, bar, cuboid, plate, and brake caliper geometries. For each shape with four different magnifications (e.g., 0.75, 1.0, 1.5, and 2.0), the exponential relationship between the volume and the surface area is illustrated in Fig. 1.

Fig. 1 The exponential relationship between various volumes (V ) and surface areas (As ) of the same geometric shape [1]

Avoiding the Cold Shut Defect by Introducing the Shape Factor …

1023

From this exponential relationship, the shape factor (Sp) for the arbitrary shape of a casting is also derived from its volume (V ) and surface area (As ), using the following equation: V = S p × A1.5 s Sp =

V A1.5 s

(2a) (2b)

Since the exponent of 1.5 for the surface area, the unit of the Sp is dimensionless (i.e., m3 /m3 or mm3 /mm3 ). It is found that a Sp value is a theorem to represent a constant value for each specific shape. In Fig. 1, the Sp value of the sphere shape with various magnifications and sizes is constant and equal to 0.094 (variance of R2 = 1). Considering the exponent of 2 used in the Chvorinov rule, a contour effect such as Sp value could then modify the rule. The modulus M could be rewritten from Eq. 2a to link the rule. M≡

V = S p × A0.5 s As

(3)

Since the M is equal to that in Eq. 1b, a novel equation is then constructed from Eqs. 1b and 3, as shown in the following: V = S p × A0.5 s As  0.5 As B= × Sp ts

M ≡ B × ts0.5 =

(4)

where a linear relationship between the mold constant B and the shape factor Sp is developed. Once the constant value of Sp for an arbitrary shape of casting geometry is measured, its solidification time t s could be calculated from Eq. 4 [1].

Methods In this study, various initial mold temperatures and filling directions were tested, the relationship between the mold constant and the shape factor was constructed, and a critical flow rate (Qc) with a critical cross-sectional area (Ac) of ingate was suggested to avoid the cold-shut formation. An aluminum knuckle was applied in the gravity die experiments with the design of the bottom ingate filling system.

1024

F.-Y. Hsu et al.

Fig. 2 The bottom ingates used for the three orientations of aluminum knuckle castings

Based on Campbellology [3–5], the critical velocity in the bottom ingate filling system below 0.5 m/s is required to avoid the so-called bifilm oxide defect generated from the free surface turbulence during filling through bottom ingates. To simplify the modeling condition setup, the velocity of the bottom ingate on the bottom boundary of the calculation domain is in a constant value of 0.48 m·s−1 . Figure 2 shows the three orientations of the aluminum knuckle with the squared bottom ingate in the constant velocity. The so-called critical flow rate (Qc), which is the minimum flow rate avoiding the cold-shut defect formation, is determined by the critical cross-sectional area (Ac) multiplied by the constant velocity, while the Ac is derived from squaring the critical length (Lc) of the squared ingate. Flow3D CAST™ was applied to model the filling process for the three orientations of the aluminum knuckle. The physical properties of liquid metal, aluminum alloy A356, and mold material, H13 heat-resistance steel, are shown in Table 1a and b, respectively. The initial filling temperature of the liquid aluminum through the bottom ingate is 700 °C (973 K). Three experimental variables of the initial mold temperatures of 350 °C (623 K), 400 °C (673 K), and 450 °C (723 K), are applied for testing the influence of mold temperature. The three orientations of the aluminum knuckle with four magnification ratios at three initial mold temperatures were modeled to find the critical length (Lc) of the side of the squared ingate. The four steps of the modeling procedure are shown in Fig. 3. Various thicknesses of the mold boundary extended from the edges of the cavity in the modeling are 30, 50, 90, and 120 mm, for the four knuckle sizes in the magnification ratios of 0.5, 1.0, 1.5, and 2.0, respectively. Cubic grids with total numbers of 3500,000 were meshed for the calculation domain.

Avoiding the Cold Shut Defect by Introducing the Shape Factor …

1025

Table 1 The physical properties of (a) Aluminum alloy A356 and (b) iron mold for solidification modeling used by Flow3D CAST™ (a) Physical parameters of A356 aluminium alloy Liquidus

Solidus

Solidification properties temperature (K)

884

828

Density (kg m−3 )

2420

2570

K−1 )

1194

1265

Thermal conductivity (W m−1 K−1 )

86.9

185

Latent heat of fusion (J kg−1 )

429,000

Initial temperature (K)

973

Fluid properties surface tension coefficient (N m−1 )

0.86

Contact angle (°)

168

Viscosity (Pa s)

0.00119

Specific heat (J kg

(b) Physical parameters of H13 steel mold Density × specific heat (kg m−3 J kg−1 K−1 )

417,600

Thermal conductivity (W m−1 K−1 )

45

Heat transfer coefficient (W m−2 )

2000

Initial mold temperature (K)

673

723

753

Fig. 3 The four-step modeling procedures for finding the critical dimensions (Lc) of ingates and critical flow rate (Qc) from the experimental variables of the four magnification ratios, the three orientations, and the three mold temperatures for the same shape of the knuckle casting

Results At the mold temperature of 400 °C (673 K), the modeling results of the filling process for the squared ingate size of 12 mm × 12 mm and 14 mm × 14 mm in the V1 orientation are respectively shown in Fig. 4a and b.

1026

F.-Y. Hsu et al.

Fig. 4 The filling sequences for the knuckle casting with an ingate dimension (L) of a 12 mm × 12 mm and b 14 mm × 14 mm (the critical ingate dimension Lc) in the ingate direction V1 at a mold temperature of 400 °C(673 K). The cold-shut defect prediction (the unfilled regions) for the ingate dimensions in c the critical length Lc and d lower than that. Note The color contour indicates the solid fraction

In Fig. 4a, the filling time of 17.6 s is longer than that of 13.0 s in Fig. 4b. In the top portion of the knuckle casting, the large regions with the dark blue color, which indicates the aluminum at a solid state, are shown in Fig. 4a, while those regions with the light blue color, which is the metal next to the solid state, in a similar part of the casting, are shown in Fig. 4b. No cold-shut phenomenon is found during the filling process in Fig. 4b. Figure 4c and d predicts regions where the cold-shut locations are. For the V1 orientation with the ingate size of 12 mm × 12 mm at the mold temperature of 400 °C (673 K), the cold-shut defect was found on the top portion of the casting as shown in Fig. 4d, while with ingate size of 14 mm × 14 mm, no cold-shut region was found as shown in Fig. 4c. Therefore, the ingate size of 14 mm × 14 mm has the critical length (Lc) of 14 mm for the V1 orientation at the mold temperature of 400 °C (673 K). At this critical ingate size, the aluminum liquid with the constant velocity of 0.48 m s−1 flows through this critical cross-sectional area (Ac) of 1.96 × 10–4 (m2 ), providing a critical flow rate (Qc) of 9.40 × 10–5 (m3 /s) into the mold cavity. In Fig. 4c, the filling process lasts for 13.0 s, and the cavity is filled completely. This critical flow rate (Qc) is defined as the minimum flow rate without the cold-shut formation at this mold temperature. From the knuckle’s volume divided by its critical flow rates, the so-called critical filling time tc of these knuckles is defined. This critical filling time implies the maximum filling time allowed for the filling with this critical flow rate without the cold-shut defect’s formation. Inspired by Eq. 1b, a novel linear relationship between this critical filling time (tc) and the casting-shaped modulus (Mc) was proposed, since a similar relationship between the solidification time and the solidification modulus is derived in the Chvorinov rule. In the cold-shut event, the physical meaning of the heat of liquid aluminum during the filling released through the geometric modulus is similar to that in the solidification process. The term of the time in the rule is like the critical filling time. Therefore, the linear relationship√between the modulus of casting Mc and the square root of the critical filling time ( tc) is developed and shown in Fig. 5.

Avoiding the Cold Shut Defect by Introducing the Shape Factor …

1027

Fig. 5 The linear relationship between the solidification moduli (Mc) and the critical maximum filling time (tc) for the knuckle castings at three ingate directions V 1(+ X), V 2(− Z), and H(− Y ) with four magnification ratios at three mold temperatures in the modeling

In Fig. 5, the slope of a linear relation derived from the same orientation with different ratio sizes represents a mold constant influenced by the same geometric shape at a particular mold temperature. Since this relation is derived from the consideration of cold-shut prevention, this slope is defined as the cold-shut mold constant with the subscript of cold, i.e., Bcold , and its unit is mm/s0.5 .

Discussion In Fig. 5, for example, in the V 1 orientation at initial mold temperatures from the low (623 K) to the high temperatures (723 K), the Bcold is from the steep (0.0038 mm/ s0.5 ) to the gradual slopes (0.0023 mm/s0.5 ). It implies that as the Mc is constant, the maximum allowable filling time tc is a longer time at a higher mold temperature. The cold-shut mold constant Bcold is in inverse relation to the filling time tc. Considering the knuckles with three orientations (V 1, V 2, and H) shown in Fig. 2, the hydraulic static pressure distance D against the gravity direction is defined. Socalled the hydraulic cold-shut shape factor Spcold is proposed as the following. As As · D Spcold =  V  = V D

(5)

1028

F.-Y. Hsu et al.

Fig. 6 a The linear relationship between the critical mold constant (Bcold ) and the hydraulic shape factor (Spcold ) for the knuckle castings at three mold temperatures, and b the linear relationship between the critical filling time (tc) and mold temperature (T ) with the four magnification ratios of knuckle casting

where V and As are the volume and surface area of the geometric shape, respectively. The unit of the Spcold is dimensionless (mm3 /mm3 ). Since the same orientation of the geometric shape with various magnification ratios always has a constant value of the Spcold , the three filling orientations of V 1, V 2, and H have the Spcold values of 0.028969, 0.024229, and 0.011515 correspondingly. Applying the slope values (Bcold ) of the linear relations in Fig. 5 to the respective orientations of the Spcold values at the three mold temperatures, a novel linear relationship, of which physical meaning is like the relation in Eq. 4, is developed and shown in Fig. 6a. If deriving a theoretical formula for thermal heat diffusivity between intimal mold temperature (T ) and the maximum critical filling time (tc) is further considered, Einstein’s simplified heat-diffusion concept for calculating carburization thickness X of a carburized steel could be introduced. X=

√

2D · t = K 1 ·

√ t

where t is the diffusion time, D is the heat diffusivity (m2 /s), and K 1 is the slope for this linear equation, which is like the mold constant B in Eq. 1b, and its unit is also the same such as (m/s0.5 ). As known, the equation of the heat diffusivity is the following:   Q D = D0 exp − R·T where D0 is the frequency factor (m2 /s), Q is the energy barrier (J・K/mol), R is the ideal gas constant (J/mol), and T is the temperature (K). Combining the above two equations, a linear equation could be evolved.

Avoiding the Cold Shut Defect by Introducing the Shape Factor …

√ √ X = 2D · t 2 · ln X = ln A − E T1 + ln(t) 2 X = 2D · t   1 2 X = 2 · D0 exp(−E T ) ·t ln(t) = E T1 + 2 ln X − ln A 1 2 X = A · exp(−E T ) ·t ln(t) = E T1 + constant

1029

(6)

where A and E represent the values of 2·D0 and Q/R, respectively. For the same volume of a knuckle geometry at its three mold temperatures, the maximum critical filling time tc, which is proportional relation to the mold temperatures, could be derived from this linear equation. The four linear relations respectively for the four magnified volumes are plotted in Fig. 6b. Once a particular linear relation for a magnified geometrical size is decided, the critical filling time tc of the H13 heat-resistance steel could be predicted.

Conclusions 1. At three mold temperatures of the H13 heat-resistance steel mold, the linear relationship between the cold-shut mold constant Bcold and the hydraulic coldshut shape factor Spcold for avoiding the cold-shut formation in an arbitrary shape of the A356 aluminum castings is developed and shown in Fig. 6a. 2. For the four 4 magnified volumes of the aluminum A356 knuckles, linear relations between the maximum critical filling time tc and the reciprocal of mold temperature of the H13 heat-resistance steel mold are respectively constructed in Fig. 6b. 3. Once the filling direction of the ingate orientation (i.e., Spcold ) is decided, the Bcold and the tc are correspondingly interpolated from the linear relations in Figs. 5 and 6a. 4. If an exact size and mold temperature of the knuckles are determined, the tc could be directly predicted from the linear relation in Fig. 6b. Acknowledgements The authors personally acknowledge the help of the colleagues at Metal Industries Research and Development Centre (MIRDC) Taiwan and the sponsorship of the Ministry of Economic Affair (MOE) Taiwan with the Technology Development Program (TDP), Mold Insdury Chain Overall Digital Transforming Key Technology and Development Program, No: 111-EC-17-A-25-1652.

References 1. Hsu F-Y, Hung C-M, Feng Y-L (2022) The study of validation between the shape factor and mold constant. J Taiwan Foundry Soc 48(2):11–24 2. Chvorinov N (1940) Theory of casting solidification. Giesserei 27, 177–186, 201–208, 222–225

1030

F.-Y. Hsu et al.

3. Campbell J (1991) Castings. Butterworth-Heinemann, Guildford 4. Campbell J (2013) Complete casting handbook, metal casting process, metallurgy, techniques and design. Butterworth-Heinemann, Guildford, pp 666–667 5. Hsu FY (2016) Bifilm defect formation in hydraulic jump of liquid aluminum. Metall Mater Trans B 47(3):1634–1648

Control of Surface Longitudinal Cracks During the Steel Continuous Casting Fengkang Wang, Jie Zeng, and Wanlin Wang

Abstract The surface longitudinal cracks have been one of the most serious defects in the cast products. In this study, the surface longitudinal cracks are mainly attributed to poor lubrication for mold flux by crack, heat transfer of mold, and properties of mold flux analysis. Comparing with the primary mold flux (PMF), the properties of optimized mold flux (PMF) had some changes: (1) the melting temperature of the optimized mold flux was decreased from 1174 to 1142 °C; (2) the wetting angle was increased from 38.64° to 49.96°, which decreased the interfacial wettability; (3) the viscosity (1300 °C) was decreased from 0.684 to 0.398 Pa s, which had a better lubrication effect; (4) the proportion of crystalline layer increased from 62.87 to 70.99%, which increased the crystallization rate; (5) the response temperature decreased from 389 to 356 °C, which resulted in better heat control. The optimized mold flux (OMF) and primary mold flux (PMF) were used to simulate continuous casting process, the optimized mold flux shows excellent performance for the quality of the shell. Keywords Surface longitudinal cracks · Bloom · Continuous casting · Mold flux

Introduction Complex, high-temperature, multiphase, transient physicochemical changes occur in the continuous casting mold, which constrains the study of the formation mechanism of cracks on the surface of the continuous casting steel. The surface defects F. Wang · J. Zeng (B) · W. Wang (B) School of Metallurgy and Environment, Central South University, Changsha 410083, China e-mail: [email protected] W. Wang e-mail: [email protected] National Center for International Research of Clean Metallurgy, Central South University, Changsha 410083, China © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_89

1031

1032

F. Wang et al.

of continuous casting steel were related to mold flux, pouring temperature, casting speed, mold conditions, taper of mold, mold oscillation, etc. [1–3]. Among others, mold flux is critical to the continuous casting process for lubricating the strand as well as controlling the heat transfer in the initial solidification during continuous casting steel [4–7]. In general, the reasons for surface longitudinal cracks may be poor lubrication in the crystallizer, poor physical and chemical properties of the protective slag and crystallizer flow field disorder. An even heat flow is necessary to prevent non-uniform solidification of the steel shell, which can lead to cracking of the cast product. Heat transfer strongly influences the occurrence of surface defects during the initial solidification of the steel in the mold. Medium carbon alloyed steels have a larger shrinkage after solidification, so they are especially prone to cracking. The gap between the mold wall and solidified shell can make the heat transfer hard to control. To minimize this gap, a constant and sufficient supply of liquid flux is essential. Furthermore, mold flux with lower viscosity and melting temperature tend to provide lower friction and better lubrication properties and thus prevent sticking. Mainly manifested as the liquid slag layer of the protective slag is too thin, poor lubrication effect, poor heat transfer performance of the protective slag leads to the friction of the primary billet shell is large, thus forming the casting billet surface longitudinal cracks [8]. Therefore, the optimization of the mold flux properties has the significance for improvement of billet surface quality during steel continuous casting. In this study, surface longitudinal cracks and used mold flux during a typical medium carbon alloyed bloom continuous casting are characterized by optical microscope (OM) and scanning electron microscope (SEM), viscometer, single hot thermocouple technology (SHTT), and the double hot thermocouple technology (DHTT). Then the optimization of the mold flux properties was investigated in detail via the viscometer, SHTT, and DHTT. Finally, the optimized mold flux (OMF) and primary mold flux (PMF) are used to simulate continuous casting process and the optimized mold flux shows excellent performance for the quality of the shell.

Experiment Arrangement As shown in Fig. 1, the bloom with 430 × 350 mm was obtained after continuous casting process. The main chemical compositions of the medium carbon alloyed steel are presented in Table 1. The longitudinal cracks were found in the wide face of bloom. The specimens containing cracks were cut from the wide face of bloom. The specimens were ground, polished, and etched with 4% nital acid solution to observe microstructure and cracks using an optical microscope (OM, Leica DM4 M, Germany). Besides, the morphology and chemical compositions of internal oxide particles near the crack were analyzed and observed using scanning electron microscopy (SEM, TESCANMIRA 3 LMU, Czech Republic) equipped with an Xray energy-dispersive spectrometer (EDS). Moreover, the chemical compositions of

Control of Surface Longitudinal Cracks During the Steel Continuous …

1033

two typical mold fluxes are listed in Table 2, which is often used for continuous casting of bloom. As shown in Fig. 2, the typical medium carbon alloyed bloom longitudinal cracks under primary mold flux during a continuous casting are firstly analyzed and then, the physical and chemical properties of the mold flux by viscometer, single hot thermocouple technology (SHTT), and the double hot thermocouple technology (DHTT). Moreover, proposing optimization of slag based on longitudinal cracking and primary-slag problems and evaluate it. Finally, the optimized mold flux (OMF) and primary mold flux (PMF) are used to simulate continuous casting process, and the surface quality of obtained shells can reveal the application effect of optimized mold flux.

Fig. 1 Production schematic of the bloom

Table 1 Chemical compositions of the bloom Element

C

Mn

Si

Cr

S

P

Al

Fe

Wt.%

0.41

0.73

0.21

1.05

0.0016

0.017

0.005

Bal.

Table 2 Chemical compositions of two typical mold fluxes SiO2

CaO

Al2 O3 Fe2 O3 MgO MnO Na2 O Li2 O B2 O3 F−

Ct

Optimized mold flux (OMF)

26.53 28.37 13.62

1.33

0.72

2.63

5.22

0.52

–

3.34 17.3

Primary mold flux (PMF)

25.54 29.37 10

0

2

2.63

4.22

0.52

2

5

17.3

1034

F. Wang et al.

Fig. 2 Schematic diagram of the experiment procedure

Results and Discussion Characterization of Bloom with Crack and Primary Mold Flux To determine origin of cracking before studying surface crack of bloom, the characterization of bloom with crack is shown in Fig. 3. It is clear in Fig. 3a, b that the whole crack length of bloom can reach 213–443 mm, which seriously affects the production quality. As shown in Fig. 3a–d, crack along the visible decarburization layer and the ferrite with grain boundary are containing Si, Mn, and Cr oxide particles. Moreover, it can be seen from Fig. 4b that the mold flux is found in the crack. Here, we will be such cracks containing mold flux within the crack is called “slagging-type cracks,” which is different from cracks accompanied by depressions. The synthesis of the above analysis of bloom cracks shows that the cracking of bloom surface may be related to the poor lubrication for mold flux. Thus, the physical and chemical properties of the primary mold flux (PMF) during bloom continuous casting need to be analyzed. As shown in Fig. 4, the physical and chemical properties of the mold flux by viscometer, SHTT, and DHTT were analyzed. It was indicated that the melting temperature of the PMF was 1174 °C, which was higher for the medium carbon alloyed steel; the wetting angle was 38.64°, which was the interfacial wettability of high; the viscosity (1300 °C) was decreased from 0.684 Pa·s, which had a terrible

Control of Surface Longitudinal Cracks During the Steel Continuous …

1035

Fig. 3 Characteristics of surface cracks in the bloom: a, b OM from longitudinal cross section of crack, c, d SEM from longitudinal cross section of crack

Fig. 4 The physical and chemical properties of the primary mold flux: a melting, b viscosity, c crystallization, d wetting angle, e response temperature

lubrication effect; the proportion of crystalline layer was 62.87%, and the response temperature was 389 °C, which resulted in better heat control. Thus, the physical and chemical properties of the mold flux need to be adjusted to some extent for providing lower friction and better lubrication properties and thus prevent sticking.

1036

F. Wang et al.

Optimization of Mold Flux As shown in Fig. 5a, it can be seen that both kinds of protective slag have different degrees of heat absorption peaks in the melting process. It can be found that the melting temperature range of the original slag is 1174.3 ~ 1427.8 °C; the melting temperature range of the optimized slag is 1142.3 ~ 1313.2 °C. The initial melting temperature and complete melting temperature of the OMF are lower than those of the PMF, indicating that the optimized slag will have a thicker liquid layer, which ensures sufficient slag consumption and lubrication. Figure 5b shows that the viscosity of the OMF is 0.684 Pa s in the viscosity of 1300 °C, and the viscosity of the OMF is 0.398 Pa s. The viscosity (1300 °C) was decreased from 0.684 to 0.398 Pa s, which had a better lubrication effect. The viscosity of the PMF rose gently after the beginning of the temperature reduction at 1300 °C, and there was no turning temperature, which was an acidic slag. The OMF had a transition temperature of 1178 °C, with the liquid slag flowing into the crystallizer slag channel, the temperature of slag films decreased, the OMF appears crystalline layer faster. As shown in Fig. 5b, the interface wetting angle of the OMF and PMF was 38.64° and 49.96°, respectively. This indicates that the interfacial tension of the OMF is less than that of the PMF. Besides, as shown in Fig. 5b, comparing with the PMF, crystalline layer of OMF increased from 62.87 to 70.99%, which increased the crystallization rate. The response temperature decreased from 389 to 356 °C, which resulted in better heat

Fig. 5 The physical and chemical properties of the primary/optimized mold flux: a melting, b viscosity, c wetting angle, d response temperature, e crystallization

Control of Surface Longitudinal Cracks During the Steel Continuous …

1037

Table 3 The physical and chemical properties of two typical mold fluxes Melting temperature

Melting rate

Wetting angle

Viscosity (1300°C)

Break temperature

PMF

1174.3–1427.8 °C

21 ± 2s

38.64 ± 2.14°

0.684 ± 0.005Pa·s

–

OMF

1142.3–1413.2 °C↓

20 ± 1s↓

49.96 ± 1.40°↑

0.398 ± 0.003Pa·s↓

1178 °C

Response temperature

Glass layer

Crystalline layer

Liquid layer

PMF

389.3 °C

28.7%

62.9%

8.4%

OMF

356.4 °C↓

15.93%

70.99%↑

13.08%↑

control. Above all, as shown in Table 3, with the changes of physical and chemistry properties of optimized mold flux, the optimized mold flux can be reduced significantly to the incidence of longitudinal cracking in actual production.

Application Effect of Mold Flux The lubrication behavior and heat control of the protective slag were regulated by changing the composition of the protective slag. As shown in Fig. 6, using OMF for simulation experiments, the surface of the billet shell obtained was relatively flat, and a uniform and continuous slag film was formed between the protective slag and the shell. The reason why the optimized slag will have a better effect is that compared with the original slag, the viscosity and melting temperature of the optimized slag has been reduced, so that the fluidity of the protective slag is good, the protective slag penetrates uniformly, and the heat transfer between the solidified billet shell-slag film-copper mold is stable. Therefore, in order to adjust the physical and chemical properties of the protective slag, through the original slag and the optimized slag of the high-temperature thermal simulation Mold Simulator experimental simulation results show that the appropriate increase in the alkalinity of the protective slag, reduce the melting temperature and viscosity, as well as to enhance the control of heat can be suppressed the initial solidification of 42CrMo molten steel crater defects.

1038

F. Wang et al.

Fig. 6 The surface quality of shells and slag flims under different mold flux: a, c Primary mold flux, b, d Optimized mold flux

Conclusions The control of surface longitudinal cracks during the steel continuous casting was investigated by optimizing mold flux. The main conclusions were drawn as follows: (1) It is indicated that the crack length of bloom reached 213–443 mm, crack along the visible decarburization layer, ferrite with grain boundary containing Si, Mn, and Cr oxide particles, and the mold flux was found in the crack. Moreover, primary mold flux had a poor the physical and chemical properties. (2) The physical and chemistry properties of optimized mold flux were changed by appropriately reducing the melting point and viscosity of the protective slag, and improving the heat control performance to provide lower friction and better lubrication properties. (3) The optimized mold flux (OMF) and primary mold flux (PMF) are used to simulate continuous casting process; the optimized mold flux shows excellent performance for the quality of the shell. Acknowledgements The financial support for this work from the National Natural Science Foundation of China (52274342, 52130408) is gratefully acknowledged. Conflict of Interest The authors declare that they have no conflict of interest in this paper. All the authors listed have approved the manuscript.

Control of Surface Longitudinal Cracks During the Steel Continuous …

1039

References 1. Cibulka J, Krzok R, Hermann R, Bocek D, Cupek J, Michalek K (2016) Impact of oscillation parameters on surface quality of cast billets. Arch Metall Mater 61(1):283–288 2. Brimacombe JK, Weinberg F, Hawbolt EB (1979) Formation of longitudinal, midface cracks in continuously-cast slabs. Metall Trans B 10:279–292 3. Mahapatra RB, Brimacombe JK, Samarasekera IV (1991) Mold behavior and its influence on quality in the continuous casting of steel slabs: Part II. Mold heat transfer, mold flux behavior, formation of oscillation marks, longitudinal off-corner depressions, and subsurface cracks. Metall Mater Trans B 22:875–888 4. Thomas BG, Jenkins MS, Mahapatra RB (2004) Investigation of strand surface defects using mould instrumentation and modelling. Ironmak Steelmak 31(6):485–494 5. Seo MS, Sohn I (2019) Substitutional effect of Na2 O with K2 O on the viscosity and structure of CaO–SiO2 –CaF2 -based mold flux systems. J Am Ceram Soc 102(10):6275–6283 6. Yan W, Zhang G, Li J (2020) Viscosity and structure evolution of CaO–SiO2 -based mold fluxes with involvement of CaO–Al2 O3 -based tundish fluxes. Ceram Int 46(9):14078–14089 7. Yoo S, Cho JW, Park SH, Park MS, Park JK, Moon KH (2020) Slag pool depth effectiveness of molten mold flux feeding technology. Metall Mater Trans B 51:1965–1972 8. Wei EF, Yang YD, Feng CL, Sommerville ID, McLean A (2006) Effect of carbon properties on melting behavior of mold fluxes for continuous casting of steels. J Iron Steel Res Int 13(2):22–26

Effect of RE Content on TiN Inclusions Formation in P110-Grade Casing Steel Jinwen Liu, Haiyan Tang, Gen Li, Kaimin Wang, Yuhang Wang, and Jiaquan Zhang

Abstract Hydrogen resistance and sulfide stress corrosion resistance of casing steels are severely impaired by large TiN inclusions. Rare earth elements have the potential to modify the properties of non-metallic inclusions in steels. The effect of RE content on the formation of TiN inclusions in P110-grade casing steel has been investigated based on industrial trial. The results show that the main types of inclusions formed in the casing steel without RE addition are pure TiN and composite Ca(-S)-Al(-Mg)-O + TiN, while pure TiN and composite RE-P(-As) + TiN or composite RE-O(-S-Ca) + TiN after RE addition. The number density of TiN inclusions in the rolled products decreases with increasing RE content (0, 0.0160%, 0.0197%), but the average size of TiN inclusions becomes smaller and then larger. Thermodynamic calculations show that increasing the RE content in casing steel reduces the precipitation temperature of TiN inclusions, which inhibits the precipitation of TiN inclusions. Keywords Casing steel · Rare earth · TiN · Inclusions

Introduction Oil casing is an essential structural component in oil and gas production, requiring high strength, toughness, hydrogen induced cracking (HIC) resistance, sulfide stress corrosion cracking (SSC) resistance, and other steel properties [1, 2]. TiN is a cubic rigid inclusion with high melting point and hardness. In particular, the large-sized and low plasticity of TiN will adversely affect the material properties and surface J. Liu · H. Tang (B) · K. Wang · Y. Wang · J. Zhang School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China e-mail: [email protected] G. Li Institute of Special Steels, Central Iron and Steel Research Institute Co., Ltd., Beijing 100081, China © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_90

1040

Effect of RE Content on TiN Inclusions Formation in P110-Grade …

1041

quality, etc. [3]. TiN inclusions adversely affect the corrosion resistance of highpurity ferritic stainless steel [4]. Some large TiN inclusions have been discovered in oil casing steel [5], which will seriously impact the corrosion resistance of oil casings. Many studies [6–9] indicate that TiN inclusions commonly precipitate during the solidification process. The high solubility of Ti and N in molten steel normally does not result in the formation of TiN. Nevertheless, TiN will precipitate when its activity product exceeds the saturated activity product as the steel temperature decreases during solidification. Li et al. [10] demonstrated that Ce is unable to directly deform TiN inclusions, but it can effectively reduce the size of composite TiN inclusions by reducing the nucleation core size through the transformation of Al2 O3 inclusions into spherical CeAlO3 inclusions. Zhang et al. [11] demonstrated that an increase in the rare earth (RE) content results in a higher number of rare earth inclusions at grain boundaries; it inhibits the precipitation of TiC at these interfaces, leading to a decrease in the quantity of large-sized TiC and Ti(C,N). Zhang et al. [12] demonstrated that increasing the N content enhances the precipitation of TiN, leading to TiN and TiC precipitation even 3.5 °C below the liquidus temperature. Furthermore, the complete solidification temperature of the steel decreases by 3.7 °C. In order to regulate the precipitation and growth of TiN inclusions, it is essential to control the contents of Ti and N in the raw material, and a reasonable cooling process should also be carried out [7, 8]. The study investigated the effect of RE content on the formation of TiN inclusions in rolled tubes, using 30MnCr petroleum casing steel as a representative steel.

Experimental The casing steel for two industrial trial groups was produced by the following process: 150 t electric arc furnace (EAF) → ladle furnace (LF) → vacuum degassing (VD) → six-stream round billet continuous casting → heating and tube rolling. One of the industrial trial groups without RE was labelled as Scheme A. Aluminum was added as a deoxidizer when tapping in the EAF. Subsequently, white slag was added in the LF to encourage desulphurisation and deoxygenation. After degassing in the VD furnace, 300 m of pure calcium were fed, and the molten steel was cast following 15 min of soft blowing. The final shape of the round billet was achieved through rolling, piercing, and expanding processes to form the rolled tube. Another industrial trial group with RE addition, named Scheme B, resembles Scheme A with the exception of the VD process. Calcium was fed, and Ar-gas was softly blown for 8 min before increasing the flow of argon to expose the steel surface. Subsequently, 110 kg of RE alloys (w(La) ≥ 19%, w(Ce) ≥ 38%) packed by iron containers were introduced, and the molten steel was cast following 10 min of soft blowing. The samples obtained from rolled tubes were named as A-R1 and B-R1, B-R2. The liquid steel was mixed in the tundish with and without RE during casting, resulting in variations in RE content of the billets and tubes produced, which also affected the

1042

J. Liu et al.

TiN inclusions. Consequently, tube samples with RE were taken from two separate tubes in Scheme B. The contents of Ce, La, P, and As were obtained via the inductive coupled plasma emission spectrometer (ICP). The content of total oxygen (T.O.) and N was determined by the infrared absorption method (TCH 600, LECO). Other elemental compositions were analyzed by an optical emission spectrometer (OES). 10 mm × 10 mm × 8 mm metallographic samples were taken from rolled tubes. Samples from tubes were detected and analyzed by using SEM-EDS (Phenom Pro) to obtain the morphology and chemical composition of the TiN inclusions. The number, composition and size of TiN inclusions in those samples were also analyzed by an automatic scanning analyzer system (EVO18).

Results Chemical Compositions The chemical compositions of the rolled tubes are shown in Table 1, and the RE content (theoretical addition of w([La]) = 0.0139%, w([Ce]) = 0.0278%) in the rolled tubes is shown in Table 2. The mixing of molten steel in the tundish results in a lower RE content in the B-R1 compared to the B-R2, as presented in Table 2.

Morphology of TiN Typical TiN Inclusions in Scheme A There are two typical TiN inclusions in Scheme A, one is pure TiN alone, as shown in Fig. 1a, and the other inclusion is a composite TiN, consisting of a Ca(-S)-Al(-Mg)-O core surrounded by an outer layer of TiN, as shown in Fig. 1b. As the steel is produced by the method of aluminium deoxidation with calcium treatment, Ca(-S)-Al(-Mg)-O inclusions are formed in the liquid steel [5]. During solidification and cooling, TiN precipitates with the inclusions as the nucleation centre and adheres around them to form composite TiN inclusions.

Typical TiN Inclusions in Scheme B There are two typical TiN inclusions in Scheme B, one is pure TiN alone, as shown in Fig. 2a, and the other inclusion is a composite TiN, comprising a RE-O(-S-Ca) or RE-P(-As) core bonded by an external layer of TiN, as shown in Fig. 2b, c. Inclusions of RE-O(-S-Ca) or RE-P(-As) were formed after the addition of RE to

0.259

0.2853

B

Si

0.273

C

0.2963

Scheme

A

Table 1 Chemical composition (wt%)

Mn

1.427

1.403

P 0.011

0.0104

As 0.0038

–

S 0.0014

0.0015

Als 0.024

0.0255

Ti 0.0055

0.0066

Ca 0.0018

0.0020

N 0.0037

0.0040

T.O. 0.0011

0.0013

Effect of RE Content on TiN Inclusions Formation in P110-Grade … 1043

1044

J. Liu et al.

Table 2 Content and yield of RE in steel of Scheme B (%) Sample

w([Ce])

w([La])

w([Ce + La])

Yield of RE

B-R1

0.011

0.0050

0.0160

38.4

B-R2

0.014

0.0057

0.0197

47.2

Fig. 1 Typical inclusions in Scheme A [5]

the steel [5]. During the solidification and cooling process, these inclusions acted as the nucleation centre, and then TiN precipitated and attached around them to form composite inclusions.

Statistic Results on TiN Inclusions Metallographic specimens of Schemes A and B were analyzed by an automatic scanning analyzer system after grinding and polishing. The sample scanning area is approximately 20 mm2 ; the minimum inclusion size of TiN is 1.5 µm.

Number Density of TiN Inclusions The number density of TiN inclusions in rolled tubes was analyzed, as shown in Fig. 3. It illustrates that the number of TiN inclusions in the rolled products decreases with increasing RE content. The explanation for this will be analyzed later.

Effect of RE Content on TiN Inclusions Formation in P110-Grade …

1045

Fig. 2 Typical inclusions in Scheme B [5] Fig. 3 Number density of TiN inclusions

Size Distribution of TiN Inclusions The size distribution of TiN inclusions is shown in Fig. 4, and the average size of TiN inclusions is shown in Fig. 5. The majority of inclusions are less than 5 µm in size, while inclusions in the 5–10 µm are primarily pure TiN. Especially in the B-R2 sample, the proportion of pure TiN inclusions of 5–10 µm reaches as high as 13%. This could be due to the different RE content in the steel, which leads to different effects on TiN inclusions during the rolling heating process [13]. The average sizes of A-R1 and B-R1 in the rolled tube are similar, but B-R1 is slightly smaller than

1046

J. Liu et al.

Fig. 4 Ratio of TiN inclusions of different sizes Fig. 5 Average diameter of TiN inclusions

A-R1, while B-R2 has a larger average size. This suggests that the average size of TiN inclusions decreases and then increases as the RE content increases.

Aspect Ratio of Inclusions The average aspect ratio of TiN inclusions is presented in Fig. 6. It demonstrates that the average aspect ratio of pure TiN inclusions is greater, suggesting their irregular shape, which could have a more detrimental effect on the steel matrix. The cores of composite TiN inclusions, such as Ca(-S)-Al(-Mg)-O, RE-P(-As), or RE-O(-SCa), have low average aspect ratios that are not significantly altered following the

Effect of RE Content on TiN Inclusions Formation in P110-Grade …

1047

Fig. 6 Average aspect ratio of TiN inclusions

precipitation of TiN inclusions. Consequently, the resulting composite inclusions also have low average aspect ratios.

Thermodynamic Formation Condition of TiN The thermodynamic condition of TiN formation is shown in Eq. (1): [Ti] + [N] = TiN(s) ∆G θ = −291,000 + 107.91T K =

1 aTiN = a[Ti] · a[N] f [Ti] · w([Ti]) · f [N] · w([N]) ∑ j lg f i = ei · w([ j]),

(1) (2) (3)

where ∆Gθ is the Gibbs free energy of TiN generation; T is temperature; K is the equilibrium constant; aTiN , a[Ti] , and a[N] are the activities of TiN, [Ti], and [N]; f Ti and f N are the activity coefficients of Ti and N; w([Ti]) and w([N]) are the mass j fractions of Ti and N, respectively. ei is the first interaction coefficient (as shown in Table 3); w([ j]) is the mass percent of j. In Eq. (2), when aTiN = 1, both sides take the logarithm of 10 at the same time, and Eq. (2) can be simplified to Eq. (4): lg K = −(lg f [Ti] + lg f [N] + lg w([Ti]) + lg w([N])).

(4)

0.05

− 0.165

0.13

Ti

N

0.047

Si

C

ei

j

− 0.0064 0.045

0.0043

P

− 0.021

Mn 0.004 − 0.028

Al

Table 3 First interaction coefficients of elements in molten steel(1873 K)

0

− 1.8

N 0.013 − 0.53

Ti 0.05

− 1.8

O

0.007

− 0.11

S

− 1.23

Ce

− 0.157

Ca

1048 J. Liu et al.

Effect of RE Content on TiN Inclusions Formation in P110-Grade …

1049

The value of lgf [Ti] is − 0.0391 and lgf [N] is 0.0182 for scheme A-R1; lgf [Ti] is − 0.0566 and lgf [N] is 0.0163 for scheme B-R1; and lgf [Ti] is − 0.0612 and lgf [N] is 0.0163 for scheme B-R2. The reaction equilibrium constant K also can be expressed as Eq. (5): lg K = −

15,098.09 ∆G θ = − 5.6358. 2.303RT T

(5)

Combined Eqs. (4) and (5), lg f [Ti] + lg f [N] + lg w([Ti]) + lg w([N]) = −

15,098.09 + 5.6358. T

(6)

The precipitation temperature of TiN with varying RE contents is displayed in Fig. 7. The data indicate that the precipitation temperature of TiN decreases as the RE content increases, which means that increasing RE content in steel can inhibit the formation of TiN inclusions. It offers a reasonable explanation for the decline in the number density of TiN inclusions in the rolled tubes, as the RE content increases. The value of lgf [Ti] and lgf [N] was used to derive the relationship between the concentration product and temperature, as Eqs. (7–9): Scheme A-R1 without RE: lg(w([Ti]) · w([N])) = −

15,098.09 + 5.6567 T

(7)

Scheme B-R1 with RE: lg(w([Ti]) · w([N])) = −

15,098.09 + 5.6761 T

(8)

Scheme B-R2 with RE: lg(w([Ti]) · w([N])) = −

Fig. 7 Precipitation temperature of TiN with different RE content

15,098.09 + 5.6807. T

(9)

1050

J. Liu et al.

Fig.8 Equilibrium curves of N–Ti at different temperatures a A-R1 (without RE); b B-R1(w([RE]) = 0.0160%); c B-R2 (w([RE]) = 0.0197%)

The equilibrium curves for N–Ti at different temperatures for schemes A-R1, BR1, and B-R2 are presented in Fig. 8. Red dots represent the actual detected Ti and N contents. It implies that TiN inclusions are relatively difficult to precipitate with RE addition.

Conclusion 1. The main types of inclusions formed in the casing steel without RE addition are pure TiN and composite Ca(-S)-Al(-Mg)-O + TiN, while pure TiN and composite RE-P(-As) + TiN or composite RE-O(-S-Ca) + TiN after RE addition. 2. The number of TiN inclusions in the rolled products decreases with increasing RE content (0, 0.0160%, 0.0197%), but the average size of TiN inclusions becomes smaller and then larger. 3. Thermodynamic calculations show that increasing the RE content in casing steel reduces the precipitation temperature of TiN inclusions, which inhibits the precipitation of TiN inclusions.

Effect of RE Content on TiN Inclusions Formation in P110-Grade …

1051

References 1. Zhang ZH, Liu M, Liu YH (2018) A systematical analysis with respect to multiple hydrogen traps influencing sulfide stress cracking behavior of API-5CT-C110 casing steel. Mater Sci Eng A Struct Mater Prop Microstruct Process 721:81–88 2. Li B, Yang FF, Liu HS (2020) Effect of solidification structure on banded defects of high strength corrosion resistant tubes. Iron Steel 55(3):87–95 3. Zhou MW, Yu H (2012) Effects of precipitates and inclusions on the fracture toughness of hot rolling X70 pipeline steel plates. Int J Miner Metall Mater 19(9):805–811 4. Nan H (2021) Effect of TiN inclusion on pitting of an ultra-pure ferritic stainless steel. Corros Prot 42(9):22–27 5. Liu JW, Tang HY, Li G (2023) Effect of rare earth on inclusions in a high-strength corrosion resistant steel. Iron Steel 58(5):70–82 6. Zhu Q, Xu JL, Xiao HT (2019) Mechanism of TiN precipitation in corrosion resistant alloys. J Iron Steel Res 31(11):1023–1030 7. Ma WJ, Bao YP, Zhao LH (2014) Control of the precipitation of TiN inclusions in gear steels. Int J Miner Metall Mater 21(3):234–239 8. Liu HY, Wang HL, Li L (2011) Investigation of Ti inclusions in wire cord steel. Ironmak Steelmak 38(1):53–58 9. Fu J, Zhu J, Di L (2000) Study on the precipitation behavior of TiN in the microalloyed steels. Acta Metall Sin 36(8):801–804 10. Li HW, Yang JC, Zhang J (2015) Precipitation behaviors of titaniferous inclusions in ceriumcontaining IF steel. J Iron Steel Res 27(9):49–52 11. Zhang YY, Peng J, Zhang F (2022) Effect of rare earth cerium on precipitation of TiC and Ti(C, N) in titanium microalloyed steel. J Iron Steel Res 34(10):1160–1168 12. Zhang XY, Peng J, Peng JH (2022) Study on nitrogen content for thermodynamics of inclusion precipitation in rare earth steel. Chinese Rare Earths 43(6):1–8 13. Zhan DP, Yang YK, Jiang ZH (2021) A review of research on inclusions evolution in steel during heating process. Iron Steel 56(10):16–27

How Various Inoculants and Their Amount Influence on the Metal Expansion Penetration in Grey Cast Iron Component Izudin Dugic

Abstract In some grey cast iron components, which are cast in sand moulds, the metal sometimes penetrates into the mould producing defects and causes difficulties when cleaning the components. To improve knowledge of the metal penetration mechanism, a series of test casting was performed in production scale where the influence of different inoculants and different amounts was studied. Investigation of the various inoculants shows that the inoculation of grey cast iron will influence the metal expansion penetration in areas with late solidification times. The amount of inoculant added shows a clear effect on the degree of metal penetration. The whole casting process was simulated with the software MagmaSoft® in order to investigate the solidification characteristics as well as the porosity in the casting component. Keywords Grey cast iron · Metal expansion penetration · Inoculant · Casting simulation · Solidification

Introduction The solidification of grey cast iron is a process that increases in complexity with the addition of further elements and can be controlled by the chemical composition, melting operation, inoculation treatment, and the cooling condition during solidification [1, 2]. The most widely used commercial grey cast irons are hypoeutectic, in which solidification starts with the nucleation and growth of austenite dendrites. It is well known that primary austenite in hypoeutectic grey cast iron grows in a dendrite mode under common industrial cooling conditions. According to Heine et al. [3], the eutectic growth in grey cast iron occurs over a range of temperatures and the temperature intervals for both dendritic and eutectic cell growth overlap. The temperature I. Dugic (B) Faculty of Technology, Department of Mechanical Engineering, Linnaeus University, 35195 Vaxjo, Sweden e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_91

1052

How Various Inoculants and Their Amount Influence on the Metal …

1053

range for growth and the extent of overlapping should be considered as a major factor in the solidification process. The microstructure is the most important factor which determines the properties of grey cast iron. The microstructure depends on the interaction between the effects of the chemical composition and the cooling rate during and after solidification in the mould [2, 4, 5]. To increase the nucleation efficiency of the melt, thereby decreasing the risk for the white solidification as well as increasing the number of eutectic cells, inoculation can be added to the melt before or during the casting. There are great numbers of inoculants with different chemical compositions. Most inoculants are based on silicon, with additions of several minor elements, e.g., Al, Ca, Sr, Ba, and Ti. With the addition of inoculants (typically 0.10–0.40%) to a cast iron melt, heterogenous nucleation sites will be created as well as more eutectic cells [6–8]. An understanding of the nucleation mechanisms is of vital importance to the foundry industry since a bad inoculation will often give defective components due the porosity, cementite formation, or poor surface quality. One important type of defect is caused by metal penetration into the sand mould [9–14]. The general definition for metal penetration accepted by the foundry industry, as proposed by Draper and Gaindar, is the condition in which liquid metal has entered the intergranular space of the moulding material, up to and beyond the first layer of sand grains [15]. To improve knowledge of the metal penetration mechanism, a series of test casting was performed in production scale where the influence of different inoculants and different amounts was studied on casting component in a production scale. Two series of experiments were done. In the first experimental series, five different inoculants were investigated. In the second experimental series, one of these inoculants was chosen and added at different levels and at different temperatures.

Experimental Alloys and Other Materials Melting was done in a high frequency furnace with a charge composition of 40% recycled metal, 20% pig iron and 40% steel. After melting, the melt is transported to a 35-ton holding furnace. From holding furnace, the metal is transported in 1 ton pouring ladle to a production line. The chemical composition was determined from cast coin specimens using the light emission spectrometer—ARL 3460. The coins were cast immediately before the melt was poured into the moulds. The chemical composition for the experiments is shown in Table 1.

1054

I. Dugic

Table 1 Chemical composition of the melts and pouring temperatures Experiments

C Exp I

Exp II

Cequ *

Element in wt.% Si

Mn

P

S

Cr

Cu

1

3.36

2.15

0.80

0.101

0.077

0.05

0.26

4.110

2

3.35

2.15

0.80

0.099

0.077

0.05

0.27

4.099

3

3.34

2.13

0.81

0.102

0.075

0.05

0.27

4.084

4

3.33

2.12

0.81

0.102

0.073

0.05

0.26

4.071

5

3.32

2.10

0.80

0.101

0.072

0.05

0.27

4.054

6

3.38

2.03

0.82

0.106

0.090

0.05

0.30

4.092

7

3.39

2.10

0.81

0.104

0.084

0.05

0.29

4.125

8

3.37

2.13

0.82

0.107

0.086

0.05

0.30

4.116

* Cequ = % C + 1/3(% Si + % P)

Table 2 Chemical composition of the inoculants Inoculant

% Si

% Ca

% Al

% Zr

% Mn

% Ba

% Sr

% Ti

A

72–78

Max 0.1

Max 0.5

–

–

–

0.6–1.0

–

B

73–78

0.09

0.48

–

–

–

0.6–1.0

–

C

59–65

1.5–3.0

1.0–1.5

–

9.0–11.0

4.0–6.0

–

– 9.0–11.0

D

51–55

1.0

1.0–1.3

–

–

–

–

E

44–50

2.5–3.5

1.0

1.5–2.0

–

–

–

Inoculants The choice of inoculant used in grey cast iron production today is probably one of the most important parameters in obtaining good quality castings. The inoculant selected determines the structure of the grey cast iron, and it was believed that it may also affect the amount of metal expansion penetration. Scanning through the products sheets from several inoculant suppliers, five inoculants were selected for testing for the first experimental series. Inoculants A and B have about the same base composition but come from different suppliers. For the second experimental series, one of these inoculants was chosen; inoculant E, containing aluminium and zirconium. The chemical composition of the inoculants and their denomination are shown in Table 2.

Experimental Procedures A typical casting component from production was selected as shown in Fig. 1. The casting component studied was named XY, and eight castings were mounted on the

How Various Inoculants and Their Amount Influence on the Metal …

1055

pattern plate. The geometry of the pattern is shown in Fig. 2. The weight of each component is 7.8 kg, the weight of the gating system is 15.6 kg, and the total casting weight is 78 kg. The castings were made in green sand moulds with a Seiatsu production line. The sand analyze is shown in Table 3. The mould hardness was measured at the critical places where metal penetration is often seen to occur. The average hardness value for all moulds was 80, measured with a GF-meter. In the experiment with five different inoculants, for each of the five inoculants, six flasks were moulded and cast. This yields a total of 30 flasks, and consequently 240 castings, thereby providing a sound statistical basis for evaluation of the effect of inoculants on the metal expansion penetration. All the casting experiments were made within 50 min. The amount of inoculant added was 0.14% for all experiments. In the second experimental series, the amounts of inoculant E added were: 0.05, 0.15, and 0.30%. For each of the three different amounts of inoculant and each of

“Side” (Bulb)

“Beneath”

Fig. 1 Casting component XY. The arrows show the areas where surface defects usually occur

Fig. 2 Geometry of the casting components—lower and upper parts

1056

I. Dugic

Table 3 Sand analyze used in the experiments Experiment

Sand

I

II

Temperature, °C

39

41

Bentonite, %

6.60

6.50

Carbon, %

3.40

3.25

Moisture content, %

2.80

2.75

Compaction pressure, %

28.40

29.00

Gas permeability, cm4 /s

110

120

Table 4 Casting temperatures and denomination for the flasks Pouring ladle no.

Inoculant amount in %

Casting temperatures (°C)

1

0.05

1440

1410

1390

2

0.15

1420

1390

1370

3

0.30

1420

1400

1370

the three different casting temperatures, four flasks were moulded and cast, except for one experiment with three flasks using 0.05% of the inoculant and a casting temperature of 1440 °C. The desired casting temperature was achieved by cooling the melt in the pouring ladle. The casting temperatures and denomination for each flask are shown in Table 4. This yields a total of 35 flasks, and consequently 280 castings, thereby providing a sound statistical basis for evaluation of the effect of inoculant amount and casting temperatures on metal expansion penetration. For both experimental series, the inoculation was made in the stream when pouring the melt from the holding furnace to the pouring ladle.

Experimental Results Castings Inspection After sand blasting, all casting components were investigated by an ocular inspection. The results from the first experimental series are given in Table 5 and from the second experimental series in Table 6. The severity of the metal penetration is measured as a “length * width” (in mm2 ) in a penetration area. The metal penetration often occurs in two locations on this casting. These locations are shown in Fig. 1, where the locations are called “side” and “beneath” respectively. The following parameters of the castings have been calculated by manual methods for each inoculant: average area of metal penetration in mm2 , percentage of castings having metal penetration defects, and percentage of casting having surface shrinkage

How Various Inoculants and Their Amount Influence on the Metal …

1057

Table 5 Average casting defects calculated for the first experimental series Inoculants Metal penetration in

mm2

Metal penetration in % Shrinkage in %

A

B

C

D

E

45.30

97.93

86.08

112.23

22.18

46.03

76.78

59.57

64.58

34.09

3.17

8.93

12.77

4.16

13.63

defects in any location. The average area of metal penetration in mm2 is calculated as the total area of metal penetration defects in the two critical places divided by the total number of castings examined. In the experiments made to investigate the influence of the amount of the inoculant and the pouring temperature, another type of surface defect was seen to be formed; called a bulb. The bulb is shown in Fig. 1. The bulb often occurs in the same places as metal penetration. The surface of the bulbs was as smooth as the casting but gave a little excess material on the surface. These results are shown in Table 6.

Microstructure Analysis and Eutectic Cell Size The penetration areas were analysed metallographically in an optical microscope. Etching was performed in “Steads etching solution” (10 g copper chloride, 40 g magnesium chloride, 20 ml hydrochloric acid dissolved in 1000 ml 95% ethyl alcohol). The etching time was 5 min at room temperature. After etching, the samples were rinsed in ammonium hydroxide to remove the precipitated copper. In Figs. 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 and 16, micrographs are shown of the microstructure and eutectic cell size close to the metal penetration areas.

Casting Simulation When examining the casting, it was observed that component no. 5 (see Fig. 2) consistently showed a larger tendency for surface defect formation. In order to investigate if these defects are related to a different solidification path in component no. 5, a series of simulations were performed with the software MAGMASOFT® ™ using the add on module MAGMAiron® ™. A complete mould with eight components, and associated gating system was modelled in the simulation. In the simulation, the mould filling sequence as well as the solidification was considered. In Fig. 17, the temperature distribution is shown when the mould is completely filled. The minimum temperature directly after mould filling is seen to be about 1328 °C (casting temperature was 1410 °C). In Fig. 18, the location of porosity is

0

0

0

Bulb (%)

Shrinkage (%) 0

0

0

0 0

Bulb (mm2 )

0

0

35.48

9.84

3.25

0.81

0

31.25

9.06

34.37

23.16

1420 °C

0

(mm2 )

0.15% 1390 °C

1440 °C

1410 °C

0.05%

The amount of inoculant and casting temperature

Metal penetration (%)

Metal penetration

Casting defects

Table 6 Average casting defects calculated for the second experimental series

0

46.66

12.50

10.00

5.50

1390 °C

0

32.26

8.06

3.22

1.16

1370 °C

0

25.00

6.25

75.00

81.12

1420 °C

0.30%

0

66.67

22.50

6.67

4.40

1400 °C

0

40.62

11.72

0

0

1370 °C

1058 I. Dugic

How Various Inoculants and Their Amount Influence on the Metal …

1059

Fig. 3 Microstructure using inoculant A

Fig. 4 Microstructure using inoculant B

Fig. 5 Microstructure using inoculant C

Fig. 6 Microstructure using inoculant D

shown, and the geometry is clipped in the z-direction. These areas perfectly match the defect areas found by experiment.

1060 Fig. 7 Microstructure using inoculant E

Fig. 8 Microstructure using 0.05% addition and pouring temperature of 1440 ºC

Fig. 9 Microstructure using 0.05% addition and pouring temperature of 1410 ºC

Fig. 10 Microstructure using 0.05% addition and pouring temperature of 1390 ºC

I. Dugic

How Various Inoculants and Their Amount Influence on the Metal … Fig. 11 Microstructure using 0.15% addition and pouring temperature of 1420 ºC

Fig. 12 Microstructure using 0.15% addition and pouring temperature of 1390 ºC

Fig. 13 Microstructure using 0.15% addition and pouring temperature of 1370 ºC

Fig. 14 Microstructure using 0.30% addition and pouring temperature of 1420 ºC

1061

1062

I. Dugic

Fig. 15 Microstructure using 0.30% addition and pouring temperature of 1400 ºC

Fig. 16 Microstructure using 0.30% addition and pouring temperature of 1370 ºC

Fig. 17 3-D results from the simulation when 100% of the mould is filled

Discussion The choice of inoculant used in grey cast iron production today is probably one of the most important parameters in obtaining good quality castings. Five different inoculants have been tested on a casting component in a production scale. Figures 3,

How Various Inoculants and Their Amount Influence on the Metal …

1063

Fig. 18 3-D porosity results from the simulation when 100% of the mould is filled

4, 5, 6 and 7 show the microstructure close to the metal penetration area. The variation in eutectic cell size and its distribution has a significant coupling to the variation in metal penetration. The castings show two different types of surface defects, namely sinks and metal expansion penetration. The sinks and the metal expansion penetration have some relationship, but they are not directly related to each other. The present experiments show that the best results in terms of reduced metal penetration have been obtained when using the inoculant which contains silicon, aluminium, and zirconium, as shown in Fig. 7. For this inoculant, the average penetration area was only about 20% of that found using the worst inoculant. However, the silicon-aluminium-zirconium inoculant also gave rise to a large tendency to form sinks. Two other inoculants, containing aluminium, silicon, and strontium, have about the same base composition. From the measurements of penetration areas, one can draw the conclusion that the inoculant with the smallest particle size gives nuclei with the shortest lifetime. The coarser particles give a longer dissolution time, and this promotes survival of the nuclei. At the end of solidification, a larger amount of graphite will precipitate at higher temperatures if new nuclei can be activated (see Figs. 3 and 4). If a hot spot is located close to the metal surface, the metal will expand into the mould; resulting in metal expansion penetration. The manganese and barium containing inoculant (see Fig. 5), also gave a high amount of metal expansion penetration and shrinkage. The worst cases of metal penetration have been obtained using an inoculant containing titanium. A large number of small eutectic cells and high volume of the small cells were observed (see Fig. 6), which led to large penetration areas. Variation of Addition and Pouring Temperature In this experimental series, one of the five inoculants from the first experimental series was chosen, inoculant E containing aluminium and zirconium. Inoculant E

1064

I. Dugic

was added at three different levels (0.05, 0.15 and 0.30%) and at various casting temperatures (from 1370 to 1440 ºC). From the results of the ocular inspection of the components, and measurements of the eutectic cell size and distribution, it can be concluded that nucleation of the eutectic cells plays an important role in the formation of expansion penetration. The castings show two different types of surfaces defects: namely, bulb and metal expansion penetration. The bulb formation and metal expansion penetration seem to be related. For cast irons, the metal will expand during eutectic solidification due to the graphite expansion. This creates an internal pressure in the liquid, which may cause a movement or deformation of the mould wall, at the same time as any porosity formed earlier may decrease in size or possibly even disappear entirely, depending on the gas content. The inoculant investigated (inoculant E) contains silicon, aluminium, and zirconium. These experiments did not show any surface sink defects. In the first experimental series, the same inoculant amount of 0.15% gave rise to a large tendency to sink formation. The influence of the casting temperatures showed the following result: by using a lower temperature, the metal penetration was reduced, but the bulb formation was unchanged. This was observed in experiments using 0.15 and 0.30% inoculants. The influence of the amount of inoculant exerted on the metal penetration indicates a clear dependence. The expansion penetration disappeared at low (0.05%) addition at the two highest pouring temperatures, although at the lowest temperature, some penetration did occur. The low temperature did not show any tendency to form white solidification (see Figs. 8 and 9). The pouring temperature seems to have a large influence in combination with high additions of inoculant. A low pouring temperature seems to increase the formation of bulbs caused by excess material during solidification. Considering both metal penetration and bulb formation, these are believed to have the same origin. The experiments with the two higher amounts of inoculant show that the metal expansion will decrease with reduced pouring temperature. The mechanism of bulb formation is proposed to depend on formation of a thin solidified layer at the mould-metal interface when the metal has completely filled the mould. This shell is thin, and a later expansion of the metal during solidification pushes the shell outward and forms a bulb, instead of bursting and causing metal penetration of the sand mould.

Conclusions These experiments show that the type and amount of inoculation of grey cast iron will influence the tendency towards metal penetration in areas with late solidification times and where the melt is in contact with the sand mould. Experiments using different inoculants show that the best results regarding reduced metal penetration have been obtained when using an inoculant which

How Various Inoculants and Their Amount Influence on the Metal …

1065

contains silicon, aluminium and zirconium. For this inoculant, the average penetration area was only about 20% of that which was found using the worst inoculant. However, this inoculant also gave rise to a large tendency to form sinks. The worst cases of metal penetration were obtained using an inoculant containing titanium. A large number of small eutectic cells and a high volume of the small cells were observed, which led to severe metal penetration. In experiments in which the amount of the inoculant addition and the pouring temperature were varied, a clear relation between a low amount of inoculant and castings free from penetration was seen. Any tendency to add extra inoculant as a “security measure” cannot be recommended due to the increased risk of metal penetration. At inoculation additions of 0.15% and 0.30%, the metal penetration decreased with reduced pouring temperature. From the microstructure analysis, it is clear that penetration is associated with a mixture of large and small eutectic cells. The best results were obtained using low inoculant additions of 0.05%, in combination with pouring temperature above 1390 °C. No penetration, bulb formation, or shrinkage was seen on these castings. From the simulation, no distinct differences could be observed between casting no. 5 and the other castings; neither considering the mould filling sequence, nor the solidification path. The amount of porosity predicted is more or less identical for all castings. Consequently, it is concluded that the problem in casting no. 5 is not related to any difference in filling behavior or heat flux. Therefore, it is likely that some other phenomenon is responsible for the severe metal penetration seen in casting no. 5. One feasible explanation is that the mould hardness close to casting no. 5 is lower than in the rest of the mould. There are at least two effects which derive from lower mould hardness. The first and probably most important one is that the volume changes differ when the mould is heated up. Secondly, the thermal properties will be lower, which will affect the heat flow away from the casting. These effects may together result in a greater tendency to metal penetration locally, an effect which we today are not able to predict by the simulation. Acknowledgements The author would like to thank Linnaeus University, Faculty of Technology, Department of Mechanical Engineering, Vaxjo, Sweden.

References 1. Grey iron castings handbook, Grey and ductile iron founder’s society, Cleveland, Ohio, USA, (1958) 2. Lambert G (ed) (1966) Typical microstructures of cast metals, 2nd ed. The institute of British Foundrymen, p 47 3. Heine RW, Loper CR (1969) On dendrites and eutectic cells in gray iron. AFS Trans, 185–191 4. Loper Jr CR, Gundlach R (1998) Inoculation, what is it and how does inoculation work. International inoculation conference, Illinois, USA 5. American Society for Testing Materials Standards (1955) Part I, Ferrous metals, pp 1371–1378

1066

I. Dugic

6. Nakae H, Takai K, Okauti K, Koizumi H (1991) Nucleation of graphite in inoculated cast iron 7. Gadd MA, Bennett GHJ (1985) The physical chemistry of inoculation of cast iron. Elsevier Science Publishing Company, Inc., pp 99–108 8. Ruff GF, Wallace JF (1976) Control of graphite structure and its effect on mechanical properties of grey iron. AFS Trans 84:705–728 9. AFS, Analysis of casting defects, 2nd ed, vol 64 (1974) 10. Levelink HG, Julien FPMA (1973) Penetration and shrinkage by interaction of solidifying cast iron and casting mould–Part 2. AFS Cast Metals Res J 9(2):105–109 11. Svoboda JM, Geiger GH (1969) Mechanisms of metal penetration in foundry moulds. AFS Trans 77:281–288 12. Draper AL, Gaindhar JL (1997) AFS Trans 83(23):593–615 13. Thorpe PJ (1971) Avoidance of metal penetration and sand burn–on in iron castings, Brit. Foundryman 64:38–396 14. Kagawa A, Kiguchi S, Osada M (1995) Expansion behavior on solidification of flake graphite, compacted vermicular graphite and spheroidal graphite cast irons, Third Asian Foundry Congress; Kyongju; South Korea; 8–10 Nov 1995, pp 256–261 15. Draper AB, Gaindhar JL (1977) Metal penetration–a critical literature review. AFS Trans 85:163–199

In-Suit Observation of the Formation of CeAlO3 Clusters on the Surface of an Al-Killed Molten Steel Qiuyue Zhou and Lifeng Zhang

Abstract The aggregation of CeAlO3 inclusions on the surface of an Al-killed molten steel was observed under argon purging using a confocal laser scanning microscopy (CLSM). The steel contained 32 ppm total oxygen, 13 ppm sulfur, 70 ppm aluminum, and 70 ppm cerium and stable inclusions were CeAlO3 . The aggregation occurred when the distance between CeAlO3 inclusions was less than 160 μm. The smaller inclusion had a shorter critical aggregation distance. Within 20 min, single inclusion particles with an initial size of 2.3 μm were aggregated into 200 μm ones. The attractive force between CeAlO3 inclusions increased with the increase of the diameter of inclusions. The attractive force between 5 μm inclusions ranged 10–17 N to 10–15 N. Keywords Al-killed steel · CeAlO3 inclusions · Aggregation

Introduction The heavy steel ingots are widely used in pressure vessel due to the excellent stress resistance. The large 16Mn steel ingot in the current study was Al-killed. The solidification time of heavy ingot was so long, which was different from the continuous casting. For a 303-ton ingot, the solidification time of molten steel was more than 20 h [1]. The inclusions in Al-killed steel were Al2 O3 inclusions [2, 3], Al2 O3 inclusions collided and aggregated to form large clusters [4]. At present, larger non-metallic inclusions in the heavy steel ingot were still one of the key problems that limit the improvement of heavy ingot quality. The capillary force is the main reason for Q. Zhou School of Metallurgical and Ecological Engineering, University of Science and Technology, Beijing 100083, China L. Zhang (B) School of Mechanical and Materials Engineering, North China University of Technology, Beijing 100144, China e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_92

1067

1068

Q. Zhou and L. Zhang

the aggregation and densification of inclusions[5]. The order of the attractive force between inclusions is: solid inclusions >semi-solid inclusions >liquid inclusions[6]. For solid inclusions, the order of attractive capillary force is Al2 O3 > CaO·6Al2 O3 > MgO > CaO·2Al2 O3 > MgAl2 O4 [7]. Cerium treatment was carried out during the refining process, the grain was refined, and the diameter of inclusions was decreased [8, 9]. For Al-killed steel, the modification order of inclusions with the increase of cerium content was Al2 O3 → CeAlO3 → Ce2 O2 S → Ce2 O2 S + CeS [10]. CeAlO3 was solid inclusion in the molten steel, and it was the first to form in Al-killed steel. CeAlO3 was easy to aggregate, which resulted in nozzle clogging and big clusters [11]. In the current study, cerium treatment was used to modify the Al2 O3 inclusions. The aggregation of CeAlO3 on the surface of molten steel was in-suit observed by confocal scanning laser microscope, and the attractive force of CeAlO3 inclusion pairs was calculated. The morphology of inclusions before and after the CSLM experiment was observed.

Methodology The chemical composition of the Al-killed steel is shown in Table 1. The production process of the Al-killed steel was electric arc furnace (EAF) → ladle furnace (LF) refining → vacuum degassing (VD) refining → Ce treatment → tundish (TD). The molten steel sample was taken in the tundish using a bucket sampler. The content of cerium in the sample was detected by inductively coupled plasma mass spectrometry (ICP-MS). The sample was polished, and the morphology and composition of the original inclusions were analyzed by scanning electron microscope energy dispersive system (SEM + EDS). As shown in Fig. 1, the sample size was ϕ8 mm * 4 mm. The samples were heated to 1570 °C for 20 min using confocal scanning laser microscope. CeAlO3 inclusions floated to the surface of the molten steel. The collision and aggregation of inclusions were observed. Photos were taken every 0.2 s; the changes of inclusion size and distance with time were counted. After the in-suit observation, the cooling rate of steel was 300 °C/s. The inclusions at the surface of the sample were analyzed by SEM + EDS. Table 1 Chemical composition of the Al-killed steel (%) C

Si

Mn

Cr

Ni

Al

S

T.O

Ce

Fe

0.17

0.23

1.17

0.18

0.29

0.007

8 μm. In the early stage of aggregation, the distance between inclusions decreased slowly. In the 0.4 s before the aggregation, the distance between inclusions decreased rapidly with time. The aggregation process of all inclusions was completed in 2.5 s. / R=

Area 4π

(1)

250

(a)

R1=2~4 µm R2=3.6 µm

200

R2=4.5 µm R2=4.7 µm R2=5.0 µm

150

R2=5.4 µm R2=5.5 µm R2=6.4 µm

100

R2=6.6 µm R2=7.5 µm R2=8.0 µm R2=15.1 µm

50

0 0.0

0.5

1.0

1.5

2.0

Distance between inclusions (µm)

Distance between inclusions (µm)

where R is the equivalent radius of the cluster inclusion. Area is the measured area of the inclusion. As shown in Fig. 6, the average velocity of the guest inclusions can be calculated in the in-situ observation, as shown in Eq. 2. The acceleration of the inclusion is

2.5

250

R 1=4~6 µm

(b)

R2=5.3 µm R2=6.0 µm R2=6.1 µm

200

150

R2=6.6 µm R2=6.7 µm R2=7.0 µm

100

R2=8.1 µm R2=9.0 µm R2=11.1 µm R2=13.8 µm

50

0 0.0

0.5

(c)

R1 =6~8 µm R 2=7 .5 µm R 2=7 .8 µm R 2=8 .0 µm R 2=8 .5 µm

200

150

R 2=8 .8 µm R 2=9 .6 µm R 2=1 2.9 µm

100

R 2=1 6.4 µm R 2=2 3.8 µm R 2=2 8.6 µm

50

0 0.0

0.5

1.0

1.5

Time (s)

2.0

2.5

Distance between inclusions (µm)

Distance between inclusions (µm)

250

1.0

1.5

2.0

2.5

Time (s)

Time (s) 250

(d)

R1 > 8 µm R2 =9.8 µm R2 =11.5 µm R2 =14.0 µm R2 =14.9 µm

200

R2 =15.3 µm R2 =17.5 µm R2 =23.2 µm

150

R2 =25.2 µm R2 =28.1 µm

100

50

0 0.0

0.5

1.0

1.5

2.0

2.5

Time (s)

Fig. 5 Distance change between CeAlO3 inclusion pairs with time: a R1 = 2–4 μm; b R1 = 4–6 μm; c R1 = 6–8 μm; d R1 > 8 μm.

1072

Q. Zhou and L. Zhang

Fig. 6 Schematic of the calculation of the inclusion acceleration

calculated according to the inclusion velocity, as shown in Eq. 4. The mass of the inclusion is calculated by Eq. 5. The attractive force between inclusions is calculated by Eq. 6. v1 =

L1 − L2 ∆t

(2)

v2 =

L2 − L3 ∆t

(3)

a2 =

v2 − v1 ∆t

(4)

4 π R23 · ρinc 3

(5)

m2 =

F = m 2 × a2 ,

(6)

where L 1 is the distance between inclusions at time 1, m; L 2 is the distance between inclusions at time 2, m; L 3 is the distance between inclusions at time 3, m; ∆t is the time interval, 0.2 s; v1 is the average velocity between inclusions from time 1 to 2, m/s; v2 is the average velocity between inclusions from time 2 to 3, m/s; a2 is the acceleration of the guest inclusion, m/s2 ; R2 is the equivalent diameter of the guest inclusion, m. m2 is the mass of the guest inclusions, kg; ρ inc is the density of CeAlO3 inclusions, 5400 kg/m3 . F is the attractive force between inclusion pairs, N. The attractive force between the inclusion pairs of different sizes is shown in Fig. 7. The attractive force increased with the decrease of the distance between inclusions and the increase of the inclusion diameter. For inclusions with sizes of 2–4, 4–8, and >8 μm, the attractive force of inclusions was 10–17 N to 10–15 N, 10–16 N to 10–14 N, and 10–15 N to 10–13 N, respectively. The critical aggregation distance between the inclusions increased with the increase of diameter. For inclusions with a size of 2–4 μm, 4–8 μm, and >8 μm, the critical aggregation distance between the inclusions was 80 μm, 110 μm, and 160 μm, respectively. CeAlO3 inclusions were easy to aggregate on the surface of molten steel and form large clusters.

In-Suit Observation of the Formation of CeAlO3 Clusters on the Surface … 1E-12

Fig. 7 Attraction force between CeAlO3 inclusions pairs with different size

R 1=2-4 μm R 1=4-6 μm R 1=6-8 μm

1E-13

Attractive force (N)

1073

R 1> 8 μm

1E-14 1E-15 1E-16 1E-17 1E-18 1E-19

0

40

80

120

160

200

Distance between inclusions (μm)

Conclusions 1. CeAlO3 inclusions were easy to aggregate on the surface of molten steel and form large clusters. The average diameter of initial CeAlO3 inclusions in steel was 2.3 μm. With the aggregation of inclusion, the number density of inclusions decreased and the diameter increased. After 20 min of aggregation, the diameter of inclusions was larger than 200 μm. 2. In the early stage of aggregation, the distance between inclusions decreased slowly. In the 0.4 s before the aggregation, the distance between inclusions decreased rapidly with time. The aggregation process of all inclusions was completed in 2.5 s. 3. For inclusions with sizes of 2–4 μm, 4–8 μm and > 8 μm, the attractive force of inclusions was 10–17 N to 10–15 N, 10–16 N to 10–14 N, and 10–15 N to 10–13 N, and the critical aggregation distance between the inclusions was 80 μm, 110 μm, and 160 μm, respectively. Acknowledgements The authors are grateful for the support from the National Natural Science Foundation of China (Grant No. U22A20171, No. 52104343), the Natural Science Foundation of Hebei Province (Grant No. E2021203222), and the High Steel Center (HSC) at Yanshan University and North China University of Technology, China.

References 1. Hu W, Zhou Q, Chen W, Zhang L (2023) Numerical simulation on the fluid flow, air entrainment, heat transfer and solidification during top pouring and cooling of a 303 ton heavy ingot. Steel Res Int 94(6):2200709 2. Zhang L, Thomas BG (2003) State of the art in evaluation and control of steel cleanliness. ISIJ Int 43(3):271–291

1074

Q. Zhou and L. Zhang

3. Zhang L (2019) Non-metallic Inclusions in steels: fundamentals (in Chinese). Metallurgical Industry Press, Beijing 4. Yang W, Wang X, Zhang L, Wang W (2013) Characteristics of alumina-based inclusions in low carbon Al-killed steel under no-stirring condition. Steel Res Int 84(9):878–891 5. Mu W, Dogan N, Coley KS (2017) Agglomeration of non-metallic inclusions at the steel/Ar interface: model application. Metall Mater Trans B 48(4):2092–2103 6. Yin H, Shibata H, Emi T, Suzuki M (1997) Characteristics of agglomeration of various inclusion particles on molten steel surface. ISIJ Int 37(10):946–955 7. Wang L, Yang S, Li J, Chen C, Li C, Li X (2021) Study on the capillary interaction between particles on the surface of high-temperature melts. Steel Res Int 92(7):2100013 8. Huang Y, Cheng G, Li S, Dai W (2018) Effect of cerium on the behavior of inclusions in H13 steel. Steel Res Int 89(12) 9. Jiao W, Li H, Feng H, Jiang Z, Xia L, Zhang S, Zhu H, Wu W (2020) Evolutions of micro- and macrostructure by cerium treatment in as-cast AISI M42 high-speed steel. Metall Mater Trans B 51(5):2240–2251 10. Ren Q, Zhang L (2020) Effect of cerium content on inclusions in an ultra-low-carbon aluminumkilled steel. Metall Mater Trans B 51(2):589–600 11. Wang Y, Liu C (2020) Agglomeration characteristics of various inclusions in Al-killed molten steel containing rare earth element. Metall Mater Trans B 51:2585–2595

Kinetic Evolution of the Composition of Desulfurizers in the Molten Steel During RH Refining Process Jujin Wang and Lifeng Zhang

Abstract The addition of desulfurizer particles to the molten steel resulted in a noticeable change in the composition of desulfurizers. This study aimed to establish a kinetic model based on the unreacted-core model to predict the quantitative evolution of desulfurizers composition. The original composition of the desulfurizer was CaO–SiO2 –CaF2 . Effects of the content of dissolved magnesium [Mg] on the composition evolution of desulfurizers were determined. Once added to the steel, a rapid displacement reaction occurred between the SiO2 in the desulfurizer and the dissolved aluminum in the molten steel. Consequently, the SiO2 content in the desulfurizer decreased from 19.5 to below 2% within 90 s, while the Al2 O3 content increased from zero to over 20%. The study confirmed that as the [Mg] content increased from 1 to 15 ppm, the MgO content in the desulfurizer increased from 0.6 to 9.1% after 900 s of reaction. Keywords Kinetic modeling · Desulfurizer · RH refining

Instruction During the Ruhrstahl-Heraeus (RH) vacuum refining process used in electrical steel production, desulfurizers were added to the molten steel to maintain a low sulfur content [1, 2]. These desulfurizers caused changes in the composition of both the molten steel and the desulfurizer through chemical reactions. In our previous study [3], a comprehensive model that considered the multiphase flow of the molten steel and the dispersion of the desulfurizer was developed to investigate the evolution of sulfur content during RH desulfurization. However, it had been generally overlooked that not only the composition of the molten steel change during the desulfurization process, but the composition of the desulfurizer also underwent noticeable changes. J. Wang · L. Zhang (B) School of Mechanical and Materials Engineering, North China University of Technology, Beijing 100144, China e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_93

1075

1076

J. Wang and L. Zhang

The desulfurization reaction was a complex process that was significantly influenced by the composition of the refining slag, the composition of the desulfurizer, and the composition of the molten steel [4, 5]. These parameters had both thermodynamic and kinetic effects on the desulfurization process. Traditional CaO–SiO2 –CaF2 desulfurizers had a high melting point, resulting in a solid phase after addition to the molten steel. This led to variations in mass transfer at different stages. For the solid phase, the mass transfer coefficient of sulfur in the steel can be calculated using the RanzMarshall equation [6], while for the liquid phase, the Sano equation should be applied [7]. In addition, increasing the rate and dosage of desulfurizer addition, as well as decreasing the particle diameter, contributed to improved desulfurization efficiency. By employing appropriate injection operating conditions and treating the steel for 10 min, the minimum sulfur content in the molten steel can be reduced from 30 to 10 ppm [8]. Kirihara et al. [9] suggested that there existed an optimal diameter of the desulfurizer to maximize the efficiency of steel desulfurization. An elevated CaO content in the desulfurizer was advantageous for molten steel desulfurization during the RH refining process [10–13]. However, if the CaO content in the desulfurizer becomes excessively high, the desulfurization effect on the molten steel actually diminished. This is because the desulfurization efficiency of desulfurizers mainly relied on liquid CaO rather than solid CaO. When the CaO content was too high, the higher melting point of CaO increased the viscosity and melting point of the desulfurizer, thereby reducing the mass transfer rate of the reaction [13]. To investigate the evolution of desulfurizer composition during the steel desulfurization process, a kinetic model based on the unreacted-core model and the doublefilm theoretical model was developed in the current study. The model aimed to elucidate the evolution law of desulfurizer composition. Additionally, effects of magnesium content in the steel on the evolution of desulfurizer composition were also analyzed.

Model Description After desulfurizers were added to the steel, these particles initially existed in a solid state. During this period, the reaction between the desulfurizer and the steel was categorized as a solid–liquid reaction, which could be described using an unreactedcore model, as illustrated in Fig. 1. After a complete melting of the desulfurizer particles at time t 2 , the desulfurizer transformed to a liquid state. Subsequently, the reaction between the desulfurizer and the molten steel changed into a liquid–liquid reaction, which could be described using a double-film theory model. Based on the unreacted-core model, the mass transfer coefficient for the interaction between the desulfurizer and molten steel, prior to the melting of the desulfurizer particles, was determined via the Ranz-Marshall formula [6], as indicated in Eq. (1). Due to the solid nature of the desulfurizer, the mass transfer resistance of its components was significantly greater than that of the components in the molten steel. Thus, it was assumed that the mass transfer coefficient of the desulfurizer components was 1%

Kinetic Evolution of the Composition of Desulfurizers in the Molten …

1077

Fig. 1 Schematic for the kinetic model of the composition evolution of the desulfurizer in the molten steel during RH process

of that in the molten steel, as shown in Eq. (4). ShP =

βM dP 1/2 1/3 = 2 + 0.6ReP ScP DM

(1)

ReP =

u P dP ρst μst

(2)

ScP =

μst ρst DM

(3)

βMOn = 0.01βM ,

(4)

where β M is the mass transfer coefficient of the steel component M, m/s; DP is the diameter of the desulfurizer particle, m; DM is the diffusion coefficient of element M in molten steel, m2 /s, with values shown in Table 1; Shp is the Sherwood number of desulfurizer particles; Rep is the Reynolds number of the desulfurizer particles; and Scp is the Schmidt number of desulfurizer particles. The relative velocity between the desulfurizer and molten steel correlated with their diameter [14], with larger sizes resulting in increased velocities. The larger the size, the greater the relative velocity. Different calculation formulas were chosen based on the Reynolds number (Re) of the desulfurizer in the molten steel. Equation (5) was employed when the Reynolds number was less than 0.5. For Reynolds number ranging from 0.5 to 1000, Eq. (6) was applied. Conversely, for Reynolds numbers surpassing 1000, Eq. (7) was utilized. up =

up =

  ρst − ρp dp2 g

18μst    2/3 g ρst − ρp 0.5 9μ0.5 st ρst

, Re < 0.5

(5)

dp , 0.5 < Re < 1000

(6)

Table 1 Diffusion coefficient of elements in the molten steel Element Diffusivity,

×10–9

m2 /s

Ca

Al

Si

Mn

Mg

O

S

3.5

3.5

4.36

4.4

3.5

2.96

4.1

1078

J. Wang and L. Zhang

   1/2 g ρst − ρp dp up = , Re > 1000. 0.33ρst

(7)

The reaction between liquid desulfurizer and the steel was similar to the reaction between the steel and slag. The mass transfer coefficient was calculated using the Sano formula [7], as shown in Eq. (8). The mass transfer resistance of components in liquid desulfurizer was slightly greater than that of components in the steel liquid. Therefore, it was assumed that the mass transfer coefficient of components in liquid desulfurizer was one-tenth of that in the steel liquid, as shown in Eq. (9).   4 3 1/4 βM dP εdP ρst 1/3 Sh = = φ 2 + 0.4 ScP DM μ3st βMOn = 0.1βM ,

(8) (9)

where φ is the shape factor, and for spherical particles, φ = 1; ε is the stirring power of the molten steel, m2 /s3 . The traditional CaO–SiO2 –CaF2 desulfurization agent predominantly consisted of CaO, SiO2 , and CaF2 . Other elements, such as carbon (C) and sulfur (S), were present in minor quantities. Thus, it was posited that the initial makeup of the desulfurizer included only CaO, SiO2 , and CaF2 . Recognizing that elements like manganese, magnesium, and sulfur in the molten steel engaged in the reaction with the desulfurizer, the formation or decomposition of CaO, Al2 O3 , SiO2 , MnO, MgO, and CaS was involved in the current study, as articulated in Eq. (10). The reaction was assumed to occur at a spherical interface and the diameter of the desulfurizer remained unchanged. In addition, the aim of the current study was to study the changes in the composition of the desulfurizer caused by the reaction between the steel and the desulfurizer. Thus, a single desulfurizer particle was taken during the calculation, and the impact of the reaction on the composition of the steel was ignored. The detailed of the kinetic and thermodynamic consideration could be found in our other studies and will not be elaborated here [15, 16]. [M] + n[O]=(MOn )

(10)

Simulation Results Initial Conditions In the current study, the composition system of both molten steel and desulfurizer had been simplified, focusing solely on elements that influence the evolution of the desulfurizer’s composition, while disregarding components with lower concentrations. Table 2 provides the composition of the molten steel, with all listed components

Kinetic Evolution of the Composition of Desulfurizers in the Molten …

1079

Table 2 Steel composition used in the current model Composition

C

Si

Mn

[S]

[Al]

[Mg]

[O]

Content, wt.%

0.001

2.965

0.14

0.0020

1.0115

0.0001

0.0005

Table 3 Initial composition of traditional and pre-melted desulfurizers used in the current model Composition

CaO

CaF2

SiO2

Content, wt.%

67.5

13

19.5

representing dissolved content. Furthermore, although the experimental process did not detect magnesium ([Mg]) content in the steel, the erosion of refractory materials by the molten steel gradually elevated the [Mg] content in the steel, leading to the generation of MgO in the desulfurizer. Consequently, the initial [Mg] content in the molten steel was established at 1 ppm. The initial composition of the desulfurizer is shown in Table 3. At the initial stage, only the CaO, CaF2 , and SiO2 contents in desulfurizers were considered. Other parameters used in the model are listed in Table 4, where the turbulent energy dissipation rate ε was obtained from the numerical simulation results in Ref. [3], taking the value of 0.035 m2 /s3 .

Changes in the Composition of Desulfurizers Over Time Figure 2 shows the composition evolution of the desulfurizer (200 µm in diameter) over time after added to molten steel. Upon entering the molten steel, SiO2 in the desulfurizer quickly reacted with the dissolved aluminum [Al] in molten steel, leading to a swift decline in SiO2 content, from 19.5 to below 2% within 90 s. Concurrently, Al2 O3 content rose from zero to over 20%. Throughout this period, CaO in the desulfurizer and dissolved sulfur [S] in the molten steel engaged in a continuous desulfurization reaction, converting CaO into CaS. By 900 s, the CaO content in the desulfurizer approximated 23%, while CaS reached around 35%. The content of CaF2 in the desulfurizer exhibited a minor reduction, which was not because of direct involvement in reactions, but due to the increasing desulfurizer mass over time. As Fig. 3 illustrates, the mass of individual desulfurizer escalated from 1.252 × 10–8 to 1.613 × 10–8 kg, resulting in a relative decrease in CaF2 content. The compositional evolution of the desulfurizer over time was intricately related to the equilibrium concentration at the reaction interface between the desulfurizer and molten steel. Figure 4 shows the time-based variations of equilibrium contents for elements [O], [S], [Ca], and [Mg] within the molten steel at this interface. In the initial minute post-desulfurizer addition, the equilibrium concentration of [O] gently receded from 7 to 6 ppm—remaining consistently above the steel bulk’s 5 ppm. Meanwhile, the equilibrium concentration of [Ca] showed a minor uptick, moving from 2.95 ppm to 3.07 ppm. During this period the dominant reaction involved [Al]

Temperature K

1823

Parameter

Value

7020

Steel density kg/m3

Table 4 Parameters used in the current model

2990

Desulfurizer density kg/m3 200

Desulfurizer diameter µm

0.035

ε m2 /s3

180

Desulfurizer melting time s

1080 J. Wang and L. Zhang

80

1081

Melted time

Fig. 2 Composition of the traditional desulfurizer varied with time after adding to the molten steel

Composition of desulfurizer particles (%)

Kinetic Evolution of the Composition of Desulfurizers in the Molten …

60

CaO

40 Al2O3 20

CaS CaF2 SiO2

0 0

180

360

540

720

900

720

900

Fig. 3 Mass of a single desulfurizer particle varied with time after adding to the molten steel

Mass of a single desulfurizer (◊10-8 kg)

Times (s)

1.8 1.7 1.6 1.5 1.4 1.3 1.2 0

180

360

540

Time (s)

in the steel reducing SiO2 in the desulfurizer. Subsequently, equilibrium contents of [O] and [S] at the interface rose continually, reaching peaks of 10.8 ppm and 11 ppm, respectively. While [Ca] content at the interface marginally ascended in the initial minute, its equilibrium content consistently waned throughout the reaction, settling at 0.25 ppm by 900 s. The equilibrium [Mg] content in molten steel remained relatively stagnant, plateauing around 3.07 ppm—this period predominantly witnessed the [Al]-driven reduction of SiO2 in the desulfurizer. Although the molten steel’s initial [Mg] content stood at 1 ppm, the equilibrium [Mg] content at the interface underwent negligible variations during the reaction, persistently staying below 1 ppm. The compositional evolution of the desulfurizer over time was intricately related to the equilibrium concentration at the reaction interface between the desulfurizer and molten steel. Figure 4 shows the variation of the equilibrium content of the

12

Melted time

Fig. 4 Equilibrium composition of the molten steel at reaction interface varied with time after adding the traditional desulfurizer particle to the molten steel

J. Wang and L. Zhang

Composition of steel at interface (ppm)

1082

10 8

[O]

6 [S]

4 [Ca] 2 [Mg] 0 0

180

360

540

720

900

Time (s)

elements [O], [S], [Ca], and [Mg] in the molten steel at the reaction interface over time. In the first minute after the desulfurizer was added to the steel, the equilibrium concentration of [O] in the steel gradually decreased from 7 to 6 ppm, but it was always greater than the 5 ppm (bulk concentration). The equilibrium concentration of [Ca] increased from 2.95 ppm to 3.07 ppm, which was a relatively small change, and the main reaction in this stage occurred in the reduction of SiO2 in the desulfurizer by [Al] in the steel. Thereafter, the equilibrium [O] and [S] contents at the interface continued to increase, and the equilibrium [O] content could reach 10.8 ppm and the equilibrium [S] content could reach 11 ppm, and the [Ca] content at the interface only increased slightly in the initial 1 min, and then the equilibrium [Ca] content continued to decrease in the reaction process, which was 0.25 ppm at 900 s. The equilibrium [Mg] content in the liquid steel increased to 3.07 ppm with little change, and this stage was mainly the reaction of [Al] reduction of SiO2 in the desulfurizer. The initial [Mg] content in the liquid steel was 1 ppm, and the equilibrium [Mg] content at the reaction interface change little during the reaction and remained below 1 ppm.

Effect of [Mg] Content on the Evolution of Desulfurizer Figure 5 shows the effect of [Mg] content in the molten steel on the compositional evolution of the desulfurizer. After 900 s of reaction, the range of CaO content in the desulfurizer was 20.3–23.3%, and the range of CaS content was 35.3–36.7% when the [Mg] content in the steel liquid was in the range of 1–15 ppm. The [Mg] content in the molten steel had less influence on the evolution of CaO and CaS content in the desulfurizer, which was due to the activity of the desulfurizer components. The desulfurizer component in the early period was mainly CaO, when the CaO activity was not affected by the Al2 O3 and MgO content in the desulfurizer. However, after

Kinetic Evolution of the Composition of Desulfurizers in the Molten …

1083

Melted time

80

60

[Mg] (ppm) 1 5 10 15 CaO

40

15 1

20

CaS

15

0 0

180

360

540

720

900

Times (s)

(a) content of CaO and CaS 40

Melted time

Composition of desulfurizer particles (%)

Fig. 5 Effect of [Mg] content in the molten steel on the composition evolution of the traditional desulfurizer

Composition of desulfurizer particles (%)

the reaction of 700 s, the Al2 O3 content in the desulfurizer reached more than 20%, and the reaction between the [Mg] in the molten steel and desulfurizer gradually showed its effect on the desulfurization reaction. The [Mg] content in the steel had little effect on the reaction between [Al] in the steel and SiO2 in the desulfurizer in the early period, but the higher the [Mg], the higher the MgO content of the desulfurizer. Taking the reaction at the moment of 900 s as an example, the MgO content in the desulfurizer increased from 0.6 to 9.1% when the [Mg] content in the steel increased from 1 to 15 ppm. This indicated that the MgO content in the desulfurizer gradually increased with the increase of refractory erosion.

30

[Mg] (ppm) 1 5 10 15

1 Al2O3

5

10 15

20

10

15 SiO2

10

MgO 1

0 0

180

360

540

5 720

Times (s)

(b) content of Al2O3 and SiO2

900

1084

J. Wang and L. Zhang

Conclusion and Summary In the current study, a kinetic model of the reaction between the steel and desulfurizer was established based on the unreacted-core model and the double-film theory, and the composition evolution of the CaO–SiO2 –CaF2 desulfurizer was analyzed. The effect of the content of [Mg] in the molten steel on the composition evolution of the desulfurizer was quantitatively analyzed. (1) Upon the addition of the desulfurizer to the steel, a rapid substitution reaction taken place between the SiO2 in the desulfurizer and [Al] in the steel. Within 90 s, the SiO2 content in the desulfurizer decreased drastically from 19.5 to less than 2%, while the Al2 O3 content surged from 0 to over 20%. (2) Throughout the reaction process, a continuous desulfurization occurred between the CaO in the desulfurizer and the [S] in the molten steel. After 900 s, the CaO content in the desulfurizer diminished from 67.5 to 23%, while the CaS content escalated from 0 to 35%. (3) With the increase of [Mg] content in the molten steel, the MgO content in the desulfurizer gradually increased. When the [Mg] content in the molten steel increased from 1 to 15 ppm, the MgO content in the desulfurizer increased from 0.6 to 9.1% after 900 s of reaction. Acknowledgements The authors are grateful for the support from the National Natural Science Foundation of China (Grant No. U22A20171, 52304340), the High Steel Center (HSC) at North China University of Technology and the High Quality Steel Consortium (HQSC) at the University of Science and Technology Beijing, China.

References 1. Cao H, Liu B, Wang H, Ren T (2015) Application and prospect of powder injection system with RH-WPB water-cooling top lance at Tianjin steel tube co. Special Steel 36(3):14–16 2. Xu X (2023) Research and practice on ultra low sulfur smelting of high grade non-oriented silicon steel w310 by KR-BOF-RH process. Special Steel 4(1):55–60 3. Peng K, Sun Y, Peng X, Chen W, Zhang L (2023) Numerical simulation on the desulfurization of the molten steel during RH vacuum refining process by cao powder injection. Metall Mater Trans B 54(1):438–449 4. He S, Zhang G, Wang Q (2012) Desulphurisation process in RH degasser for soft-killed ultra low-carbon electrical steels. ISIJ Int 52(6):977–983 5. Kim T, Park J (2021) Viscosity-structure relationship of CaO–Al2 O3 –FetO–SiO2 –MgO Ruhrstahl-Heraeus (RH) refining slags: fundamentals of high temperature processes. ISIJ Int 61(3):724–733 6. Ranz W, Marshall W (1952) Evaporation from drops, Part I. Chem Eng Prog 48(3):141–146 7. Sano Y, Yamaguchi N, Adachi T (1974) Mass transfer coefficients for suspended particles in agitated vessels and bubble columns. J Chem Eng Jpn 7(4):255–261 8. Zhu C, Chen P, Li G, Luo X, Zheng W (2016) A mathematical model of desulphurization kinetics for ultra-low-sulfur steels refining by powder injection during RH processing. ISIJ Int 56(8):1368–1377

Kinetic Evolution of the Composition of Desulfurizers in the Molten …

1085

9. Kirihara T, Uehara H, Nakato H, Kato Y (2003) Desulfurization of steel melt by pulverized CaO blasted through top lance of vacuum vessel in RH degasser. Tetsu-to-Hagané 89(10):14–18 10. Wu S (2019) Research on thermodynamics and kinetics of desulphurization in the electroslag remelting process of Inconel 718 superalloy. University of Science and Technology Liaoning 11. Shi Q (2006) The development of less-fluoride or free-fluoride desulphurizer for RH vacuum treatment. Wuhan University of Science and Technology 12. Shen B (2016) Study on desulfurization in RH by Input method for soft-killed steel. Chongqing University 13. Liao J (2014) Research on the deep desulphurization process of non-oriented electrical steel in RH. Jiangxi University of Science and Technology 14. Park J, Todoroki H (2010) Control of MgO·Al2 O3 spinel inclusions in stainless steels. ISIJ Int 50(10):1333–1346 15. Wang J, Zhang L, Cheng G, Ren Q, Ren Y (2021) Dynamic mass variation and multiphase interaction among steel, slag, lining refractory and nonmetallic inclusions: laboratory experiments and mathematical prediction. Int J Miner Metall Mater 28(8):1298–1308 16. Wang J, Zhang L, Wen T, Ren Y, Yang W (2021) Kinetic prediction for the composition of inclusions in the molten steel during the electroslag remelting. Metall Mater Trans B 52(3):1521–1531

Mold Simulator Study of Lubrication Behavior of High Carbon Steel Slag Film Inside Continuous Casting Mold Zichao Wang, Wanlin Wang, Haihui Zhang, and Jie Zeng

Abstract During the continuous casting of high carbon steel, mold sticking breakout occurs frequently, which may be due to poor lubrication of the slag film infiltrating into the gap between the mold and the shell. The study investigated the lubrication behavior of the slag film near the meniscus area using a mold simulator technique. The results showed that the heat flux and temperature of the mold initially increased, followed by a subsequent decrease along the casting direction. The thickness of the slag film initially decreases, followed by an increase along the casting direction. Overall, the thickness of the slag film ranges from 1.21 to 2.87 mm. Additionally, the thickness of the liquid slag film is 0.41 mm at the shell tip and decreases to 0.13 mm at a location situated 10 mm below the tip. Keywords Continuous casting · Slag film · Shell · Heat transfer

Introduction Mold flux plays very important roles in the continuous casting process, including providing thermal insulation to prevent the steel surface from freezing, lubricating the shell, controlling heat transfer, absorbing nonmetallic inclusions, and preventing reoxidation of liquid steel during continuous casting [1, 2]. Mold sticking breakout is a common problem during the continuous casting of high carbon steel. It is caused by poor lubrication of the slag film infiltrating into the gap between the mold and the shell, which leads to the shell sticking to the mold [3]. To prevent this issue, it is essential to maintain an adequate thickness of the shell forming within the mold and to develop effective control technologies. Z. Wang · W. Wang (B) · J. Zeng School of Metallurgy and Environment, Central South University, Changsha 410083, China e-mail: [email protected] H. Zhang Faculty of Materials Metallurgy and Chemistry, Jiangxi University of Science and Technology, Ganzhou 341000, China © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_94

1086

Mold Simulator Study of Lubrication Behavior of High Carbon Steel …

1087

Many studies have investigated the lubrication of high carbon steel mold flux. These studies have focused on the changes in slag film lubrication by adjusting the mold flux compositions [4, 5]. The composition of mold flux can affect not only the lubrication properties of the slag film but also its melting temperature and viscosity. The effect of mold flux composition on these properties can be complex and may depend on various factors such as basicity, MgO content, and liquid flux thickness [6, 7]. Several casting parameters can affect the lubrication of the slag film, including casting speed, mold oscillation, and steel pouring temperature. For example, increasing the casting speed can reduce the thickness of the slag film and lead to poor lubrication, while decreasing the casting speed can result in a thicker slag film and better lubrication. Wang et al. [8] conducted a study on the influence of mold oscillation frequency on slag film lubrication during continuous casting of steel. Their results showed that a higher oscillation frequency can lead to thinner liquid slag film layers, which can result in poor shell lubrication and an increased risk of mold sticking breakout. Hanao et al. [9] found that mold flux consumption decreases with increasing casting speed during continuous casting of steel. This is because a higher casting speed can lead to a thinner slag film, which can result in a lower amount of mold flux being consumed during the process. Zhou et al. [10] indicated that increasing the superheat of the steel can slow down the penetration of the mold flux and sometimes result in a smoother surface of the shell. Therefore, it is important to carefully consider the casting parameters to achieve optimal lubrication of the slag film and prevent quality issues such as mold sticking breakout. Numerous studies have explored the lubrication of high carbon steel mold flux, but only a limited number of studies have specifically examined the lubrication effects of the slag film along the casting direction on the shell. Consequently, this study aims to examine the lubrication behavior of the slag film near the meniscus area utilizing a mold simulator technique.

Experimental Apparatus and Procedure Mold Simulator Figure 1a depicts the schematic of the mold simulator. The system comprises six key components: an inverse type water-cooled copper mold (30 mm × 50 mm × 350 mm), a mold oscillator system, an extractor, an induction furnace, a temperature acquisition system, and an Ar gas protection system. The water-cooled copper mold features water-cooling groove that is embedded within a copper plate. The watercooling groove has a central water inlet and dual water outlets on either side. The mold is equipped with an extractor that exposes a single face of the copper mold to the liquid melt. The extractor withdraws the solidified shell downwards with respect to the copper mold, so that the solidified shell continues to solidify and grow. The extractor plays the role that likes the dummy bar does at the start-up of a continuous

1088

Z. Wang et al.

Fig. 1 Schematic of the mold simulator

casting. The distribution of 14 highly sensitive T-type thermocouples is illustrated in Fig. 1b. These thermocouples are arranged in two columns (2 × 7) at varying depths beneath the mold surface. Two columns of thermocouples are spaced 3 mm (hot side) and 8 mm (cold side) away from the mold surface, respectively, and the distance between thermocouples in each row is 3 mm.

Experimental Process In the experiment, approximately 25kg high carbon steel ([C]: 0.42 wt pct, [Si]: 0.25 wt pct, [Mn]: 0.8 wt pct, [Al]: 0.01 wt pct) was firstly added to the induction furnace within a 99.99 pct pure argon atmosphere. Once the charge had melted, the temperature of molten steel was adjusted to the desired experimental casting temperature. Subsequently, mold flux (Basicity: 1.20, Al2 O3 : 8.00, MgO: 3.00, Na2 O + Li2 O: 7.00, MnO + Fe2 O3 : 4.00, F− : 5.00) designed for high carbon steel (about 0.3 kg) was added to the top surface of liquid bath. This resulted in the formation of a 6-mm-thick layer of molten flux atop the liquid steel. Next, terminate the power supply to the induction furnace upon reaching the desired casting temperature. The water-cooled copper mold began to oscillate and slowly dropped to the predetermined position in the molten steel together with the extractor. Then, the oscillating mold was hold for 4 s, allowing the surface of the water-cooled copper mold and the extractor to have enough time to contact with the molten steel and generate a shell with thick enough to resist the pulling force and prevent breakage during the subsequent continuous casting process. Fourth, the extractor withdrew the solidifying shell downward at the casting speed to simulate the continuous casting process, emulating the continuous casting process. Concurrently, the mold moved upward at a certain speed to compensate for the rise of mold level, so that the liquid mold flux surface and meniscus could be kept at the same position with respect to the mold. In this process, the liquid slag layer on the liquid steel’s surface continuously infiltrated the gap between the copper mold and the initial solidified shell, giving rise to the

Mold Simulator Study of Lubrication Behavior of High Carbon Steel …

1089

Table 1 Mold oscillation setting and casting conditions Casting temperature Tc

Casting speed V c

Frequency, f

Stroke 2A

1785–1795 K

0.6 m/min

2.75 Hz

9.4 mm

formation of a mold flux film. When casting was completed for the desired length (about 60mm), the mold and the extractor were retracted from the molten material and cooled in ambient air. From the time the mold started to lower into the bath to the completion of casting, the mold was kept oscillating sinusoidally at the pre-set frequency and stroke (oscillation parameters are listed in Table 1). Finally, the solidified shell and the slag film between the solidified shell and mold were picked up for further study.

Calculation Method of Slag Film Lubrication Figure 2 shows the heat transfer model of the slag film existing between the mold and the initial solidification shell. A 2D-IHCP mathematical model [11] was utilized to compute the temperature and heat flux across the mold surface, using measured mold temperatures. Additionally, a 1DITPS mathematical model [12] was employed to determine the surface temperature of the initial solidified shell, based on experimental measurements of its thickness. Furthermore, the thickness of the liquid slag film can be calculated using the heat transfer model of the slag film between the mold and initial solidification shell, based on the measured thickness of the slag film. The physical parameters of steel and mold flux used in these calculations are listed in Table 2 and Table 3, respectively. For more information regarding the process of calculating slag film heat transfer, please refer to our previous studies [8].

Fig. 2 Heat transfer model of slag film between mold and initial solidification shell [8]

1090

Z. Wang et al.

Table 2 Physical properties of experimental steel [12, 13] Steel

Value

Density, ρ steel (kg/m3 )

7300

Specific heat, c (J/kg·K)

870

Latent Heat, L a (J/kg)

268,000

Conductivity in solid k s and Liquid k l (W/m·K)

33, 33

Liquidus temperature, T l (K)

1767

Solidus Temperature, T s (K)

1677

Table 3 Physical properties of mold flux [8, 12–14] Mold flux

Value

Crystalline slag emission εcry

0.7

Shell emission εsh

0.78

Slag refractive index m

1.6

Stefan-Boltzmann constant σB (W/(m2 K4 ) Absorption coefficient of liquid slag al

(m−1 )

5.6705 × 10–8 400

Thermal conductivity of liquid slag k sl (W/m·K)

1.0

Apparent thermal conductivity of solid slag k eff (W/m K)

2.8

Slag density ρ slag

(kg/m3 )

Crystallization temperature T c (K)

2500 1441

Experimental Result and Discussion Mold Surface Temperature and Heat Flux Figure 3 shows the recorded temperatures within the mold during the continuous casting. It could be observed that the responding temperatures are in the range from 333 to 382 K. The recorded temperatures range from 333 to 382 K. Specifically, the thermocouples located 3 mm away from the mold surface (referred to as the “hot side”) register temperatures approximately 6–18 K higher than their counterparts positioned 8 mm away from the mold surface (referred to as the “cold side”). Figure 4 shows the profiles of mold heat flux and temperature along the casting direction during the continuous casting. The point on the graph where Z equals zero corresponds to the location of the shell tip. It can be observed that the heat flux and temperature of the mold surface initially increase, followed by a subsequent decrease. The maximum values for mold surface heat flux and temperature are 1.40 MW/m2 and 360.6 K, respectively.

Mold Simulator Study of Lubrication Behavior of High Carbon Steel … 420

(a) 400

T13_hot T11_hot

380

T9_hot 360

T7_hot 340 T1_hot T3_hot

T5_hot

Meauasred Temperature(K)

Meauasred Temperature(K)

420

320

1091

(b) 400 380

1

2

3 Times(s)

4

5

6

T10_cold

360 340

T2_cold T4_cold 320

0

T14_cold T12_cold

0

1

2

3 4 Times(s)

T8_cold T6_cold 5

6

370

2.2 Heat Flux, qm(MW/M2)

Fig. 4 Mold heat flux and temperature calculated by 2D-IHCP model

Heat Flux Mold Hot Face Temperature

2.0

365

1.8 1.6

360 1.4 1.2

355

1.0 0.8

0

2 4 6 8 Distance below shell ship, Z (mm)

350 10

Mold Hot Face Temperature, Tm(K)

Fig. 3 Measured mold wall temperatures during casting stage: a Thermocouples with 3 mm beneath mold surface, b thermocouples with 8 mm beneath mold surface

Initial Solidified Shell Surface Temperature As Fig. 5a shows, the measured thickness of the initial solidified shell along the casting direction was fitted with a square root function, d shell = Kt s 1/2 . The solidification time (t s , second) can be calculated using the equation t s = Z/V c , where Z is the distance below the shell tip, and V c is the casting speed. The shell solidification factor K was calculated to be 2.39 mm/s1/2 , which is consistent with the reported values [8, 12, 13]. By incorporating the shell solidification factor K into the 1DITPS model, the temperature field of the solidifying steel was reconstructed. As shown in Fig. 5b, the surface temperatures of the solidified shell decrease along the casting direction, ranging from 1767 to 1554 K in the vicinity of the meniscus with 0–10 mm below the tip of the initial solidified shell.

1092

Z. Wang et al.

(a)

4

1800

(b)

Measured Fitting line

Shell surface temperature (K)

Shell thickness, dshell (mm)

5

3 2 1 K=2.39mm/s0.5 0

0

2

4 6 8 10 12 14 16 18 Distance below shell ship, Z (mm)

20

1750 1700 1650 1600 1550 1500

0

2 4 6 8 Distance below shell ship (mm)

10

Fig. 5 Initial solidification shell thickness and surface temperature along the casting direction: a measured thickness, b temperature of shell surface calculated by 1DITPS model

Lubrication Behavior of Slag Film Near Meniscus After the experiment, the slag film that adhered to the mold along the casting direction was removed. Measurements of the slag film thickness were taken at various positions along the casting direction, and this process was repeated three times. The average of these measurements was then adopted as the thickness of the slag film present between the mold and the initial solidified shell. Figure 6a shows the slag film thickness along the casting direction. It is observed that a decrease in slag film thickness at the meniscus area, ranging from 2.87 mm at the shell tip to 1.21 mm at a location situated 10 mm below the shell tip. Based on the mold surface heat flux and temperature, as well as the measured slag film thickness along the casting direction, the heat transfer model of the slag film between the mold and initial solidification shell was utilized to compute the thickness of the liquid slag film and the temperature distribution within the interior of the slag film. Figure 6b shows the liquid slag film thickness within the slag film along the casting direction, which decreases from 0.41 mm at the shell tip to 0.13 mm at a location located 10 mm below the tip. Based on the calculated surface temperature distribution of the mold using the 2DHICP mathematical model, as well as the surface temperature profile of the initial solidified shell derived from the 1DITPS mathematical model, and incorporating the computed interior temperature distribution of the slag film using the heat transfer model between the mold and the shell, we were able to reconstruct the temperature distribution of the mold-slag film-initial solidified shell system along the casting direction, in the vicinity of the meniscus with 0–10 mm below the tip of the initial solidified shell (Fig. 7). Furthermore, the initial solidified shell exhibits a larger deformation along the casting direction, which could be attributed to the high temperature stress on the shell.

Mold Simulator Study of Lubrication Behavior of High Carbon Steel … Liquid slag film thickness, dl (mm)

Slag film thickness, dm (mm)

3.2

(a) 2.8 2.4 2.0 1.6 1.2 0.8 0.4

0

1 2 3 4 5 6 7 8 9 Distance below shell ship, Z (mm)

10

1093

0.6

(b) 0.5 0.4 0.3 0.2 0.1 0.0

0

2 4 6 8 Distance below shell ship, Z (mm)

10

Fig. 6 Slag film thickness and liquid slag film thickness along the casting direction: a slag film thickness b liquid slag film thickness

Fig. 7 Temperature field of mold-slag film-initial solidification shell along the casting direction

Conclusion In this study, a mold simulator technique was successfully investigate the lubrication behaviors of high carbon steel slag film along the casting direction on the shell. The results are summarized as follows: (1)

The heat flux and temperature of the mold surface initially increase, followed by a subsequent decrease. The maximum values for mold surface heat flux and temperature are 1.40 MW/m2 and 360.6 K, respectively.

1094

(2)

(3)

Z. Wang et al.

The surface temperature of the initial solidified shell decreases along the casting direction. The temperature ranges from 1767 to 1554 K in the vicinity of the meniscus, with a distance of 0 to 10 mm below the tip of the initial solidified shell. The liquid slag film thickness experiences a reduction along the casting direction. It diminishes from 0.41 mm at the shell tip to 0.13 mm at a location situated 10 mm below the tip.

Acknowledgements This work was supported by NSFC (52130408, 52074135), Jiangxi Provincial Natural Science Foundation (No. 20224ACB214011), and Youth Jinggang Scholars Program in Jiangxi Province (QNJG2020049).

References 1. Brandaleze E, Di Gresia G, Santini L et al (2012) Mould fluxes in the steel continuous casting process. Sci Technol Cast Process 233 2. Mills KC, Däcker CÅ (2017) The casting powders book. Springer International Publishing, Cham, Switzerland 3. Ohba Y, Yoshioka T, Matsui R et al (2021) Development of mold flux for continuous casting of high-carbon steel bloom. Tetsu Hagane-J Iron Steel Inst Jpn 107(1):64–72 4. Perrot C, Pontoire JN, Marchionni C et al (2005) Several slag rims and lubrication behaviours in slab casting. Metall Res Technol 102(12):887–896 5. Zhang S, Wang Q, He S et al (2018) Study of the mechanism of liquid slag infiltration for lubrication in slab continuous casting. Metall Mater Trans B 49:2038–2049 6. Li HR, Sun LG, Ai LQ (2014) The mould flux viscosity designing of high carbon steel for thin slab continuous casting. Adv Mater Res 1022:48–51 7. Pyhtilä TM (2022) Review of selection rules for casting powders. T. Pyhtilä 8. Wang W, Long X, Zhang H et al (2018) Mold simulator study of effect of mold oscillation frequency on heat transfer and lubrication of mold flux. ISIJ Int 58(9):1695–1704 9. Hanao M, Kawamoto M (2008) Flux film in the mold of high speed continuous casting. ISIJ Int 48(2):180–185 10. Zhou D, Wang W, Zhang H et al (2014) A study for initial solidification of Sn-Pb alloy during continuous casting: Part II. Effects of casting parameters on initial solidification and shell surface. Metall Mater Trans B 45:1048–1056 11. Zhang H, Wang W, Zhou L (2015) Calculation of heat flux across the hot surface of continuous casting mold through two-dimensional inverse heat conduction problem. Metall Mater Trans B 46:2137–2152 12. Zhang H, Wang W (2017) Mold simulator study of heat transfer phenomenon during the initial solidification in continuous casting mold. Metall Mater Trans B 48:779–793 13. Wang W, Lou Z, Zhang H (2018) Effect of slag-steel reaction on the initial solidification of molten steel during continuous casting. Metall Mater Trans B 49:1034–1045 14. Wang X, Kong L, Du F et al (2016) Mathematical modeling of thermal resistances of mold flux and air gap in continuous casting mold based on an inverse problem. ISIJ Int 56(5):803–811

Study of Tube/Pipe Cracking Induced by Casting Defects in Medium Carbon Steels Tihe Zhou, Youliang He, Peng Zhang, and Ryan Lu

Abstract Medium carbon steels have an excellent combination of tensile strength/ ductility, and low yield to tensile ratio, which are cost effective to produce and can be heat treated to different tube/pipe strength levels based on their applications. Ultrasonic failure (due to cracks) causes the most rejections for pipe and tube makers. This contribution investigated the medium carbon tube and/or pipe cracking after forming and welding. Macro- and microstructure study and SEM EDS characterization indicated these cracks are caused by casting defects, e.g., inclusions in the slab from steelmaking, centerline segregation, and slab internal cracking due to the improper casting parameter employed. Keywords Medium carbon steel · Tube/pipe · Ultrasonic test failure · Casting defects · Inclusions · Centerline segregation · Slab internal cracking

Introduction Medium carbon steels have an excellent combination of tensile strength and ductility, which are very widely used in many industries such as construction, automobile, machinery, piping and tubing, and offshore structure [1]. Using medium carbon steel to replace high strength microalloyed steel grades not only reduces the production cost but also can control yield strength pickup during cold forming due to the low yield strength to tensile ratio [2]. To improve the mechanical properties, alloying elements such as Cr, Si, Mo, Cu, Ni, and B, can be added to improve both hot-rolled and heattreated mechanical properties, as well as weldability, corrosion, and wear resistance. T. Zhou (B) · R. Lu McMaster University, Hamilton, ON, Canada e-mail: [email protected] Y. He CanmetMATERIALS, Natural Resources Canada, Hamilton, ON, Canada P. Zhang Algoma Steel Inc., Sault Ste. Marie, ON, Canada © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_95

1095

1096

T. Zhou et al.

For instance, 0.34% C steel with Cu and Ni addition has been used for cement mixer drums and tubes to improve corrosion resistance. 0.30% C steel with boron addition is used for truck axle tube to improve the hardenability during heat treatment. 0.28% C steel with Cr and Mo addition has been used for American Petroleum Institute (API) 5CT L-80/P110 pipe/tubes to improve hardenability and tensile properties [3]. For pipe/tube applications, the hot-rolled steel strips are slitted to different widths based on pipe/tube diameters, then the slitted strips are cold formed into pipe/tube and joined by electric resistance welding (ERW). Ultrasonic test (UT) is used to evaluate the welding seams and the pipe/tube body to meet different specifications and requirements. UT failure causes the most rejections for pipe and tube makers. This paper investigates three pipe types that failed UT due to the cracks which are related to the casting defects, and recommendations made to reduce these defects based on this study.

Experimental Materials and Methods Three pipes/tubes with different chemistries were selected as experimental materials in this paper, which are labeled as #S1, #S2 and #S3 sample, respectively. To investigate the pipe/tube cracking, samples were extracted and prepared using standard metallographic techniques. The sample chemical compositions were analyzed using an optical emission spectrometer. Macro- and microstructures were characterized using an optical microscopy (OM) and a scanning electron microscopy (SEM) with energy dispersive X-ray spectroscopy (EDS). Hardness measurements in HRC and microhardness HV were taken across the weld area at the OD surface and centerline and through the thickness on the parent material. Based on the pipe/tube sample casting heat identifications, the slab and hot rolled strip samples were retrieved to understand the root cause of the cracks.

Results and Discussion Inclusions The chemical composition and retrieved heat chemistry of sample #S1 are listed in Table 1. #S1 is designed for API 5CT P110 application, and the chemical composition is closely matched with the casting heat chemistry. Table 1 Chemical comparison of #S1 (wt.%) C

Mn

Si

Cr

Mo

Ni

Cu

S

P

Al

B

Ti

#S1 Pipe 0.28 1.35 0.23 0.45 0.06 0.02 0.02 0.005 0.014 0.031 0.002 0.005 Heat 0.27 1.34 0.23 0.45 0.06 0.02 0.2

0.005 0.013 0.032 0.002 0.005

Study of Tube/Pipe Cracking Induced by Casting Defects in Medium …

1097

The #S1 tube sample has UT failure and exhibits cracks in the weld zone. The microstructure close to the cracks is shown in Fig. 1. The hot-rolled microstructure of this material is ferrite and pearlite. Figure 1a is as polished cracks at tube OD surface. Figure 1b shows the cracks initiated in the weld heat affected zone and propagated through the tube thickness along the fusion line. Figure 1c, d illustrates that the elongated nonmetallic inclusions close to the cracks would be related to the tube cracks. Figure 1e, f confirms that these nonmetallic inclusions are manganese sulfide (MnS). EDS analysis at different locations is summarized in Table 2.

Figure 1 a As polished of cracks at OD surface, b 2% nital etched cracks at OD surface, c high magnification of cracks with nonmetallic inclusions, d 2% nital etched nonmetallic inclusion close to the cracks, e SEM image of cracks with nonmetallic inclusions, and f EDS analysis of nonmetallic inclusions

1098

T. Zhou et al.

Table 2 EDS analysis of nonmetallic inclusions at different locations Element

Site 1 (wt.%)

Site 2 (wt.%)

S

29.2

21.1

Site 3 (wt.%) 27.3

16.3

Site 4 (wt.%)

Mn

43.4

41.3

47.7

32.8

Fe

27.4

37.6

25.1

50.9

Total

100

100

100.1

100

Based on the metallurgical analysis, it is seen that the tube cracks near the weld for the UT failure samples are associated with the presence of MnS inclusion stringers. During the continuous casting process of medium carbon steel, the evolution of MnS inclusion strongly depends on the solidification macro-structure along the continuous casting slab thickness [4]. In the chill zone, the high cooling leads to the formation of tiny spherical MnS inclusions between fine equiaxed grains. As the cooling continues, the columnar dendrites grow along the slab thickness, and slim rodlike MnS inclusions are formed between columnar crystals, as well as some small-size dendritic MnS inclusions. Then, a mixed zone arises before the columnar zone completely transforms into equiaxed zone. The large secondary dendrite arm spacing (SDAS), high sulfur content, and low cooling rate in the mixed zone provide favorable conditions for the formation and growth of MnS inclusions, which finally grow into large size and closely distributed ones. Furthermore, the equiaxed zone is formed near the slab center, where a large amount of MnS inclusions precipitated between the dendrites. The morphologies of MnS are divided into three categories: (a) randomly dispersed globular sulfides resulting from metastable monotectic reaction (Type I), (b) the product of stable eutectic reaction, rodlike or dendrite sulfides (Type II), (c) angular sulfides (Type III) [5, 6]. Type II sulfides have good deformability and are regarded as the most harmful nonmetallic inclusions, because they can be deformed into large size stringers during hot rolling [7]. From Fig. 1c, d, it is seen that the tube cracks are induced by the large MnS stringers in the fusion line and heat affected zone. According to the work by Takada et al. [8] Type II sulfides would form in the steels once the sulfur content is more than 0.05%. To reduce Type II MnS in steelmaking, the hot metal rotary lance desulphurization technology could be used to produce ultra-low sulphur capability for pipe/tube applications [9] to reduce the UT failures.

Centerline Segregation #S2 UT failure is related to the centerline segregation. The UT failed tube chemical analysis and retrieved heat chemistry are listed in Table 3. #S2 is a medium C steel with B addition, which is used for truck axle tube application. Again, the sample chemical analysis matched well with the heat chemistry. Visual inspection did not reveal cracks at the tube surface. However, the marked UT failure had cracks after polishing as shown in Fig. 2a. Nital etched microstructure

Study of Tube/Pipe Cracking Induced by Casting Defects in Medium …

1099

Table 3 Chemical comparison of #S2 (wt.%) C

Mn

Si

Cr

Mo

Ni

Cu

S

P

Al

B

Ti

#S2 Pipe 0.31 1.21 0.21 0.04 0.01 0.02 0.03 0.003 0.014 0.027 0.003 0.003 Heat 0.32 1.20 0.22 0.04 0.01 0.02 0.03 0.003 0.014 0.026 0.003 0.003

in Fig. 2b showed that the cracks initiated at the tube surface in the weld heat affected zone and propagated along the fusion line. Figure 2c suggests the cracking continued along the quarter position segregation line. Figure 2d is the microstructure away from the crack, consisting of ferrite and pearlite. #S2 has more pearlite microstructure than #S1 due to its higher C content. Martensite is present along the crack as shown in Fig. 2e, and the hardness is 68 HRC. Microhardness measurement across the weld in Fig. 2f confirmed that austenite transformed to martensite due to the centerline segregation. According to microstructure analysis and hardness measurement, it can be concluded that the UT failure was related to high C, and Mn segregated along the centerline during solidification. The centerline will be pushed to the top surface during forming before welding. The austenite with high C and Mn in heat affected zone and fusion line can transform to martensite after welding. This martensite with low plasticity induced the cracks which caused the UT failure [10]. Medium carbon steels have higher C, Mn and Si addition, and these elements are prone to segregate in the centerline area during solidification in the continuous casting process. The ratio of segregation of P and S can reach high values; however, the total amount of these elements is very low in the segregated area; thus, they have little impact on the activity of carbon in austenite. In addition, S is prone to form sulfide inclusions in the solidification process, which has no impact to modify C activity. Mn and Si contents in these steels are high enough to modify the carbon activity. Si has a smaller effect, due to the Si content in these steels is less than Mn. Si also has a weaker influence on C activity than Mn. Mn has a strong effect in stabilizing centerline segregation. It diffuses very slowly, so there is no chance for Mn homogenization under industrial conditions, and this can result in a higher C content in the centerline area than the average C content, because Mn modifies the activity of C locally. In addition, Mn promotes bainite and martensite formation during the austenite to ferrite transformation process. To reduce the centerline segregation of continuously cast slabs, it is important to employ compatible steel composition, casting technology and casting machine settings, especially in the last third of solidification. For instance, soft-core reduction has been used in conventional continuous casting and thin slab casting to reduce the centerline homogeneity [3, 11].

Slab Internal Cracking The #S3 chemical composition and retrieved heat chemistry are listed in Table 4. #S3 is designed for API 5CT L80 large diameter pipe application, with B addition to improve the hardenability. The customer reported high pipe failure due to

1100

T. Zhou et al.

Fig. 2 a As polished view of the OD cracks, b 2% nital etch view of cracks in the weld, c the quarter position segregation continuing the cracking, d microstructure away the crack, e martensite along the cracks, f microhardness across the weld at the OD surface

the UT rejections; however, there were no pipe samples for lab investigation. The retrieved slab sample and hot-rolled samples from the same heat were investigated to understand the root cause of the UT failure. Table 4 Chemical composition of #S3 (wt.%) C

Mn

Si

Cr

Mo

Ni

Cu

S

P

Al

B

Ti

#S3 Strip 0.26 1.00 0.25 0.18 0.01 0.01 0.01 0.006 0.013 0.025 0.0028 0.022 Heat 0.26 1.02 0.25 0.18 0.01 0.01 0.01 0.006 0.013 0.025 0.0027 0.021

Study of Tube/Pipe Cracking Induced by Casting Defects in Medium …

1101

Figure 3a is macro-etch of L80 slab; it shows midway cracks which are perpendicular to the centerline. These cracks are parallel to the centerline after rolling to steel strip as shown in Fig. 2b. Figure 2c, d are optical images of midway cracks from full width steel strip sample (b). The refill cracks in the halfway position are trapped with rich solute as shown in Fig. 2e, f. After the hot-rolled steel strip is slitted into different narrow strips, the halfway cracking is pushed into the pipe surface during the ERW process and causes pipe/tube ultrasonic test failure of the weld [3]. EDS analysis of trapped solute is summarized in Table 5. These refill solutes are nonmetallic inclusion; thus, both the pipe body and the weld cannot pass the UT test. Compared to low carbon manganese (C-Mn) and low carbon microalloyed chemistries, secondary cooling, casting speed and soft-core reduction are key parameters to ensure sound slab internal quality and minimize solute segregation for medium and high carbon chemistry. During the solidification process, the first solid

Fig. 3 a Macro-etch L80 slab, b macro-etched full width hot-rolled strip sample with midway cracks, c strip sample with midway cracks (as polished), d nital etch, e SEM image of midway cracks, f EDS analysis of midway cracks

1102

T. Zhou et al.

Table 5 EDS analysis of midway crack trapped solute Element

O

Al

Si

P

S

Ca

Ti

Mn

Fe

Weight %

28.5

1.2

1.5

0.9

0.5

1.3

6.3

1.5

58.3

Atomic %

56.5

1.4

1.7

0.9

0.5

1.0

4.2

0.9

33.0

nuclei forms at the mould wall when the liquid steel first touches the copper mould, and these nuclei grow into equiaxed grains, forming the “chill zone”. The outer equiaxed crystals subsequently grow opposite to the direction of heat flow, forming the “columnar zone”. Depending on the solidification conditions, the columnar zone can consist of columnar grains, columnar dendrites, or a combination of both. As the columnar grains approach the center region of the mould, the detached branches become nucleation sites for new grains. These grains are exposed to a radial thermal gradient and grow independently at the center area, forming the “inner equiaxed zone” [12]. As-cast microstructure is a function of the temperature gradient and growth rate ahead of the microscopic solidification front. Increasing secondary cooling with restricted casting speed will increase cooling rate. As a result, the primary and second dendrite arm spacing will decrease [13, 14]. In addition, the refined as-cast microstructure makes it easier to homogenize solute segregation and the solidified shell does not bulge between rolls in the upper machine segments, preventing shell cracking. Figure 4a is composite image of a macro-etched L80 slab using increased secondary cooling (full hard secondary cooling), and Fig. 4b is hotrolled strip macro-etch from the same heat with no indication of midway cracking. Light centerline segregation is still present in both the slab and hot-rolled stirps. The above study summarized three types of pipe/tube that failed UT due to the cracks related to the casting defects. Other related defects might also cause UT failure including slab surface cracking, metallurgical, and mechanical seams, hot strip rolling mill edge scratches, rolled in scales, etc. which are beyond the scope of this study.

Fig. 4 a L80 slab and b hot rolled strip macro-etch with increased secondary cooling

Study of Tube/Pipe Cracking Induced by Casting Defects in Medium …

1103

Conclusions Three pipe/tube UT failures are related to three different casting defects: inclusions in the slab from steelmaking, centerline segregation during solidification in continuous casting process, and slab internal cracking due to the improper casting parameter setups. Reducing the pipe/tube cracking requires to control steel making using clean steelmaking practices, control the cast speed and soft-core reduction to reduce the centerline segregation and slab internal cracking. In addition, other factors causing pipe/tube cracking will require further investigation.

References 1. Dossett JL (2020) Practical heat treating: basic principles, ASM technical books, pp 1–19. https://doi.org/10.31399/asm.tb.phtbp.9781627083263 2. He BB, Wang M, Liu L, Huang MX (2019) High-strength medium Mn quenching and partitioning steel with low yield ratio. Mater Sci Technol 35(17):2109–2114 3. Zhou T, Zhang P, Kuuskman K, Cerilli E, Cho SH, Burella D, Zurob HS (2018) Development of medium-to-high carbon hot-rolled steel strip on a thin slab casting direct strip production complex. Ironmak Steelmak 45(7):603–610 4. Yu Q, Yang X, Lai C, Tong Z (2022) Study on MnS inclusion casting slab thickness of medium carbon structural steel. Metals 12:56. https://doi.org/10.3390/met12010056 5. Yoichi I, Noriyuki M, Kaichi M (1980) Formation of MnS-type inclusion in steel. Tetsu-toHagane 66:647–656 6. Oikawa K, Da Ishi K, Nishizawa T (1997) Effect of titanium addition on the formation and distribution of MnS inclusions in steel, during solidification. ISIJ Int 37:332–338 7. Diederichs R, Bleck W (2006) Modelling of manganese sulphide formation during solidification, Part I: description of MnS formation parameters. Steel Res Int 77:202–209 8. Takada H, Bessho I, Ito T (1978) Effect of sulfur content and solidification variables on morphology and distribution of sulfide in steel ingots. Trans Iron Steel Inst Jpn 18:564–573 9. Zhou T, Overby D, Badgley P, Martin-Root C, Wang X, Liang S, Zurob HS (2019) Study of processing, microstructure and mechanical properties of hot rolled ultra-high strength steel. Ironmak Steelmak 46:535–541 10. Réger M, Fábián ER, Tóth L (2019) Centerline inhomogeneity of flat products. 2019 IOP conference series: materials science and engineering, vol 572, p 012036 11. Zhou T, O’Malley RJ, Zurob HS, Subramanian M, Cho SH, Zhang P (2019) Control of upstream austenite grain coarsening during the thin-slab cast direct-rolling (TSCDR) process. Metals 9(2). https://doi.org/10.3390/met9020158 12. Cahn RW, Haasen P (1996) Physical metallurgy, 4th ed. North-Holland Physics Publishing 13. McCarrney DG, Hunt JD (1981) Measurements of cell and primary dendrite arm spacing in directionally solidified aluminum alloys. Acta Metall 29(11):1851–1863 14. Bouchard D, Kirkaldy JS (1997) Prediction of dendrite arm spacings in unsteady and steadystate heat flow of unidirectionally solidified binary alloys. Metall Mater Trans B 28B(4):651– 663

Study on Secondary Phase Precipitation Behavior of Ship Plate Steel Slab Under Different Cooling Rates in Continuous Casting Process Huisheng Wang, Qing Liu, Biao Tao, Jun Wu, Ming Li, Min Guan, and Weili Huang

Abstract The blank surface quality could be prevented through the control of the second phase precipitation. In this study, the precipitation behavior of carbon-nitrides was studied by a high-temperature confocal laser scanning microscope under the cooling rates of 0.1, 0.5, 1.0, 3.0, and 5.0 °C/s. And the effects of cooling rate on the morphology and distribution of precipitates were obtained. The results show that the initial precipitation temperature and “fast-growing region” of carbon-nitrides are varied under different cooling rates. As the cooling rate increases, the nucleation location of carbon-nitrides changes from grain boundary to grain interior. Meanwhile, its size and quantity gradually decrease. When the cooling rate is larger than 1 °C/s, the carbon-nitride mainly precipitates in grain interior. Combining the above research, a new secondary cooling method for ship plate steel slab is proposed and industrial tests are conducted, which improves the surface quality of the slab in continuous casting. Keywords Ship plate steel · Carbon-nitride precipitation · Cooling rate · Slab surface quality · Secondary cooling

H. Wang · Q. Liu (B) State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing 100083, China e-mail: [email protected] B. Tao · M. Li Nanjing Iron and Steel Co., Ltd., Nanjing, Jiangsu 225267, China J. Wu Xinjiang Bayi Iron and Steel Co. Ltd., Urumqi 830000, China M. Guan Technology Center, Jiangsu Boji Spray Systems Co., Ltd., Yangzhou 225267, Jiangsu, China W. Huang Delong Steel Co. Ltd., Xingtai 054000, Hebei, China © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_96

1104

Study on Secondary Phase Precipitation Behavior of Ship Plate Steel …

1105

Introduction Ship plate steel (SPS) is an important material in shipbuilding industry, and its quality and performance directly affect the safety and reliability of ships. SPS steel belongs to micro-alloyed steel, which will experience a series of complex physicochemical changes such as the secondary phase precipitation and the solid phase transformation in the process of continuous casting production. When the improper cooling strategy are adopted, a large number of secondary phase particles precipitate along the austenite grain boundaries, greatly increasing the occurrence of the surface and subsurface cracks of the blank [1–7]. Cooling rate is a critical parameter in controlling the secondary phase precipitation behavior, which can affect the category, dimension, morphology, and distribution of the precipitates [8–10]. The results of Luo et al. [11] and Chen et al. [12] indicated that with the increase of cooling rate, the size of carbon-nitrides gradually decreased, and the nucleation location was changed from the grain boundary to the grain interior. Dou et al. [13, 14] and Zou et al. [15] obtained similar results in their studies of micro-alloyed steels containing the elements of Nb, V, and Ti. Increasing the cooling rate promoted diffuse precipitation of the secondary phase inside the austenite grains and strengthened the microstructure of the blank surface. Generally, the precipitation temperature of carbon-nitrides is around 800–1000 °C [16, 17]. Therefore, the secondary cooling condition is the primary factor affecting the carbon-nitrides precipitation behavior. However, to obtain the reasonable secondary cooling condition, some detailed operating parameters, such as the cooling rate and temperature range, need to be clarified in continuous casting process. In this study, a high-temperature confocal laser scanning microscope (HTCLSM) was employed to observe the precipitation behavior of the secondary phase at different cooling rates. Besides, a field emission scanning electron microscopy (FESEM) were used to analyze the size and distribution of the secondary phase particles. Finally, the cooling rate and the corresponding temperature range for controlling the carbon-nitrides precipitation during the continuous casting process were obtained, and a new secondary cooling method was described to improve the surface quality of SPS slab. The plant trials show that the crack on the subsurface of SPS slab have virtually disappeared and the surface cracking ratio decreases by about 35%.

Materials and Methods The present study focused on a SPS slab produced in one steelmaking plants. SPS belongs to micro-alloyed steel, which is strengthened by adding micro-alloyed elements of V, Ti, and Nb into carbon manganese steel. The main chemical composition of SPS was obtained by testing the molten steel composition in the tundish, as shown in Table 1. In this study, a HTCLSM was adopted for an in-situ observation of the solidification of SPS slab. The experimental specimens were extracted from

1106

H. Wang et al.

Table 1 Main chemical composition of SPS, % C

Nb

V

Ti

N

Other elements

0.048

0.051

0.0195

0.009

0.004

2.877

Fig. 1 The schematic diagram of sampling location and specimen size

the columnar crystal zone of the slab with a section size of 2770 mm × 320 mm, as shown in Fig. 1. The center segregation and porosity of the slab were avoided during sampling, and the as-cast microstructure of each specimen was similar. The specimen was machined into a cylinder with a size of ϕ5 mm × 3 mm, whose surfaces were grinded and polished before put them into alumina crucibles for experiments. The experiments were carried out under the thermal regime. During the experiment, the specimens were heated from room temperature to 1495 °C at a heating rate of 10 °C/s and then held isothermally for 15 min to dissolve the carbon-nitrides. After that, the specimens were cooled to experimental temperatures at five different cooling rates of 0.1, 0.5, 1, 3, and 5 °C/s to observe the effects of cooling rate on the precipitation behavior of the carbon-nitrides. During the experiments, the specimens were heated and cooled under an ultra-high purity argon atmosphere (99.999%). The thermocouple placed in the crucible was used to measure the specimen temperature. The corresponding principles and operating methods are consistent with those described by Zou et al. [15], Dou et al. [13], Griesser et al. [18], and Kimura et al. [19].

Results and Discussion To control the carbon-nitrides precipitation behavior in continuous casting process, it is essential to clarify the detailed parameters such as precipitation temperature and reasonable cooling rate, which requires the investigations of the carbon-nitrides precipitation behavior under different cooling rates.

Study on Secondary Phase Precipitation Behavior of Ship Plate Steel …

1107

In-Situ Characterization of Secondary Phase Precipitation In-situ characterization is a method for continuously observing the microstructural evolution of the specimen surface at a defined cooling rate. The precipitation temperature of the carbon-nitrides is usually obtained using thermodynamic or kinetic calculations. Unfortunately, the calculated results often deviate from the actual results due to the difficulty of accurately obtaining the phase transition parameters. In contrast, in-situ characterization of carbon-nitrides precipitation removes this problem effectively. To simulate the secondary cooling condition during the continuous casting process of SPS slab, the carbon-nitrides precipitation behavior was investigated at a cooling rate of 0.1 °C/s, as shown in Fig. 2. The observation results illustrate that a few dark particles appear near the austenite grain boundary when the temperature decreases from 1495 to 1455 °C (as shown in Fig. 2a). As is found by Slater et al. [20] and other scholars [13, 21], the dark particles are the direct signs of the carbon-nitrides, and similar experimental phenomena have been reported in previous in-situ observation studies [12, 19, 22, 23]. Therefore, the present study investigates the behavior of carbon-nitrides precipitation by observing the formation and change of dark particles. Dark particles are first formed near austenite grain boundary due to the segregation of solute elements usually occurs in this area. As illustrate in Fig. 2a–c, the dark particles increase rapidly between 1455 and 1375 °C with the temperature decreases. After that, when the temperature decreases to 1116 °C, a new type of dark particles with smaller sizes starts to appear near the austenite grain boundary, as shown in Fig. 2d. The new dark particles increase rapidly between 1116 and 959 °C. Furthermore, the eutectoid phase transformation occurs between 720 and 670 °C, which corresponds to the location after the straightening zone of continuous casting process. Thermo-Calc software was used to calculate the diagram of SPS phase equilibrium, as shown in Fig. 3. It is found that TiN starts to precipitate at 1146 °C, and the fastest precipitation temperature is around 1350–1400 °C. The initial precipitation temperature of Nb(C, N) is about 1056 °C, and the fastest precipitation temperature is in the range of 950–1000 °C. V(C, N) precipitates with the precipitation of Nb(C, N), while the amount of V(C, N) precipitation is extremely minor (less than 1% of total precipitation). The above calculation results are consistent with the in-situ observation by HTCLSM. Furthermore, Xie et al. [17] and Parker et al. [16] investigated the carbon-nitrides precipitation in Nb-containing steel through kinetic calculation, and the results suggested that the initial precipitation temperature of carbon-nitrides was about 1100 °C. Liu et al. [22] also discovered some dark particles on Ti-containing steel surface using in-situ observation, and found that under the dark particle was Ti(C, N). Zou et al. [15] clarified the mechanism for the formation of dark particles on micro-alloyed steel surface during in-situ observation process. Therefore, in this study, the dark particles detected via in-situ observations were adopted to characterize the behaviors of carbon-nitrides precipitation. According to the experimental results, it can be inferred that the fastest precipitation temperature of TiN is around 1455–1375 °C, which is around 1116–959 °C for Nb(C, N).

1108

H. Wang et al.

Fig. 2 Experimental results of in-situ observations at 0.1 cooling rate, a 1455 °C; b1400 °C; c 1375 °C; d 1116 °C; e 1050 °C; f 959 °C Fig. 3 Diagram of SPS phase equilibrium calculated using Thermo-Calc software

Effects of Cooling Rate on Secondary Phase Precipitation Behavior In the secondary cooling zone (SCZ) of continuous casting, the cooling rate on the slab surface varies with cooling water volume. The present study simulated the solidification phase transition process of SPS slab under different cooling conditions by setting different cooling rates, which included 0.5, 1.0, 3.0, and 5.0 °C/s.

Study on Secondary Phase Precipitation Behavior of Ship Plate Steel …

1109

Effects of Cooling Rate on TiN Precipitation The in-situ observation of TiN precipitation at different cooling rates is shown in Fig. 4. The results illustrate that the initial temperature of TiN precipitation gradually decreases with the increase of cooling rate. When the cooling rate is 0.5 °C/s, 1.0 °C/s, 3.0 °C/s and 5.0 °C/s, TiN starts to precipitate at the temperature of 1452 °C, 1445 °C, 1439 °C, and 1422 °C, respectively. Besides, the corresponding fastest precipitation temperature is around 1452–1373 °C, 1445–1370, 1439–1358, and 1422–1345 °C. Furthermore, as the cooling rate increases, the precipitation location of TiN gradually changes form grain boundary to grain interior, and the quantity of precipitation gradually decreases. The reason is that the diffusion coefficient of solute elements decreases exponentially with the increase of cooling rate [15]. Therefore, most of the Ti atoms are solubilized in the steel matrix at high cooling rates, rather than being enriched at grain boundaries or forming TiN precipitates. As shown in Fig. 4b–d, when the cooling rate is increased to 1 °C/s, the TiN precipitation basically disappears from austenite grain boundaries. Moreover, when the cooling rate is enlarged to 5 °C/ s, the size of dark particles induced formation by TiN precipitation is less than 1/5 of that at 0.1 °C/s cooling rate. Due to the high temperature of TiN precipitation, the TiN precipitation on SPS slab surface is generally completed in the mold cooling process during continuous casting, where the cooling rate on the slab surface is considerably greater than 5 °C/s. It is indicated that TiN precipitation will be smaller in size and quantity, and have less effect on grain boundaries. Therefore, the precipitation of TiN is not the major reason for the crack formation on SPS slab surface in continuous casting process.

Effects of Cooling Rate on Nb(C, N) Precipitation The in-situ observation of Nb(C, N) precipitation at different cooling rates is shown in Fig. 5. Similar to the change in the precipitation distribution of TiN, the precipitation location of Nb(C, N) also changes form grain boundary to grain interior with the cooling rate increases. When the cooling rate is less than 3 °C/s, the initial precipitation temperature and the quantity of Nb(C, N) precipitation decrease rapidly with the increase of the cooling rate, especially in increasing of the cooling rate from 0.5 to 1 °C/s. This is because increasing the cooling rate significantly decreases the migration rate of solute elements such as Nb, which in turn reduces its enrichment at grain boundaries. Meanwhile, a large amount of Nb is solidly dissolved in the steel matrix. When the cooling rate is 0.5 °C/s, 1.0 °C/s, and 3.0 °C/s, the initial precipitation temperature of Nb(C, N) is 1094 °C, 1010 °C, and 1001 °C, with the corresponding fastest precipitation temperature in the range of 1094–954 °C, 1010–952 °C, 1001– 948 °C, respectively. The effect of cooling rate on the end temperature of the fastest precipitation is minor, indicating that the fastest precipitation temperature range of Nb(C, N) gradually decreases as the cooling rate increases. When the cooling rate enlarges from 0.1 to 3 °C/s, the fastest precipitation temperature range reduces from 157 to 51 °C, which is conducive to controlling the precipitation behavior of Nb(C,

1110

H. Wang et al.

Fig. 4 In-situ observation of TiN precipitation at different cooling rates, a 0.5 °C/s; b 1.0 °C/s; c 3.0 °C/s; d 5.0 °C/s

N) on the SPS slab surface in the continuous casting process. However, when the cooling rate adds from 3 to 5 °C/s, the initial precipitation temperature of Nb(C, N) increases from 1001 to 1060 °C with the fastest precipitation temperature around 1060–1020 °C. The distribution of Nb(C, N) precipitation is dispersed inside the grain. Considering the high Nb content in SPS (about 510 ppm), increasing the cooling rate rapidly reduces its local solubility in the steel matrix, which in turn facilitates the precipitation of Nb(C, N). Therefore, under the cooling rate of 5 °C/ s, the precipitation temperature of Nb(C, N) is increased and the precipitation is fine-sized and dispersed inside the austenite grains, as shown in Fig. 5d. In the SCZ of continuous casting, the surface temperature of SPS slab is around 900–1200 °C, which is consistent with the precipitation temperature of Nb(C, N). Hence, the precipitation behavior of Nb(C, N) has an important effect on the formation of SPS slab surface and subsurface crack. Reasonable temperature and cooling rate are key to controlling Nb(C, N) precipitation behavior in continuous casting.

Study on Secondary Phase Precipitation Behavior of Ship Plate Steel …

1111

Fig. 5 In-situ observation of Nb(C, N) precipitation at different cooling rates, a 0.5 °C/s; b 1.0 °C/ s; c 3.0 °C/s; d 5.0 °C/s

Effects of Cooling Rate on the Morphology and Distribution of Precipitations To clearly observe the morphology and distribution of the precipitated phase, a FESEM was applied to analyze the precipitated phase at different cooling rates. The FESEM has higher magnification and resolution. Figure 6 shows the observation results by FESEM in the secondary electrolysis mode. At a low cooling rates of 0.1 °C/s or 0.5 °C/s, chain-like carbon-nitrides precipitate at austenite grain boundaries, which greatly reduces the bonding force of austenite grain boundaries and then induces the occurrence of crack defects. When the cooling rate is between 1 and 5 °C/ s, the chain-like precipitation of carbon-nitrides is basically disappeared. In addition, the precipitates are diffusely distributed on the surface of the steel matrix. The above results are consistent with the observations of HTCLSM.

1112

H. Wang et al.

Fig. 6 Morphology of precipitates at different cooling rates, a 0.1 °C/s; b 0.5 °C/s; c 1.0 °C/s; d 3.0 °C/s; e 5.0 °C/s; f energy-dispersive spectrum analysis

In summary, increasing the cooling rate is conducive to promoting the diffuse precipitation of carbon-nitrides, fully exerting its fine grained and precipitate strengthening, thus enhancing the strength of micro-alloyed steel. To achieve useful secondary precipitation phase on SPS slab surface, the cooling rate requires to more than 1 °C/s. The study conducted by our team on micro-alloyed steel billets has confirmed this conclusion [15]. Meanwhile, the slab surface temperature suggests to rapidly reduced to 950 °C to shorten the precipitation time of the secondary phase.

A New Cooling Method for SPS Slab During the continuous casting process of SPS, mild cooling mode was adopted to avoid cracks in the straightening zone. However, serious cracks still existed on the slab surface and subsurface. To find the reason of the crack formation, optical microscope (OM) and scanning electron microscope (SEM) were employed to observe the micromorphology and element distribution of the cracks. Figure 7 shows the OM images of crack distribution of SPS slab. The cracks extend along the austenite grain boundaries with a length of less than 1 mm. These small cracks seriously damage the hot ductility of steel. Furthermore, Nb and Ti elements are enriched near the cracks, as shown in Fig. 8. Therefore, it can be inferred that carbon-nitrides precipitations at grain boundaries are the primary reason for subsurface crack formation. A heat transfer model considering the actual water distribution in the SCZ is established to calculate the thermal behavior and cooling rate of SPS slab. The detailed modeling process and the calculation of cooling rate were provided in the previous works of our team [13, 24, 25]. The heat transfer model was verified by comparing the measured temperatures with the calculated ones. An infrared radiation pyrometer was used to measure the surface temperature of SPS slab, whose error range

Study on Secondary Phase Precipitation Behavior of Ship Plate Steel …

1113

Fig. 7 OM morphology of the subsurface cracks of SPS slab

Fig. 8 Element distribution in a surface crack

was ±1.5%. During the measurement, the pyrometer was required to remain perpendicular to the surface of the inner arc and peak values were adopted as the local temperature of the slab surface. Figure 9 shows the temperature profiles of SPS slab under different cooling patterns. Apparently, the calculated results agreed with the measured values with an error less than 1%, which confirmed the heat transfer model is generally reliable. In the SCZ of continuous casting, the surface temperature of SPS slab is between 1116 and 1032 °C under the original cooling pattern. The average cooling rates of the first to forth segments in the SCZ are 2.41, 0.88, 0.31, and 0.28 °C/s. Obviously, the average cooling rates in other segments are less than 0.3 °C/s. The surface temperature of SPS slab in the first segment of the SCZ is around 1116–1107 °C. Combine with the above analysis, the slab surface experienced a comparatively longer period of high temperatures in the SCZ during continuous casting, which provides sufficient conditions for Nb(C, N) to nucleate and precipitate from the matrix and the austenite grain boundaries. To prevent the precipitation and growth of the secondary phase at grain boundaries, a new secondary cooling method for SPS slab is applied in this study. Specifically, the water flowrate in the first to third and fifth segments are increased to 1.5 times than that the original water flowrate and the other segments remains constant. The temperatures of the slab surface center and corner after conducting the new cooling pattern are

1114

H. Wang et al.

Fig. 9 The SPS slab surface temperatures in different secondary cooling patterns

shown in Fig. 9. At the end of the second segment in the SCZ, the temperature on the slab surface center is significantly decreases to 950 °C, indicating that most of carbonnitride particles have precipitated. The cooling rate in the second segment increases from 0.88 to 1.24 °C/s, which effectively prevents the carbon-nitrides precipitation from the grain boundaries. In addition, the maximum reheating temperature on the slab surface is 96 °C/m after adopting the relatively high water flowrate in the SCZ, suggesting that no internal cracks will be induced. Due to the slab corner involves twodimensional cooling, the solidification behavior shows relatively lower temperature and higher cooling rate [13, 26], which effectively inhibits the precipitation of carbonnitrides. In addition, the corner temperature in the straightening zone larger than the third brittleness temperature of the SPS slab (around 666–745 °C). After the implementation of the secondary cooling scheme, the cracks on SPS slab subsurface disappeared and the surface cracking ratio decreases by about 35%.

Conclusion The carbon-nitride precipitation behavior was characterized in-situ by HTCLSM, and the effect of cooling rate on the morphology, distribution, initial precipitation temperature, and “fast-growing region” were investigated by HTCLSM and FESEM. Based on these, a new secondary cooling method for SPS slab is proposed. The conclusions are as follows: (1) The precipitation process of carbon-nitrides is usually accompanied by the formation of dark particles. As the cooling rate increases, the precipitation location of carbon-nitrides gradually changes from grain boundaries to the steel matrix, and the corresponding number and size are relatively reduced.

Study on Secondary Phase Precipitation Behavior of Ship Plate Steel …

1115

(2) TiN precipitates at high temperatures, and when the cooling rate increases from 0.1 to 5 °C/s, the initial precipitation temperature decreases from 1455 to 1422 °C. Nb(C, N) precipitates at a relatively low temperature, and its value is around 1116–1001 °C. The lowest completion temperatures for the fastest precipitation of TiN and Nb(C, N) are 1345 and 948 °C at different cooling rates. (3) Nb(C, N) precipitated at grain boundaries is the main reason for inducing cracks on the SPS slab surface. Intensive cooling is carried out by increasing the water flowrate to 1.5 times than that the original water flowrate in the first to third and fifth segments of the SCZ. The plant trials show that the cracks disappeared and the surface cracking ratio decreases by about 35% after applying this secondary cooling scheme. Acknowledgements The present work was financially supported by the independent subject of State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, China, (No. 41622007), Nanjing Iron & Steel Co., Ltd., China (No. 2020-0617), Xinjiang Bayi Iron and Steel Co., Ltd., China (No. 2015-275), Innovative & Entrepreneurial Talent Project in Jiangsu province, China (No. 2016A426) and Delong Steel Co., Ltd., China (No. 2019-0509).

References 1. Annan K, Siyasiya C, Stumpf W (2018) Austenite grain growth kinetics after isothermal deformation in microalloyed steels with varying Nb concentrations. ISIJ Int 58(2):333–339. https:// doi.org/10.2355/isijinternational.ISIJINT-2017-464 2. Gong P, Palmiere E, Rainforth W (2015) Dissolution and precipitation behaviour in steels microalloyed with niobium during thermomechanical processing. Acta Mater 97:392–403. https://doi.org/10.1016/j.actamat.2015.06.057 3. Kim S, Kim J, Kim N (2002) Effect of boron on the hot ductility of Nb-containing steel. Metall Mater Trans A 33(3):701–704. https://doi.org/10.1007/s11661-002-0133-2 4. Mohamed Z (2002) Hot ductility behavior of vanadium containing steels. Mater Sci Eng A Struct Mater: Prop Microstruct Process 326(2):255–260. https://doi.org/10.1016/S0921-509 3(01)01490-3 5. Qing J, Wang L, Dou K, Wang B, Liu Q (2016) Influence of V-N microalloying on the hightemperature mechanical behavior and net crack defect of high strength weathering steel. High Temp Mat Pr-Isr 35(6):575–582. https://doi.org/10.1515/htmp-2014-0240 6. Qu T, Tian J, Chen K, Xu Z, Wang D (2019) Precipitation behaviour of TiN in Nb-Ti containing alloyed steel during the solidification process. Ironmak Steelmak 46(4):353–358. https://doi. org/10.1080/03019233.2017.1396722 7. Senuma T (2001) Physical metallurgy of modern high strength steel sheets. Isij Int 41(6):520– 532. https://doi.org/10.2355/isijinternational.41.520 8. Carpenter K, Dippenaar R, Killmore C (2009) Hot ductility of Nb- and Ti-bearing microalloyed steels and the influence of thermal history. Metall Mater Trans A 40(3):573–580. https://doi. org/10.1007/s11661-008-9749-1 9. Cho K, Mun D, Kim J, Park J, Lee J, Koo Y (2010) Effect of boron precipitation behavior on the hot ductility of boron containing steel. Metall Mater Trans A 41(6):1421–1428. https://doi. org/10.1007/s11661-010-0211-9 10. Mun D, Shin E, Choi Y, Lee J, Koo Y (2012) Effects of cooling rate, austenitizing temperature and austenite deformation on the transformation behavior of high-strength boron steel. Mater Sci Eng A 545:214–224. https://doi.org/10.1016/j.msea.2012.03.047

1116

H. Wang et al.

11. Luo Y, Guo H, Guo J (2019) Effect of cooling rate on the transformation characteristics and precipitation behaviour of carbides in AISI M42 high-speed steel. Ironmak Steelmak 46(7):698–704. https://doi.org/10.1080/03019233.2018.1461593 12. Chen T, Ji C, Zhu M (2020) Effect of cooling rate on the nucleation and growth of large TiC particles in Ti-Mo steel. J Alloy Compd 823:153650. https://doi.org/10.1016/j.jallcom.2020. 153650 13. Dou K, Liu Q (2020) A new cooling strategy in curved continuous casting process of vanadium micro-alloyed YQ450NQR1 steel bloom combining experimental and modeling approach. Metall Mater Trans A 51(8):3945–3955. https://doi.org/10.1007/s11661-020-05819-9 14. Dou K, Meng L, Liu Q, Liu B, Huang Y (2016) Influence of cooling rate on secondary phase precipitation and proeutectoid phase transformation of micro-alloyed steel containing vanadium. Met Mater Int 22(3):349–355. https://doi.org/10.1007/s12540-016-2676-6 15. Zou L, Zhang J, Liu Q, Tao B (2022) Characterization and control of secondary phase precipitation of Nb–V–Ti microalloyed steel during continuous casting process. ISIJ Int 62(11):2286–2293. https://doi.org/10.2355/isijinternational.ISIJINT-2022-172 16. Park J, Ha Y, Lee S, Lee Y (2009) Dissolution and precipitation kinetics of Nb(C, N) in austenite of a low-carbon Nb-microalloyed steel. Metall Mater Trans A 40(3):560–568. https://doi.org/ 10.1007/s11661-008-9758-0 17. Xie S, Lee J, Yoon U, Yim C (2002) Compression test to reveal surface crack sensitivity between 700 and 1100 °C of Nb-bearing and high Ni continuous casting slabs. ISIJ Int 42(7):708–716. https://doi.org/10.2355/isijinternational.42.708 18. Griesser S, Reid M, Pierer R, Bernhard C, Dippenaar R (2014) In situ quantification of microsegregation that occurs during the solidification of steel. Steel Res Int 85(8):1257–1265. https:// doi.org/10.1002/srin.201300024 19. Kimura S, Nakajima K, Mizoguchi S, Hasegawa H (2002) In-situ observation of the precipitation of manganese sulfide in low-carbon magnesium-killed steel. Metall Mater Trans A 33(2):427–436. https://doi.org/10.1007/s11661-002-0103-8 20. Slater C, Hechu K, Sridhar S (2017) Characterisation of solidification using combined confocal scanning laser microscopy with infrared thermography. Mater Charact 126:144–148. https:// doi.org/10.1016/j.matchar.2017.02.025 21. Griesser S, Bernhard C, Dippenaar R (2014) Effect of nucleation undercooling on the kinetics and mechanism of the peritectic phase transition in steel. Acta Mater 81:111–120. https://doi. org/10.1016/j.actamat.2014.08.020 22. Liu T, Long M, Chen D, Huang Y, Yang J, Duan H, Gui L, Xu P (2020) Investigation of the peritectic phase transition in a commercial peritectic steel under different cooling rates using in situ observation. Metall Mater Trans B 51(1):338–352. https://doi.org/10.1007/s11663-01901758-y 23. Liu Z, Kobayashi Y, Yang J, Nagai K, Kuwabara M (2006) “In-situ” observation of the δ/ γ phase transformation on the surface of low carbon steel containing phosphorus at various cooling rates. Isij Int 46(6):847–853. https://doi.org/10.2355/isijinternational.46.847 24. Han Y, Yan W, Zhang J, Chen J, Chen WQ, Liu Q (2021) Comparison and integration of final electromagnetic stirring and thermal soft reduction on continuous casting billet. J Iron Steel Res In 28(2):160–167. https://doi.org/10.1007/s42243-020-00412-1 25. Han Y, Yan W, Zhang J, Chen W, Chen J, Liu Q (2020) Optimization of thermal soft reduction on continuous-casting billet. ISIJ Int 60(1):106–113. https://doi.org/10.2355/isijinternational. ISIJINT-2019-409 26. Shamsi M, Ajmani S (2010) Analysis of mould, spray and radiation zones of continuous billet caster by three-dimensional mathematical model based on a turbulent fluid flow. Steel Res Int 81(2):132–141. https://doi.org/10.1002/srin.200900103

Part XXX

Electrical Steels

Effect of Processing Methods on the Magnetic Properties of Non-oriented Electrical Steel Shengjie Wu, Wanlin Wang, Chongxiang Yue, and Hualong Li

Abstract The effects of two sample processing methods, punching and laser cutting, on the magnetic properties of high-grade non-oriented electrical steel were studied. The results show that the coercivity and iron loss of laser cutting samples are higher than those of mechanical punching, while the permeability gets lower in laser cutting samples. Through the analysis of grain internal stress by EBSD, it is found that there is a stress concentration area in the cutting section of punching sample, while there is no obvious stress concentration area near in the cutting section of laser cutting sample. While the laser cutting surface is wrapped with an oxide layer with the thickness of 1 µm through EDS energy spectrum analysis. The oxide layer causes the hysteresis loss increased under the magnetic induction intensity of 1.0 T, and the influence is amplified with the increase of loading frequency. However, when the magnetic induction intensity increases to 1.5 T, the influence of oxide layer on hysteresis loss decreases and the abnormal loss increases. Keywords Non-oriented electrical steel · Laser cutting · Hysteresis loss · Abnormal loss

Introduction Non-oriented electrical steel (NOES) is a kind if soft magnetic material used in the iron core of motors and generator rotors working in rotating magnetic fields. The electrical motor working in high efficiency and low cost not only meets the low carbon S. Wu · W. Wang (B) School of Metallurgy and Environment, Central South University, Changsha 410083, Hunan, China e-mail: [email protected] National Center for International Research of Clean Metallurgy, Central South University, Changsha 410083, Hunan, China C. Yue · H. Li Institute of Research of Iron and Steel, Shasteel, Zhangjiagang 215625, Jiangsu, China © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_97

1119

1120

S. Wu et al.

development demand, but also improves machine competitiveness; it is necessary to develop high performance NOES with high magnetic induction and low iron loss [1–5]. To develop high performance NOES, researchers mainly focus on the composition and production process [6–9]. However, there is limited research on the impact of sample processing methods on the magnetic properties of NOES [10–14]. At present, in the field of magnetic property testing sample processing, there are mainly mechanical cutting, laser cutting, and wire cutting methods. Some studies suggest that shear stress is generated during the mechanical stamping and cutting process, leading to grain bending deformation, lattice distortion. The destruction of magnetic domains along the shear edge with a width of 0.5–1 mm [15]. Vandenbossche used a mathematical model to calculate the distribution of magnetic permeability in the stress affected zone [16]. The results indicate that the closer to the edge, the more pronounced the deterioration of magnetic permeability. The main reasons for the deterioration of electrical steel damage caused by stamping and cutting are: (1) increased edge hysteresis loss caused by punching stress; (2) the edge permeability decreases. In order to achieve higher magnetic induction intensity, it is necessary to increase the magnetic flux in the iron core, indirectly change the magnetization characteristics at the edges, and increase iron loss. In order to reduce the concentration of edge stress during the punching process and improve the automation of sample processing, laser cutting processing has been widely adopted by various steel mills in recent years. This article focuses on the comparative study of the impact of laser cutting and plate cutting processing on the loss of non-oriented electrical steel.

Materials and Experimental Procedure The experimental material is a high-grade non-oriented electrical steel 35WV1900 produced by a domestic steel factory, with chemical composition (mass fraction) of 0.002%C, 3.0%Si, 0.5%Al, 0.25%Mn, and the rest being Fe and inevitable impurities. The size of the experimental template is 0.35 mm × 1200 mm × 400 mm. The samples were processed into 20 sets of Ebstein magnetic property measurement standard samples using TGJG-1000GZ laser automatic cutting machine and ACCER61355 cold rolling shearing machine, with a sample size of 0.35 mm × 30 mm × 300 mm, with a total of 24 samples per set, including 12 samples in both the horizontal and vertical directions. To avoid differences in test samples, the raw plate before processing is adjacent to the industrial production raw roll. After sampling adjacent positions, laser cutting and plate cutting processing are carried out separately. After the sample processing is completed, the magnetic properties are tested using TD-8520 magnetic property measuring instrument, with testing frequencies of 50– 400 Hz and magnetic induction strengths of 1.0 T and 1.5 T, respectively. The microhardness on the edge area of tested samples is measured by WilsonVH3100 hardness

Effect of Processing Methods on the Magnetic Properties …

1121

tester, with a test load of 20 g. The residual stress is analyzed by EBSD method. The composition of cut section is analyzed by EDS method using JSM-7001F scanning electron microscopy.

Results The Influence of Sample Processing Methods on Magnetic Properties Figure 1 shows the comparative data of iron loss P1.0/400 of NOES 35WV1900 under two processing methods of laser cutting and plate cutting in 20 groups. The measurement of iron loss for NOES mainly limits two parameters, one is the magnetic induction and the other is the loading frequency. For example, iron loss P1.0/400 represents the iron loss of the sample under magnetic induction intensity of 1.0 T and loading frequency of 400 Hz. In Fig. 1, it can be found that the iron loss of laser cutting samples is significantly higher than that of punching samples. The average iron loss of laser cutting 20 groups of samples is 18.518 W/kg, while the average iron loss of punching samples is 17.311 W/kg, with a deviation of 1.207 W/kg between the two groups. In order to investigate the iron loss of two processing methods under different excitation conditions, two sets of samples with the same original coil position and different processing methods were selected for magnetic property comparison testing. The iron loss of laser cutting samples P1.0/400 was 18.531 W/kg, and the iron loss of punching samples P1.0/400 was 17.227 W/kg. To further investigate the impact of two processing methods on iron loss under different excitation conditions. Two sets of magnetic performance test samples were selected for comparative analysis of magnetic performance under different magnetic induction intensities of 0.15–1.75 T and loading frequencies of 50–400 Hz. Figure 2 shows the magnetization process and magnetic permeability of the samples under two processing methods, with a fixed loading frequency of 400 Hz and an external field strength of 20–8000 A/m. From Fig. 2a, it can be found that when the external magnetic field intensity is lower than 700 A/m, the magnetic induction intensity excited by the laser cutting sample is relatively lower under the same magnetic field intensity. When the external magnetic field intensity is greater than 700 A/m, the magnetic induction intensity excited by the same magnetic field intensity is basically the same. In Fig. 2b, the magnetic permeability μ of the laser cutting sample is relatively lower than punching sample. Figure 3 shows the iron loss and coercive force of two sets of processing methods of samples under the condition of fixed magnetic induction intensity of 1.0 T and loading frequency of 50–400 Hz. In Fig. 3, it can be found that the samples processed by laser cutting have higher iron loss and coercivity than those processed by punching under various frequency conditions. When the loading frequency increased, the deviation

1122

S. Wu et al.

Fig. 1 Iron loss of 35WV1900 non-oriented electrical steel under laser cutting and punching processes

Fig. 2 Effect of processing methods on the a magnetization curve and b permeability at 400 Hz

values of iron loss and coercive force show an increasing trend. During the process of alternating magnetization, the increase in coercivity is an important reason for the increase in iron loss.

Analysis of Edge Stress State Some studies suggest that the increased iron loss of the laser cutting sample is related to the thermal stress generated during the laser cutting process [1]. For this purpose,

Effect of Processing Methods on the Magnetic Properties …

1123

Fig. 3 Effect of sample processing method on iron loss and coercivity under different frequencies. a Total iron loss (Ps ); b coercivity (H c )

this article conducts microhardness tests on the edges of the two processing methods of the test samples, with a point spacing of 50 µm. The results are shown in Fig. 4. It can be found that the hardness of the cutting edge is 235 HV0.2, while the hardness of the laser cutting edge is 220 HV0.2, and the hardness of the sample center far from the processing edge is 205 HV0.2. It can be seen that punching is more prone to cause stress concentration on the edge, while laser cutting has a smaller degree of edge stress concentration. To further characterize the impact of two processing methods on edge stress concentration, the EBSD method was used to analyze the internal stress in edge grains. By characterizing grain defects and dislocation density, local orientation differences were used to analyze the internal stress. Areas with higher values indicated higher defect density. The results are shown in Fig. 5. It can be seen found there is no significant difference in microstructure between laser cutting and punching, with an average grain size of 120 µm. There is a significant stress concentration area within the range of 100 µm in punching sample, while there is no significant stress concentration area at the edge of the laser cutting sample. According to research result [17], stress concentration at the edge of the cutting plate processing can lead to an increase in coercive force and iron loss of the sample during AC magnetization. However, from the actual magnetic performance test results, the iron loss of the laser cutting sample is higher than that of the shear plate processing. This indicates that compared to the stress concentration in punching sample, there are other reasons for the increasing in coercivity and iron loss.

Cross-Section Energy Spectrum Analysis To further analyze the differences between laser cutting and punching processing, the surface and cross-section of the samples processed by the two methods were analyzed by EDS. The results are shown in Fig. 6. In Fig. 6a, it can be found that the laser cutting sample extends throughout the entire cutting section to wrap a layer of

1124

S. Wu et al.

Fig. 4 Hardness distribution of cutting edge under different processing methods

aluminum oxide on the surface, while the cutting surface processed by punching is an exposed iron matrix without an aluminum oxide layer, as shown in Fig. 6b. To further clarify the thickness of the oxide layer on the laser cut section, a depth of 10 µm was cut using a focused ion beam (FIB) in a scanning electron microscope vacuum environment groove and EDS energy spectrum surface scanning were performed on the FIB cross-section, as shown in Fig. 7. It can be found that the original laser cutting cross-section was not only aluminum oxide, but also a layer of silicon aluminum composite oxide layer, with a thickness of approximately 1µm. Through EDS analysis and observation from different perspectives, it is clear that after laser cutting, the cross-section of the sample is covered with a layer of silicon aluminum oxide layer, and the schematic diagram is shown in Fig. 8.

Discussion Regarding the impact of processing methods on the magnetic properties of NOES, some studies suggest that the internal stress generated during sample processing can lead to an increase in iron loss. Laser cutting generates thermal stress due to rapid heating and cooling, which in turn affects the iron loss during magnetic property testing. Some studies suggest that [18], the thermal stress generated by laser cutting is higher than the internal stress generated by punching, resulting in higher iron loss of laser cutting samples during magnetic property testing compared to punching. From the experimental results in this article, it can be found that there is no significant stress concentration at the edge of the cutting surface of the laser cutting sample,

Effect of Processing Methods on the Magnetic Properties …

a

b

c

d

1125

Internal stress Fig. 5 Edge stress distribution under different processing methods. a and b punching; c and d laser cutting

but there is an encapsulated silicon aluminum oxide layer on the cutting surface. This oxide layer is mainly due to the rapid melting and vaporization irradiated by highpower laser beams during laser cutting. The alloy elements silicon and aluminum in NOES are easily oxidized at high temperatures with oxygen in the air, forming a silicon aluminum oxide layer [19]. Through comparative magnetic properties tests, it was found that the impact of laser cutting of the oxide layer on iron loss testing is greater than the impact of internal stress during mechanical punching. However, there is a lack of theoretical analysis on the influence of laser cutting of the oxide layer on the hysteresis loss Ph , eddy current loss Pe , and anomalous loss Pa . Therefore, this article further investigated the composition of the iron loss of the two processing methods of the samples under different excitation conditions. According to the iron loss model proposed by Bertotti [18], under alternating excitation conditions, the measured iron loss value of the epstein square coil can be represented by the following equation: PFe = Ph + Pe + Pa

(1)

1126

S. Wu et al.

(a)

(b)

Fig. 6 EDS of cutting section under different processes: a laser cutting, b punching

PFe = kh f B α + ke f 2 B 2 + ka f 1.5 B 1.5

(2)

(√ )2 √ PFe =a+b f +c f f

(3)

In Eq. 1, PFe is the total iron loss, hysteresis loss Ph , eddy current loss Pe , and anomalous loss Pa . In Eq. 2, k h , k a , k e are the material constants, f is the frequency, B is the magnetic induction, α = 1.5–2.5; In Eq. 3, a = kh B α , b = ka B 1.5 , c = ke B 2 .

Effect of Processing Methods on the Magnetic Properties …

1127

Fig. 7 EDS of cutting section under laser cutting process

oxide layer

30mm×300mm Epstein sample

Fig. 8 Schematic of cutting section oxidation of Epstein sample after laser cutting processing

Under specified magnetic induction and different frequency conditions, the iron loss PFe obtain a fitted PFe /f − f 0.5 curve, as shown in Fig. 9. According to the experimental curve fitting, the coefficients a, b, and c in Eq. 3 are obtained. The hysteresis loss Ph , eddy current loss Pe , and anomalous loss Pa can be calculated based on the coefficients a, b, c in fitting Eq. 3, as well as the loading frequency f . The specific calculation formula is as follows: Ph = a × f ;

(4)

Pe = c × f 2 ;

(5)

Pa = b × f 1.5 ;

(6)

The hysteresis loss Ph , eddy current loss Pe , and anomalous loss Pa can be calculated under different frequency conditions of 1.0 and 1.5 T for two processing methods: punching and laser cutting. The results are shown in Fig. 10 [19]. In Fig. 10a, it can be seen that the total iron loss is mainly hysteresis loss under the conditions of magnetic induction intensity of 1.0 T and frequency of 50–400 Hz.

1128

S. Wu et al.

Fig. 9 Iron loss separation curve under different magnetic induction intensity and different frequencies: a 1.0 T; b 1.5 T

Iron loss /W/kg

7

Punching-1.0T Ph Pe Pa Laser cutting-1.0T Ph Pe Pa

6 5 4 3 2

(b) 25 Iron loss /W/kg

(a)

Punching-1.5T Ph Pe Pa Laser cutting-1.5T Ph Pe Pa

20 15 10 5

1 0

0 0

50 100 150 200 250 300 350 400 450

Frequency/Hz

0

50 100 150 200 250 300 350 400 450

Frequency/Hz

Fig. 10 Iron loss separation under different magnetic induction intensity: a 1.0 T; b 1.5 T

The total iron loss of laser cutting sample is higher than that of punching. This is mainly due to the high hysteresis loss. The magnitude of hysteresis loss depends on the area of the hysteresis loop, which depends on the magnitude of the coercive force, which is related to the movement of the magnetic domain wall. The oxide layer on the cutting surface hinders the movement of magnetic domain walls, leading to an increase in hysteresis loss. In addition, as the loading frequency increases, hysteresis loss, eddy current loss, and anomalous loss all continue to increase. When the loading frequency reaches 400 Hz, hysteresis loss is equivalent to eddy current loss. From Fig. 10b, it can be seen that when the magnetic induction intensity increases to 1.5 T, the hysteresis loss of the two processing methods is not significantly different. This is mainly because the magnetic induction intensity of the sample needs to reach 1.5 T, and the external magnetic field intensity is relatively high. Under high magnetic field intensity conditions, the magnetization process of NOES is mainly characterized by the rotation of magnetic domain walls, and the resistance of the rotation process of magnetic domain walls comes from magnetic crystal anisotropy, which needs

Effect of Processing Methods on the Magnetic Properties …

1129

to be overcome. The total iron loss of laser cutting sample is higher than that of punching, mainly due to the high abnormal loss, and the deviation value increases with the increase of loading frequency. In addition, when the loading frequency of the sample processed by punching is below 270 Hz, the core loss is mainly magnetic hysteresis loss. When the loading frequency is higher than 270 Hz, the eddy current loss sharply increases and becomes the main component of iron loss. The loading frequency transition point of the laser cutting sample is 290 Hz.

Conclusions 1. By comparing 20 sets of laser cutting and punching samples produced in industrial production, it was found that under the conditions of magnetic induction intensity of 1.0 T and loading frequency of 400 Hz, the iron loss of laser cutting samples was higher than that of punching, and the average iron loss increased by 1.207 W/kg. Through EBSD stress analysis, there is no obvious stress concentration layer at the cutting section during laser cutting, but a layer of 1 µm is formed on the surface of the cutting section. The silicon aluminum oxide layer is the direct cause of high iron loss in laser cutting samples. 2. Through iron loss separation calculation, under the condition of magnetic induction intensity of 1.0 T and frequency of 50–400 Hz, the total iron loss of laser cutting samples is higher than that of punching. This is mainly due to the high hysteresis loss. The surface oxide layer formed by laser cutting increases the resistance of magnetic domain wall movement, leading to the coercive force and hysteresis loss increased. 3. Through iron loss separation calculation, when the magnetic induction intensity increases to 1.5 T and the frequency is 50–400 Hz, the total iron loss of laser cutting sample is higher than that of punching, mainly due to the high abnormal loss, and the deviation value increases with the increase of loading frequency.

References 1. Shi W-M, Liu J, Cao H-D et al (2014) Recent advances in application of silicon steel for electric vehicle motor. J Wuhan Univ Sci Technol 37(6):432–437 2. Du L-Y, Xue H, Li R-F et al (2015) Influence of the cutting process on the fatigue properties of non-oriented electrical steels. J Wuhan Eng Inst 27(4):29–31 3. Zhang H-L, Xiang Q, Xiong L-B et al (2020) Effect of processing methods on mechanical properties of non-oriented high grade electrical steel. Electr Steel 3:34–37 4. Tietz M, Biele P, Jansen A et al (2012) Application-specific development of non-oriented electrical steel for EV traction drives. In: 2012 2nd international on electric drives production conference (EDPC). IEEE

1130

S. Wu et al.

5. Chen X, Xie S, Wang B (2015) Development of non-oriented silicon steels for traction motor use in electric vehicles. In: The 10th China iron and steel annual conference and the 6th Baosteel academic annual conference 6. Dong H, Zhao Y, Yu XJ et al (2009) Effects of Sn addition on core loss and texture of nonoriented electrical steels. J Iron Steel Res Int 16(6):86–89 7. Zhang YX, Lan MF, Wang Y et al (2019) Microstructure and texture evolution of thin-gauge non-oriented silicon steel with high permeability produced by twin-roll strip casting. Mater Charact 150:118–127 8. Schulte M, Steentjes S, Leuning N et al (2019) Effect of manganese in high silicon alloyed non-oriented electrical steel sheets. J Magn Magn Mater 477:372–381 9. Li J, Yue T-J, Yu J et al (2008) Effect of chemical composition on core loss of low grade gold rolled non-oriented Electrical Steel. Spec Steel 29(2):4–6 10. Gong Y (2017) Study of effect of stress on magneto strictive properties of electrical steel sheet. Shenyang University of Technology, Shen Yang 11. Li J-D, Gu M-Q (1994) Investigation of lowering the core loss of grain-oriented silicon steel by means of laser processing. Iron Steel 029(8):44–47 12. Winter K, Liao ZR, Ramanathan R et al (2021) How non-conventional machining affects the surface integrity and magnetic properties of non-oriented electrical steel. Mater Des 210:1–19 13. Cristiana SN, AlmirSilva N, Vinícius A et al (2021) Influence of the cutting process, heat treatment, and maximum magnetic induction on the magnetic properties of highly oriented electrical steels. J Magn Magn Mater 537:1–7 14. Shi W-M (2016) The influence of stress and working environment on the properties of electrical steel for EV motor. Wuhan University of Science and Technology, Wu Han 15. Ni F-C (2008) Application of magnetic measurement sensor in precision machining and harsh working environment. Aviat Precis Manuf Technol 44(3):32–34 16. Lode V, Sigrid J, Francois H et al (2019) Impact of cut edges on magnetization curves an iron losses in e-machines for automotive traction. In: The 25th world battery, hybrid and fuel cell electric vehicle symposium and exhibition. IEEE, Shenzhen, pp 5–9 17. Naumoski H, Riedmüller B, Minkowb A et al (2015) Investigation of the influence of different cutting procedures on the global and local magnetic properties of non-oriented electrical steel. J Magn Magn Mater 392:126–133 18. Bertotti G (1998) General properties of power losses in soft ferromagnetic material. IEEE Trans Magn 24(1):621–630 19. Dan MI, Mircea P, Stephen JD et al (2006) On the variation with flux and frequency of the core loss coefficients in electrical machines. IEEE Ind Appl 42(3):658–667

Effect of Melt Superheat on Interfacial Heat Transfer Behavior of Sub-Rapid Solidification Process Lulu Song, Wanlin Wang, Xueying Lyu, Yunli Zhang, and Huihui Wang

Abstract As a new technology, the ultra-thin strip casting technology has inherent advantages in the production of non-oriented silicon steel, with excellent initial texture and a short process. The effects of different melt superheat (15 °C, 45 °C, 65 °C) on the interfacial heat transfer behavior and wetting phenomena of 2.5 wt.% Si non-oriented Electrical Steel produced by the ultra-thin strip were studied. The empirical findings indicate a swift surge in interfacial heat flow upon initial interaction between molten steel and the copper matrix. The cooling contraction of the molten material prompts the formation of an air gap between the solidified billet shell and the copper substrate, resulting in a peak of interfacial heat flow followed by rapid attenuation. Elevating the superheat levels extends the solidification period, affording the molten material ample time to wet the substrate. This, in turn, fosters interfacial heat transfer and augments the interfacial heat flow. Keywords Electrical steel · Melt superheat · Heat transfer · Wetting phenomena

Introduction The ultra-thin strip casting technology, a novel and innovative approach to steel production characterized by its abbreviated processing cycle and environmentally considerate attributes, has garnered significant attention within the contemporary steel industry research landscape [1]. This method entails the direct solidification of steel upon swiftly moving copper crystallization matrices, resulting in the formation of slender cast strips measuring 1–5 mm in thickness [2]. Subsequent to casting, these strips undergo online rolling or are subjected to further processing as per requirements, culminating in the attainment of finalized or semi-finished thin L. Song · W. Wang (B) · X. Lyu · Y. Zhang · H. Wang School of Metallurgy and Environment, Central South University, Changsha 410083, China e-mail: [email protected] National Center for International Cooperation of Clean Metallurgy, Changsha 410083, China © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_98

1131

1132

L. Song et al.

strip steel products. In comparison with conventional methodologies, this technique offers notable merits encompassing streamlined production procedures, diminished energy requisites, and economically frugal operations. As an emerging focal point, thin strip casting stands poised as a transformative advancement in the realm of steel fabrication, aligning with the imperatives of resource efficiency and ecological consciousness [3]. The process of melt solidification at the surface of the metal substrate can be delineated into two distinct stages. The initial stage involves the direct interaction between the liquid metal and the substrate. This process is intricate, influenced by a multitude of interrelated factors. However, the fundamental aspect underpinning this stage is the wetting behavior exhibited between the liquid and the substrate. The intricate interplay of various process parameters ultimately manifests through their influence on the wettability, consequently affecting heat transfer dynamics. The subsequent interaction between the molten metal and the substrate brings about a temperature reduction due to the dissipation of heat, leading to solidification. Following this solidification, the formation of a solidified shell at the interface is primarily governed by the dimensions of the intervening air gap. One of the primary determinants impacting the heat flow from the melt to the interface encompasses factors such as the extent of superheating, compositional variations, and other pertinent considerations. Wang and Matthys [4] observed that augmenting the melt superheat generally amplifies the heat transfer coefficient during liquid–solid contact across most scenarios. Akin outcomes were discerned in the investigations conducted by Loulou et al. [5], Netto et al. [6], and Nolli et al. [7]. This phenomenon finds a comprehensive rationale in the context that heightened superheat corresponds to a reduction in the surface tension of the melt. This decrease, in turn, enhances the wettability of the substrate during the interaction phase, thereby culminating in escalated interfacial heat flow and a concurrent reduction in interfacial thermal resistance. Nevertheless, the findings of Strezov and Herbertson [8] present a counterintuitive trend, wherein the interfacial heat flow diminishes as superheat levels rise. This divergence is attributed by the authors to a concurrent reduction in the nucleation rate. To reconcile this intriguing paradox, the present study investigates the influence of superheat on interfacial heat transfer and the wettability of high-temperature liquid steel (2.5 wt.% Si Electrical Steel) within the context of thin strip continuous casting.

Experimental The molten droplet solidification apparatus has been specifically designed to replicate the sub-rapid solidification process encountered in strip casting. The schematic representation of the droplet solidification tester is presented in Fig. 1, encompassing integral components including the heating system, cooling system, and atmosphere control system. Initially, 3.5 wt.% Si steel plates were fashioned into cylinders with dimensions measuring 6 mm in diameter and 15 mm in length. Subsequently, meticulous polishing was conducted with 400-grit metallographic sandpaper to eliminate the

Effect of Melt Superheat on Interfacial Heat Transfer Behavior …

1133

Fig. 1 Schematic representation of strip casting simulator [9]

oxide layer. The prepared sample was then carefully positioned within a quartz tube, subsequently subjected to induction heating to induce melting. Controlled manipulation of melt superheat values was enacted, specifically setting them at 15, 45, and 65 °C. Upon attaining the designated temperature, the liquefied sample was expeditiously deposited onto a copper mold to ensure rapid solidification. Temperature fluctuations during the solidification course were captured in real-time through Omega thermocouples strategically embedded at varying depths within the copper substrate. Additionally, the data acquisition system by National Instruments (NI) facilitated concurrent recording, while subsequent employment of the heat transfer inverse problem algorithm permitted computation of heat flow density at a later experimental phase. The entire progression of solidification was adeptly captured by a high-speed industrial video camera, affording a comprehensive real-time depiction.

Results and Discussion Interfacial Heat Transfer Behavior The provided figure illustrates heat flow density alongside heat conductivity-time curves at varying superheat levels. Analyzing Fig. 2a, it is evident that the heat flow exhibits a discernible pattern characterized by rapid escalation to its zenith, succeeded by a swift descent, culminating in a phase of stability. The heat transfer process transpiring at the juncture between the liquid steel and the copper substrate unfolds in two distinct stages. The initial stage involves the initial contact between the liquid metal and the copper matrix, where interfacial heat flow experiences an abrupt surge

1134

L. Song et al.

Fig. 2 Heat flux and maximum heat flux: a heat flux versus time. b Maximum heat flux versus superheat

owing to the favorable contact conditions. Subsequently, the second stage manifests as a solid contact situation between the solidified billet shell and the copper matrix. Given that the solidification of steel entails a contraction due to cooling, an interstice emerges between the solidified billet shell and the copper matrix. This interstice engenders a pronounced surge in interfacial thermal resistance, thereby causing the interfacial heat flow to peak at 0.6S before commencing a gradual decline. Analysis of the thermal conductivity-time curves reveals a progressive augmentation in thermal conductivity over time. However, the slopes of these curves exhibit conspicuous discrepancies attributable to differing superheat degrees and distinct heat transfer conditions. Experimental observations of heat transfer across varying levels of superheat reveal substantial disparities. For example, in specimen 1, characterized by a superheat level of 15 °C, the peak heat flow density measures 2.74 MW/m2 . Similarly, for specimen 2, exhibiting a superheat level of 45 °C, the peak heat flow density records at 5.28 MW/m2 . Furthermore, specimen 3, which experiences a superheat level of 65 °C, demonstrates a peak heat flow density of 6.6 MW/m2 . This data clearly illustrates an increase in peak heat flow density with rising superheat levels. The interfacial heat flow demonstrates a positive correlation with the escalation of the interfacial temperature difference. Within this experimental framework, the copper mold is maintained at a constant temperature of 26 °C via precise regulation of cooling water temperature. The manipulation of the interfacial temperature difference primarily hinges upon the modulation of melt superheat, an aspect contingent upon the casting procedure. Notably, the augmentation of the interfacial temperature difference exhibits constrained growth. Conversely, the heat flow density experiences an exponential surge corresponding to the degree of superheat. Consequently, it becomes evident that the amplification of the interfacial temperature difference does not singularly underpin the observed increase in interfacial heat flow. The initial phase of steel solidification onto the substrate encompasses a wetting process entailing interactions between the liquid and solid phases. This wetting phenomenon also

Effect of Melt Superheat on Interfacial Heat Transfer Behavior …

1135

exerts discernible influence upon the interfacial heat transfer dynamics. To unravel the intricate interplay between interfacial heat flow and the predominant influencing variables, a comprehensive analysis of the melt’s wetting process on the copper substrate proves imperative.

Wetting Phenomena The most foundational determinant within the context of direct interaction between liquid metal and a substrate resides in the wetting phenomenon at the liquid-substrate interface. Distinct process parameters, in their entirety, exert their influence on heat transfer dynamics by modulating the wettability characteristics. As shown in Fig. 3, wetting of a liquid upon a solid surface finds expression through the concept of the wetting angle. When liquid droplets are deposited on a solid surface, under the influence of gravity, and reach an equilibrium state at which gas, liquid, and solid phases remain immiscible, three distinguishable interfaces form. The angle θ, termed the contact angle, is defined at the juncture of the gas–liquid crescent tangent and the solid surface. This contact angle serves as a quantifier of the affinity between the substances involved and the ensuing wetting attributes of the liquid. Notably, a diminishing wetting angle corresponds to an enhanced affinity and contact between the liquid and the solid surface. A critical demarcation arises at θ = 90°, signifying the threshold between wetting and non-wetting behaviors. Specifically, for θ < 90°, wetting is observed, while θ > 90° signifies non-wetting characteristics. Figure 4 presents the contact angles and areas of solidified droplet samples across varying superheat levels. The visual representation clearly illustrates the diminishing trend in contact angles between molten droplet samples and the copper substrate, reducing from 111.2° to 102.7° and further to 94.6° as superheat elevates from 15 to 45 °C and subsequently to 65 °C. In the context of thin strip continuous casting, the temporal interval between the high-temperature melt and the copper substrate remains exceedingly brief. Within a span of 20–30 ms following the initial contact between the steel and substrate, the solidified shell takes shape. During this transient period, the wetting angle does not achieve thermodynamic equilibrium due to the relatively low substrate surface temperature. As a result, mutual dissolution or other interactions between the melt

Fig. 3 Schematic of wetting angle

1136

L. Song et al.

Fig. 4 Wetting angles of molten droplets and the bottoms of solidified samples

and substrate surface are notably restricted, resulting in contact angles exceeding 90°. The distinctive annular shape characterizing the solidified droplet’s base can be ascribed to a progression wherein the central section of the high-temperature droplet promptly establishes contact with the substrate surface and undergoes rapid solidification during the droplet’s course. Subsequently, solidification extends outward, gradually culminating in the annular configuration observed at the base. Ultimately, this process yields a nearly hemispherical solidified droplet. Concurrently, a rise in superheat levels from 15 to 45 °C and 65 °C prompts a reduction in the basal area: from 1.31 cm2 to 1.42 cm2 and then to 1.58 cm2 . Figure 5 delineates the patterns of alteration in contact angle and basal area across various experimental trials. This visualization indicates a gradual reduction in contact angle with escalating superheat, alongside an augmentation in the droplet’s basal area. The combined effect of decreased contact angle and increased contact area signifies an amelioration in the wetting characteristics between liquid steel and the substrate, correlating with heightened superheat degrees. As the degree of superheat rises, the surface tension of the liquid experiences a decline, leading to enhanced fluidity. Consequently, the contact angle exhibits a decreasing trajectory concomitant with elevated superheat levels, indicative of improving interfacial contact conditions. Moreover, the escalation in superheat degree extends the duration required for the molten material to solidify. This prolonged period grants the melt ample time to effectively wet the substrate, thereby bolstering interfacial heat transfer mechanisms and resulting in an augmentation of interfacial heat flow.

Effect of Melt Superheat on Interfacial Heat Transfer Behavior …

1137

Fig.5 Change rule of contact angle and bottom area of steel liquid and matrix under different superheat degree

Conclusions This paper investigates the impact of superheat on interfacial heat flow and hightemperature liquid steel wettability in the context of ultra-thin strip casting. The study employs molten drop solidification equipment utilizing 2.5 wt.% Si Steel as the subject of analysis. The findings can be summarized as follows: (1) During the initial interaction between molten steel and the copper substrate, the interfacial heat flow experiences a rapid increase. Concurrently, as the molten material cools and contracts, an air gap emerges between the solidified billet shell and the copper substrate. This phenomenon leads to an augmentation in interfacial thermal resistance, resulting in a peak of interfacial heat flow, followed by a swift decrease and eventual stabilization. (2) With an elevation in superheat levels from 15 to 65 °C, the peak heat flow amplifies from 2.74 to 3.61 MW/m2 . This signifies a direct relationship between interfacial heat flow and superheat degree an escalation in superheat degree corresponds to an increase in interfacial heat flow. (3) Furthermore, heightened superheat degrees contribute to a reduction in the liquid’s surface tension and an improvement in fluidity. The contact angle diminishes from 111.2° to 94.6° as superheat levels rise from 15 to 65 °C, indicating enhanced wettability.

1138

L. Song et al.

References 1. Wechsler R (2003) The status of twin-roll casting technology. Scand J Metall 32(1):58–63. https://doi.org/10.1034/j.1600-0692.2003.00636.x 2. Maleki A, Taherizadeh A, Hosseini N (2017) Twin roll casting of steels: an overview. ISIJ Int 57(1):1–14. https://doi.org/10.2355/isijinternational.ISIJINT-2016-502 3. Ge S, Isac M, Guthrie RIL (2013) Progress in strip casting technologies for steel; technical developments. ISIJ Int 53(5):729–742. https://doi.org/10.2355/isijinternational.53.729 4. Wang GX, Matthys EF (2002) Experimental determination of the interfacial heat transfer during cooling and solidification of molten metal droplets impacting on a metallic substrate: effect of roughness and superheat. Int J Heat Mass Tran 45(25):4967–4981. https://doi.org/10.1016/ S0017-9310(02)00199-0 5. Loulou T, Artyukhin EA, Bardon JP (1999) Estimation of thermal contact resistance during the first stages of metal solidification process: I-experiment principle and modelisation. Int J Heat Mass Tran 42(12):2119–2127. https://doi.org/10.1016/S0017-9310(98)00333-0 6. Netto PGQ, Tavares RP, Isac M, Guthrie RIL (2001) A technique for the evaluation of instantaneous heat fluxes for the horizontal strip casting of aluminum alloys. ISIJ Int 41(11):1340–1349. https://doi.org/10.2355/isijinternational.41.1340 7. Nolli P, Cramb AW, Choo DK (2004) The effect of surface oxide films on heat transfer behavior in the strip casting process. Iron Steel Technol 1(12):117 8. Strezov L, Herbertson J (1998) Experimental studies of interfacial heat transfer and initial solidification pertinent to strip casting. ISIJ Int 38(9):959–966. https://doi.org/10.2355/isijinter national.38.959 9. Lu C, Wang WL, Zeng J, Liu XY, Li HL (2023) Effect of chromium coating roughness and thickness on interfacial heat transfer behaviour of sub-rapid solidification process. Philos Mag 103(2):171–185. https://doi.org/10.1080/14786435.2022.2141904

Influence of Hot Rolling Reduction Rate on the Microstructure and Texture of a Strip Cast Fe-2.5 wt.% Si Non-oriented Electrical Steel Huihui Wang, Wanlin Wang, Peisheng Lyu, Chenyang Zhu, Xueying Lyu, Lulu Song, and Yunli Zhang

Abstract A 2.5 wt.% Si electrical steel was prepared based on the ultra-thin strip casting process, and its magnetic properties are closely related to the material’s microstructure and texture. Therefore, it is the focus of this paper to control the evolution of grain size and texture by modulating the thermal processing parameters, so as to improve the magnetic properties. In this paper, we mainly study the effect of the hot rolling reduction rate (30–70%) on the microstructure and texture. The results show that with the increase in the reduction rate, the grain is gradually refined. The heavy reduction rate (70%) increased the area fraction of Goss ({110}) and γ-fiber texture grains and decreased the grain size, which was mainly a result of recrystallization. At lower reduction rates of 30%, the λ-fiber texture is still inherited and deformation bands dominate within the grains. Keywords Hot rolling · Ultra-thin strip casting · Texture · Reduction rate

Introduction The ultra-thin strip casting and rolling process has unique advantages in the production of non-oriented electrical steel, which has received attention from the world steel industry [1–3]. Hot rolling and normalization are the front processes with great influence in the production of electrical steel, which determine the subsequent texture characteristics and finished product properties of electrical steel [4–9]. Therefore, it is necessary to conduct research on the microstructure and texture of hot rolling and the normalization of ultra-thin strip casting, which is of great significance for the application of ultra-thin strip casting and hot rolling process to the production of electrical steel. The normalization process has been discussed in previous work, so this study will focus on the effect of the hot rolling process. H. Wang · W. Wang (B) · P. Lyu · C. Zhu · X. Lyu · L. Song · Y. Zhang School of Metallurgy and Environment, Central South University, Changsha 410083, China e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_99

1139

1140

H. Wang et al.

In recent years, researchers have conducted a large number of experiments in the laboratory on the twin-roll strip casting and rolling process. The existing research mainly based on the cold rolling process. Jiao et al. [10] study the preparation of Fe-1.3 wt.% Si non-oriented electrical steel from twin-roll strip casting. The casting strips with the thickness of 1.7 mm were prepared, and after cold rolled for 2–5 times with the reduction rates were 29%, 50%, 67%, and 79%, respectively, followed by annealing of 79% cold rolled specimens. The properties were significantly improved compared to the conventional process, but the large under-pressure of cold rolling resulted in γ-fiber texture generation within the samples, which would affect the product properties. Sha et al. [11] investigated the texture evolution of Fe-2.8 wt.% Si non-oriented electrical steel directly cold-rolled from a twin-roll strip casting to prepare 2.0 mm thick cast strip with cold rolling reduction rates of 82.5%, and then subjected to annealing treatment. Compared with conventional processes, the initial stage of the cast strip is easier to form cube deformation bands and cube shear bands. There are significant difficulties and challenges in controlling the re-nucleation of Cube shear bands and γ-fiber texture. Li et al. [12] prepared the twin-roll strip casting preparation of Fe-6.5 wt.% Si, and the cast strip of 2.5 mm thickness was subjected to the hot-rolling-warm-rolling-annealing treatment. The hot rolling reduction rate was 40%, followed by a warm-rolling under pressure rate of 66.7% to 0.5 mm at 250 °C, and the introduction of large under pressure by the warm-rolling increased the α-fiber structure while still part of the formation of γ texture structure and increased energy consumption. In summary, the current twin-roll strip casting and rolling process is still in the research and development stage. In this study, the ultra-thin strip continuous casting process is used for casting strips, followed by the study of the hot rolling process, mainly to analyze the effect of hot rolling conditions on microstructure and texture, with the aim of determining the optimal hot rolling process, and create a good environment for the inheritance and formation of subsequent beneficial texture enhancement.

Experimental The material investigated in this study was an Fe-2.5 wt.% Si non-oriented electrical steel containing (wt.%): 0.0022 C, 2.5 Si, 0.267 Mn, 0.006 Al. The detailed processing steps are illustrated in Fig. 1. The superheat of the casting strip is 60–70 °C, and the thickness of the cast strip experimental steel was 1.8–2 mm. The cast strips were hot-rolled at 750 °C, 850 °C, and 950 °C with depressions of 30%, 50%, and 70%, respectively. The microstructure, precipitation, and texture were characterized by optical microscopy (OM) and electron backscatter diffraction (EBSD). OM samples were prepared using conventional metallographic procedures. The microstructure of the material was investigated using EBSD analysis. The longitudinal sections determined by rolling direction (RD) and normal direction (ND) were observed by optical microscopy and analyzed by EBSD.

Influence of Hot Rolling Reduction Rate on the Microstructure …

1141

Fig. 1 Schematic diagram showing the processing steps of hot-rolling used to produce the Fe-2.5 wt.% Si non-oriented electrical steel

Results and Discussion Microstructure and Texture of the As-Cast Strip The organization of the cast strip of non-oriented electrical steel under sub-rapid solidification is well-developed columnar crystals and {100} oriented grains are predominant. Figure 2 shows the microstructure of the casting strip of non-oriented electrical steel with ultra-thin strip. The microstructure (Fig. 2a) is mainly composed of columnar structure across the thickness, and the columnar grains are similar to the typical casting structure formed from directional cooling of the melt [12]. Figure 2b shows the EBSD micrograph of the casting strip, where the {001} of stripes can be clearly observed. In addition, it can be observed that some {101} oriented grains in the cast strip. As a result, the overall texture is mainly λ-fiber texture ({001}) (Fig. 2c), with texture is quite weak of {116}.

Evolution of Microstructure and Texture During Hot Rolling The microstructure of the steel after hot rolling is shown in Fig. 3. The cast strip was subjected to different reduction rates and temperatures of hot rolling; it can be found that the reduction of 30% with the hot rolling temperature of 750 °C, the slip band is dominated, with the rise of the hot final rolling temperature, the slip band gradually decreases, the deformation of the band increases. Under the reduction rate of 50%, the lower rolling temperature deformation difficulties and some grains are broken (Fig. 3d). However, grain deformation is significant at high hot rolling temperatures,

1142

H. Wang et al.

Fig. 2 Microstructures of casting strip of ultra-thin strip non-oriented electrical steel. a Optical microscopy images, b inverse pole figure (IPF) map, and c texture (ϕ2 = 45° ODF section, Bunge notation)

and a small amount of slip bands can still be observed at low temperatures. At the pressure rate of 70%, the larger pressure makes the grain internal storage energy is high, the dislocation accumulation is serious, with more nucleation points. As the temperature increase, the grains recrystallization and growth (Fig. 3i). Through the analysis of the IPF and ODF map in Fig. 4, it can be found that the grains gradually refined with the increase of the reduction rate, and there are obvious recrystallized grains at reduction rate of 70%, which leads to the diffuse texture structure and lower strength. The hot rolling temperature of 750 °C and reduction rate of 30%, deformation bands texture {112} can be observed, and there are more slip bands and deformation bands are observed in the IPF diagram. At 850 °C with reduction rate of 30%, the grains are deformed and the orientation is rotated, the mainly dominated by rotated Cube, and at the same time, with nearly α*-fiber texture of {112} is generated. At 950 °C with 30%, the deformation is obvious, and the orientation is mainly dominated by λ-fiber texture, but with lower strength. When the reduction rate increases to 50% at 750 °C, the orientation is dominated by the deformation band texture {114}, which will provide the basis for the subsequent {001} nucleation with some λ-fiber texture, and as the

Fig. 3 Microstructures of hot rolled sheets under different temperature and reduction rate of ultrathin strip non-oriented electrical steel

Influence of Hot Rolling Reduction Rate on the Microstructure …

1143

temperature continues to rise, the texture is diffuse and there is γ-fiber texture. When the reduction rate is 70%, recrystallization is also less. At 950 °C with rate of 30%, the grain orientation are λ-fiber texture and {113} orientation is dominated. With reduction rate of 70%, the recrystallization and growth are obvious occurs, and the texture structure of the diffuse and weak strength.

Fig. 4 Cross-section (RD-ND) microstructure and microtexture of the hot-rolled plates 2.5 wt.% Si electrical steel: IPF map and ODF diagram of ϕ2 = 45° section of hot rolled strip normalized at different temperature and reduction rates

1144

H. Wang et al.

In summary, it can be seen that the hot rolling of temperature and reduction rate have a significant effect on the evolution of grains and fiber texture structure. When hot-rolled at 750 °C with 50%, there is deformation band texture formation, which is very beneficial for subsequent recrystallization nucleation of {001} textures, and there is λ-fiber texture inheritance.

Conclusions An Fe-2.5 wt.% Si non-oriented electrical steel was strip cast and hot rolled with different amounts of thickness reduction (30–70%) to investigate the effect of temperature and hot rolling reduction rate on the microstructure and texture of the steel sheets. (1) The initial cast strip is mainly composed of columnar crystals, λ-fiber texture develops, after hot rolling, some λ-fiber texture can be inherited. (2) As the hot rolling temperature increases, deformation becomes easier, and the texture gradually disperses. And the hot rolling depression rate directly affects the degree of tissue recrystallization, and the larger the depression rate, more severe the recrystallization. (3) Through experimental research and analysis, the optimal hot rolling process for preparing non-oriented electrical steel with ultra-thin strips is to conduct a 50% reduction at 750 °C.

References 1. Zhang YX, Lan MF, Wang Y, Fang F, Lu X, Yuan G, Misra RDK, Wang G-D (2019) Microstructure and texture evolution of thin-gauge non-oriented silicon steel with high permeability produced by twin-roll strip casting. Mater Charact 150:118–127 2. Wang Y, Zhang YX, Lu X, Fang F, Xu YB, Cao GM, Li CG, Misra RDK, Wang GD (2016) A novel ultra-low carbon grain oriented silicon steel produced by twin-roll strip casting. J Magn Magn Mater 419:225–232 3. Liu HT, Wang YP, An LZ, Wang ZJ, Hou DY, Chen JM, Wang GD (2016) Effects of hot rolled microstructure after twin-roll casting on microstructure, texture and magnetic properties of low silicon non-oriented electrical steel. J Magn Magn Mater 420:192–203 4. Xi SP, Gao XL, Liu W, Lu YL, Fu GQ, Tao HC, Zang YC (2021) Hot deformation behavior and processing map of low-alloy offshore steel. J Iron Steel Res Int 29(3):474–483 5. Takajo S, Merriman CC, Vogel SC, Field DP (2019) In-situ EBSD study on the cube texture evolution in 3 wt.% Si steel complemented by ex-situ EBSD experiment—from nucleation to grain growth. Acta Mater 166:100–112 6. Song HY, Liu HT, Lu HH, Li HZ, Liu WQ, Zhang XM, Wang GD (2014) Effect of hot rolling reduction on microstructure, texture and ductility of strip-cast grain-oriented silicon steel with different solidification structures. Mater Sci Eng: A 605:260–269 7. Akta GJRS, Sellars CM (2005) Hot deformation and recrystallization of 3% silicon steel Part 1: microstructure, flow stress and recrystallization characteristics. ISIJ Int 45(11):1666–1675

Influence of Hot Rolling Reduction Rate on the Microstructure …

1145

8. Rodríguez-Calvillo P, Houbaert Y, Petrov R, Kestens L, Colás R (2012) High temperature deformation of silicon steel. Mater Chem Phys 136(2–3):710–719 9. Pinoy L, Eloot K, Standaert C, Jacobs S, Dilewijns J (1998) Influence of composition and hot rolling parameters on the magnetic and mechanical properties of fully processed non-oriented low-Si electrical steels. J Phys IV 08:Pr2-487–Pr2-490 10. Jiao H, Xu Y, Zhao L, Misra RDK, Tang Y, Liu D, Hu Y, Zhao M, Shen M (2020) Texture evolution in twin-roll strip cast non-oriented electrical steel with strong Cube and Goss texture. Acta Mater 199:311–325 11. Sha YH, Sun C, Zhang F, Patel D, Chen X, Kalidindi SR, Zuo L (2014) Strong cube recrystallization texture in silicon steel by twin-roll casting process. Acta Mater 76:106–117 12. Xu H, Xu Y, He Y, Jiao H, Yue S, Li J (2020) Influence of hot rolling reduction rate on the microstructure, texture and magnetic properties of a strip-cast Fe-6.5 wt.% Si grain-oriented electrical steel. J Magn Magn Mater 494

Interfacial Heat Transfer Behavior Between Liquid Steel and Mold of Non-oriented Electrical Steel Containing Manganese in Thin Strip Continuous Casting Xueying Lyu, Wanlin Wang, Yunli Zhang, Lulu Song, and Huihui Wang

Abstract Thin strip continuous casting technology has great advantages in the field of non-oriented electrical steel due to its near-final forming and sub-rapid solidification characteristics. However, it is prone to heat transfer reduction and strip breaking in the production process. The deposition behavior of oxide film between liquid steel and copper cooling crystallizer of non-oriented electrical steel containing manganese and its effect on interfacial heat transfer were investigated by using the experimental equipment of melt drop solidification technology. The results show that with the deposition of oxide film, its surface morphology goes through three stages: agglomeration, cluster, and three-dimensional network. The interfacial heat transfer between molten steel and crystallizer decreases first, then increases, reaches a peak, and then decreases. The main components of the naturally deposited film are oxides of Mn, Si, and Fe. With the continuous progress of the experiment, the components of the oxide film are basically stable. Keywords Sub-rapid solidification · Non-oriented electrical steel · Interfacial heat transfer

Introduction Fuel vehicles consume a large amount of fossil fuels, which is not only affected by the fluctuation of energy supply prices, but also causes air pollution and leads to the development crisis of the automobile industry. New energy vehicles can ease the dependence of cars on fossil fuels, reduce greenhouse gas emissions, and reduce environmental pollution [1], so they have received the attention of governments X. Lyu · W. Wang (B) · Y. Zhang · L. Song · H. Wang School of Metallurgy and Environment, Central South University, Changsha 410083, China e-mail: [email protected] National Center for International Cooperation of Clean Metallurgy, Changsha 410083, China © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_100

1146

Interfacial Heat Transfer Behavior Between Liquid Steel and Mold …

1147

around the world and have broad development prospects [2, 3]. The drive motor is one of the core components of new energy vehicles, and the premise of achieving high-quality development of new energy vehicles is to improve the energy conversion efficiency of the drive motor. Iron core is the key component of driving motor to realize energy conversion. Magnetic materials for the preparation of iron cores include conventional non-oriented silicon steel and other high-end materials such as iron- or cobalt-based amorphous alloys, super cores, Ni–Fe alloys, biphase materials, and nanocrystalline alloys [4]. Considering the electromagnetic properties of the material, industrial manufacturability, material cost and processing and manufacturing cost, the core material with the highest cost performance and the most common commercial application is still non-oriented silicon steel. Thin strip continuous casting process is to inject the liquid steel into the mold formed by the rotating casting roll and the side seal plate, and then in a short time, the sub-rapid solidification shape, the thickness of 1.0–3.0 mm, the solidification speed can reach 102 –104 K/s [5, 6]. Because of its advantages in forming thickness and cooling rate, the process has two characteristics of near-final process and subrapid solidification, as well as the advantages of short production line flow, energy saving and environmental protection, and low cost [7, 8]. The finished product of non-oriented silicon steel requires coarse structure and developed {100} texture, while the grain size and shape of the solidification structure of ferrite are affected by the superheat of molten steel, pouring temperature and casting and rolling speed, etc. Large grain size and strong {100} texture can be obtained simultaneously in the casting strip control. There is no doubt that the thin strip continuous casting process has great technical potential in the preparation of non-oriented silicon steel. However, in the process of industrial trial production, it was found that when thin strip continuous casting technology was used to prepare non-oriented silicon steel, heat transfer would be reduced in some parts of the casting strip, and the liquid steel could not be solidified quickly, resulting in belt breaking accidents, causing major economic losses and great safety risks. The key means to solve this problem is to improve the interfacial heat transfer efficiency between molten steel and cooling crystallizer. Previous studies [9–11] have pointed out that silicon and manganese oxides will be left after the solidification of molten steel on the cooled substrate, and the formation of oxide film will greatly affect the interface heat flux between molten steel and the substrate. However, the different components of the oxide film formed by the different composition of steel grades are different, the deposition rate is different, and the effect on the interface heat transfer efficiency is also very different. Mn element can improve the strength, hardness, and hardenability of steel and is a commonly used alloying element. However, the effect of naturally deposited oxide film on interfacial heat transfer of non-oriented electrical steel containing Mn has not been reported, which has considerable research value. In this paper, the experimental equipment of melt drop solidification technology was used to simulate the observation of thin strip continuous casting of non-oriented electrical steel containing manganese, and the oxidation film deposition behavior and interfacial heat transfer between liquid steel and copper cooling crystallizer were investigated. The effects of different experimental times on the surface morphology

1148

X. Lyu et al.

and deposition thickness of the oxide film, as well as the effects of different layers of oxide film on the peak heat flow and thermal conductivity at the interface, were compared and analyzed.

Experimental Procedures In this study, experimental equipment for droplet solidification technology (Fig. 1) is used to observe the solidification phenomenon of metal droplet impacting on watercooled copper substrate in situ, which can accurately reflect the sub-rapid solidification process of thin strip continuous casting process, and has the advantages of small scale, less consumption, and high accuracy [12]. The experimental equipment is composed of three main systems: heating and melting system, atmosphere control system, and data acquisition system. The infrared pyrometer is installed above the furnace tube, and the PID controller can adjust the heating power of the induction furnace according to the temperature signal collected by it at any time, so as to control the melting sample temperature. Two parallel holes are arranged 1 and 5 mm below the surface of the cooling crystallizer, and two sensitive K-type thermocouples are inserted respectively to collect the reaction temperature at different depths at a frequency of 75 Hz. The sample composition used in this experiment is Fe-3.5%Si0.85%Mn. First, the steel sample is cut into a small cylindrical sample with a mass of 4.0 g (±0.1 g) by wire cutting method, with a height of about 11.5 mm and a diameter of about 7 mm. All samples have the same shape and almost the same size. Then, the sample is polished with #180 and #400 sandpaper in order to remove various impurities on the surface, which can be used for the droplet solidification experiment. Prior to the start of the experiment, the copper cooling crystallizer was polished with #1500 sandpaper to ensure cleanliness and surface roughness. In one set of experiments,

Fig. 1 Experimental device for droplet solidification technology

Interfacial Heat Transfer Behavior Between Liquid Steel and Mold …

1149

multiple droplet solidification tests were performed, and the copper crystallizer was not cleaned in each test in order to deposit a natural oxide film on the original oxide film and study its effect on the corresponding heat flux. To ensure the same superheat, the pouring temperature of the samples before spraying was controlled at 1873 K (1600 °C). According to the temperature data collected at different depths, onedimensional inverse algorithm is used to build a mathematical model to calculate the interface heat flux. The thermal conductivity curve can be obtained by integrating the heat flux.

Results and Discussion Oxidation Film Deposition of Non-oriented Electrical Steel Containing Manganese After the experiment, in order to facilitate observation, the substrate with 3, 5, 7, and 9 layers of naturally deposited film was selected, and its surface morphology was observed by scanning electron microscope. The results are shown in Fig. 2. Figure 2a shows the deposition of the oxide film after three droplet experiments. It can be seen that a complete deposition film has been formed on the cooled base, and 3 to 4 spherical particles with an average particle size of 0.4 µm have gathered to form clusters. At higher magnification, it was found that the spherical particles were formed from the agglomeration of even finer oxides. After 5 experiments, the oxides on the deposited film changed from spherical particles to uniformly distribute in clusters. At high magnification, it is found that this cluster shape is caused by the small oxides growing and stacking, and the particle size increases to a certain extent, and cannot be tightly aggregated to form a sphere (Fig. 2b). In particular, after the end of the 7th experiment, the oxide film underwent a remelting phenomenon, and its surface morphology was greatly changed. The surface layer showed a threedimensional network structure with smooth veins, and the average diameter of the mesh void was about 0.8 µm (Fig. 2c). Under the high-power microscope, it can be observed that the subsurface layer is spherical oxide particles. Different from the oxide film deposited in previous experiments, the space between the oxide particles at this time is very small, and the overall density is relatively dense. On the basis of the network structure obtained after the seventh experiment, a large number of spherical oxide particles were deposited on the entire grid, and the average diameter of the mesh voids increased to about 1 µm, and the depth also increased significantly compared with the seventh experiment, indicating that the subsequent oxides continued to be deposited on the grid (Fig. 2d). Obviously, with the increase of the number of droplet experiments, the size of oxide particles gradually increased at first, and the oxide aggregate changed from cluster-like to cluster-like, which significantly changed after 7 experiments, and the oxide particles disappeared and changed into a three-dimensional grid structure. With

1150

X. Lyu et al.

Fig. 2 Surface morphology of oxide film after 3rd (a), 5th (b), 7th (c), and 9th (d) deposition experiments

the continuous progress of the experiment, the grid structure gradually accumulated. After the changes in the surface morphology of the oxide film were preliminatively determined, in order to further characterize the deposition of the oxide film, the cross section of the oxide film was observed and the thickness of the oxide film was measured under different experimental times (see Fig. 3). After three experiments, the average thickness of oxide film deposition was about 15.20 µm, and there were certain thickness differences in different locations (Fig. 3a). After 5 experiments, the thickness difference of each part of the oxide film continued to decrease, and the average thickness increased to 18.00 µm (Fig. 3b). After the 7th and 9th experiments, the thickness of oxide film was 19.60 µm and 22.40 µm, respectively, and the overall deposition situation was relatively uniform (Fig. 3c, d). We found that the thickness of the oxide film deposited in the 6th and 7th experiments was smaller than that deposited in the 4th and 5th experiments, while that deposited in the 8th and 9th experiments was larger than that deposited in the 6th and 7th experiments. Combined with the observation of the surface morphology of the oxide film, it should be due to the remelting of the oxide film after the 7th experiment, which became more dense. Therefore, the deposition thickness also decreases. However, the oxide particles generated in the 8th and 9th experiments accumulated on the grid structure, which significantly increased the height of the grid structure, so the deposition thickness increased.

Fig. 3 Thickness of oxide film after 3 (a), 5 (b), 7 (c), and 9 (d) deposition experiments

Interfacial Heat Transfer Behavior Between Liquid Steel and Mold …

1151

Table 1 Element content of oxide film after 3rd, 5th, 7th, and 9th deposition experiments Mn

O

Fe

Cr

7.71

25.23

45.78

4.20

17.08

5次

9.60

27.74

49.10

1.87

11.69

7次

10.35

29.97

50.19

0.82

8.67

9次

12.04

31.96

52.11

0.28

3.61

Element/wt.% 3次

Si

After the morphology was observed by scanning electron microscopy, the element content of each oxide film was determined by X-ray energy spectrometer, as given in Table 1, and the changes of deposited film components under different deposition times were plotted, as shown in Fig. 4. Because the steel contains more Si and Mn elements, with the multiple deposition of the oxide film, they continue to volatilize from the steel and combine with the residual oxygen in the air to form oxides, and finally deposit on the copper cooling base, so the content gradually increases, but the growth rate is gradually slow. At the beginning of the experiment, some Fe element was volatilized and deposited, but because the vapor pressure of Mn element was much higher than that of Fe, it was easier to be separated from the liquid steel. Therefore, as the experiment continued, the mass fraction of Mn in the oxide film continued to increase, while Fe gradually decreased. After detection, the main components of the oxide film are SiO2 , MnO, and FeO three oxides, in addition to a very small number of other types of oxides. The element Cr also appeared in the test results, which is because the oxide film was deposited on the chromium coating on the surface of the copper cooled substrate. When the oxide film deposition times were small, the oxide film thickness was small, and the oxide content was low. Xray penetrating the oxide film detected Cr, and the content of Cr was the highest at this time. However, when the oxide film deposition times increased, its thickness increased, the X-ray obstruction increased, so the detected Cr content also decreased from 17.08 to 3.61%.

Interfacial Heat Transfer of Non-oriented Electrical Steel Containing Manganese After the change of the morphology and thickness of the natural deposited oxide film, the influence of different deposited oxide film number on the heat transfer at the interface between molten steel and crystallizer was further studied. Figure 5 shows the interface heat flow curves obtained from the first, third, fifth, seventh, and ninth droplet experiments. It can be seen that the change trend of interfacial heat flow in experiments with different oxide film number is the same, that is, the rapid rise reaches the peak within the first 0.25 s, the rapid decline within 0.25–0.5 s, and the slow decline at a relatively gentle speed and tends to be stable within 0.5–1.0 s. This is because the temperature difference between the liquid steel and the cooling base is

1152

X. Lyu et al.

Fig. 4 Changes of oxide film components after 3rd, 5th, 7th, and 9th deposition experiments

Fig. 5 Interface heat flow curves of the first, third, fifth, seventh, and ninth droplet experiments

very large when the liquid steel is just in contact with the cooling base, and the heat transfer rate is very fast so that the interface heat flow rises rapidly to reach the peak. After contacting the substrate, the temperature gradient decreases sharply, the liquid steel solidifies and shrinks from the bottom, and the resulting air gap hinders the heat transfer. Moreover, the gradually thickening solidified shell further increases the interfacial thermal resistance, so the interfacial heat flow gradually decreases until it flattens out under the joint action of the three. In addition, the interface heat flow values of each experiment are basically the same in the initial rising stage, but the difference value of interface heat flow is larger when the experiment is closer to the peak position, and gradually decreases after the peak value, and the interface heat flow is closer near the end of the experiment. This also shows that the increase

Interfacial Heat Transfer Behavior Between Liquid Steel and Mold …

1153

of the number of oxide film will not cause a great change in the heat transfer form of steel. Figure 6 shows the changes of peak heat flow and total thermal conductivity in the first 2 s under different experimental times. With the increase of the number of experiments, that is, the increase of the number of deposited oxide film, the peak value of heat flow at the interface first decreases, turns at the 5th experiment, rises to the maximum value at the 7th experiment, and then decreases again. The change trend of the total thermal conductivity in the first 2 s is basically consistent with the change of the interface heat flow peak. Combined with the observation of the morphology and thickness of oxide films with different layers, it can be seen that in the early stage of the experiment, due to the increasing of oxide film thickness and the presence of more air gaps between oxide particles, the increase of interface thermal resistance leads to the decrease of the peak value of interface heat flow and the total thermal conductivity. In the 7th experiment, when the thickness of the oxide film increases to a certain value, too much heat accumulates on the oxide film, reaching the oxide melting point, causing it to remelt, the oxide air gap decreases, and the oxide film becomes dense, so the peak heat flow and total thermal conductivity at the interface reach the maximum value. After that, the thickness of oxide film continues to increase, and the air gap increases due to the formation of three-dimensional grid structure, so the peak value of interface heat flow and the total thermal conductivity decreases again.

Fig. 6 Change curves of interface heat flow peak value and total thermal conductivity in the first 2 s of the first, third, fifth, seventh, and ninth droplet experiments

1154

X. Lyu et al.

Conclusions (1) With the increase of the number of experiments, the thickness of oxide film deposition gradually increases, and its surface morphology goes through three stages: agglomeration, cluster, and three-dimensional network. After the seventh experiment, due to the remelting phenomenon, the oxide film appears as a threedimensional network structure, and then the oxide particles continue to deposit on the grid. (2) The main components of the naturally deposited film produced during continuous casting of manganese containing non-oriented electrical steel are oxides of Mn, Si, and Fe. With the continuous progress of the experiment, the oxide film components are basically stable. (3) The interfacial heat transfer between liquid steel and crystallizer of non-oriented electrical steel containing manganese decreases first, then increases, reaches a peak, and then decreases. The turning point occurred in the 7th deposition experiment, because at this time, the thermal resistance of the oxide film was large, the accumulated heat reached its melting point, and the phenomenon of remelting occurred, which reduced the air gap between the liquid steel and the crystallizer, so the heat transfer efficiency was improved.

References 1. Chengyi Z, Yuankai B, Yong W et al (2021) Application status and performance control research progress of non-oriented silicon Steel for new energy vehicle drive motor. Mater Rev 35(23):8 2. Senda K, Uesaka M, Yoshizaki S et al (2019) Electrical steels and their evaluation for automobile motors. World Electr Veh J 10(2):31. https://doi.org/10.3390/wevj10020031 3. Oda Y, Okubo T, Takata M (2016) Recent development of non-oriented electrical steel in JFE steel. JFE Tech Rep 21:7–13 4. Pradhap D, Ramesh P, Lenin NC (2019) Design and performance comparison of permanent magnet-assisted synchronous reluctance motors. In: International conference on power engineering, computing and control 5. Song JM, Chou TS, Chen LH et al (2001) Texture examination on strip-cast Fe-C-Si while cast iron. Scr Mater 44:1125–1130 6. Luiten EM, Blok K (2003) Stimulating R&D of industrial energy-efficient technology: the effect of government intervention on the development of strip casting technology. Energy Policy 31(13):1339–1356 7. Phinichka N, Misra P, Fang Y et al (2002) Initial solidification phenomena in the casting of steels. In: Dr. Manfred Wolf symposium. Zurich, Switzerland, pp 46–59 8. Wechesler R, Campbell P (2002) The first commercial plant for carbon steel strip casting at Crawfordsville. In: Dr. Manfred Wolf symposium. Zurich, Switzerland, pp 70–79 9. Strezov L, Herbertson J, Belton GR (2000) Mechanisms of initial melt/substrate heat transfer pertinent to strip casting. Metall Mater Trans B 31(5):1023–1030

Interfacial Heat Transfer Behavior Between Liquid Steel and Mold …

1155

10. Strezov L, Herbertson J (2007) Experimental studies of interfacial heat transfer and initial solidification pertinent to strip casting. ISIJ Int 38(9):959–966 11. Phinichka N (2001) The effect of surface tension, superheat and surface films on the rate of heat transfer from an iron droplet to a water cooled copper mold. Carnegie Mellon University 12. Zhu C, Wang W (2017) Study on interfacial heat transfer and film deposition in thin strip continuous casting by new droplet solidification technology. Chinese Society of Metals. In: Proceedings of the 11th China iron and steel annual conference—S02. Steelmaking and continuous casting. Chinese Society of Metals, p 5

Recrystallization of a 2.8 wt% Si Non-oriented Electrical Steel After Skew Cold Rolling at Different Angles to the Hot Rolling Direction Youliang He and Mehdi Sanjari

Abstract The magnetic properties of non-oriented electrical steel (NOES) are closely related to the final microstructure and texture of the annealed sheets, which not only depend on the annealing parameters, but also on the prior thermomechanical processing procedures applied to the steel before annealing. The cold deformation immediately before annealing generates an energized and inhomogeneous material state that is critical to the subsequent recrystallization since the nucleation and grain growth are all affected by the microstructure/substructure, texture, and the strain energy generated during the deformation process. Conventional cold rolling is a plane-strain compression process (2D), which normally produces very similar deformation and final annealing textures, i.e., the //RD (rolling direction) and //ND (normal direction) fibers, which are not the desired orientations for good magnetic properties. In this study, skew cold rolling is employed to process nonoriented electrical steel, in which the hot-rolled steel plates are fed into the rolls at different angles (22.5° and 45°) from the conventional rolling direction. This rolling scheme generates a unique three-dimensional (3D) deformation mode that can significantly alter the cold rolling texture, which in turn, leads to different recrystallization texture. A 2.8 wt% Si non-oriented electrical steel is skew cold rolled and the recrystallization of the steel is investigated by annealing the sheets at 1050 °C for different times (30 s and 60 s) to capture both partial and complete recrystallization. The results are compared to those after conventional rolling and cross rolling. It is shown that skew rolling can significantly enhance the //ND texture (desired for good magnetic properties) and largely reduce or eliminate the detrimental / /ND texture. Keywords Non-oriented electrical steel · Texture · Microstructure · Recrystallization · Skew rolling · EBSD

Y. He (B) · M. Sanjari CanmetMATERIALS, Natural Resources Canada, Hamilton, ON, Canada e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_101

1156

Recrystallization of a 2.8 wt% Si Non-oriented Electrical Steel After …

1157

Introduction Non-oriented electrical steel (NOES) is the dominant soft magnetic material for the manufacturing of electric motors and generators. The demand for NOES is projected to increase rapidly in the coming years [1], due to the transition from fossil fuels to renewable and clean energy in global economy, which heavily relies on NOES to manufacture generators and electric motors. Not only is the NOES production to be increased, but the quality of the steel is also to be improved. The most important magnetic property of the NOES is the core loss (also known as iron loss), which is dependent on both the microstructure and texture of the steel sheets after final annealing [2]. If conventional cold rolling is employed to produce NOES sheets, the cold rolling texture is usually very similar regardless the operational parameters used [3–5]. Likewise, the final annealing texture is also quite similar, i.e., consisting of the undesired //RD and //ND fibers [6]. To obtain the desired //ND texture in the final annealed steel sheets, many studies have been carried out, e.g., varying the chemical compositions, optimizing the hot rolling parameters, changing the cold rolling schemes, and altering the annealing conditions, etc. [7]. Although with somewhat improvement in the texture and/or microstructure, no remarkable change of the final texture has been reported. A few special techniques [8–11] have also been proposed and evaluated, which include the skew rolling process [11]. Skew rolling has been shown to be able to produce significantly different deformation textures from conventional rolling, which is expected to create very different final annealing texture as well. However, the recrystallization behavior of the steel produced by skew cold rolling has not been studied in detail [12]. This paper examines the recrystallization behavior of a 2.8 wt% Si NOES skew rolled at different angles (22.5° and 45°) from the hot rolling direction and discusses the evolution of texture during recrystallization. The textures are compared to those after conventional rolling and cross rolling. It is shown that the final annealing texture of the skew-cold-rolled steel shows much stronger //ND fiber than conventionally rolled and cross-rolled steels. The detrimental //ND fiber is largely weakened or eliminated.

Material and Experimental Procedure The material investigated in this study was a 2.8 wt% Si NOES. The chemical composition is given in Table 1. The steel was vacuum melted in an induction furnace and cast into an ingot of 200 mm × 200 mm (cross section). The ingot was then reheated to about 1040 °C and hot rolled (both roughing and final rolling) to plates of about 2.5 mm in thickness. After pickling in hot HCl acid, the hot-rolled plates were annealed at ~840 °C for 60 h in a 100% dry H2 atmosphere. The plates were then cold rolled in three different schemes as shown in Fig. 1. For conventional cold rolling, the plate was rolled along the original hot rolling direction (HRD), while

1158

Y. He and M. Sanjari

for cross rolling, the cold rolling was performed along the hot transverse direction (HTD). In both cases, the rolling is a 2D plane-strain compression process, and only the initial texture is rotated 90° around the ND in cross rolling. For skew rolling, the plate was fed into the rolls at 22.5° and 45° (α) from the conventional rolling direction. This feeding scheme not only rotates the initial texture around the ND before cold rolling, but also fundamentally changes the deformation mode from 2D to 3D, the latter consisting of thickness reduction, elongation, width spread as well as bending of the plate (Fig. 1). Due to the force in the roll axis direction, the plate will move along the roll axis during skew rolling [11]. In this study, all the plates were cold rolled to a thickness of 0.5 mm in a laboratory reversing rolling mill in multiple passes. The microstructure of the cold-rolled steel sheets was characterized by optical microscopy. The textures of the cold-rolled sheets were measured by X-ray diffraction (XRD) at the mid-thickness plane and the orientation distribution functions (ODFs) were calculated and represented in Euler space (Bunge’s notation) using MTEX. The steel sheets after cold rolling using different schemes were annealed at 1050 °C for 30 s (partial recrystallization) and 60 s (complete recrystallization) to examine the effect of cold rolling scheme on the final recrystallization texture. Crosssection (RD-ND plane) microstructure and microtexture were characterized by electron backscatter diffraction (EBSD) under scanning electron microscope (SEM). The samples for EBSD measurements were prepared using conventional metallographic techniques, and a final polishing step using a 0.05 μm colloidal silica suspension Table 1 Chemical composition (wt%) of the investigated NOES Steel

C

2.8Si

0.0033

Mn 0.303

P

S

0.010

0.0011

Si 2.767

Al

Fe

0.516

Bal

Fig. 1 Schematic illustration of the skew rolling process as compared to conventional rolling and cross rolling

Recrystallization of a 2.8 wt% Si Non-oriented Electrical Steel After …

1159

was applied. The ODFs were calculated using a harmonic series expansion method with a Gaussian of 5° and a series rank of 22. The textures were plotted on the ϕ2 = 45° section of the Euler space with a triclinic sample symmetry (due to the lack of orthorhombic sample symmetry during skew rolling). For skew rolling, two skew angles, a = 22.5° and 45°, were used, which generated different cold rolling and recrystallization textures.

Results and Discussion Microstructure and Macrotexture After Cold Rolling Figure 2 shows the microstructure and macrotexture of the samples after cold rolling. While the microstructures characterized by optical microscopy do not show obvious differences among the samples, the textures do illustrate apparent discrepancies. The major difference is the maximum texture component. For conventional rolling, the strongest texture is at {112} on the α-fiber (//RD), which is a common cold rolling texture for bcc (body centered cubic) metals. There are also continuous α- (//RD) and γ-fibers (//ND), typical for bcc metals after rolling. For cross rolling, although the deformation mode is also plane-strain compression, the rotation of the hot-band texture (after annealing) by 90° around the ND changes the crystal orientations and the active slip systems, which inevitably induces different deformation textures. In this case, the maximum texture is around the rotated cube ({001}), which is believed to be the result of the //TD texture (90° rotation around ND of the α-fiber) [7]. The //TD texture is unstable and tends to rotate toward the {001} orientation. For skew rolling, the maximum texture component depends on the skew angle: at a skew angle of 22.5°, the maximum component is close to {112}, very similar to conventional rolling, while at a skew angle of 45°, the strongest texture is at {001} on the //ND fiber, which is about 15° from the rotated cube. It has been shown in previous study [11] that the skew rolling process applies a complicated 3D deformation mode on the material, with very strong shear deformation even in the mid-thickness plane, which significantly influences the orientation flow during deformation, leading to different textures from conventional rolling. However, how exactly the final texture is formed during the skew rolling process is not clear, which deserves further investigation. In all the cases, a //ND fiber is also present in the texture. However, the main component on this fiber is different between the conventional/cross-rolled and skew-rolled samples. {111} is the major component for conventional/crossrolled samples, while a component between {111} and {111} is the dominant orientation in the skew-rolled samples. Apparently, skew rolling not only moves the major component on the //ND fiber from the stable {001} in conventional rolling to {001}, but also shifts the {111} on the // ND fiber toward the {111} orientation. The intensities of the //ND fiber

1160

Y. He and M. Sanjari

RD

TD

Fig. 2 Microstructure and macrotexture of the 2.8 wt% Si NOES after cold rolling using different schemes: a cross-section microstructure (optical microscopy), b ϕ2 = 45° sections of the ODFs at mid-thickness plane (measured by XRD) [10, 11], and c common texture components and fibers on the ϕ2 = 45° section

in the samples cold rolled by cross rolling and skew rolling are lower than that by conventional rolling, indicating the improvement of the cold rolling texture.

Microstructure and Microtexture After Annealing at 1050 °C for 30 s Figure 3 shows the EBSD inverse pole figure (IPF) maps of the samples (recrystallized grains) after annealing at 1050 °C for 30 s. In all the samples, recrystallization is incomplete, and the fractions of the recrystallized grains in samples cold rolled using different schemes differ considerably (Table 2). Conventional rolling leads to the lowest recrystallization rate (72.3%) among all the samples. Cross rolling results in the fastest recrystallization (92.2%). The recrystallization of the skew-rolled samples is faster than conventional rolling but is slower than cross rolling. The recrystallized fraction of the sample with a skew angle of 22.5° (83.2%) is slightly higher than that with a 45° skew angle (74.7%). The average grain size of the recrystallized crystals shows a large difference (Table 2) between the cross-rolled sample and the samples cold rolled by conventional

Recrystallization of a 2.8 wt% Si Non-oriented Electrical Steel After …

1161

Fig. 3 Microstructure and microtexture of the steel (recrystallized grains) after annealing at 1050 °C for 30 s: a–d EBSD inverse pole figure maps, e–h ϕ2 = 45° sections of the ODFs. Crystals with grain orientation spread (GOS) ≤3° are considered as recrystallized grains

Table 2 Area fractions of recrystallized grains and the average grain sizes Conventional rolling

Cross rolling

Skew rolling 22.5°

Skew rolling 45°

Fraction of recrystallized grains (%)

72.3

92.2

83.2

74.7

Average grain size of recrystallized grains (μm)

21.0

39.9

21.7

19.0

and skew rolling. The average grain size of the cross-rolled steel (~40 μm) is roughly double those of conventionally or skew-rolled samples (~20 μm). This means that cross rolling not only leads to a higher stored energy in the microstructure which causes a faster recrystallization, but also favors the growth of the recrystallized grains in a short time, which gives rise to a larger average grain size than the other samples. The textures of the recrystallized grains in these samples also show apparent differences, although the maximum intensities are all relatively low as compared to the cold-rolled samples. Annealing of the conventionally rolled sample produces a strong Goss texture ({011}), which originates from the nucleation of Goss grains within shear bands [13, 14]. A relatively strong //ND fiber also forms, and the //ND texture is weak. Recrystallization of the cross-rolled sample creates a strong {111} texture as well as a relatively strong cube texture. The Goss texture is very weak. For the sample skew rolled at 22.5°, the strongest texture

1162

Y. He and M. Sanjari

is the {001} component on the //ND fiber, which is ~15° from the cube ({001}). Relatively strong {111} and {115} also form. Annealing of the 45° skew-rolled sample produces strong textures close to {001} and {110}. A strong, continuous //ND fiber is also formed. At an annealing temperature of 1050 °C, new grains can rapidly form in the deformed grains, especially within the substructures (e.g., shear bands, microbands, transition bands, etc.) that have higher stored energy than the matrix [15]. The difference in the deformation texture after cold rolling using different schemes implies different stored energies in crystals of different orientations as well as different substructures within the deformed matrix, which determine the recrystallization behaviour during annealing. As shown before, after conventional rolling, a / /ND fiber and a //RD fiber dominated the texture. It is well known that the Taylor factors (and thus the stored energies) of the //ND grains are higher than those of the //RD grains under plane-strain compression, and the //ND grains tend to form substructures within the deformed grains, which have higher stored energy than the matrix [13, 15]. These substructures are preferred nucleation sites. When recrystallization starts, the //ND grains are first consumed by forming new grains (Goss is one of the preferred orientations) in these grains, while the deformed //RD or //ND grains have lower stored energy and will not recrystallize at the beginning. As a result, the {001} < 110 > and {112} < 110 > orientations are the main texture components retained in the unrecrystallized grains (see Fig. 4a and e). On the other hand, although the deformation mode for cross rolling is the same as conventional rolling, the deformation texture is significantly different (Fig. 2b). This

Fig. 4 Microstructure and microtexture of the deformed grains (retained) after annealing at 1050 °C for 30 s: a–d EBSD inverse pole figure maps, e–h ϕ2 = 45° sections of the ODFs. Crystals with grain orientation spread >3° are considered as deformed grains

Recrystallization of a 2.8 wt% Si Non-oriented Electrical Steel After …

1163

results in rapid recrystallization and apparent grain growth. As shown in Fig. 4b, no elongated grains are retained after 30 s of annealing. This, unfortunately, makes the investigation of the initial recrystallization very difficult as it is not able to observe which grains recrystallize first. The uncrystallized grains in the skew-rolled samples (Figs. 4g and h) show //ND and //RD textures, similar to conventional rolling, which indicate that these grains have smaller stored energy than the // ND grains and thus recrystallize later. However, in both cases, some {111} grains are retained, which are not seen in the conventionally rolled steel. This seems to suggest that some of the //ND grains after skew rolling may have low stored energy (instead of high stored energy as in plane-strain compression) and are not easy to recrystallize.

Microstructure and Microtexture After Annealing at 1050 °C for 60 s The recrystallization textures of the steel cold rolled using different schemes as shown above may not be preserved as the new grains grow. In fact, if the annealing is performed at the same temperature (1050 °C), but the holding time is extended to 60 s, significant grain growth is noticed in all the samples (Fig. 5a–d). Surprisingly, the average grain size of the cross-rolled sample is now the smallest (~130 μm), while those of the conventionally rolled and skew rolled are slightly larger (~140– 145 μm). The textures are also quite different from those after initial recrystallization. After annealing for 30 s, the maximum intensities (8.4–8.5) of the conventionally and cross-rolled samples are slightly higher than those of the skew-rolled samples (6.4–7.5). After annealing for 60 s, these are just the opposite. While the maximum intensities of the conventionally and cross-rolled samples are reduced to 5.7–6.1, those of the skew-rolled samples are significantly increased to 14.4–17.6. Although in all the cases the strongest texture is on the //ND fiber (the desired texture for good magnetic properties), the skew-rolled samples show much higher intensities than conventionally or cross-rolled samples. This means that skew rolling does significantly improve the crystallographic texture. In all the cases, the //ND fiber texture is quite weak or is essentially eliminated [16], which gives rise to excellent magnetic properties. The average grain size of around 130~145 μm (close to the optimal grain size of about 150 μm [17]) might have also contributed to the good magnetic properties.

1164

Y. He and M. Sanjari

Fig. 5 Microstructure and microtexture of the after annealing at 1050 °C for 60 s: a–d EBSD inverse pole figure maps, e–h ϕ2 = 45° sections of the ODFs

Conclusions It is shown in this study that, the application of skew cold rolling on the 2.8 wt% Si NOES can significantly improve the final texture, i.e., producing a very strong / /ND texture (the desired texture), and optimize the microstructure, i.e., creating an average grain size (~145 μm) close to the optimal grain size of ~150 μm, after complete recrystallization (annealing at 1050 °C for 60 s). This is due to the different deformation mode and the different cold rolling texture formed in the material before annealing. While the detrimental //ND fiber does exist in the initial recrystallization texture (annealing at 1050 °C for 30 s), extending the annealing time significantly weakens or essentially eliminates this texture. Thus, skew rolling is believed to be an effective technique to optimize the texture, microstructure, and magnetic properties of non-oriented electrical steels. Acknowledgements Funding for this work was provided by Natural Resources Canada through the Program of Energy Research and Development (OERD). Dr. Erik Hilinski is thanked for providing the electrical steel. The authors are grateful to Michael Attard for cold rolling the steel, and to Renata Zavadil and Jian Li for assistance in EBSD measurements.

References 1. Vittori C, Evans G, Fini M (2021) Electrical steel—another temporary supply chain shortage or a threat to OEMs’ electrification plans? IHS Markit, S&P Global Mobility

Recrystallization of a 2.8 wt% Si Non-oriented Electrical Steel After …

1165

2. Moses J (1990) Electrical steels: past, present and future developments. IEE Proc A (Phys Sci Measure Instrum Manage Educ) 137(5):233–245 3. Raphanel JL, Van Houtte P (1985) Simulation of the rolling textures of b.c.c. metals by means of the relaxed taylor theory. Acta Metall 33(8):1481–1488 4. Hölscher M, Raabe D, Lücke K (1991) Rolling and recrystallization textures of bcc steels. Steel Res 62(12):567–575 5. Raabe D (1995)Simulation of rolling textures of b.c.c. metals considering grain interactions and crystallographic slip on {110}, {112} and {123} planes. Mater Sci Eng A 197(1):31–37 6. Kestens LAI, Pirgazi H (2016) Texture formation in metal alloys with cubic crystal structures. Mater Sci Tech 32(13):1303–1315 7. Kestens L, Jacobs S (2008) Texture control during the manufacturing of nonoriented electrical steels. Texture, Stress, Microstruct 173083:1–9 8. Tomida T (1996) A new process to develop (100) texture in silicon steel sheets. J Mater Eng Perform 5(3):316–322 9. Tomida T, Uenoya S, Sano N (2003) Fine-grained doubly oriented silicon steel sheets and mechanism of cube texture development. Mater Trans 44(6):1106–1115 10. He Y, Hilinski E, Li J (2015) Texture evolution of a non-oriented electrical steel cold rolled at directions different from the hot rolling direction. Metall Mater Trans A 46(11):5350–5365 11. He Y, Hilinski EJ (2017) Skew rolling and its effect on the deformation textures of non-oriented electrical steels. J Mater Process Techn 242:182–195 12. He Y, Hilinski E (2022) Textures of non-oriented electrical steel sheets produced by skew cold rolling and annealing. Metals 12(17):1–20 13. Ushioda K, Hutchinson WB (1989) Role of shear bands in annealing texture formation in 3% Si–Fe (111) [112] single crystals. ISIJ Inter 29(10):862–867 14. Park JT, Szpunar JA (2003) Evolution of recrystallization texture in nonoriented electrical steels. Acta Mater 51(11):3037–3051 15. Mehdi M, He Y, Hilinski E, Kestens L, Edrisy A (2020) The evolution of cube ({001}) texture in non-oriented electrical steel. Acta Mater 185(2):540–554 16. Mehdi M, He Y, Hilinski E, Edrisy A (2019) Texture evolution of a 2.8 wt% Si non-oriented electrical steel and the elimination of the //ND texture. Metall Mater Trans A 50(7):3343– 3357 17. Shiozaki M, Kurosaki Y (1989) The effects of grain size on the magnetic properties of nonoriented electrical steel sheets. J Mater Eng 11:37–43

Part XXXI

Electronic Packaging and Interconnection Materials

Numerical Modeling of Electromigration in Al(0.25 at. % Cu) Interconnects James Gordineer and Ping-Chuan Wang

Abstract Electromigration is a failure mechanism of major interest in the microelectronics industry. It is well known that introducing Cu solute into Al interconnects greatly increases the resistance against electromigration degradation. Al electromigration is significantly slowed by the presence of Cu solutes until they are preferentially electromigrated away, and it only occurs within the Cu-depleted region where a resulting short-range stress gradient was hypothesized. In this study, a numerical model is developed to simulate the effects of Cu solute on electromigration induced short-range stress development in an Al(0.25 at.% Cu) interconnect. The simulation results are compared with a recent set of experimental observations by an X-ray microbeam technique to extract material parameters related to the electromigration process in Al(Cu) alloy. This study could further our understanding of electromigration mitigation, particularly for alloy-based interconnects in advanced IC technologies. Keywords Electromigration · Al interconnects · Numerical modeling · Microelectronics · Reliability

Introduction Electromigration is a degradation mechanism present in computer chip interconnects. The effect it causes is negligible in larger wires and cables used in the household, but the damage caused in microchips is detrimental due to the significantly higher current density and temperature involved in integrated circuit (IC) operations [1]. In aluminum (Al) IC interconnects, the Al atoms are battered with a continuous flow of electrons. As a result of the momentum transfer from the electrons, or the so-called electron wind force, Al atoms are displaced within the interconnects from cathode to anode. Due to flux divergence at the ends of the interconnects, mass depletion occurs J. Gordineer · P.-C. Wang (B) State University of New York at New Paltz, New Paltz, NY, USA e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_102

1169

1170

J. Gordineer and P.-C. Wang

at the cathode end and eventually leads to void formation and open circuit fail; mass accumulation occurs at the anode end that results in extrusions and potential electrical shorts to adjacent interconnects. These are major concerns in developing new IC technologies with ever-decreasing device dimensions. In the meantime, electromigration of Al atoms induces mechanical stress along the interconnects, developing tensile and compressive stress at the cathode and anode ends, respectively [1, 2]. This stress gradient induces a backflow of Al atoms opposite to the electron wind force, slowing down or even completely stopping the Al transport. Copper (Cu) has been added to Al interconnects to form Al(Cu) alloyed interconnects which are more resistant to electromigration. It has been reported that the addition of Cu increases the electromigration lifetime by about 100× [3–6]. In this case, Cu tends to decorate the grain boundaries in polycrystalline Al interconnects, blocking the Al grain boundary diffusion until it is depleted from the region. Therefore, Al electromigration is delayed and can only occur within the Cu-depleted region [7, 8]. It is proposed that the delay of Al electromigration is due to the short-range stress gradient developed within the Cu-depleted region [5, 9, 10]. This hypothesis was first observed experimentally by an X-ray microdiffraction study [11] and recently confirmed by scanning X-ray microbeam topography measurements [12]. In this paper, we report the attempt of using numerical modeling with finite difference method to simulate the electromigration stress development in Al(Cu) interconnects. First, preliminary simulation for a pure Al interconnect was conducted to demonstrate feasibility of the algorithm in adopting the governing equations by Korhonen et al. [13]. Simulations of both Cu and Al electromigration in an Al(Cu) interconnect were then carried out to reproduce the recent experimental observations [12] and to provide insight in the relationship between Al and Cu diffusion in Al(Cu), from which some material parameters dictating Al(Cu) electromigration can be extracted.

Numerical Methods The Al and Al(Cu) interconnect modeled in this study is 200 µm long, 10 µm wide, and 0.5 µm thick, segmented into 40 cells with 5 µm in length for each cell, as shown in Fig. 1. Material parameters and variables used for numerical calculations in simulating the electromigration process in pure Al and Al(Cu) interconnects are listed in Table 1. Some of the parameters were estimated from the iterative adjustments to fit the experimental observations and interpretations [12], including critical Cu ∗ ∗ and Z Al , respectively, as concentration, C Cu,crit , effective valence of Cu and Al, Z Cu well as the initial atomic density of the Al interconnect nAl,0 before electromigration which is slightly smaller than the natural density due to the slight tensile stress developed in the fabrication process.

Numerical Modeling of Electromigration in Al(0.25 at.% Cu) … Fig. 1 Schematic top view of the interconnect for the numerical modeling

ni,j or Ci,j

Cathode

e-

1171

Ji

Anode

Ji+1 cell i

10 µm

200 µm

Table 1 Parameters used in the model calculation Symbol

Physical quantity

Value

Units

e

Electron charge

− 1.60E−19

C

ρ

Al resistivity

5.90E−2

Ω µm

j

Current density

4.00E−3

Ω

Al atomic volume

1.70E−11

A µm2 µm3

kB

Boltzmann’s constant

1.38E−23

◦K

T

Experimental temperature

576.6

◦K

∆x

Cell length

5

µm

∆t

Time interval for calculation

4

s

J Al,EM

Al atom flux from electron wind

–

J Al,BF

Al atom flux from backflow

–

nAl,0

Al initial atomic density before electromigration

6.04E10 [12]

nAl

Al atomic density

–

at. µm2 at. µm2 at. µm3 at. µm3

∗ Z Al

Al effective valence

− 1.9 [12]

DAl

Al diffusivity

2.82E−2 [2]

µm2 s

eff DAl

Effective Al diffusivity

–

µm2 s

Beff

Effective bulk modulus

33.3 [13]

GPa

J Cu,EM

Cu atom flux from electron wind

–

J Cu,BF

Cu atom flux from backflow

–

at. µm2 at. µm2

C Cu

Cu concentration

–

C Cu,crit

Critical Cu concentration

0.164 [12]

∗ Z Cu

Cu effective valence

− 5.6 [12]

DCu

Cu diffusivity

1.05E−2 [14]

J

µm2 s at. µm3

µm2 s

Simulation of Pure Al Interconnect for Feasibility Demonstration Simulation for pure Al was first conducted to demonstrate the feasibility of using finite difference method to model the electromigration behavior, employing the analytical model developed by Korhonen et al. [13]. Two primary equations govern

1172

J. Gordineer and P.-C. Wang

the total flux of Al atoms within a given cell. First, during electromigration the electron wind-driven flux can be expressed by [15] JAl,EM =

∗ eρ j DAl n Al Z Al , kB T

(1)

which transports Al atoms from cathode to the anode end of the interconnect, generating difference in Al atomic density and hence mechanical stress along the interconnect. As a result, based on the stress generating mechanism established by , or Korhonen et al. [13], back-diffusion of Al occurs due to the stress gradient ∂σ∂ EM x ∂n Al Al density gradient ∂ x for simulation purposes, as the driving force. This diffusion flux occurs in the opposite direction from the electron wind-driven flux J A1,EM and can be expressed by the stress gradient-driven flux J A1,BF JAl,BF = −

( ) DAl BΩ ∂n Al . kB T ∂x

(2)

Therefore, the total atom flux J Al,total in each cell at any time during electromigration is ( ) DAl ∂n Al ∗ n Al Z Al eρ j − BΩ . (3) JAl,total = kB T ∂x The total atom flux at both ends of the interconnect (i.e., x = 0 and 200 µm) is set to 0 as the boundary conditions for the model calculations. The change in Al atomic density over time in each given cell can be obtained from the continuity equation ∂ JAl,total ∂n Al =− . ∂t ∂x

(4)

Therefore, the finite difference simulation can be carried out using Eq. (5) below, which is an adaptation of Eq. (4): n i, j − n i, j−1 Ji+1, j − Ji, j = . t j − t j−1 xi+1 − xi

(5)

With the atomic density n i, j−1 at a given time, Eq. (5) can then be used to solve for n i, j to determine the concentration of each interconnect cell after a time interval. Solving for subsequent densities yields the necessary variables to determine the total flux of each cell proceeding into the next iteration of the interconnect simulation. With a time interval of 4 s for convergence, this chain of dependent iterations of Al

Numerical Modeling of Electromigration in Al(0.25 at.% Cu) …

1173

interconnect cells forms the basis for the primary simulation and gives an estimate of the electromigration process in a pure Al interconnect. To demonstrate the feasibility of the numerical model, simulation was conducted to calculate the Al atomic density change in a pure Al interconnect during electromigration. Using the parameters listed in Table 1, Fig. 2 shows the results of the simulations at different times up to 1 h, with the upper and lower limits in the Al atomic density set at values based on the estimated stress limit in the Al interconnect [11, 12]. As can be seen in Fig. 2, Al atomic density consistently evolves as Al moves from the cathode end to the anode end from the electron wind force, gradually develops a counter-acting density gradient that opposes the electron wind force. Within 0.5 h, the density gradient approaches the steady state as the Al atomic density reaches the upper and lower limits at the cathode end and anode end, respectively. Extending simulation run time passed 0.5 h would slightly further linearize the density gradient. Note that the change in Al atomic density is proportional to the stress change in the interconnect through an effective modulus of the interconnect. Therefore, the general trend of Al atomic density change is consistent with the analytical stress calculations by Korhonen et al. [13], demonstrating the feasibility of the numerical calculations to model the electromigration in Al(Cu).

Fig. 2 Simulated evolution of Al atomic density along a pure Al interconnect

1174

J. Gordineer and P.-C. Wang

Working Simulation of Electromigration in Al(Cu) Interconnects For electromigration in Al(Cu) alloyed interconnects, Cu solutes tend to block Al electromigration until they are preferentially migrated off by electron wind [4-6]. In the region where Cu is depleted, the subsequent Al electromigration is modeled to follow similar behavior as in pure Al interconnects. Therefore, the preferential electromigration of Cu needs to be determined first before simulating the Al electromigration. Upon electromigration, the electron wind-driven Cu flux is described by [4] JCu,EM =

∗ eρ j DCu CCu Z Cu , kB T

(6)

and the concentration gradient-driven Cu backflow flux by JCu,BF = −

( ) DCu CCu ∂ ln CCu kB T . kB T ∂x

(7)

Therefore, the total Cu flux J Cu,total in each cell at any time during electromigration is ( ) DCu CCu ∂ ln CCu ∗ Z Cu eρ j − k B T , (8) JCu,total = kB T ∂x with the same flux divergence at the ends of the interconnects as the boundary condition: JCu,total = 0 at x = 0 and 200 µm. Figure 3 shows the calculated Cu concentrations at various times during the simulated electromigration process, with an initial evenly distributed Cu concentration of 0.25 at.% over the interconnect. In general, Cu atoms migrate from cathode to the anode region during electromigration, piling up at the anode end. The maximum concentration is limited to 0.40 at.% which is the solubility limit of Cu in Al at the simulated temperature of 576 °K (or 303 °C) [14]. Beyond the solubility limit, Al2 Cu precipitation occurs as the sink for additional Cu added into the anode end. eff To simulate Al diffusion in Al(Cu), effective Al diffusivity DAl was used for the calculation and was treated as dependent on the Cu concentration in each cell. Cu was assigned its own uniform starting concentration of 0.25 at.% and was processed through Eq. (8) to generate concentration C Cu of each cell during each iteration. The eff on Cu concentration is not well studied. A dependence of effective Al diffusivity DAl step-function dependence has been proposed for the analytical modeling of the stress evolution by Korhonen et al. [9]. The step-function dependence was also adopted by Kao et al. to reproduce their measurement results on the relationship between Cu concentration and stress generation during electromigration, which is the only experimental observation of such relationship that we are aware of currently [11].

Numerical Modeling of Electromigration in Al(0.25 at.% Cu) …

1175

Fig. 3 Simulated evolution of Cu concentration along an Al(0.25 at.% Cu) alloyed interconnect

Based on the step-function dependence, a critical Cu concentration C Cu,crit is defined as the threshold concentration above which Al diffusion is completely eff = 0), as described by Eq. (9) and illustrated in Fig. 4. In regions blocked (DAl where Cu concentration is reduced to below C Cu,crit , Al diffusion was treated as diffusion in pure Al, independent of the Cu concentration. eff DAl =

DAl CCu < CCu,crit 0 CCu ≥ CCu,crit

(9)

With the simulated Cu concentration shown in Fig. 3 and the effective Al diffueff defined in Eq. (9), the Al atomic density during electromigration can be sivity DAl calculated. Figure 5 shows the Al atomic density profiles after 8.14 h of electromigration, calculated for different values of critical Cu concentration C Cu,crit . For C Cu,crit = 0, the Al electromigration is completed block along the entire line and the atomic density remains at its initial value as expected. With finite C Cu,crit , a shortrange gradient in Al atomic density develops in the region where Cu concentration is below the corresponding critical value. In the upstream cathode region, the Al atomic density decreases to below the initial value, indicating the development of tensile stress. On the other hand, in the downstream portion of the Cu-depleted region, the Al atomic density increases that leads to expected compressive stress development there. No change in Al atomic density can be seen further downstream beyond the Cu-depleted region where Al diffusion is completely blocked. Based on a recent experimental study of electromigration in Al(Cu) using scanning X-ray microbeam topography and fluorescence techniques [12], the measurement

1176

J. Gordineer and P.-C. Wang

eff on Cu concentration modeled for the simulation Fig. 4 Dependence of effective Al diffusivity DAl of Al electromigration in Al(0.25 at.% Cu) interconnect

Fig. 5 Simulated evolution of Al atomic density along an Al(0.25 at.% Cu) interconnect after 8.14 h of electromigration, with different values for the critical Cu concentration C Cu,crit above eff on Cu which Al diffusion is completely blocked. The dependence of effective Al diffusivity DAl concentration is a step function

Numerical Modeling of Electromigration in Al(0.25 at.% Cu) …

1177

results at ~ 8.14 h of electromigration can be best reproduced by adopting C Cu,crit = 0.164 at.%. Other experimental observations used to estimate the relevant simulation parameters listed in Table 1 include the rate of Cu depletion (related to Cu effective ∗ valence Z Cu ), as well as the distance over which the maximum Al atomic density ∗ ). gradient was established (related to Al effective valence Z Al Figure 6 shows the calculated Al atomic density at different times during the electromigration process. At the cathode end of the interconnect, the atomic density quickly drops upon electromigration and reaches and stays at the lower limit. At the downstream end of the growing Cu depletion region, the atomic density gradually increases within the first ~ 5 h. that maintains the maximum atomic density gradient (and thus a maximum Al backflow flux J A1,BF ) within the Cu depletion region. This maximum Al backflow flux counterbalances the electron wind flux J A1,EM during this “incubation time” during which no mass depletion was observed in Al(Cu) interconnects [5, 6]. Afterwards, the stress at the downstream end of the growing Cu depletion region is limited to the upper limit, causing the atomic density gradient to decrease with time and leading to mass depletion after the incubation time. The simulated results shown in Fig. 6 reproduce the recent experimental observations by Wang et al. [12] and provides another insight into the fundamental mechanism in Al(Cu) electromigration. eff Another model of the effective Al diffusivity DAl is entertained by treating its dependence on Cu concentration as linear, as described by

Fig. 6 Simulated evolution of Al atomic density along an Al(0.25 at.% Cu) interconnect at various times before and during electromigration, with the critical Cu concentration C Cu,crit = 0.164 at.%. eff on Cu concentration is a step function The dependence of effective Al diffusivity DAl

1178

J. Gordineer and P.-C. Wang

eff DAl

=

( DAl × 1 − 0

CCu CCu,crit

)

CCu < CCu,crit CCu ≥ CCu,crit

.

(10)

In such case, as in the step-function dependence model, the Al diffusion is completely blocked in regions where Cu concentration is above the critical value C Cu,crit of 0.164 at.%. In regions with lower Cu concentration, the effective Al diffusivity is linearly dependent on the Cu concentration below the critical Cu concentration C Cu,crit as described in Eq. (10) and illustrated in Fig. 4. Figure 7 shows the calculated Al atomic density at different times under electromigration, with parameters identical to those used in generating Fig. 6 that best reproduce the recent experimental observations [12]. In the upstream cathode region, eff models is insignificant, with slight delay the difference in the results from the two DAl in atomic density reduction (or tensile stress development) at the very early stages of electromigration before reaching its lower limit. In the downstream portion of the Cu depletion region, in addition to the slight delay in the atomic density increase (or compressive stress development) during the early stages of electromigration, the Al atomic density plateaus at the upper limit over a finite distance in the downstream portion of the Cu depletion region, as seen in the calculations for 8.14 h and beyond shown in Fig. 7. As a result, the Al atomic density gradient (and thus the Al backflow flux J AL,BF ) in the cathode region persists at the maximum value over a longer period of time. This implies that the incubation time predicted by the linear-dependence eff on C Cu model is ~ 50% longer than that from the step-function dependence of DAl model shown previously in Fig. 6.

Fig. 7 Simulated evolution of Al atomic density along an Al(0.25 at.% Cu) interconnect at various times before and during electromigration, with the critical Cu concentration C Cu,crit = 0.164 at.%. eff on Cu concentration is linear The dependence of effective Al diffusivity DAl

Numerical Modeling of Electromigration in Al(0.25 at.% Cu) …

1179

Note that this report is aimed at demonstrating the feasibility of using finite difference method to simulate the electromigration-induced atomic transport in Al(Cu) interconnects. The boundary conditions and assumptions used in the numerical modeling are described based on the underlying physics and proposed mechanisms. It is not in the scope of this study to discuss the detailed comparison with the experimental observations [12]. Further works are in progress to develop a methodology to optimize the simulation parameters in reproducing the experimental observations and extracting the relevant material parameters more accurately.

Conclusion In this paper, the effects of Cu solute on the electromigration degradation of Al(0.25 at.% Cu) alloyed interconnects are studied with finite difference numerical simulations. Results of the calculations support the observations that Cu solute effectively retards diffusion of Al. During electromigration, Cu preferentially migrates away from the cathode region of the interconnect, creating a Cu depletion region where Al migration takes place. The subsequent diffusion of Al induces a shortrange Al atomic density (and thus stress) gradient, resulting in the opposing Al backflow diffusion to counteract Al electromigration. The mechanism is modeled eff on Cu concentration by the simplified dependence of effective Al diffusivity DAl C Cu , with a critical Cu concentration C Cu,crit above which Al diffusion is completely blocked. Results of the simulations support the experimentally observed “incubation time” during which no apparent electromigration degradation can be observed. Going forward, optimization methods can be developed to determine the best simulation parameters to reproduce the recent experimental observations by an X-ray microbeam technique. This may provide further insight into the fundamental mechanism of electromigration in Al(Cu) interconnects and other alloy-based interconnects in advanced IC technologies.

References 1. Blech IA (1976) Electromigration in thin aluminum films on titanium nitride. J Appl Phys 47(4):1203–1208. https://doi.org/10.1063/1.322842 2. Wang P-C, Cargill GS III, Noyan IC, Hu C-K (1998) Electromigration-induced stress in aluminum conductor lines measured by x-ray microdiffraction. Appl Phys Lett 72:1296–1298. https://doi.org/10.1063/1.120604 3. Ames I, d’Heurle FM, Horstmann RE (1970) Reduction of electromigration in aluminum films by copper doping. IBM J Res Dev 14:461–463. https://doi.org/10.1147/rd.144.0461 4. Blech IA (1977) Copper electromigration in aluminum. J Appl Phys 48:473–477. https://doi. org/10.1063/1.323689 5. Hu C-K, Ho PS, Small MB (1992) Electromigration in two-level interconnect structures with Al alloy lines and W studs. J Appl Phys 72:291–293. https://doi.org/10.1063/1.352335

1180

J. Gordineer and P.-C. Wang

6. Filippi RG, Biery GA, Wachnik RA (1995) The electromigration short-length effect in TiAlCu-Ti metallization with tungsten studs. J Appl Phys 78:3756–3768. https://doi.org/10.1063/ 1.360749 7. Rosenberg R (1972) Inhibition of electromigration damage in thin films. J Vac Sci Technol 9:263–270. https://doi.org/10.1116/1.1316576 8. Liu C-L, Liu X-Y, Borucki LJ (1999) Defect generation and diffusion mechanisms in Al and Al-Cu. Appl Phys Lett 74:34–36. https://doi.org/10.1063/1.123124 9. Korhonen MA, Liu T, Brown DD, Li C-Y (1995) Stress-voiding and electromigration in multilevel interconnects. Mater Res Soc Symp Proc 391:411–422. https://doi.org/10.1557/PROC391-411 10. Park Y-J, Andleigh VK, Thompson CV (1999) Simulations of stress evolution and the current density scaling of electromigration induced failure times in pure and alloyed interconnects. J Appl Phys 85:3546–3555. https://doi.org/10.1063/1.369714 11. Kao H-K, Cargill GS III, Giuliani F, Hu C-K (2003) Relationship between copper concentration and stress during electromigration in an Al(0.25 at.% Cu) conductor line. J Appl Phys 93:2516– 2527. https://doi.org/10.1063/1.1539282 12. Wang P-C, Cavanagh KT, Gordineer JS, Caprotti NM (2024) Characterization of electromigration-induced short-range stress development in Al(0.25 at. % Cu) conductor line. J Appl Phys 135:025105. https://doi.org/10.1063/5.0178543 13. Korhonen MA, Børgesen P, Tu KN, Li C-Y (1993) Stress evolution due to electromigration in confined metal lines. J Appl Phys 73:3790–3799. https://doi.org/10.1063/1.354073 14. Kao H-K, Cargill GS III, Hu C-K (2001) Electromigration of copper in Al(0.25 at.% Cu) conductor lines. J Appl Phys 89:2588–2597. https://doi.org/10.1063/1.1344917 15. Huntington HB, Grone AR (1961) Current-induced marker motion in gold wires. J Phys Chem Solids 20:76–87. https://doi.org/10.1016/0022-3697(61)90138-X

Part XXXII

Environmental Degradation of Multiple Principal Component Materials

Aloe Saponaria Gel as a Green Corrosion Inhibitor of Carbon Steel in an Acid Medium Flavia A. Schmidt, Alicia E. Ares, and Claudia M. Méndez

Abstract Chemical inhibitors play an important role in protection and mitigation strategies to retard corrosion; however, their use can cause negative effects on the environment. Due to this, the use of plant extracts as corrosión inhibitors has been suggested since they are non-toxic, biodegradable and abundant in nature. Aloe Saponaria gel was used as a green corrosión inhibitor of mild carbon steel in 0.5 M HCl acid medium. The corrosion inhibition performance was investigated by electrochemical impedance and potentiodynamic polarization in the absence and presence of the inhibitor, in different concentrations (10, 20, 30% v/v), at the following temperatures: 298, 308, 315, and 323 K. The trend is observed that the higher the inhibitor concentration, the lower the corrosion rate, this is due to the adsorption of organic matter creating a cover on the surface of the steel. Keywords Impedance · Inhibition · Carbon steel · Aloe Saponaria

Introduction Both H2 SO4 and HCl are used in pickling processes to remove oxides, scale, and organic/inorganic contaminants on the metal surface. In order to reduce the degree of corrosion of the solutions, inhibitors are added to them in small quantities, which F. A. Schmidt · A. E. Ares (B) · C. M. Méndez Programa de Materiales y Fisicoquímica - Facultad de Ciencias Exactas, Químicas y Naturales – FCEQyN, Universidad Nacional de Misiones - UNaM, Félix de Azara 1552 (N3300LQD), Posadas-Misiones, Argentina e-mail: [email protected] C. M. Méndez e-mail: [email protected] A. E. Ares · C. M. Méndez Instituto de Materiales de Misiones - IMAM (Consejo Nacional de Investigaciones Científicas y Técnicas – CONICET, Universidad Nacional de Misiones - UNaM), Félix de Azara 1552. (3300), Posadas-Misiones, Argentina © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_103

1183

1184

F. A. Schmidt et al.

makes them profitable and practical as a protection method [1]. Despite the high degree of inhibition, most inhibitors are not ecological, which is why research has led to finding non-toxic inhibitors. Due to this reason, the use of plant extracts as corrosion inhibitors has been suggested. Most natural inhibitors are non-toxic, biodegradable, and abundant in nature. Until now, extracts from seeds, fruits, leaves, flowers, etc., have already been used [2, 3], and it has been found that they significantly reduce the rate of corrosion. The inhibitory effect is attributed to the adsorption of these organic substances on the metal surface, which blocks the active sites or forms a protective layer [4–6]. Published investigations speak mostly of Aloe Vera gel as a corrosion inhibitor for both zinc [7], stainless steel [8], and mild steel [9], in acid media, indicating that Aloe components such as aloin, aloesin, aloe resin, and aloe emodin, can be adsorbed on the surface of the metals to be protected. Previous works by our group have found that Aloe Saponaria is an effective inhibitor to protect aluminum in an acid medium [10], the leaves of both Aloe Vera and Saponaria contain saponins, aloin, lignin, phenols, flavonoids, anthraquinones, vitamins, and minerals. The epidermis of the leaf of Aloe has a thick cuticle and a central part of greater content consisting of Aloe gel, a majority part is saponin, the same has a great biological activity, is found in greater percentage in Aloe Saponaria at different heights of the leaf. The water content is 90–98%, reaching the highest values where the gel itself is. In the present work, we will study the effect of Aloe Saponaria as an inhibitor of corrosion of mild carbon steel in an acid medium of HCl.

Methodology The gel was carefully removed from the fresh leaves, by filleting the aloe, leaf and sifted into a clear liquid. The gel was diluted with a solution of 0.5 M HCl in concentrations of 10, 20, 30% v/v. Mild carbon steel was used as test material whose composition (% wt) is C-0.10, Si-0.30, Mn-0.5 at 0.6, P-0.025, S-0.0250 at 0.030 and rest is completed with Fe. Samples of 1 cm2 were cut to assemble working electrodes to be used in electrochemical measurements, and samples of 5–6 cm2 for weight loss tests. The samples were roughed with SiC paper with granulometry of 500, 600, 1000, and 1200, washed and ultrasonicated in immersion in distilled water and finally air dried. All experiments were carried out at 298, 308, 315, and 323 K, where at each temperature it was tested in the absence and presence of the inhibitor, with concentrations of 10, 20, 30%v/v of Aloe Saponaria. The electrochemical measurements were performed using a three-electrode electrochemical cell, a Calomel electrode as reference electrode (SCE), a platinum counter electrode, and the mild carbon steel-working electrode. All the potentials mentioned in the work are versus SCE. We worked with a Gamry Reference 600® potentiostat.

Aloe Saponaria Gel as a Green Corrosion Inhibitor of Carbon Steel …

1185

The potentiodynamic polarization curves were obtained after 30 min of being in open circuit, then varying the electrode potential automatically, at a sweep speed of 0.16 mVs−1 , from −0.50 V with respect to the open circuit potential (Eop ) to − 0.60 V vs SCE. The adjustment of the polarization curves was performed using the Gamry Echem data analysis software Analyst™, thus finding the corrosion potentials (Ecorr ), the corrosion current densities (Icorr ), the Tafel slopes (βa, βc), and the polarization resistances (Rp ) of each experience. With these data, the inhibition efficiency was found (ηPOT %), calculated from the values obtained from Icorr with Eq. (1): ηPOT % =

I0corr − Iicorr x100 I0corr

(1)

where I0corr is the corrosion intensity of the mild carbon steel in the absence of the inhibitor, and Iicorr , in the presence of the inhibitor. Electrochemical Impedance Spectroscopy (EIS) measurements were taken between the frequency of 100 kHz–0.10 Hz, using 10 mV (peak to peak) of alternating current, after leaving the metal in the medium in open circuit for 30 min. The resistance to load transfer (RP ) was obtained taking into account where the semicircle cuts the real axis of the Nyquist diagram. The efficiency of the inhibitor is through Eq. (2), ηEIS % =

RiP − R0P x100 RiP

(2)

where R0P is the polarization resistance of the mild carbon steel in the absence of the inhibitor and RiP is the resistance to polarization in the presence of it.

Results and Discussion Mild carbon steel potentiodynamic polarization curves were obtained in 0.5 M HCl solution, in the presence and absence of Aloe saponaria as corrosion inhibitor, at different temperatures, see Fig. 1. The cathodic branch retains practically the same slope, having a pure activation control, they change only slightly, indicating that these extracts adsorb on the steel surface, obstructing active corrosion sites without changing the mechanism of cathodic reactions [11]. Then, in the anodic branch, the anodic current density increases rapidly above −0.45/−0.40 V (called desorption potential, Ed), which can be explained by the desorption of the studied extracts from the mild steel surface, this it begins to become more evident as we increase the temperature [12]. Table 1 shows the electrochemical parameters such as the corrosion potential, Ecorr , and the corrosion current density, icorr , where it is observed that the corrosion

1186

F. A. Schmidt et al.

Fig. 1 Effect of inhibitor concentration on mild carbon steel corrosion in 0.5 M HCl solutions at 298 K (a), 308 K (b), 315 K (c), and 323 K (d), potentiodynamic polarization measurements

density, associated with the corrosion rate, decreases with the increase in inhibitor concentration, obtaining inhibition yields of up to 89.46% at 308 K at the maximum concentration of Aloe Saponaria. The Ecorr values do not present a trend, that is, it cannot be said that as the concentration of inhibitor increases, the Ecorr increases or decreases. In the bibliography, it is mentioned that the minimum difference between Ecorr without inhibitor and with inhibitor must be ± 85 mV to define its nature, anodic or cathodic, since this is not fulfilled we are dealing with a mixed inhibitor [13]. In acidic solution, physical adsorption can take place due to the electrostatic interaction between protonated forms of Schiff bases and (FeCl− )ads species. Coordinate covalent bond formation can take place between the electron pairs of unprotonated N atoms in a heteroaromatic ring, as well as between the free amino group and the metal surface. The chemical adsorption is due to the interaction of its || orbitals, of the components of the Aloe extract, with the metal surface [9]. The pickling process has a short duration, measurements are therefore short, and EIS experiments are particularly suitable when corrosion rates are to be obtained quickly and accurately. Figure 2 shows the Nyquist and Bode diagrams of mild carbon Steel exposed in 0.5 M HCl acid, in the absence and presence of inhibitor. A single time constant is observed in all measurements; this indicates that the corrosion reaction is carried out under control by load transfer. The impedance results

Aloe Saponaria Gel as a Green Corrosion Inhibitor of Carbon Steel …

1187

Table 1 Kinetic parameters obtained from the Tafel curves for aluminum in 0.5 M HCl in the presence and absence of Aloe Saponaria at different concentrations and working temperatures T (K)

Cinh (% v/v)

Ecorr (mV vs SCE)

icorr (uA cm−2 )

βa (mV dec−1 )

−βc (mV dec−1 )

ηP OT %

298

0

−495.14

379.81

110

330

–

10

−540.09

188.56

160

190

50.35

20

−480.01

118.95

220

170

68.68

30

−524.64

113.91

220

190

70.01

0

−489.21

1774.35

160

180

–

10

−443.00

1032.27

140

200

41.82

20

−552.85

278.26

170

190

84.32

308

315

323

30

−510.17

187.03

140

220

89.46

0

−511.65

1142.80

120

230

–

10

−499.32

459.53

160

250

59.79

20

−517.81

402.23

160

240

64.80

30

−503.04

311.05

130

260

72.78

0

−504.34

1544.72

140

225

–

10

−504.72

431.45

180

220

72.07

20

−494.90

386.57

120

240

74.98

30

−523.32

301.71

140

240

80.47

were matched using a simple equivalent circuit, see Fig. 3, all were matched to the same circuit. This circuit consists of the solution resistance (Rs ) between the working and reference electrodes, and a charge transfer resistance (Rct ) in parallel with a single nonideal constant phase element (CPE), this indicates that the inhibition it is associated with a geometric blocking effect that achieves high efficiency [14]. The heterogeneity of the steel surface is observed in the value of the phase coefficient (n). The CPE was calculated mathematically according to Eq. (3) [15, 16]: −n ZCPE = Y−1 0 (iw)

(3)

where Y0 is a proportional factor and n represents the deviation from ideal behavior, can indicate surface roughness or the existence of interfacial phenomena, and the values are between 0 and 1. Equation 4 is used to calculate the capacitance value of the double layer [17]: Cdl = Y0 (Rct )(1−n)/n 1/n

(4)

the calculated capacitance values, which are given in Table 2. The Rct resistance increases as we increase the concentration of the inhibitor; this indicates a greater adsorption of organic molecules on the active sites of the

1188

F. A. Schmidt et al.

-300

-70 -60

2

2.0

-100

-50 -40

1.5

-30 1.0

phase (°)

2

-80 2.5

log |Z| (ohm.cm )

-200 Zimag (ohm.cm )

-90

3.0

0 % v/v fit 10 % v/v fit 20 % v/v fit 30 % v/v fit

-20 -10

0.5

0

0

100

200

0.0 0.1

300

1

10

2

Zreal (ohm.cm )

(a)

1,000

10,000

10 100,000

(b)

-100

2.0

0 % v/v fit 10 % v/v fit 20 % v/v fit 30 % v/v fit

-50

-90 -80 -70

1.5

-60

2

log |Z| (ohm.cm )

2

Zimag (ohm.cm )

100

f (Hz)

-50 1.0

-40 -30

phase (°)

0

-20

0.5

-10 0

0

0.0

0

50

100 2

Zreal (ohm.cm )

(c)

0.1

10 1

10

100

1,000

10,000

100,000

f (Hz)

(d)

Fig. 2 Nyquist and Bode diagrams obtained for a and b at 298 K, c and d at 323 K, the results of EIS of the inhibitory action of Aloe Saponaria on mild carbon steel corrosion in HCl Fig. 3 Equivalent circuit used to adjust the results of EIS of the inhibitory action of Aloe Saponaria on aluminum corrosion in HCl

steel at the metal/solution interface, which is related to the Tafel βc slope, which is maintained quasi constant in value. This formation of a barrier film prevents water molecules from passing to the steel surface [18]. The fact that Cdl decreases may be due to the decrease in the local dielectric constant or to the increase in the thickness of the electrical double layer, which suggests the substitution of H2 O molecules (with a higher dielectric constant) by inhibitory molecules (with a lower dielectric constant) leading to the formation of a thin protective film on the electrode surface [19]. The apparent activation energy for the corrosion of mild carbon steel in acid, in the absence and presence of inhibitor, was determined using the Arrhenius equation, Eq. (5):

Aloe Saponaria Gel as a Green Corrosion Inhibitor of Carbon Steel …

1189

Table 2 Electrochemical parameters obtained from EIS measurements for mild carbon steel in 0.5 M HCl with and without inhibitor T (K) 298

308

315

323

Cinh (%v/v)

RS (Ω cm2 )

Rct (Ω cm2 )

Y0 (μΩ−1 s−1 cm−2 )

n

Cdl (μF cm−2 )

ηE I S %

0

1.97

17.95

180.70

0.85

68.40

–

10

2.65

104.21

51.18

0.83

17.91

82.78

20

3.31

246.63

46.46

0.88

25.66

92.72

30

2.80

273.59

35.72

0.89

20.02

93.44

0

1.59

11.16

300.22

0.85

110.47

-

10

1.84

156.73

77.65

0.87

38.35

92.88

20

1.77

288.42

45.82

0.88

26.05

96.13

30

2.12

182.03

61.17

0.88

32.42

93.87

0

2.03

8.51

376.67

0.86

149.93

-

10

2.12

40.51

114.01

0.83

39.49

79.00

20

2.12

90.63

78.76

0.85

33.44

90.61

30

1.98

86.90

38.63

0.86

16.35

90.21

0

1.60

6.38

402.64

0.87

166.19

–

10

1.59

27.03

268.09

0.79

71.42

76.40

20

1.61

52.74

123.88

0.84

45.43

87.91

30

1.79

83.05

88.95

0.85

36.94

92.32

logicorr =

−Ea + logA 2.303RT

(5)

where icorr is the corrosion density found from potentiodynamic measurements, Ea is the apparent activation energy, T is the absolute temperature, R is the ideal gas constant (8.314 J K−1 mol−1 ), and A is the frequency factor. According to the icorr results, Fig. 4 is obtained, where by regression we obtain a line that will give us information on the corresponding parameters Ea , see Table 3. To calculate the values of enthalpy (∆S∗a ) and activation entropy (∆H∗a ) we use Eq. (6) [ ( )] ( ) kb ∆S∗a ∆H∗a i corr = log + − log T h 2.303R 2.303RT

(6)

where kb is the Boltzmann constant and h is Planck’s constant. The Ea values decrease with the inhibitor content, taking into account that the Ea value without inhibitor was 45.90 kJ mol−1 K−1 . In general, it could then be explained that the decrease in adsorption energy with increasing inhibitor concentration is due to chemisorption processes [20]. It may also be due to the fact that the nature of the adsorption mode changes, from physical adsorption at low temperatures to chemisorption as the temperature increases, Noor et al. suggested that the

1190

F. A. Schmidt et al.

Fig. 4 Arrhenius diagram for the corrosion rate of aluminum in a 0.5 M HCl solution, in the absence and presence of Aloe Saponaria

3.2

0% v/v 10% v/v 20% v/v 30% v/v

log icorr(A.cm-2)

3.0 2.8 2.6 2.4 2.2 2.0

0.0031

0.0032

0.0033

0.0034

1/T (K-1)

Table 3 Thermodynamic activation parameters at different concentrations of Aloe Saponaria Cinh (% v/v)

Ea (kJ mol−1 K−1 )

∆H∗a (kJ mol−1 )

∆S∗a (J mol−1 K−1 )

10

29.01

26.42

−112.16

20

40.91

38.33

−75.94

30

33.79

31.22

−100.29

increase in temperature can produce chemical changes in the inhibitor molecules, increasing the electron density in the adsorption centers of the molecule, which causes an improvement in the efficiency of the inhibition [21, 22]. The positive value in the enthalpy of activation reflects the endothermic nature of the mild carbon steel dissolution process. The entropy values decrease with the increase in inhibitor concentration, indicating that the process becomes more orderly as the inhibitor covers the metal surface, it goes from a disordered process at room temperature to a more orderly one, in addition to the fact that the method of adsorption is quite slow and the rate-determining step is adsorption rather than desorption. Several authors [23, 24] admit that one of the ways in which the organic corrosion inhibitor acts on the metal surface is by adsorption. This phenomenon may be due to the quasi-substitution of the water molecules, H2 O(ads) , found on the material by the organic compounds found in solution, Org(sol) : Org(sol) + xH2 O(ads)← → Org(ads) + xH2 O(sol)

(7)

where x is the ratio of the number of water molecules that are replaced by one inhibitor molecule. More information regarding the interaction between inhibitory molecules with the metal surface can be obtained from the study of adsorption isotherms. The fit of the data to a Langmuir isotherm (8) was tested:

Aloe Saponaria Gel as a Green Corrosion Inhibitor of Carbon Steel …

Langmuirisotherm :

1191

1 Cinh = + Cinh θ Kads

(8)

but when graphed we see that the slopes do not acquire the value of 1, therefore the Villamil isotherm (9) is used, which is a correction of the Langmuir Isotherm: Villamilisotherm :

Cinh x + xCinh = θ Kads

(9)

in the Villamil isotherm the value of “x” is a constant introduced to consider all the factors not taken into account in the derivation of the Langmuir isotherm, this occurs when the slope in the Langmuir equation is not one, it must Therefore, it can be considered that there is an interaction between the species adsorbed on the metal surface [25], adjusting the data obtained from the EIS measurements to this isotherm, Fig. 5 is obtained. The changes in the free energy of standard adsorption have been calculated through Eq. (10): ∆G0ads = −RTln(CH2 O xKads )

(10)

where R is the gas constant, T is the absolute temperature, CH2 O is the concentration of water (1000 gL−1 ) [26], and Kads was found from the fit values of the isotherm of Villamil. The values found for ∆Gads were from −12.42 kJ mol−1 at 298 K, decreasing to −15.19 kJ mol−1 at 323 K. The sign tells us that we are facing a spontaneous phenomenon, the value gives us an idea of the behavior, generally values greater than −20 kJ mol−1 are associated with electrostatic interactions between the metal surface and organic molecules, such as the physical adsorption [27]. 45

Fig. 5 Fit to an isotherm from Villamil

298 K 315 K 323 K

40

Cinh/θ (% v/v)

35 30 25 20 15 10

0

5

10

15

20

25

Cinh (% v/v)

30

35

40

1192

F. A. Schmidt et al.

Conclusions 1. Aloe Saponaria is a good inhibitor for mild carbon steel in 0.5 M HCl solution. Its efficiency remains within acceptable values, being more effective when used at 308 K at 20 and 30% v/v. 2. Aloe Saponaria acts as a mixed inhibitor, although more prone to physical adsorption on mild carbon steel. Furthermore, this behavior can be understood in terms of an inhibition mode resulting from the geometric blocking of the metal surface by the adsorbed inhibitory species. 3. Aloe Saponaria when adsorbed on mild Carbon steel obeys the Villamil adsorption isotherm.

References 1. Keramatinia M, Ramezanzadeh B, Mahdavian M (2019) Green production of bioactive components from herbal origins through one-pot oxidation/polymerization reactions and application as a corrosion inhibitor for mild steel in HCl solution. J Taiwan Inst Chem Eng 105:134–149. https://doi.org/10.1016/j.jtice.2019.10.005 2. Raja PB, Sethuraman MG (2008) Natural products as corrosion inhibitor for metals in corrosive media—a review. Mater Lett 62:113–111. https://doi.org/10.1016/j.matlet.2007.04.079 3. Abdullah Dar M (2011) A review: plant extracts and oils as corrosion inhibitors in aggressive media. Ind Lubr Tribol 63(4):227–233. https://doi.org/10.1108/00368791111140431 4. Abdel-Gaber AM, Abd-El-Nabey BA, Sidahmed IM, El-Zayady AM, Saadawy M (2006) Inhibitive action of some plant extracts on the corrosion of steel in acidic media. Corros Sci 48:2765–2779. https://doi.org/10.1016/j.corsci.2005.09.017 5. Singh A, Ahamad I, Singh VK, Quraishi MH (2010) Inhibition effect of environmentally bening Karanj (Pongamia pinnata) seed extract on corrosion of mild steel in hydrochloric acid solution. J Solid State Electrochem 15:1087–1097. https://doi.org/10.1007/s10008-010-1172-z 6. Anuradhaa K, Vimalab R, Narayanasamyc B, Arockia J, Rajendrand S (2008) Corrosion inhibition of carbon steel in low chloride media by an aqueous extract of Hibiscus rosa-sinensis Linn. Chem Eng Commun 195:352–366. https://doi.org/10.1080/00986440701673283 7. Abiola OK, James AO (2010) The effects of aloe vera extract on corrosion and kinetics of corrosion process of zinc in HCl solution. Corros Sci 52(2):661–664. https://doi.org/10.1016/ j.corsci.2009.10.026 8. Mehdipour M, Ramezanzadeh B, Arman SY (2015) Electrochemical noise investigation of aloe plant extract as green inhibitor on the corrosion of stainless steel in 1 M H2 SO4 . J Ind Eng Chem 21:318–327. https://doi.org/10.1016/j.jiec.2014.02.041 9. Singh AK, Mohapatra S, Pani B (2016) Corrosion inhibition effect of aloe vera gel: gravimetric and electrochemical study. J Ind Eng Chem 33:288–297. https://doi.org/10.1016/j.jiec.2015. 10.014 10. Friedrich MS, Ares AE, Méndez CM (2020) Corrosion inhibition effect of Aloe Saponaria gel on the corrosion resistance of aluminum. In: Tomsett A (ed) Light metals 2020. The minerals, metals & materials society 2020, the minerals, metals & materials series, Pittsburgh. Springer, New York, pp 452–459 11. Ouakki M, Galai M, Benzekri Z, Verma C, Ech-chihbi E, Kaya S, Boukhris S, Ebenso EE, Touhami ME, Cherkaoui M (2021) Insights into corrosion inhibition mechanism of mild steel in 1 M HCl solution by quinoxaline derivatives: electrochemical. SEM/EDAX. UV-visible.

Aloe Saponaria Gel as a Green Corrosion Inhibitor of Carbon Steel …

12.

13.

14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

24. 25.

26. 27.

1193

FT-IR and theoretical approaches. Colloids Surf A Physicochem Eng Asp 611. https://doi.org/ 10.1016/j.colsurfa.2020.125810 Hjouji K, Ech-chihbi E, Atemni I, Ouakki M, Ainane T, Taleb M, Rais Z (2023) Datura stramonium plant seed extracts as a new green corrosion inhibitor for mild steel in 1M HCl solution: experimental and surface characterization studies. Sustain Chem Pharm 34:101170. https://doi.org/10.1016/j.scp.2023.101170 Hukovic-Metikos M, Babik R, Grubac Z (2002) The study of aluminium corrosion in acidic solution with nontoxic inhibitors. J Appl Electrochem 32:35–41. https://doi.org/10.1023/A: 1014265407060 Alvarez PE, Fiori-Bimbi MV, Neske A, Brandán SA, Gervasi CA (2017) Rollinia occidentalis extract as green corrosión inhibitor for carbón steel in HCl solution. J Ind Eng Chem 58:92–99. https://doi.org/10.1016/j.jiec.2017.09.012 Machado Fernandes C, Alvarez LX, dos Santos NE, Maldonado Barrios AC, Ponzio EA (2019) Green synthesis of 1-benzyl-4-phenyl-1H-1,2,3-triazole, its application as corrosion inhibitor for mild steel in acidic medium and new approach of classical electrochemical analyses. Corros Sci 149:185–194. https://doi.org/10.1016/j.corsci.2019.01.019 Benbouguerra K, Chafaa S, Chafai N, Mehri M (2018) Synthesis. spectroscopic characterization and a comparative study of the corrosion inhibitive efficiency of an a: aminophosphonate and Schiff base derivatives: experimental and theoretical investigations. J Mol Struct 1157:165–176. https://doi.org/10.1016/j.molstruc.2017.12.049 Qiang Y, Zhang S, Zhao H, Tan B, Wang L (2019) Enhanced anticorrosion performance of copper by novel N-doped carbon dots. Corros Sci 161. https://doi.org/10.1016/j.corsci.2019. 108193 Zhang HH, Qin CK, Chen Y, Zhang Z (2019) Inhibition behaviour of mild steel by three new benzaldehyde thiosemicarbazone derivatives in 0.5 M H2 SO4 : experimental and computational study. R Soc open sci 6:190192. https://doi.org/10.1098/rsos.190192 Amin MA, El-Rehim SSA, El-Sherbini EEF, Bayoumi RS (2007) The inhibition of low carbon steel corrosion in hydrochloric acid solutions by succinic acid. Part I. Weight loss, polarization, EIS, PZC, EDX and SEM studies, Electrochim Acta 52:3588–3600. https://doi.org/10.1016/j. electacta.2006.10.019 Znini M, Majidi L, Bouyanzer A, Paolini J, Desjobert J-M, Costa J, Hammouti B (2012) Essential oil of Salvia aucheri mesatlantica as a green inhibitor for the corrosion of steel in 0.5 M H2 SO4 . Arab J Chem 5:467–474. https://doi.org/10.1016/j.arabjc.2010.09.017 Noor EA, Al-Moubaraki AH (2008) Thermodynamic study of metal corrosion and inhibitor adsorption processes in mild steel/1-methyl-4[4(-X)-styryl pyridinium iodides/hydrochloric acid systems. Mater Chem Phys 110:145–154. https://doi.org/10.1016/j.matchemphys.2008. 01.028 Soltani N, Tavakkoli N, Khayatkashani M, Jalali MR, Mosavizade A (2012) Green approach to corrosion inhibition of 304 stainless steel in hydrochloric acid solution by the extract of Salvia officinalis leaves. Corros Sci 62:122–135 Beda RHB, Niamien PM, Avo Bilé EB, Trokourey A (2017) Inhibition of aluminium corrosion in 1.0 M HCl by caffeine: experimental and DFT studies. Hindawi Adv Chem 2017:10. https:// doi.org/10.1155/2017/6975248 Morad MS, Sarhan AAO (2008) Application of some ferrocene derivatives in the field of corrosion inhibition. Corros Sci 50:744–753. https://doi.org/10.1016/j.corsci.2007.09.002 Obot IB, Obi-Egbedi NO, Umoren SA, Ebenso EE (2010) Synergistic and antagonistic effects of anions and Ipomoea invulcrata as green corrosion inhibitor for aluminium dissolution in acidic medium. Int J Electrochem Sci 5:994–1007. https://doi.org/10.1016/S1452-3981(23)153 38-7 Bockris JO’M, Yang B (1991) The mechanism of corrosion inhibition of iron in acid solution by acetylenic alcohols. J Electrochem Soc 138:2237–2252. https://doi.org/10.1149/1.2085956 Deng S, Xianghong L (2012) Inhibition by Ginkgo leaves extract of the corrosion of steel in HCl and H2 SO4 solutions. Corros Sci 55:407–415. https://doi.org/10.1016/j.corsci.2011. 11.005

Behavior in Cooling-Induced Oxide Scale Spallation of Original and Modified Cantor’s HEA Alloys Oxidized at High Temperature Nassima Chenikha, Corentin Gay, Pauline Spaeter, Lionel Aranda, and Patrice Berthod

Abstract Cast Cantor’s alloys, and derivatives issued from Mn and Cr Contents modifications and/or MC (TaC and HfC) carbides in situ formation, suffer more or less from oxide spallation at cooling. To investigate the dependence of this phenomenon on the alloy chemical composition and on the single-phased or doublephased state of the alloys, several alloys were first exposed to isothermal oxidation, and second to cooling down to room temperature with mass variation recording. The differences between the isothermal oxidation temperature and the temperature of mass loss start, the sequences of the following steps of spallation and the final spallation-induced mass loss were analyzed as functions of the chemical and microstructural characteristics of the alloys. This evidenced the influences, on oxide spallation at cooling, of the Cr/Mn ratio and of the presence or not of the MC carbides. These observations led to recommendations for thermal cycling conditions in service. Keywords High-entropy alloys · MC carbides · Oxide scale spallation · Manganese · Chromium

Introduction Hot components in aeroengines, power-producing turbines or glass-forming processes are generally made of superalloys. To work with a durability long enough, these alloys are initially designed to be able of outstanding mechanical and chemical resistances at high temperature [1, 2]. These remarkable properties are brought by

N. Chenikha · C. Gay · P. Spaeter · P. Berthod (B) Université de Lorraine, Campus Victor Grignard, 54500 Vandoeuvre-Lès-Nancy, France e-mail: [email protected] L. Aranda · P. Berthod Institut Jean Lamour, 2 Allée André Guinier, Campus ARTEM, 54000 Nancy, France © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_104

1194

Behavior in Cooling-Induced Oxide Scale Spallation of Original …

1195

particular microstructures and chemical compositions. The most common superalloys are based on nickel and/or cobalt, elements which are unfortunately to be considered as critical elements because of their increasing problems of availability and cost [3, 4]. Nowadays, it can be considered as crucial to replace them by other elements, at least for a part of their actual quantities. Fe, and possibly Mn, can be candidates for such partial substitution. Such modification of the chemical compositions of (Ni, Co)-based superalloys may lead to new composition in which a series of elements— Ni, Co, Fe, Mn, and Cr for the chromia-forming superalloys [2, 5]—cohabit with contents not far from one another. Such new alloys can be then considered as MultiPrincipal Elements Alloys (MPEAs) [6], and even as High-Entropy Alloys (HEAs) [7] in case of good respect of the corresponding criteria by the obtained compositions. Further, targeting equivalent molar contents between Co, Ni, Fe, Mn, and Cr ought to lead to alloys looking as the Cantor’s alloys [8]. These equimolar (or close to equimolar) alloys, which are among the best known HEAs, are able of high levels of mechanical properties at various temperatures, from moderately high, down to the cryogenic ones. However, for the high temperatures of usual work for superalloys (more than 1000 °C), Cantor’s alloys risk to be mechanically too weak, and they need strengthening solutions. Combining a Cantor-type matrix and script-like interdendritic eutectic MC carbides is a way which recently started to be investigated [9, 10]. First results obtained in creep at high temperatures demonstrated that these equimolar CoNiFeMnCr alloys strengthened by either TaC or HfC carbides are able to deform slowly [11], much slower than the original not modified equimolar alloy. In the high temperature oxidation field, their resistance to oxidation in air at temperatures ranging over [1000, 1100 °C] is much too low [12]: too fast isothermal oxidation, and severe oxide scale spallation when temperature decreases. Concerning the too high isothermal oxidation rate, the deleterious influence of Mn was identified. But another responsible element was chromium, since the content in this element known to improve oxidation resistance was too low because of the equimolarity condition (≤20 wt.%Cr). Decreasing the Mn content and increasing the Cr one are possible very efficient solutions to significantly improve the oxidation behavior at high temperature for these alloys. In this work, new versions with a Mn content equal to only half the one of the initial value, and with a Cr content increased by 50%, were elaborated and tested in oxidation at 1000 and 1100 °C. In this paper, attention is focused on the effects of these Mn and Cr content changes on the behavior in scale spallation of the external oxides during the post-isothermal oxidation cooling, while the effects of these changes in Mn and Cr contents on the isothermal oxidation behavior are the purpose of a parallel paper [13].

Experimental Three alloys were synthesized from pure elements (Alfa Aesar, purity > 99.9 wt.%), by high frequency induction melting (CELES furnace) under an inert atmosphere (300 millibars of pure Ar). These alloys, with as targeted compositions

1196

N. Chenikha et al.

CONiFeMn0.5 Cr1.5 , {96 wt.% CoNiFeMn0.5 Cr1.5 , 3.7 wt.%Ta, 0.25 wt.%C} and {96 wt.% CONiFeMn0.5 Cr1.5 , 3.7 wt.%Hf, 0.25 wt.%C}, will be thereafter designed simply by “Mn0.5 Cr1.5 ”, “Mn0.5 Cr1.5 TaC”, and “Mn0.5 Cr1.5 HfC”, respectively. Three ovoid ingots weighing about 40 g were obtained. They were cut using a metallographic saw to obtain parts for the preparation of various samples. {3 mm × 8 mm × 8 mm} parallelepipeds were ground all around using SiC papers (#1200grit) with smoothing of the edges and corners, for the tests of the alloys in hot oxidation. These isothermal oxidation tests were carried out at 1000 and 1100 °C for 50 h, using a SETARAM TGA92 thermo-balance in 1.5L h−1 continuous flow of dry synthetic air (80% N2 –20% O2 ) at 1 atm. The initial heating rate was +20 °C min−1 , and the final cooling rate was −5 °C min−1 . The oxidized samples were embedded in a cold {resin + hardener} mixture and cut into two equal parts. Each half part was embedded a second time, for obtaining cross sections. These ones, as well as the embedded as-cast sample, were ground with SiC papers (up to #1200-grit) and polished (textile disk containing 1 µm-hard alumina particles) until obtaining a mirror-like state. These mounted and ground/polished samples were thereafter examined by electron microscopy (voltage: 15–20 kV), using a JEOL JSM6010LA scanning electron microscope (SEM). Imaging was done using the back scattered electron mode (BSE), and chemical characterization was done using Energy Dispersion Spectrometry (EDS) using the EDS spectrometer attached to the SEM.

Results and Discussion Control of the Chemical Compositions and of the Obtained Microstructures The chemical compositions of the three “Mn0.5 Cr1.5 ”-type samples were measured by full frame EDS analysis (five ×250 areas randomly chosen → average values and standard deviations). The results are displayed in Table 1 (bold characters), in comparison with the measured chemical compositions of the original equimolartype alloys (in italic characters). The weight contents of cobalt, nickel and iron are all close to 20 wt.%. The chromium contents (≈30 wt.%) and the manganese ones (≈10 wt.%) show that the 50% increase in Cr and the 50% decrease in Mn were successfully obtained. The contents in tantalum and in hafnium are a little overestimated. This is a phenomena which is usually encountered when the main parts of these elements are contained in hard carbides (TaC and HfC) which emerge out of the polished surface because of their high level hardness (they are thus more exposed to the electron beam than matrix). The carbon content, which cannot be specified by EDS, was however judged as also successfully obtained, considering the densities of the obtained carbides population. The as-cast microstructures of the Mn0.5 Cr1.5 TaC and Mn0.5 Cr1.5 HfC alloys only are illustrated in Fig. 1. Indeed, the one of the single-phased Mn0.5 Cr1.5 alloy is not interesting (SEM/BSE micrographs

Behavior in Cooling-Induced Oxide Scale Spallation of Original …

1197

uniformly gray). For comparison, the microstructures of the initial equimolar versions [9, 10] (Mn1 Cr1 TaC and Mn1 Cr1 HfC) are also reminded. As for the initial equimolar versions, the new alloys are double-phased: matrix and MC carbides (either TaC or HfC). The MC carbides are seemingly present with a slightly higher density in these new alloys. They are again obviously of a eutectic nature and their script-like shapes are expected to favor interlocking of neighbor dendrites and thus to delay the {steady state to tertiary} creep regime transition. Their creep resistance should be then high, similarly to the original equimolar versions.

Oxidized States of the Alloys At the end of the oxidation tests the oxidized samples were carefully extracted from the support, and carefully handled before observation. Photographs of their main faces were taken by scanning at 1200 dpi using a simple office scanner. The images obtained on the two main faces are showed in Figs. 2 and 3 for the samples oxidized at 1000 °C and at 1100 °C respectively, with an enlarged view of one of the samples, on the right side. With these images one can see that oxide scale spallation occurred in some cases, notably for the samples oxidized at 1100 °C. The cross-sectional views of the oxidized samples (Fig. 4 for 1000 °C and Fig. 5 for 1100 °C) allow seeing that the external oxide scales (mainly made of complex oxide of Mn and Cr) obviously suffered from shear cracks and even ruptures. This is seemingly more severe for the samples oxidized at 1100 °C than for the ones oxidized at 1000 °C.

Oxide Spallation Evidenced on Thermogravimetry Curves The mass variations during the cooling are plotted in Fig. 6 for the Mn0.5 Cr1.5 and Mn1 Cr1 alloys after the isothermal stages at 1000 °C (left) and at 1100 °C (right). Obviously, the Mn0.5 Cr1.5 alloy was less affected by the phenomenon than the Mn1 Cr1 alloy at both temperatures. No mass loss (except the artificial one due to the increase of the Archimede’s thrust) can be evidenced for the Mn0.5 Cr1.5 alloy for 1000 °C while visible mass loss took place bellow 100 °C for the Mn1 Cr1 alloy. For 1100 °C slow irregular mass decrease occurred for this Mn0.5 Cr1.5 alloy (loss of few oxide only), while the Mn1 Cr1 alloy was much more affected (important mass loss below 200 °C). Obviously, the higher the temperature of the isothermal stage, the more severe the mass loss. Analogous comments can be done concerning the two TaC-containing alloys (Fig. 7) and for the HfC-containing ones (Fig. 8). These curves were analyzed in terms of temperature at which mass variation started to be irregular and decreased significantly and of spallation-induced final mass loss values. The results are presented as histograms in Fig. 9 (temperature of spallation start) and in Fig. 10 (total mass loss by spallation). Obviously, the irregular

21.5 ± 0.5

20.0 ± 0.5

20.0 ± 0.1

Mn1 Cr 1

Mn0.5 Cr1.5

20.2 ± 0.6

19.5 ± 0.2

19.9 ± 0.3

19.7 ± 0.4

Mn1 Cr 1 HfC

Mn0.5 Cr1.5 HfC

20.1 ± 0.3

20.1 ± 0.5

20 ± 0.5

19.3 ± 0.2

Mn1Cr1TaC

Mn0.5 Cr1.5 TaC

20.5 ± 0.3

Ni

Co

Alloys ↓

19.1 ± 0.3

18.4 ± 0.4

19.1 ± 0.3

18.6 ± 0.5

19.8 ± 0.2

19.5 ± 0.5

Fe

8.8 ± 0.3

18.2 ± 0.2

8.4 ± 0.2

18.3 ± 0.3

8.3 ± 0.5

19.5 ± 0.5

Mn

27.8 ± 0.7

19.3 ± 0.5

28.5 ± 0.3

19.2 ± 0.3

31.3 ± 0.4

20.5 ± 0.5

Cr

/

/

4.6 ± 0.2

4.5 ± 0.4

/

/

Ta

4.5 ± 0.6

4 ± 1.9

/

/

/

/

Hf

0.25

0.25

0.25

0.25

/

/

C

Table 1 Chemical compositions measured for the three alloys (“Mn0.5 Cr1.5 ”-type; this work); presence of the ones of the original equimolar versions (“Mn1 Cr1 ”type; [9, 10]) for comparison

1198 N. Chenikha et al.

Behavior in Cooling-Induced Oxide Scale Spallation of Original …

1199

Fig. 1 Micrographs illustrating the as-cast microstructures of the previous equimolar versions Mn1 Cr1 TaC (top, left) and Mn1 Cr1 HfC (top right) alloys and of the new Mn0.5 Cr1.5 TaC (bottom, left) and Mn0.5 Cr1.5 HfC (bottom, right) alloys

Fig. 2 Photographs of the two main faces of the samples oxidized at 1000 °C (left: the Mn0.5 Cr1.5 sample, middle: the Mn0.5 Cr1.5 TaC sample, right: the Mn0.5 Cr1.5 HfC sample)

Fig. 3 Photographs of the two main faces of the samples oxidized at 1100 °C (left: the Mn0.5 Cr1.5 sample, middle: the Mn0.5 Cr1.5 TaC sample, right: the Mn0.5 Cr1.5 HfC sample)

1200

N. Chenikha et al.

Fig. 4 Cross-sectional view of the external oxide scales (and of the sub-surfaces indirectly damaged by oxidation) developed during 50 h at 1000 °C for the Mn0.5 Cr1.5 alloy (top), for the Mn0.5 Cr1.5 TaC alloy (center) and the Mn0.5 Cr1.5 HfC alloy (bottom), evidencing the damages having affected the external scales during the post-isothermal stage cooling

mass loss occurred sooner (i.e. at a higher temperature) and the total mass loss due to scale spallation is greater, for the Mn1 Cr1 -type alloys than for the Mn0.5 Cr1.5 -type ones. Among the Mn1 Cr1 -type alloys as well as among the Mn0.5 Cr1.5 -type ones, the presence of TaC or HfC carbides obviously favors scale spallation (starting at higher temperature) and its severity (total mass loss by scale spallation). Thus, the factors that seems enhancing the mass loss during cooling, that is the oxide scale spallation, would be: a higher Mn content and a lower Cr content, the presence of MC carbides, and a higher temperature of the isothermal stage. One can remark that all these factors also favor a higher mass gain after 50h of isothermal oxidation, as this can be reminded by the initial mass gains shown by the ordinate of the first (left) points of the curves plotted in Figs. 6, 7, and 8 i.e. at the start of cooling. So, a severe oxide spallation can be simply due to a higher mass of oxide per surface unit area, favored by high Mn and low Cr contents, by the presence of MC carbides and by a higher temperature of the 50 hours isothermal stage.

Behavior in Cooling-Induced Oxide Scale Spallation of Original …

1201

Fig. 5 Cross-sectional view of the external oxide scales (and of the sub-surfaces indirectly damaged by oxidation) developed during 50 h at 1100 °C for the Mn0.5 Cr1.5 alloy (top), for the Mn0.5 Cr1.5 TaC alloy (center) and the Mn0.5Cr1.5HfC alloy (bottom), evidencing the damages having affected the external scales during the post-isothermal stage cooling Mn0.5Cr1.5 vs. Mn1Cr1 (50h@1000°C)

Scale spallation start

8.E-03 6.E-03 4.E-03

Mn1Cr1 Mn0.5Cr1.5

2.E-03

temperature (°C) 800

600

mass variation (g/cm²)

1.E-02

0.E+00 400

200

0

Fig. 6 Mass variation curves plotted versus temperature for the post-isothermal cooling part for evidencing the start of oxide scale spallation during the cooling, for the Mn0.5 Cr1.5 alloy (left: 1000 °C, right: 1100 °C) in comparison with its previously studied equimolar version (Mn1 Cr1 )

1202

N. Chenikha et al.

Fig. 7 Mass variation curves plotted versus temperature for the post-isothermal cooling part for evidencing the start of oxide scale spallation during the cooling, for the Mn0.5 Cr1.5 TaC alloy (left: 1000 °C, right: 1100 °C) in comparison with its previously studied equimolar version (Mn1 Cr1 TaC)

700 600 500 400 300 200 100 0

Oxide scale spallation during the cooling from 1000°C

MnCr Mn1Cr1…

MnCr TaC Mn0.5Cr1.5…

MnCr HfC

T spallstart (°C)

T spallstart (°C)

Fig. 8 Mass variation curves plotted versus temperature for the post-isothermal cooling part for evidencing the start of oxide scale spallation during the cooling, for the Mn0.5 Cr1.5 HfC alloy (left: 1000 °C, right: 1100 °C) in comparison with its previously studied equimolar version (Mn1 Cr1 HfC) 700 600 500 400 300 200 100 0

Oxide scale spallation during the cooling from 1100°C

MnCr Mn1Cr1…

MnCr TaC

MnCr HfC

Mn0.5Cr1.5…

Fig. 9 Start temperature for oxide scale spallation during the cooling (left: alloys oxidized at 1000 °C, right: alloys oxidized at 1100 °C)

Conclusions In addition to the differences of isothermal high temperature oxidation behavior due to the decrease in Mn and the increase in Cr, the analysis of the cooling parts of the mass gain files allowed here evidencing differences of oxide scale behavior when temperature decrease. The CONiFeMn0.5 Cr1.5 alloys with or without 0.25 wt.% C

Behavior in Cooling-Induced Oxide Scale Spallation of Original … Oxide scale spallation during the cooling from 1000°C 30 20 10 0

40

mass loss due to oxide spallation (mg/cm²)

mass loss due to oxide spallation (mg/cm²)

40

30

1203

Oxide scale spallation during the cooling from 1100°C

20 10 0

MnCr Mn1Cr1…

MnCr TaC Mn0.5Cr1.5…

MnCr HfC

MnCr Mn1Cr1…

MnCr TaC

MnCr HfC

Mn0.5Cr1.5…

Fig. 10 Total mass loss by oxide scale spallation during the cooling (left: alloys oxidized at 1000 °C, right: alloys oxidized at 1100 °C)

and 3.7 wt.% Ta or Hf behave much better than their equimolar versions in terms of oxidation resistance [13] and of scale spallation resistance (this work). Real thermal cycling conditions (e.g. several cycles, and sometimes a great number of cycles, high cooling and re-heating rates) are much more severe than here where only a cooling was applied and that at a particularly low rate (−5 °C min−1 ). So, after these first observations simply made by exploiting the mass variation results during cooling available in the last parts of files obtained with isothermal oxidation tests using thermogravimetry, these are real thermal cycling experiments which are required to explore much farer the behavior of these alloys. These experiments will probably show the same trends as evidenced here but with accelerated degradation of the alloys. The Mn0.5 Cr1.5 -type alloys are expected to resist better than the Mn1 Cr1 -type but one can imagine that protective coatings will be compulsory for keeping benefit from the good creep properties brought by the presence of the TaC or HfC carbides.

References 1. Bradley EF (1988) Superalloys: a technical guide. ASM International, Metals Park (USA) 2. Kofstad P (1988) High temperature corrosion. Elsevier Applied Science, London (U.K.) 3. Tkaczyk AH, Bartl A, Amato A, Lapkovskis V, Petranikova M (2018) Sustainability evaluation of essential critical raw materials: cobalt, niobium, tungsten and rare earth elements. J Phys D: Appl Phys 51:203001 4. Grandell L, Lehtilä A, Kivinen M, Koljonen T, Kihlman S, Lauri LS (2016) Role of critical metals in the future markets of clean energy technologies. Renew Energy 95:53–62 5. Young DJ (2008) High temperature oxidation and corrosion of metals. Elsevier Corrosion Series, Amsterdal (The Netherlands) 6. Senkov ON, Miller JD, Miracle DB, Woodward C (2015) Accelerated exploration of multiprincipal element alloys with solid solution phases. Nat Commun 6:6529. https://doi.org/10. 1038/ncomms7529 7. Ye YF, Wang Q, Lu J, Liu CT, Yang Y (2016) High-entropy alloy: challenges and prospects. Mater Today 19:349–362 8. Cantor B (2021) Multicomponent high-entropy cantor alloys. Prog Mater Sci 120:100754 9. Berthod P (2022) As-cast microstructures of high entropy alloys designed to be TaC–strengthened. J Metallic Mater Res 5:1–10

1204

N. Chenikha et al.

10. Berthod P (2022) As–cast microstructures of HEA designed to be strengthened by HfC. J Eng Sci Innov C Chem Eng Mater Sci Eng 7:305–314 11. Berthod P (2023) Strengthening against creep at elevated temperature of HEA alloys of the CoNiFeMnCr type using MC-Carbides. TMS 2023 152nd annual meeting & exhibition supplemental proceedings, pp 1103–1111. https://doi.org/10.1007/978-3-031-22524-6_102 12. Berthod P (2023) High temperature oxidation of CoNiFeMnCr high entropy alloys reinforced by MC-carbides. TMS 2023 152nd annual meeting & exhibition supplemental proceedings, pp 933–941. https://doi.org/10.1007/978-3-031-22524-6_86 13. Spaeter P, Chenikha N, Gay C, Aranda L (2024) Isothermal high temperature oxidation of Cantor’s–based MC–reinforced HEAs versus their Mn and Cr contents. TMS 2024 153rd annual meeting & exhibition supplemental proceedings

Corrosion Resistance of 316L Stainless Steel in HCL and FeCl3 ThankGod Nwokocha and T. David Burleigh

Abstract Stainless steel containers made from annealed 316L are used for storing radioactive laboratory wastes including disposable gloves, polyvinylchloride (PVC) bags, and paper Kimwipes. Radiolysis of the PVC bags stored in the containers can form several by-products, including HCl acid. The question is whether the HCl acid can significantly attack the stainless steel and reduce the planned lifetime of the containers. This research is aimed at estimating the lifetime of the 316L stainless steel containers when exposed to the vapors of HCl or immersed in varying concentrations of HCl (12 M, 10 M, 1 M, 0.1 M) and 1.5 M FeCl3 ). The test methods included weight loss, thickness loss, potentiodynamic polarization, and electrochemical impedance spectroscopy. The preliminary test results indicate that the “uniform” corrosion occurs in concentrated HCl (12 M), but pitting occurs in FeCl3 . The corrosion rate starts slowly and increases with time in HCl while the opposite happens in FeCl3 . Keywords Corrosion rates · 316L · HCl · Stainless steel · PVC Radiolysis · FeCl3

Introduction Typically, the 316 low carbon austenitic stainless steels are recommended for industrial applications, owing to their high resistance to corrosion attack. This is as a result of the formation of a very thin, invisible, oxide layer that forms on the surface. Stainless 316L is an iron alloy with 18 Wt% Cr, 10 Wt% Ni, and 2 Wt% Mo and minute amounts of other elements. In general, containers made from 316L stainless steel have an excellent mechanical, physical, chemical, and thermal properties in terms of durability, high temperature resistant, low maintainability, corrosion resistivity, etc. but can be susceptible to both uniform and pitting corrosion specifically T. Nwokocha (B) · T. D. Burleigh Materials & Metallurgical Engineering, New Mexico Tech, Socorro, NM 87801, USA e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_105

1205

1206

T. Nwokocha and T. D. Burleigh

when exposed to acidic chloride environments [1]. This has been the motivating factor behind research investigations. Hence, it has raised concerns on their life expectancy. The radiolysis of the waste stored in the containers results in condensation of HCl on the internal walls, and hence corrosion on the wall surface. The formation of the HCl is due to the radiolysis process of the polyvinylchloride (PVC) materials [2]. The wall thickness of the containers is 1/32 inch (0.03 in or 0.8 mm), and they are designed to have a long service life after multiple usage, but this can only be guaranteed by determining the corrosion resistance after constant exposure to HCl. There is not very much published on the corrosion rate of 316L stainless steel in HCl acid. The exception has been on the use of inhibitors to slow the corrosion rate [3]. The primary objective of this research is to determine the expected lifetime of these containers by exposing them to HCl vapor or immersion using the weight loss, potentiodynamic polarization, electrochemical impedance spectroscopy and the Scanning Electron Microscopy. Tests have been carried out using each of these experimental methods. Equations 1 and 2 below give the anodic and cathodic reactions between the 316L steel and the HCl solution. Anode : Fe → Fe2+ + 2e−

(1)

Cathode : 2H+ + 2e− → H2(g)

(2)

As the 316L steel is exposed to the HCl, the iron dissolves from the surface and leaves a layer of Cr2 O3 on the surface which slows the corrosion rate. If the presence of FeCl3 is assumed, then the cathodic reaction will be different and is shown in Eq. 3. Cathode : Fe+3 + e− → Fe+2

(3)

Experimental Procedure Materials Specification The 316L stainless steel sheets 0.79 mm (1/32 in.) thick were cut into samples and were cleaned with reagent alcohol and weighed before testing. The chemical analysis of two different heats of the 316L sheet is given in Table 1.

Corrosion Resistance of 316L Stainless Steel in HCL and FeCl3 Table 1 Compositional analysis of two heats of 316L steel used in this research [4]

1207

Sample ID

TGN8

TGN15

Element

Wt %

Wt %

Silicon

0.350

0.287

Manganese

1.43

1.24

Phosphorus

0.030

0.029

Chromium

17.14

17.00

Molybdenum

1.99

2.06

Nickel

10.16

10.14

Aluminum

0.028

0..001

Cobalt

0.421

0.355

Copper

0.461

0.406

Niobium

0.038

0.042

Vanadium

0.072

0.088

Tungsten

0.076

0.091

Tin

0.008

0.008

Carbon

0.022

0.018

Sulfur

0.005

0.006

Nitrogen

0.043

0.067

Weight Loss Method For the depth versus time analysis, two different corrosion test methods were employed; immersion weight loss and the vapor corrosion test. For the weight loss tests, a 20-mm diameter glass O-ring cylinder was placed at the center of the 51 × 51 × 0.79 mm stainless sheet with an O-ring between the stainless steel and the base of the cylinder. Apiezon L grease was generously applied to the O-ring and the base of the glass cylinder to prevent crevice corrosion. The cylinders were tightly clamped to the steel sheets to prevent leakage of the solutions as shown in Fig. 1. The experimental procedure was carried out using different concentrations of HCl (12 M, 10 M, 1.0 M, 0.1 M) and 1.5 M FeCl3 solutions on separate 316L stainless steel sheet samples. The top of all the glass cylinders were sealed with parafilm wax and placed in the fume hood to avoid escaping fumes. The various solutions were left in contact with the stainless steel and were observed for different periods of 10, 20, and 30 days, respectively. Afterwards, the solutions were poured out, the sheet samples were rinsed with DI water, dried, cleaned with a plastic bristle brush, and the grease was removed with acetone. The samples were weighed after cleaning and some of the samples were imaged on the Scanning Electron Microscope to observe the corroded surfaces. The surface area was 4.5 cm2 , and the weight loss was converted to thickness lost by assuming a uniform dissolution of the disk-shaped area.

1208

T. Nwokocha and T. D. Burleigh

Fig. 1 Experimental set-up for the immersion test weight loss

Vapor Test The HCl vapor tests were started with 0.001, 0.002, 0.003, and 0.004-inch-thick 316L stainless steel foil. The 316L foil was cut into 51 × 51 mm2 , and was sealed to the top of an Erlenmeyer flask that contained 2 mL of concentrated (12 M) HCl. The foil was sealed to the flask using Lexel silicone rubber and a pH paper was placed on top of the 316L stainless steel sheet and on top of the of the pH paper was a clear polycarbonate window as shown in Fig. 2. The assembly was clamped together and was visually inspected frequently. When the stainless steel foil was perforated by corrosion, the pH paper would turn red, and the time was recorded. Fig. 2 Experimental set-up for the HCl vapor corrosion test

Corrosion Resistance of 316L Stainless Steel in HCL and FeCl3

1209

Potentiodynamic Polarization Techniques For the potentiodynamic polarization techniques, the set-up was the same as shown for the Fig. 1 immersion test but in this case, the 316L sheet became the working electrode (WE). The platinum counter electrode (CE) and the Ag/AgCl reference electrode (RE) were inserted from above. This polarization was carried out with a Princeton Applied Research PARSTAT 2263 operating PowerCORR software. The polarization started with a 30 s delay, and then ramped from 0.020 V below the open circuit potential (OCP −0.020 V) to 0.020 V above the open circuit potential (OCP +0.020 V) at a scan rate of 1 mV/sec. The polarization was repeated periodically.

Electrochemical Impedance Spectroscopy The electrochemical impedance spectroscopy had the same experimental set-up as the potentiodynamic polarization technique described above. This experimental process was carried out with the Princeton Applied Research PARSTAT 2263 operating PowerSINE software, starting at 100 kHz and going to 100 MHz with an AC amplitude of 10 mV rms versus the open circuit potential, and with an initial open circuit delay of 30 s.

Scanning Electron Microscopy Some of the samples were imaged on the JEOL JSM-IT 700 h Scanning Electron Microscopy to observe the corroded surfaces. Prior to imaging, the samples were rinsed with DI water, scrubbed with a plastic bristle brush, and then cleaned with reagent alcohol.

Results and Discussion Weight Lost by Immersion The weight loss was converted into thickness lost by assuming that the corrosion was uniform across the 4.5 cm2 surface area. Figures 3 and 4 show some of the test results for the immersion test for 316L sheet plotted against log(time) for the 12 and 3 M HCl. The container thickness is assumed to be 0.7 mm. Extrapolation of the data in Fig. 3 showed that the 316L sheet will be perforated in 105 days or 300 years for 12 M HCL, but a later test in Fig. 4 showed that the sheet will be only half-perforated after 109 days (3 million years). This uncertainty in the corrosion rate for the two

1210

T. Nwokocha and T. D. Burleigh

Fig. 3 Extrapolation of the weight loss shows perforation in 300 years for sample TGN8

Fig. 4 Extrapolation of the weight loss shows only half-perforation in 3 million years for TGN15

different 316L sheets given in Table 1 indicates that additional test methods need to be employed.

Vapor Test The vapor test results are shown in Fig. 5 is plotted on a log-linear graph and it shows that a 0.7 mm thick container of 316L will be perforated in 1012 days, or approximately three billion years, when exposed to concentrated HCl vapor. This is even a much slower rate than the immersion tests shown above, but these 316L stainless steel foils were also from different heats than the 316L sheet samples.

Corrosion Resistance of 316L Stainless Steel in HCL and FeCl3

1211

Fig. 5 Perforation is expected in 3 billion years based on 12 M HCl vapor corrosion of thin foils of 316L

Potentiodynamic Polarization Techniques The potentiodynamic polarization results are shown in Figs. 6 and 7. Figure 6 shows that in 12 M HCl, the corrosion resistance is very high at t = 0 (a very steep slope of V/i). Over the next 24 h, the slope drops continually, indicating that the corrosion rate is increasing rapidly. However, with 1.5 M FeCl3 (see Fig. 7), the opposite is true. The corrosion resistance (a shallow slope of V/i) becomes steeper with time, indicating that the corrosion resistance is increasing (the corrosion rate is decreasing). The cathodic reaction (Eq. 3) consumes the Fe3+ , and so the corrosion rate drops over time as the cathodic reactant, Fe+3 , is used up, causing the OCP to also drop. Fig. 6 Slope V/i decreases over time meaning that the corrosion rate increases over time in the 12 M HCl

1212

T. Nwokocha and T. D. Burleigh

Fig. 7 Slope V/i increases over time, meaning that the corrosion rate decreases over time in the 1.5 M FeCl3

Electrochemical Impedance Spectroscopy Typical electrochemical impedance spectroscopy results are shown in Fig. 8, and the RC model for the system is shown in Fig. 9. The metal oxide film can be modeled as a capacitor C and a resistor Rp. The electrolyte is simply a resistor, Rs (solution resistance). The curve intercept at the right side of the graph is the solution (electrolyte) resistance, Rs. The solution resistance starts at 30 ohms at t = 0 h, and decreases to 2 ohms after 24 h as Fe+2 dissolves into the acid and makes it more conductive. On the left side of the graph is the polarization resistance plus the solution resistance (Rp + Rs). Over the 24 h, the Rp increases from 80 ohms to about 350 ohms, which shows that the total corrosion rate is slowing down over time for the 1 M HCl.

Scanning Electron Microscopy Figures 10 and 11 are SEM images of the surface after the weight loss experiments. Figure 10 is the 316L sheet with “uniform” corrosion (at 80 × magnification) after immersion in 12 M HCl solution. Figure 11 is the 316L sheet with pitting corrosion (at 50 × magnification) after immersion in the 1.5 M FeCl3 solution. The different electrolytes caused different forms of corrosion. The uniform corrosion would preferable because it is predictable. The pitting corrosion is not preferable because a small pit could perforate the wall of the container and allow the contents to leak.

Corrosion Resistance of 316L Stainless Steel in HCL and FeCl3

1213

Fig. 8 EIS of 316L in 1 M HCl solution

Fig. 9 RC model of the film

Uniform Corrosion Versus Pitting and Crevice Corrosion Although predictable uniform corrosion would be preferable, there are other factors at play, as seen from the lack of reproducibility in the above results. In addition, there are conditions that can promote pitting corrosion or crevice corrosion as seen in Figs. 12 and 13 respectively. Figure 12 shows perforation by pitting after 20 days, but we feel this is due to the Fe+3 . The crevice corrosion shown in Fig. 13 was due to inadequate greasing of the O-ring with Apiezon L vacuum grease. However, there might be similar conditions for crevice corrosion inside the stainless steel containers if trash presses against the container sides.

1214

T. Nwokocha and T. D. Burleigh

Fig. 10 “Uniform” corrosion in 12 M HCl after 7 days (TGN50)

Fig. 11 Pitting corrosion in 1.5 M FeCl3 after 7 days (TGN49)

Corrosion Resistance of 316L Stainless Steel in HCL and FeCl3

1215

Fig. 12 Stainless 316L immersed in 1.5 M FeCl3 was perforated after 20 days (TGN21). (Fresh electrolyte was added at 14 days.) Fig. 13 Crevice corrosion under the O-ring in 12 M HCl after 6 days (TGN13) due to inadequate Apiezon L grease on the O-ring

Figures 14 and 15 show the corrosion of a large sheet sample of 316L. Even though the center of the sheet appears to be “uniform” corrosion visually, the SEM image in Fig. 15 shows a very rough surface with the individual metal grains etched out.

1216

T. Nwokocha and T. D. Burleigh

Fig. 14 Pitting corrosion of 316L sheet in 12 M HCl (TGN17) along the edges

Fig. 15 High magnification (800×) of the center area TGN17 12 M HCl. This image shows the individual metal grains and the initiation of pitting

Conclusion These results show that “uniform” corrosion occurs in concentrated 12 M HCl, and that it starts slowly and then accelerates over 24 hours. Pitting corrosion occurs in 1.5 M FeCl3 but the rate decreases over time as the Fe+3 is consumed. These results indicate that the 316L stainless steel containers will last anywhere from 6 days to 3 billion years depending on the presence of FeCl3 , the concentration of the HCL

Corrosion Resistance of 316L Stainless Steel in HCL and FeCl3

1217

and the form of corrosion. Therefore, for an accurate prediction of the lifetime of these containers, we need a better understanding of the parameters that control the corrosion rate. These parameters include the concentration of the HCL released by radiolysis, the effect of the 316L composition, and whether the best graphical fit (to time) is logarithmic, linear or different function. This work is in progress. PVC waste during radiolysis. Once we understand the concentration of the HCl and the presence of FeCl3 , it will be possible to extrapolate from the short-term results to predict a lifetime of hundreds to millions of years.

References 1. Bhadeshia HKDH, Honeycombe RWK (2017) Steels, microstructure and properties, 4th edn. Elsevier, Cambridge, MA 2. Huijing T, Xiuhua Z, Long C, Kang L, Wenxi Z, Bairu X (2019) The self- degradation mechanism of polyvinyl chloride-modified slag/fly ash binder for geothermal wells. Energies 2821. https:// doi.org/10.3390/en12142821 3. Abdallah M, Salem MM, Al Jahdaly BA, Awad MI, Helal E, Fouda AS (2017) Corrosion inhibition of stainless steel type 316L in 1.0 M HCl solution using 1,3-thiazolidin-5-one derivatives. Int J Electrochem Sci 12(2017):4543–4562. https://doi.org/10.20964/2017.05.35 4. Westmoreland Mechanical Testing & Research, Report No. 01-2300002769, 16 Feb 2023

Environmental Degradation of Polymer-Based Composite Materials: Challenges and Mitigation Strategies Kate Mokobia, Eribe M. Jonathan, Glory Oyiborhoro, Muniratu Maliki, and Ikhazuagbe Hilary Ifijen

Abstract Polymer-based composites are crucial in various industries due to their versatility and exceptional properties. However, they face persistent threats from environmental degradation, including UV radiation, moisture, and chemical exposure. This review addresses the challenges posed by such degradation, encompassing reduced performance, safety concerns, maintenance costs, and economic and environmental consequences. To counter these challenges, the review explores mitigation strategies, including protective coatings, formulation enhancements, recycling practices, and innovative materials and technologies. These strategies not only preserve composite integrity but also align with sustainability and circular economy principles, reducing waste and resource consumption. The review also highlights emerging trends and technologies that promise to address environmental degradation and emphasizes the role of circular economy principles and sustainability in shaping the future of polymer-based composites. As industries seek durable and environmentally responsible solutions, this review offers insights into mitigating environmental degradation challenges, ensuring the continued success of polymer-based composite materials.

K. Mokobia Department of Science Laboratory Technology, Delta State Polytechnic, Otefe, Oghara, Delta State, Nigeria E. M. Jonathan Department of Physical Sciences, Benson Idahosa University, PMB 1100, Benin City, Edo State, Nigeria G. Oyiborhoro Delta State College of Health Sciences and Technology Ofuoma, Ughelli, Delta State, Nigeria M. Maliki Department of Chemistry, Edo State University, Uzairue, Edo State, Nigeria I. H. Ifijen (B) Department of Research Outreach, Rubber Research Institute of Nigeria, Benin City, Edo State, Nigeria e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_106

1218

Environmental Degradation of Polymer-Based Composite Materials …

1219

Keywords Polymer-based composites · Environmental degradation · UV radiation · Moisture exposure · Chemical attack · Material degradation

Introduction Polymers, with their diverse molecular structures and remarkable adaptability, form the bedrock of modern materials science and engineering [1–5]. These versatile compounds have revolutionized numerous industries, offering a broad spectrum of applications, from everyday consumer products to high-tech aerospace components [6–10]. Polymers, characterized by their long chains of repeating molecular units, exhibit a wide range of properties that make them indispensable in countless applications [11, 12]. Their low density, high strength-to-weight ratio, flexibility, and corrosion resistance, among other attributes, have positioned polymers at the forefront of material innovation [13–15]. These attributes, coupled with the capacity to customize polymers to precise needs, have led to a diverse range of materials that has been instrumental in the evolution of polymer-based composites [16]. Within this chapter, we delve deeply into the intricate field of polymer science, examining the categorization of polymers, their molecular structures, and the essential determinants influencing their behaviour. An appreciation of the distinctive traits exhibited by different polymer categories, spanning from thermoplastics to thermosetting resins, is imperative for a comprehensive grasp of the complex domain surrounding polymer-based composite materials [17]. Polymer composites, a class of materials consisting of a polymer matrix reinforced with fibers, particles, or other materials, have gained prominence due to their exceptional mechanical properties, versatility, and cost-effectiveness [18]. The interplay between the polymer matrix and reinforcing materials is pivotal in determining the final properties of these composites, making it essential to grasp the fundamentals of polymer behaviour [19, 20]. As we embark on this exploration of polymers, we lay the groundwork for an in-depth examination of the environmental challenges faced by polymer-based composites. These challenges extend from chemical degradation in the face of harsh substances to physical degradation under the influence of factors such as ultraviolet (UV) radiation, heat, and mechanical stresses. This chapter serves as a steppingstone for the broader discussion in subsequent chapters. As we navigate the intricate world of polymers, we will build a strong foundation to better understand how these materials interact with their environment, the vulnerabilities they face, and the strategies available to mitigate environmental degradation. By doing so, we can ensure that the remarkable capabilities of polymerbased composites coexist harmoniously with our planet’s ecological well-being.

1220

K. Mokobia et al.

Polymer-Based Composite Materials Two approaches are usually considered in the design of environmentally degradable polymeric materials in an attempt to reduce the global problem related to inert polymer waste [21]. One is to design polymeric materials with inherent biodegradability, and another is to enhance the biodegradation of recalcitrant petroleumbased polymers by modifying them (e.g., in blends or composites) with degradable components, usually bio-based ones, that can induce degradation by generating free radicals [22]. Examples of biodegradable polymeric materials include starch, chitosan, chitin, cellulose, lignin, polylactic acid (PLA), poly(3-hydroxybutyrate) (PHB), poly(3-hydroxybutirate-3-hydroxyvalerate) (PHBV), poly(butyrate adipateco-terephthalate) (PBAT), poly-"-caprolactone. A clear distinction should be made between bio-based polymers and biodegradable ones, since some biodegradable plastics are made from fossil resources, while some plastics made from biomass are nonbiodegradable. It is also important to consider the specific conditions and the timeframe under which a ‘biodegradable’ polymer actually biodegrades. For example, most packaging materials marked as ‘biodegradable’ completely break down only if composted in industrial units, while they will most probably have limited biodegradation when landfilling. It is more difficult to establish the reasonable period of time in which the changes in the material allow it to be considered biodegradable, since this varies widely depending on the product, application, and environmental conditions. For example, it is desirable for plastic mulch film to completely degrade before the following crop cycle, to avoid soil burial of incompletely degraded plastic fragments [23]. Environmental degradation and the toxicity level of plastic materials are determined based on various standard methods and testing practices [24], as briefly described below. Ultimate biodegradation follows the evolution of CO2 and CH4 when polymeric materials are maintained in microbial conditions. Respirometric test methods were standardized both for aerobic biodegradation in soil burial [25, 26] or in compost [27], and for anaerobic biodegradation under sewage sludge [28] or anaerobic digestion [29]. While these methods are similar in the procedure of measuring the evolving CO2 and CH4 , they differ in testing conditions, substrate composition, and type of microbial inoculums used for tests. Ecotoxicity determines the potential environmental toxicity of all products (e.g., volatile gases, leachate, residue) resulting from the biodegradation or composting processes. The large macromolecular backbone of polymers is virtually harmless, being not directly available to living cells; however, low-molecular mass compounds such as additives, degradation products, and intermediates (e.g., oligomers, monomers) or metabolic derivatives, can be harmful to the living organisms in the environment [30, 31].

Environmental Degradation of Polymer-Based Composite Materials …

1221

Changes in properties of the material such as changes of the molecular mass and its distribution (determined by size exclusion chromatography—SEC); structural and compositional changes of chemical species in the material or its degradation products (determined by infrared spectroscopy—IR or nuclear magnetic resonance spectroscopy—NMR); changes in physical and morphology properties, such as surface features, mass loss, glass transition (Tg ), melting temperature (Tm ), crystallinity, thermal behaviours (determined by differential scanning calorimetry—DSC or thermogravimetry—TG thermal analysis methods); or modification in mechanical properties, such as tensile strength or elongation at break, are useful parameters to evaluate the degradability of materials. The above-mentioned analysis and characterization methods are suitable to evaluate the evolution of degradation; however, they cannot be used for direct quantification of the processes. For example, quantitative studies on the evolution of mass loss can be problematic due to moisture absorption or difficult recovery of disintegrated material.

Environmental Degradation Mechanism of Polymer-Based Composite Materials Environmental degradation of polymer-based composite materials is a complex process influenced by various factors. These materials are commonly used in industries such as aerospace, automotive, construction, and marine due to their lightweight, high strength, and durability [19]. However, their environmental degradation poses significant challenges, and understanding the mechanisms involved is crucial for sustainable material development and usage. Here, we will discuss the mechanisms of environmental degradation in polymer-based composite materials in detail. 1. Mechanical Stress: Mechanical stress is a significant factor contributing to the degradation of composite materials. When these materials are subjected to repeated loading and cyclic stresses, several detrimental effects can occur. Microcracks tend to form within the composite, often at a microscopic scale [32]. These tiny cracks can initiate and propagate, weakening the material’s structural integrity over time. Delamination, the separation of composite layers or plies, is another consequence of cyclic stresses, further compromising the material’s strength and stiffness [32]. Perhaps more importantly, microcracks and delamination provide pathways for environmental agents like moisture and chemicals to infiltrate the material [33]. Once inside, these agents can accelerate degradation processes. Moisture can lead to physical swelling of the polymer matrix, while chemicals can induce chemical degradation, altering the material’s chemical structure and reducing its mechanical properties [33]. Moreover, these defects caused by mechanical stress can exacerbate fatigue and creep, as they serve as stress concentration points and initiation sites for additional cracks [34]. To ensure the long-term performance and durability of composite materials, it’s

1222

K. Mokobia et al.

essential to manage and minimize mechanical stress through proper design, maintenance, and protective measures [34]. This proactive approach helps mitigate the detrimental effects of mechanical stress and ensures the continued reliability of composite materials in a variety of applications. 2. Moisture Ingress: Moisture is one of the most significant environmental factors affecting polymer composites [19]. It can penetrate the material through defects, microcracks, and even diffusion through the polymer matrix. Moisture leads to several degradation mechanisms. Water can break the chemical bonds within the polymer matrix through hydrolysis [19]. This process weakens the material by reducing the polymer’s molecular weight, which ultimately results in decreased mechanical properties [35]. Absorbed moisture can cause the composite to swell, leading to stress concentration at the interface between the polymer matrix and reinforcing fibers [35]. This can lead to delamination and reduced mechanical strength. In a study carried out in 2016, Davies et al. conducted a comprehensive investigation into the effects of seawater aging on composite materials commonly employed in various marine structures, ranging from boats to tidal turbines [36]. Their findings hold significant implications for marine engineers, researchers, and industry practitioners, offering crucial insights into material behaviours in aquatic environments. A recurring theme throughout the research underscores the utmost importance of considering environmental degradation, particularly in the context of multiscale modelling of composite materials. Given the prolonged exposure of these materials to seawater in marine applications, understanding their evolution over time becomes imperative. One key finding revolves around the evolution of testing methodologies. Traditionally, material aging assessment involved subjecting samples to varying durations of seawater immersion, followed by post-immersion tests. However, this study advocates for a more advanced approach, emphasizing the shift towards methodologies that consider the intricate interplay between water diffusion and mechanical loading, providing a more accurate estimation of long-term material behaviours. Figure 1 illustrates the aging of unreinforced acrylic matrix resin. Figure 1a showcases weight gain plots, suggesting Fickian behavior with a saturation moisture content of approximately 1.8%. Remarkably, the study reveals that saturation occurred for 2.7 mm thick unreinforced resin samples at all tested temperatures after about two months of immersion. Figure 2b demonstrates that while there was a slight decrease in modulus and strength after one year in seawater at 60 °C, both properties were recovered after drying at the same temperature, indicating reversible plasticization. Another critical insight pertains to the need for accelerated testing protocols. Given the extended service life expected of materials in marine environments, these accelerated protocols become essential for obtaining practical data within reasonable timeframes. The study underscores the necessity of a comprehensive understanding of degradation mechanisms. This involves collecting both physico-chemical and mechanical test data to depict material behaviours comprehensively over time, aiding informed material selection and design decisions for marine structures. The research also highlights transformative advancements in

Environmental Degradation of Polymer-Based Composite Materials …

1223

Fig. 1 Ageing of unreinforced acrylic matrix resin. a Weight gains after immersion in seawater at different temperatures and b matrix resin tensile strength after ageing, in the wet and dry state [36]

composite materials used in marine engineering. Notable innovations include lowstyrene emission resins, vacuum resin infusion processes, and stitched fabrics, which have elevated composite quality and improved working conditions. Additionally, the study emphasizes the growing importance of life-cycle analysis during marine structure design. This analysis encompasses considerations of energy consumption during manufacturing and environmental implications during end-of-life disposal, significantly impacting the overall sustainability of marine composites. Strategies to reduce the environmental impact of marine composites are explored, including substituting petrochemical-based thermosetting polyester with recyclable thermoplastics and biosourced thermoplastics like polylactic acid. The introduction of the EliumTM range of acrylic resins is particularly promising. The study also delves into utilizing natural fibers as composite reinforcements, citing their environmental advantages. However, it acknowledges the challenge of natural fibers’ water absorption and the importance of controlling water exposure, as demonstrated in Fig. 2a. In conclusion, this study challenges traditional laboratory aging approaches and suggests that actual material durability in seawater may surpass initial estimates. These findings foster optimism for the adoption of advanced composite materials in marine structures, potentially revolutionizing the field (see Figs. 1 and 2 for visual representations of key findings). 3. UV Radiation: UV Radiation: Ultraviolet (UV) radiation from sunlight is a significant environmental factor that can cause the degradation of polymer composites. This form of degradation primarily affects the material’s surface and can lead to a range of adverse effects [37]. One of the fundamental mechanisms underlying UV degradation is the breaking of chemical bonds within the polymer chains. UV rays possess sufficient energy to cleave the polymer’s backbone bonds, resulting in a reduction in molecular weight [38]. This molecular degradation weakens the material, making it more vulnerable to mechanical stress, and consequently, reducing its overall mechanical properties. Furthermore, the surface of the polymer composite is particularly susceptible to UVinduced chemical reactions. These reactions give rise to the formation of chemical species, such as free radicals, which can further react with oxygen from the atmosphere. This surface degradation leads to a loss of material integrity, manifested as

1224

K. Mokobia et al.

Fig. 2 Natural fibre composites in marine application. a Weight gain during immersion of natural fibre composites in seawater at 25 °C, and exposure of the same composites to seawater on one face only. b The Gwalaz biocomposite multi-hull [36]

changes in surface morphology and chemistry [37]. Another noticeable effect of UV exposure is discoloration. UV-induced chemical reactions often generate chromophoric groups within the polymer matrix, causing changes in the material’s colour [37]. This discoloration can be problematic for applications where the aesthetic appeal of the material is important, such as outdoor furniture or automotive components. To counteract the damaging effects of UV radiation, various mitigation strategies are employed [38]. One common approach is the use of UV stabilizers, which are chemical additives incorporated into the polymer matrix. These stabilizers function by either absorbing or dissipating UV radiation. They act as sacrificial components, shielding the polymer chains from direct exposure to UV energy. Examples of UV stabilizers include hindered amine light stabilizers (HALS) and ultraviolet absorbers (UVAs) [39]. Another effective method to protect polymer composites from UV damage is the application of UV-resistant coatings. These coatings typically contain UV-blocking pigments or compounds that reflect or absorb UV rays. Additionally, they create a protective barrier over the material’s surface, safeguarding it from environmental factors [39]. Lu et al. (2018) conducted a notable research study with the objective of developing a specialized UV degradation model tailored specifically for polymers and Polymer Matrix Composites (PMCs) [40]. Their primary aim was to gain a comprehensive understanding of the consequences of UV exposure on different surface topographies and to predict the effects of UV damage under varying conditions. To achieve this, the researchers employed a combination of numerical simulations and experimental testing. In the numerical simulations, factors such as UV intensity, exposure time, and surface topography were taken into account. These simulations allowed them to predict how UV damage would affect the local rates of material degradation, particularly on uneven surfaces like sinusoidal epoxy surfaces. The experimental validation of their findings involved exposing neat epoxy specimens to UV radiation in an environment with an elevated temperature of 80 °C for a duration of 1000 h (Fig. 3). The results of these experiments provided crucial insights

Environmental Degradation of Polymer-Based Composite Materials …

1225

Fig. 3 Average weight changes of epoxy polymer composite (a) and PVC (b) samples at 80 °C with and without UV [40]

into the effects of UV exposure on the material. One significant observation from their research was that UV-induced degradation had a pronounced impact on uneven polymer surfaces. It led to a reduction in surface roughness, effectively making the surfaces more planar. Furthermore, the research indicated that the degradation rates were most significant at the tips of the local surface heights. This finding suggested that elevated points on the surface experienced more substantial UV-induced degradation compared to the valleys. In addition to surface effects, the research also examined mass changes in the epoxy-based polymer composite and PVC samples exposed to UV radiation and elevated temperature alone for 1000 h. The results demonstrated that mass losses decelerated with time in both cases. This phenomenon was attributed to reductions in the amounts of available volatiles within the materials as they were exposed to both heat and UV radiation over time. In summary, the study by Lu et al. (2018) provided valuable insights into the complex mechanisms and consequences of UV damage on polymers and Polymer Matrix Composites [40]. This research not only enhanced our understanding of UVinduced degradation but also had practical implications. The findings contribute to the development of more durable and UV-resistant materials, which is essential for various applications where UV exposure is a critical factor. Overall, the study highlighted the significance of considering surface topography and local effects when assessing the impact of UV radiation on polymer composites. 4. Thermal Degradation: Exposure to high temperatures can trigger thermal degradation in polymer composites, impacting both the polymer matrix and reinforcing fibers. This degradation process results in chemical and structural changes, leading to a loss of mechanical strength and stiffness in the composite material [19]. As a consequence, the material becomes more brittle and less capable of withstanding mechanical stresses, potentially causing deformation or failure. Thermal degradation can also result in dimensional instability, which can be problematic in applications requiring precise dimensions [19]. To counteract these effects, it’s important to use high-temperature-resistant materials, select appropriate reinforcing fibers, and employ thermal management techniques to maintain the integrity and performance of polymer composites in elevated-temperature

1226

K. Mokobia et al.

environments [41]. The rate of thermal degradation is influenced by factors like the type of polymer, processing conditions, and temperature. For instance, Ogabi et al. (2021) conducted a comprehensive investigation into the degradation trends of polymeric materials, emphasizing the importance of different procedures to address the presence of various polymeric fractions, such as PET, PP, SBR, ABS, resin, and tire waste [42]. Their research focused on understanding and implementing strategies for degrading, transforming, and ultimately eliminating these polymeric materials from the environment, considering the diverse range of materials involved. A significant portion of their work revolved around thermal pyrolysis, a process where materials are subjected to high temperatures in the absence of oxygen, leading to chemical decomposition. This process was examined in detail, considering factors such as the chemical composition of the materials, the potential reaction mechanisms, the choice of raw materials, and the influence of process temperature on the yields of low, medium, and high boiling products. One key aspect explored in their research was the potential for enhancing the degradation process through the use of catalytic additives. Catalysts play a critical role in improving the efficiency of thermal degradation processes. Ogabi et al. discussed the impact of different catalysts, including ZSM-5 (Zeolite Socony Mobil-5), ZSM-5 with ammonium groups, and ZSM-5 with 10% Ni [42]. These catalysts were found to enhance the efficiency of several heating processes, which can be crucial for achieving desired degradation outcomes. The study also highlighted that the choice of the optimal degradation technique depends on several factors, including the type of polymer being processed and the desired qualities of the final products. Different degradation processes and catalysts can lead to distinct final product compositions and properties. Ultimately, the final products resulting from the degradation of polymeric materials were determined by various factors, including the specific degradation processes employed, the characterization of the materials, and the scale of the reactors utilized. This research provides valuable insights into strategies for effectively managing and reducing the environmental impact of polymeric materials by exploring diverse degradation options and considering the role of catalysts in improving process efficiency. It underscores the importance of tailoring degradation approaches to the unique characteristics of different polymers and the desired outcomes of the degradation process. 5. Chemical Exposure: Exposure to chemicals, including acids, bases, solvents, and pollutants, poses a significant risk to polymer composites [43]. Chemical attack can result in structural alterations to the polymer matrix, leading to a decrease in mechanical properties and heightened vulnerability to other forms of degradation. This degradation is often marked by reduced stiffness, strength, and toughness, making the material more brittle and prone to failure under stress [43]. Furthermore, chemical degradation can set the stage for additional forms of deterioration, such as environmental factors like UV radiation or microbial attacks, compounding the material’s overall degradation [18]. Physically, it can cause visible changes in appearance, including discoloration, surface roughness,

Environmental Degradation of Polymer-Based Composite Materials …

1227

cracks, or pits. In practical terms, chemical degradation can impair the functionality of polymer composites, particularly in applications requiring chemical resistance [18]. To mitigate these effects, careful material selection, protective coatings, and proper handling and storage practices are crucial. Understanding the specific chemical environment and potential risks is essential for ensuring the long-term performance and reliability of polymer composites across diverse applications. For example, Amini et al. (2019) reported a series of experimentalbased investigations to assess the issue [44]. For this purpose, glass fiber/polyester samples were immersed in HCl (10% wt.) at three different temperatures, 25, 50, and 70 °C. The effects on the bending, tensile, and hardness properties, changes in the appearance, and microstructural analyses were evaluated over periods of 1 to 4 weeks of immersion. The results indicated that the bending strength, ultimate tensile strength, Young’s modulus, and hardness of the samples decreased when exposed to longer exposure duration and/or higher temperature. The polyester degradation was demonstrated by increased surface roughness, cracks, and changes in the solution color. In addition, visual inspection of tensile test fracture surfaces and SEM images of the broken sections revealed the drastic corrosion of the fibers and the interface. Finally, atomic absorption spectroscopy (AAS) was carried out, indicating the occurrence of ion exchange reactions. The results revealed that the underlying mechanism affecting the corrosion happens in the interfacial zone of these composites. No significant changes were observed in the appearance of the samples immersed in HCl solution at 25 °C. Only the colour of the sample became brighter (Fig. 4a). However, in the case of the elevated temperatures of 50 and 70 °C, more evident changes in the appearance were detected. As illustrated in Fig. 4b and c, in these cases fibers placed in the longitudinal direction were totally visible when the exposure process was completed. It resulted from the gradual loss of the surface resin and the glass fibers of the outermost mat layers in these exposure conditions. Accordingly, the etching and softening observed on the surfaces could result in destructive impacts on the specimens. This phenomenon was further investigated by inspection of the colour of the exposure solutions. The colour of the acid solutions was changed from colourless to yellow for all three samples, increasing with increasing temperature. This can be a sign of the composite corrosion of the samples immersed at 25, 50, and 70 °C, demonstrating that the destruction of the composite was increased by increasing the acidic solution temperature. This was mainly attributed to the occurrence of the ion exchange process between the liquid solution and the composite surface [44]. 6. Biological Attack: In some specific applications, polymer composites may come into contact with biological agents, including fungi, bacteria, and marine organisms. When these organisms colonize the surface of the composite material, it can result in both physical and chemical degradation [45]. Biological degradation is particularly relevant to biodegradable polymers, as they are designed to break down in the presence of microorganisms. These organisms produce enzymes that can catalyze the degradation of polymer chains, causing the material to lose its

1228

K. Mokobia et al.

Fig. 4 Changes in the surface appearance of the samples with different treating time exposed to HCl (10% wt.) solution at a room temperature, b 50 °C, and c 70 °C [44]

structural integrity [45]. This degradation process can result in reduced mechanical properties and structural failure of the composite. Marine environments, in particular, pose a significant threat to polymer composites due to the abundance of moisture and the presence of aggressive marine organisms [46]. Composite materials used in marine applications, such as boat hulls or offshore structures, may be vulnerable to biofouling, where marine organisms attach and grow on the surface, leading to both physical and chemical deterioration. To combat biological degradation, various protective coatings and treatments can be applied to polymer composites to prevent or slow down the colonization of microorganisms [46]. Additionally, the choice of composite materials, especially in marine applications, plays a crucial role in determining resistance to biofouling and degradation. In summary, in certain scenarios, polymer composites can be exposed to biological agents that colonize their surface, leading to physical and chemical degradation [47]. This is a significant concern for biodegradable polymers and materials used in marine environments, emphasizing the importance of protective measures and material selection to ensure the longevity and performance of composite structures. Breister et al. (2020) conducted a comprehensive study that employed a multidisciplinary approach to investigate the degradation processes of polymeric materials, with a particular focus on vinyl ester-based polymer composites [47]. One significant aspect of their research involved measuring the reduction

Environmental Degradation of Polymer-Based Composite Materials …

1229

in mechanical properties of the polymer composites, attributed to biologically driven molecular chain breakage of esters. This reduction in mechanical properties is indicative of the degradation process occurring within the materials. In their study, the researchers measured the reduction in mechanical properties of the polymer composites, which was attributed to biologically driven molecular chain breakage of esters. This reduction in mechanical properties is indicative of the degradation process occurring within the materials. To delve deeper into the microbial aspects of polymer composite degradation, the researchers reconstructed 121 microbial genomes to describe the microbial diversity and pathways associated with the degradation of these composites. The research also considered the impact of different environments on polymer composite degradation. Through thermogravimetric analysis (TGA), the researchers assessed the extent of degradation over varying exposure periods and under different conditions. The TGA results showed that exposure to soil solution (S + DI) led to a significant reduction in the onset temperature compared to other conditions, indicating a higher degree of degradation. Furthermore, the research explored the adverse influence of microbial degradation on the mechanical properties of vinyl ester polymer composites (Fig. 5). Surface nanoindentation tests revealed a drastic reduction in modulus and hardness, coupled with an increase in displacement, with increasing exposure time to soil solution (S + DI). In summary, Breister et al. (2020) conducted a comprehensive investigation into the degradation of vinyl ester-based polymer composites, emphasizing the role of microbial communities in driving the degradation process. Their research integrated various analytical techniques and materials characterization to provide valuable insights into the mechanisms and consequences of polymer composite degradation. The study highlights the importance of considering both microbial and chemical factors when assessing the durability and performance of next-generation structural materials in natural environments. 7. Fatigue and Creep: Fatigue and creep are significant mechanical phenomena that can affect the performance and durability of polymer composites [49]. Fatigue: Fatigue occurs when a material experience repeated cyclic loading over time. In the context of polymer composites, cyclic loading can lead to the initiation and propagation of microcracks within the material [49]. These microcracks, often too small to be seen with the naked eye, can gradually grow and coalesce, leading to macroscopic cracks. As a result, the material’s mechanical properties, such as stiffness and strength, are compromised [50]. Fatigue can be especially problematic in applications where the composite is subjected to dynamic or fluctuating loads, such as aircraft components or automotive parts. Creep: Creep is a time-dependent deformation that occurs when a material is subjected to a sustained load over an extended period. In polymer composites, the long-term application of stress can cause the material to slowly deform or flow, even at constant load levels and temperatures [49]. This deformation is often characterized by matrix softening, where the polymer matrix becomes more pliable and

1230

K. Mokobia et al.

Fig. 5 TGA and MALDI-TOF mass spectra of carbon fiber-reinforced vinyl ester composites. a Representative TGA weight loss (%) graphs with temperature for carbon fiber-reinforced vinyl ester composites in soil solution with deionized water (S + DI), b graph of onset decomposition temperature (logarithmic fit) in different environments: autoclaved soil solution with deionized water (= −S + DI + A), soil solution with deionized water (O-S + DI), and autoclaved deionized water (∆-DI + A), measured at different exposure time periods. c MALDI-TOF mass spectra of carbon fiber-reinforced vinyl ester composites in soil solution with deionized water (S + DI) indicating a reduction in average molecular weight with time at 2793, 2364, and 2138 g mol−1 corresponding to weeks 0, 10, and 20 (bottom to top figure) [47]

less resistant to deformation. Creep can lead to dimensional changes, loss of structural integrity, and a decrease in mechanical properties over time. Both fatigue and creep can result in microstructural changes within polymer composites, affecting their overall performance and reliability. These changes may not be immediately apparent but can lead to a reduction in mechanical properties, making the material more susceptible to failure [50]. To mitigate the effects of fatigue and creep, engineers and materials scientists often incorporate design strategies, select appropriate composite materials, and consider factors such as load levels, operating temperatures, and loading frequencies. Additionally, advanced modelling and testing techniques are used to predict and assess the long-term behaviour of polymer composites under cyclic and sustained loading conditions, helping to ensure their durability and safety in various applications. Samareh-Mousavi and Taheri-Behrooz (2020) presented a novel creep-fatigue stiffness degradation model for composite materials (Fig. 1) [48]. This model introduced a nonlinear stress–strain constitutive equation that considered both time and cycles simultaneously. The model consisted of two primary components: (1) A linear

Environmental Degradation of Polymer-Based Composite Materials …

1231

elastic component that degraded with the number of cycles, representing the fatigueinduced degradation. (2) A nonlinear time-dependent component that captured the combined effects of time and cycles on the material’s behaviours, addressing the time-dependent viscoelastic response of composites. To validate the model’s predictions, the researchers compared them to experimental data obtained from literature sources, specifically for short fiber E-glass/polyamide 6,6 and [±45]2s HTA(12K)/ 6376 epoxy composites. Additionally, the study discussed the presentation of creep response data, highlighting the use of isochronous stress–strain curves (Figu). These curves are generated by extracting data points from creep curves at different predetermined times and plotting them on stress–strain diagrams. Isochronous curves offer a composite representation of data extracted from creep curves at various stress levels. The concept of isochronous curves has practical applications in describing the timedependent behaviours of materials, particularly in the context of elevated temperature service, as seen in ASME BPV standards. In summary, Samareh-Mousavi and Taheri-Behrooz’s study (Fig. 6) introduced an innovative model for predicting the behavior of composite materials under creep-fatigue conditions. The model combines the effects of cycles and time on material response and was validated using experimental data. Additionally, the study discussed the use of isochronous stress–strain curves as a valuable tool for analysing time-dependent material behavior, particularly in elevated temperature applications. To mitigate environmental degradation in polymer-based composite materials, various strategies can be employed, including the use of protective coatings, selecting appropriate matrix materials, reinforcing fibers, and additives, and designing structures to minimize stress concentration points. Additionally, regular inspection and maintenance are essential to monitor and manage degradation in real-world applications. Developing more environmentally friendly composite materials with improved resistance to degradation is an ongoing research focus to ensure sustainability in various industries.

Fig. 6 Schematic of creep response for a viscoelastic material a conventional presentation, b isochronous stress/strain curves representation [48]

1232

K. Mokobia et al.

Challenges Environmental degradation of polymer-based composite materials presents several challenges and problems, with economic and environmental consequences that need to be considered: Environmental degradation poses significant challenges to polymerbased composite materials used across various industries. This degradation can result from exposure to a range of environmental factors, including UV radiation, moisture, chemicals, high temperatures, and mechanical stress. The consequences of this degradation include reduced mechanical properties, safety concerns, increased maintenance costs, and negative economic and environmental impacts [20–37]. 1. Reduced Performance: Environmental degradation can lead to a decline in the mechanical properties of composite materials, such as strength, stiffness, and durability. This can compromise their functionality and safety in critical applications. 2. Safety Concerns: In sectors like aerospace, automotive, and construction, the failure of composite materials due to degradation can have severe safety implications, potentially leading to accidents and injuries. 3. Maintenance Costs: Degradation often necessitates frequent maintenance, repair, or even replacement of composite components. These processes can be expensive and time-consuming, increasing operational costs. 4. Economic and Environmental Consequences: Premature degradation can result in increased waste generation, higher resource consumption, and a larger carbon footprint, negatively impacting both the economy and the environment.

Mitigation Strategies To address these challenges, several mitigation strategies can be employed [40–50]: 1. Protective Coatings: Applying protective coatings or barriers can shield composite materials from environmental agents such as UV radiation and chemicals, preserving their integrity. 2. Formulation Enhancements: Adjusting the composition and formulation of composite materials can improve their resistance to environmental factors. This may involve incorporating additives or modifying the matrix material. 3. Recycling and Sustainable Practices: Implementing recycling practices and adopting sustainable manufacturing processes can extend the life of composite materials, reduce waste, and minimize resource consumption. 4. Innovative Materials and Technologies: Exploring novel materials and advanced technologies can lead to the development of composites with enhanced resistance to environmental degradation. This includes the use of biodegradable polymers, smart monitoring systems, and eco-friendly manufacturing methods.

Environmental Degradation of Polymer-Based Composite Materials …

1233

5. Design for Durability: Designing composite products with durability in mind, including considerations for end-of-life recycling or disposal, is crucial for minimizing the environmental impact of degradation. Addressing the challenges of environmental degradation in polymer-based composite materials requires a multifaceted approach. By implementing mitigation strategies that encompass protective coatings, formulation enhancements, recycling, and sustainable practices, industries can ensure the longevity and sustainability of these materials. This proactive approach not only safeguards performance but also aligns with principles of environmental responsibility and resource conservation.

Conclusion Polymer-based composite materials play a pivotal role in a wide range of industries due to their exceptional properties and versatility. However, the environmental degradation of these materials poses significant challenges and concerns. Throughout this minireview, we have explored the various mechanisms of environmental degradation, from UV radiation to chemical exposure, and delved into the real-world implications of such degradation. The challenges presented by environmental degradation are multifaceted, encompassing issues related to reduced performance, safety, maintenance costs, and their broader economic and environmental repercussions. These challenges highlight the pressing need for effective mitigation strategies to ensure the sustainability and longevity of polymer composites. Mitigation strategies discussed herein, including protective coatings, formulation enhancements, recycling practices, and innovative materials, represent promising avenues for addressing these challenges. These strategies not only protect the integrity of composite materials but also align with the principles of sustainability and the circular economy, minimizing waste and resource consumption. Looking ahead, the future of polymer-based composites holds great promise. Emerging technologies and materials, coupled with a strong commitment to sustainability, are poised to revolutionize how we approach environmental degradation challenges. By embracing these advancements and promoting responsible practices, we can navigate the complexities of environmental degradation and continue to harness the remarkable potential of polymer-based composites across diverse industries.

References 1. Ifijen IH, Ikhuoria EU, Omorogbe SO, Otabor GO, Aigbodion AI, Ibrahim SD (2023) A review of P(St-MMA-AA) synthesis via emulsion polymerization, 3D P(St-MMA-AA) photonic crystal fabrication, and photonic application. In: TMS2023 152nd annual meeting & exhibition supplemental proceedings. The minerals, metals & materials series. Springer, Cham. https://doi.org/10.1007/978-3-031-22524-6_30

1234

K. Mokobia et al.

2. Ifijen IH, Ikhuoria EU, Omorogbe SO, Aigbodion AI (2019) Ordered colloidal crystals fabrication and studies on the properties of poly (styrene–butyl acrylate–acrylic acid) and polystyrene latexes. In: Srivatsan T, Gupta M (eds) Nanocomposites VI: nanoscience and nanotechnology in advanced composites. The minerals, metals & materials series. Springer, Cham, pp 155–164. https://doi.org/10.1007/978-3-030-35790-0_11 3. Omorogbe SO, Ikhuoria EU, Ifijen HI, Simo A, Aigbodion AI, Maaza M (2019) Fabrication of monodispersed needle-sized hollow core polystyrene microspheres. Springer Tracts Modern Phys 155–164. https://doi.org/10.1007/978-3-030-05861-6_14 4. Egharevba O, Ong SK, Okieimen FE, Ifijen IH (2023) Exploring the exceptional properties of polypropylene/polystyrene-grafted-natural rubber (NR-g-PS) blends. Chem Africa. https:// doi.org/10.1007/s42250-023-00718-z 5. Ifijen IH, Omonmhenle SI (2023) Polystyrene-based photonic crystals with chemical, thermal, and bio-responsive properties. Biomed Mater Dev. https://doi.org/10.1007/s44174-023-001 00-0 6. Ifijen IH, Jonathan EM, Jacob JN, Nyaknno UU, Archibong UD (2022) Synthesis of polydispersed P(St-MMA-AA) microspheres and fabrication of colloidal crystals with non-compact morphology. Tanzania J Sci 48(1):140–147. https://doi.org/10.4314/tjs.v48i1.13 7. Ifijen HI, Ikhuoria EU, Omorogbe SO (2018) Correlative studies on the fabrication of poly (styrene-methyl-methacrylate-acrylic acid) colloidal crystal films. J Dispers Sci Technol 40(7):1023–1030. https://doi.org/10.1080/01932691.2018.1494605 8. Ifijen HI, Ikhuoria EU (2020) A simple technique for the fabrication of colour tunable P(StBAAA) colloidal crystal microdots on ink-jet paper. Elsevier-Heliyon 6(6):e04196. https://doi. org/10.1016/j.heliyon.2019.e01621 9. Ifijen IH, Maliki M, Ovonramwen OB, Aigbodion AI, Ikhuoria EU (2019) Brilliant coloured monochromatic photonic crystals films generation from poly (styrene-butyl acrylate-acrylic acid) latex. J Appl Sci Environ-Manage 23(9):1661–1664. https://doi.org/10.4314/jasem.v23 i10.7 10. Ifijen IH, Ikhuoria EU (2019) Generation of highly ordered 3D vivid monochromatic coloured photonic crystal films using evaporative induced technique. Tanzania J Sci 45(3):439–449. https://www.ajol.info/index.php/tjs/article/view/191721 11. Ifijen IH, Maliki M, Omorogbe SO, Ibrahim SD (2022) Incorporation of metallic nanoparticles into Alkyd Resin: a review of their coating performance. In: The minerals, metals & materials society (eds) TMS 2022 151st annual meeting & exhibition supplemental proceedings. The minerals, metals & materials series. Springer, Cham, pp 338–349. https://doi.org/10.1007/9783-030-92381-5_31 12. Ifijen IH, Maliki M, Odiachi IJ, Aghedo ON, Ewanole OB (2022) Solvents based alkyd resins and water-soluble alkyd resins: impacts of modification on their coating properties. Chem Afr. https://doi.org/10.1007/s42250-022-00318-3 13. Ifijen IH, Udokpoh NU, Onaiwu GE, Jonathan EM, Ikhuoria EU (2022) Coating properties of alkyd resin, epoxy resins and polyurethane based nanocomposites: a review. Momona Ethiopian J Sci (MEJS) 14(1):1–33. https://doi.org/10.4314/mejs.v14i1.1 14. Otabor GO, Ifijen IH, Mohammed FU, Aigbodion AI, Ikhuoria EU (2019) Alkyd resin from rubber seed oil/linseed oil blend: a comparative study of the blend properties. Heliyon 5(5):e01621. https://doi.org/10.1016/j.heliyon.2019.e01621 15. Ifijen IH, Odi HD, Maliki M, Omorogbe SO, Aigbodion AI, Ikhuoria EU (2020) Correlative studies on the properties of rubber seed and soybean oil based-alkyd resins and their blends. J Coat Technol Res 18:459–467. https://doi.org/10.1007/s11998-020-00416-2 16. Ramesh M, Rajeshkumar L, Sasikala G, Balaji D, Saravanakumar A, Bhuvaneswari V, Bhoopathi R (2022) A critical review on wood-based polymer composites: processing, properties, and prospects. Polymers 14:589. https://doi.org/10.3390/polym14030589 17. Lambert S, Sinclair C, Boxall A (2014) Occurrence, degradation, and effect of polymer-based materials in the environment. In: Whitacre D (ed) Reviews of environmental contamination and toxicology, vol 227. Springer, Cham, pp 1–53. https://doi.org/10.1007/978-3-319-01327-5_1

Environmental Degradation of Polymer-Based Composite Materials …

1235

18. Brebu M (2020) Environmental degradation of plastic composites with natural fillers—a review. Polymers 12:166. https://doi.org/10.3390/polym12010166 19. Barreira-Pinto R, Carneiro R, Miranda M, Guedes RM (2023) Polymer-matrix composites: characterising the impact of environmental factors on their lifetime. Materials 16:3913. https:// doi.org/10.3390/ma16113913 20. Chaurasia A, Sahoo NG, Wang M, He C, Mogal VT (2015) Fundamentals of polymers and polymer composite. In: Nee A (ed) Handbook of manufacturing engineering and technology. Springer, London, pp 1–30. https://doi.org/10.1007/978-1-4471-4670-4_19 21. Idumah CI, Obele CM (2021) Understanding interfacial influence on properties of polymer nanocomposites. Surf Interfaces 22:100879. https://doi.org/10.1016/j.surfin.2020.100879 22. Tokiwa Y, Calabia BP, Ugwu CU, Aiba S (2009) Biodegradability of plastics. Int J Mol Sci 10(9):3722–3742 23. Rocha DB, Rosa DS (2017) Biodegradable composites: properties and uses. In: Thakur VK, Thakur MK, Kessler MR (eds) Handbook of composites from renewable materials*, vol 5, pp 215–250. Scrivener Publishing LLC 24. Steinmetz Z, Wollmann C, Schaefer M, Buchmann C, David J, Tröger J, Muñoz K, Frör O, Schaumann GE (2016) Plastic mulching in agriculture. Trading short-term agronomic benefits for long-term soil degradation? Sci Total Environ 550:690–705 25. Hemjinda S, Krzan A, Chiellini E, Miertus S (2007) EDP environmentally degradable polymeric materials and plastics. Guidelines to standards and testing practices. United nations industrial development organization and the international centre for science and high technology (ICS-UNIDO) 26. Mas-Castellà J, Urmeneta J, Lafuente R, Navarrete A, Guerrero R (1995) Biodegradation of poly-hydroxyalkanoates in anaerobic sediments. Int Biodeterior Biodegrad 35(3–4):155–174 27. Ohtaki A, Sato N, Nakasaki K (1998) Biodegradation of poly-ε-caprolactone under controlled composting conditions. Polym Degrad Stab 61(3):499–505 28. Ohtaki A, Akakura N, Nakasaki K (1998) Effects of temperature and inoculum on the degradability of poly-ε-caprolactone during composting. Polym Degrad Stab 62(2):279–284 29. O’Malley L (2006) Evaluation and modification of the OECD 301F respirometry biodegradation test method with regard to test substance concentration and inoculum. Water Air Soil Pollut 177(1–4):251–265 30. Gartiser S, Wallrabenstein M, Stiene G (1998) Assessment of several test methods for the determination of the anaerobic biodegradability of polymers. J Polym Environ 6(3):159–173 31. Bellia G, Tosin M, Degli-Innocenti F (2000) The test method of composting in vermiculite is unaffected by the priming effect. Polym Degrad Stab 69(1):113–120 32. Koch I, Just G, Brod M, Chen J, Doblies A, Dean A, Gude M, Rolfes R, Hopmann C, Fiedler B (2019) Evaluation and modeling of the fatigue damage behavior of polymer composites at reversed cyclic loading. Materials (Basel) 12(11):1727. https://doi.org/10.3390/ma12111727 33. Beaumont PWR (2020) The structural integrity of composite materials and long-life implementation of composite structures. Appl Compos Mater 27:449–478. https://doi.org/10.1007/ s10443-020-09822-6 34. Gagg CR, Lewis PR (2009) In-service fatigue failure of engineered products and structures— case study review. Eng Fail Anal 16(6):1775–1793. https://doi.org/10.1016/j.engfailanal.2008. 08.008 35. Al-Maharma AY, Al-Huniti N (2019) Critical review of the parameters affecting the effectiveness of moisture absorption treatments used for natural composites. J Compos Sci 3:27. https:// doi.org/10.3390/jcs3010027 36. Davies P (2016) Environmental degradation of composites for marine structures: new materials and new applications. Philos Trans Roy Soc A: Math Phys Eng Sci 374:20150272. https://doi. org/10.1098/rsta.2015.0272 37. Yousif E, Haddad R (2013) Photodegradation and photostabilization of polymers, especially polystyrene: review. Springerplus 2:398. https://doi.org/10.1186/2193-1801-2-398 38. Asmatulu R, Mahmud GA, Hille C, Misak HE (2011) Effects of UV degradation on surface hydrophobicity, crack, and thickness of MWCNT-based nanocomposite coatings. Prog Org Coat 72(3):553–561. https://doi.org/10.1016/j.porgcoat.2011.06.015

1236

K. Mokobia et al.

39. Jacobs JF, Koper GJM, Ursem WNJ (2007) UV protective coatings: a botanical approach. Prog Org Coat 58(2–3):166–171. https://doi.org/10.1016/j.porgcoat.2006.08.023 40. Lu T, Solis-Ramos E, Yi Y, Kumosa M (2018) UV degradation model for polymers and polymer matrix composites. Polym Degrad Stab 154:203–210. https://doi.org/10.1016/j.polymdegrads tab.2018.06.004 41. Gao X, Han T, Tang B, Yi J, Cao M (2022) Reinforced structure effect on thermo-oxidative stability of polymer-matrix composites: 2-D plain woven composites and 2.5-D angle-interlock woven composites. Polymers (Basel) 14(17):3454. https://doi.org/10.3390/polym14173454 42. Ogabi R, Manescau B, Chetehouna K, Gascoin N (2021) A study of thermal degradation and fire behaviour of polymer composites and their gaseous emission assessment. Energies 14:7070. https://doi.org/10.3390/en14217070 43. Chamas A, Moon H, Zheng J, Qiu Y, Tabassum T, Jang JH, Abu-Omar M, Scott SL, Suh S (2020) Degradation rates of plastics in the environment. ACS Sustain Chem Eng 8(9):3494–3511. https://doi.org/10.1021/acssuschemeng.9b06635 44. Amini M, Khavandi A (2019) Degradation of polymer-based composites in corrosive media: experimental attempts towards underlying mechanisms. Mech Time-Depend Mater 23:153– 172. https://doi.org/10.1007/s11043-018-09408-7 45. Silva RRA, Marques CS, Arruda TR, Teixeira SC, de Oliveira TV (2023) Biodegradation of polymers: stages, measurement, standards and prospects. Macromolecules 3:371–399. https:// doi.org/10.3390/macromol3020023 46. Viel T, Manfra L, Zupo V, Libralato G, Cocca M, Costantini M (2023) Biodegradation of plastics induced by marine organisms: future perspectives for bioremediation approaches. Polymers 15:2673. https://doi.org/10.3390/polym15122673 47. Breister AM, Imam MA, Zhou Z et al (2020) Soil microbiomes mediate degradation of vinyl ester-based polymer composites. Commun Mater 1:101. https://doi.org/10.1038/s43246-02000102-1 48. Samareh-Mousavi SS, Taheri-Behrooz F (2020) A novel creep-fatigue stiffness degradation model for composite materials. Compos Struct 237:111955. https://doi.org/10.1016/j.compst ruct.2020.111955 49. Movahedi-Rad AV, Keller T, Vassilopoulos AP (2019) Creep effects on tension-tension fatigue behavior of angle-ply GFRP composite laminates. Int J Fatigue 123:144–156. https://doi.org/ 10.1016/j.ijfatigue.2019.02.010 50. Ulaeto SB, Ravi RP, Udoh II, Mathew GM, Rajan TPD (2023) Polymer-based coating for steel protection, highlighting metal-organic framework as functional actives: a review. Corros Mater Degrad 2023(4):284–316. https://doi.org/10.3390/cmd4020015

Environmental Impact of Multi-component Fiber-Reinforced Composites: Challenges and Green Solutions Glory Oyiborhoro, Bala Anegbe, Ifeanyi J. Odiachi, Best Atoe, and Ikhazuagbe Hilary Ifijen

Abstract Multi-component fiber-reinforced composites are vital in various industries, offering exceptional mechanical properties but also posing significant environmental challenges. This mini-review explores the complex relationship between these composites and the environment. It highlights issues like high carbon footprints, energy-intensive production, greenhouse gas emissions, and resource depletion, exacerbated by landfill disposal. However, the review also presents promising eco-friendly solutions. These include incorporating recycled and bio-based materials, applying design for sustainability principles, and promoting recycling and circular economy models. Life Cycle Assessment (LCA) plays a crucial role, illustrated through real-world case studies that inform sustainable decision-making. Existing environmental regulations guide responsible composite use. The review features case studies of pioneering industries, showcasing the benefits, challenges, and lessons learned from adopting green solutions. Looking ahead, it explores emerging trends and innovations in environmentally friendly composites, identifying research areas to explore. In summary, this mini-review provides a comprehensive view of the intricate connection between multi-component fiber-reinforced composites and environmental responsibility, emphasizing the need for collective commitment to sustainability. G. Oyiborhoro · I. H. Ifijen (B) Department of General Studies, Delta State College of Health Sciences and Technology, Ofuoma-Ughelli, Delta State, Nigeria e-mail: [email protected] B. Anegbe Department of Basic and Industrial Chemistry, Western Delta University, P.M.B. 10, Oghara, Delta State, Nigeria I. J. Odiachi Department of Science Laboratory Technology, Delta State Polytechnic, Ogwashi-Uku, Nigeria B. Atoe Department of Daily Need, Worldwide Healthcare, 100, Textile Mill Road, Benin City, Edo State, Nigeria © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_107

1237

1238

G. Oyiborhoro et al.

Keywords Fiber-reinforced composites · Multi-component · Environmental impact

Introduction Fiber-reinforced composites have become integral materials across diverse industries, ranging from aerospace and automotive to construction and consumer goods [1]. These composite materials, comprised of a matrix reinforced with fibers, offer a unique combination of strength, durability, and lightweight properties, making them indispensable for achieving high-performance and efficiency in engineering applications [2, 3]. However, with the increasing utilization of fiber-reinforced composites, there comes a growing concern about their environmental impact [4]. As these materials have become ubiquitous in modern manufacturing, it is imperative to assess their contribution to environmental challenges such as carbon emissions, energy consumption, and resource depletion [5, 6]. Additionally, the disposal and end-oflife management of these composites present significant challenges, including landfill issues and long-term environmental consequences [6, 7]. This mini-review seeks to delve into the environmental impact of multi-component fiber-reinforced composites and address the associated challenges. Furthermore, it explores green solutions and sustainable practices adopted by industries to mitigate these environmental concerns. The objectives of this review are to shed light on the current state of affairs regarding the environmental impact of these materials, present innovative approaches to minimize their footprint, and inspire further research and sustainable practices in composite manufacturing. Throughout the review, we will discuss Life Cycle Assessments (LCAs), regulations, case studies, and future trends to comprehensively examine this critical subject.

Multi-component Fiber-Reinforced Composites Multi-component fiber-reinforced composites, commonly known as composite materials, belong to a category of materials consisting of two primary elements: a matrix material and reinforcing fibers [8]. These materials are designed to harness the beneficial characteristics of both constituents, leading to a material that demonstrates enhanced mechanical, thermal, and occasionally electrical properties when compared to each component individually [9]. 1. Composition and Structure: Multi-component fiber-reinforced composites consist of a matrix material that provides the bulk of the structure and a reinforcement phase, typically in the form of fibers, which imparts strength and stiffness [10]. The matrix can be composed of various materials, including polymers,

Environmental Impact of Multi-component Fiber-Reinforced …

1239

metals, ceramics, or even other composites. The reinforcing fibers are typically made from materials such as carbon, glass, aramid, or natural fibers like hemp or flax [11]. The combination of these components allows for tailoring the material’s properties to meet specific engineering requirements [11]. 2. Applications Across Industries: These composites have found widespread applications across numerous industries [12]. In aerospace, they are used to construct lightweight yet robust components, such as aircraft fuselages and wings, to improve fuel efficiency and performance [13]. In the automotive sector, composites are employed to reduce vehicle weight, enhance fuel economy, and maintain safety standards [14]. In the construction industry, they contribute to the development of durable and corrosion-resistant infrastructure. Moreover, composites are utilized in sporting goods, renewable energy systems, and even consumer electronics [14]. 3. Environmental Implications: The extensive utilization of multi-component fiberreinforced composites across these industries has raised concerns about their environmental impact [15]. As these materials continue to replace traditional materials like metals and concrete, there is a pressing need to assess their life cycle environmental footprint [15]. The extraction, production, transportation, use, and disposal of composite materials can contribute to issues such as carbon emissions, energy consumption, and resource depletion [16]. Understanding and mitigating these environmental consequences are essential steps towards more sustainable material choices and practices. In the subsequent sections, this mini-review will delve deeper into the environmental challenges posed by multi-component fiber-reinforced composites and explore innovative strategies for addressing these concerns.

Environmental Challenges The pervasive use of multi-component fiber-reinforced composites in various industries has raised significant environmental challenges that warrant attention and sustainable solutions. These challenges encompass a range of issues, including: 1. Carbon Footprint: The production of multi-component fiber-reinforced composites involves energy-intensive processes, from the extraction of raw materials to the manufacturing of composite components [17]. The carbon footprint of composites can be substantial, contributing to greenhouse gas emissions, particularly when traditional energy sources are employed [18]. Reducing this carbon footprint is imperative in the context of global efforts to mitigate climate change. 2. Energy Consumption: The energy-intensive nature of composite manufacturing contributes to high energy consumption [19]. Notably, processes like curing and moulding require elevated temperatures and long processing times, consuming significant energy resources [20]. Minimizing energy consumption in composite production is essential for reducing environmental impact [20].

1240

G. Oyiborhoro et al.

3. Greenhouse Gas Emissions: The energy-intensive processes used in composite manufacturing result in emissions of greenhouse gases, including carbon dioxide (CO2 ) and methane (CH4 ) [21]. These emissions exacerbate climate change and air quality issues [21]. Addressing emissions from composite production and transportation is crucial for achieving sustainability goals. 4. Resource Depletion: The production of composite materials relies on the extraction of raw materials such as petroleum-based resins or carbon fibers [21]. This extraction contributes to resource depletion and can result in habitat destruction and ecosystem disruption [22, 23]. Sustainable sourcing of raw materials and reducing reliance on non-renewable resources are critical steps in addressing this challenge. 5. Landfill Issues: The end-of-life management of multi-component fiberreinforced composites presents a significant challenge. Composite materials are often difficult to recycle, leading to their disposal in landfills [24]. This contributes to waste management challenges and long-term environmental consequences. 6. Toxic Materials: Some composite components, such as resins and additives, may contain toxic materials. The disposal of composite waste containing these substances can pose environmental and health risks [25]. Addressing these environmental challenges requires a holistic approach, encompassing sustainable materials sourcing, energy-efficient manufacturing processes, waste reduction, recycling and disposal strategies, and adherence to environmental regulations and standards. In the subsequent sections, we will delve into green solutions and sustainable practices that offer potential remedies to mitigate these challenges and reduce the environmental impact of multi-component fiber-reinforced composites.

Green Solutions and Sustainable Practices As the environmental challenges associated with multi-component fiber-reinforced composites have gained recognition, industries have been actively exploring green solutions and sustainable practices to mitigate their impact. Several approaches have emerged to address these challenges [3, 26–29]: 1. Recycled and Bio-based Materials: Industries are increasingly turning to recycled and bio-based fibers and resins in composite manufacturing. Recycled carbon fibers and thermoplastic resins, for example, offer a sustainable alternative to virgin materials. Additionally, bio-based fibers derived from renewable sources like plant-based polymers provide an eco-friendly option. These materials reduce the reliance on fossil fuels, lower carbon emissions, and minimize resource depletion.

Environmental Impact of Multi-component Fiber-Reinforced …

1241

2. Design for Sustainability: Adopting a design for sustainability approach is crucial. Engineers and designers are now integrating sustainability considerations into the early stages of product development. This entails optimizing material selection, component design, and manufacturing processes to reduce waste, energy consumption, and environmental impact. 3. Recycling and Circular Economy: Implementing recycling programs for composite waste is gaining traction. Composite components can be disassembled, and recyclable materials can be reclaimed for future use. This circular economy approach promotes resource efficiency and minimizes landfill waste. 4. Reducing Waste and Energy Efficiency: Composite manufacturing processes are being optimized to reduce waste and energy consumption. Innovations such as out-of-autoclave curing and automated manufacturing techniques enhance energy efficiency. Minimizing scrap and improving production yields contribute to sustainability goals. 5. Sustainable Sourcing: Industries are increasingly prioritizing the sustainability of raw material sourcing. Responsible sourcing practices ensure that raw materials, particularly natural fibers and resins, are acquired from suppliers committed to environmentally friendly and ethical practices. Sustainable fibers, often referred to as "Eco-friendly" fibers, align with several criteria outlined in Fig. 1. These criteria include low water and energy consumption, utilization of waste materials and renewable resources, control over chemical consumption, and prevention of soil erosion. These fibers are typically biodegradable and frequently derived from bio-based sources. The growing interest in using sustainable fibers from renewable and biodegradable origins for the production of bio-based and environmentally friendly products has spurred extensive research into their potential use as reinforcement materials for green and potentially sustainable bio-composites. 6. Environmental Certifications: Adherence to environmental certifications and standards, such as ISO 14001, demonstrates a commitment to sustainable practices. These certifications often involve monitoring and reducing environmental impacts at every stage of production. By incorporating these green solutions and sustainable practices into composite manufacturing, industries can significantly reduce the environmental footprint of multi-component fiber-reinforced composites. Furthermore, these initiatives align with global sustainability goals, contribute to a more circular economy, and promote the responsible use of materials and resources. In the subsequent sections, we will delve into specific case studies, Life Cycle Assessments, and regulatory frameworks that exemplify the successful implementation of these sustainability measures within the composite industry.

1242

G. Oyiborhoro et al.

Fig. 1 Criteria for sustainable fibers [2]

Life Cycle Assessment (LCA) Life Cycle Assessment (LCA) is a systematic and comprehensive methodology used to evaluate the environmental impact of a product, process, or service throughout its entire life cycle—from raw material extraction and production to use and disposal or recycling [30]. LCA is a valuable tool for assessing the environmental footprint of multi-component fiber-reinforced composites and other materials [31]. Here’s an overview of LCA and its significance: 1. Concept of LCA: LCA assesses the environmental impacts associated with a product or system by quantifying resource consumption, energy use, emissions, and other environmental indicators at each stage of its life cycle [32]. These stages typically include: – Raw Material Acquisition: This phase involves extracting or harvesting raw materials, such as fibers, resins, and additives. – Manufacturing: During manufacturing, raw materials are processed into composite components using energy and various processes. – Transportation: The transportation of materials and components, whether locally or globally, contributes to the overall environmental impact. – Use Phase: This stage considers the energy consumption and emissions during the product’s use, including any maintenance and repair.

Environmental Impact of Multi-component Fiber-Reinforced …

1243

– End-of-Life: LCA evaluates the disposal methods, recycling, or reuse of the product at the end of its life cycle. 2. Significance of LCA: LCA offers several key benefits [32]: – Holistic Perspective: LCA provides a holistic view of environmental impacts, helping to identify “hotspots” in the life cycle where the most significant impacts occur. – Informed Decision-Making: It enables informed decision-making by comparing alternative materials, designs, and processes to select the most environmentally friendly options. – Continuous Improvement: LCA results can guide manufacturers and industries in making improvements to reduce environmental impacts over time. – Environmental Labelling: LCA findings can be used to inform environmental labelling and certification schemes, helping consumers make sustainable choices. 3. Examples of LCAs on Composites: Several LCAs have been conducted to assess the environmental performance of multi-component fiber-reinforced composites [33]. These studies examine factors such as carbon emissions, energy consumption, and resource use. For instance, an LCA might compare the environmental impact of composites to that of traditional materials like steel or concrete in specific applications like automotive body panels or wind turbine blades [33]. Such comparisons help highlight the advantages and areas where improvements can be made. A comparison of the LCA analysis was performed for PFRCs and glass fibrereinforced composites were made, and the results may be used to rationalize items’ ecological performance by identifying the vital causal elements [34]. Plant fibers can indicate non-sustainable energy utilization for fiber production, weather conditions, as they are excellent environmental indicators [34]. To address this detention, fibers with low manures and high resistance towards local conditions are to be produced. Few research for lightweight materials on the theme of LCA occurred in the late 1990s. Earlier stage research comparing the LCA on automotive door side panels manufactured from hemp fiber and acrylonitrile–butadiene–styrene conveyed that energy needed for the manufacturing of the panel by hemp fiber saves almost 55% when compared with the energy utilization of acrylonitrile. But the problem is the quantity of NOx emission, though not too high for hemp fibers, yet was not up to the mark [35]. Schmehl et al. [36] analysed the results on properties of automobile body components made by hemp and other plant fibers. Shen and Patel [37] conducted LCA studies in order to gain insight into the environmental profiles of PFRCs in comparison with the conventional petro-chemical polymers. It is found that for each stage of the life cycle, including production and waste management, these products show better environmental profiles than their conventional counterparts in terms of non-renewable energy use and GHG emissions. Pandita et al. [38] investigated the jute/glass fiber composites by using LCA in

1244

G. Oyiborhoro et al.

GaBi 4.3 software, steering the focus towards the composite production process. In industrial jute cultivation, high energy consumption is related emphatically to transportation, which is related emphatically with CO2 emissions, and pesticides and fertilizers are required. In 1000 kg of jute fiber production, tentatively 520–1120 kg of CO2 is emitted, whereas about 2400 kg of CO2 is inhaled by the plant to grow, and so a positive adjustment of 1300–1900 kg of CO2 per 1000 kg of jute fiber is established. The positive effect will be 8.7–12.7 GJ/ton, if at all for every 1 GJ of energy, 150 kg of CO2 is released. The energy consumption during the process was presumed to be 30 MJ/kg. The energy utilization for resin infusion or other composite production was supposed to be 10 MJ [39]. 4. Informed Decision-Making: LCA findings are instrumental in guiding decisionmaking processes [40]. For example, if an LCA reveals that a particular composite material has a lower carbon footprint compared to conventional materials, manufacturers can opt for the more sustainable choice [41]. LCA can also assist in optimizing production processes to reduce environmental impacts, such as minimizing waste and energy consumption [42]. In summary, Life Cycle Assessment is a powerful tool for evaluating the environmental impact of multi-component fiber-reinforced composites. By quantifying and analyzing the full life cycle of these materials, LCA informs sustainable decision-making, promotes eco-friendly design choices, and contributes to the overall reduction of environmental burdens associated with composite production and use.

Regulations and Standards The use of multi-component fiber-reinforced composites is subject to various environmental regulations and standards aimed at ensuring the responsible and sustainable production and disposal of these materials. Understanding and complying with these regulations is crucial for manufacturers and industries utilizing composites. Here’s an overview: 1. Environmental Regulations: Many countries have established environmental regulations that impact the production and use of composite materials. These regulations often address emissions, waste disposal, and the use of hazardous materials [43]. For instance: – Emissions Control: Regulations may set limits on emissions of volatile organic compounds (VOCs) and other pollutants during composite manufacturing processes. Manufacturers must implement control measures to meet these standards. – Waste Management: Regulations may govern the disposal of composite waste. Proper disposal practices are required to minimize the environmental impact of composite end-of-life materials.

Environmental Impact of Multi-component Fiber-Reinforced …

1245

– Hazardous Materials: Restrictions may exist on the use of certain hazardous materials in composite production, such as specific resins or additives. Compliance ensures the safety of both workers and the environment. 2. Product-Specific Standards: In addition to general environmental regulations, there are often industry-specific standards that pertain to composite materials. These standards define quality, performance, and safety criteria for composites used in particular applications. For example: – Aerospace Standards: The aerospace industry has stringent standards for composite materials used in aircraft construction. These standards ensure the reliability and safety of aircraft components. – Automotive Standards: Similarly, the automotive industry has standards that dictate the properties and performance of composites in vehicle applications. Compliance is essential to meet safety and performance requirements. 3. Eco-Labels and Certifications: Various eco-labels and certifications are available for composite products. These labels, such as eco-friendly certifications or energy-efficient designations, provide assurance to consumers and businesses that the composites meet specific environmental criteria. Compliance with these certifications can enhance marketability and sustainability credentials.

Implications for Manufacturers Compliance with environmental regulations and standards carries several implications for manufacturers of multi-component fiber-reinforced composites: – Legal Compliance: Non-compliance with environmental regulations can lead to legal consequences, including fines and penalties. Manufacturers must adhere to these regulations to avoid legal issues. – Market Access: Compliance with industry-specific standards is often a requirement to access certain markets or customers. Manufacturers must meet these standards to remain competitive. – Environmental Responsibility: Complying with regulations and standards aligns with environmental responsibility and sustainability goals. It demonstrates a commitment to minimizing the environmental impact of composite production. – Consumer Trust: Meeting eco-labels and certifications can build trust among consumers and businesses, leading to increased market demand for eco-friendly composite products. In summary, manufacturers of multi-component fiber-reinforced composites must navigate a complex landscape of environmental regulations, industry standards, and eco-certifications. Compliance with these measures is not only a legal requirement but also a vital step toward sustainable and responsible composite production.

1246

G. Oyiborhoro et al.

Case Studies Several industries and companies have embarked on initiatives to implement green solutions and reduce the environmental impact of multi-component fiber-reinforced composites. These case studies demonstrate innovative approaches and provide valuable insights into the benefits, challenges, and lessons learned from such initiatives: 1. Aerospace Industry: Prominent aerospace manufacturers have embraced sustainability in composite manufacturing [2]. They allocate resources to research endeavours aimed at creating lightweight, recyclable composites while integrating bio-based resins into their processes. These initiatives result in reduced aircraft weight, decreased fuel consumption, and lower carbon emissions [2]. Despite the challenges of upholding stringent safety standards, the experiences gained underscore the promising prospects of sustainable aviation. In the realm of sustainable fibre-reinforced polymer composite (FRP) composites, mechanical properties assume paramount importance, as they determine the potential applications across various sectors such as automotive, aerospace, household, and sports [2]. Figure 2 provides an overview of key parameters that typically exert an influence on the mechanical properties of FRP composites.

Fig. 2 Influencing factors for mechanical properties of FRP composites [2]

Environmental Impact of Multi-component Fiber-Reinforced …

1247

Fig. 3 Automobile components made of natural fiber composites [44]

2. Automotive Sector: Automotive companies are increasingly using composites to make vehicles more fuel-efficient. For example, BMW’s i3 electric car features a passenger cell made of carbon fiber-reinforced composites, reducing weight and improving energy efficiency [44]. Challenges include high material costs, but the case underscores the automotive industry’s commitment to sustainability. Figure 3 illustrates automotive parts constructed from natural fiber composites [45]. 3. Construction and Infrastructure: The construction sector explores sustainable composites for building applications. Companies like Fibercore Europe manufacture prefabricated bridge decks using composite materials. These decks are lightweight, durable, and require less maintenance. Challenges include initial costs, but the case demonstrates the long-term benefits of reduced maintenance and extended infrastructure lifespan. 4. Recycling Initiatives: Companies like ELG Carbon Fibre specialize in recycling carbon fiber-reinforced composites. They collect composite waste, process it, and produce recycled carbon fiber products. These initiatives reduce landfill waste and promote the circular economy. Challenges involve scaling up recycling processes, but they offer valuable lessons in resource conservation. 5. Bio-based Composites: Companies like FlexForm Technologies produce biobased composites using natural fibers and bio-resins. These composites find applications in automotive interiors and consumer goods. Challenges include sourcing consistent biomaterials, but the case underscores the importance of sustainable sourcing.

1248

G. Oyiborhoro et al.

6. Renewable Energy: Wind turbine manufacturers incorporate composites into blade construction. Vestas, a leading wind turbine manufacturer, designs recyclable blades with composite materials. Challenges involve blade disposal, but the case demonstrates the role of composites in sustainable energy production. Benefits of these initiatives include reduced carbon emissions, improved resource efficiency, and enhanced sustainability credentials. Challenges often revolve around higher initial costs, supply chain complexities, and waste management. Lessons learned emphasize the importance of collaboration, innovation, and a long-term perspective in achieving sustainability goals. These case studies illustrate that industries and companies are actively working toward greener solutions for multi-component fiber-reinforced composites. Their experiences offer valuable insights into the feasibility and potential of sustainable practices, encouraging further innovation and responsible composite manufacturing [3, 23–29].

Future Directions and Research Needs The field of environmentally friendly composites is poised for continued growth and innovation. To drive sustainability in composite materials, it is crucial to focus on future trends, address remaining challenges, and foster collaboration among academia, industry, and policymakers. Here are some key considerations [34–44]: 1. Advanced Materials and Recycling Technologies: Future composites will likely incorporate advanced materials, including bio-based resins, natural fibers, and recycled fibers. Research in material science will continue to develop highperformance, sustainable alternatives. Additionally, recycling technologies for composites will advance, making it easier to recover and reuse composite materials. 2. Circular Economy and Design for Sustainability: The adoption of circular economy principles will become more prevalent. Design for sustainability will play a pivotal role in reducing waste and emissions. Innovations in product design, manufacturing processes, and end-of-life strategies will emphasize resource efficiency and recycling. 3. Multi-Material Composites: Future composites may involve combinations of materials, such as metals, ceramics, and polymers. Research will focus on optimizing these multi-material composites for specific applications while considering environmental impacts. 4. Life Cycle Assessments (LCAs): LCAs will continue to be integral in evaluating the environmental impact of composites. More studies will be conducted to compare different composite materials and manufacturing processes, providing data-driven insights for sustainable decision-making.

Environmental Impact of Multi-component Fiber-Reinforced …

1249

5. Regulatory Frameworks: Policymakers will likely introduce stricter environmental regulations and standards, encouraging industries to adopt greener practices. Collaborations between government bodies and industry stakeholders will help shape effective policies. 6. Education and Training: Academic institutions will play a vital role in educating the next generation of engineers, designers, and researchers in sustainable composite practices. Training programs and research initiatives will focus on eco-conscious composite manufacturing. 7. Waste Management Solutions: Research into waste management and recycling solutions for composite materials will be essential. Innovations in recycling techniques and the development of composite materials with easy-to-recycle properties will be explored. 8. International Collaboration: The global nature of composite manufacturing necessitates international cooperation. Academia, industry, and policymakers from different regions will collaborate on research projects, share best practices, and harmonize standards. 9. Market Demand: Consumer and industrial demand for sustainable products will continue to drive the development of environmentally friendly composites. Market forces will incentivize innovation and the adoption of greener materials. 10. Cost-Efficiency: As sustainable materials and practices become more mainstream, their costs are expected to decrease. Cost-efficiency will be a key factor in the broader adoption of eco-friendly composites.

Conclusion The mini-review has navigated the complex terrain of multi-component fiberreinforced composites, shedding light on their pervasive use in modern industries and the pressing environmental concerns that accompany their widespread adoption. We have unravelled the multifaceted challenges posed by these materials, from their substantial carbon footprint and energy-intensive production processes to the emissions of greenhouse gases and the depletion of vital resources. The looming issue of landfill disposal further underscores the urgency of addressing their environmental impact. However, amid these challenges, we have uncovered a path toward sustainability and responsible manufacturing practices. The exploration of green solutions and sustainable initiatives has revealed promising avenues for mitigating the environmental footprint of multi-component fiber-reinforced composites. The embrace of recycled and bio-based materials, the integration of design for sustainability principles, and the promotion of recycling and circular economy concepts offer a glimmer of hope. Crucially, we have introduced the pivotal role of Life Cycle Assessment (LCA) as a tool for comprehensive environmental evaluation. Through real-world examples, we have demonstrated how LCA findings can illuminate the ecological footprint of these composites, empower informed decision-making, and pave the way for more sustainable choices. The study has also emphasized the significance

1250

G. Oyiborhoro et al.

of existing environmental regulations and standards that cast a guiding light on the responsible use of composite materials. Compliance with these norms is paramount for manufacturers seeking to navigate the evolving landscape of environmental stewardship. Furthermore, we have unveiled inspiring case studies of industries and companies that have championed green solutions, offering valuable insights into the practicality of sustainable practices. These cases illustrate not only the benefits but also the challenges and lessons learned, serving as beacons of inspiration for others embarking on similar journeys. As we cast our gaze into the future, the study has contemplated forthcoming trends and innovations in the realm of environmentally friendly composites. The identification of uncharted research territories underscores the imperative for continued investigation and innovation to overcome the remaining challenges. The mini-review stands as a testament to the intricate interplay between multi-component fiber-reinforced composites and the environment. It calls for a collective commitment to sustainability in both manufacturing and application. By heeding this call and embracing green solutions, we can pave the way for a more environmentally responsible and sustainable future for these essential materials.

References 1. Hegde S, Shenoy BS, Chethan KN (2019) Review on carbon fiber reinforced polymer (CFRP) and their mechanical performance. Mater Today: Proc 19(Part 2):658–662. https://doi.org/10. 1016/j.matpr.2019.07.749 2. Maiti S, Islam MR, Uddin MA, Afroj S, Eichhorn SJ, Karim N (2022) Sustainable fiberreinforced composites: a review. Adv Sustain Syst 6(11):2200258. https://doi.org/10.1002/ adsu.202200258 3. Azman MA, Asyraf MRM, Khalina A, Petr˚u M, Ruzaidi CM, Sapuan SM, Wan Nik WB, Ishak MR, Ilyas RA, Suriani MJ (2021) Natural fiber reinforced composite material for product design: a short review. Polymers (Basel) 13(12):1917. https://doi.org/10.3390/polym13121917 4. Song YS, Youn JR, Gutowski TG (2009) Life cycle energy analysis of fiber-reinforced composites. Compos A Appl Sci Manuf 40(8):1257–1265. https://doi.org/10.1016/j.compositesa.2009. 05.020 5. Miller SA, Srubar WV III, Billington SL, Lepech MD (2015) Integrating durability-based service-life predictions with environmental impact assessments of natural fiber–reinforced composite materials. Resour Conserv Recycl 99:72–83. https://doi.org/10.1016/j.resconrec. 2015.04.004 6. Sbahieh S, Rabie M, Ebead U, Al-Ghamdi SG (2022) The mechanical and environmental performance of fiber-reinforced polymers in concrete structures: opportunities: challenges and future directions. Buildings 12:1417. https://doi.org/10.3390/buildings12091417 7. Feng T, Guo W, Li W, Meng Z, Zhu Y, Zhao F, Liang W (2023) Unveiling sustainable potential: a life cycle assessment of plant–fiber composite microcellular foam molded automotive components. Materials 16:4952. https://doi.org/10.3390/ma16144952 8. Stanciu MD, Teodorescu Draghicescu H, Tamas F, Terciu OM (2020) Mechanical and rheological behaviour of composites reinforced with natural fibres. Polymers (Basel). 12(6):1402. https://doi.org/10.3390/polym12061402 9. Todor MP, Bulei C, Heput T, Kiss I (2018) Research on the development of new composite materials complete/partially biodegradable using natural textile fibers of new vegetable origin and those recovered from textile waste. IOP Conf Ser Mater Sci Eng 294:012021

Environmental Impact of Multi-component Fiber-Reinforced …

1251

10. Boey JY, Lee CK, Tay GS (2022) Factors affecting mechanical properties of reinforced bioplastics: a review. Polymers (Basel) 14(18):3737. https://doi.org/10.3390/polym14183737 11. Bagherpour S (2012) Fibre reinforced polyester composites. In: Polyester. InTech. Retrieved from https://doi.org/10.5772/48697 12. Muhammad A, Rahman MR, Baini R, Bakri MKB (2021) Applications of sustainable polymer composites in automobile and aerospace industry. In: Advances in sustainable polymer composites. Woodhead Publishing Series in Composites Science and Engineering, pp 185–207. https:// doi.org/10.1016/B978-0-12-820338-5.00008-4 13. Siengchin S (2023) A review on lightweight materials for defence applications: present and future developments. Defence Technol 24:1–17. https://doi.org/10.1016/j.dt.2023.02.025 14. Sharma AK, Bhandari R, Aherwar A, Rimašauskien˙e R, Pinca-Bretotean C (2020) A study of advancement in application opportunities of aluminum metal matrix composites. Mater Today: Proc 26(Part 2):2419–2424. https://doi.org/10.1016/j.matpr.2020.02.516 15. Khalid MY, Rashid AA, Arif ZU, Ahmed W, Arshad H, Zaidi AA (2021) Natural fiber reinforced composites: sustainable materials for emerging applications. Results Eng 11:100263. https://doi.org/10.1016/j.rineng.2021.100263 16. Elfaleh I, Abbassi F, Habibi M, Ahmad F, Guedri M, Nasri M, Garnier C (2023) A comprehensive review of natural fibers and their composites: an eco-friendly alternative to conventional materials. Results Eng 19:101271. https://doi.org/10.1016/j.rineng.2023.101271 17. Zhang J, Chevali VS, Wang H, Wang C-H (2020) Current status of carbon fibre and carbon fibre composites recycling. Compos B Eng 193:108053. https://doi.org/10.1016/j.compositesb. 2020.108053 18. Bianchi I, Forcellese A, Simoncini M, Vita A, Delledonne L, Castorani V (2023) Life cycle assessment of carbon ceramic matrix composite brake discs containing reclaimed prepreg scraps. J Clean Prod 413:137537. https://doi.org/10.1016/j.jclepro.2023.137537 19. Collinson MG, Bower MP, Swait TJ, Atkins CP, Hayes SA, Nuhiji B (2022) Novel composite curing methods for sustainable manufacture: a review. Compos Part C: Open Access 9:100293. https://doi.org/10.1016/j.jcomc.2022.100293 20. https://www.epa.gov/ghgemissions/overview-greenhouse-gases 21. Moshood TD, Nawanir G, Mahmud F, Mohamad F, Ahmad MH, AbdulGhani A (2022) Sustainability of biodegradable plastics: new problem or solution to solve the global plastic pollution? Curr Res Green Sustain Chem 5:100273. https://doi.org/10.1016/j.crgsc.2022.100273 22. Hopewell J, Dvorak R, Kosior E (2009) Plastics recycling: challenges and opportunities. Philos Trans Royal Soc B: Biol Sci 364(1526):2115–2126. https://doi.org/10.1098/rstb.2008.0311 23. Kumar R, Verma A, Shome A, Sinha R, Sinha S, Jha PK, Kumar R, Kumar P, Shubham DS et al (2021) Impacts of plastic pollution on ecosystem services, sustainable development goals, and need to focus on circular economy and policy interventions. Sustainability 13:9963. https:// doi.org/10.3390/su13179963 24. Chatziparaskeva G, Papamichael I, Voukkali I, Loizia P, Sourkouni G, Argirusis C, Zorpas AA (2022) End-of-life of composite materials in the framework of the circular economy. Microplastics 1:377–392. https://doi.org/10.3390/microplastics1030028 25. Kehinde O, Ramonu OJ, Babaremu KO, Justin LD (2020) Plastic wastes: Environmental hazard and instrument for wealth creation in Nigeria. Heliyon 6(10):e05131. https://doi.org/10.1016/ j.heliyon.2020.e05131 26. Kamarudin SH, Mohd Basri MS, Rayung M, Abu F, Ahmad S, Norizan MN, Osman S, Sarifuddin N, Desa MSZM, Abdullah UH et al (2022) A review on natural fiber reinforced polymer composites (NFRPC) for sustainable industrial applications. Polymers 14:3698. https://doi.org/ 10.3390/polym14173698 27. Mohammed M, Mohamad Jawad AJ, Mohammed AM, Oleiwi JK, Adam T, Osman AF, Dahham OS, Betar BO, Gopinath SCB, Jaafar M (2023) Challenges and advancement in water absorption of natural fiber-reinforced polymer composites. Polym Testing 124:108083. https:// doi.org/10.1016/j.polymertesting.2023.108083 28. Andrew JJ, Dhakal HN (2022) Sustainable biobased composites for advanced applications: recent trends and future opportunities—a critical review. Compos Part C: Open Access 7:100220. https://doi.org/10.1016/j.jcomc.2021.100220

1252

G. Oyiborhoro et al.

29. Gowda YT, Girijappa T, Rangappa SM, Parameswaranpillai J, Siengchin S (2019) Natural fibers as sustainable and renewable resource for development of eco-friendly composites: a comprehensive review. Front Mater 6:226. https://doi.org/10.3389/fmats.2019.00226 30. Muralikrishna IV, Manickam V (2017) Chapter five - life cycle assessment. In: Environmental management: science and engineering for industry, pp 57–75. https://doi.org/10.1016/B978-012-811989-1.00005-1 31. Curran MA (2016) Life-cycle assessment. In: Encyclopedia of ecology (2nd edn), vol 4. Reference module in earth systems and environmental sciences, pp 359–366. https://doi.org/10.1016/ B978-0-12-409548-9.09700-1 32. Tamoor M, Samak NA, Yang M, Xing J (2022) The cradle-to-cradle life cycle assessment of polyethylene terephthalate: environmental perspective. Molecules 27(5):1599. https://doi.org/ 10.3390/molecules27051599 33. Khasreen MM, Banfill PFG, Menzies GF (2009) Life-cycle assessment and the environmental impact of buildings: a review. Sustainability 1:674–701. https://doi.org/10.3390/su1030674 34. Duigou AL, Davies P, Baley C (2011) Environmental impact analysis of the production of flax fibers to be used as composite material reinforcement. J Biobased Mater Bioenergy 5:153–165 35. Wotzel K, Wirth R, Flake M (1999) Life cycle studies on hemp fiber reinforced components and ABS for automotive parts. Angew Makromol Chem 272:121–127 36. Schmehl M, Mussig J, Schonfeld U et al (2008) Life cycle assessment on a bus body component based on hemp fiber and PTP. J Polym Environ 16:51–60 37. Shen L, Patel MK (2008) Life cycle assessment of polysaccharide materials: a review. J Polym Environ 16:154–167 38. Pandita SD, Yuan X, Manan MA et al (2014) Evaluation of jute/glass hybrid composite sandwich: water resistance, impact properties and life cycle assessment. J Reinf Plast Compos 33:14–25 39. Song YS, Youn JR, Gutowski TG (2009) Life cycle energy analysis of fibre reinforced composites. Compos A Appl Sci Manuf 40:1257–1265 40. Navarro D, Wu J, Lin W et al (2020) Life cycle assessment and leather production. J Leather Sci Eng 2:26. https://doi.org/10.1186/s42825-020-00035-y 41. Banerjee R, Sinha Ray S (2022) Sustainability and life cycle assessment of thermoplastic polymers for packaging: a review on fundamental principles and applications. Macromol Mater Eng. https://doi.org/10.1002/mame.202100794 42. Müller LJ, Kätelhön A, Bachmann M, Zimmermann A, Sternberg A, Bardow A (2020) A guideline for life cycle assessment of carbon capture and utilization. Front Energy Res. https:// doi.org/10.3389/fenrg.2020.00015 43. Sethi S, Ray BC (2015) Environmental effects on fibre reinforced polymeric composites: evolving reasons and remarks on interfacial strength and stability. Adv Coll Interface Sci 217:43–67. https://doi.org/10.1016/j.cis.2014.12.005 44. Holbery J, Houston D (2006) Natural-fiber-reinforced polymer composites in automotive applications. JOM 58(11):80–86 45. Mohammed L, Ansari MNM, Pua G, Jawaid M, Islam MS (2015) A review on natural fiber reinforced polymer composite and its applications. Int J Polym Sci 2015:243947. https://doi. org/10.1155/2015/243947

Investigation of Mechanical Stress and B10 Exposure on FKM Polymer Qi An, Ralph Bäßler, Andreas Hertwig, Heike Strehlau, Gundula Hidde, and Frank Otremba

Abstract Mechanical stress often accelerates the failure of polymer materials. The aim of this research is to study the interaction between the sealing material FKM and biofuels B10 (heating oil with 10% biodiesel). The mechanical stress test was carried out in a special apparatus. Both mechanical and non-mechanical stress tests were conducted on specimens at 20, 40, and 70 °C for 28 days to document changes in mass, volume, and tensile properties. Both increasing temperature and mechanical stress have a significant effect on the tensile strength of the FKM polymer when exposed to B10. The combination of increasing temperature and mechanical stress induced rupture within 2 h. It was also established that FKM polymer with preexposure in B10 survived longer during mechanical stress compared to specimens exposed only to air. With the support of infrared (IR) spectroscopy, we were able to confirm the penetration of B10 into the FKM polymer. Keywords Biofuels · Sealing materials · Mechanical stress · Change in tensile properties

Introduction Biofuels, particularly biodiesel, have gained significant attention as an alternative to traditional fossil fuels in recent years [1]. Biofuels are primarily produced from oilseeds such as rapeseed, palm [2], and soy [3], and is transformed into fatty acid methyl esters (FAME) by transesterification [4]. Unlike diesel, which contains hundreds of compounds [5, 6], biodiesel only contains a few compounds in the C16–C18 carbon chain, depending on the seed or vegetable oil [7]. However, the use of biodiesel in automobile and transportation applications can result in problems of degradation or even damage in materials [8]. Polymers [9], Q. An · R. Bäßler · A. Hertwig · H. Strehlau · G. Hidde · F. Otremba (B) Federal Institute for Materials Research and Testing (BAM), Unter den Eichen 44-46, Berlin, Germany e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_108

1253

1254

Q. An et al.

such as those used in fuel hoses and gaskets, can suffer from mechanical stress [10], high temperature, and chemical exposure, which can speed up material failure[11] and pose potential dangers. Among the commonly used polymer materials, fluorocarbon (FKM) shows excellent performance and high stability and compatibility towards oil, diesel, ethanol, and other chemicals [12, 13]. FKM is a family of fluorocarbon-based fluoroelastomer materials, which provide excellent high temperature and chemical stability compared to other elastomers. As a result, FKM is widely used in chemical processes such as petroleum refining, where it is used for sealings, pumps, and other components [14]. In this work, the physical and chemical behavior of mechanical stressed FKM in 8-year-aged B10 (heating oil with 10% FAME) at 20, 40, and 70 °C was investigated. The aim was to determine the compatibility and stability of FKM under these conditions. Results were compared with none mechanically stressed FKM. By investigating the impact of mechanical stress on FKM, this study provides insights into the long-term performance and durability of FKM in biofuel applications, which are crucial for ensuring the safe and reliable use of such substances in various industries.

Materials and Methods Preparation of Test Specimens Vulcanized rubber plates of fluorocarbon rubber (FKM) were used for the exposure tests. At least six test specimens of each elastomer were cut out of the plates with the following dimensions according to DIN 53504. The physical properties of FKM are specified in Table 1. Total length: 75 mm, Width at the end: 12.5 mm, Length of the narrow parallel part: 25 mm, Width of the narrow parallel part: 4 mm. Table 1 Physical properties of FKM elastomer

Density [g/cm3 ]

1.84 76

Shore A Tensile strength

[N/mm2 ]

12.1

Elongation at break [%]

218

Temperature range [°C]

−15 to 200

Investigation of Mechanical Stress and B10 Exposure on FKM Polymer

1255

Fig. 1 Experimental setup for exposure without mechanical stress

Exposure Tests in B10 Six test specimens of non-mechanically treated sealing material were exposed to 8year-aged B10 at 20, 40, and 70 °C for 28 days in a specimen jar (diameter: 100 mm and height: 200 mm) with a sufficiently tight-fitting lid according to ISO 1817. The test specimens were fully immersed in B10, as shown in Fig. 1. Six test specimens of mechanically treated sealing material were exposed to 8year-aged B10 at 20, 40, and 70 °C for 28 days in a specimen jar (depth: 145 mm, width: 255 mm, and height: 250 mm) with specimens fixed by screws and nuts. A constant mechanical stress of 24.3 newtons was applied by weight discs, as shown in Fig. 2. Six circular test specimens of each sealing material were exposed for 28 days to the biofuel at 20, 40, and 70 °C (see Table 2).

Determination of Change in Mass and Visual Detection The test specimens were weighed before and after exposure to the B10 at standard laboratory temperature of 23 °C and standard laboratory humidity of 50 ± 10%.

1256

Q. An et al.

Fig. 2 Apparatus for mechanical stress experiment Table 2 Specification of biofuel B10

FAME content [%] Density at 15 °C

[kg/m3 ]

10.1 843.8

Initial boiling point [°C]

186

Sulphur content [mg/kg]

8

Water content [mg/kg]

83

Acid number [mg KOH/g]

99.9 wt.%). These syntheses were achieved by high frequency induction melting (CELES furnace) under an inert atmosphere made of 300 millibars of pure argon. Cutting of the obtained 40 g-weighing ovoid-shaped ingots using a metallographic saw allowed obtaining parts for the preparation of various samples. Parallelepipeds with 3 mm × 8

1264

P. Spaeter et al.

mm × 8 mm as approximative dimensions (but carefully measured to obtain accurate values of their external surfaces) were obtained. They were ground all around using SiC papers to obtain an initial #1200grit-surface state on all the main sides and the smoothed edges and corners. They were subjected to isothermal oxidation tests using a SETARAM TGA92 thermo-balance in 1.5 L h−1 continuous flow of dry synthetic air (80% N2 –20% O2 ) at 1 atm, for 50 h at 1000 °C or 1100 °C. The initial heating was achieved at +20 °C min−1 and the final cooling at −5 °C min−1 . The external oxides formed on the main faces were analyzed by X-ray diffraction (XRD) using a Bruker D8 Advance diffractometer. After that, the oxidized samples were embedded in a cold resin + hardener mixture, and cut into two equal parts. A second embedding of each half part led to cross-sectional mounted samples. The mounted as-cast samples and the cross-sectional oxidized samples were ground with SiC papers (up to #1200-grit) and polished (textile disk containing 1 µm–hard alumina particles → mirror-like state). They were then examined by electron microscopy (voltage: 15 or 20 kV), using a JEOL JSM6010LA scanning electron microscope (SEM) in back scattered electron mode (BSE), and characterized by energy dispersion spectrometry (EDS) using the EDS device attached to the SEM.

Results and Discussion Obtained Chemical Compositions and As-Cast Microstructures The obtained chemical compositions of the three “Mn0.5 Cr1.5 ”-type alloys were controlled by full frame EDS (5 × 250 areas randomly selected → average and standard deviation values). They are displayed in Table 1 in which the chemical compositions of the three previous equimolar-type alloys are also reminded (in italic characters). The weight contents of the Co, Ni, and Fe elements are all close to 20 wt.% (i.e. the same values as for the atomic contents, due to the similar molar masses of these elements). The Cr contents (all close to 30 wt.%) and the Mn ones (all close to 10 wt.%) demonstrate that the 50% increase in Cr and 50% decrease in Mn were successfully obtained. The Ta and Hf contents are, again, a little overestimated (usual problem of overexposure to the beam of the hard TaC and HfC carbides after polishing). The carbon content, which cannot be specified by EDS, was however judged as also successfully obtained, considering the densities of the obtained carbides population. The microstructure of the quinary CoNiFeMn0.5 Cr1.5 alloy (“Mn0.5 Cr1.5 ”) in its as-cast condition is not illustrated since the BSE micrographs taken on this singlephased alloy (a unique phase, face centered cubic, confirmed by XRD) are uniformly gray, and thus without any interest. Only the ones of the as-cast Mn0.5 Cr1.5 TaC and Mn0.5 Cr1.5 HfC alloys are presented, in Fig. 1. The ones of the initial equimolar versions [7, 8] (Mn1 Cr1 TaC and Mn1 Cr1 HfC) are also reminded, for comparison.

20.1 ± 0.5

20 ± 0.5

20.2 ± 0.6

20.1 ± 0.3

19.3 ± 0.2

19.5 ± 0.2

19.9 ± 0.3

19.7 ± 0.4

Mn1 Cr1 HfC

Mn0.5 Cr1.5 HfC

Mn0.5 Cr1.5

Mn1 Cr1 TaC

21.5 ± 0.5

20.5 ± 0.3

20.0 ± 0.5

20.0 ± 0.1

Mn1 Cr1

Mn0.5 Cr1.5 TaC

Ni

Co

Alloys ↓

19.1 ± 0.3

18.4 ± 0.4

19.1 ± 0.3

18.6 ± 0.5

19.8 ± 0.2

19.5 ± 0.5

Fe

8.8 ± 0.3

18.2 ± 0.2

8.4 ± 0.2

18.3 ± 0.3

8.3 ± 0.5

19.5 ± 0.5

Mn

27.8 ± 0.7

19.3 ± 0.5

28.5 ± 0.3

19.2 ± 0.3

31.3 ± 0.4

20.5 ± 0.5

Cr

/

/

4.6 ± 0.2

4.5 ± 0.4

/

/

Ta

4.5 ± 0.6

4 ± 1.9

/

/

/

/

Hf

0.25

0.25

0.25

0.25

/

/

C

Table 1 Chemical compositions of the three alloys (“Mn0.5 Cr1.5 ”-type; this work) and of the previous equimolar versions (“Mn1 Cr1 ”-type; [7, 8] for comparison; average ± standard deviation calculated from five full frame EDS results obtained on five × 250 randomly selected areas)

Isothermal High Temperature Oxidation of Cantor’s-Based … 1265

1266

P. Spaeter et al.

Fig. 1 SEM/BSE micrographs illustrating the as-cast microstructures of the Mn0.5 Cr1.5 TaC and Mn0.5 Cr1.5 HfC alloys (bottom); comparison with the ones of the initial versions (top)

Similarly to the initial equimolar versions, the new alloys are obviously doublephased: matrix and MC carbides (either TaC or HfC). The MC carbides, seemingly present with a slightly higher density in these new alloys, are again obviously of a eutectic nature. Their script-like shapes, favorable to inter-dendrite solidarity and thus able to make difficult the {steady state to tertiary} creep regime transition, are expected to produce similar strength as observed for the equimolar versions of these MC-containing alloys.

Mass Gain Kinetics The obtained isothermal mass gains are plotted in Fig. 2. Despite the presence of small irregularities in some cases, these curves are all globally parabolic. This is confirmed by the straight lines obtained by plotting the mass gain versus the square root of time (Fig. 3). The Kp values were deduced from the slopes of these straight lines. The obtained results are graphically provided in Fig. 4 for 1000 and 1100 °C. On the mass gain curves it was already obvious that the two MC-containing alloys oxidized faster than the carbide-free alloy. This is confirmed by the values of the parabolic constants (orange histogram bars). Indeed, by comparison with the Kp values earlier determined for their equimolar versions earlier studied, their Kps are significantly lower. However, they are still higher than the Kp earlier obtained for a chromia-forming alloy (Ni–30 wt.%Cr [11]). One can remark that the Mn0.5 Cr1.5 alloy is almost as oxidation resistant as this Ni–30Cr alloy, at both temperatures.

Isothermal High Temperature Oxidation of Cantor’s-Based …

1267

Fig. 2 Mass gain curves at 1000 °C (top) and at 1100 °C (bottom) for the Mn0.5 Cr1.5 , Mn0.5 Cr1.5 TaC, and Mn0.5 Cr1.5 HfC alloys

Fig. 3 Mass gain curves at 1000 °C (left) and at 1100 °C (right) for the Mn0.5 Cr1.5 , Mn0.5 Cr1.5 TaC, and Mn0.5 Cr1.5 HfC alloys, plotted versus the square root of time

1268 200

Parabolic constants for 1000°C Kp / 10-12 g2 cm-4 s-1

Kp / 10-12 g2 cm-4 s-1

100

P. Spaeter et al.

80 60 40 20 Ni–30Cr

0 MnCr Mn1Cr1…

MnCr TaC Mn0.5Cr1.5…

MnCr HfC

Parabolic constants for 1100°C

150 100 50 Ni–30Cr

0 MnCr Mn1Cr1…

MnCr TaC

MnCr HfC

Mn0.5Cr1.5…

Fig. 4 Histograms representing the Kp values at 1000 °C (left) and at 1100 °C (right) for the three studied alloys (orange) and for their initial equimolar versions (blue), with addition of the Kp for 1000 and 1100 °C of the really chromia-forming Ni–30 wt.%Cr alloy [11]

Oxidation Products The oxide scales developed on surface and the sub-surfaces deteriorated by oxidation are illustrated in the cross-sectional SEM/BSE micrographs presented in Fig. 5. The external oxide scales, thicker for 1100 °C than for 1000 °C but partially lost by spallation during cooling, are composed of several types of oxides, as evidenced by the different visible gray levels. Internal oxidation occurred in the case of carbidescontaining alloys. Elemental cartography acquisition was also performed. Two examples are given in Fig. 6: Mn0.5 Cr1.5 TaC oxidized at 1000 °C (left) and at 1100 °C (right). The three alloys are covered by a multi-constituted scale in which chromium, but also (and principally) Mn, are involved. The variations of gray level are due to difference in the metal/oxygen ratio but also in the Mn/Cr ratio, as evidenced by these X-maps and also by EDS spot analysis. This is obviously this complex external scale which governed (limits more and more) the diffusion of the ions involved in the oxidation process, and thus the mass gain kinetic (represented by Kp). Concerning the Mn0.5 Cr1.5 TaC alloy, Ta was also oxidized in situ (where TaC existed initially) as well as close to the oxidation front. The not directly oxidized TaC obviously dissolved in the sub-surface over a depth increasing with temperature and Ta diffused towards the oxidation front to be oxidized simultaneously with Cr. In contrast, for the Mn0.5 Cr1.5 HfC alloy, the HfC carbides did not dissolve and were exclusively oxidized in situ. Internal chromium oxides also formed in the neighborhood of the oxidized HfC. In addition to XRD, numerous EDS spot analyses allowed specifying the natures of all oxides, external and internal. A summary of these identifications is given in Table 2, in which the oxides earlier observed in the case of the equimolar versions of the alloys are reminded for comparison. It seems that, in contrast with the initial equimolar versions (Mn1 Cr1 -type alloys) for which the external oxides were not well defined (continuous variation in Mn and in Cr from Mn-rich/Cr-poor to Mn-poor/ Cr-rich), there are here mainly an outer Mx Oy oxide (M = more Mn than Cr) and an inner MnCr2 O4 spinel oxide for these Mn0.5 Cr1.5 -type alloys (i.e. the Cr/Mn = 2 ratio for the oxide, not far from the Cr/Mn = 3 ratio for the alloys). For the present alloys one can also notice the presence of a thin continuous almost pure chromia

Isothermal High Temperature Oxidation of Cantor’s-Based …

1269

Fig. 5 Illustration of the oxidation-induced damages on surface and in sub-surface as visible on the cross-sectional samples prepared from the oxidized Mn0.5 Cr1.5 -type alloys (SEM/BSE micrographs)

layer in the middle of the external scale, separating the outer Mx Oy oxide and the inner MnCr2 O4 spinel oxide. This thin intermediate chromia scale is evidenced in Fig. 7 which contains the reformatted and enlarged SEM/BSE micrograph, Cr-map, O-map, and Mn-map coming from Fig. 6(top, left).

Commentaries For these Mn0.5 Cr1.5 , Mn0.5 Cr1.5 TaC, and Mn0.5 Cr1.5 HfC alloys, by comparison with the previous equimolar versions Mn1 Cr1 , Mn1 Cr1 TaC, and Mn1 Cr1 HfC, the enrichment in Cr and the lowering of the presence of Mn thus modified the oxide externally formed, by promoting the formation of Cr-enriched/Mn-empoverished oxide seemingly close to the MnCr2 O4 spinel as well as a continuous intermediate chromia scale (Cr2 O3 also formed for the equimolar versions but as discontinuous oxide). The presence, in addition to an outer thick Mn-rich (Mn, Cr)x Oy oxide, of this inner thick spinel layer and this thin intermediate chromia continuous layer, disposed like a sandwich, may explain why the oxide growth was much slower than for the equimolar versions. This was due to the more difficult ions across the successive continuous spinel and the chromia scales. This can explain why their oxidation rates are so lowered and are close to the ones of a chromia-forming alloy. The MC-containing Mn0.5 Cr1.5 type alloys also take benefit from this new external multi-composed oxide scale with improved protective effect, but Ta and Hf also oxidize, inducing faster mass gains. These ones stay nevertheless much slower than for the equimolar versions.

1270

P. Spaeter et al.

Fig. 6 Examples of EDS elemental cartography (top: Mn0.5 Cr1.5 TaC oxidized at 1000 °C, bottom: 1100 °C)

Isothermal High Temperature Oxidation of Cantor’s-Based …

1271

Table 2 Lists of the external and internal oxides identified by EDS spot analysis, for the three studied alloys oxidized at the two temperatures; corresponding results earlier obtained for the equimolar versions reminded for comparison Alloys ↓

Oxides at 1000 °C (50h)

Oxides at 1100 °C (50 h)

Mn1 Cr1

(Mn, Cr)3 O4 and/or (Mn, Cr)2 O3 MO, Cr2 O3

(Mn, Cr)2 O3 Cr2 O3

Mn0.5 Cr1.5

(Mn, Cr)2 O3 /Cr2 O3 /MnCr2 O4

(Mn, Cr)2 O3 /Cr2 O3 /MnCr2 O4

Mn1 Cr1 TaC

(Mn, Cr)3 O4 and/or (Mn, Cr)2 O3 MO, Cr2 O3 , CrTaO4

(Mn, Cr)2 O3 Cr2 O3 , CrTaO4

Mn0.5 Cr1.5 TaC

(Mn, Cr)2 O3 /Cr2 O3 /MnCr2 O4 / CrTaO4

(Mn, Cr)2 O3 /Cr2 O3 /MnCr2 O4 / CrTaO4

Mn1 Cr1 HfC

(Mn, Cr)3 O4 and/or (Mn, Cr)2 O3 MO, Cr2 O3 , HfO2

(Mn, Cr)2 O3 Cr2 O3 , HfO2

Mn0.5 Cr1.5 HfC

(Mn, Cr)2 O3 /Cr2 O3 /MnCr2 O4 / HfO2

(Mn, Cr)2 O3 /Cr2 O3 /MnCr2 O4 / HfO2

Fig. 7 Enlargement of a part of the SEM/BSE micrograph and of the corresponding Cr, O, and Mn elemental maps presented in the left side of Fig. 6

Conclusion Clearly, the decrease in Mn and the increase in Cr improved significantly the oxidation behavior of initial Cantor alloy and of its MC-strengthened derivatives. The matrices of these new alloys still belong to the high entropy alloys category since the Mn content did not decrease below 5 wt.% and its intrinsic strength can be expected to be preserved. However the constitution of the external oxide scales is still complex and some problems of sustainability of the protective external scale are to be expected,

1272

P. Spaeter et al.

for instance concerning their mechanical behavior in case of thermal variations. It can be judicious to totally remove Mn from the composition to favor the formation of chromia only and to introduce another element instead.

References 1. Bradley EF (1988) Superalloys: a technical guide. ASM International, Metals Park (USA) 2. Kofstad P (1988) High temperature corrosion. Elsevier Applied Science, London (UK) 3. Tkaczyk AH, Bartl A, Amato A, Lapkovskis V, Petranikova M (2018) Sustainability evaluation of essential critical raw materials: cobalt, niobium, tungsten and rare earth elements. J Phys D: Appl Phys 51:203001 4. Grandell L, Lehtilä A, Kivinen M, Koljonen T, Kihlman S, Lauri LS (2016) Role of critical metals in the future markets of clean energy technologies. Renew Energy 95:53–62 5. Senkov ON, Miller JD, Miracle DB, Woodward C (2015) Accelerated exploration of multiprincipal element alloys with solid solution phases. Nat Commun 6:6529. https://doi.org/10. 1038/ncomms7529 6. Ye YF, Wang Q, Lu J, Liu CT, Yang Y (2016) High-entropy alloy: challenges and prospects. Mater Today 19:349–362 7. Cantor B (2021) Multicomponent high-entropy Cantor alloys. Prog Mater Sci 120:100754 8. Berthod P (2022) As-cast microstructures of high entropy alloys designed to be TaC–strengthened. J Metallic Mater Res 5:1–10 9. Berthod P (2022) As–cast microstructures of HEA designed to be strengthened by HfC. J Eng Sci Innovation C Chem Eng Mater Sci Eng 7:305–314 10. Berthod P (2023) Strengthening against creep at elevated temperature of HEA alloys of the CoNiFeMnCr type using MC-carbides. In: TMS 2023 152nd annual meeting & exhibition supplemental proceedings, pp 1103–1111. https://doi.org/10.1007/978-3-031-22524-6_102 11. Berthod P (2023) High temperature oxidation of CoNiFeMnCr high entropy alloys reinforced by MC-carbides. In: TMS 2023 152nd annual meeting & exhibition supplemental proceedings, pp 933–941. https://doi.org/10.1007/978-3-031-22524-6_86 12. Berthod P (2005) Kinetics of high temperature oxidation and chromia volatilization for a binary Ni–Cr alloy. Oxid Met 64:235–252

Study of the Corrosive Effect of Enzymatic, Multi-enzymatic, and Sodium Hypochlorite Solutions on Surgical Grade Stainless Steel Instruments Used in the Operating Room Area of the Clinical Hospital Jhasmmany G. Lovera and Jaime A. Rocha

Abstract Surgical instruments play a fundamental role in the success of surgical procedures. They have traditionally been manufactured from stainless steel due to its corrosion resistance and ease of sterilization. However, exposure to corrosive substances during cleaning and disinfection can affect their integrity over time. This study investigates the corrosive effect of enzymatic, multi-enzymatic, and sodium hypochlorite solutions on surgical grade stainless steel instruments. Samples were immersed in solutions under different concentrations and their breakdown potential was measured. Likewise, tests were carried out using normal ringer’s serum as a medium, which is employed according to ISO 10993-15 standard, to evaluate the corrosion resistance of materials used for prostheses. The results showed that the breakdown potential depends on the concentration of the solution and temperature. Enzymatic and multi-enzymatic solutions do not pose a significant risk if kept within recommended concentrations. However, normal ringer’s serum induces corrosion from 8 h of exposure. This study provides relevant information for cleaning and maintaining surgical instruments in order to optimize their performance and safety. Keywords Surgical instruments · Stainless steel · Corrosion · Enzymatic · Hypochlorite

J. G. Lovera (B) Materials Engineering in Metallurgical and Materials Research Institute (IIMETMAT), Major University of San Andrés (UMSA), Santa Rosa Street, No. 100 Corner, Las Américas Avenue, Villa Fatima, La Paz, Bolivia e-mail: [email protected] J. A. Rocha University of Concepsión, Concepción, Chile Metallurgical and Materials Research Institute (IIMETMAT), Major University of San Andrés (UMSA), Santa Rosa Street, No. 100 Corner, Las Américas Avenue, Villa Fatima, La Paz, Bolivia © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_110

1273

1274

J. G. Lovera and J. A. Rocha

Introduction Surgical procedures require the use of instruments that meet strict quality and safety standards to ensure the success of interventions and patient health. Stainless steel has traditionally been widely used in their manufacture due to its corrosion resistance, durability, and ease of sterilization [1]. However, during cleaning and disinfection, instruments are exposed to potentially corrosive substances such as enzymatic, multi-enzymatic, and sodium hypochlorite [2]. This could affect their integrity and functioning over time [3, 4]. On the other hand, during longer surgical procedures, instruments remain in prolonged contact with body fluids [1], which can also induce corrosion. This work aims to establish the consequences of using enzymatic solutions and disinfection on corrosion of surgical grade stainless steel instruments, by evaluating their breakdown potential and surface morphology. Likewise, tests were carried out with the instruments in ringer’s serum, simulating their exposure to body fluids. The results provide relevant information to optimize their maintenance and increase their useful life.

Background Various studies have shown that corrosion is one of the most frequent causes of incorporation of surgical instruments [3, 5]. This is mainly due to the action of body fluids, chemical agents present in cleaning solutions, and poor practices by medical personnel during handling [4, 6]. A survey of surgical area professionals [3] revealed that 24% of discarded instruments showed signs of corrosion. This demonstrates the need to determine the concrete effect of the products used in cleaning. Sodium hypochlorite has traditionally been used for disinfection, whose corrosive action on metals is known [2]. As an alternative, there are enzymatic and multienzymatic preparations whose aggressiveness on metal surfaces has not been fully established. It is necessary to establish safe ranges of concentration that allow effective disinfection without compromising the integrity of the instruments. This will result in less premature discard and cost savings for health centers.

Study of the Corrosive Effect of Enzymatic, Multi-enzymatic …

1275

Methodology Materials and Methods Surgical grade martensitic stainless steel instrument samples manufactured by Reda Instrumente approximately 1 cm3 were used. The study solutions were prepared in tap water with the idea of simulating the same working conditions of the operating theatre at increasing concentrations of Enzymex L9 enzymatic, Bonzyme multienzymatic, and concentrated X.5 sodium hypochlorite, within concentration ranges established as adequate to carry out disinfection within aseptic requirements. The probes were subjected to immersion in the solutions for a controlled time, evaluating visual and morphological changes using SEM. The breakdown potential was determined using a Gamry G-300 potentiostat and polarization curves according to ISO 10993-15. To simulate exposure to body fluids, normal ringer’s serum was used following a similar procedure to that already mentioned. The results were statistically analyzed.

Variables Enzymatic concentration: 4–6 ml/L. Multi-enzymatic concentration: 6.5–8.5 ml/L. Hypochlorite concentration: 0.01–0.03 ml/L. Immersion time: Up to 21 days, in ringer’s serum: 8–32 h.

Results and Discussion Breakdown Potential Polarization curves were constructed for each concentration, as shown in Figs. 1, 2 and 3, based on which the Open Circuit Potential (OCP) and Breakdown Potential (EP) were determined. The breakdown potential values decreased as the solution concentration increased (Tables 1, 2 and 3), coinciding with greater aggressiveness. However, in all situations the EP exceeded 600 mV/ENH, which is the limit established by the US FDA, except for the 6 ml/L enzymatic solution. Within the range evaluated, the enzymatic and multi-enzymatic solutions did not demonstrate significant harmful effects on the stainless steel (EP > 600 mV).

1276

J. G. Lovera and J. A. Rocha

Fig. 1 Polarization curve, stainless steel immersed in 5 ml/L enzymatic solution

Fig. 2 Polarization curve, stainless steel immersed in 7.5 ml/L multi-enzymatic solution

Study of the Corrosive Effect of Enzymatic, Multi-enzymatic …

1277

Fig. 3 Polarization curve, stainless steel immersed in 0.02 ml/L sodium hypochlorite solution Table 1 Results obtained from enzymatic solution diluted to different concentrations Code

Concentration (ml/L)

ENZI-1000

4

OCP (mV/ENH) 58.3

ENZI-1125

4.5

ENZI-1250

5

ENZI-1375

5.5

EP (mV/ENH) 1004

–3.8

994

111.3

944

6.4

844

ENZI-1500

6

6.0

794

ENZI-1250Pt

5

424.8

1644

Table 2 Results obtained from multi-enzymatic solution diluted to different concentrations Code

Concentration (ml/L)

MULTI-1625

6.5

OCP (mV/ENH) −45.9

EP (mV/ENH) 1244

MULTI-1750

7

−63

1394

MULTI-1875

7.5

−38.1

1444

MULTI-2000

8

−89.9

1594

MULTI-2125

8.5

−137.5

1244

MULTI-1875Pt

7.5

594.9

1644

1278

J. G. Lovera and J. A. Rocha

Table 3 Results obtained from sodium hypochlorite solution diluted to different concentrations Code

Concentration (ml/L)

OCP (mV/ENH)

EP (mV/ENH)

CLOR-100

0.01

−80.7

1494

CLOR-200

0.02

−50.6

1544

CLOR-300

0.03

−78

1494

CLOR-200Pt

0.02

812.3

2244

Table 4 Percentage table of mass loss due to corrosion and deposited mass in a defined time

Probe

Time (h)

Mass loss (%)

Deposited mass (%)

SUERO-1

8

0.01

0.01

SUERO-2

16

0.03

0.01

SUERO-3

24

0.04

0.02

SUERO-4

32

0.06

0.03

On the other hand, hypochlorite induced lower corrosion resistance, especially at concentrations of 0.02 ml/L (Table 3). In all three cases, using platinum instead of stainless steel, it was observed that the EP exceeded the other values, showing the stability of the solution and reliability of the results obtained.

Time-Controlled Immersion No visual or morphological changes were observed after 21 days of exposure to enzymatic, multi-enzymatic, and sodium hypochlorite solutions within the established ranges. However, when dipping the probes in normal ringer’s serum, oxidation formation was detected after 8 h. In addition, a progressive increase in mass loss and deposition was quantified over time of contact (Table 4 and Fig. 4).

Scanning Electron Microscope Thanks to the electron microscope, it was possible to evidence changes on the surface of the probes that were immersed in the different solutions (Fig. 5). Micro-corrosion traces were detected on samples exposed to enzymatic and sodium hypochlorite solutions (Figs. 5 and 6). On the other hand, probes treated with ringer’s serum showed considerable damage to their surface.

Study of the Corrosive Effect of Enzymatic, Multi-enzymatic …

1279

Fig. 4 Graphical representation of the percentage masses lost and obtained by deposition over time of exposure

Fig. 5 SEM photomicrographs with 500× resolution, secondary electron detector. 1 Untreated. 2 Enzymatic solution. 3 Multi-enzymatic solution. 4 Solution with sodium hypochlorite

1280

J. G. Lovera and J. A. Rocha

Fig. 6 SEM photomicrographs with 500× resolution, backscattered electron detector. 1 Untreated. 2 Enzymatic solution. 3 Multi-enzymatic solution. 4 Solution with sodium hypochlorite

Conclusions The study established that the breakdown potential of surgical grade stainless steel depends directly on the concentration of the cleaning solutions used. Enzymatic and multi-enzymatic solutions do not pose a risk to instruments as long as recommended dilutions are respected and exposure time does not exceed 24 h. On the other hand, ringer’s serum induces corrosion in relatively short exposure periods, which could compromise the integrity of instruments during prolonged surgical procedures. The results obtained are relevant for optimizing cleaning and disinfection procedures for surgical instruments. It is recommended to strictly monitor instruments after long procedures to detect possible corrosion damage induced by body fluids. It is also important to provide constant training to medical personnel regarding the proper use of cleaning solutions, recommended concentrations, and maximum exposure times. This will result in a longer useful life of instruments and lower associated replacement costs.

Study of the Corrosive Effect of Enzymatic, Multi-enzymatic …

1281

Recommendations . Strictly follow manufacturers’ recommended concentrations to avoid unintentional corrosion. . Limit prolonged contact of instruments with body fluids through periodic cleaning and disinfection during long surgeries. . Constantly monitor instruments, especially after prolonged procedures, detecting signs of corrosion. . Maintain continuous communication with manufacturers to obtain updated guidelines for instrument use and maintenance. . Periodically train medical personnel on handling, cleaning, and care of instruments to prevent damage. . Conduct more studies to better understand the effects of cleaning solutions on other materials and medical devices.

References 1. Equinox (n.d.) ¿Qué es el Acero Inoxidable de grado quirúrgico? 2. Yanapa (2020) Lavandina Concentrada X.5 3. Rodríguez Gamboa MS (2018) Cuidado y mantenimiento del instrumental quirúrgico laparoscópico 4. Metrex (n.d.) Detergentes Enzimáticos 5. Folgueras Méndez J et al (2011) Evaluación de Calidad en el Instrumental Quirúrgico. Havana, Cuba 6. Moreno Amaya AA (2014) Corrosión en instrumental quirúrgico. Sustancias que generan corrosión

Part XXXIII

Environmentally Assisted Cracking: Theory and Practice

Effect of Hydrogen Concentration and Residual Stress on the Delayed Cracking Performance of the 22MnB5 Hot Roll Bending Pipe Ping Zhu, Tianhan Hu, Jiayi Zhou, Yu Sun, Wufeng Dong, Kai Ding, and Yulai Gao

Abstract The microstructure and delayed cracking performance of the 22MnB5 hot roll bending pipe was analyzed in this study. The main microstructure of the surface and central zones of the pipe were martensite and ferrite before and after annealing. The delayed cracking test indicated that the annealed pipe possessed better delayed cracking performance than the original one. The residual stress of the original and the annealed pipes was tensile stress. In particular, the tensile stress at the outer bending of the pipe was the largest. The hydrogen content at the inner and outer bending zones increased slightly after annealing. The crack after soaking in acid was only observed at the outer bending zone of the pipe. According to the test results of residual stress and hydrogen content, it was deemed that the larger residual stress could induce the cracks. Meanwhile, no obvious effect of the hydrogen content on the delayed cracking performance could be detected. Keywords Hot roll bending · 22MnB5 steel pipe · Delayed cracking · Hydrogen concentration · Residual stress

P. Zhu · T. Hu · J. Zhou · Y. Sun · W. Dong · K. Ding (B) · Y. Gao (B) State Key Laboratory of Advanced Special Steel, School of Materials Science and Engineering, Shanghai University, Shanghai 200444, China e-mail: [email protected] Y. Gao e-mail: [email protected] Y. Gao Shanghai Engineering Research Center for Metal Parts Green Remanufacture, Shanghai 200444, China © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_111

1285

1286

P. Zhu et al.

Introduction With the increasing environmental degradation and energy shortage, automobile lightweight had become the focus of industrial transformation for automobile manufacturing [1]. Advanced high strength steels (AHSSs) with high strength and plasticity could absorb enough energy to ensure safety during collision. In addition, the application of AHSSs could effectively reduce the weight of body parts, achieving the purpose of lightweight. Thus, AHSSs had been widely used in the production of various automotive parts [2, 3]. As a kind of AHSS, 22MnB5 hot stamping steel possessed obvious advantages in strength, formability, and dimensional accuracy, widely applied in the manufacture of automobile structural parts [4, 5]. The initial tensile strength of 22MnB5 steel was about 600 MPa while it could reach more than 1,500 MPa through complex heat treatment process [6]. Unfortunately, the delayed cracking performance of steel deteriorated sharply when the tensile strength of the steel exceeds 1,000 MPa. In addition, 22MnB5 steel was prone to delayed cracking, especially in the harsh service environments, seriously reducing the service life of the workpieces [7]. Thus, the effective improving of the delayed cracking performance of the steel had become an important issue in the development of AHSSs [8]. Several studies showed that the delayed cracking performance of AHSS depended on the coupling effect of microstructure, hydrogen content, and stress–strain state in the steel [9, 10]. Shingo et al. [11] pointed out that when the local hydrogen content reached a critical level, it would lead to the initiation of delayed crack. Generally, the main microstructure in AHSS was ferrite, martensite, and bainite. Among them, the delayed cracking sensitivity of martensite was relatively higher [12]. Yamabe et al. [13] also found the hydrogen diffusion in martensite was faster than that in austenite and ferrite phase. Lian et al. [14] deemed that the residual stress distribution could produce a significant effect on the delayed cracking performance by experiments and numerical simulations. And the obvious difference of delayed cracking performance with different stress state could be detected. Also, the sensitivity of hydrogen embrittlement increased with the tensile stress of AHSS becoming higher [15]. The main stress relief methods in industry included annealing, vibratory, ultrasonic treatment, etc. Among them, annealing stress relief was considered as an effective method to reduce the residual stress in materials [16]. However, the annealing process could lead to the warpage and distortion of the materials [17, 18]. Especially, the mechanical strength of AHSS could be reduced by the annealing process with high temperature, affecting the application of AHSS. Nevertheless, little information was available on the residual stress release of AHSS by annealing process with relative low temperature. As an advanced stamping technique, hot roll bending was an important method for high strength steel sheet [19, 20]. However, the delayed cracking was easy to be induced for the hot roll bending pipe, owing to the large residual stress accumulated during the stamping process and the harsh service environment. In this paper, the effect of low temperature annealing on the delayed cracking performance of hot roll bending pipe was systematically studied by acid soaking

Effect of Hydrogen Concentration and Residual Stress on the Delayed …

1287

experiment. The microstructure of the pipes in both original and annealing states was observed. The hydrogen content at different typical positions of the hot roll bending pipes was obtained. Moreover, the residual stress of the hot roll bending pipes in different states was detected. Meanwhile, the effects of microstructure, hydrogen content, and residual stress on the delayed cracking performance of the hot roll bend pipes were comparatively discussed.

Experimental Procedures The 22MnB5 hot roll bending pipe was chosen as the raw specimens, and the chemical composition of the 22MnB5 steel was listed in Table 1. The appearance of the hot roll bending double-cell pipes was shown in Fig. 1. The overall appearance of the pipes was presented in Fig. 1a. The size of the cross section of the pipe was approximately 4.2 cm × 9 cm, as displayed in Fig. 1b, c. One of the pipes was selected to be annealed at 150 °C for 15 min as the control group. The pipes in the original state and after annealing were cut from the middle for the convenience of the subsequent delayed cracking test. The cleaned pipes were dipped in the solution of 0.1 mol/L hydrochloric acid for 300 h, with the ratio of solution volume to sample weight 7 ml/g. The hydrochloric acid was not changed during the experiment. The hot roll bending pipes with different state after acid soaking were systematically observed to study the delayed cracking performance. The specimens for microstructure analysis were obtained by wire electrical discharge machining (WEDM). The specimens were etched after being ground Table 1 Chemical composition of the 22MnB5 steel (wt%) Elements

C

Si

Mn

P

S

Cr + Mo

B

Al

Ti

Fe

22MnB5

0.25

0.4

0.14

0.025

0.01

0.5

0.0035

0.015

0.05

Bal.

Fig. 1 Appearance of the hot roll bending pipes in the original state: a overall appearance, b and c cross-section appearance

1288

P. Zhu et al.

and polished. The microstructure of the pipes was observed by optical microscopy (OM, Zeiss Imager A2m). The residual stress test was carried out by X-ray stress analyzer (X-350A). The residual stress of the position at the inner and outer bending was emphatically analyzed. The hydrogen content of the inner and outer bending of the pipes was detected by ONH analyzer (Leco ONH836).

Results and Discussion The microstructure of the hot roll bending pipe in original state was presented in Fig. 2. The metallographical images of the pipes near surface and at the central region were shown in Fig. 2a, b and Fig. 2c, d, respectively. The main microstructure was ferrite and martensite. No obvious difference could be observed between the microstructure of the surface and central of the pipe. The microstructure of the hot roll bending pipe after annealing was displayed in Fig. 3. The metallographical images of the pipes adjacent to the surface and at the central region were shown in Fig. 3a, b and Fig. 3c, d, respectively. The main microstructure was still ferrite and martensite. Generally, the annealing process could lead to the coarsening of the grains. However, no obvious grain size change of the

Fig. 2 Metallographical images of the hot roll bending pipe in original state: a and b near surface, c and d central region

Effect of Hydrogen Concentration and Residual Stress on the Delayed …

1289

Fig. 3 Metallographical images of the hot roll bending pipe specimen in annealing treatment state: a and b adjacent to the surface, c and d central region

pipe after annealing could be detected because of the low temperature and short time annealing. The effect of annealing under these parameters on the microstructure was limited. That is to say, the annealing in this experiment is only to release the residual stress. The real-time values of pH and temperature changes during the delayed cracking test were shown in Fig. 4. It can be found that the pH value increased with the increase of the time. And the pH value kept stable at about 4.4 after 100 h, indicating that the whole delayed cracking test was completed under acidic condition. The temperature of the solution during the delayed cracking test was always at the range of 15–21 °C, which ensured the stability of the experiment. The appearance of the original hot roll bending pipe after acid soaking was presented in Fig. 5. All four sides of the pipe were carefully observed. The obvious crack could be found at the outer bending of the pipe (see Fig. 5e). On the contrary, no obvious crack could be observed at each side of the annealed hot roll bending pipe after acid soaking (see Fig. 6). The results indicated that the hot roll bending pipe after annealing obtained better delayed cracking performance than the original one. In general, the delayed cracking performance was closely related to the residual stress [10]. In order to shed much light on the effect of residual stress on the delayed cracking performance of hot roll bending pipe, the residual stress of the pipes with

1290

P. Zhu et al.

Fig. 4 Fluctuation of the pH and temperature during the delayed cracking test

Fig. 5 Appearance of the original hot roll bending double-cell pipe after soaking in acid for 300 h: a–d overall appearance, e region with crack

Fig. 6 Appearance of the hot roll bending pipe in annealing treatment state after soaking in acid for 300 h

Effect of Hydrogen Concentration and Residual Stress on the Delayed …

1291

Fig. 7 Test results of residual stress before and after annealing treatment of the hot roll bending pipes

different state was tested, and the results were shown in Fig. 7. The residual stress could be divided into tensile stress and compressive stress [21]. No matter what state, each test position of the pipes presented tensile stress. Niwa et al. [22] found that the tensile stress was easy to cause the delayed cracks due to the promotion of the hydrogen diffusion. No obvious residual stress fluctuation could be found between the original and annealed pipes on the whole. The residual stress at these test positions of the annealed pipe was lower than that of the original pipe. However, it could be found that the residual stress at the outer bending zone where the crack occurred was relatively larger than the other positions. Thus, the initiation of the delayed crack could be ascribed to the excessive residual stress. The hydrogen content of the outer and inner bending zones was compared to further study the factors of the crack initiation, the result was presented in Fig. 8. The hydrogen content at the inner and outer bending zones of the hot roll bending pipes in both original and annealed states was below 2 ppm. Loidl et al. [21] measured the diffusible hydrogen content of several advanced high strength steels with different strength levels by the thermal desorption spectroscopy, and found that the hydrogen content of the advanced high strength steels was in the range of 0.5–3 ppm. What’s more, the hydrogen content of the pipe in annealed state was relatively higher than that of the original pipe. However, the delayed cracks couldn’t be found in the annealed pipe with more hydrogen content, implying that the hydrogen content with relatively low value could only produce little effect on the crack initiation at the outer bending zones of the hot roll bending pipes. That is to say, the crack initiation of the pipes caused by hydrogen embrittlement could possibly occur only when the hydrogen content exceeded a critical value. The delayed cracking performance of the hot roll bending pipe depend on the microstructure, residual stress, and hydrogen content. In the study, no obvious microstructure transformation could be found. Besides, the hydrogen content of the

1292

P. Zhu et al.

Fig. 8 Results of hydrogen content at the inner and outer bending zones of the hot roll bending pipes before and after annealing treatment

pipes in different states was relatively low. Thus, the microstructure and hydrogen content produced little effect on the delayed cracking performance of the hot roll bending pipe at the involved parameters. However, the tensile stress at the outer bending zone of the pipe was easily accumulated during the hot roll bending process. Therefore, the excessive tensile stress that existed in the outer bending was the main factor for occurrence of the delayed cracks. On the contrary, the annealing process could reduce the tensile stress at the outer bending to a certain extent, effectively improving the delayed cracking performance of the hot roll bending pipe.

Conclusions The delayed cracking performance of the hot roll bending pipes in the solution of 0.1 mol/L HCl with various times was comparatively investigated. The delayed cracking performance of the hot roll bending pipe could be improved with the annealing process. The microstructure of both original and annealed states was mainly ferrite and martensite. Some crack was observed in the original pipe after acid soaking with 300 h, while no obvious crack could be found in the annealed one. In addition, the residual stress test showed that the tensile stress was the main stress type of the pipes in both states. No obvious fluctuation of hydrogen content could be detected between the original and annealed pipes, with all the hydrogen contents of the test positions at the pipes below 2 ppm. It could be found that the crack initiation mainly occurred at the outer bending zone of the pipe, which could be ascribed to the relatively large tensile stress. On the contrary, the hydrogen content could produce little effect on the delayed cracking performance of the hot roll bending pipe due to its relatively low content.

Effect of Hydrogen Concentration and Residual Stress on the Delayed …

1293

Acknowledgements This work is supported by the National Natural Science Foundation of China (Grant no. 52101042) and China Postdoctoral Science Foundation (Grant no. 2021M702082).

References 1. Hu X, Ding H, Liu J (2023) Deformation behaviors and microstructure evolution of a novel multiphase medium Mn high Al lightweight steels with excellent strength-ductility combinations. Mater Sci Eng A:145478 2. Dong WF, Lei M, Pan H, Ding K, Gao YL (2022) Role of the internal oxidation layer in the liquid metal embrittlement during the resistance spot welding of the Zn-coated advanced high strength steel. J Mater Res Technol 21:3313–3326 3. Dai ZB, Ding R, Yang ZG, Zhang C, Chen H (2018) Thermo-kinetic design of retained austenite in advanced high strength steels. Acta Mater 152:288–299 4. Hong SH, Kim D, Lee S, Kim SJ (2023) Microstructural evolution of liquid metal embrittlement in 1.5-GPa-grade Zn-coated hot-press-forming steels. Mater Sci Eng A 874:145059 5. Lesch C, Kwiaton N, Klose FB (2017) Advanced high strength steels (AHSS) for automotive applications-tailored properties by smart microstructural adjustments. Steel res Int 88(10):1700210 6. Taylor T, Clough A (2018) Critical review of automotive hot-stamped sheet steel from an industrial perspective. Mater Sci Technol 34(7):809–861 7. Komatsuzaki Y, Joo H, Yamada K (2008) Influence of yield strength levels on crack growth mode in delayed fracture of structural steels. Eng Fract Mech 75(3–4):551–559 8. Sanchez J, Lee SF, Martin-Rengel MA, Fullea J, Andrade C, Ruiz-Hervias J (2016) Measurement of hydrogen and embrittlement of high strength steels. Eng Fail Anal 59:467–477 9. Wang J, Xue P, Zhang LQ, Qiao Y, Zhu XD, Wang SZ, Zhong Y, Mao XP (2023) The compact-strip-produced martensitic steel possessing better resistance to hydrogen-induced delayed cracking. Scripta Mater 230:115419 10. Berrahmoune MR, Berveiller S, Inal K, Patoor E (2006) Delayed cracking in 301LN austenitic steel after deep drawing: martensitic transformation and residual stress analysis. Mater Sci Eng A 438:262–266 11. Yamasaki S, Takahashi T (1997) Evaluation method of delayed fracture property of high strength steels. Mater Sci 83(7):454–459 12. Zhu X, Li W, Hsu TY, Zhou S, Wang L, Jin XJ (2015) Improved resistance to hydrogen embrittlement in a high-strength steel by quenching-partitioning-tempering treatment. Scripta Mater 97:21–24 13. Yamabe J, Takakuwa O, Matsunaga H, Itoga H, Matsuoka S (2017) Hydrogen diffusivity and tensile-ductility loss of solution-treated austenitic stainless steels with external and internal hydrogen. Int J Hydrogen Energ 42(18):13289–13299 14. Lian J, Sharaf M, Archie F, Münstermann S (2012) A hybrid approach for modelling of plasticity and failure behaviour of advanced high-strength steel sheets. Int J Damage Mech 22(2):188–218 15. Ma M, Yi H, Lightweight car body and application of high strength steels. In Advanced Steels, Springer: Berlin, Heidelberg, 2011, 187–198. 16. Song Y, Yang JZ, Song KX, Zhou YJ, Huang T, Zhang CW, Li T, Fan WD (2023) Effect of tensile stress annealing on residual stress and strength of C19400 alloy. J Mater Res Technol 25:786–798 17. Popovich A, Sufiiarov V, Polozov I, Borisov E, Masaylo D, Orlov A (2016) Microstructure and mechanical properties of additive manufactured copper alloy. Mater Lett 179:38–41 18. Zhou YJ, Yang JZ, Song KX, Yang SD, Zhu QQ, Peng XW, Liu YH, Du YB, He SY (2022) Effect of annealing temperature on dual-structure coexisting precipitates in Cu-2.18Fe-0.03P alloy and softening mechanism at high temperature. J Mater Sci 57(44):20815–20832

1294

P. Zhu et al.

19. Golling S, Frometa D, Casellas D, Jonsen P (2019) Influence of microstructure on the fracture toughness of hot stamped boron steel. Mater Sci Eng A 743:529–539 20. Demes M, Janke N, Beuscher J, Kuhn M, Droder K (2019) Process integration of hot stamping steel and thermoforming fibre-reinforced thermoplastics. Procedia CIRP 85:141–146 21. Skiadopoulos A, de Castro e Sousa A, Lignos DG (2023) Experiments and proposed model for residual stresses in hot-rolled wide flange shapes. J Constr Steel Res 210:108069 22. Niwa M, Shikama T, Yonezu A (2015) Mechanism of hydrogen embrittlement cracking produced by residual stress from indentation impression. Mater Sci Eng A 624:52–61

Hydrogen Content and Charpy Toughness of Pipeline Steels with Different Hydrogen Charging Processes Xin Pang and Su Xu

Abstract Hydrogen embrittlement of pipeline steels has become a major design concern for the transportation of pure hydrogen gas or hydrogen blends using pipeline, especially at high design stresses. Quantification of the effects requires measurement of hydrogen content in test samples and suitable test controls to simulate the practical service conditions. In this work, the total hydrogen content in pipeline steels pre-charged using electrolytic and gaseous methods was measured using the inert gas fusion (LECO) analysis. The analysis results showed that an average of approximately 0.2 ppm hydrogen existed in the as-received X65 steel specimens without either electrolytic or gaseous hydrogen charging. The electrolytic pre-charging in 0.1 M NaOH solution with 150 mg/L As2 O3 was effective to introduce hydrogen into the X65 steel, and the highest total hydrogen content of 1.4 ppm was achieved at a charging current density of 2.5 mA/cm2 and charging time of one hour. The highest total hydrogen content achieved by the gaseous charging technique in pure H2 at 10.3 MPa pressure at room temperature for 15 days was 0.4 ppm. Pd surface coating promoted hydrogen absorption into the steel and led to almost doubled total hydrogen contents for both charging techniques. Ex-situ Charpy tests of electrolytically pre-charged X65 specimens at room temperature showed approximately maximum 20% reduction in Charpy absorbed energy (CVN) compared to uncharged specimens. The discrepancy in the pre-charging time needed to reach the saturation effect (i.e., one hour for LECO vs. five hours for Charpy) can be attributed to the different sample geometry and dimensions for the LECO and Charpy tests. Keywords Hydrogen embrittlement · Hydrogen content · Pipeline steel · Hydrogen charging · Toughness · Charpy test

X. Pang (B) · S. Xu CanmetMATERIALS, Natural Resources Canada, 183 Longwood Road South, Hamilton, ON L8P 0A1, Canada e-mail: [email protected] © His Majesty the King in Right of Canada, as represented by the Minister of Natural Resources 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_112

1295

1296

X. Pang and S. Xu

Introduction Under the Paris Agreement, many countries including Canada have committed to achieve net-zero emissions by 2050. To reach this target, hydrogen could play a valuable role as an alternative energy carrier in the decarbonisation of energy systems [1]. A widescale hydrogen economy will require a significant development of infrastructure for hydrogen storage and transport. The direct contact of gaseous hydrogen with the pipeline networks may lead to hydrogen uptake by the carbon steels, potentially triggering a variety of degradation modes that are generally referred to as hydrogen embrittlement. The deleterious effects of hydrogen on the mechanical and toughness properties of pipeline steels have become a major concern for pipeline transportation of hydrogen or hydrogen and natural gas blends, especially at high design stresses. For a given steel tested under controlled hydrogen environment and loading conditions, the hydrogen content in the metal is a key factor determining hydrogen embrittlement effects. To quantify and compare hydrogen induced degradation in pipeline steels, accurate measurement of hydrogen content in the metal under different hydrogen charging conditions is required. It should be noted that in many previous studies the actual hydrogen content in the metal was unknown and/or the level of hydrogen uptake was assessed indirectly. In this work, the total hydrogen content in various grades of pipeline steels precharged electrolytically or in gaseous hydrogen was measured using inert gas fusion technique, which can provide quick determination of hydrogen concentration in ppm level utilizing a commercially available and easy-to-use LECO analyzer. This can help to examine the effects of charging methods, charging conditions, and electroplated Pd surface coating on the hydrogen content of the steel specimens. Comparative ex-situ Charpy tests of hydrogen pre-charged specimens have been conducted at room temperature to investigate the hydrogen effects on the impact toughness properties of the steels. The results can help to quantify the influences of hydrogen charging process on hydrogen uptake of pipeline steels and assess their effects on the fracture toughness properties of the steels.

Materials and Experimental Procedures Several grades of pipe steel were tested and showed similar trends but only the results of an X65 pipe steel are presented in this paper due to the page limitation. The X65 steel pipe was from a previous R&D research project and manufactured in 2004, with a yield strength of 428 MPa, outside diameter of 914.4 mm, and wall thickness of 13.7 mm. The main chemical composition (wt%) of the steel is 0.072 C-1.4 Mn0.19 Si-0.037 Al-0.049 Nb-0.033 Ti-0.019 Cu-0.023 Cr. The steel was machined into 5 × 5 × 10 mm specimens for hydrogen measurements using inert gas fusion (LECO) technique and standard 10 × 10 × 55 mm V-notch Charpy specimens as per ASTM E23 [2] for impact fracture toughness tests. The microstructure of the

Hydrogen Content and Charpy Toughness of Pipeline Steels …

1297

steel was characterized using light optical microscopy and the etchant used was a Nital solution containing 4 vol.% nitric acid in ethanol. The X65 pipe steel exhibited a microstructure consistent with the modern steel processes, containing ferrite and bainite/pearlite with round-shaped inclusions. Two types of charging methods were used to pre-charge hydrogen into the steel specimens: electrolytic and gaseous charging. For electrolytic charging, an aqueous solution containing 0.1 M NaOH and 150 mg/L As2 O3 as hydrogen recombination poisoner was used at ambient temperature under galvanostatic conditions. During the electrolytic pre-charging, the steel specimens were subjected to a constant cathodic current in the solution for various durations up to 24 h. To prevent the potential hydrogen damage caused by a high charging current [3], current densities no more than 25 mA/cm2 were used. During gaseous charging, the steel specimens were exposed to 99.9999% pure H2 gas under a pressure of 10.3 MPa (1500 Psi) at room temperature for 2–10 weeks. Prior to hydrogen charging, the surface of the steel specimens was hand polished lightly using 600-grit SiC sandpaper to remove the surface oxide layer, degreased in acetone, rinsed in DI water, and blow dry using an air gun. To prevent hydrogen egress, the specimens were put in liquid nitrogen immediately after hydrogen pre-charging and then transferred to an ONH836 LECO elemental analyzer. For each charging condition, three to four repetitive specimens were examined and the average of measured hydrogen concentrations and standard deviation was reported. The effect of palladium plated surface coating on the hydrogen absorption of the steel specimens was studied. The plating was conducted using a solution bath containing 5 g/L PdCl2 in 28 wt% ammonia aqueous solution [4] under a constant current density of 2.5 mA/cm2 for 5 min. V-notch Charpy impact test has been widely used to qualify toughness of steels and welds (e.g., [5, 6]). In this work, instrumented Charpy tests of pre-charged steel specimens were conducted at ambient temperature using a pendulum machine with a capacity of 750 J. Two to three repetitive specimens were tested for each pre-charging condition. To prevent hydrogen outgassing, the Charpy specimens were transferred and subjected to Charpy impact test within 2 min post electrolytic hydrogen precharging.

Results and Discussion LECO Analysis It is important to distinguish between diffusible and trapped hydrogen when determining hydrogen concentration using various measurement techniques. Techniques such as thermal desorption spectroscopy (TDS) can detect diffusible hydrogen [7, 8], while hydrogen extraction techniques such as LECO measure the total concentration of hydrogen and the sum of trapped and diffusible hydrogen [9, 10]. The results of LECO measurement of total hydrogen content for the X65 specimens pre-charged

1298

X. Pang and S. Xu

electrolytically (Fig. 1) and in gaseous hydrogen (Fig. 2) under different charging conditions are listed in Table 1. An average of around 0.2 ppm hydrogen was measured in the as-received X65 steel specimens without hydrogen pre-charging, which can be ascribed to hydrogen absorption from either the steel production and service processes (e.g., acid pickling and cathodic protection etc.) or the ambient atmosphere during storage. Previous study reported detectable hydrogen uptake in various metals including stainless steel

Fig. 1 Total hydrogen content for X65 specimens electrolytically pre-charged at various current densities for a 1 h and b 24 h, and at c 2.5 mA/cm2 for different time durations Fig. 2 Total hydrogen content for X65 specimens pre-charged in gaseous hydrogen at 10.3 MPa (1500 Psi) for different time durations

Hydrogen Content and Charpy Toughness of Pipeline Steels …

1299

Table 1 Total H content measured by LECO for X65 specimens pre-charged under various conditions Charging method

Electrolytic

Gaseous

Pre-charging conditions Current density (mA/ cm2 )

Time (h)

0

0

Pd coating

Average (individual) hydrogen content (ppm)

No

0.2 (0.3, 0.2, 0.3, 0.1)

1

1

No

0.9 (0.6, 0.9, 1.0, 1.2)

2.5

1

No

1.4 (1.6, 1.8, 1.2, 1.1)

25

1

No

1.2 (1.4, 0.7, 1.4, 1.3)

25

1

Yes

2.8 (2.6, 3.2, 2.8, 2.4)

1

24

No

1.1 (1.1, 1.2, 1.3, 0.9)

2.5

24

No

1.3 (1.1, 1.4, 1.1, 1.4)

2.5

0.25

No

0.7 (1.0, 0.8, 0.4)

Pressure (MPa)

Time (day)

10.3

15

No

0.4 (0.4, 0.3, 0.4, 0.4)

10.3

15

Yes

0.7 (0.8, 0.7, 0.5)

10.3

70

No

0.3 (0.3, 0.3, 0.3)

10.3

70

Yes

0.6 (0.5, 0.7, 0.7)

after a long-term exposure to ambient humid air at room temperature [11]. To confirm this, the as-received X65 steel specimens were baked at 200 °C in flowing N2 environment for 3 h and then stored in a sealed vial filled with N2 gas. The measured hydrogen content of the baked specimens was less than 0.1 ppm or undetectable (i.e., showing negative H-concentration in LECO analysis). It can be seen that even one hour of electrolytic charging was effective to introduce hydrogen into the 5 × 5 × 10 mm specimens of X65 steel. The variation of total hydrogen content with the charging current density for X65 specimens pre-charged for 1 h is given in Fig. 1a. The total hydrogen content increased with the increasing current density and saturated (1.4 ppm) at 2.5 mA/cm2 . A much higher charging current density of 25 mA/cm2 for 1 h did not lead to any further increase in the total hydrogen content and no test with longer charging time was conducted at this current density. The gradual increase in the hydrogen content with the increase of charging current density up to 2.5 mA/cm2 was also observed for specimens charged for 24 h (Fig. 1b). An extension of charging time from 1 to 24 h did not bring significant increase in the hydrogen content in the steel under both 1 and 2.5 mA/cm2 charging current densities (Fig. 1c). When exposed to the same electrolytic charging process (at 25 mA/cm2 for 1 h), the Pd plated X65 specimens showed an average total hydrogen content of 2.8 ppm, while the bare X65 specimens had 1.2 ppm hydrogen on average (Fig. 1a). Similar effect of Pd coating on the hydrogen uptake of the steel was also seen in the gaseous hydrogen charged conditions (Fig. 2). It is worth noting that merely 15 min of electrolytic charging at 2.5 mA/cm2 was able to introduce 0.7 ppm hydrogen into the steel (Fig. 1c), manifesting the

1300

X. Pang and S. Xu

effectiveness of the electrolytic charging method. In contrast, only 0.4 ppm hydrogen was introduced into the X65 steel after 15 days of gaseous charging in 10.3 MPa of high purity hydrogen at room temperature (Fig. 2). In a recent work [12], the diffusible hydrogen was found to be about 0.1 ppm in an X65 pipe steel after gaseous hydrogen charging at a pressure of 25 MPa for 25 h at room temperature. It might be estimated that the trapped hydrogen in the current pipe steel after gaseous charging would be 0.2–0.3 ppm assuming that the same level of diffusible hydrogen was achieved as in [12]. The effect of Pd coating on hydrogen content was also evident in gaseous charging. Further extension of the charging time to 70 days in the gaseous environment did not result in a higher hydrogen content. The effectiveness of the electrolytic charging was also demonstrated in the studies conducted by Atrens and Liu et al. [13, 14] on determination of the hydrogen activity (or pressure) during gaseous hydrogen charging that is equivalent to the hydrogen activity during the electrolytic charging. It was reported that under the most severe charging condition in 0.1 M NaOH solution, the calculated hydrogen fugacity at an overpotential of 0.9 V was 658.6 MPa (6500 atm) [14]. Pd has a strong affinity to hydrogen and promotes hydrogen molecular dissociation on its surface as well as atom diffusion into the bulk [15, 16]. In this work, the application of electroplated Pd surface coating resulted in a considerable increase in the total hydrogen content measured for the steel specimens. With the electroplated Pd coating, the total hydrogen content in the steel specimens almost doubled compared to the uncoated specimens for both charging time durations. However, it must be pointed out that it is unknown whether the hydrogen is uniformly distributed in the Pd coated steel or more hydrogen gathers in the Pd surface layer than in the steel. Further investigation is needed to ascertain the hydrogen distribution in the Pd coated steel. Currently work is also underway to further analyze the diffusible and total hydrogen contents in pipeline steels using thermal desorption spectroscopy (hot extraction technique).

Charpy Test The results of the Charpy impact tests at ambient temperature for electrolytically precharged X65 specimens are summarized in Table 2. The average Charpy absorbed energy (CVN) values for the pipeline steel specimens under different pre-charging conditions are plotted in Fig. 3, where the error bars show the CVN variation range of the repetitive specimens. It can be seen from Fig. 3 that the hydrogen pre-charged into the X65 steel led to obviously reduced Charpy toughness of the steel. The effect aggravated with an increase in charging current density (Fig. 3a) and charging time (Fig. 3b), and saturated at around 2.5 mA/cm2 of charging current density and 5 h of charging time. It should be noted that the results of LECO measurements showed that the total hydrogen content in the steel also increased with the charging current density (Fig. 1a, b) and charging time (Fig. 1c), but reached saturation at 2.5 mA/ cm2 and 1 h. The hydrogen resulted in approximately maximum 20% decrease in

Hydrogen Content and Charpy Toughness of Pipeline Steels …

1301

CNV for the steel. Further increase of charging time to 24 h and charging current density to 20 mA/cm2 did not result in any further degradation of Charpy toughness for X65 steel. These trends agreed well with the results of the LECO analysis of the electrolytically pre-charged X65 specimens. The discrepancy in the pre-charging time needed to reach the saturation (i.e., 1 h for LECO vs. 5 h for Charpy) can be attributed to the different sample geometry and dimensions for the LECO and Charpy tests. The results are generally in agreement with the effect of hydrogen on tensile curve, i.e., hydrogen has little effect on strengths before necking [17]. However, as impact loading decreases the effect of hydrogen embrittlement, slow-rate in-situ tests would be more suitable than ex-situ tests at impact rates for quantifying the hydrogen effect on toughness of pipeline steels, because under normal operational conditions pipelines are exposed to pressure loading similar to the in-situ slow-rate loading. The development of three-point bend testing facility and procedures with in-situ electrolytic hydrogen charging capacity is currently underway at the authors laboratory. Table 2 Charpy impact test data for X65 steel specimens pre-charged under difference conditions Steel grade Pre-charging current density Pre-charging time (h) Average (individual) Charpy (mA/cm2 ) absorbed energy CVN (J) X65

0

0

234 (233, 237, 233)

1.0

24

201 (205, 196)

2.5

24

188 (194, 182)

20.0

24

192 (188, 195)

2.5

1

207 (215, 199)

2.5

5

192 (192, 191)

Fig. 3 Charpy absorption energy for X65 steel specimens a pre-charged for 24 h as a function of pre-charging current density and b pre-charged at 2.5 mA/cm2 as a function of pre-charging time

1302

X. Pang and S. Xu

Conclusions The effects of charging methods, charging conditions, and electroplated Pd surface coating on the hydrogen content of the specimens were studied. Ex-situ Charpy tests have been conducted at room temperature to investigate the hydrogen effects on the impact fracture toughness properties of the steels. Following conclusions can be drawn: 1. The inert gas fusion (LECO) analysis showed that an average of approximately 0.2 ppm hydrogen existed in the as-received X65 steel specimens without hydrogen pre-charging, which can be ascribed to hydrogen absorption from either the steel production or service processes. 2. Electrolytic pre-charging in 0.1 M NaOH with 150 mg/L As2 O3 at 2.5 mA/cm2 was effective for introducing hydrogen into X65 pipeline steel. Results of LECO analysis showed that an average of 1.4 ppm total hydrogen in X65 was seen for specimens pre-charged at 2.5 mA/cm2 for 1 h. Further increase of charging current density and time did not result in noticeable increase in the hydrogen content. The electrolytic charging method was a more aggressive charging condition than the gaseous charging technique. 3. Pd electroplated surface coating promoted hydrogen absorption into the steel and led to doubled total hydrogen content under both electrolytic and gaseous hydrogen charging conditions. However, further investigation is needed to ascertain the hydrogen distribution in the Pd coated steel. 4. Ex-situ Charpy tests of electrolytically pre-charged X65 specimens at room temperature showed approximately maximum 20% reduction in CVN compared to uncharged specimens. The results could be correlated with the hydrogen content after pre-charging. The discrepancy in the pre-charging time needed to reach the saturation effect (i.e., 1 h for LECO vs. 5 h for Charpy) can be attributed to the different sample geometry and dimensions for the LECO and Charpy tests. Acknowledgements Financial support from the Hydrogen Codes and Standards R&D program, Office of Energy Research and Development (OERD), and Natural Resource of Canada (NRCan) is gratefully acknowledged. The authors would like to express their appreciation to David Saleh, Jie Liang, Magdalene Matchim, Chao Shi, and Renata Zavadil of CanmetMATERIALS, NRCan for their technical assistance.

References 1. https://www.nrcan.gc.ca/climate-change-adapting-impacts-and-reducing-emissions/canadasgreen-future/the-hydrogen-strategy/23080 2. ASTM E23-18 (2018) Standard test methods for notched bar impact testing of metallic materials. ASTM International, West Conshohocken, PA

Hydrogen Content and Charpy Toughness of Pipeline Steels …

1303

3. Escobar DP, Minambres C, Duprez L, Verbeken K, Verhaege M (2011) Internal and surface damage of multiphase steels and pure iron after electrochemical hydrogen charging. Corros Sci 53:3166–3176 4. Vucko F, Bosch C, Aoufi A, Delafosse D (2014) Palladium coating on quenched-tempered martensitic steel for hydrogen electrochemical permeation tests. Research report # ENSMSESMS-2014-01, http://hal-emse.ccsd.cnrs.fr/emse-00951142v2 5. (2018) CSA Z245.1-18, Steel pipe. Canadian Standards Association 6. (2018) API specification 5L, line pipe, 46th edn. American Petroleum Institute 7. Rudomilova D, Prosek T, Luckeneder G (2018) Techniques for investigation of hydrogen embrittlement of advanced high strenght steels. Corros Rev 36:413–434 8. Gangloff RP Somerday BP (eds) (2012) Gaseous hydrogen embrittlement of materials in energy technologies. In: Volume 2: Mechanisms, modelling and future developments. Woodhead Publishing Limited, Cambridge 9. Evers S, Senoz C, Rohwerder M (2013) Hydrogen detection in metals: a review and introduction of a Kelvin probe approach. Sci Technol Adv Mater 14:014201 10. Ha HM, Ai J-H, Scally JR (2014) Effects of prior cold work on hydrogen trapping and diffusion in API X-70 line pipe steel during electrochemical charging. Corrosion 70(2):166–184 11. Hultquist G, Graham MJ, Smialek JL, Jonsson B (2015) Hydrogen in metals studied by Thermal Desorption Spectroscopy (TDS). Corros Sci 93:324–326 12. Ishikawa N, Shimamura J, Izumi D, Okano H, Nishihara Y (2022) Hydrogen effect on linepipe steel and material compatibility to a high-pressure hydrogen pipeline. Int J Offshore Polar Eng 32(4):448–456 13. Atrens A, Mezzanotte D, Fiore NF, Genshaw MA (1980) Electrochemical studies of hydrogen diffusion and permeability in Ni. Corros Sci 20(5):673–684 14. Liu Q, Atrens AD, Shi Z, Verbeken K, Atrens A (2014) Determination of the hydrogen fugacity during electrolytic charging of steel. Corros Sci 87:239–258 15. Conrad H, Ertl G, Latta EE (1974) Adsorpton of hydrogen on palladium single crystal surfaces. Surf Sci 41:435–446 16. Schwarzer M, Hertl N, Nitz F, Borodin D, Fingerhut J, Kitsopoulos TN, Wodtke AM (2022) Adsorption and absorption energies of hydrogen with palladium. J Phys Chem C 126:14500– 14508 17. Xu K (2012) Hydrogen embrittlement of carbon steels and their welds. In: Gaseous hydrogen embrittlement of materials in energy technologies, vol 1. Woodhead Publishing, Oxford, pp 526–561

Part XXXIV

Fatigue in Materials: Fundamentals, Multiscale Characterizations and Computational Modeling

The Effect of Injection-Production Process Parameters on the Fatigue Life of High-Pressure Injection-Production String Lihua Wan, Zhihuan Wang, Songyuan Ai, Haohao Zhang, Rundong Zhang, Mujun Long, Huamei Duan, and Dengfu Chen

Abstract During the operation of underground gas storage, the periodic internal pressure fluctuations in high-pressure injection-production string have a significant impact on the fatigue life of the string. This study established a localized fatigue simulation model for the injection-production string and investigated the effects of factors such as average internal pressure, alternating load amplitude and frequency, and wall thickness reduction on fatigue life. The results indicate that as the average internal pressure, alternating load amplitude and frequency, and wall thickness reduction increase, the fatigue life of the string diminishes. Among these factors, the average internal pressure has the greatest influence on the fatigue life. When the average internal pressure increases from 20 to 45 MPa, the fatigue life decreases from 6.999 × 1013 cycles to 4.984 × 105 cycles. The research findings provide a theoretical basis for optimizing the injection-production process of underground gas storage and preventing fatigue failure in the string. Keywords Fatigue life · Injection-production string · Alternate load · Finite element simulation

Introduction Underground gas storage (UGS) is an artificial gas field formed by re-injecting natural gas into underground spaces, offering advantages such as large storage capacity, high flexibility, and a wide range of peak shaving capabilities [1]. Due to the significant role played by UGS in energy supply–demand balancing, it has witnessed rapid L. Wan · Z. Wang · S. Ai · H. Zhang · R. Zhang · M. Long (B) · H. Duan · D. Chen Laboratory of Materials and Metallurgy, College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China e-mail: [email protected] National Key Laboratory of Advanced Casting Technologies, Shenyang 110000, China © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_113

1307

1308

L. Wan et al.

development both in recent years [2, 3]. The injection-production string, as a critical component for gas transportation, plays a crucial role in ensuring the safety, stability, and sustainable supply of the UGS [4]. However, during the cyclic operation of gas injection and withdrawal in UGS, the injection-production string constantly endures alternating loads generated by pressure fluctuations in a complex operational environment [5, 6]. This places higher technical requirements on the reliability and risk control of the injection-production string. Therefore, conducting safety assessments on the injection-production string is of significant importance. Currently, many researchers have conducted relevant studies on the safety assessment of injection-production strings. For example, Wang et al. [5] conducted experimental studies on the mechanical properties and sealing performance of the threaded connections of injection-production string under cyclic loading. The results showed that after multiple cycles of loading, the mechanical properties such as yield strength decreased, and leakage may occur during the service life of the string. Ma et al. [7] used a three-dimensional vector method to establish a three-dimensional equivalent axial force model for the injection-production string, effectively addressing the issue of mechanical detection of the string. Cai et al. [8] conducted an analysis and research on the corrosion behavior of 13Cr110 injection-production string using methods such as corrosion simulation and corrosion morphology analysis, and proposed recommendations for controlling corrosion on the outer surface of the string. However, there is limited research on the fatigue failure of injection-production string during the gas injection-production process, especially the lack of studies on the fatigue performance changes of the string under different operating conditions. Therefore, accurately analyzing and predicting the fatigue life of injection-production string under different operating conditions is of utmost importance. Traditional durability fatigue testing is an accurate and effective method for predicting fatigue life. However, the fatigue type of injection-production string belongs to high-cycle fatigue. The fatigue testing under different conditions is timeconsuming and requires a significant amount of material and financial resources. In comparison, finite element fatigue simulation enables convenient modeling of fatigue behavior under various operating conditions and is more cost-effective. Therefore, this paper conducted a static structural analysis of the local injection-production string using Ansys Workbench and performed fatigue life assessment of the string under different operating conditions using nCode Designlife. The study summarized the impact patterns of various process parameters on the fatigue life of the string, providing a scientific basis for optimizing the injection-production process of UGS and preventing fatigue failure of the string.

The Effect of Injection-Production Process Parameters on the Fatigue …

1309

Fig. 1 Finite element model of the injection-production string

Table 1 Material parameters of the injection-production string Steel grade

Density (g cm−3 )

Poisson’s ratio

Young’s modulus (GPa)

Tensile yield strength (MPa)

Tensile ultimate strength (MPa)

J55

7.85

0.3

210

410

517

Finite Element Model Model Simplification and Material Selection When studying the fatigue life of injection-production string in the actual service environment of UGS, the following assumptions can be made [9]: (1) The study focuses on independent injection-production string in a shallow well area, and it is assumed to be a hollow cylindrical shape of a certain length, with a smooth and defect-free surface. (2) Only the internal gas pressure is considered as the external load acting on the injection-production string, thus the string is subjected to hoop stress without considering other factors such as axial stress, bending moment, and temperature. (3) The alternating load caused by pressure fluctuations within the string can be simplified as a sinusoidal load with constant amplitude. The modeling of the injection-production string was performed using the Spaceclaim module available in Ansys Workbench. The solid model of the string, as shown in Fig. 1, has the following geometric parameters: outer diameter of 89.0mm, wall thickness of 6.45mm, and length of 500mm. The simulation material used is J55 steel grade commonly used in shallow well areas, and its material parameters are listed in Table 1.

Meshing and Boundary Condition Settings As the string model is a regular geometric cylinder, an adaptive hexahedral mesh was employed using Ansys Workbench. Reasonable element size can enhance the accuracy of simulation results while reducing computational time. To obtain optimal element size and minimize the error in simulation results, a sensitivity analysis of element size, as shown in Fig. 2, was conducted. The maximum equivalent stress and fatigue life under an internal pressure of 30 MPa were used as evaluation criteria.

1310

L. Wan et al.

Fig. 2 Element t size sensitivity analysis of the injection-production string finite element model

When the element size decreased to 2 mm, its impact on the maximum equivalent stress and fatigue life became insignificant. Therefore, a 2 mm element size was chosen for this study. The final mesh division of the model consisted of 531,412 nodes and 108,181 elements. As the string model is a regular geometric cylinder, an adaptive hexahedral mesh was employed using Ansys Workbench. Reasonable element size can enhance the accuracy of simulation results while reducing computational time. To obtain optimal element size and minimize the error in simulation results, a sensitivity analysis of element size, as shown in Fig. 2, was conducted. The maximum equivalent stress and fatigue life under an internal pressure of 30 MPa were used as evaluation criteria. When the element size decreased to 2 mm, its impact on the maximum equivalent stress and fatigue life became insignificant. Therefore, a 2 mm element size was chosen for this study. The final mesh division of the model consisted of 531,412 nodes and 108,181 elements.

Fatigue Life Prediction Study of the Injection-Production String Basic Process of Fatigue Analysis This paper utilizes nCode DesignLife software for fatigue life analysis. Figure 3 shows the basic process of fatigue life analysis, which involves obtaining the finite element static analysis results from Ansys Workbench, importing them into the FE input module of nCode DesignLife, setting up load spectra and material fatigue life

The Effect of Injection-Production Process Parameters on the Fatigue …

1311

Fig. 3 Basic flowchart of fatigue life analysis

curves, selecting a suitable fatigue analysis engine, and ultimately obtaining the corresponding fatigue life prediction results.

Time Series Load Spectrum Load spectrum defines the variation of pressure inside the injection-production string and is an important factor affecting material fatigue life. In this study, a time series load spectrum as shown in Fig. 4 is selected. The time series load channel is associated with the finite element static analysis results from Ansys Workbench, and the stress load history is created by proportionally or linearly superimposing them using the following equation. σi j (t) =

(P(t)S + O)σi j,static , d

(1)

where σi j (t) represents the time-dependent stress tensor, P(t) is the load multiplier of the time series load channel; S is the scaling factor (default value is 1); O is the offset value (default value is 0), and d is the proportion control parameter for the total load (default value is 1).

Setting and Modification of S–N Curves Currently, there are two commonly used methods for fatigue analysis: one is the nominal stress method based on stress-life curve (S–N curve), and the other is the local stress–strain method based on strain-life curve (ε–N curve). The former is

1312

L. Wan et al.

Fig. 4 Time series load spectrum

suitable for high-cycle fatigue, while the latter is suitable for low-cycle fatigue. The fatigue mode of the high-pressure injection-production string belongs to high-cycle fatigue, therefore the S–N stress fatigue solver engine is selected in nCode. To accurately assess the high-cycle fatigue life of the injection-production string, it is necessary to obtain the S–N curve of the material for fatigue calculations. This can be achieved by creating the J55 material in the Material Mapping section of the StressLife Analysis and inputting material properties such as tensile strength. Due to the non-symmetric constant-amplitude cyclic loading on the injection-production string, the average stress needs to be corrected using the Goodman correction model. The modified S–N curve of the J55 material is shown in Fig. 5.

Stress Analysis of the Injection-Production String Figure 6 shows the equivalent stress contour plots of the injection-production string at an average pressure of 30 MPa. From the cross-section of the injection-production string in Fig. 6, it can be observed that the distribution of the equivalent stress forms a circular ring shape. The maximum equivalent stress occurs at the inner wall of the string with a value of 209.65MPa, which is lower than the yield strength of the J55 material (410 MPa).

The Effect of Injection-Production Process Parameters on the Fatigue …

1313

Fig. 5 Modified S–N curve of the J55 material

Fig. 6 Equivalent stress contour plots of the injection-production string

Fatigue Analysis of the Injection-Production String The static analysis results from Ansys Workbench were imported into the nCode Designlife, and with the configuration of various module parameters, the fatigue life and fatigue damage contour plots were obtained for an average pressure of 30MPa, load spectrum amplitude of 0.3, and frequency of 10 Hz, as shown in Fig. 7. It is observed that the minimum fatigue life and the maximum fatigue damage of the injection-production string occur at the inner wall. This is due to direct contact between the inner wall of the string and the alternating load, leading to cumulative

1314

L. Wan et al.

Fig. 7 Fatigue analysis results of the injection-production string. a Fatigue life; b fatigue damage

damage and the initiation of fatigue cracks. Additionally, the reciprocal relationship between the maximum fatigue damage value of 6.463 × 10–10 and the minimum fatigue life of 1.547 × 109 complies with the principles of fatigue analysis. In order to provide more design and maintenance strategies for the injectionproduction string and improve the performance and sustainable operation of underground gas storage system, further exploration is needed on the influence patterns of average pressure, amplitude and frequency of alternating loads, as well as the impact of wall thickness reduction on the fatigue performance of the injection-production string.

Results and Discussion The Influence of Average Pressure on the Fatigue Life of the Injection-Production String The variation in average pressure affects the maximum equivalent stress and fatigue life of the injection-production string. In this study, under a load spectrum amplitude of 0.25 and frequency of 10 Hz, six sets of average pressure levels were respectively assigned within the range of 20–45 MPa. The influence curves of average pressure on the fatigue life and maximum equivalent stress of the injection-production string were obtained through simulation calculations. The results are presented in Fig. 8. As the average pressure increases, the maximum equivalent stress shows a linear increasing trend, while the fatigue cycle number significantly decreases. When the average pressure reaches 45 MPa, the maximum equivalent stress is 314.47 MPa, and the fatigue cycle count is only 4.984 × 105 cycles. Therefore, during the operation of

The Effect of Injection-Production Process Parameters on the Fatigue …

1315

Fig. 8 Influence curves of average pressure on the fatigue life and maximum equivalent stress of the injection-production string

UGS, it is advisable to avoid prolonged operation of the injection-production string under high average pressure levels in order to extend its fatigue life.

The Influence of Alternating Load Amplitude and Frequency on the Fatigue Life of the Injection-Production String Pattern of alternating amplitude and frequency on the fatigue life of the injectionproduction string was obtained. The results are shown in Fig. 9. It can be observed that for a constant alternating frequency, the fatigue life of the injection-production string significantly decreases as the load spectrum amplitude increases. When the frequency is 10Hz and the amplitude increases from 0.15 to 0.40, the fatigue cycle count decreases from 2.434 × 1013 cycles to 2.804 × 107 cycles. At an amplitude of 0.10, the fatigue life is the same for different alternating frequencies. This is because the stress amplitude caused by the low alternating amplitude is lower than the fatigue strength of the J55 material, which is insufficient to cause fatigue damage and the fatigue cycle count reaches its maximum value for all three alternating frequencies. For other amplitude levels, the alternating frequency and fatigue cycle count are inversely proportional. To improve the reliability and service life of the injection-production system in UGS, engineers and operators should pay attention to controlling the fluctuation level of pressure inside the string to reduce the impact of fatigue damage on its fatigue life.

1316

L. Wan et al.

Fig. 9 Influence curves of alternating amplitude and frequency on the fatigue life of injectionproduction string

The Influence of Wall Thickness Reduction on the Fatigue Life of Injection-Production String High-pressure injection-production strings operating in corrosive environments are prone to defects such as wall thickness reduction and corrosion pits due to long-term erosion by high-speed gas flow, resulting in a significant decrease in the fatigue life of the strings[10]. This study assumes that the overall wall thickness reduction of the string varies within the range of 0%–25% and is divided into six levels. The impact of wall thickness reduction on the fatigue life of the injection-production string was studied through simulation calculations under the operating conditions of an average pressure of 30 MPa, a load spectrum of 0.25, and a frequency of 10 Hz. The results are presented in Fig. 10. When the wall thickness reduction reaches 25%, the fatigue cycle count decreases from the original 1.965 × 1010 cycles to 1.029 × 107 cycles. This phenomenon can be attributed to the stress concentration and cumulative fatigue damage caused by wall thickness reduction. Operators of UGS can take measures such as optimizing pipe column design, using appropriate materials, strengthening monitoring and maintenance, to reduce the damage of wall thickness thinning on the fatigue life of the string.

The Effect of Injection-Production Process Parameters on the Fatigue …

1317

Fig. 10 Influence curve of wall thickness reduction on the fatigue life and maximum equivalent stress of the injection-production string

Conclusion This paper focuses on the local injection-production string of UGS. Static structural analysis of the string was conducted using Ansys Workbench, and fatigue life assessment was performed using nCode Designlife. The study investigated the impact of average pressure, cyclic load amplitude and frequency, as well as wall thickness reduction on the fatigue life of the string. The conclusions are as follows: (1) With the increase in average pressure, cyclic load amplitude and frequency, and wall thickness reduction, the fatigue life of the injection-production string decreases. Among these factors, average pressure has the greatest impact, and higher levels of average pressure significantly damage the fatigue life of the injection-production string. (2) The amplitude of the cyclic load has a greater impact on the fatigue life of the injection-production string compared to the frequency. Specifically, when the amplitude increases from 0.15 to 0.40, the fatigue cycle count decreases from 2.434 × 1013 cycles to 2.804 × 107 cycles. (3) When the wall thickness reduction reaches 25%, the fatigue cycle count decreases from the original 1.965 × 1010 cycles to 1.029 × 107 cycles, indicating that wall thickness reduction causes certain damage to the fatigue life of the injection-production string. Acknowledgements The study is supported by the Chongqing Talents Plan for Young Talents (Project No. cstc2021ycjh-bgzxm0227).

1318

L. Wan et al.

References 1. Xue W, Wang Y, Chen Z, Liu H (2023) An integrated model with stable numerical methods for fractured underground gas storage. J Clean Prod 393:136268 2. Zhang J, Tan Y, Zhang T, Yu K, Wang X, Zhao Q (2020) Natural gas market and underground gas storage development in China. J Energy Storage 29:101338 3. Zhang S, Yan Y, Sheng Z, Yan X (2021) Uncertainty failure risk quantitative assessments for underground gas storage near-wellbore area. J Energy Storage 36:102393 4. Ma X, Wang Z (2020) Injection and production string design. In: Handbook of underground gas storages and technology in China. pp 1–19 5. Wang J-J, Sui X-F, Jia S-P, Hua Z-Z, Wang S-Y (2022) Experimental study on sealing failure mechanism of injection-production string in underground gas storage under cyclic loading. Adv Mater Sci Eng 6. Xinhua M, Zheng D, Ruichen S, Chunyan W, Jinheng L, Junchang S (2018) Key technologies and practice for gas field storage facility construction of complex geological conditions in China. Pet Explor Dev 45(3):507–520 7. Ma S, Wang H, Lan W, Jiang H, Liu Y, Che J, Wei Z, Gong Z (2023) Mechanical detection system for injection production string in oil and gas wells with high temperature and high pressure. IEEE/ASME Transactions on Mechatronics 8. Cai R, Gui J, Li M, Zhao B, Bai X, Cheng G (2021) Corrosion reason analysis of 13Cr110 tubing in an injection and production well of the Suqiao gas storage group. Int J Photoenergy 2021:1–12 9. Wang Z, Ma X, Fan X, HY (2019) Study of residual strength of X80 pipe used steel with flat bottom square. Process Equip Pip 56(1):70–75 10. Zhang S, Yan Y, Shi L, Li L, Zhao L, Wang R, Yan X (2021) A semi-empirical model for underground gas storage injection-production string time series remaining useful life analysis in process safety operation. Process Saf Environ Prot 154:1–17

Part XXXV

Formability and Spring-Back Issues in Ultra-High Strength Steels and High Strength Aluminum Alloys

Influence of Yoshida-Uemori Model on Springback Prediction X. Lemoine and J. M. Devin

Abstract Today, the advanced hardening Yoshida-Uemori model is recommended for an improved springback prediction in stamping numerical simulation. This model is a combined hardening model coupled with the elastic evolution modulus8 which depends on the equivalent plastic strain. It is implemented in the most used FEA stamping codes with occasionally some variations. In order to provide material cards for the FEA stamping codes, ArcelorMittal has at one’s disposal the equipment to perform reverse shear tests and hysteresis loops. An in-house methodology has been developed to identify the Yoshida-Uemori adjusting parameters. The developed identification protocol leads to a set of material parameters improving the springback prediction compared to a purely isotropic hardening model. The results analysis shows that the elastic modulus evolution has an influence on springback prediction of the same order as the combined hardening. A solution is proposed here to improve the elastic modulus evolutive model according to the final stress state after springback. Keywords Isotropic hardening · Kinematic hardening · Steel · Springback

Introduction Today, the advanced hardening Yoshida-Uemori model [1–3] is recommended for an improved springback prediction in stamping numerical simulation [4–7]. This model is a combined hardening model coupled with the elastic evolution modulus which depends on the equivalent plastic strain. It is implemented in the most used FEA stamping codes (Autoform® , Pamstamp® , LS-Dyna® , etc.) with occasionally some variations [8, 9]. X. Lemoine (B) Global R&D ArcelorMittal Maizières, voie Romaine, BP30320, F-57283 Maizières-lès-Metz, France e-mail: [email protected] J. M. Devin Global R&D ArcelorMittal Montataire, 1 Route de Saint-Leu, F-60160 Montataire, France © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_114

1321

1322

X. Lemoine and J. M. Devin

In order to provide material cards for the FEA stamping codes for its steel grades, ArcelorMittal has at one’s disposal the equipment to perform reverse shear tests and hysteresis loops for all steel grades. An in-house methodology has been developed to identify the Yoshida-Uemori adjusting parameters in a very precise, robust, and reproductible manner. According to experimental observations, the developed identification protocol leads to a set of material parameters improving the springback prediction compared to a purely isotropic hardening model. The results analysis shows that the elastic modulus evolution has an influence on springback prediction of the same order as the combined hardening [10]. The Yoshida-Uemori elastic modulus evolution model corresponds currently to a linear approximation of a nonlinear unloading whose final value is zero stress. However, numerical predictions of a stamped part show that less than 5% of the integration points have a stress close to zero after springback [11]. A solution is proposed here to improve the elastic modulus evolutive model according to the final stress state after springback.

Identification Procedures Hysteresis loops, uniaxial tensile and shear tests (monotonous and reverse) are used to get experimentally the data needed for the identification of the Yoshida-Uemori model parameters: hysteresis loop for evolutive elastic modulus model; uniaxial tensile and shear tests for combined hardening Yoshida-Uemori model.

Parameter’s Identification of Evolutive Elastic Modulus Model The hysteresis loops (Fig. 1a) between 0.2% of plastic deformation and uniform elongation (UEL), by steps of 1%, are realized to capture the evolution of elastic modulus with plastic pre-strain. The strain is measured with a high-resolution Zwick® digiClip extensometer as per Annex G of ISO 6892-1 standard. For each loop, there are several ways to define an unloading elastic module: • Deduction from the linear regression on unloading path between the points A (maximal stress at the beginning of the loop) and B (minimal stress of loop) (red curve in Fig. 1b) [10]. • Chord slope (segment [DB]) (black dotted curve in Fig. 1b) [12]. • Average of instantaneous modulus resulting from a polynomial regression of second degree on unloading path between the points A and B (or in a sub-range of the unloading path: for example, the middle third).

Influence of Yoshida-Uemori Model on Springback Prediction

1323

Fig. 1 Hysteresis loops are used to identify of the elastic evolution modulus Yoshida model parameters: a Hysteresis loop (orange curve) conducted every 1% until the end of the uniform elongation; b Elastic modulus following two definitions: linear regression on unload path (red curve), chord slope (black curve); c Experimental points (blue dots) versus elastic modulus evolution model (red line) for a Fortiform® 980 steel (E 0 = 200 GPa, E a = 157 GPa and ξ = 42.85); d Evolution of elastic modulus for the four definitions [11]

Fig. 2 Reverse shear tests are used to identify of the hardening Yoshida-Uemori model parameters

1324

X. Lemoine and J. M. Devin

Table 1 Parameters identified for four definitions (Fortiform® 980 steel), E 0 = 200 GPa Chord [DB]

Linear regression [AB]

Average of instantaneous modulus [AB]

Middle third of [AB]

E a (GPa)

154

157

160

156

ξ

38.94

42.85

42.13

40.82

The two adjusting parameters E a and ξ are fitted according to a gradient method (red curve on Fig. 1c) in order to get the better correspondence between Eq. (1) and experimental results derived from hysteresis loops tests (blue points). E( p) = E 0 − (E 0 − E a )(1 − exp(−ξ p)),

(1)

where E 0 is initial Young’s modulus; E a and ξ are two material parameters, and p is equivalent plastic strain. The parameters identified for each definition are presented in Table 1. Four definitions proposed lead to a difference of elastic modulus of about 6 GPa (Fig. 1d).

Parameter’s Identification of Combined Hardening Model Identification loop has been developed and validated for an accurate fitting of the Yoshida-Uemori material parameters. The target is to fit at the same time: (a) the four experimental curves obtained from shear tests and (b) the mechanical characteristics of the uniaxial tensile test: yield stress, ultimate tensile strength, uniform elongation, and hardening coefficient n. The reasons of reverse shear tests (Fig. 2) are: (1) no limitation due to diffuse necking like with tension–compression tests, (2) buckling limit of thin sheets is observed later compared to a compression test, and (3) very large plastic deformation, representative of strain levels in stamping, can be reached. The identification loop is based on the direct solving of the Yoshida-Uemori equations for uniaxial loads. It uses optimization methods proposed in LS-OPT software. Very accurate results are got (Fig. 3).

Interest of Using Yoshida-Uemori Model for Springback Prediction For a Fortiform® 980 steel, springback predictions of nine parts with PamStamp® 2022 with three configurations of elastic modulus confirm the interest of using Yoshida-Uemori model: one configuration with the elastic modulus evolution and two others with a constant elastic modulus (either 200 GPa or 150 GPa) (Fig. 1c). The impact of the elastic modulus evolution with cumulative plastic strain

Influence of Yoshida-Uemori Model on Springback Prediction

1325

Fig. 3 Identification loop for production of PamStamp and LS-DYNA material cards applied to Fortiform® 980

varies according to the stamping parts (Tables 2 and 3). Some parts with very weak impact like the front side-rail part: the value remains close to 200 GPa because cumulative plastic strain is low after stamping ( n > 3 indicates site saturation plus Avrami nucleation as the nucleation mechanism. The solid fraction and time relationship curves of the experimental steels were analyzed with the equation above, and the fitting results are shown in Fig. 3. According to Fig. 3, the rate constant k and Avrami exponent n of the S1 steel were 7.59 × 10–5 and 2.77, respectively. S1 steel was the site saturation nucleation owing to the Avrami exponent being less than 3. After the addition of 0.002% Ce, the Avrami exponent n of the S2 steel was 2.6, which was still less than 3. The nucleation mechanism did not change. Nevertheless, the rate constant k was increased to 5.68 × 10–4 . After cerium treatment, the velocity of transformation from liquid to solid phase during the solidification was increased, resulting in a dramatic reduction in the solidification time.

Effect of Cerium on Solidification Nucleation and Microstructure Due to the fact that inclusion could act as the core of heterogeneous nucleation, it is an essential factor affecting the solidification nucleation. The EDS spectrums

1406

F. Huang and J. Li

and element mappings of typical inclusions in the experimental steels are shown in Fig. 4. It can be seen that the typical inclusions in the S1 steel were mainly CaS and CaS+MgAl2 O4 . CaS inclusions were spherical or long strip, as shown in Fig. 4a, b. As shown in Fig. 4c, d, the shape of the CaS+MgAl2 O4 complex inclusions was irregular. After the addition of rare earth, the typical inclusions in the S2 steel were modified to CeAlO3 +CaS and Ce2 O2 S+CaS complex inclusions, as shown in Fig. 4e–h. From SEM-EDS determination, the area brighter than the steel matrix of the complex inclusions was Ce-containing inclusions, and that darker than the matrix was CaS. The complex inclusions were spherical or ellipsoidal in shape and 1–2 μm in size. To identify the effect of Ce on the size and number of inclusions, the average size and number density of inclusions in the experimental steels were counted and the results are shown in Fig. 5. As can be seen from Fig. 5, the average size of the inclusions decreased from 2.83 to 1.56 μm, and the number density increased from 46.21 to 64.85 mm−2 after adding Ce. The results demonstrated that Ce could significantly refine the inclusions in the steel [18, 19] and increase the number of these inclusions. During solidification, the liquid phase transformed into the δ-Fe and γ-Fe phases. Thus, the effect of CaS, MgAl2 O4 , CeAlO3, and Ce2 O2 S on the promotion of δ-Fe and γ-Fe formation by heterogeneous nucleation was investigated. The possibility of the inclusions acting as the heterogeneous cores could be determined in terms of

Fig. 4 SEM images and EDS results of the typical inclusions observed in the experimental steels: a–d S1 steel; e–h S2 steel

Effect of Cerium on the Nucleation and Microstructure of High-Strength …

1407

Fig. 5 Number density and average size of inclusions in the experimental steels

the disregistry between the inclusions and the nucleated phases. The disregistry was calculated based on the Bramfitt disregistry theory model, as shown in the following equation [20]. (hkl) δ(hkl)ns

=

3  i=1

|d[uvw]is cos θ −d[uvw]in | d[uvw]in

3

× 100

(2)

where i is the three lowest-index directions within 90° of the nucleated solid and substrate planes; (hkl)s/n is the low-index plane of the substrate/nucleated solid; [uvw]s/n is the low-index direction of (hkl)s /(hkl)n ; d[uvw]s/n is the interatomic spacing along [uvw]s /[uvw]n ; θ is the angle between the [uvw]s and [uvw]n . Table 2 presents the relevant parameters and results of the disregistry calculation between inclusions and δ-Fe/γ-Fe on the basis of Eq. (2). In accordance with Bramfitt disregistry theory, the substrate could effectively promote the nucleation of the nucleated solid with the disregistry of less than 12%. As can be seen in Table 2, the disregistry results between CeAlO3 /Ce2 O2 S inclusions and δ-Fe/γ-Fe phases were all less than 12% compared to CaS and MgAl2 O4 inclusions. Therefore, the generated rare earth inclusions after Ce treatment were effective in promoting the heterogeneous nucleation of δ-Fe and γ-Fe during solidification [21, 22]. Furthermore, the addition of Ce increased the number of inclusions and decreased their size. Ultimately, the number of effective nucleation cores in the liquid steel increased, causing the nucleation site density to increase considerably. Figure 6 shows the inverse pole figure (IPF) maps and average grain size of the S1 and S2 steel analyzed via EBSD. Compared to the Ce-free steel, the grain distribution of the Ce-containing steel was more uniform, as shown in Fig. 6a, b. According to Fig. 6c, the average grain size decreased by 10.03% from 13.76 to 12.38 μm after adding Ce. Rare earth can play a role in the refinement of grains [23].

1408

F. Huang and J. Li

Table 2 The disregistry calculation parameters and results between inclusions and δ-Fe/γ-Fe Substance

Lattice parameter/nm

Orientation

Disregistry results

δ-Fe

a = 0.29315

–

–

γ-Fe

a = 0.3681

–

–

CaS

a = 0.5622

(111) CaS // (111) δ-Fe

4.11%

(111) CaS // (111) γ-Fe

52.73%

MgAl2 O4

a = 0.8085

(111) MgAl2 O4 // (111) δ-Fe

37.90%

(111) MgAl2 O4 // (111) γ-Fe

119.64% 9.14%

CeAlO3

a = b = 0.3767, c = 0.3797

(100) CeAlO3 // (100) δ-Fe (100) CeAlO3 // (100) γ-Fe

2.34%

Ce2 O2 S

a = b = 0.401, c = 0.683

(0001) Ce2 O2 S // (111) δ-Fe

3.27%

(0001) Ce2 O2 S // (100) γ-Fe

10.50%

Fig. 6 IPF color maps and average grain size of the experimental steels: a IPF color map of the S1 steel (0 Ce); b IPF color map of the S2 steel (0.002% Ce); c Average grain size of the experimental steels with different Ce contents

Effect of Cerium on the Nucleation and Microstructure of High-Strength …

1409

On the basis of the above results, the mechanism of the influence of Ce on the solidification nucleation and microstructure was defined. Without the addition of Ce, the inclusions in the S1 steel were CaS and MgAl2 O4 , which were not effective in inducing the solidification nucleation. The velocity of solidification phase transformation was slow, and the time for grain growth was sufficient, resulting in the large grains in the solidification microstructure. After Ce treatment, the inclusions in the S2 steel were modified to CeAlO3 and Ce2 O2 S, and their disregistries with δ-Fe or γ-Fe were all less than 12%. At the initial stage of solidification, the large number of fine rare earth inclusions increased the amount of δ-Fe, providing more effective nucleation sites for the formation of γ-Fe in the subsequent peritectic reaction and facilitating the reaction [24]. Meanwhile, rare earth inclusions could also induce the heterogeneous nucleation of γ-Fe at the end of solidification. Consequently, the nucleation site density increased dramatically during solidification. In addition, the increase of phase transformation velocity shortened the solidification time. The nucleated grains did not have time to grow, leading to the refinement of the grains during solidification.

Conclusions The effect of cerium on the nucleation and microstructure of high-strength lowalloy steel during solidification were investigated by experimental observations and theoretical calculations. The main results are summarized below: (1) The solidification path of the experimental steel was L → L + δ → L + δ + γ → L + γ → γ. After 8 and 16 s, the density of nucleation site in the Cecontaining steel was 115.74 and 222.90 mm−2 , respectively, which was 47.16 and 115.74 mm−2 higher than that of the Ce-free steel. After cerium treatment, the temperature range and time of solidification decreased from 48.1 °C and 52.02 s to 30.5 °C and 29.58 s, respectively. (2) According to the JMAK theory, the Avrami exponent n changed from 2.77 to 2.6 after adding Ce, and the nucleation mechanism was the site saturation nucleation. The addition of Ce increased the solidification rate constant k from 7.59 × 10–5 to 5.68 × 10–4 , promoting the transformation from liquid to solid phase. (3) The typical inclusions in the Ce-free steel were CaS inclusions and CaS+MgAl2 O4 complex inclusions. In the Ce-containing steel, the typical inclusions were CeAlO3 +CaS and Ce2 O2 S+CaS complex inclusions. The average size of inclusions decreased from 2.83 to 1.56 μm, and the number density increased from 46.21 to 64.85 mm−2 with the addition of Ce. (4) Based on the Bramfitt disregistry theory, the disregistry results between rare earth inclusions and δ-Fe/γ-Fe were all less than 12%, contributing to the formation of δ-Fe and γ-Fe. Upon the addition of rare earth, the large number of fine rare earth inclusions generated could effectively induce the heterogeneous

1410

F. Huang and J. Li

nucleation of δ-Fe and γ-Fe during solidification. Therefore, the microstructure was refined due to the increased number of nucleation and the shortened time of solidification. The average grain size decreased from 13.76 to 12.38 μm with the addition of 0.002% Ce. Acknowledgements The authors are grateful for the financial support of the National Natural Science Foundation of China (No. 52074026). Disclosure Statement No potential conflict of interest was reported by the authors. Funding This work was supported by the National Natural Science Foundation of China (grant number 52074026).

References 1. Alipooramirabad H, Ghomashchi R, Paradowska A, Reid M (2016) Residual stressmicrostructure-mechanical property interrelationships in multipass HSLA steel welds. J Mater Process Tech 231:456–467. https://doi.org/10.1016/j.jmatprotec.2016.01.020 2. Nathan SR, Balasubramanian V, Malarvizhi S, Rao AG (2016) Effect of tool shoulder diameter on stir zone characteristics of friction stir welded HSLA steel joints. Trans Indian Inst Metals 69:1861–1869. https://doi.org/10.1007/s12666-016-0846-3 3. Ji YP, Zhang MX, Ren HP (2018) Roles of lanthanum and cerium in grain refinement of steels during solidification. Metals 8(11):884. https://doi.org/10.3390/met8110884 4. Zhang SH, Yu YC, Wang SB, Li H (2017) Effects of cerium addition on solidification structure and mechanical properties of 434 ferritic stainless steel. J Rare Earth 35(5):518–524. https:// doi.org/10.1016/S1002-0721(17)60942-6 5. Bartlett LN, Avila BR (2016) Grain refinement in lightweight advanced high-strength steel castings. Int J Metalcast 10:401–420. https://doi.org/10.1007/s40962-016-0048-0 6. Qu TP, Wang DY, Wang HH, Hou D, Tian J, Hu SY, Su LJ (2021) Interface characteristics between TiN and matrix and their effect on solidification structure. J Iron Steel Res Int 28:1149– 1158. https://doi.org/10.1007/s42243-020-00546-2 7. Wu ZH, Zheng W, Li GQ, Matsuura H, Tsukihashi F (2015) Effect of inclusions’ behavior on the microstructure in Al-Ti deoxidized and magnesium-treated steel with different aluminum contents. Metall Mater Trans B 46:1226–1241. https://doi.org/10.1007/s11663-015-0311-4 8. Shi MH, Kannan R, Zhang J, Yuan XG, Li LJ (2019) Effect of Zr microalloying on austenite grain size of low-carbon steels. Metall Mater Trans B 50:2574–2585. https://doi.org/10.1007/ s11663-019-01701-1 9. Guan QF, Jiang QC, Fang JR, Jiang H (2003) Microstructures and thermal fatigue behavior of Cr-Ni-Mo hot work die steel modified by rare earth. ISIJ Int 43(5):784–789. https://doi.org/10. 2355/isijinternational.43.784 10. Zhao QC, Luo H, Pan ZM, Wang XF, Cheng HX (2023) Study on mechanical properties of rare earth elements modified high carbon chromium bearing steel. Mater Today Commun 34:105329. https://doi.org/10.1016/j.mtcomm.2023.105329 11. Qiao XY, Han X, He ZJ, Zhuang Z, Yang X, Mao FX (2022) Effect of cerium addition on microstructure and mechanical properties of as-cast high grade knives steel. J Iron Steel Res Int 29(12):1986–1994. https://doi.org/10.1007/s42243-022-00798-0 12. Zhang JS, Li GQ, Wang HH, Wan XL, Hu MF, Cao YL (2022) Effect of cerium on microstructure and microsegregation behavior of novel cryogenic high-Mn austenitic steel weld metal. Mater Charact 194:112427. https://doi.org/10.1016/j.matchar.2022.112427

Effect of Cerium on the Nucleation and Microstructure of High-Strength …

1411

13. Griesser S, Reid M, Bernhard C, Dippenaar R (2014) Diffusional constrained crystal nucleation during peritectic phase transitions. Acta Mater 67:335–341. https://doi.org/10.1016/j.actamat. 2013.12.018 14. Chen HB, Long MJ, Cao JS, Chen DF, Liu T, Dong ZH (2017) Phase transition of peritectic steel Q345 and its effect on the equilibrium partition coefficients of solutes. Metals 7(8):288. https://doi.org/10.3390/met7080288 15. Liu T, Long MJ, Chen DF, Huang YW, Yang J, Duan HM, Gui LT, Xu P (2020) Investigation of the peritectic phase transition in a commercial peritectic steel under different cooling rates using in situ observation. Metall Mater Trans B 51:338–352. https://doi.org/10.1007/s11663019-01758-y 16. Tuttle R (2012) Effect of rare earth additions on grain refinement of plain carbon steels. Int J Metalcast 6:51–65. https://doi.org/10.1007/BF03355527 17. Christian JW (1965) The theory of transformations in metals and alloys. Pergamon Press, Oxford 18. Wang H, Bao YP, Zhao M, Wang M, Yuan XM, Gao S (2019) Effect of Ce on the cleanliness, microstructure and mechanical properties of high strength low alloy steel Q690E in industrial production process. Int J Min Met Mater 26:1372–1384. https://doi.org/10.1007/s12613-0191871-0 19. Zhuo C, Liu R, Zhao ZR, Zhang YL, Hao XS, Wu HJ, Sun YH (2022) Effect of rare earth cerium content on manganese sulfide in U75V heavy rail steel. Metals 12(6):1012. https://doi. org/10.3390/met12061012 20. Bramfitt BL (1970) The effect of carbide and nitride additions on the heterogeneous nucleation behavior of liquid iron. Metall Trans 1:1987–1995. https://doi.org/10.1007/BF02642799 21. Gao JZ, Fu PX, Liu HW, Li DZ (2015) Effects of rare earth on the microstructure and impact toughness of H13 steel. Metals 5(1):383–394. https://doi.org/10.3390/met5010383 22. Yang J, Hao FF, Li D, Zhou YF, Ren XJ, Yang YL, Yang QX (2012) Effect of RE oxide on growth dynamics of primary austenite grain in hardfacing layer of medium-high carbon steel. J Rare Earth 30(8):814–819. https://doi.org/10.1016/S1002-0721(12)60136-7 23. Xin WB, Zhang J, Luo GP, Wang RF, Meng QY, Song B (2018) Improvement of hot ductility of C-Mn Steel containing arsenic by rare earth Ce. Metall Res Technol 115(4):419. https://doi. org/10.1051/metal/2018030 24. Torkamani H, Raygan S, Garcia MC, Rassizadehghani J, Palizdar Y, San-Martin D (2018) Contributions of rare earth element (La, Ce) addition to the impact toughness of low carbon cast niobium microalloyed steels. Met Mater Int 24:773–788. https://doi.org/10.1007/s12540018-0084-9

Effect of Vanadium on the Mechanical and Microstructural Properties of Medium-Mn Steels Felisters Zvavamwe, Minkyu Paek, Kudakwashe Nyamuchiwa, and Clodualdo Aranas Jr.

Abstract The automotive industry faces the challenge of enhancing fuel efficiency while meeting global environmental regulations concerning emissions. Thus, advanced high-strength steels (AHSS) recently gained significant attention due to their improved combination of strength and ductility compared to conventional steels, allowing the manufacturing of lighter body-in-white assemblies. Among the AHSS, medium-manganese steels, which contain 3–12 wt% Mn and belong to the thirdgeneration category, are of great interest. Since the mechanical and microstructural properties of medium-manganese steels rely heavily on the amount and stability of retained austenite, the impact of adding vanadium, ranging from 0 to 0.75 wt%, was explored. The results showed that the microstructure of the microalloyed mediumMn steels consists of martensite and retained austenite phases. The findings also revealed that increasing the vanadium content led to an increase in the proportion of retained austenite coupled with the refinement of austenite grain size. Keywords Medium manganese steels · Advanced high-strength steels · Retained austenite

Introduction Advanced high-strength steels (AHSS), which offer better strength-to-ductility combinations in comparison to conventional high-strength steels (HSS), have attracted significant attention in the automotive industry [1, 2]. These steels offer F. Zvavamwe · K. Nyamuchiwa · C. Aranas Jr. (B) Mechanical Engineering, University of New Brunswick, Fredericton, NB, Canada e-mail: [email protected] F. Zvavamwe e-mail: [email protected] M. Paek Research Institute of Industrial Science & Technology, Pohang, South Korea © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_121

1412

Effect of Vanadium on the Mechanical and Microstructural Properties …

1413

a combination of economy, reduced densities, and recyclability. The automotive industry is a huge consumer of the AHSS. The advanced high-strength steels are classified into three main categories, first generation, second generation, and thirdgeneration AHSS. The third-generation AHSS includes medium manganese steels, which is the scope of the present work [3, 4]. The concept of medium manganese steels, containing 3–12 wt% Mn, was originally started by Miller in the 1970s. In addition to manganese, the common alloying elements in medium manganese steels are carbon (0.01–0.7 wt%), aluminum (0–10 wt%), and silicon (0–3 wt%). Manganese plays a role in austenite retention and stabilization at room temperature. The addition of manganese results in a decrease in the martensite start (M s ) temperature and lowers the M d30 temperature. The addition of manganese also decreases the Ae1 and Ae3 temperatures. Consequently, this lowers the austenite ferrite intercritical temperature range. Like manganese, carbon also acts as an austenite stabilizer and lowers the Ae1 and Ae3 temperatures. Carbon also plays a role in solid solution strengthening for the ferrite and martensite phases. Increasing the carbon content increases the austenite stacking fault energy, thus impacting the deformation behavior of the austenite. Aluminum acts as a ferrite stabilizer and increases the size of the ferrite–austenite region. It also reduces the density of the steel, which is important in reducing its overall weight. The addition of aluminum also increases the stacking fault energy of austenite. Silicon has a similar effect to that of aluminum in ferrite stabilization and reduction of the mass density of the steels. Finally, silicon is also important for solid solution strengthening of the steels [3]. More recently, attention has been given to medium manganese steels due to the higher demand for high-strength and lightweight steels from the automotive industry. Tensile strengths of up to 2400 MPa and total elongation of up to 95% have been reported for medium manganese steels. The mechanical behavior of medium manganese steels is highly dependent on the volume fraction and stability of retained austenite, which improves the work hardening rate and provides better strengthductility combinations. The most common strengthening mechanisms within this group of steels are transformation-induced plasticity (TRIP) and twinning-induced plasticity (TWIP). These mechanisms depend on the stacking fault energy (SFE), which is a composition-dependent parameter. In general, an austenite stacking fault energy of 20 mJ/m2 results in the formation of mechanical twins (TWIP). When the SFE is in the range of 16–20 mJ/m2 , TWIP and TRIP can occur simultaneously. However, the occurrence of these mechanisms does not solely depend on austenite, but may also be influenced by carbon content, stress, and grain size. Other strengthening mechanisms, such as solid solution strengthening and precipitation strengthening, also contribute to the mechanical properties of these steels[1, 3–5]. The microalloying of medium manganese steels using niobium, titanium, vanadium, and molybdenum has been found to enhance their mechanical properties. The microalloying elements precipitate in austenite and ferrite as fine carbides, nitrides or carbonitrides, and contribute to grain refinement and precipitation strengthening. The addition of 0.15 wt% Ti to 5 wt% in Mn-steels has been found to suppress grain

1414

F. Zvavamwe et al.

Table 1 Composition of vanadium microalloyed medium manganese steel in wt% 0

Al

Si

Mn

V

C

O

N

S

1.47

1.588

8.07

0

0.3164

0.00406

0.008

0.0017

1

1.44

1.475

7.87

0.06

0.3112

0.00333

0.013

0.0013

2

1.38

1.344

7.54

0.75

0.3089

0.00217

0.018

0.0022

growth in the austenite phase [6–8]. Adding 0.22 wt%Mo, 0.05% Nb, and 6.5% Mn increases the stability and volume fraction of retained austenite at room temperature; thus improving mechanical properties such as ductility and yield strength [9]. The addition of vanadium has been reported to produce vanadium carbide precipitates, which increase the yield strength of ferrite by precipitation hardening without compromising ductility [10–13]. Since the effect of the incremental addition of vanadium has not been extensively studied yet, in this work, the effect of microalloying medium manganese steel is investigated. Three steels with different vanadium contents, 0, 0.06, 0.75 wt%, were studied and characterized.

Materials and Methods The medium manganese steels with different vanadium content were cast using an arc melting furnace. Their chemical composition compositions were obtained by means of Inductively Coupled Plasma (ICP) and are presented in Table 1. These samples were prepared by rough polishing using sandpaper from 240 to 1200 grit, followed by fine polishing using 3- and 1-micron diamond suspension. To perform microscopy analysis, the polished samples were etched using 4% nital solution. The microstructural analysis was carried out using a Zeta-20 optical microscope and a JSM-6010LA analytical scanning electron microscope equipped with EDS detector. The samples were also analyzed using electron backscatter diffraction (EBSD) to evaluate microtexture and crystallographic information using a Hitachi SU-70 electron microscope. The data was then analyzed using HKL Channel 5 software.

Results and Discussion The optical microscopy images of the medium manganese steels with 0, 0.06, and 0.75 wt% vanadium are shown in Fig. 1. The dark (martensite) and light (austenite) regions denote the formation of a dual-phase structure. It appears that the addition of vanadium increases the retained austenite during cooling, consistent with the effect of an austenite stabilizer. The observed retained austenite seems to be from the grain boundaries of prior austenite grains. On the other hand, the formation of the martensite matrix is due to the rapid quenching and high hardenability due to the

Effect of Vanadium on the Mechanical and Microstructural Properties …

1415

Fig. 1 Optical micrographs for a vanadium microalloyed medium manganese steel with varying vanadium content: a 0 wt%, b 0.06 wt%, and c 0.75 wt%

Fig. 2 SEM images for a vanadium microalloyed medium manganese steel with varying vanadium content: a 0 wt%, b 0.06 wt%, and c 0.75 wt%

relatively high manganese content of the steels. The observations from the optical images are consistent with the scanning electron microscopy images, as shown in Fig. 2. A martensitic structure is evident, and the grain size decreases with the addition of vanadium. In order to confirm the existence of retained austenite, an EBSD analysis was performed, as displayed in Fig. 3. In Fig. 3a–c, the distribution of austenite on the martensitic matrix is presented. As can be observed, the retained austenite fraction increases with increasing vanadium content. More specifically, the retained austenite increased from 6.9 wt% (0 wt% V) to 14.5% (0.06 wt% V). However, only a slight increase in retained austenite is observed from 0.06 wt% V (14.5 wt% austenite) to 0.75 wt% V (14.8 wt%). The crystallographic texture appears random, as can be seen from the Inverse Pole Figure maps in Fig. 3d–f. The incremental change of austenite fraction due to the addition of vanadium is presented in Fig. 4a, complemented with microhardness measurement in Fig. 4b. The retained austenite increased the strength of the medium manganese steel, which can be accounted to the TRIP effect during deformation. A more detailed analysis related to the formation of retained austenite on microalloyed medium manganese steel will be studied in future work. Moreover, the effect of heat treatment on the phase stability of retained austenite will also be explored.

1416

F. Zvavamwe et al.

Fig. 3 a–c Phase maps for 0, 0.06 and 0.75 wt% vanadium microalloyed medium manganese steel, respectively and d–f IPF maps for 0, 0.06 and 0.75 wt% vanadium microalloyed medium manganese steel, respectively

Fig. 4 Effect of vanadium content on austenite fraction and hardness

Conclusions This work explored the effect of vanadium addition on medium manganese steels. It can be concluded that the volume fraction of retained austenite increases with the addition of vanadium, as can be seen from optical and electron microscopy images. The retained austenite appears to be situated along the boundaries of the prior austenite grains during solidification. The addition of vanadium also increased the hardness of the medium manganese steels by about 5%. This can be attributed to the TRIP effect from the retained austenite generated by adding microalloying elements. Future work is needed to understand the mechanism of the formation of

Effect of Vanadium on the Mechanical and Microstructural Properties …

1417

retained austenite after vanadium addition, including the response of the material after heat treatment. Acknowledgements The authors acknowledge with gratitude funding received from the Natural Sciences and Engineering Research Council of Canada (NSERC), Canada Foundation for Innovation (CFI), New Brunswick Innovation Foundation (NBIF), and the Harrison McCain Foundation.

References 1. Lee Y-K, Han J (2015) Current opinion in medium manganese steel. Mater Sci Technol 31(7):843–856. https://doi.org/10.1179/1743284714Y.0000000722 2. Hu B, Luo H, Yang F, Dong H (2017) Recent progress in medium-Mn steels made with new designing strategies, a review. J Mater Sci Technol 33(12):1457–1464. https://doi.org/10.1016/ j.jmst.2017.06.017 3. Sun, B et al (2023) Physical metallurgy of medium-Mn advanced high-strength steels. Int Mater Rev:1–39. https://doi.org/10.1080/09506608.2022.2153220 4. Sun B, Processing, microstructure and mechanical behavior of medium manganese steels 5. Dumay A, Chateau J-P, Allain S, Migot S, Bouaziz O (2008) Influence of addition elements on the stacking-fault energy and mechanical properties of an austenitic Fe–Mn–C steel. Mater Sci Eng A 483–484:184–187. https://doi.org/10.1016/j.msea.2006.12.170 6. Wang Z et al (2016) Effect of molybdenum addition on the precipitation of carbides in the austenite matrix of titanium micro-alloyed steels. J Mater Sci 51(10):4996–5007. https://doi. org/10.1007/s10853-016-9804-z 7. Han Y, Shi J, Xu L, Cao WQ, Dong H (2011) TiC precipitation induced effect on microstructure and mechanical properties in low carbon medium manganese steel. Mater Sci Eng A 530:643– 651. https://doi.org/10.1016/j.msea.2011.10.037 8. Han Y, Shi J, Xu L, Cao WQ, Dong H (2012) Effects of Ti addition and reheating quenching on grain refinement and mechanical properties in low carbon medium manganese martensitic steel. Mater Des 34:427–434. https://doi.org/10.1016/j.matdes.2011.08.015 9. Varanasi RS, Gault B, Ponge D (2022) Effect of Nb micro-alloying on austenite nucleation and growth in a medium manganese steel during intercritical annealing. Acta Mater 229:117786. https://doi.org/10.1016/j.actamat.2022.117786 10. Pham MK, Nguyen DN, Hoang AT (2018) Influence of vanadium content on the microstructure and mechanical properties of high-manganese steel. 18(2) 11. Di X, Li M, Yang Z, Wang B, Guo X (2016) Microstructural evolution, coarsening behavior of vanadium carbide and mechanical properties in the simulated heat-affected zone of modified medium manganese steel. Mater Des 96:232–240. https://doi.org/10.1016/j.matdes.2016. 02.038 12. Park TM, Jeong MS, Jung C, Choi WS, Choi P-P, Han J (2021) Improved strength of a mediumMn steel by V addition without sacrificing ductility. Mater Sci Eng A 802:140681. https://doi. org/10.1016/j.msea.2020.140681 13. Lagneborg R, Siwecki T, Zajac S, Hutchinson B (1999) The role of vanadium in microalloyed steel. Scand J Metal 28:186–241

Formation and Decomposition Mechanism of Carbides in AISI M35 High-Speed Steel Produced by ESR Wei Liang, Jing Li, and Jia-hao Li

Abstract The morphology of carbides in AISI M35 high-speed steel electroslag remelting ingot, as well as decomposition mechanism of the carbides at high temperature were investigated by thermodynamic calculations, microscopy analyses, and phase analyses. The calculation results indicated that the main types carbides formed in steel during solidification were MC and M2 C. Through observation, it was found that there were lots of network eutectic carbides in the electroslag ingot, and the size of carbides at the center was larger than that at the edge. The micro morphologies of carbides in the ingot mainly had two types: a lath-like shape and a brain one, and both phases were identified as M2 C. They could be decomposed and formed new phases MC and M6 C at high temperatures. The decomposition of M2 C carbides occurred obviously with the increasing holding temperature, especially at 1,423 to 1,473 K. Which were more easily broken and deformed in the subsequent working. Keywords Network eutectic carbides · M2 C · Decomposition · High-speed steel

Introduction High-speed steel (HSS) is a type of tool steel that has the characteristics of high hardness, good wear resistance, and red hardness. Metal-cutting tools made of HSS usually have a hardness of over 63HRC after heat treatment. Due to the abundance of alloying elements in steel and long local solidification time, there is a large amount of eutectic carbides in HSS ingots. Take AISI M2 and AISI M42 HSSs as examples, Wang and Luo et al. [1, 2] found that network eutectic carbides would be formed during the solidification, and the micro morphology of carbides was lath or fibrous. The traditional casting process with low cooling rates causes severe element segregation during the solidification and the formation of large-sized and unevenly W. Liang · J. Li (B) · J. Li State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing 100083, China e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_122

1418

Formation and Decomposition Mechanism of Carbides in AISI M35 …

1419

distributed eutectic carbides in the ingot. Compared to casting process, electroslag remelting (ESR) process has a higher cooling rate, resulting in a smaller size of eutectic carbides, and a better density of the microstructure in the ingot [3]. As the crucial process of HSS hot working, forging can help obtain the required size of billets through heating, insulation, and deformation. The eutectic carbides in the ingot are broken and deformed in this process, thereby improving their size and distribution [4]. By exploring the heating and deformation sequence of the HSS forging process and observing the degree of M2 C decomposition in the billets, Zhou et al. [5, 6] proposed the deformation-induced carbide transformation (DICT), which was beneficial for the refinement of carbides. However, the uneven distribution of large-sized carbides in the steel were prone to detachment during processing and using, but also caused stress concentration in the matrix, leading to deterioration in the strength and toughness of the steel [7, 8]. AISI M35 is a typical high-performance HSS, with a hardness of 70 HRC after heat treatment, which can be used to prepare complex cutting tools with higher red hardness and better wear resistance [9]. There is currently limited research on the formation and controlling of carbides in AISI M35 HSS. Therefore, the formation of carbides in the AISI M35 HSS will be investigated, as well as the influence of heating temperature before forging on carbides. They can provide theoretical guidance for optimizing process parameters and controlling the size and distribution of carbides in the HSS.

Experimental Materials HSS is generally produced using the melting process in the plant, as shown in Fig. 1. Specifically, it is melted in an electric arc furnace (EAF) or induction furnace (IF), after ladle furnace (LF) and vacuum degasser (VD) refining, ESR or casting is carried out, and then bars and wires are made through forging, hot rolling, and cold-drawing. And the production of AISI M35 HSS involves IF melting and ESR process. The material sample with the dimensions of 230 mm in diameter and 300 mm in height was taken from the bottom of the unannealed AISI M35 ingot after ESR.

Methods The chemical compositions of AISI M35 ESR ingot were determined by the high frequency infrared carbon sulfur analyzer and direct reading spectrometer, and the results were shown in Table 1. The solidification model in JMatPro software was

1420

W. Liang et al.

Fig. 1 Schematic drawing of HSS production process

used to calculate the formation of carbide phases in AISI M35 HSS during nonequilibrium solidification. Figure 4 shows the formation rule and elemental composition of carbides in Steel with the solid fraction increasing. The samples were taken from center and edge of the ingot using wire cutting machine and the samples size was 10mm × 10mm × 10mm. The morphology and size of carbides in the samples were observed by scanning electron microscope (SEM). The specimens with dimensions of ϕ5mm × 3mm were taken from the above samples for electron backscatter diffraction (EBSD) analysis were electropolished at 273 K in a solution containing 5% perchloric acid and 95% alcohol. Carbide phases were analyzed using EBSD. Furthermore, the samples with dimensions of 20 mm × 20 mm × 20 mm used for thermal decomposition experiments were extracted from the center of the ingot. The temperatures were set to hold for 1 h at 1,273 K, 1,323 K, 1,373 K, 1,423 K, and 1,473 K, respectively. The specimens with dimensions of 10mm × 10mm × 10mm were taken from the heated samples for observation and analysis of carbides using SEM and energy dispersive spectrometer (EDS). Then the specimens were machined into dimensions of ϕ 5 mm×3 mm for EBSD analysis. The detailed sampling scheme was shown in Fig. 2. Table 1 Chemical compositions of the investigated ESR ingot (wt%) C

Si

Mn

P

S

W

Mo

Cr

V

Co

Ti

Nb

0.915

0.320

0.322

0.021

0.002

5.830

4.815

4.120

1.770

4.770

0.005

0.128

Formation and Decomposition Mechanism of Carbides in AISI M35 …

1421

Fig. 2 Schematic drawing of sampling scheme of the AISI M35 ESR ingot

Results and Discussion Morphology and Type of Carbides in ESR Ingot Figure 3 shows the carbides characteristics of center and edge in the ingot. As shown in Fig. 3a–d, a quantity of network eutectic carbides was formed, and the size of the carbides at the center is larger than that at the edge. It is generally believed that the higher cooling rate at the edge, the lower degree of element segregation, resulting in a smaller size of the formed carbide. Moreover, the morphologies of carbides in the ingot mainly had two types: a lath-like shape and a brain one. The size of the brain like carbide shown in Fig. 3e was less than 6 µm. The phases in AISI M35 HSS were high temperature ferrite, austenite, MC, and M2 C during the solidification, as shown in Fig. 4(a), and the formation temperatures were 1,673 K, 1,621 K, 1,571 K, and 1,499 K, respectively. The elemental compositions of MC were mainly V, W, Mo, and Nb, while the elemental compositions of M2 C were mainly W, Mo, V, and Cr in Fig. 4b,c. EBSD phase maps and corresponding orientation maps of carbides with different morphologies are shown in Fig. 5. The carbides with lath-like and brain like were all M2 C. However, as shown in Fig. 5c,f, the internal orientations of M2 C were diverse, indicating that they originated from different nucleation cores during the solidification.

1422

W. Liang et al.

Fig. 3 Characteristics of carbides at different positions in the AISI M35 ESR ingot: a and b center; c and d edge; e brain like carbide

Fig. 4 The solidification diagram and elemental composition of carbides in AISI M35 HSS: a formation law of phases; b elemental composition of MC; c elemental composition of M2 C

Formation and Decomposition Mechanism of Carbides in AISI M35 …

1423

Fig. 5 EBSD phase maps and corresponding orientation maps of carbides with different morphologies in the AISI M35 ESR ingot: a–c lath-like carbides; d–f brain like carbides

Effect of High Temperature Heating on Carbides in ESR Ingot The morphology changes of carbides in the ingot after holding for 1 h at different temperatures are shown in Fig. 6. The carbides in the specimens did not change obviously in Fig. 6a,b, and their morphologies remained lath-like shape. With the increase of temperature, the morphology of carbides changed at 1,373 K. The new dark gray phases appeared in the interior and edge of the lath-like carbides, that was the decomposition behavior of carbides. Besides, the decomposition and spheroidization of carbides were more pronounced at 1,423 K and 1,473 K as shown in Fig. 6d,e. Considering that the actual heating temperature of AISI M35 ESR ingot in the plant generally was not more than 1,473 K, the typical changes of carbides in the specimens after holding for 1 h at 1,323 K and 1,423 K were analyzed. Figure 7 shows the back scattered electron (BSE) images and EDS results of different carbides. At 1,323 K, elements such as Mo, V, and W were concentrated on the bright white region of carbides, while trace amounts of Cr could be found in Fig. 7a. Because of the insignificant changes of carbides in the specimen at 1,323 K, the above element distribution results were consistent with the elemental composition of M2 C calculated in Fig. 4b. In Fig. 7b, only Mo and W were concentrated on the bright white region, while V was concentrated on dark gray region of carbides at 1,423 K. Then it could be inferred that the elements of M2 C carbides in the specimens had migrated during high temperature heating, resulting in the formation of new carbides. Figure 8 and Fig. 9 show EBSD phase maps and corresponding orientation maps of carbides with different morphologies in the specimens after holding for 1 h at different temperatures. At 1,323 K, the M2 C carbides with the lath-like and brain like in the specimens were partially decomposed and transformed, correspondingly, only a

1424

W. Liang et al.

Fig. 6 SEM images of the morphology changes of carbides in the ingot after holding for 1 h at different temperatures: a 1,273 K; b 1,323 K; c 1,373 K; d 1,423 K; e 1,473 K

Fig. 7 BSE images and corresponding element mappings of carbides in the ingot after holding for 1 h at different temperatures: a 1,323 K; b 1,423 K

Formation and Decomposition Mechanism of Carbides in AISI M35 …

1425

Fig. 8 EBSD phase maps and corresponding orientation maps of carbides in the ingot with different morphologies in the ingot after holding for 1 h at 1,323 K: a–c lath-like carbide; d–f brain like carbide

small amount of MC and M6 C carbides were formed. At 1,423 K, the transformation of brain like M2 C carbides was completed, while lath-like carbides were mostly transformed. Therefore, high temperature heating can promote the decomposition and transformation of M2 C carbides in the HSS ingots. In addition, the decomposition degree of M2 C carbides increases with the temperature elevated.

Decomposition and Transformation Behavior of M2 C Carbides Figure 10 shows the analysis of the decomposition and transformation of M2 C carbides in the ingot. Combined with the research results of literature [10], M2 C carbides were considered to be metastable at high temperature. In Fig. 10, the elements of W and Mo in the M2 C carbides diffused into the matrix to form M6 C carbides, while the residual V and other elements formed MC carbides. The corresponding reaction formula was M2 C + Fe(γ ) → M6 C + MC. The MC and M6 C carbides formed by the decomposition of M2 C carbides will be broken and deformed in the subsequent hot working, which is beneficial to promoting the dispersion of carbides in the billets.

1426

W. Liang et al.

Fig. 9 EBSD phase maps and corresponding orientation maps of carbides in the ingot with different morphologies in the ingot after holding for 1 h at 1,423 K: a–c lath-like carbide; d–f brain like carbide

Fig. 10 Decomposition and transformation behavior of M2 C carbides in HSS: a schematic drawing; b SEM image

Conclusion (1) A large amount of network eutectic carbides was formed in the AISI M35 ESR ingot during the solidification, and the size of the carbides in the center was larger than that at the edge. The morphologies of carbides in the ingot mainly had two types: a lath-like shape and a brain one.

Formation and Decomposition Mechanism of Carbides in AISI M35 …

1427

(2) The carbides in AISI M35 HSS were mainly MC and M2 C during nonequilibrium solidification, and the formation temperatures were 1,571 K and 1,449 K. Besides, the carbides with lath-like and brain like were M2 C. (3) The M2 C carbides can be decomposed and transformed into MC and M6 C carbides at high temperature. The above behavior will become more apparent with the temperature increasing.

References 1. Wang W, Pan F, Tang A (2011) Decomposition of the coarse primary carbides in the M2 high speed steels containing silicon. Rare Met Mater Eng S3:38–42 2. Luo YW, Guo HJ, Sun XL (2020) Effects of nitrogen on the morphology and evolution of M2C eutectic carbides in Fe-Mo-W-Co-Cr-VC alloy. JOM 72:326–332 3. Xiao ZX, Li HP, Feng JH (2018) Microstructural homogeneity of electroslag remelting M2 high speed steel ingot. J Iron Steel Res 30(07):529–535 4. Zhou B, Shen Y, Chen J (2011) Breakdown behavior of eutectic carbide in high speed steel during hot compression. J Iron Steel Res Int 18(1):41–48 5. Zhou XF, Zheng ZX, Zhang WC (2020) Effect of pre-deformation on decomposition and spheroidization of M2C carbide in high-speed steel. Metall Mater Trans A 51:3552–3564 6. Zhou XF, Zheng ZX, Zhang WC (2020) Deformation-induced carbide transformation in M2 high-speed steel. Metall Mater Trans A 51:568–573 7. Narahari PS, Rajasekhar K, Chatterjee M (2013) Influence of composition and processing on properties of stainless steels. Adv Mater Res 794:117–123 8. Chen K, Cheng SC, Zhang JZ (2012) The effect of large Nb containing MC carbides on the high-temperature properties of LF2 alloy. Mech Eng Mater 36(3):18–21 9. Deng YK (2002) High speed tool steel. Metallurgical Industry Press, Beijing 10. Zhou B, Shen L, Chen J (2010) Evolving mechanism of eutectic carbide in As-cast AISI M2 high-speed steel at elevated temperature. J Shanghai Jiaotong Univ (Sci) 15(04):463–471

Phase Transformation, Microstructure, and Mechanical Properties on Nickel-Free High Chromium Weld Metal Fikret Kabakcı, Mustafa Acarer, and Nurcan Akduran

Abstract High chromium Ferritic-martensitic (FM) steels are employed for especially thermal and nuclear power plant because of their low thermal expansion, corrosion resistance, and creep performance. In this study, weld metal phase transformation and mechanical properties oh high chromium steel without Ni were investigated. The microstructure of produced all weld metal were characterized by optical microscope (OM), scanning electron microscopy (SEM) with EDS. In addition, ThermoCalc software was used to consider thermodynamic equilibrium stages and phase transformations. Differential scanning calorimetry (DSC) was employed in order to detect A1, A2, A3, and Ms-Mf temperature. Weld metal microstructure has tempered martensitic also precipitates observed mostly in the PAGB and lath boundary. α → γ transformation 834 °C and Curie temperature 737 °C observed by DSC. Impact energy at 25 °C 57J while 60 °C was 97J observed. Keywords 9Cr weld metal · Toughness · Phase transformation · Creep resistant steel

Introduction High chromium Ferritic-martensitic (FM) steels are used at elevated temperature applications such as nuclear power plant, energy production with fossil foil power plant, hydro crackers, because their thermal expansion lover and thermal conductivity F. Kabakcı Zonguldak Bülent Ecevit University, Alaplı Vocational School, Zonguldak, Turkey e-mail: [email protected] M. Acarer (B) · N. Akduran Selçuk University, Metallurgy and Material Engineering, Konya, Turkey e-mail: [email protected] N. Akduran e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_123

1428

Phase Transformation, Microstructure, and Mechanical Properties …

1429

higher compared to austenitic stainless steels and Ni-based alloys [1]. 9%Cr steels mainly P91 and P92 are known for these applications. P91 steel have 9%Cr, 1% Mo alloying element while in P92 steel Mo content decreased to 0.5% and 1.5–2%W added for improving creep resistance. In addition, according to the standard published in [2], P93 steel with 9%Cr, the amount of Mo removed from the composition and W content increased to 3.5%max and Co was added up to 3.5%. FM steels with 9% Cr have a martensite phase with cooling at room temperature from the austenite phase. Therefore, it is used in tempered condition in order to achieve low hardness and high toughness. In the tempered state, their microstructure comprises tempered martensite phase. The weld metals of these steels should also have a similar tempered martensitic structure. However, secondary delta ferrite phase is formed especially in P92 steel weld metal [3, 4]. Delta ferrite phase formed in the weld metal reduces toughness [5] and also detrimental effect on long-term creep strength [4]. Nevertheless, the delta ferrite phase cannot be removed by heat treatment. The chemical compositions of the filler weld metal used for P92 differs from the base metal, in order to prevent delta ferrite formation and guarantee the tempered martensitic structure after PWHT [6]. Balancing of ferrite and austenite forming elements is very important in determining to chemical composition of the weld metal. Since PWHT is required after welding of these steels, selected elements shouldn’t reduce the A1 temperature in order to make the PWHT and time economically. 9% Cr steels transform from austenite phase to martensite by cooling even at room temperature. If PWHT is made above A1 temperature, untempered (fresh) martensite phase will remain in the structure, which will reduce the toughness. Nickel lowers A1 temperature like Mn so Mn + Ni content is limited to 1.5% on P91 welding consumable specification [6, 7]. Also has been reported that cobalt does not lower the A1 temperature as much as nickel [8]. In this study, the phase transformations of 0.5% Co and 1.9% W containing 9% Cr steel weld metal without nickel were investigated and mechanical properties were also determined.

Experimental In order to investigate phase transformations and mechanical properties in nickel-free weld metal, all weld metal test was produced by SMAW welding method according to specified in the AWS 5.5 standard [9]. Stick electrode for SMAW produced by Gedik Welding company in Turkey. The all weld metal design and positions of the mechanical test pieces on the all weld metal are shown in the Fig. 1. Before the welding process, base metals were subjected to 200 °C and the inter-pass temperature was kept as 240 °C. Produced all weld metal was let to cool room temperature at the end of the welding process, and then it was subjected to 760 °C for 4h. Calculated heat input is about 1.5kJ/mm. Chemical composition of the all weld metal was determined by optical emission spectrometry. N–O analysis also performed with LECO equipment in accordance with ASTM E-1019. Tensile test was carried out at room temperature while impact tests were carried out at 20, 40, and 60 °C.

1430

F. Kabakcı et al.

Fig. 1 All weld metal design

The microstructural characterization performed with Nikon Eclipse MA100 optical invert microscope. Test specimens were subjected to grinding and polishing processes via using conventional methods followed by etching with Picral (2.5 picric acid + 2.5 ml hydrochloric acid in 95% ethanol). In addition, QUANTA 450 Field-emission Gun (FEG) Electron microscope (SEM) was used for microstructure investigation. In order to investigate phase transformation, thermal analysis used by METTLER TOLEDO TGA/DSC 2 performed with 40 °C/min heating and cooling condition up to 1000 °C. Also Thermo-Calc TCS Steel and Fe-alloys Database V8 (400–2000 °C) used for thermodynamically stable phases investigation.

Results and Discussion Chemical composition of the weld metal is given at Table 1.

Microstructure and Phase Transformation Optical microscopy investigation revealed that weld metal has tempered martensitic microstructure after PWHT. The microstructure images of weld metal can be seen in Fig. 2 (a) and (b) arrow showed that PAGB (prior austenite grain boundary). Delta ferrite phase was not observed in the microstructure. Delta ferrite phase reduces the toughness [10] and creep resistance [4, 11]. Also reported by researchers

Mn

0.69

Si

0.21

C

0.08

0.01

P

0.008

S 0.13

Ni

Table 1 Chemical composition of weld metal Wt.% 8.47

Cr 0.52

Mo 0.44

Co 0.05

Nb 0.19

V 1.93

W

0.01

Ti

Bal

Fe

384

N (ppm)

534

O (ppm)

Phase Transformation, Microstructure, and Mechanical Properties … 1431

1432

F. Kabakcı et al.

Fig. 2 Optical microstructure of weld metal after PWHT at 760 °C 4h (etch. Picric HCI)

that cobalt helps to prevent delta ferrite formation [11–13]. Absence of delta ferrite in the microstructure thought to be caused by the effect of cobalt. 9%Cr FM steels and weld metals’ heat resistance is possible owing to the carbides and carbonitrides that prevent the dislocation movement in their microstructures. SEM images of the weld metal is given in the Fig. 3. As seen in the Fig. 3, carbides are prominently present at the PAGB and the boundary of lath. These carbides were identified as M23 C6 and MC type.

Fig. 3 SEM microstructure of weld metal a Lower mag. and b Higher mag. PWHT at 760 °C 4h. c Spherical oxide inclusions in weld metal d EDX spectrum of oxide particle (etch. Picric HCI)

Phase Transformation, Microstructure, and Mechanical Properties …

1433

Fig. 4 Phases in the weld metal, depending on temperature calculated with Thermo-Calc, a ferrite and austenite transformations, b precipitation phases showed

Mole fraction of phases calculated by Thermo-Calc were given in Fig. 4 according to the chemical composition of the weld metal (Table 1). Major phases (left) are Ferrite, Austenite, δ-ferrite, liquid and minor phases (right) Sigma, Z-phase, Laves, M23 C6 , M6 C, MX. Major phase transformation temperatures corresponding to Thermo-Calc are Ac1; α → γ 812 °C, Ac3 ; 874 °C, Ac4 ; γ → δ 1210 °C, and melting point (Tm) calculated as 1503 °C calculated. A2 temperature (Tc) couldn’t determine by Thermo-Calc. Also, minor phases are M23 C6, Laves, Z-phase, sigma, M6 C, and MX type carbide calculated. Although these phases are found under equilibrium conditions, creep resistance provides by M23 C6 (M; Cr, Fe, Mo, W) that and MX (M; V, Nb and X; C, N) type carbides, which are more stable at the high temperature condition [11]. Although it has no effect in normalized and tempered conditions, the laves phase (rich; Mo and W) under high temperature conditions has also been reported to be harmful to mechanical properties of the base metal and weld metal [14]. Weld metal analyzed with DSC up to 1000 °C heating and cooling data are shown in the Fig. 5. Also phase transformation temperature given in Table 2. A2 temperature (Tcurie), which could not be detected with Thermo-Calc, was determined with DSC as 737 °C. Curie temperature is important for high temperatures components. While diffusion is slow below the curie temperature (T c ), above Tc it is higher [15]. The operating temperature of high temperature materials is chosen below the Tc temperature. It has also been reported that it would be appropriate to reduce nickel and add Co to reduce the diffusion coefficient [11]. In the study on weld metals containing 9Cr, it was determined that the creep strength increased with the addition of cobalt [8]. Reported in literature that Tc temperature was as 730 °C [16] in the DSC examination of the P92 steel containing 9% Cr that is lower than this research this attributed added cobalt and low nickel.

1434

F. Kabakcı et al.

Fig. 5. 40 °C/min heating and cooling curve of weld metal sample (28.26 mg wt)

Table 2 Phase transformation temperature observed with DSC Heating

Cooling

Tcurie

Ac1

Ac3

Ms

MF

737

834

879

392

305

Mechanical Properties The mechanical properties of weld metal were determined by tensile, hardness, and Charpy impact test with the temperature as 25, 40, and 60 °C. Table 3 shows the tensile and hardness test results. The tensile test results satisfy the minimum yield and tensile strength specifications for P91 (415–585 MPa) and P92 (440–620 MPa) 9% Cr steel by ASTM [2]. The 9% Cr FM steel weld metal very sensitive to temperature because of weld metal microstructure. Figure 6 shows the charpy impact test results with different temperature. Average toughness value was determined as 56 J at, 74.5 J at 40 °C, and 97 J at 60 °C. Base metal toughness of 9% Cr FM is very high compared to weld metal. Toughness value of P92 steel is 200 J [10], that of P91 is 170 J [17] at room temperature reported in literature. The significant difference in toughness between base metal and weld metal may have caused inhomogeneity of grain boundaries and Table 3 Tensile and hardness test results of all weld metal Yield strength (MPa)

Tensile strength (MPa)

Elongation at rupture (%)

Hardness HB

637

762

20

241 ± 6

Phase Transformation, Microstructure, and Mechanical Properties …

1435

Fig. 6 Effect of temperature on impact energy

non-metallic inclusions in the weld metal. However, the toughness values are similar with literature in 9% Cr weld metal [6, 7]. Figure 7 shows also fractured surface area at +40 and +60 °C. The brittle area calculated by image J lover at +60 °C compared with +40 °C. Total area calculated by image J at +40 °C 85.46 mm2 and +60 °C 79.89 mm2 this maybe help to calculate ductile brittle transition temperature (DBTT) given in Table 4. Similar study is available in the literature [18]. Figure 8 shows SEM image of the fractured weld metal at +40 °C. Mixed fracture mode (dimple and cleavage) observed in the weld metal. Also, spherical Type I non-metallic inclusions were observed inside the dimple.

1436

F. Kabakcı et al.

Fig. 7 Macro surface of Charpy impact test specimens

Table 4 Fracture behavior of the weld metal Test temp. (°C ) Total area (mm2 ) Brittle area (mm2 ) (Brittle area/total 100-brittle area) × 100 = fracture = %brittle fracture %ductile fracture +40

85.46

24.15

28.25

71.75

+60

79.89

13.90

17.39

82.61

Phase Transformation, Microstructure, and Mechanical Properties …

1437

Fig. 8 SEM images of weld metal fracture surface

Conclusion In this study, nickel-free weld metal phase transformation and mechanical properties of were investigated. The results are given below. 1. Although there is no austenite forming nickel, delta ferrite was not observed in the weld metal, showing that Cobalt prevents delta ferrite formation. 2. It was observed that the transformation temperature (α → γ) calculated with Thermo-Calc (812 °C) was lower than DSC (834 °C). 3. Cobalt raised the Curie temperature. 4. Impact tests results showed that weld metal toughness is very sensitive to temperature, at 25 °C an average value 57 J while 60 °C was observed 97 J. Acknowledgements The authors would like to acknowledge the financial support provided by SANTEZ (University-Industry Collaboration Grant Programme-Ministry of Science, Industry and Technology) with the Grant Number of 0374.STZ.2013-2. Authors also thank to Gedik Welding Company, Istanbul, Turkey.

References 1. Abe F (2015) Research and development of heat-resistant materials for advanced USC power plants with steam temperatures of 700 °C and above. Engineering 1(2):211–224

1438

F. Kabakcı et al.

2. Standard A (2020) Standard specification for seamless ferritic alloy-steel pipe for hightemperature service, A335/A335M-19a, pp 1–12 3. Adhithan B, Pandey C (2021) Study on effect of grain refinement of P92 steel base plate on mechanical and microstructural features of the welded joint. Int J Press Vessels Pip 192:104426 4. Chakraborty G, Kumar JG, Vasantharaja P, Das C, Albert S, Laha K (2019) Effect of delta ferrite on microstructure and mechanical properties of high-chromium martensitic steel. J Mater Eng Perform 28(2):876–885 5. Barnes A, Abson D (2003) The effect of composition on microstructural development and toughness of weld metals for advanced high temperature 9–13% Cr steels. In: 2nd international conference intergrity of high temperature welds. London 6. Zhang Z, Holloway G, Marshall A (2009) Properties of T/P 92 steel weld metals for ultra super critical (USC) power plant. Ommi 6(1):1–14 7. Arivazhagan B, Sundaresan S, Kamaraj M (2008) Effect of TIG arc surface melting process on weld metal toughness of modified 9Cr-1Mo (P91) steel. Mater Lett 62(17–18):2817–2820 8. Kabakcı F, Acarer M, Baydo˘gan M, Keskinkılıç AS, Acar FK, Çimeno˘glu H (2021) Effect of Co addition on the creep rupture properties of 9Cr-1.8 W-xCo weld metals. Metall Mater Trans A 52(1):129–142 9. A5.5-96 A (1996) Specification for low-alloy steel electrodes for shielded metal arc welding. ANSI/AWS A5.5-96. AWS, Florida 10. Peñalba F, Gómez-Mitxelena X, Jiménez JA, Carsí M, Ruano OA (2016) Effect of temperature on mechanical properties of 9% Cr ferritic steel. ISIJ Int 56(9):1662–1667 11. Maruyama K, Sawada K, Koike J-I (2001) Strengthening mechanisms of creep resistant tempered martensitic steel. ISIJ Int 41(6):641–653 12. Helis L, Toda Y, Hara T, Miyazaki H, Abe F (2009) Effect of cobalt on the microstructure of tempered martensitic 9Cr steel for ultra-supercritical power plants. Mater Sci Eng, A 510– 511:88–94 13. Wang X, Zhan L-F, Pan Q-G, Liu Z-J, Liu H, Tao Y-S (2010) Microstructure and creep properties of high Cr resisting weld metal alloyed with Co. J Zhejiang Univ, Sci, A 11(10):756–760 14. Saini N, Mulik RS, Mahapatra MM (2018) Study on the effect of ageing on laves phase evolution and their effect on mechanical properties of P92 steel. Mater Sci Eng, A 716:179–188 15. Gustafson Å, Ågren J (2001) Possible effect of Co on coarsening of M23C6 carbide and Orowan stress in a 9% Cr steel. ISIJ Int 41(4):356–360 16. Hajra RN, Rai AK, Tripathy HP, Raju S, Saroja S (2016) Influence of tungsten on transformation characteristics in P92 ferritic–martensitic steel. J Alloy Compd 689:829–836 17. Kabakcı F, Acarer M, Keskinkılıç S, Acar FK (2017) Žilavost osnovnega materiala in zvarov P91. Livarski Vestnik 64(3):154–161 18. Park TC, Kim BS, Son JH, Yeo YK (2021) A new fracture analysis technique for charpy impact test using image processing. J Korean Inst Metals Mater 59(1):61–66

Precipitation and Evolutionary Behavior of Eutectic Carbides in Electroslag Remelted 7Cr13N Steel Shouhui Li, Jing Li, and Shuang Zhu

Abstract The precipitation and evolutionary behavior of eutectic carbides in 7Cr13N steel were investigated and compared with 8Cr13MoV steel. The results showed that the eutectic carbide precipitation at the center and edge of 7Cr13N ingot was reduced by 26.8% and 67.0% compared with 8Cr13MoV ingot. The decrease in carbon content and the increase in solid mass fraction at the start of carbide precipitation are the main reasons for the decrease in eutectic carbide precipitation in 7Cr13N steel. Eutectic carbide will be broken during the cogging process to increase its volume fraction. Then, the eutectic carbides will be dissolved during the diffusion annealing process, and the undissolved eutectic carbides will be further broken and dispersed during the hot rolling process. The eutectic carbide will not change basically after the end of hot rolling. The size of the eutectic carbide that remains in the final tool is between 3–5 µm. Keywords Eutectic carbides · High-carbon martensitic stainless steel · Nitrogen · Electroslag remelting

Introduction High-carbon martensitic stainless steel contains more than 0.6wt% C and more than 13wt% Cr, and is widely used to manufacture high-grade kitchen knives, razors, and other products that require high hardness, strength and good corrosion resistance [1, 2]. The high content of C and Cr elements leads to the precipitation of a large number of large, irregular M7 C3 eutectic carbides from the liquid steel at the end of solidification [3, 4]. Residual eutectic carbides in the finished tool will reduce its serviceability and should be made to dissolve and break up as much as possible during the production process [5]. The dissolution and fragmentation behavior of S. Li · J. Li (B) · S. Zhu State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing 100083, China e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_124

1439

1440

S. Li et al.

eutectic carbides during the production of high-carbon martensitic stainless steel is closely related to the precipitation of secondary carbides during spheroidal annealing and the performance and structure of the finished tool [6]. The production of high quality high-carbon martensitic stainless steel needs to go through electroslag remelting, cogging, diffusion annealing, hot rolling, spheroidal annealing, cold rolling, recrystallization annealing, quenching, and tempering processes. The eutectic carbide morphology and quantity will evolve differently in different production processes. The eutectic carbide evolution behavior will be influenced by the original state of the eutectic carbide in the as-cast ingot and the parameters of each process. Carbon and nitrogen are interstitial atoms that have similar solid solution strengthening and precipitation strengthening effects in steel [7–10]. In the present study, a 7Cr13 high-carbon martensitic stainless steel with 0.084% nitrogen content is introduced and compared with 8Cr13MoV steel to analyze the effect of “reduce carbon content and increase nitrogen content” on eutectic carbides. In addition, the evolutionary behavior of eutectic carbides in the new high-nitrogen 7Cr13 steel is discussed by thermodynamic analysis, carbide observation and statistics.

Experimental Procedure The chemical composition of 7Cr13N and 8Cr13MoV steels is shown in Table 1. Samples were taken for carbide observation in electroslag remelting, cogging, high temperature diffusion annealing, hot rolling, recrystallization annealing, and tempering processes, respectively. The eutectic carbide distribution was observed by scanning electron microscopy in backscattering mode after the specimens were ground and polished, and the volume fraction of eutectic carbide was counted by Image-Pro software. After the specimens were eroded by FeCl3 alcohol solution (25 mL alcohol, 25 mL hydrochloric acid, and 5 g ferric chloride), the morphology of eutectic carbides was observed by scanning electron microscopy in secondary electron mode. Thermo-Calc thermodynamic software was used to calculate the equilibrium phase diagram of the 7Cr13N steel. Table 1 Chemical compositions of remelted ingots (wt%) C

N

Cr

V

Ti

Si

Mn

Ni

7Cr13N

0.725

0.084

13.11

0.11

0.005

0.20

0.50

0.06

8Cr13MoV

0.823

0.042

13.82

0.15

0.005

0.35

0.38

0.14

Precipitation and Evolutionary Behavior of Eutectic Carbides …

1441

Results and Discussion Precipitation Behavior of Eutectic Carbides During Solidification The type of eutectic carbide in 7Cr13N and 8Cr13MoV steels has been identified as M7 C3 in previous studies [3, 4, 11]. Figure 1 shows the distribution of eutectic carbides in the center and edge positions of 7Cr13N and 8Cr13MoV electroslag remelting ingots, where the black part is eutectic carbides and the gray part is the steel matrix. The amount of eutectic carbides precipitated in 8Cr13MoV steel is significantly more than that in 7Cr13N steel. The precipitation of eutectic carbides in the center of the ingot exceeds the precipitation of eutectic carbides at the edges. In the center of the 8Cr13MoV ingot, a large number of eutectic carbides are connected with each other to form the network structure. The volume fraction of eutectic carbides in the ingot was further counted and the results are shown in Fig. 2. The volume fractions of eutectic carbides in the center and edges of 7Cr13N ingots are 1.34% and 0.31%, respectively, which are 26.8 and 67.0% lower compared to 1.83 and 0.94% in the center and edges of 8Cr13MoV ingots. Nitrogen is not a forming element of the eutectic carbide M7 C3 [4, 12], and the amount of eutectic carbide in high-carbon martensitic stainless steel depends on the content of C and Cr elements. The reduction of carbon content in the steel significantly reduces the precipitation of eutectic carbides during solidification. The precipitation and growth of eutectic carbides in high-carbon martensitic stainless steels is related to the supersaturation of alloying elements in the liquid steel, heterogeneous nucleation particles, dendrite spacing, and solid phase mass fraction at the time of carbide precipitation [3, 4, 12]. The mass fractions of solid for eutectic carbide precipitation in 7Cr13N and 8Cr13MoV steels are 0.944 and 0.917, respectively. The low content of carbon atoms in the liquid steel during solidification and the inhibitory effect of nitrogen on the segregation of carbon elements make the solid mass fraction corresponding to eutectic carbide precipitation in 7Cr13N steel higher, which will facilitate the inhibition of sufficient growth of carbides [4]. The dendrite morphology and dendrite spacing statistics of 7Cr13N and 8Cr13MoV steel ingots at different locations are shown in Figs. 3 and 4, respectively. The spacing of secondary dendrites at different locations in the 7Cr13N ingot is larger than that of 8Cr13MoV ingot, indicating that the reduction of carbon content does not play a role in refining the dendrites. Both the increase in carbon and nitrogen content favors the refinement of secondary dendrites [13, 14]. The effect of decreasing carbon content on the coarsening of secondary dendrites exceeds the effect of increasing nitrogen content on the refinement of secondary dendrites, and the coarse secondary dendrites will be detrimental to the refinement of eutectic carbides. The higher N content in 7Cr13N steel allows the precipitation of more (Ti, V) N precipitated phases during solidification, which will facilitate the precipitation of eutectic carbides by heterogeneous nucleation [12]. Therefore, the reduction of eutectic carbide precipitation caused by “reduce carbon content and increase nitrogen

1442

S. Li et al.

Fig. 1 Distribution of eutectic carbides in electroslag remelting ingots: a and b 8Cr13MoV, c and d 7Cr13N Fig. 2 Statistical results of area fraction of eutectic carbides in ingots

content” in high-carbon martensitic stainless steel is mainly due to the reduction of carbide forming element (carbon) content and the increase of solid mass fraction at the beginning of carbide precipitation caused by the reduction of carbon content.

Precipitation and Evolutionary Behavior of Eutectic Carbides …

1443

Fig. 3 Dendrite morphology in the center and edge positions of electroslag remelted ingots: a and b 8Cr13MoV, c and d 7Cr13N Fig. 4 Statistical results of secondary dendrite spacing in different positions of ingots

Evolutionary Behavior of Eutectic Carbides During Heat Treatment Figure 5 shows the equilibrium solidification phase diagram of 7Cr13N steel, in which the alloying elements can be fully diffused and finally reach equilibrium

1444

S. Li et al.

Fig. 5 Diagram of the equilibrium solidification of 7Cr13N steel

during the calculation using this model. The existence temperature range of M7 C3 eutectic carbide is 577–1180 °C, and the carbide precipitation mass fraction is up to 8.07%. Equation (1) was used to complete the conversion between eutectic carbide volume fraction and mass fraction: W (Carbide) =

ρcarbide Vcarbide ρcarbide Vcarbide + ρsteel Vsteel

(1)

where W (carbide) is the carbide mass fraction, ρ carbide and ρ steel are the densities of carbide and steel matrix, and V carbide and V steel are the volume fractions of carbide and steel matrix. The densities of M7 C3 eutectic carbide and steel matrix are 6.77 g·cm−3 and 7.31 g·cm−3 , respectively [15]. The mass fraction of M7 C3 eutectic carbide at the center and edge positions of the 7Cr13N ingot was calculated by Eq. (1) as 0.87% and 0.28%, respectively. The corresponding equilibrium temperatures in the equilibrium phase diagram are 1150 °C and 1170 °C, respectively. This means that the eutectic carbides in the center and edge positions of the 7Cr13N ingot can only start to dissolve when the heat treatment temperature exceeds 1150 and 1170 °C. The heat treatment temperature and time of different production processes of high-carbon martensitic stainless steel are shown in Table 2. Only the temperature of the holding process before cogging and the diffusion annealing process is higher than 1150 °C and the holding time is long, the eutectic carbide has the conditions for dissolution.

Dissolution and Fragmentation of Eutectic Carbides The evolutionary behavior of eutectic carbides during electroslag remelting, cogging, diffusion annealing, and hot rolling is shown in Fig. 6.

Precipitation and Evolutionary Behavior of Eutectic Carbides …

1445

Table 2 Process parameters for the production process of high-carbon martensitic stainless steel Process

Heat treatment temperature

Heat treatment time

Before cogging

1200 °C

120 min

Cogging

Below 1200 °C

–

Diffusion annealing

1200 °C

60 min

Hot rolling

Below 1200 °C

–

Spheroidal annealing

Max. 860 °C

8h

Cold rolling

25 °C

–

Quenching

1050 °C

10 min

Tempering

180 °C

120 min

Fig. 6 Evolutionary behavior of eutectic carbides during the production of high-carbon martensite

The morphology of eutectic carbides in as-cast ingots is irregularly blocky, fibrous, and spherical. The main purpose of the holding process before cogging is to austenitize the ingot so that it can be deformed during the cogging process. The content of alloying elements around the eutectic carbide in the ingot is high, and only a small amount of carbide is dissolved during the holding process before cogging. Passivation of the eutectic carbide tip occurs at the end of the holding time, and the volume fraction increases slightly compared to the volume fraction of carbide in the ingot. This is due to the precipitation of secondary carbides during the cooling process. The eutectic carbides were fragmented and lined along the rolling direction after the cogging treatment, and the carbide volume fraction increased to 1.53%. The eutectic carbides dissolved heavily during the diffusion annealing process and the carbide volume fraction decreased to 0.95%. The removal rate of eutectic carbide was 37.9%

1446

S. Li et al.

and the size of the remaining eutectic carbide became smaller. The remaining eutectic carbides are further fragmented and dispersed during the hot rolling process, and the high content of alloying elements around the eutectic carbides leads to the precipitation of a large number of secondary carbides during the cooling process. It is noting that the volume fraction of eutectic carbides is higher than the amounts of eutectic carbides actually present in the steel plate due to the presence of secondary carbides, except for the volume fraction of eutectic carbides in electroslag remelting ingots.

Residual Eutectic Carbide The temperature and holding time of spheroidizing annealing, cold rolling, recrystallization annealing, quenching, and tempering heat treatment at the end of the hot rolling process cannot meet the thermomechanical conditions for eutectic carbide dissolution, and carbide will not dissolve and eventually remain in the finished tissue. Figures 7a,b show the microstructure of 7Cr13N steel after recrystallization annealing and tempering, respectively, where the microstructure after tempering is consistent with the microstructure of the final tool product. It can be seen that the size of the eutectic carbide left in the final finished tissue mostly between 3–5 µm, which is larger than the secondary carbide. Residual eutectic carbide is often the first to flake off and form pits during tool use, resulting in unstable tool performance. In the production process, the eutectic carbide dissolution should be improved during the diffusion annealing process. Zhu’s study [5] shows that eutectic carbide removal rate in 8Cr13MoV steel could reach 92.8% when the holding time of diffusion annealing was extended from 1 to 2 h. The removal of eutectic carbides significantly improves the sharpness of the tool.

Fig. 7 Residual eutectic carbides in the finished tissue: a recrystallized annealed structure, b tempered structure

Precipitation and Evolutionary Behavior of Eutectic Carbides …

1447

Conclusion (1) The reduction of carbon content can effectively reduce the precipitation of eutectic carbides during the solidification of steel. The volume fractions of eutectic carbides in the center and edges of 7Cr13N ingots are 1.34 and 0.31%, respectively, which are 26.8 and 67.0% lower compared to 1.83 and 0.94% in the center and edges of 8Cr13MoV ingots. (2) The reduction of carbon content and increase of nitrogen content in martensitic stainless steels increases the secondary dendrite spacing and the tendency of carbides to precipitate by heterogeneous nucleation, which will promote the precipitation of eutectic carbides during solidification. The decrease in carbon content and the increase in solid mass fraction at the start of carbide precipitation are the main reasons for the decrease in eutectic carbide precipitation in 7Cr13N steel. (3) The eutectic carbide will be broken during the cogging process to increase its volume fraction. Then, the eutectic carbides will be dissolved during the diffusion annealing process, and the residual eutectic carbides will be further broken and dispersed during the hot rolling process. The eutectic carbide will not change basically after the end of hot rolling. The eutectic carbide left in the final tool tissue with the size between 3–5 µm.

References 1. Zhu S, Li J, Li SH, Sun C (2023) Effect of quenching and tempering processes on sharpness of knives made from 6Cr13 high-carbon martensitic stainless steel. Trans Indian Inst Met. https:// doi.org/10.1007/s12666-023-03058-1 2. Bush R, Gill J, Teakell J (2016) Heat Treatment Optimization and Fabrication of a 440C Stainless Steel Knife. JOM 68(12):3167–3173. https://doi.org/10.1007/s11837-016-2117-5 3. Zhang J, Li J, Shi CB, Huang J (2021) Growth and agglomeration behaviors of eutectic M7C3 carbide in electroslag remelted martensitic stainless steel. J Mater Res Technol 11:1490–1505. https://doi.org/10.1016/j.jmrt.2021.01.113 4. Li SH, Li J, Sun C, Zhu S (2023) Effect of nitrogen content on the precipitation and growth behavior of eutectic carbides M7C3 in electroslag remelted 7Cr13 steel. J Mater Res Technol 24:9793–9807. https://doi.org/10.1016/j.jmrt.2023.05.178 5. Zhu QT, Li J, Zhang J, Shi CB (2019) Effect of primary carbides on the sharpness of kitchen knives made of 8Cr13MoV steel. J Mater Eng Perform 28(8):4511–4521. https://doi.org/10. 1007/s11665-019-04209-6 6. Yu WT, Li J, Shi CB, Zhu QT (2017) Effect of spheroidizing annealing on microstructure and mechanical properties of high-carbon martensitic stainless steel 8Cr13MoV. J Mater Eng Perform 26(2):478–787. https://doi.org/10.1007/s11665-016-2461-1 7. Gu JB, Li JY, Chang RJ, Li LH (2019) Comprehensive effect of nitrogen on Cr-Mo-V hotworking die steel with enhanced strength and toughness. Mater Sci Eng A 766:138386. https:// doi.org/10.1016/j.msea.2019.138386 8. Feng H, Li HB, Jiao WC, Jiang ZH, Cai MH, Zhu HC, Chen ZG (2019) Significance of partial substitution of carbon by nitrogen on strengthening and toughening mechanisms of high

1448

9.

10.

11.

12.

13. 14.

15.

S. Li et al.

nitrogen Fe-15Cr-1Mo-C-N martensitic stainless steels. Metall Mater Trans A 50A(11):4987– 4999. https://doi.org/10.1007/s11661-019-05398-4 Gu JB, Li JY, Yanagimoto J, Li LH (2021) Microstructural evolution and mechanical property changes of a new nitrogen-alloyed Cr–Mo–V hot-working die steel during tempering. Mater Sci Eng A 804:140721. https://doi.org/10.1016/j.msea.2020.140721 Cai X, Hu XQ, Zheng LG, Li DZ (2021) Redistribution of C and N Atoms in High Nitrogen Martensitic Stainless Steel During Cryogenic Treatment. Acta Metall Sin (Engl Lett) 35(4):591–595. https://doi.org/10.1007/s40195-021-01265-7 Zhu QT, Li J, Zhang J, Shi CB, Li JH (2019) Precipitation mechanism and reduction of amount of primary carbides during electroslag remelting of 8Cr13MoV stainless steel. Metall Mater Trans B 50(3):1365–1377. https://doi.org/10.1007/s11663-019-01573-5 Shi CB, Zhu QT, Yu WT, Song HD, Li J (2016) Effect of oxide inclusions modification during electroslag remelting on primary carbides and toughness of a high-carbon 17 mass% Cr tool steel. J of Materi Eng and Perform 25(11):4785–4795. https://doi.org/10.1007/s11665-0162361-4 Won YM, Thomas BG (2001) Simple model of microsegregation during solidification of steels. Metall Mater Trans A 32(7):1755–1767. https://doi.org/10.1007/s11661-001-0152-4 Li SH, Li J, Zhang J, Shi CB (2023) Effect of nitrogen on microstructure and microsegregation of martensitic stainless steel 4Cr13 produced by electroslag remelting. J Iron Steel Res Int 30:1854–1861. https://doi.org/10.1007/s42243-022-00851-y Zhang J (2021) Formation and dispersion control of carbides in the steel used for high-quality knives and shears. Ph.D. thesis, University of Science and Technology Beijing

Part XXXVIII

High Temperature Electrochemistry: An FMD Symposium Honoring Uday B. Pal

Considerations for Measuring High Electrical Conductivity Molten Salts with Concentric Electrodes Thomas Villalón

Abstract New technologies are requiring the use of molten salts (i.e. electrolytic cells, certain fusion reactor designs, etc.). As a result, thermoelectric properties like electrical conductivity are required to further these design efforts. To increase the accuracy of the electrical conductivity measurements, several factors need to be taken into account. In particular, molten salt wetting characteristics, materials selection, and measurement geometry must be thoroughly evaluated to ensure accurate data is measured while maintaining an accurate calibration in a highly dynamic environment. These factors will be discussed in the context of a concentric electrode measurement apparatus. Keywords Electrical conductivity · Surface tension · Materials compatibility · Electrode geometry

Introduction In the past several decades, molten salts have been used in a variety of applications, whether commercially applicable or only in academic settings. These use cases, among others, include: nuclear reactors, solar energy storage, fuel cells, metal producing electrolytic cells, and fusion reactors [1–3]. In looking at these applications, large scale deployment of fuel cells, metal producing electrolytic cells, and fusion reactors require careful modeling due to the non-linear behaviors seen while scaling these technologies. Here, electrical conductivity is a fundamental property that underlies all of these technologies and is something that should be measured with great care. With it, proper electrical conduction and thermal conduction can be

T. Villalón (B) Phoenix Tailings, Inc., 8 Henshaw Street, Woburn, MA 01801, USA e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_125

1451

1452

T. Villalón

achieved, allowing continuous operation of the technology. Given the extreme conditions that these aforementioned systems operate at, measurement of these salts respective electrical conductivity must be done in a reliable and robust manner utilizing materials that can withstand the system’s operating conditions.

A Review of Concentric Electrodes Measurement Technique A review of molten salt electrical conductivity characterization techniques indicates that a variety of different methods exist. These include: capillary tubes, parallel plates, parallel rods, and concentric electrodes [2, 4–7]. These electrodes are primarily used in conjunction with electrochemical impedance spectroscopy (EIS) to determine a system’s impedance, which can be used to determine electrical conductivity. Variations of these methods have been used to measure molten salts’ electrical conductivities, but practical limitations can complicate their usage. One of the biggest limitations is the sophisticated fabrication required to make these apparatuses. For high conductivity applications, a capillary tube setup is favored [4]. This setup requires working with fragile glass tubes that require some level of further manipulation, typically some type of hot glasswork. This highly specialized work can limit the amount of setups that can be made. In addition, these capillary experiments require “at temperature” calibrations to determine the cell constant. During calibration, these instruments can be thermally shocked, making premature equipment failure a possibility. For high electrical conductivity measurement methods, the concentric electrodes are particularly interesting because they do not require determining the cell constant prior to their utilization due to their geometry [7]. Furthermore, the electrodes’ simple geometry, a rod and tube of arbitrary thickness, allow for a variety of materials to be used without highly elaborate fabrication. At worst, holes have to be drilled and tapped to make electrical connections to current collectors. A variation of this apparatus can be seen in Fig. 1. For objects operating under extreme conditions, which tend to be brittle or hard to work with, ease of manufacture is a critical factor for high temperature materials. Additionally, the robust nature of the apparatus’ design and materials means that several experiments can be run with the exact same equipment or at least components of the equipment. Once the apparatus is built, it can be quickly calibrated with a known molten salt prior to further experimentation after minor descaling and cleaning.

Geometric Analysis of Concentric Electrodes Looking at the concentric electrode design, the conductivity of a system can be analyzed as the inverse of resistivity, as seen in Eq. 1:

Considerations for Measuring High Electrical Conductivity …

1453

Fig. 1 Side view and top view of concentric electrode assembly

σ =

1 ρ

(1)

where ρ is in units of Ohm meter and σ is in units of Siemens/meter or 1/(Ωm) [7]. A closer examination shows that the resistance of a system can be tied into the resistivity of a system via Eq. 2, ρ= R∗

A l

(2)

where A is the area of electrodes in units of square meters and l is the distance between the electrodes in units of meters. Equation 2 is meant to show the relationship between square plates but can also be generalized using a geometric cell constant, G, in place of Al . Combining Eqs. 1 and 2, the equation derived for measuring conductivity using the concentric electrode apparatus is Eq. 3 after applying a geometric constant factor: (b)

σ =

ln a ∗ 2π

( d

1 Rsalt

dz

) (3)

where b is the inner diameter of the outer electrode in units of meters, a is the outer diameter of the inner electrode in units of meters, Rsalt is the resistance of the molten salt in units of Ohms, and z is the immersion depth of the electrodes in units of meters [7]. It is important to note here that Rsalt is not the total resistance of the system. Rsalt has two distinct features, show in Eqs. 4 and 5:

1454 Table 1 Conductivity data from an aluminum oxyfluoride salt

T. Villalón

Immersion depth (m)

Resistance (Ω)

Conductance (S)

0.0127

0.311

3.22

0.015875

0.204

4.91

0.01905

0.142

7.03

Rsalt = Rohmic − Rleads − Relectrodes Rsalt =

1 1 + Rradial Rfringe

(4) (5)

where Rohmic is the total ohmic resistance of the system in units of Ohms, Rleads is the resistance of the leads in units of Ohms, Relectrodes is the resistance of the electrodes in units of Ohms, Rradial is the radial resistance of the molten salt in units of Ohms, and Rfringe is the upper and lower fringe resistances of the molten salt in units of Ohms. Equations 3 through 5 have a profound impact on the accurate measurement of the electrical conductivity of molten salts with different variables affecting different parts of the measurement. Equation 3 is worth starting with since it defines the geometric constraints of an accurate apparatus. A general rule of thumb for measurements of this nature is that the resistance of the molten salt must be the dominant resistance for this system by a factor of 5–10. For that to be the case, the geometry of the electrodes must compensate for this. This can be seen in a set of data collected in Table 1 on the conductivity of a oxyfluoride aluminum salt with a composition of 12 wt% CaO, 9 wt% Al2 O3 , 4 wt% YF3 , and bulk eutectic MgF2 –CaF2 . Since the resistance of the leads and electrode was 0.03 Ω, data points with lower immersion depths were out of bounds for this apparatus and data points with higher immersion suffered from fringe effects. Using Eq. 3, the conductivity for this system was found to be 147 S/m. Knowing that the geometry for this system was a 0.04445 m outer diameter and a 0.009525 m inner diameter, it is worth examining how large the outer electrode diameter should be to get more data points within tolerance across different conductivity values. Using Eq. 6, the resistance of a tube, an outer diameter dimension can be calculated for a maximum depth of 0.0381 m with an expected ohmic resistance of 0.15 Ω (i.e. 5 times larger than the apparatus resistance) and an inner electrode diameter of 0.04445 m [8]. Rsalt

( ) b ρ ∗ ln = 2πl a

(6)

Here, ρ is the resistivity of the system in units of Ohm meter, l is the immersion depth of the salt in units of meters, b is the outer diameter of the tube in units of meters, and a is the inner diameter of the tube in units of meters. Performing an analysis

Considerations for Measuring High Electrical Conductivity … Table 2 Outer electrode inner diameter as a function of salt conductivity

Conductivity (S/m)

1455

Outer electrode inner diameter (m)

50

0.06

75

0.14

100

0.35

125

0.85

150

2.08

175

5.10

200

12.53

from 50 to 200 S/m, Table 2 was created to show the necessary outer diameter for a 0.15 Ω measurement. Looking at the outputs of Table 2, the jump in outer electrode diameter is quite drastic upon reaching a conductivity of 125 S/m. Practically speaking, the only setup small enough for conventional lab furnace use is the 0.14 m setup, but this falls on the lower end of expected conductivities. So, either a shallower immersion depth should be targeted, or efforts must be taken to reduce the leads and electrodes resistance.

Material Selection for Concentric Electrodes Given the analysis from Table 2, care must be given to the materials that the apparatus is made out of. Firstly, the materials must be inert to the salt, otherwise in-situ reacts can occur that will make any measurements inaccurate. Additionally, efforts must be made to decrease the resistance of the system as much as possible while maintaining geometric accuracy. Looking at room temperature resistivities, a handful of materials stand out as good candidates for portions of the apparatus. Copper and aluminum are excellent conductors with good mechanical strength, and they should be used whenever temperatures are low enough for extended use. However, given that molten salt operating temperatures tend to be greater than 700 °C, both copper and aluminum may suffer from creep and degradation during testing. Equation 2 indicates that the length of item is a key contributing factor to the overall resistance of a system. So, attempts were made to minimize this component of the apparatus’ resistance. Prior experience has indicated that molybdenum or steel rods have made good current collectors with robust strength at temperature. Graphite could also be used in extremely volatile salt environments, but if the rods are too long and thin, they tended to fracture from small mechanical perturbations. Among those three materials, molybdenum was generally favored due to its higher electrical conductivity, which lowered the apparatus’ resistivity on longer current collector rod lengths. Additionally, these rods were machined to make threads that could then go into electrode bodies of steel, graphite, or copper, depending on the operating temperature of the molten salt. Generally, steel was favored in making the

1456

T. Villalón

electrodes as a compromise of high melting point, reasonable conductivity, and ease of fabrication. Again, graphite could be used in place of steel if corrosion was an expected problem. One item to note as well was if the salt would wet the material to make good electrical contact. One reason that graphite was seldom used for these types of experiments was that certain types of salt would not wet adequately, making EIS measurements highly inconsistent. Fluoride salts in particular were found to wet poorly with graphite. This can be seen by the fact that after the fluoride-based salt cooled, it would slip out of graphite crucibles. So, prior to running EIS tests on new salts, test samples had to be made to determine if the material would wet adequately and provide useful data. To keep things aligned, a ceramic spacer was put on top of the electrodes that keep the electrodes collinear. This had to be a pure dielectric to prevent additional current paths from existing. Typically, a Macor or alumina spacer could be drilled from a thin plate. Under extreme corrosion, boron nitride could be used as well, although its fragile mechanical nature could make long term use difficult. Ironically, boron nitride’s fragility also translated into ease of machinability, making it an ideal candidate to make a batch of spacers that could be changed out as needed. So, as a whole, compromises were made to maximize the conductivity, wettability, and lifetime of the entire system. The key was to pick materials that ensured good connectivity between components, ease of fabrication, and keeping the conductivity of the system as high as possible. So, a typical configuration ended up being molybdenum current collectors, steel electrodes, and a boron nitride spacer.

Fringe Effects for Concentric Electrodes One final note for experimental accuracy comes from the process of taking measurements with the apparatus. Looking at Eq. 4, the resistance of the system comes from two portions of the system, a radial portion and a fringe portion. This can be seen in Fig. 2. Looking at Fig. 2, the path of the current ends up manifesting in a full set of measurements having three regimes: a fringe dominant high resistance regime, a radial dominant linear regime, and a fringe dominant low resistance regime. Initially when the electrodes are immersed, minor wetting of the electrodes occurs. Thus, the fringe portion has the current travel through a tortuous path, making the resistance measurements higher than expected. Upon sufficient immersion, which was generally found to be about 0.009525 m, the radial portion of the system became dominant. Here, the resistance would decrease regularly as the electrodes were systemically immersed further into the molten salt. Lastly, a low resistance regime could occur. If the electrodes were immersed close enough to the crucible’s bottom, then the resistance could drastically drop. This would occur because the lower field lines would interact with the crucible, which was almost always a conducting media, and

Considerations for Measuring High Electrical Conductivity …

1457

Fig. 2 Field line analysis of concentric electrodes

the crucible would then become electroactive. This would make the entirety of the molten salt conducting, dropping the resistance of the measurements sharply. One possible complication that would occur from time to time would be that the viscosity of the salt would exacerbate these fringe effects. If the salt was too viscous, particularly in high molten oxide content salts, the molten salt would wet in very strange fashions, leading the salt to climb up the electrodes in a concave geometry. So, the radial component of the salt would end up being small relative to fringe effects above it. This would give lower resistance signals prematurely and could lead to very strange, non-linear plots. Generally, this was avoided by increasing the diameter of the electrodes or decreasing the viscosity of the molten salt.

Conclusion In the search to better characterize molten salts for large scale applications, new more accurate methods are required to determine properties, like electrical conductivity. As new methods are developed, though, thought must be put into the limitations of each method or apparatus. In the case of concentric electrodes combined with EIS, electrode geometry, materials selection, and field line effects must be taken into account. With good thought and robust design, techniques like this can be quickly adapted and used to further our knowledge and understanding of the fundamental properties of molten salts.

1458

T. Villalón

References 1. Xi X et al (2020) Applications of molten salt and progress of molten salt electrolysis in secondary metal resource recovery. Int J Miner Metall Mater 27(12):1599–1617. https://doi.org/10.1007/ s12613-020-2175-0 2. Wang X et al (1992) Electrical conductivity of cryolitic melts. In: Light metals, pp 57–64. https:// doi.org/10.1007/978-3-319-48156-2_8 3. Moriyama H et al (1998) Molten salts in fusion nuclear technology. Fusion Eng Des 39–40:627– 637. https://doi.org/10.1016/s0920-3796(98)00202-6 4. Bloom H, Heymann E (1947) The electric conductivity and the activation energy of ionic migration of molten salts and their mixtures. Proc R Soc Lond Ser A Math Phys Sci 188(1014):392–414. https://doi.org/10.1098/rspa.1947.0016 5. Lore JD (1974) Electrical conductivity measurements of molten-salt fluxes from an electroslag remelting process, pp 1–14 6. Kim KB, Sadoway DR (1992) Electrical conductivity measurements of molten alkaline-earth fluorides. J Electrochem Soc 139(4):1027–1033. https://doi.org/10.1149/1.2069335 7. Schiefelbein SL, Sadoway DR (1997) A high-accuracy, calibration-free technique for measuring the electrical conductivity of molten oxides. Metall Mater Trans B 28(6):1141–1149. https:// doi.org/10.1007/s11663-997-0070-y 8. Zahn M (1979) Electromagnetic field theory: a problem solving approach. Wiley, Hoboken

Electrically-Enhanced Boron and Phosphorus Removal from Silicon by CaO–SiO2 –Al2 O3 /–MgO Slag Treatment Andreas Diga Pratama Putera, Katri Avarmaa, Matthew Humbert, Himawan Tri Bayu Murti Petrus, Geoffrey Brooks, and M. Akbar Rhamdhani

Abstract It has been recognised that reactions between liquid metal and liquid slag are electrochemical in nature. Hence, manipulation of the reactions (enhancement or retardation) may be expected when an external electromotive force is applied. In this work, the removal of both, boron and phosphorus, from silicon by CaO–SiO2 –Al2 O3 / –MgO slags, enhanced by applying electromotive force (EMF), was investigated. An improved cell configuration was developed and utilized. New data were generated by carrying out experiments in an argon atmosphere at 1773 K for 120 min with different currents (0.5 or 1.0 A) passed through the molten slag and silicon. The change of the element concentrations as well as the current and potential difference across the slag and silicon were tracked and measured. The current and potential readings of the experiments show that the molten CaO–SiO2 –Al2 O3 slag was more electrically conductive than the CaO–SiO2 –MgO slag at 1773 K. The electrical field that was applied to the system reduced the concentration of boron in the silicon by 45.0% for the CaO–SiO2 –Al2 O3 slag (with both electrical currents, 0.5 and 1 A), and 8.3% for CaO–SiO2 –MgO slag (with 0.5 A imposed). The phosphorus concentration in the silicon was not influenced by the electric slag treatment. Keywords Electrochemical reactions · Slag-metal reactions · Boron · Phosphorus · Silicon refining A. D. P. Putera (B) · K. Avarmaa · M. Humbert · G. Brooks · M. A. Rhamdhani (B) Fluid and Process Dynamics (FPD) Research Group, Department of Mechanical and Product Design Engineering, Swinburne University of Technology, Melbourne, VIC 3122, Australia e-mail: [email protected] M. A. Rhamdhani e-mail: [email protected] H. T. B. M. Petrus Department of Chemical Engineering (Sustainable Minerals Processing Research Group), Faculty of Engineering, Universitas Gadjah Mada, Jl. Grafika No.2, Kampus UGM, Yogyakarta 55281, Indonesia © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_126

1459

1460

A. D. P. Putera et al.

Introduction It has been widely accepted that the essence of slag-metal reactions is governed by thermodynamics, and the reactions that occur in the system are naturally electrochemical [1, 2]. The liquid silicon–liquid slag system studied can be described as a heterogeneous reaction, where the liquids are immiscible with each other, and the reactions occur at the interface [1, 3]. The elemental reactions between metal and slag that involve oxidation can generally be described by the following reaction: ) ( [M] + O2− = (MOx ).

(1)

and the equilibrium constant equation for this reaction is: K =

(MOx ) [M]

(2)

Reaction [1] can be described with the following anodic reaction: ) ( [M] = M2+ + 2e− ,

(3)

and subsequent cathodic reaction: ) ( (O) + 2e− = O2− .

(4)

When system includes two liquid phases, slag and silicon in this case, the redox reaction can be written as [4, 5]: 2 [B] + 1.5 (SiO2 ) = 1.5 [Si] + (B2 O3 )

(5)

where [M] and [A] are the metal species in the liquid metal/metalloid phase, (MOx ) and (BO) are the metal oxides in the liquid slag phase. Looking at the two-immiscible liquids and the ionic reactions and transfer between these liquids, the system resembles galvanic cell, named after the scientist Luigi Galvani and Alessandro Volta who created an electrochemical cell in which oxidation–reduction (redox) reaction occurred [6]. Compared to the slag-metal system in an electrically-enhanced cell, there are clear differences. One of the most important differences is that metal primarily conducts electricity, i.e., possesses electrical conductivity. Therefore, in the electrically-enhanced slag-metal system, the liquid metal acts as a molten electrode while the slag acts as the molten electrolyte [7–10]. Nevertheless, the thermodynamics and equilibrium state of the system can be described using Gibbs free energy and Nernst–Planck equation [10, 11]: ΔG 0 = −n F E 0

(6a)

Electrically-Enhanced Boron and Phosphorus Removal from Silicon …

1461

ΔG 0 = −RT lnK

(6b)

−n F E 0 = −RT lnK

(6c)

( E = 0

) RT lnK nF

(6d)

Substituting reaction (2) into Eq. (6d) we get: ( E0 =

) RT (MOx ) ln nF [M]

(7)

where E 0 , R, T, n, F, are the standard potential of the cell (V), molar standard (8.314 J mol−1 K−1 ), absolute temperature (K), electron transfer number, and Faraday’s constant (96,485 J V−1 mol−1 ). Reaction (7) clearly indicates that the equilibrium of the oxidizing reaction can be shifted by applying electromotive force in the cell. This means that one can enhance the yield of slag-metal reaction by manipulating the electric potential of the system. In general, several investigations have studied the removal of impurities from metals/metalloids (specifically silicon) using electrically-enhanced slag-metal reactions. Rhamdhani and co-workers [2, 12] were the first to propose the application of applied external field to enhanced impurities removal from silicon. They studied the removal of boron from silicon using SiO2 –CaO–Al2 O3 slag at 1823 K at various applied potentials and slag compositions. They found that the addition of electric potential to the system enhanced the removal rate of boron by approximately 50 to 125% at 2 and 3 V respectively, for 35CaO–65SiO2 slag system. The addition of electrical potential to the Si-slag system also improved boron removal at equilibrium by approximately 13 and 21% in the mentioned system. Wang et al. [13] studied the mechanism of boron removal from silicon alloy using electric field slag treatment (CaO–SiO2 –Al2 O3 ) at 1773 K for 120 min and also demonstrated that higher voltage applied can improve the boron removal from the silicon alloy from approximately 10% to 60% using 0.5 V and 6 V, respectively. In addition, the mechanism of boron removal by enhanced electric field slag treatment was proposed as follows: (1) oxygen mass transfer from slag to silicon-slag interface, (2) oxygen ion reaction with boron, i.e., oxidation of boron, and (3) mass transfer of boron oxide to the slag. It was also reported that the oxygen is supplied by the reduction of SiO2 in the slag phase [13]. In a different metal-slag system, Kim et al. [9] studied the enhanced desulphurization of molten steel with SiO2 –CaO–Al2 O3 –MgO slag and proposed both the kinetics equation and mechanism of the process. Although there have been a number of works, these literatures only present limited information and discussion on the applied electrical signals or microstructures of the slag-metal phases. These omissions contain critical information related to operation of the electrochemical cell within the context studied. This work aims to investigate the effects of an applied electromotive force

1462

A. D. P. Putera et al.

Table 1 Summary of experimental program Slag Compositions (wt%)

Alloy Composition

45SiO2 –45CaO–10Al2 O3

Si (bal) 400 ppmw B 400 ppmw P

45SiO2 –45CaO–10MgO

T, K

Duration

Voltage limit, V

Current limit, A

1773

120 min

5

0.5; 1.0

1773

120 min

5

0.5

for boron and phosphorus removal from silicon using different slag systems, (SiO2 – CaO–Al2 O3 /–MgO). In addition, the microstructure of the slag-metal phases was also examined.

Experimental Method Master Slag and Silicon Preparation The following raw materials for slags making were supplied by Sigma-Aldrich (Merck KGaA, Darmstadt, Germany): calcium oxide (CaO) 99 wt%, silicon dioxide (SiO2 ) 99.5 wt%, aluminum oxide (Al2 O3 ) 99.5 wt%, and magnesium oxide (MgO) 99.5 wt%. The slag compositions used for this study are shown in Table 1. Master slags were prepared by melting mixed oxides with appropriate compositions. Each slag with mentioned compositions were mixed in a ball mill using cylinder container and ceramic balls; rotated at 60 rpm for 60 min. After mixing, the mixture was placed in a Pt crucible (of approximately 30 g each run) and melted in a muffle furnace at 1823 K (1550 °C) for 30 min before casting on a casting steel plate. Remelting was carried out to ensure homogenized composition. The raw materials for the silicon master alloy were 99.99 wt% silicon; crystalline boron powder 99 wt%, and 99.99 wt% phosphorus all from Sigma Aldrich or Alfa Aesar (Thermo Fisher Scientific Inc. Australia Pty Ltd). The silicon master alloy was prepared by melting approximately 120 g of silicon and 0.048 g of each boron and phosphorus inside an alumina crucible (∅ 47 mm × 125 mm height) in a hot zone inside a vertical tube furnace at 1773 K for 120 min under 200 mL/min argon gas flow. The concentration of boron and phosphorus was targeted at 400 ppm for the silicon master alloy, and the composition was measured afterwards with ICP-AES.

Experimental Design In this study, a new cell configuration for the electrically-enhanced reaction experimentation has been developed. The furnace and cell configuration are shown in Fig. 1 (right). The sample included initially 6 g of Si–B–P master alloy and 12 g of

Electrically-Enhanced Boron and Phosphorus Removal from Silicon …

1463

slag contained in reactor alumina crucible. The reactor crucible was placed inside a safety crucible that was attached to alumina pedestal. The sides of the alumina pedestal had holes drilled to provide a pathway for the wires. Before lifting the reactor crucible inside the safety crucible, 99.97% Mo-wire (∅ 1 mm), graphite rods (∅ 5 mm × 100 mm (H)), and alumina shields for Mo-wire were prepared. The electrodes (graphite rods, obtained from Nanyang Xinyu New Material Technology Co., Ltd.) were attached to the Mo-wire using Cotronics Resbond® 360 M binder alumina paste. The electrodes were left overnight to dry before attached to the pedestal and safety alumina crucible. In this setup, the reactor and safety alumina crucibles were not glued to each other so the sample can be removed easily after experiment. This means that the safety crucible and the pedestal setup can be reused. The cruciblepedestal-wiring configuration is presented in Fig. 1 (left). The free ends of the Mowires were connected to a DC power source. Various electric currents, which were supplied using DC power source (PowerLine Electronics Labornetzgerat Regulated Power Supply 522) between the silicon and slag, were imposed from the beginning of the experiment. The experimental program is provided in Table 1. The wires were also connected to the Arduino Current Sensor Module with USB-5801 Advantech DAQNavi Data Logger to record the current of the system and the potential difference between the two graphite electrodes. Initially, the sample was placed in the cold zone inside the vertical tube furnace and the furnace was then sealed. Argon gas with a flow rate of 200 ml/min was flushed

Fig. 1 The experimental assembly of the electrically-enhanced slag-Si reaction system (not in scale) (right); and schematic of crucible setup (left). 1—Alumina tube cover, 2—graphite rod, 3—safety crucible, 4—alumina paste, 5—reactor crucible, 6—Mo-wire, 7—molten silicon alloy, 8—molten slag, 9—drilled holes in the pedestal for Mo-wire

1464

A. D. P. Putera et al.

into the furnace for 15 min to ensure an inert atmosphere. During that 15 min, the DC power source and the Data Logger software were also prepared. The bottom ends of the Mo-wires were connected to the DC power source using alligator pins. The current from the DC power source was set to a particular value for each condition studied as shown in Table 1. It is important to mention that this setup was a closed-circuit slag-metal system (higher current will require higher potential and vice versa). After 15 min of stabilizing the gas atmosphere, the ‘Start Acquisition’ button in the Data Logger software was activated and the pedestal-crucible setup was inserted into the hot zone. It took approximately 1 min to insert the pedestal into the hot zone and seal the system gas tight. The samples were reacted for 120 min under Argon gas after which they were lowered to the cold zone to stop the reaction; and the Data Logger was stopped by clicking ‘Stop Acquisition’ button. It took approximately 20 to 30 s to move the pedestal to the cold zone for quenching.

Analysis and Characterizations To determine the compositions of the initial master slag, master alloy, as well as the boron concentration after experiments in the silicon phase, bulk chemical analyses using inductively coupled plasma atomic emission spectrometry (ICP-AES) were carried out. One gram of each sample was crushed and analyzed for its composition. A scanning electron microscope coupled with energy dispersive spectroscopy detector (SEM–EDS) was utilized to investigate the morphology and elemental compositions of the phases. The samples were prepared by using wet metallographic techniques (mounting, grinding, and polishing) for the SEM–EDS analyses. In this study, the microscopic analysis was carried out using ZEISS Supra 40 Field Emission Scanning Electron Microscope (Carl Zeiss) at Electron and Microscopy Facility in Swinburne University of Technology. The accelerating voltage applied for imaging ranges between 15 to 20 keV, depending on the nature of specimen. In addition, the overall images of the sample were taken by Olympus BX61.

Results and Analysis Current and Potential Responses The current and potential recordings from selected three experiments are presented in Fig. 2. The voltage from the power supply was limited to 5 V, and the current was varied between 0.5 A and 1 A. From the measurements, two separate conditions can be observed: (1) Current-limited condition, where the current reading was the same as that set on the DC power source. This condition occurred when the current was set to 0.5 A for both 10 wt%-Al2 O3 and 10 wt%-MgO slags. (2) Voltage-limited

Electrically-Enhanced Boron and Phosphorus Removal from Silicon …

1465

condition occurred when the potential reading was the same with the voltage set in the DC power source. This condition occurred when the current was set to 1 A. In these two set ups, a higher current in the cell can be imposed when the voltage limit is set to a higher value. In the current-limited condition (Figs. 2b, c), we can compare the resulting potential difference between the two slag compositions (with 10 wt% Al2 O3 and 10 wt % MgO). From the potential readings, it is clear that the resulting potential for slag with 10 wt% MgO was higher than that with 10 wt% Al2 O3 , i.e., 2.65 V and 1.67 V, respectively. The difference is clearly shown in Figure. This result indicates that the electrical resistance for slag with 10 wt% MgO is higher than that with 10 wt% Al2 O3 . Additionally, these measurements indicate that the Si-slag system melted approximately 5–6 min after the samples were placed in the hot zone and the data acquisition was started. This can be seen from the potential drop (see the arrows) at the mentioned times in Figs. 2 and 3.

Bulk Chemical Analysis Results The ICP-AES analysis results of the Si master alloy and slag, and the Si alloy after melting are presented in Tables 2 and 3. The 0 V and 0 A sample results in Table 3 indicate the Si-slag experimental results achieved without applied EMF after 120 min of reaction. Initially, the master silicon had 270 ppm of both boron and phosphorus. Additionally, Fe and Al were measured in the master alloy; possibly being traces from the alumina crucible or from the impurities in the reagent chemicals. Figure 4 shows the boron and phosphorus concentration in the silicon from the experimental studies. In general, in the absence of applied potential, the silicon reacted with 10 wt%-MgO-slag had lower boron concentration than that of reacted with 10 wt%-Al2 O3 -slag. However, when external potential was applied, the silicon that was reacted with 10 wt%-Al2 O3- slag had a lower boron concentration. The boron concentration in the respective sample was reduced by 45% compared to the that without electromotive force (from 100 to 55 ppm). On the other hand, the boron concentration in the silicon that was reacted with 10 wt%-MgO-slag only reduced from 60 to 55 ppm (only by 8.3%) with 0.5 A of applied electric current. This result may be related to the electrical conductivity that was higher in the 10 wt%-Al2 O3 slag, as explained in Figs. 2 and 3. Nevertheless, this result is in line with the previous results which described that the DC electric force can enhance the boron removal from silicon [2, 13]. Phosphorus concentration in the silicon, on the other hand, appeared to be not influenced by the applied electrical current. In general, phosphorus is expected to distribute more in the silicon phase compared to the slag phase [14], whereas boron distributes more in the slag [15–17]. Thus, higher phosphorus concentrations compared to boron are expected in Si. Additionally, a possibility of vaporization [18, 19] of Si, P, and B can influence the composition of the Si phase. Other light metals,

Fig. 2 Current and potential readings of the reacting slag-silicon melt at 1773 K for 120 min under Ar atmosphere. a slag 45SiO2 –45CaO–10Al2 O3 —1A; b slag 45SiO2 –45CaO–10Al2 O3 —0.5A; b slag 45SiO2 –45CaO–10MgO—0.5A

1466 A. D. P. Putera et al.

Electrically-Enhanced Boron and Phosphorus Removal from Silicon … Fig. 3 Potential difference of the Si-Slag melts at 1773 K for 120 min under Ar atmosphere

1467

Melting phase

such as Mg, was found in high concentration in Si in the sample with MgO-containing slag, and consequently Al in Si with Al2 O3 -containing slag.

Microstructure Analysis Results For microstructure analysis, the samples were cut into half (cross-sectionally through the crucible including the electrodes). Ideally, one graphite electrode is immersed in the slag phase and the other electrode is in the silicon melt. Figure 5 shows that both electrodes were submerged into the correct phases, although some silicon droplets can be seen separated from the main silicon melt. The cross section of sample of Si reacted with 45SiO2 –45CaO–10Al2 O3 with applied 10 A was analyzed using Olympus BX61 optical microscope to investigate the microstructure, see Fig. 6. From the image, it is clear that a number of metallic droplets existed at the graphite electrode interface that was immersed in the slag phase. These metallic droplets were further analyzed using SEM–EDS as silicon as shown in Fig. 7. Spectra 1, 2, and 3, which are the droplets located in the slag were found to be pure Si. The slag composition is presented in Spectrum 4, as well as the graphite electrode composition in Spectrum 5. This result appeared to support the mechanism of boron removal proposed by Wang et al. [13] which stated that the oxygen needed to oxidize boron was supplied by the silica in the slag phase and therefore, silicon was produced and deposited on the graphite electrode, following these reactions: Reaction on the cathode (reduction): 3 3 3 SiO2 + 3e− = Si + O2− 4 4 2

(8)

Reaction on the anode (oxidation): ) ( + 3e− B + 3O2− = BO3− 3

(9)

270

–

–

Master Si

Master Slag—10Al2 O3

Master Slag—10MgO

[B] ppm

Sample

–

–

270

[P] ppm

–

–

2E15 n/ cm2 sec). The Peripheral Target Positions (PTP) are of greatest interest because they reside closest to the driver fuel ring, and thus have the highest innate fast-to-thermal flux ratio. The key aim of the HFIR PTP option in this study was to assess the impacts and limitations of thermal neutron filtering in these PTP positions. Figure 7 shows the location of these PTP locations. ATR can shuffle fuel assemblies with varying burnups and burnable absorber contents to compensate for differences in lobe power and experiments with negative reactivity worth, such as those with Cd-baskets, in order to operate up to a full 60day cycle. HFIR’s fuel management scheme is different since its driver fuel loading, which consists of two rings of fuel plates, is entirely replaced every 24-day cycle. Thus, use of experiments with thermal neutron absorbers in the HFIR flux trap must be minimal to maintain cycle length and operational efficiency. A key mission for the irradiation targets in HFIR’s flux trap is production of special isotopes through thermal neutron interactions, which is another reason why experiments with thermal neutron absorbers must be minimal to avoid significant thermal flux reduction in adjacent positions. It is for these reasons that general guidance for use of PTP positions states that experiments containing significant neutron poisons “are discouraged because of their adverse effects on isotope production rates, fuel cycle length, and fuel element power distribution.” [11] While HFIR is uncontested in offering the highest fast flux available in the US, the key questions revolve around how much experimental volume could reasonably be allocated for such experiments without undue impact on HFIR’s other mission priorities.

1506

N. Woolstenhulme et al.

Fig. 7 HFIR core map with PTP locations highlighted [10]

Neutronic Assessments This section describes the neutronics work that has been done to assess each of the options previously described. For each of the options, the primary calculational items of interest are the incident neutron flux (both fast and thermal), the total neutron fluence/cumulative atom displacements, helium production rate due to thermal neutron capture in nickel, and the potential impact that the thermal neutron filter material, either cadmium or gadolinium, has on the cycle length of a given reactor’s irradiation cycle. The latter point is important because both cadmium and gadolinium have very high thermal absorption cross sections. This makes them excellent thermal neutron filters, but the removal of those neutrons means that there are fewer thermal neutrons to sustain the chain reaction in the reactor itself. To compensate, the control shims must be removed/rotated out farther than a reactor without a thermal neutron filter installed. This directly impacts how long the reactor can stay critical in a given irradiation cycle. There are many materials that are envisioned for irradiation in these types of irradiations, but Inconel 625 is used as the target material in this assessment for the purposes of determining neutron flux, atom displacements, and helium production. This alloy was selected because its composition is well known and its high nickel content makes it an interesting test case for assessing helium production through thermal neutron capture and transmutation. Calculations for Option 1 are made using the Common Monte Carlo Design Tool (CMCDT) system as well as the Monte Carlo N-Particle (MCNP) code. The CMCDT system is developed and maintained by the Naval Nuclear Laboratory and MCNP

Challenges and Solutions for Fast Neutron Irradiation of Bulk Material …

1507

is developed and maintained by Los Alamos National Laboratory. The CMCDT system includes the Monte Carlo code MC21 and the Physics Unified Modeling and Analysis (PUMA) system. MC21 is a highly optimized code for the reactor core physics analysis by supporting several complex physical phenomena, including material depletion, thermal and xenon feedbacks, and photon and neutron heating. PUMA is used to process problem dependent specifications, such as geometry and material data, and create MC21 input files.

Neutronics Assessment of Option 1: ATR, Cd-Baskets in Outboard-A Positions As previously discussed, the use of a cadmium-lined basket in the ATR is not a novel concept. However, Cd-baskets are not typically used in outboard-A positions due to their impact on the neutron economy in the reactor. In this assessment, a standard Cdbasket filled with Inconel 625 is placed in both outboard-A positions as well as both small-B positions in the southwest (SW) lobe of the ATR to evaluate the maximum impact to cycle length. The diameter of the basket is scaled to fit the diameter of the experiment position and the basket is modeled over the entire 48'' ATR core height. A cross section of the MC21 model can be seen in Fig. 8. Depletion calculations were made with MC21 to simulate a 40-day HTSS cycle in the ATR with and without the Cd-baskets installed. In both cases, the ATR remained critical for the full 40-day cycle, but the amount of excess reactivity at the end of the cycle was significantly reduced when the Cd-baskets were installed. In practice,

Fig. 8 MC21 ATR model with Cd-baskets installed in SW lobe Outboard-A and small-B positions

1508

N. Woolstenhulme et al.

the ATR tends to operate with some amount of extra excess reactivity to ensure planned cycle lengths are met, so this change is probably tenable, but more detailed evaluations are needed to assess specific core configurations. Table 1 shows the peak neutron flux in the Inconel 625 regions, averaged across the 40-day cycle. Results are normalized to a 32 MW SW lobe power, which is the planned nominal power for an HTSS cycle. The total fluence is calculated via time integration of the neutron flux. The end-of-cycle (EOC) total fast fluence is also shown in Table 1. Neutron fluxes were also calculated in the outer aluminum portion of the Cdbasket to assess the effectiveness of using cadmium as a thermal neutron filter. As can be seen in Table 2, the cadmium sleeve surrounding the Inconel 625 reduces the thermal neutron flux by approximately a factor of ten, while the fast flux remains relatively unchanged. Due to the ATR being a thermal spectrum reactor, there are more thermal neutrons present in the cadmium-shrouded test specimen than there would be in a true fast spectrum reactor. As such, helium production in nickel via thermal neutron capture in 59 Ni and subsequent alpha decay becomes a concern. To estimate the amount of helium present in the Inconel 625 after a 40-day HTSS cycle, the helium production reaction rate from 59 Ni was tallied and integrated with respect to time. Table 3 shows Table 1 Peak neutron flux and fast fluence in Inconel 625 for outboard-A and small-B positions in the ATR. Flux data is averaged across the 40-day cycle and normalized to a 32 MW SW lobe power. Fluence data is the time integrated flux for the entire 40-day cycle Location

Average thermal (0.1 meV) Flux (n/cm2 s)

Average fast-to-thermal ratio

EOC fast (>0.1 meV) fluence (n/ cm2 )

Outboard-A

1.47E + 13

5.55E + 14

45.6

1.93E + 21

Small-B

1.13E + 13

3.27E + 14

33.0

1.13E + 21

Table 2 Effect of cadmium on the neutron flux spectrum. Data is averaged across the 40-day cycle and normalized to a 32 MW SW lobe power Location

Average thermal flux (n/ cm2 s)

Average fast (>0.1 meV) flux (n/cm2 s)

Average fast-to-thermal ratio

Outboard-A positions Outside Cd

1.29E + 14

5.61E + 14

5.9

Inside Cd

1.47E + 13

5.55E + 14

45.9

Inside/outside

0.11

0.99

–

3.29E + 14

3.3

Small-B positions Outside Cd

1.39E + 14

Inside Cd

1.13E + 13

3.27E + 14

33.0

Inside/outside

0.08

0.99

–

Challenges and Solutions for Fast Neutron Irradiation of Bulk Material … Table 3

58 Ni, 59 Ni

Location

1509

and 4 He concentrations after a 40-day HTSS cycle in the ATR

EOC 58 Ni concentration (atoms/b cm)

EOC 59 Ni concentration (atoms/b cm)

EOC 4 He concentration (atoms/b cm)

Outboard-A

3.42E−02

1.45E−05

2.06E−08

Small-B

3.42E−02

9.97E−06

1.09E−08

Table 4 Neutron flux and atom displacements in nickel for fueled test specimens in the SFT of ATR using the BEAST experimental concept [10] Location

Thermal flux (0.1 meV) (n/cm2 s)

Fast-to-thermal ratio

Atom displacement in nickel (dpa/30 days)

ATR SFT BEAST

1.39E + 13

7.46E + 14

53.7

1.04

the calculated 58 Ni concentration, 59 Ni concentration, and helium density at the end of a 40-day HTSS cycle in the ATR.

Neutronics Assessment of Option 2: ATR, Boosted Fast Flux in a Flux Trap Detailed calculations for the BEAST geometry have yet to be performed, but a recent scoping study for fuel specimen testing [10] can provide insight into the capabilities. In that study, seven U–Zr fuel pins were placed inside the BEAST booster element geometry in the south flux trap (SFT) of the ATR and the neutron flux was calculated in the central pin. The BEAST geometry from the study can be seen in Fig. 5. The scoping study also provided atom displacement values for various materials and although Inconel 625 was not explicitly examined, it is approximately 58% nickel so the nickel data from the study is a reasonable approximation. Flux and atom displacement information can be seen in Table 4.

Neutronic Assessment of Option 3: HFIR, Peripheral Target Position Unlike the ATR, HFIR typically uses gadolinium as a thermal neutron filter, which is functionally very similar to cadmium. In this assessment, a small gadolinium-lined capsule filled with Inconel 625 was created in an MCNP model of HFIR Cycle 400 and placed near the core midplane in each of the PTP positions. Figure 9 shows the geometry for this assessment.

1510

N. Woolstenhulme et al.

Fig. 9 MCNP Geometry for HFIR Assessment. a Cross section of experiment capsule, b radial slice of the flux trap with experiment capsules in the PTPs, c axial slice of PTP-D1 (6 o’clock position) showing location of experiment capsule

It should be noted that the ATR assessment assumed that the Cd-basket ran the entire fueled height of the core (48'' ). However, HFIR is a much smaller reactor than the ATR so adding that much thermal neutron filter material would severely impact the results. As such, it was decided to just place a single experiment capsule in the axial center of each PTP position for assessing the impact to cycle length. Similar to the ATR studies, a depletion was performed to simulate 25 days of HFIR operation at 85 MW. A baseline depletion with no experiment capsules installed was also performed for comparison of cycle length. Due to the compact nature of the HFIR core, the neutron filter material does have a measurable effect on the achievable cycle length. This study estimates that the maximum cycle length of HFIR will be reduced by approximately one day if one gadolinium-lined capsule is placed in each of the six PTP positions. If fewer gadolinium-lined capsules were used, or if they were moved away from HFIR core centerline, the impact to cycle length would likely be reduced. Table 5 shows the peak neutron flux in the Inconel 625 regions, averaged across the 24-day cycle. Results are normalized to an 85 MW core power. Calculated EOC atom displacement values are also shown in Table 5. Another thing to consider with HFIR is the impact of thermal neutron absorbing materials on surrounding target positions. One of the primary missions for HFIR is isotope production which relies heavily on an abundance of thermal neutrons. Thus,

Challenges and Solutions for Fast Neutron Irradiation of Bulk Material …

1511

Table 5 Peak neutron flux and atom displacements in Inconel 625 for PTP positions in HFIR per 24-day cycle at 85 MW core power Location

Average thermal (0.1 meV) Flux (n/cm2 s)

Average fast-to-thermal ratio

EOC atom displacement in Inconel 625 (dpa)

HFIR PTP

2.82E + 13

1.17E + 15

41.6

1.6

the presence of the thermal neutron absorbing material could have an adverse effect on isotope generation. Figure 10 shows the percent change in thermal flux in the areas directly adjacent to the gadolinium-lined experiment capsules relative to the baseline case with no gadolinium. As can be seen in the figure, the presence of the experiment capsules causes a decrease in thermal neutron flux of 10–20% across the entire flux trap, with local reductions of 20–30% in the test positions directly adjacent to the experiment capsules. The impact that this reduction in thermal flux would have on isotope production rates has yet to be predicted explicitly but is presumed to be untenable for HFIR’s isotope production missions.

Fig. 10 Change in thermal neutron flux due to the presence of gadolinium-lined capsules in HFIR’s PTPs

1512

N. Woolstenhulme et al.

Table 6 Summary of neutron fluxes for each irradiation option Location

Thermal flux (0.1 meV) (n/ Fast-to-thermal ratio (n/cm2 s) cm2 s)

ATR SFT BEAST 1.39E + 13

7.46E + 14

53.7

ATR Outboard-A

1.47E + 13

5.55E + 14

45.6

ATR Small-B

1.13E + 13

3.27E + 14

33.0

HFIR PTP

2.82E + 13

1.17E + 15

41.6

Summary and Discussion In this assessment, three options for fast neutron testing were evaluated for neutronic feasibility. For each of the options, the primary calculational items of interest were the incident neutron flux (both fast and thermal), the total neutron fluence/cumulative atom displacements, helium production rate due to thermal neutron capture in nickel, and the potential impact that the thermal neutron filter material has on the cycle length of a given reactor’s irradiation cycle. A summary of the calculated neutron flux information is shown in Table 6. Overall, HFIR produces the highest fast neutron flux of all the investigated options, but the amount of test volume that can be utilized without impacting the reactor operating tempo and other mission goals (e.g., isotope production) could be an issue. The size and number of PTP Gd-shielded would need to be sizably reduced to find a viable configuration. Future work should investigate this option. While not assessed explicitly, it should be noted that HFIR PTP irradiations could be very well suited to fast reactor materials which are not so sensitive to spurious thermal neutron effects and can thus be performed without thermal neutron shielding. While this category excludes many alloys of interest since they contain iron and nickel, this category could include materials such as silicon carbide composites. The BEAST option in ATR provides the next highest fast flux and provides ample space for test specimens but is still under development and its commissioning schedule is uncertain. The outboard-A positions in the ATR provide slightly less fast flux than the BEAST option, but they are readily available now and provide adequate volume for several specimens. Since their test cavities are the same diameter, a practical approach should be considered where capsules begin irradiation in ATR Cd-basket outboard-A positions and are later shuffled into BEAST after it is deployed. This strategy is likely the most expeditious path one can pursue to achieve high fast fluences on significant volumes of test specimens.

Challenges and Solutions for Fast Neutron Irradiation of Bulk Material …

1513

References 1. Jensen CB, Woolstenhulme NE (2021) Irradiation performance: fast reactor fuels, vol 2, sec 5. Encyclopedia of Nuclear Energy, 2021 Elsevier Inc, pp 392–406 2. Final Versatile Test Reactor Environmental Impact Statement Summary, DOE/EIS-0542, May 2022 3. Advanced Test Reactor User Guide, September 2021, INL Report INL/EXT-21–64328. https:// inldigitallibrary.inl.gov/sites/sti/sti/Sort_53406.pdf 4. High Flux Isotope Reactor (HFIR) User Guide, Revision 2, November 2015. https://neutrons. ornl.gov/sites/default/files/High%20Flux%20Isotope%20Reactor%20User%20Guide%202. 0.pdf 5. Harp JM, Hayes SL, Medvedev PG, Porter DL, Capriotti L (2017) Testing fast reactor fuels in a thermal reactor: a comparison report. INL/EXT-17–41677, Revision 0, Sep 2017 6. Ingram FW, Ambrosek RG, Chang GS, Utterbeck DJ (2001) JAPEIC irradiation report for the SFT-1, SFT-2, SFT-3 and FELI-2/3 Specimens. INEEL/EXT-01–01174, Sep 2001 7. LaBrier DP, Lilley B, Higgins AM, Palmer TS, Marcum WR (2019) Comparison of fuel meat materials for boosted fast flux concepts at the advanced test reactor. Proceedings of Top Fuel 2019 Conference 8. Boosted Fast Flux Loop Final Report. INL/EXT-09–16413, Sep 2009 9. Curnutt B, Woolstenhulme N, Nielsen J, Oldham N, Weaver K, Jensen C, Fradeneck A (2022) A neutronics investigation simulating fast reactor environments in the thermal-spectrum advanced test reactor. Nucl Eng Des 387 10. Daily CR, McDuffee JL (2019) Design studies for the optimization of 238 Pu production in NpO2 targets irradiated at the high flux isotope reactor. Nucl Technol. https://doi.org/10.1080/ 00295450.2019.1674594 11. In-Vessel Irradiation Experiment Facilities at HFIR. Oak ridge national laboratory, neutron sciences directorate. https://neutrons.ornl.gov/hfir/in-vessel-irradiation#ptp 12. Woolstenhulme N, Brookman J, Jesse C, Downey C, Murdock C (2023) Scoping study for fast flux testing in the advanced test reactor. INL/RPT-23–72212, April 2023

Part XLI

Materials and Chemistry for Molten Salt Systems

Effect of Chloride Molten Salt on the Structural Characteristics of Deposited Carbon-Based Electrolysis Products Tao Rong, Haibin Zuo, Qingguo Xue, and Haoqing Yang

Abstract Electrochemical graphitization in molten salts is a novel method for converting amorphous carbon into graphite materials at relatively low temperatures. For this process, it is of great significance to further understand the correlation between the thermal and physical properties of molten salt and the structural properties of the electrolyte to optimize the molten salt selection further and adjust the product’s microstructure. In this work, the electrochemical transformation of deposited carbon in different chloride (NaCl, KCl, and CaCl2 ) molten salts was studied. The results show that under conditions at a cell voltage of 2.8 V and a molten pool temperature of 900 °C for eight hours, amorphous deposited carbon can achieve graphitization transformation in CaCl2 , accompanied by removing O, N, and S atoms. Pearson correlation analysis of molten salt thermophysical properties and electrolytic product structure showed that the conductivity and viscosity of molten salt affected the change of specific surface area during the electrochemical transformation of deposited carbon. The molecular simulation results show that the charge transfer of cations to cathode DC in molten salt contributes to the change of surface chemical properties of the electrolysis products, and the greater the transfer charge, the greater the degree of graphitization transformation of amorphous carbon, and the greater the removal rate of impurity elements. Keywords Deposited carbon · Molten salt · Thermal properties · Correlation · Charge transfer

T. Rong · H. Zuo (B) · Q. Xue State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing 100083, China e-mail: [email protected] H. Yang Jiangsu Branch of China Academy of Machinery Science and Technology Group Co., Ltd., Changzhou 213000, Jiangsu, China © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_131

1517

1518

T. Rong et al.

Introduction In recent years, due to the low working temperature, simple process, and fast reaction kinetics, the electrochemical strategy of molten salt can convert amorphous carbon into graphitic carbon materials with high graphitization degree and crystallinity, which has attracted the attention of the many of scientific researchers [1, 2]. Jin [3, 4] was the first to study the electrochemical conversion of amorphous carbon to graphite. The conversion of carbon black into graphite by cathodic polarization in melting calcium chloride includes the removal of oxygen atoms from amorphous carbon and the long-distance rearrangement of carbon atoms under cathodic polarization. Based on this strategy, by cathodic polarization in molten calcium chloride, Bishnu P. Thapaliya [5] converted activated coconut charcoal into highly crystalline graphite nanosheets (ID /IG = 0.2, G = 0.82). Huimin Luo [6] uses molten calcium chloride to convert Gasified coal char into crystalline graphite with high specific surface area and porosity (ID /IG = 0.18, G = 0.78). Prashant Bagri et al. [7] converted hard carbon to graphite using an electrochemical pathway of MgCl2 at low temperatures (750 °C). Compared with commercial synthetic graphite, synthetic graphite exhibits significantly enhanced electrochemical performance at a high charge–discharge rate (5C). Tu [8] used inert SnO2 as the anode to achieve graphitization transformation of amorphous carbon in CaCl2 -LiCl molten salt. Zhu [9] used molten calcium chloride to convert coal extracts into petal-shaped graphite nanosheets. Most previous studies focused on exploring the influence of electrolysis parameters (including time, temperature, and cell voltage) on the electrolysis products and the electrochemical application performance of the electrolysis products. There are few reports on the effect of molten salt on the structural characteristics of electrolysis products, especially the effect of molten salt on the removal mechanism of heteroatoms in amorphous carbon during electrochemical transition. Understanding the effect of molten salts on structural characteristics of electrolysis products can help optimize the electrochemical transition process of molten salts and regulate the surface chemistry of the electrolysis products. In this study, different molten salts (calcium chloride, potassium chloride, and sodium chloride) were used to the cathodic electrolysis of amorphous DC. The structural characteristics of electrolytic products under different molten salt electrolyte conditions were comprehensively discussed, and the correlation between the thermal properties of molten salt electrolytes and the structural characteristics of electrolytic products was analyzed. In addition, the adsorption behavior of metal cations in electrolyte and amorphous DC was analyzed by the quantum chemistry method. The charge transfer from cations to DC facilitates the removal of heteroatoms on the surface of DC.

Effect of Chloride Molten Salt on the Structural Characteristics …

1519

Table 1 Element content of the DC sample (wt. %) Element

C

H

O

N

S

Content

85.1

2.384

10.198

1.19

1.128

Experimental Materials The raw material is the deposited carbon (DC) from the coke oven ascension pipe of the coking plant of Tangshan Iron and Steel Co., Ltd., and its main elemental composition is shown in Table 1. The median particle size (d(50)) of DC is 34.7 µm. In addition, anhydrous calcium chloride (Aladdin, AR, 99.9%), sodium chloride (Boer, AR, 99.5%), and potassium chloride (Macklin, AR, 99.5%) were purchased from Sinopharm Chemical Reagents Beijing Co., Ltd.

Experimental Procedure Figure 1 is the molten salt electrochemical transformation diagram. The electrochemical workstation was used for constant cell voltage electrolysis. The cell voltage was set to 2.8 V. The high-purity graphite rod and 1 g DC powder wrapped in stainless steel were used as anode and cathode, respectively. The reaction temperature and electrolysis time were 900 °C and 8 h, respectively. The experimental equipment and operation details for electrolysis were the same as those mentioned in our previous study [10]. Different cathode products could be obtained by changing the molten salt electrolyte (Table 2).

Characterizations After washing and drying, the cathode electrolysis products (EP) were characterized at multiple scales to obtain structural characteristics. The crystal structure of carbon in the sample was studied with an X-ray diffractometer (SMARTLAB-9, Rigaku). According to the position of the (002) peak in the XRD patterns, the interlayer spacing (d002 ) of the carbon material can be calculated by using Eq. (1) [5, 11]. The carbon structure of the synthesized material was tested by Raman spectroscopy (Lab RAM HR Evolution, HORIBA) with a wavelength of 532 nm in the range of 1000– 3000 cm−1 . The N2 adsorption and desorption isotherms of the sample at 77 K were obtained by a specific surface and porosity analyzer (ASAP2020, Micromeritics), and the Brunauer–Emmett–Teller (BET) method and Barrett-Joyner-Halenda (BJH)

1520

T. Rong et al.

Fig. 1 Molten salt electrochemical transition diagram of DC

Table 2 Test generation conditions of electrolytic products No

Temperature(°C)

Cell voltage (V)

Reaction time (h)

Electrolyte

Products

1

900

2.8

8

CaCl2

EP(Ca)

2

900

2.8

8

KCl

EP(K)

3

900

2.8

8

NaCl

EP(Na)

method were used to calculate the specific surface area and pore size distribution of the samples. The chemical properties of the sample surface were detected by X-ray photoelectron spectroscopy (XPS, ESCALAB250Xi, Thermo Fisher Scientific). d002 =

λ 2 sin θ002

(1)

Results and Discussion Structural Characterization of Cathode Electrolysis Products The diffraction peak of the graphite (002) crystal plane indicated that DC was graphitized in CaCl2 molten salt after 8 hours of electrolysis at 2.8 V cell voltage. The graphite layer spacing d002 results calculated by Eq. (1) are shown in Fig. 2b. DC

Effect of Chloride Molten Salt on the Structural Characteristics …

1521

Fig. 2 a XRD patterns; b d002 of the samples; c Raman spectra; d ID /IG of the samples

had a d002 value of 0.3542 nm as a typical amorphous carbon material. After electrochemical treatment, the d002 value of EP (Ca) is significantly reduced, which was close to the ideal graphite (0.3354 nm) [12, 13]. In addition, the d002 values of EP (K) and EP (Na) were slightly larger than those of DC. The Raman spectra of DC, EP (Ca), EP (K), and EP (Na) had two significant peaks, which were the D peak near 1350 cm−1 and the G peak near 1580 cm−1 [14–16], respectively (Fig. 2c). The ratio of ID /IG was usually used as an index to judge the degree of structural ordering of carbon materials. After electrolysis, compared with DC, the degree of carbon ordering in EP (Ca) increased, while the degree of carbon ordering in EP (K) and EP (Na) decreased, which was consistent with XRD results. In addition, these results also indicated that different molten salt electrolytes had different effects on the electrochemical transition process of DC. The effects of different molten salt electrolytes on the structural transformation of DC were further explored by using N2 adsorption and desorption isotherms, BET specific surface area, and pore size distribution at 77 K. Figure 3a and b are the N2 adsorption and desorption isotherms of DC and electrolytic products, respectively. All samples showed significant adsorption before p/po = 1, indicating the presence of macroporous structure [11]. Figure 3c and d are the pore size distribution of DC and electrolytic products, respectively. The specific surface area, pore volume, and average pore size of the samples calculated by BET and BJH methods are listed in Table 3. Among all samples, EP(Ca)

1522

T. Rong et al.

Fig. 3 a N2 adsorption and desorption isotherm of DC; b N2 adsorption and desorption isotherms of electrolysis products; c Pore size distribution of DC; d Pore size distribution of electrolytic products

had the largest specific surface area of 14.3821 m2 /g, followed by EP (K) of 5.7076 m2 /g. Compared with DC, EP (Na) had a smaller specific surface area. After electrolysis, the pore volume of EP (Ca) was the largest, and the pore volume of EP (K) and EP (Na) was smaller than that of DC. In addition, the average pore size of EP (Ca) was the largest, which was 19.2142 nm, and the average pore size of EP (K) and EP (Na) was smaller than that of DC. According to previous studies [10, 12], in calcium chloride molten salt, carbon materials (carbon black, HPC) exhibited complex morphological changes, such as the appearance of petal-like graphite structure, which increased the pore volume and specific surface area of the cathode material. However, according to the results in Table 2, EP (K) and EP (Na) did not seem to show significant morphological changes after 8 h of electrolysis. Especially in the electrolysis process, under the action of molten potassium chloride and sodium chloride, the pores of DC were blocked, which was not conducive to the transfer of molten salts, resulting in a decrease in the electrochemical activity of the cathode, which also explained the Raman results. The degree of ordering of EP (K) and EP (Na) did not change significantly.

Effect of Chloride Molten Salt on the Structural Characteristics …

1523

Table 3 Pore characteristics from the N2 adsorption and desorption Samples

BET surface area/(m2 /g)

1

EP(Ca)

2

EP(K)

No

BJH adsorption cumulative volume of pores/(cm3 /g)

Adsorption average pore diameter/nm

14.3821

0.068092

19.2142

5.7076

0.012619

9.5930

3

EP(Na)

2.4000

0.005355

8.6804

4

DC

4.3213

0.012893

12.3035

The surface chemical properties of DC and electrolytic products were tested by XPS. After electrochemical conversion in different molten salt electrolytes, the total amount of heteroatoms (O, N, and S) on the surface of electrolytic products decreased. Under different electrolyte conditions, O as the main impurity element was removed, and the O/C atomic ratio of the surface layer of EP (Ca) with the highest degree of order was the lowest, which was 0.0401 (Fig. 4a). In this study, applying calcium chloride as a molten salt electrolyte confirmed the above point of view. In potassium chloride and sodium chloride, the removal ability of heteroatoms was significantly weaker. The occurrence state of the oxygen element was further analyzed by deconvolution of the XPS fine spectrum of O1s. Figure 4b–e are the O1s fitting curves of EP (Ca), EP (K), EP (Na), and DC, respectively. It could be seen that there were three primary occurrence states of oxygen, namely C–O (~532 eV), COO– (~535 eV), and C=O (~530 eV) [17]. Under different molten salt electrolytic electrolyte conditions, the occurrence state of O element on the surface of electrolytic products was different, and the relative content of oxygen-containing functional groups is shown in Fig. 4f. The most abundant oxygen-containing group in all samples was C–O. The difference of oxygen-containing functional groups on the surface of electrolytic products was mainly reflected in the relative content of C=O and COO–. In the electrolysis process, oxygen atoms are removed because of the electrochemical conversion of oxygen-containing functional groups. Different molten salt electrolytes are specific for converting different oxygen-containing functional groups. Under the action of sodium chloride molten salt, C–O seems to be preferentially converted to COO– . Under the action of potassium chloride molten salt, C–O may be preferentially converted to C=O. Under the action of calcium chloride molten salt, C–O gradually transformed into COO– and C=O.

Effect of Thermal Properties of Molten Salt on the Structure of Electrolytic Products Through the analysis of the above results, the reason for the change in the carbon structure and surface chemical properties of the electrolytic products was the application of different molten salt electrolytes. In this study, calcium chloride, potassium

1524

T. Rong et al.

Fig. 4 a O/C, and (O + N + S)/C atomic ratios obtained by XPS using by high resolution scans; b O1s of EP (Ca); c O1s of EP (K); d O1s of EP (Na); e O1s of DC; f concentration of functional groups

chloride, and sodium chloride had different electrical conductivities and viscosities at 900 °C, which could be calculated by Eq. (2) and Eq. (3), respectively [18, 19]. Figure 5a and b are the calculation results of conductivity and viscosity of different molten salts. σ = Ae− RT B

D

η = Ce RT

(2) (3)

Figure 5a and b are the calculation results of conductivity and viscosity of different molten salts, respectively. Among the three chlorides, the conductivity of sodium chloride was the highest, followed by calcium chloride and potassium chloride. However, in terms of viscosity, calcium chloride has the largest viscosity, followed by sodium chloride, and potassium chloride has the smallest viscosity. In this study, seven characteristics of electrolytic products, including d002 , ID /IG , BET surface area (BSA), BJH adsorption cumulative volume of pores (BAV), adsorption average pore diameter (APD), (O + N + S)/C, and O/C, were selected to study the correlation with the thermal properties of molten salts. Figure 5c is the correlation heat map between the characteristic index of electrolytic products and the thermal properties of molten salt. The correlation coefficients are classified as follows: 0.8–1.0 represents a strong correlation, 0.6–0.8 represents a strong correlation, 0.4–0.6 represents a moderate correlation, 0.2–0.4 represents a weak correlation, and 0–0.2 represents several correlations or no correlation [20]. According to the results in Fig. 5c, there was a moderate correlation between d002 , ID /IG with conductivity, a negative strong

Effect of Chloride Molten Salt on the Structural Characteristics …

1525

Fig. 5 a Conductivity of molten salt; b viscosity of molten salt; c correlation coefficient between the characteristic index of electrolytic products and the thermal properties of molten salt

correlation between BSA with conductivity, a negative moderate correlation between BAV, APD with conductivity, and a strong correlation between (O + N + S)/C, O/ C with conductivity. There was a strong negative correlation between d002 , ID /IG with viscosity, a strong correlation between BSA, BAV, and APD with viscosity, and a strong negative correlation between (O + N + S)/C and viscosity. Electrolyte conductivity and viscosity were essential parameters for regulating the characteristics of electrolytic products.

Effect of the Adsorption Behavior of Cations on the Structure of Electrolytic Products A simple DC model consisting of seven benzene rings was constructed using Materials Studio 2019 software. The adsorption behavior of Ca2+ , K+ , and Na+ on the benzene ring in the center of the DC model was calculated using the Dmol3 module. The molecular structure was geometrically used with the GGA-PBE functional, and the self-selected non-restrictive was considered in the calculation process. The convergence criterion of geometric optimization was energy of 1.0 × 105 Ha and force field intensity of 2 × 10−3 Ha/nm. In order to compare the adsorption behavior of different molten salt cations on the surface of DC, the adsorption energy Eabs of Ca2+ , K+ , and Na+ on DC is calculated in Eq. (4) [21], respectively. Here, Ex-DC is the total energy of the system; Ex is cation energy; EDC is the energy of DC. All units are Ha.

1526

T. Rong et al.

E abs = E x−DC − E x − E DC

(4)

Figure 6a is the stable adsorption form of different cations on DC. DC had different forms in different adsorption systems, mainly caused by the complex electrostatic attraction and van der Waals force during the adsorption process. In these three adsorption systems, the adsorption energies were negative (Fig. 6b), which indicated that the adsorption process released heat. The adsorption energy of K+ -DC was the smallest, indicating that the heat released was the most and the adsorption structure was the most stable. The complex interaction in the adsorption process was one of the reasons for the structural transformation of DC. In the structure shown in Fig. 6a, the charge numbers of Ca, K, and Na were 0.002, 0.007, and 0.001, respectively. Their initial charge numbers were 2, 1, and 1, respectively, indicating that the molten salt cations transferred a large amount of charge to DC during the adsorption process, which was the cause of the removal of heteroatoms on the surface of DC. Among them, the Ca2+ -DC system has the largest number of transferred charges, and the heteroatom content in EP (Ca) was the lowest.

Fig. 6 a Adsorption of Ca2+ , K+ , and Na+ on the benzene ring in the center of the DC model; b Eabs of different adsorption systems; c charge of cations under different adsorption systems

Effect of Chloride Molten Salt on the Structural Characteristics …

1527

Conclusions The electrochemical transformation of coke oven solid waste DC was carried out by molten salt electrolysis. It was found that under conditions at a cell voltage of 2.8 V and a molten pool temperature of 900 °C for eight hours, DC realized the graphite transformation in molten calcium chloride, and its ID/IG value was about 0.36. In addition, the specific surface area was significantly increased. However, DC showed a decrease in the degree of order in potassium chloride and sodium chloride, accompanied by a decrease in pore volume and average pore size. In the three molten salt electrolytes, the heteroatoms on the surface of DC were removed, and the removal rate of heteroatoms in molten calcium chloride was the highest. There was a strong negative correlation between the specific surface area of the electrolytic product with the conductivity, and a strong correlation with the viscosity. Electrolyte conductivity and viscosity seem to be essential parameters for regulating the characteristics of electrolytic products. The molecular calculation results showed that the charge transfer from the cation in the molten salt electrolyte to the cathode DC contributed to the change of the surface chemical properties of the electrolytic products, which had crucial guiding significance for regulating the electrochemical transformation process of the molten salt recording waste. Acknowledgements This work was supported by the National Natural Science Foundation of China (2019YFC1905705 and U1960205) and China Minmetals Science and Technology Special Plan Foundation (2020ZXA01).

References 1. Shi JL, Ming YW, Wei LS (2022) Electrochemical graphitization in the molten salts: Progress and prospects. Chin J Eng 4(44):546–560 2. Zhu F, Ge J, Gao Y(2023) Molten salt electro-preparation of graphitic carbons. Exploration 3(1) 3. Jin X, He R, Dai S (2017) Electrochemical graphitization: an efficient conversion of amorphous carbons to nanostructured graphites. Chem Eur J 23(48):11455–11459 4. Peng J, Chen N, He R (2017) Electrochemically driven transformation of amorphous carbons to crystalline graphite nanoflakes: a facile and mild graphitization method. Angew Chem 129(7):1777–1781 5. Thapaliya BP, Luo H, Li M (2021) Molten salt assisted low-temperature electro-catalytic graphitization of coal chars. J Electrochem Soc 168(4):46504 6. Thapaliya BP, Luo H, Halstenberg P (2021) Low-cost transformation of biomass-derived carbon to high-performing nano-graphite via low-temperature electrochemical graphitization. ACS Appl Mater Interfaces 13(3):4393–4401 7. Bagri PP, Thapaliya B, Yang Z (2020) Electrochemically induced crystallization of amorphous materials in molten MgCl2 : boron nitride and hard carbon. Chem Commun 56(18): 2783–2786 8. Tu J, Wang J, Li S (2019) High-efficiency transformation of amorphous carbon into graphite nanoflakes for stable aluminum-ion battery cathodes. Nanoscale 11(26):12537–12546 9. Zhu Z, Zuo H, Li S (2020) Preparation of petaloid graphite nanoflakes in molten salt for high-performance lithium-ion batteries. Ionics 26(7):3351–3358

1528

T. Rong et al.

10. Rong T, Guan W, Song W (2022) Electrochemical graphitization transformation of deposited carbon for Li-ion storage: sustainable energy utilization from coke oven solid waste. J Mater Chem A 11(1):84–94 11. Wang R, Lee J, Khoshk Rish S (2022) One-pot synthesis of N-doped carbon nanosheets from Victorian brown coal with enhanced lithium storage. Fuel Process Technol 238:107498 12. Xing B, Zhang C, Cao Y (2018) Preparation of synthetic graphite from bituminous coal as anode materials for high performance lithium-ion batteries. Fuel Process Technol 172:162–171 13. Zhong M, Yan J, Wu H (2020) Multilayer graphene spheres generated from anthracite and semi-coke as anode materials for lithium-ion batteries. Fuel Process Technol 198:106241 14. Jiang J, Yang W, Cheng Y (2019) Molecular structure characterization of middle-high rank coal via XRD, Raman and FTIR spectroscopy: Implications for coalification. Fuel 239:559–572 15. Jiang J, Zhang S, Longhurst P (2021) Molecular structure characterization of bituminous coal in Northern China via XRD, Raman and FTIR spectroscopy. Spectrochim Acta Part A Mol Biomol Spectrosc 255:119724 16. Li K, Liu Q, Cheng H (2021) Classification and carbon structural transformation from anthracite to natural coaly graphite by XRD, Raman spectroscopy, and HRTEM. Spectrochim Acta Part A Mol Biomol Spectrosc 249:119286 17. Wen Z, Yuan Y, Wei J (2022) Study on gas production mechanism of medium- and low-rank coals excited by the external DC electric field. Fuel 324:124704 18. Redkin AA, Nikolaeva EV, Dedyukhin AE (2012) The electrical conductivity of chloride melts. Ionics 18(3):255–265 19. Liang W, Lu G, Yu J (2021) Theoretical prediction on the local structure and transport properties of molten alkali chlorides by deep potentials. J Mater Sci Technol 75:78–85 20. Tong L, Zhang C, Peng Z (2021) Spatial-temporal distribution characteristics and correlation analysis of air pollutants from ships in inland ports. Sustainability 14(21):14214 21. Zhu F, Song WL, Ge J (2023) High-purity graphitic carbon for energy storage: sustainable electrochemical conversion from petroleum coke. Adv Sci 10(8)

Thermodynamic Analysis of Preparation of Fe-Si/Fe3 Si Intermetallic by Treating Valuable Elements in Red Mud with Molten Salt Geng Chen, Hui Li, and Jinglong Liang

Abstract Red mud is an alkaline solid waste generated during the smelting process of bauxite, but its utilization rate is low, and there are still billions of tons of red mud that are not effectively treated every year. In this study, the molten salt electrodeoxidation process was employed to extract valuable elements from red mud. Based on the characterization results of the red mud raw materials, thermodynamic calculations of the reactants in the system were performed using HSC and Factsage thermodynamic calculation software. The results showed that Fe2 O3 and SiO2 in the cathode reacted with CaO in the molten salt to form Ca2 Fe2 O5 and Ca2 SiO4 before electrochemical reduction due to the rapid electrolytic deoxygenation of Fe2 O3 , indicating that the reduction process of the Fe component is Ca2 Fe2 O5 /Fe2 O3 → Fe3 O4 → FeO → Fe; and the reduction process of the Si component is SiO2 /Ca2 SiO4 → Si. Keywords Thermodynamic analysis · Fe-Si/Fe3 Si intermetallic · Molten salt electrode oxidation process

Introduction Red mud is a strongly alkaline solid waste generated during the extraction of alumina from bauxite. Over the past decade, the annual production of alumina has shown a gradual increase, leading to a corresponding rise in the generation of red mud. The accumulation of billions of tons of red mud not only impacts the environment and human health but also results in significant resource wastage [1, 2]. Therefore, seeking effective methods for the comprehensive utilization of red mud holds great significance for the sustainable development of the aluminum industry. G. Chen · H. Li (B) · J. Liang Key Laboratory of Ministry of Education for Modern Metallurgy Technology and College of Metallurgy and Energy, North China University of Science and Technology, Tangshan 063009, Hebei, China e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_132

1529

1530

G. Chen et al.

In an era where composite metal materials find widespread applications, the drawbacks of extracting single metals from red mud have become increasingly apparent. Iron-based intermetallic compounds have emerged as crucial constituents in the field of materials. Fe-Si intermetallic compounds have gained attention due to their high hardness, high melting point, and cost-effectiveness. Moreover, the wide range of silicon content in Fe-Si intermetallic compounds provides a theoretical basis for material modification. However, traditional processes have posed limitations on the preparation of such materials [3–10]. The molten salt electrolysis method offers advantages such as a shorter process, lower temperature and energy requirements, and environmental friendliness when it comes to producing metal elements or alloys [11–13]. This paper proposes a novel approach to directly electrolyzing red mud for the preparation of Fe-Si intermetallic compounds using molten salt electrolysis. Based on thermodynamic calculations and theoretical analysis, it explores the interactions between major oxides in red mud and the molten salt system, as well as the electrode reactions during the electrolytic reduction process. Furthermore, it determines the theoretical reduction sequence of each oxide in the electrolysis process, based on standard Gibbs free energy and theoretical decomposition voltage. This approach provides theoretical guidance and a scientific basis for achieving the desired products from red mud. As a new direction in metallurgical extraction and solid waste recycling, this method holds significant promise for future resource recovery and utilization efforts.

Selection of Molten Salt System and Theoretical Electrolysis Temperature The molten salt electrolysis process generally uses the chloride of alkali metals or alkaline earth metals with a relatively wide electrochemical window as the molten salt material. In addition to the wide electrochemical window, when selecting a molten salt system, other characteristics of the molten salt are typically considered: The raw materials of the oxides to be electrolyzed, as well as their corresponding metals (or semiconductors), should be insoluble in or have very low solubility in the molten salt. Good ionic conductivity and a high solubility of O2− facilitate the smooth progress of the crucial O2− transfer process during the electro-deoxidation. Lower melting point, lower viscosity, non-toxicity, and harmlessness. High thermal stability to prevent reactions with oxide raw materials, electrolytic products, and other experimental equipment in contact with the molten salt. Ease of separation and removal from the obtained electrolytic products. Cost-effectiveness and ease of storage within acceptable cost limits. Chloride salt systems generally use CaCl2 , NaCl, KCl, LiCl, and BaCl2 as raw materials. Among these, LiCl and BaCl2 are expensive, while CaCl2 is cost-effective and has a high O2− solubility. It can be removed from the product at room temperature by washing with water. Figure 1 shows the thermodynamic phase diagrams of two

Thermodynamic Analysis of Preparation of Fe-Si/Fe3 Si Intermetallic …

1531

Fig. 1 Thermodynamic phase diagrams of the CaCl2 -NaCl and CaCl2 -KCl systems

common binary systems: CaCl2 -NaCl and CaCl2 -KCl. As seen from the figure, the melting point of pure CaCl2 salt is as high as 771 °C, often requiring reactions to be conducted at temperatures of 900 °C or higher to ensure fluidity. The addition of a certain proportion of NaCl or KCl to CaCl2 reduces its melting point, allowing reactions to proceed smoothly at lower temperatures. In the CaCl2 -NaCl system, the eutectic point with the lowest melting point is achieved at a molar ratio of 0.52:0.48, with a melting point of 504 °C. In the CaCl2 -KCl system, the lowest melting point is achieved at a molar ratio of 0.25:0.75, with a melting point of 600 °C. Due to the poor O2− solubility and diffusion in NaCl-KCl salt systems, and their strong hygroscopicity, it is advisable to maintain an electrolysis temperature above the eutectic point of the salt system, typically in the range of 200–300 °C, to ensure good fluidity and low viscosity. Therefore, this study selected the CaCl2 -NaCl salt system with a molar ratio of 0.52:0.48, and the thermodynamic research temperature was determined to be 800 °C.

The Relationship Between Standard Gibbs Free Energy and Temperature The red mud raw material studied in this paper is a solid waste generated by a Bayer process aluminum oxide plant, and its component contents are shown in Table 1. In this paper, a thermodynamic analysis will be conducted on the theoretical decomposition voltage of the main oxide components in the given red mud composition and the electrode reactions during the electrolysis process. Table 1 Primary chemical composition of dried red mud Oxides

Fe2 O3

Al2 O3

SiO2

Na2 O

TiO2

CaO

Others

Mass content/%

40.999

23.007

16.908

11.066

5.182

1.347

1.491

1532

G. Chen et al.

Figure 2 provides the standard Gibbs free energy of chemical reactions between the molten salt components and various oxides in the raw material, calculated with 1 mol of oxide as the reference. It demonstrates that the standard Gibbs free energy for these reactions at temperatures ranging from 0 to 1000 °C is consistently greater than 0, indicating that these reactions are non-spontaneous. This rules out the possibility of a reaction between the reactants and the molten salt. To determine the alloy phases formed by Fe and Si metals at different temperatures, the Fe-Si binary phase diagram shown in Fig. 3 was constructed using the Factsage thermodynamic software. From the phase diagram analysis, it can be deduced that at 800 °C, the electrolysis product obtained by quenching in water at 25 °C consists of an alloy phase with a Fe3 Si/ Fe-Si structure. Based on the results shown in Eqs. (1) and (2), it can be observed that the standard Gibbs free energy for the reaction between Ca2+ and O2− is more negative compared to the reaction between Na+ and O2− . This indicates that O2− , which is rapidly deoxygenated at the cathode, is more likely to react with Ca2+ in the molten salt to produce a significant amount of CaO. Furthermore, according to the thermodynamic phase diagram analysis provided in Fig. 4, it can be deduced that CaO can dissolve in the molten salt at 800 °C. Na+ + O2− = Na2 O G 800 ◦ C = −798.55 kJ/mol

(1)

Ca2+ + O2− = CaO G 800 ◦ C = −1251.045 kJ/mol

(2)

Figure 5 presents the relationship between the standard Gibbs free energy and temperature for potential reactions involving the cathode solid and various substances

Fig. 2 A G  -T relationship diagram for the reaction between molten salt and oxide in the raw material

Thermodynamic Analysis of Preparation of Fe-Si/Fe3 Si Intermetallic …

Fig. 3 Phase diagram of Fe-Si alloy at different temperatures

Fig. 4 Thermodynamic phase diagram of the CaCl2 -CaO system

1533

1534

G. Chen et al.

Fig. 5 A G  -T relationship diagram for possible reactions on the cathode solid

in the molten salt. The priority of reactions can be determined based on the magnitude of their standard Gibbs free energy, indicating that Fe2 O3 , SiO2 , and TiO2 in the red mud combine with the dissolved CaO in the molten salt, resulting in transformations into phases like Ca2 Fe2 O5 , Ca2 SiO4 , and Ca3 Ti2 O7 . Subsequently, theoretical decomposition voltage calculations will be performed for the main oxide components in the cathode and their transformed phases.

The Relationship Between Theoretical Decomposition Voltage and Temperature The molten salt electrolysis process involves complex chemical reactions and electrochemical reactions. The theoretical decomposition voltage refers to the minimum voltage that needs to be externally applied when electrolyzing metal oxides. The reaction equation is as follows, as shown in Eq. (3): Mx O y = xM +

y O2 (g) 2

(3)

In the equation, M represents the metal (or semiconductor) element present in the oxide. The relationship between the theoretical decomposition voltage of the reaction and the standard Gibbs free energy of the reaction is given by Eq. (4): G  = − nFE 

(4)

Thermodynamic Analysis of Preparation of Fe-Si/Fe3 Si Intermetallic …

1535

In the formula: G  —the standard Gibbs free energy, kJ·mol−1 ; E  —the theoretical decomposition voltage at standard conditions, V; F—Faraday’s constant, 96,485 C·mol−1 ; n—number of electrons gained or lost in the reaction equation. Theoretical decomposition voltages of the main oxides in red mud and the components of the molten salt were calculated using HSC Chemistry 6.0 thermodynamic calculation software at temperatures ranging from 500 to 1000 °C, and the results are shown in Fig. 6. It can be seen that under the experimental conditions at 800 °C, the theoretical decomposition voltages of CaCl2 and NaCl in the molten salt components are the highest, providing a larger electrochemical window for the electrolysis reaction. Through thermodynamic calculations, it was determined that Fe2 O3 , SiO2 , and TiO2 in red mud combine with CaO dissolved in the molten salt to form Ca2 Fe2 O5 , Ca2 SiO4 , and Ca3 Ti2 O7 , respectively. When a sufficiently high electrolysis voltage is applied, the reduction process of the Fe component occurs step by step, with the reduction sequence being Ca2 Fe2 O5 → Fe3 O4 → FeO → Fe. Due to the possibility of incomplete reaction of some Fe2 O3 within a short time, its reduction process is Fe2 O3 → Fe3 O4 → FeO → Fe. The reduction process of the Si component is Ca2 SiO4 → Si. However, there may still be some SiO2 that has not combined to form Ca2 SiO4 , and its reduction process is SiO2 → Si. The reduction process of the Ti component is Ca3 Ti2 O7 → Ti3 O5 → Ti2 O3 → TiO → Ti, but there may still be some TiO2 that has not participated in the reaction, and its reduction process is TiO2 → Ti3 O5 → Ti2 O3 → TiO → Ti. The reduction process of the Al component is Ca3 Al2 O6 → Al, but there may still be some Al2 O3 that has not participated in the reaction, and its reduction process is Al2 O3 → Al. The reduction process of the Na component is Na2 O → Na. By controlling the electrolysis voltage in the range of − 2.22 to −2.27 V, the reduction of Ca3 Ti2 O7 , TiO, Ca3 Al2 O6 , Al2 O3 , and CaO does not occur during the electrolysis process. Among these, the elemental Na produced by the reduction of Na2 O will facilitate the reduction of other components in the red mud through sodium thermal reduction. In summary, by controlling the range of the electrolysis voltage, it is theoretically possible to use red mud as the cathode material for the preparation of Fe-Si/Fe3 Si intermetallic compounds. Table 3 lists various anode reactions and their corresponding electrode potentials when different anodes are used. According to the results, when a graphite anode is used, the required potential for the generation of CO and CO2 is relatively low. This is advantageous for increasing the cathode potential, thereby promoting the electrode reactions. Additionally, compared to other inert electrodes, graphite electrodes have a lower cost.

1536

G. Chen et al.

Fig. 6 A E  -T relationship diagram for the components of the molten salt and possible substances on the cathode solid Table 3 Standard electrode potential of the anode at 800 °C (vs. Ca2+ /Ca) Reaction equation

Electrode potential/V versus Ca2+ /Ca

2O2− − 4e− = O2 (g)

2.710

C + 2O2− − 4e− = CO2 (g)

1.683

C + O2− − 2e− = CO(g)

1.638

2Cl−

3.292

−

2e−

= Cl2 (g)

The Relationship Between Partial Pressure of Oxygen and Temperature In red mud, most metal and metal-like elements exist in the form of oxides, and during the process of molten salt electrolysis, a series of intermediate products are generated. The magnitude of oxygen partial pressure determines whether the reaction can proceed and the ease with which the reaction occurs, as shown in Eq. (5): G  = − RT ln PO2 = − 2.303 RT lg PO2

(5)

In the formula: G  —the standard Gibbs free energy, J·mol−1 ; T —temperature, K; ln PO2 /lg PO2 —oxygen partial pressure. According to Fig. 7, the stability of various substances that may exist in the cathode decreases in the following order from high to low: Ca3 Ti2 O7 , CaO, Ca3 Al2 O6 , Al2 O3 ,

Thermodynamic Analysis of Preparation of Fe-Si/Fe3 Si Intermetallic …

1537

Fig. 7 Relationship diagram for the oxygen partial pressure and temperature

TiO, Ca2 SiO4 , SiO2 , Ti2 O3 , Ti3 O5 , Ca2 Fe2 O5 , TiO2 , Na2 O, FeO, Fe3 O4 , Fe2 O3 . During the process of using molten salt electrolysis to deoxidize red mud and prepare Fe-Si/Fe3 Si, the higher the stability of the phase, the greater the difficulty of electrolytic reduction to the pure substance, and the greater the required external driving force.

Conclusions This study conducted a thermodynamic analysis of the theoretical decomposition voltage of the major oxides in red mud raw materials and the electrode reactions during the electrolysis process. The following conclusions were drawn: (1) Under the experimental temperature conditions of 800 °C, the theoretical decomposition voltage of all oxides in red mud is lower than the decomposition voltage of the CaCl2 -NaCl molten salt component. Therefore, the electrolysis in CaCl2 -NaCl molten salt can achieve the electrolytic reduction of metal oxides. (2) When the voltage range is controlled within −2.22 to −2.27 V, the cathode only undergoes the reduction process of Fe, Si, and Na components. The thermodynamic reduction process of the Fe component is Fe2 O3 /Ca2 Fe2 O5 → Fe3 O4 → FeO → Fe; the thermodynamic reduction process of the Si component is SiO2 / Ca2 SiO4 → Si; and after reduction, Na is separated from the cathode in a liquid or gaseous form, while the Fe and Si components are transformed into Fe-Si/ Fe3 Si metal intermetallic compounds through deoxidation and alloying. (3) Ca in red mud and Ca2+ in the molten salt may have adverse effects on the deoxidation of oxides during the reduction process, but they can be completely removed in the end.

1538

G. Chen et al.

(4) When a graphite anode is used, the generation of CO2 (or CO) from the anode reaction requires a lower potential than the generation of O2 . Therefore, it is easier to release CO2 (or CO) gas. Acknowledgements This work was supported by the National Natural Science Foundation of China under Grant No. 52174315 and Tangshan Science and Technology Innovation Team Training Program Project under Grant No. 21130207D.

References 1. Wang L, Sun N, Tang H et al (2019) A review on comprehensive utilization of red mud and prospect analysis. Minerals-Basel 9(6):362–381 2. Power G, Grafe M, Klauber C (2011) Bauxite residue issues: I. Current management, disposal and storage practices. Hydrometallurg 108(1):33–45 3. Li G, Liu M, Rao M et al (2014) Stepwise extraction of valuable components from red mud based on reductive roasting with sodium salts. J Haz Mat 280:774–780 4. Gao F, Zhang J, Deng X et al (2019) Comprehensive recovery of iron and aluminum from ordinary Bayer red mud by reductive sintering–magnetic separation–digesting process. JOM 71:2936–2943 5. Agrawal S, Rayapudi V, Dhawan N (2019) Comparison of microwave and conventional carbothermal reduction of red mud for recovery of iron values. Miner Eng 132:202–210 6. Li X, Wei X, Wei L et al (2009) Recovery of alumina and ferric oxide from Bayer red mud rich in iron by reduction sintering. T Nonferr Metal Soc 19(5):1342–1347 7. Li W, Zheng Y, Kang Y et al (2020) Magnetic behavior of soft magnetic composites constructed by rapidly quenched flake-like Fe-SiAl alloy. J Alloy Compd 819:153028–153034 8. Neamtu B, Belea A, Popa F et al (2020) Properties of soft magnetic composites based on Fe fibres coated with SiO2 by hydrothermal method. J Alloy Compd 826:154222–154231 9. Jiang X, Whalen S, Darsell J et al (2017) Friction consolidation of gas-atomized Fe-Si powders for soft magnetic applications. Mater Char 123:166–172 10. Wang Z, Liu X, Kan X et al (2019) Preparation and characterization of flaky Fe-SiAl composite magnetic powder core coated with MnZn ferrite. Curr Appl Phys 19(8):924–927 11. Chen G, Fray D, Farthing T (2020) Direct electrochemical reduction of titanium dioxide to titanium in molten calcium chloride. Nat 407(6802):4–361 12. Chang C, Tu J, Chen Y et al (2022) Electro-deoxidation behavior of solid SeO2 in a lowtemperature molten salt. Chem Commun 58(65):9108–9111 13. Li S, Zou X, Zheng K et al (2018) Electrosynthesis of Ti5 Si3 , Ti5 Si3 /TiC and Ti5 Si3 /Ti3 SiC2 from Ti-bearing blast furnace slag in molten CaCl2 . Metall Mater Trans B 49(2):790–802

Thermodynamic Analysis of the Recovery of Metallic Mn from Waste Lithium Manganese Battery Using the Molten Salt Method Ling Yue Song, Hui Li, and Jinglong Liang

Abstract Lithium-ion batteries (LIBs) have a wide range of applications due to their excellent properties, resulting in a sharp increase in the quantity of waste LIBs. The cathode materials of waste LIBs contain a large amount of metal ions such as cobalt, manganese, and nickel. If not properly treated in a timely manner, it can lead to resource waste and environmental pollution. The molten salt method provides a possibility for the recovery of valuable metal materials from the cathode of LIBs. In this paper, the feasibility of recovering metallic manganese through the molten salt method is analyzed through thermodynamic calculations. The results show that at temperatures above 600 °C, Mn(IV) can spontaneously reduce to Mn(III), and Mn(III) gradually undergoes reduction when a voltage is applied, following the reduction process of Mn(IV) → Mn(III) → Mn(II) → Mn. This paper provides theoretical support for the molten salt deoxidation recovery of metallic manganese from lithium manganese oxide. Keywords Thermodynamics analysis · Waste LIBs · Molten salt deoxidation process

Introduction Lithium-ion batteries (LIBs), with their outstanding characteristics such as high specific capacity, stable operating voltage, and low self-discharge rate, are considered one of the most promising energy and energy storage devices of the new century [1, 2]. Lithium manganese oxide (LiMn2 O4 ) has a spinel structure, allowing lithium ions to embed and de-intercalate smoothly, which is beneficial for current charge and discharge [3, 4]. Moreover, it has low cost and high safety, making it an ideal cathode material for batteries. However, during the cycling process, manganese L. Y. Song · H. Li · J. Liang (B) College of Metallurgy and Energy, North China University of Science and Technology, Tangshan 063210, China e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_133

1539

1540

L. Y. Song et al.

ions may undergo redox reactions with the electrolyte, leading to the loss of active material and resulting in a decline in lithium-ion capacity [5]. Additionally, the Jahn–Teller effect [6] can cause lattice distortion, reducing the specific capacity of LiMn2 O4 material, and thereby limiting the cycling performance and lifespan of lithium manganese oxide batteries. With the continuous development of electronic products and the widespread adoption of new energy vehicles, the demand for lithium batteries in the market continues to grow [7, 8], and the number of waste LIBs is also rapidly increasing. Improper disposal not only leads to resource wastage but also environmental pollution. Therefore, efficient recovery of valuable metals from waste LiMn2 O4 -based Li-ion batteries deserves further research. Currently, the recycling process of waste lithium-ion batteries mainly focuses on hydrometallurgy, using acid leaching, alkaline leaching, or ammonia leaching to leach out valuable metals, followed by separation through precipitation, and so on [9–13]. Using lithium manganese oxide from waste LIBs as raw material, a new LiMn2 O4 cathode material can be prepared through the sol–gel method, enabling direct recycling of manganese [14]. To maximize resource utilization, there is still a need for a green and environmentally friendly method to recover valuable metals from LiMn2 O4 [15]. Since the proposal of the molten salt electrolysis method, it has been applied in the smelting of metals and alloys such as titanium, aluminum, and nickel [16–20]. Mirza et al. [21] recovered cobalt from lithium battery cathode materials in a LiCl–KCl molten salt system, and Zhang et al. [22] achieved the extraction of Li and Co elements from LiCoO2 through molten salt electrolysis. Therefore, molten salt electrolysis can be used to recover valuable metals from waste LIBs. In this study, the feasibility of using molten salt electrolysis to recover manganese elements from waste LiMn2 O4 -based Li-ion batteries is analyzed through thermodynamic calculations. A molten salt system is selected, and the theoretical reduction sequence of manganese oxides is determined to provide theoretical support for the recovery of manganese metal through molten salt electrolysis.

Reaction Thermodynamics Thermodynamics of Manganese Reduction During the reduction process of high-valence manganese oxides to lower-valence oxides and elemental manganese, there may be six potential reactions (1) to (6). The sequence of these reactions occurring can be determined through thermodynamic analysis. 4MnO2 = 2Mn2 O3 + O2 (g)

(1)

2MnO2 = 2MnO + O2 (g)

(2)

Thermodynamic Analysis of the Recovery of Metallic Mn from Waste …

1541

MnO2 = Mn + O2 (g)

(3)

2Mn2 O3 = 4MnO + O2 (g)

(4)

2/3Mn2 O3 = 4/3Mn + O2 (g)

(5)

2MnO = 2Mn + O2 (g)

(6)

The standard Gibbs free energies for each reaction have been calculated using HSC6.0 software, where the standard Gibbs free energy is calculated with the reference of producing 1 mol of O2 . Please refer to Fig. 1 for details. When the temperature exceeds 600 °C, spontaneous reduction reactions occur from MnO2 to Mn2 O3 . Furthermore, with increasing reaction temperature, the standard Gibbs free energy decreases. Therefore, in molten salts with temperatures above 600 °C, the Mn(IV) in LiMn2 O4 may spontaneously undergo a reduction reaction, converting to Mn(III), which can eliminate the electrical energy consumption during the reduction process. Additionally, in the reactions mentioned above, the one with the highest required Gibbs free energy is the reduction of Mn(II) to elemental manganese, suggesting that this step might be the final one in the reduction process. To determine the sequence of Mn reduction under electrical conditions, equilibrium electrode potentials for reactions (1) to (6) are calculated using Eq. (7). The calculation results are shown in Fig. 2.

Fig. 1 Standard Gibbs free energy ΔGΘ curve with temperature (T = 400 ~ 900 °C)

1542

L. Y. Song et al.

Fig. 2 Equilibrium electrode potential for low-cost manganese oxide reduction(T = 400 ~ 900 °C)

ΔG Θ = −nFEΘ

(7)

where ΔG Θ was the standard Gibbs free energy (kJ·mol−1 ), E Θ was the theoretical decomposition voltage in the standard state (V), F was the Faraday constant (96,485C·mol−1 ), n was the number of electrons gained or lost in the reaction equation. When an external electric field is applied, the initial reduction process involves the conversion of Mn(IV) to Mn(III). Subsequently, the reduction continues in the following order: Mn2 O3 → MnO → Mn. From the theoretical analysis results, it is expected that the reduction process of LiMn2 O4 containing Mn(IV) to elemental manganese proceeds through three steps: Mn(IV) → Mn(III) → Mn(II) → Mn.

Molten Salt System Common molten salt systems include NaCl, KCl, LiCl, CaCl2 , et al., which have low melting points, wide electrochemical windows, and good conductivity. The reduction reactions of alkaline earth metal chlorides are as follows: 2NaCl = 2Na + Cl2 (g)

(8)

2KCl = 2K + Cl2 (g)

(9)

Thermodynamic Analysis of the Recovery of Metallic Mn from Waste …

1543

CaCl2 = Ca + Cl2 (g)

(10)

2LiCl = 2Li + Cl2 (g)

(11)

To select the molten salt system, the highest theoretical decomposition voltage required for the manganese reduction process is compared with the theoretical decomposition voltages of various molten salt components, as shown in Fig. 3. At the same temperature, the maximum standard electrode potential required for the conversion of MnO to elemental manganese is adjusted to be lower than that of alkaline earth metal chlorides. Therefore, all four types of molten salts can be used in the molten salt system. From the perspective of reduction potential, molten salt systems with more negative standard electrode potentials have wider electrochemical windows. However, in the context of resource recovery processes, one must also consider factors such as process complexity, economic viability, and energy consumption. LiCl is more expensive, and KCl is highly hygroscopic. Therefore, for the recovery of manganese from lithium manganese oxide, the NaCl-CaCl2 molten salt system is selected as the molten salt system. From Fig. 4, it can be observed that in the NaCl-CaCl2 binary molten salt system, the eutectic point occurs at a molar ratio of NaCl to CaCl2 of 0.48:0.52, with the lowest melting point at 503.25 °C. During the heating process, when the salt temperature reaches the eutectic temperature, the salt begins to melt. To ensure that the molten salt exhibits good fluidity, conductivity, and low viscosity, an experimental temperature of above 600 °C is chosen.

Fig. 3 Standard electrode potential of MnO2 and alkaline earth metal chloride

1544

L. Y. Song et al.

Fig. 4 Binary phase diagram of the NaCl-CaCl2 melts

Thermodynamic Analysis of the Electrochemical Reduction of Lithium Manganate in Molten Salt The manganese-oxygen binary phase diagram in Fig. 5 reveals that within the temperature range of 600–750 °C when the oxygen content is relatively high, the primary phases are MnO2 and gaseous substances. As the oxygen content decreases, some of the MnO2 gradually reduces to Mn2 O3 . However, at temperatures above 750 °C, when the oxygen content reaches a molar ratio of 0.6 or higher, the predominant phases are Mn2 O3 and gaseous substances, and MnO2 no longer exists. MnO2 spontaneously reduces to Mn2 O3 , consistent with the results obtained in Fig. 1. With the reduction in oxygen content, different phases are formed. Mn2 O3 gradually transforms into Mn3 O4 , which contains both divalent and trivalent manganese. When the oxygen content ratio falls below 0.5 and approaches zero, the proportion of elemental manganese increases gradually, while the proportion of manganese oxides continuously decreases until MnO completely disappears, leaving only elemental manganese. In LiMn2 O4 , the molar ratio of oxygen content to total manganese oxide content is 2:3, approximately 0.67. If the electrolysis temperature is chosen to be above 750 °C, both trivalent and tetravalent manganese species are present initially. When LiMn2 O4 begins the electrochemical deoxygenation process, the first step is the

Thermodynamic Analysis of the Recovery of Metallic Mn from Waste …

1545

Fig. 5 Manganese-oxygen binary system phase diagram

conversion of Mn(IV) to Mn(III) as it gains electrons. If LiMn2 O4 is placed in the molten salt without applying a voltage promptly for deoxygenation, spontaneous reduction of Mn(IV) may occur, leading to the formation of Mn2 O3 . As the electrochemical deoxygenation process continues, Mn(III) gradually gets reduced to Mn(II). Simultaneously, from the phase diagram, it can be seen that the presence of Mn3 O4 is limited. When a relatively high voltage is applied, the reduction process accelerates due to a stronger electrochemical driving force, making it challenging to detect Mn3 O4 , which has a limited appearance range in the phase diagram. As the oxygen content decreases to below 0.5, the majority of the products become MnO. The proportion of elemental manganese gradually increases, eventually reducing entirely to elemental manganese.

Conclusion Through thermodynamic calculations, the standard Gibbs free energy, oxygen partial pressure, equilibrium electrode potential, and other reaction conditions during the manganese reduction process are determined. The impact of changes in oxygen content on manganese oxide compounds is analyzed, and a preliminary assessment

1546

L. Y. Song et al.

is made of the possible reactions of LiMn2 O4 in the molten salt system, leading to the following conclusions: (1) A molten salt system consisting of NaCl-CaCl2 with a molar ratio of 1:1 has been selected as the research subject. (2) At temperatures above 600 °C Mn(IV) can spontaneously reduce to Mn(III), and when an electrical voltage is applied, the reduction process of Mn(III) proceeds as follows: Mn(III) → Mn(II) → Mn. Therefore, it is preliminarily determined that the extraction of manganese from LiMn2 O4 through molten salt electrolysis is feasible. Acknowledgements This work was supported by the National Natural Science Foundation of China (No. 51774143, No.52174315) and the Tangshan Science and Technology Innovation Team Training Program Project (No. 21130207D).

References 1. Zhu J, Cao G, Li Y et al (2020) Efficient utilisation of rod-like nickel oxalate in lithium-ion batteries: a case of NiO for the anode and LiNiO2 for the cathode. Scripta Mater 178:51–56 2. Li H, Song L, Huo D et al (2023) Cattail-grass-derived porous carbon as high-capacity anode material for Li-ion batteries. Molecules 28(11):4427 3. Guan P, Zhou L, Yu Z et al (2020) Recent progress of surface coating on cathode materials for high-performance lithium-ion batteries. J Energy Chem 43:220–235 4. Liang S, Yan W, Wu X et al (2018) Gel polymer electrolytes for lithium ion batteries: Fabrication, characterization and performance. Solid State Ionics 318:2–18 5. Peters JF, Weil M (2018) Providing a common base for life cycle assessments of Li-Ion batteries. J Clean Prod 171:704–713 6. Fang T, Guo S, Jiang K et al (2019) Revealing the critical role of titanium in layered manganese-based oxides toward advanced sodium-ion batteries via a combined experimental and theoretical study. Small Methods 3(4):1800183 7. Xu Y, Dong Y, Han X et al (2015) Application for simply recovered LiCoO2 material as a high-performance candidate for supercapacitor in aqueous system. ACS Sustain Chem Eng 3(10):2435–2442 8. Tang X, Tang W, Duan J et al (2021) Recovery of valuable metals and modification of cathode materials from spent lithium-ion batteries. J Alloy Compd 874:159853 9. Yu J, Ma B, Qiu Z et al (2023) Separation and recovery of valuable metals from ammonia leaching solution of spent lithium-ion batteries. ACS Sustain Chem Eng 10. Zhu J, Guo G, Wu J et al (2022) Recycling and reutilization of LiNi0.6 Co0.2 Mn0.2 O2 cathode materials from spent lithium-ion battery. Ionics 1–10 11. Chen X, Cao L, Kang D et al (2018) Recovery of valuable metals from mixed types of spent lithium ion batteries. Part II: selective extraction of lithium. Waste Manage 80:198–210 12. Wang WY, Yen CH, Lin JL et al (2019) Recovery of high-purity metallic cobalt from lithium nickel manganese cobalt oxide (NMC)-type Li-ion battery. J Mater Cycles Waste 21:300–307 13. Sattar R, Ilyas S, Bhatti HN et al (2019) Resource recovery of critically-rare metals by hydrometallurgical recycling of spent lithium ion batteries. Sep Purif Technol 209:725–733 14. Chiu KL, Shen YH, Chen YH et al (2019) Recovery of valuable metals from spent lithium ion batteries (LIBs) using physical pretreatment and a hydrometallurgy process. Adv Mater 8(1):12–20

Thermodynamic Analysis of the Recovery of Metallic Mn from Waste …

1547

15. Liang J, Wang D, Wang L et al (2022) Electrochemical process for recovery of metallic Mn from waste LiMn2 O4 -based Li-ion batteries in NaCl−CaCl2 melts. Int J Min Met Mater 29(3):473– 478 16. Xu Y, Zhao G, Cai Y (2021) Preparation of titanium by electro-deoxidation of CaTiO3 in a molten CaCl2 -NaCl salt. Int J Electrochem Sci 16(211022):2 17. Bin W, Liu KR, Chen JS (2011) Reaction mechanism of preparation of titanium by electrodeoxidation in molten salt. T Nonferr Metal Soc 21(10):2327–2331 18. Xu Y, Jiao H, Wang M et al (2019) Direct preparation of V-Al alloy by molten salt electrolysis of soluble NaVO3 on a liquid Al cathode. J Alloy Compd 779:22–29 19. Li M, Liu C, Ding A et al (2023) A review on the extraction and recovery of critical metals using molten salt electrolysis. J Environ Chem Eng 109746 20. Huan S, Wang Y, Peng J et al (2020) Recovery of aluminum from waste aluminum alloy by low-temperature molten salt electrolysis. Miner Eng 154:106386 21. Mirza M, Abdulaziz R, Maskell WC et al (2021) Recovery of cobalt from lithium-ion batteries using fluidised cathode molten salt electrolysis. Electrochim Acta 391:138846 22. Zhang B, Xie H, Lu B et al (2019) A green electrochemical process to recover Co and Li from spent LiCoO2 -based batteries in molten salts. ACS Sustain Chem Eng 7(15):13391–13399

Part XLII

Materials Processing and Kinetic Phenomena: From Thin Films and Micro/ Nano Systems to Advanced Manufacturing

Fabrication of Periodic Textures at Micron Level on Silicone Membrane Using Femtosecond Laser S. Chatterjee, A. S. Cholkar, D. Kinahan, and D. Brabazon

Abstract Membranes in microfluidics have several uses, including separation/ filtration such as particle separation, solute separation, and reverse osmosis. Membranes are increasingly being employed in biomedical applications such as blood partitioning and can be used to extract circulating tumor cells. In the current work, a femtosecond 400 fs laser was used to fabricate periodic structures on silicone membranes, including pCO2 and pO2 . The goal is to generate periodic forms without cutting through the membranes’ thin coated surface. The maintenance of the hydrophobicity of the laser-fabricated samples is another area of interest in the study. To accomplish the study’s goal, several input laser process parameters were varied. From the study, it was observed that the fabrication of different periodic structures on pCO2 and pO2 is feasible with the depth of penetration being controlled well via control of the scanning speed. This study provides a route for manufacturers to implement femtosecond laser surface profiling required for surface modification of medical and sensor membrane and products. Keywords Membrane · Femtosecond laser · Laser-Induced Periodic Surface Texture (LIPSS) · Wettability S. Chatterjee (B) · A. S. Cholkar · D. Kinahan · D. Brabazon I-Form Advanced Manufacturing Centre, Dublin City University, Dublin 9, Ireland e-mail: [email protected] Advanced Processing Technology Research Centre, School of Mechanical and Manufacturing Engineering, Dublin City University, Glasnevin, Dublin 9, Ireland National Centre for Plasma Science & Technology, Dublin City University, Glasnevin, Dublin 9, Ireland A. S. Cholkar e-mail: [email protected] D. Kinahan e-mail: [email protected] D. Brabazon e-mail: [email protected] © The Minerals, Metals & Materials Society 2024 The Minerals, Metals & Materials Society (ed.), TMS 2024 153rd Annual Meeting & Exhibition Supplemental Proceedings, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-031-50349-8_134

1551

1552

S. Chatterjee et al.

Introduction Silicone rubber insulators have recently gained popularity in power system networks due to their greater performance over traditional ceramic and glass-based insulators. Despite its popularity, silicone is not as frequently utilized as certain other materials, which results in poor economies of scale. Siloxanes, commonly known as silicones, are polymers which have large molecules composed of many repeated sub-units. A chain of alternating silicone and oxygen atoms that is commonly coupled with carbon and/or hydrogen is the building block of these polymers. As an elastomer, silicone rubber is non-reactive, stable, and resistant to harsh conditions and temperatures. These qualities make silicone a popular material for use in electronics, HVAC systems, autos, airplanes, and rail transportation. Silicone also has advanced and distinguished properties such as superior hydrophobicity and hydrophobic recovery, lightweight, flexibility, vandal resistance, and other benefits distinguish silicone insulators [1, 2]. The hydrophobic silicone rubber (contact angle: 110°) has excellent dielectric properties as well as a high aging resistance. In order to address such issues, a superhydrophobic silicone surface with self-cleaning capabilities is required. This can be accomplished by using low surface energy coatings [2] or by creating a textured silicone surface using laser [3–5]. Laser surface texturing (LST), electrochemical, chemical etching, masked meshing of microtextured coatings, etching-plasma nitriding, and photochemical machining (PCM) are all different approaches for material surface modification [6]. Laser surface texturing (LST) is a promising and rapidly evolving surface modification technology. It encompasses a wide range of processes based on various types of laser material processing, such as heating, melting, sublimation, subtractive, and additive technologies. LST procedures provide for a wide range of variation in the basic features of the treated surface, such as macrostructure, roughness, porosity, and wetting qualities [7–9]. Furthermore, the employment of a focused laser enables surface alteration with set structural parameters without the use of any masks. In the present study, laser surface texturing on pCO2 and pO2 membranes has been performed using ultrafast laser processing. The fabrication of different periodic patterns (parallel and crosshatch) on the membranes was carried out using different laser process parameters without thorough cut of the substrate. The study was carried out at different parametric settings so that maximum process-related information can be gathered from less experimental trails.

Fabrication of Periodic Textures at Micron Level on Silicone Membrane …

(a)

1553

(b)

Fig. 1 Pictures of the two different silicone materials before laser processing a pCO2 and b pO2

Material and Methods Materials The two distinct types of silicone rubber that are coated on PET-foil having thickness of 200 µm were used in the current study to create periodic structures using an ultrafast laser. The two different silicone materials (Fig. 1) used for the experimentation are shown below: 1. Cover layer of optical pCO2 -sensor knife coated on PET-sheet (filler: pigment black) (Fig. 1a). 2. Cover layer of optical pO2 -sensor knife coated on PET-sheet (filler: carbon black) (Fig. 1b).

Experimentation The ultrafast laser is having an average wavelength of 1030 nm, a pulse duration