Light Metals 2020 (The Minerals, Metals & Materials Series) 3030364070, 9783030364076

Citation preview

Edited by ALAN TOMSETT

The Minerals, Metals & Materials Series

Alan Tomsett Editor

Light Metals 2020

123

Editor Alan Tomsett Rio Tinto Brisbane, QLD, Australia

ISSN 2367-1181 ISSN 2367-1696 (electronic) The Minerals, Metals & Materials Series ISBN 978-3-030-36407-6 ISBN 978-3-030-36408-3 (eBook) https://doi.org/10.1007/978-3-030-36408-3 © The Minerals, Metals & Materials Society 2020, corrected publication 2020 This work is subject to copyright. All rights are reserved 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

Preface

It is my honour to present to you Light Metals 2020 and welcome you to the 149th TMS Annual Meeting and Exhibition in San Diego. Light Metals 2020 is a collaborative effort from hundreds of authors plus session chairs, subject chairs, and TMS staff. It is their dedication that makes this meeting a success. The global aluminum industry has gone through a period of rapid growth and change in recent years. While growth is slowing, challenges such as low metal prices, decarbonisation of energy sources and processes, and deteriorating raw material quality remain. Light Metals 2020 contains many innovative responses to these challenges for the industry. Our markets are also changing with increasing demand for aluminum that has been produced responsibly and sustainably. These market changes are also reflected in this year’s volume where we have sessions dedicated to Bauxite Residue Reuse and Remediation, Spent Pot Lining, Recycling, Cast Shop Safety and Potroom Environment. This year marks the 50th year of continuous publication of the Light Metals proceedings. Throughout that time, Light Metals has provided a repository for the combined knowledge of researchers and industry practitioners and today remains the pre-eminent reference work for our industry. It is timely that this year’s Light Metals keynote session will focus on attracting and growing the next generation of technical talent. Continuing to bring in new talent will be critical in developing the solutions required to meet the global industry challenges and to provide the next generation of contributors and volunteers for the Light Metals proceedings. These proceedings are the culmination of the efforts of many people, in particular, the Subject Chairs: James Vaughan, Dmitry Eskin, Jayson Tessier, Johannes Morscheiser, and Duygu Kocaefe. It has been a pleasure working with this team and I thank them for their support and enthusiasm. They, along with the session chairs and reviewers, have volunteered many hours to ensure we have a full and high-quality program. In addition, I would like to thank Patricia Warren and the other the TMS staff working behind the scenes for their support, understanding, and flexibility in managing our requests. The help and advice from past editors Corleen Chesonis and Olivier Martin are also greatly appreciated. Finally, the Light Metals proceedings would not exist without the willingness of the authors to share their research and experience with the broader community. We all owe them our deepest gratitude for continuing the 50-year tradition of Light Metals. Alan Tomsett

v

Contents

Part I

Alumina and Bauxite

Impacts of Mineralogy on Soluble Phosphorus Concentrations During Low Temperature Processing of Jamaican Bauxites . . . . . . . . . . . . . . . . . . . . . . . . . . Michael D. Coley, Anthony M. Greenaway, and Khadeen E. Henry-Herah

3

Effects of the Granular Properties of Bauxite Pisolithes on the Solid/Liquid Separation in Liquid Fluidized Beds of Classifiers . . . . . . . . . . . . . . . . . . . . . . . . T. Grillot, G. Simard, R. Chesnaux, D. Boudeville, and L. Perrachon

12

Mineralogical Assessment of the Solid Phase Obtained on Leaching of Brazilian Red Mud . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. B. Botelho Junior, D. C. R. Espinosa, and J. A. S. Tenório

21

Low-Quality Aluminum-Containing Raw Materials: Experience, Problems and Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vadim Lipin and Ekaterina Sofronova

26

Inhibition of Kaolinite Dissolution in Bayer Liquor Through Lithium Addition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Horace Ogilvie, James Vaughan, and Hong Peng

33

Ionic Effect of NaCl and KCl on the Flotation of Diaspore and Kaolinite Using Sodium Oleate as Collector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chaojun Fang, Shichao Yu, Hong Peng, Xiaowei Deng, and Jun Wang

40

Quantifying the Effect of Seeds on Gibbsite Crystallization—Mathematical Modelling of Particle Size Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Thiago T. Franco and Marcelo M. Seckler

47

Experimental Study on Flow Field Characteristics in Seed Precipitation Tank and Influence on Physical Properties of Al(OH)3 Products . . . . . . . . . . . . . Xiangyu Zou, Yan Liu, Xiaolong Li, and Ting’an Zhang

54

Application of Advanced Oxidative Process for Organic Compounds Removal from Bayer Liquor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Miguel Antonio Soplin, Amilton Barbosa Botelho Junior, Marcela dos Passos Galluzzi Baltazar, Jorge Alberto Soares Tenório, and Denise Crocce Romano Espinosa A Review of Comprehensive Utilization of High-Iron Red Mud of China . . . . . . Ting’an Zhang, Kun Wang, Yan Liu, Guozhi Lyu, Xiaofei Li, and Xin Chen Conversion Behavior of Iron-Containing Minerals in the Process of Dissolving High-Iron Bauxite by Starch Hydrothermal Method . . . . . . . . . . . . . . . . . . . . . . Yongfei He, Yiyong Wang, Hun Jin, Ning Zhe, and Xingyuan Wan

60

65

72

vii

viii

Contents

Disc Magnetic Separator Applied to the Extraction of Magnetite in Bauxite Residue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Y. Robert, G. Simard, and S. Fortin Recovery of Iron from High-Iron Bayer Red Mud by Smelting Reduction . . . . . Kun Wang, Yan Liu, Guozhi Lyu, Xiaofei Li, Xin Chen, and Ting’an Zhang Bayer Process Towards the Circular Economy—Metal Recovery from Bauxite Residue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Paula de Freitas Marques Araújo, Patricia Magalhães Pereira Silva, Andre Luiz Vilaça do Carmo, Fernando Gama Gomes, Alex Mota dos Santos, Raphael Vieira da Costa, Caio César Amorim de Melo, Adriano Reis Lucheta, and Marcelo Montini Bayer Process Towards the Circular Economy—Soil Conditioners from Bauxite Residue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Roseanne Barata Holanda, Patricia Magalhães Pereira Silva, Andre Luiz Vilaça do Carmo, Alice Ferreira Cardoso, Raphael Vieira da Costa, Caio César Amorim de Melo, Adriano Reis Lucheta, and Marcelo Montini Brazilian Bauxite Residue Physical–Chemical Characterization and Acidic Neutralization Potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Patricia Magalhães Pereira Silva, Andre Luiz Vilaça do Carmo, Roseanne Barata Holanda, Fernando Gama Gomes, Emanuele Nogueira, Raphael Vieira da Costa, Caio César Amorim de Melo, Adriano Reis Lucheta, and Marcelo Montini Effect of Concentrations and Pressures of CO2 on Calcification–Carbonation Treatment of Bauxite Residue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xi Chao, Ting-an Zhang, Guo-zhi Lv, and Yang Chen Comprehensive Utilization of Red Mud Through the Recovery of Valuable Metals and Reuse of the Residue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fei Lyu, Li Wang, Jiande Gao, Honghu Tang, Wei Sun, Yuehua Hu, Runqing Liu, and Lei Sun

85 92

98

107

115

124

129

A Review of Research on Alumina Extraction from High-Alumina Fly Ash and a New Method for Preparing Alumina by Electrotransformation . . . . . . . . . Xiu-xiu Han, Ting-an Zhang, Guo-zhi Lv, Xi-juan Pan, and Da-xue Fu

136

Effect of Sodium Alkali Concentration on Calcification–Carbonization Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yang Chen, Ting-an Zhang, Guo-zhi Lv, and Xi Chao

143

Part II

Aluminum Alloys, Processing and Characterization

Stress Characterization of Bore-Chilled Sand Cast Aluminum Engine Blocks in As-Cast and T7 Condition with Application of Neutron Diffraction . . . . . . . . J. Stroh, D. Sediako, G. Byczynski, A. Lombardi, and A. Paradowska Molecular Dynamics Simulations of the Solidification of Pure Aluminium . . . . . Michail Papanikolaou, Konstantinos Salonitis, and Mark Jolly Nanoindentation and Cavitation-Induced Fragmentation Study of Primary Al3Zr Intermetallics Formed in Al Alloys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Abhinav Priyadarshi, Tungky Subroto, Marcello Conte, Koulis Pericelous, Dmitry Eskin, Paul Prentice, and Iakovos Tzanakis

153 158

168

Contents

ix

In Situ Neutron Diffraction Solidification Analyses of Rare Earth Reinforced Hypoeutectic and Hypereutectic Aluminum–Silicon Alloys . . . . . . . . . . . . . . . . . J. Stroh, D. Sediako, D. Weiss, and V. K. Peterson

174

Influence of TiB2 Particles on Modification of Mg2Si Eutectic Phase in Al–Zn–Si–Mg–Cu Cast Alloys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Byung Joo Kim, Sung Su Jung, Yong Ho Park, and Young Cheol Lee

179

A Statistical Analysis to Study the Effect of Silicon Content, Surface Roughness, Droplet Size and Elapsed Time on Wettability of Hypoeutectic Cast Aluminum–Silicon Alloys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Amir Kordijazi, Swaroop Kumar Behera, Omid Akbarzadeh, Marco Povolo, and Pradeep Rohatgi

185

Aluminum Trace Elements Analyses Using Epsilon 1 Meso EDXRF Technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hussain Al Halwachi

194

Effect of Cooling Rate During Solidification of Aluminum–Chromium Alloy . . . . G. Muthusamy, S. Wagstaff, and A. Allanore Effects of Si on the Electrical Conductivity, Microhardness, Microstructure and Hot Tearing of Al–0.8Fe–0.5Mg–0.4Ni Alloys . . . . . . . . . . . . . . . . . . . . . . . . Stephanie Kotiadis, Adam Zimmer, Abdallah Elsayed, Eli Vandersluis, and C. Ravindran The Efficacy of Replacing Metallic Cerium in Aluminum–Cerium Alloys with LREE Mischmetal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zachary C. Sims, David Weiss, Orlando Rios, Hunter B. Henderson, Michael S. Kesler, Scott K. McCall, Michael J. Thompson, Aurelien Perron, and Emily E. Moore Effects of Sc and Y on the As-Cast Microstructure of AA6086 . . . . . . . . . . . . . . Sandi Žist, Varužan Kevorkijan, Matej Steinacher, and Franc Zupanič Ternary Interactions and Implications for Third Element Alloying Potency in Al–Ce-Based Alloys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hunter B. Henderson, David Weiss, Zachary C. Sims, Michael J. Thompson, Emily E. Moore, Aurélien Perron, Fanqiang Meng, Ryan T. Ott, and Orlando Rios Development and Analysis of Al7075 Alloy Materials Using Press and Sinter Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Steven C. Johnson, Corey D. Clark, and Jason S. Alvarez Formation of Rare Earth Intermetallics in Al–Cu Cast Alloys . . . . . . . . . . . . . . M. G. Mahmoud, A. M. Samuel, H. W. Doty, and F. H. Samuel

204

210

216

222

227

233 241

Retrogression Forming and Reaging of AA7075-T6 Alclad to Produce Stampings with Peak Strength . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Katherine E. Rader, Jon T. Carter, Louis G. Hector Jr., and Eric M. Taleff

247

High Cycle Fatigue Properties of the Zr-Modified Al–Si–Cu–Mg Alloy at Elevated Temperatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Guangyu Liu, Paul Blake, and Shouxun Ji

253

Effect of Mo on Elevated-Temperature Low-Cycle Fatigue Behavior of Al-Si 356 Cast Alloy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Chen, K. Liu, and X.-G. Chen

261

x

State Parameter-Based Simulation of Temperature- and Strain Rate Dependent Flow Curves of Al-Alloys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bernhard Viernstein, Philipp Schumacher, Benjamin Milkereit, and Ernst Kozeschnik Coarsening-Resistance of a Severely Deformed Al-0.2 Wt% Sc Alloy . . . . . . . . . Yan Huang

Contents

267 272

The Effect of Modified Strain-Induced Melt Activation (Modified SIMA) Process on the Microstructure and Mechanical Properties of Al-7Si Alloy . . . . . Chandan Choudhary, K. L. Sahoo, and D. Mandal

277

Effect of Mg on Flow Behavior of Al–Mg Alloys and Its Constitutive Modeling Using Finite Element Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shahin Ahmad, Vilas Tathavadkar, Alankar Alankar, and K. Narasimhan

283

Influence of Thermal Treatment and Design Parameters on the Fatigue Life of Automotive Control Arm Fabricated from A357 Semi-solid Alloy . . . . . . . . . . Mohamed Attia, Khaled Ragab, Mohamed Bouazara, and X. Grant Chen

289

The Formation of Al6(Fe, Mn) Phase in Die-Cast Al–Mg Alloys . . . . . . . . . . . . . Xiangzhen Zhu and Shouxun Ji Spark Plasma Sintering of Graphene Nanoplatelets Reinforced Aluminium 6061 Alloy Composites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mahmood Khan, Rafi Ud-Din, Abdul Wadood, Wilayat Husain Syed, Shahid Akhtar, and Ragnhild Elizabeth Aune Effects of Mn and Mo Micro-additions on Al–Zr–Sc–Er–Si Mechanical Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shipeng Shu, Anthony De Luca, David N. Seidman, and David C. Dunand Nanotreating High-Zinc Al–Zn–Mg–Cu Alloy by TiC Nanoparticles . . . . . . . . . . Jie Yuan, Min Zuo, Maximilian Sokoluk, Gongcheng Yao, Shuaihang Pan, and Xiaochun Li Microstructure and Mechanical Response of an Artificially Aged Al–Mg–Si Alloy: Experiments and Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yoojin Kim and Sharvan Kumar Effect of Zn Additions on the Mechanical Properties of High Strength Al–Si–Mg–Cu Alloys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sung Su Jung, Soo Been Hwang, Byung Joo Kim, Yong Ho Park, and Young Cheol Lee Utilization of 3D Printed Materials in Expendable Pattern Casting Process . . . . Dika Handayani, Nicole Wagner, Victor Okhuysen, Michael Seitz, and Kyle Garibaldi Hemming Evolution of 6xxx Aluminum Alloys in the Course of Natural Aging Following the Continuous Annealing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. Lalpoor, E. Lambrechts, A. Miroux, C. Bollmann, and C. Yu The Effect of Deformation Mode and Microstructure on the IGC Susceptibility of Al–Mg–Si–Cu Alloys for Automotive Applications . . . . . . . . . . . . . . . . . . . . . R. Müller-Jena, J. Becker, T. Beyer, T. Hentschel, M. Rosefort, A. Stieben, and D. Zander Evolution of Grain Refinement in AA5083 Sheet Metal Processed by ECAP . . . . Christian Illgen, Philipp Frint, Maximilian Gruber, Wolfram Volk, and Martin F.-X. Wagner

297

301

312 318

324

331

338

345

352

362

Contents

xi

Mechanical and Microstructural Behavior of Dissimilar AA2014-T6 and AA7075-T6 Aluminium Alloys Joined by Friction Stir Welding . . . . . . . . . . Mohammad Adil and Jyoti Mukhopadhyay High Strength Nanotreated Filler Material for TIG Welding of AA6061 . . . . . . . Maximilian Sokoluk, Gongcheng Yao, Shuaihang Pan, Chezheng Cao, and Xiaochun Li

370 380

Optimization of Thermo-Mechanical Processes of Continuous Casting Products Using High Magnesium Aluminum Alloys in Automotive Industry Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Görkem Demir, Ali Ulaş Malcıoğlu, Sümbüle Sağdiç, Ali Ulus, Salim Aslanlar, and Erdinç İlhan

386

Plastic Flow of AA6013-T6 at Elevated Temperatures and Subsequent Reaging to Regain Full Strength . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Katherine E. Rader, Jon T. Carter, Louis G. Hector Jr., and Eric M. Taleff

400

Influence of Chemical Composition and Pre-deformation on the Age-Hardening Response of Al-Mg-Si Alloys . . . . . . . . . . . . . . . . . . . . . . A. Wimmer

406

Hot Deformation and Die-Quenching of 6000-Series Alloys—The Effect of Quench-Interruption Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tanja Pettersen, Benedikte Jørgensen Myrold, Calin Daniel Marioara, and Ola Jensrud Descriptors and Predictors: New Tools for the Predictive Modelling of Production Paths and the Properties of Aluminum-Based End-Products . . . . . Varužan Kevorkijan Effect of Extrusion Parameters on Microstructural and Mechanical Properties of EN AW 6063 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mehmet Buğra Güner, Cem Mehmetalioğlu, Osman Halil Çelik, Murat Konar, and Görkem Özçelik Simulation Study on Equal Channel Right Angular Extrusion Process of Aluminum Alloy 6061 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wenhuan Jiang, Liangying Wen, Huan Yang, Mengjun Hu, Meilong Hu, Jiahuan Jiang, and Paul K.-L. Song Characterization of Dynamic Material Property of AlSi10 Mg Aluminum Alloy Under High Strain Rate Compressive Loading . . . . . . . . . . . . . . . . . . . . . . . . . . Md Salah Uddin, Kristofer Kuelper, and Brahmananda Pramanik Current Efficiency for Direct Production of an Aluminium–Titanium Alloy by Electrolysis in a Laboratory Cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Omar Awayssa, Rauan Meirbekova, Gudrun Saevarsdottir, Gudjon Atli Audunsson, and Geir Martin Haarberg

412

419

425

433

440

445

Corrosion Inhibition Effect of Aloe Saponaria Gel on the Corrosion Resistance of Aluminum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Malena Soledad Friedrich, Alicia Esther Ares, and Claudia Marcela Méndez

452

Experimental Investigation of MgAl2O4 Spinel Formation in Oxidation of Al–Mg Alloys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Young-Ok Yoon, Seong-Ho Ha, Bong-Hwan Kim, Hyun-Kyu Lim, and Shae K. Kim

460

xii

Contents

Impact of Dispersion Hardening by Alumina Nano Particles on Mechanical Properties of Al 1100 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ilya Zhukov, Alexander Kozulin, Anton Khrustalev, Evgeny Moskvichev, Alexander Vorozhtsov, and Dmitry Lychagin Investigation of Temperature Variation During Friction Drilling of 6082 and 7075 Al-Alloys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nadia Hamzawy, Mahmoud Khedr, Tamer S. Mahmoud, Iman EI-Mahallawi, and Tarek A. Khalifa Study on the Anti-EMF of Al-Er Master Alloy Prepared by Er2O3 as Erbium Source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hongguang Kang, Jidong Li, Chaogang Zhang, Qian Wang, Yiyong Wang, Zhe Ning, Jilin Lu, and Jing Li Part III

465

471

478

Aluminum Reduction Technology

Comparison Between Different Laminated Aluminum Busbars Expansion Joints in Terms of Mechanical Performance and Relative Costs . . . . . . . . . . . . . André Felipe Schneider, Daniel Richard, David Leroux, Olivier Charette, and Francis Quintal

485

Demo Retrofit Study of a Chinese Inspired Cell Technology . . . . . . . . . . . . . . . . Marc Dupuis and Valdis Bojarevics

495

Mass Transport by Waves on the Bath Metal Interface in Electrolysis Cell . . . . L. Rakotondramanana, L. I. Kiss, S. Poncsák, S. Guérard, and J.-F. Bilodeau

510

Numerical Investigation of Flow Field Effect on Ledge Shape in Aluminum Reduction Cell by Coupled Thermo-Flow Model . . . . . . . . . . . . . . . . . . . . . . . . . Hongliang Zhang, Qiyu Wang, Shuai Yang, Jie Li, Jinding Liang, and Ling Ran Study of Heat Distribution Due to ACD Variations for Anode Setting . . . . . . . . Choon-Jie Wong, Yuchen Yao, Jie Bao, Maria Skyllas-Kazacos, Barry J. Welch, and Ali Jassim

517 527

Anodic Incident Detection through Multivariate Analysis of Individual Anode Current Signals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . David LaJambe, Éric Poulin, Carl Duchesne, and Jayson Tessier

535

Fault Detection and Diagnosis of Alumina Feeding System Using Individual Anode Current Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yuchen Yao, Jie Bao, Maria Skyllas-Kazacos, Barry J. Welch, and Ali Jassim

543

Change of Anode Operation Pattern from Single to Double Staircase at Albras . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Camila R. Silva, Vanderlei O. Fernandes, Nilton F. Nagem, and Ivar E. V. Sousa

550

An Advanced Nonlinear Control Approach for Aluminum Reduction Process . . . Jing Shi, Yuchen Yao, Jie Bao, Maria Skyllas-Kazacos, Barry J. Welch, and Ali Jassim Model Based Approach for Online Monitoring of Aluminum Production Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lucas José da Silva Moreira, Gildas Besançon, Francesco Ferrante, Mirko Fiacchini, and Hervé Roustan Predictive Analytics for Enhancing Productivity of Reduction Cells . . . . . . . . . . Shanmukh Rajgire, Abhijeet Vichare, Amit Gupta, and Devendra Pathe

556

566

572

Contents

xiii

Restart of Shutdown Pots: Troubles, Solutions and Comparison with Normal Pots to Improve Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ved Prakash Rai and Vibhav Upadhyay Electrochemical Behaviour of Cu-Al Oxygen-Evolving Anodes in Low-Temperature Fluoride Melts and Suspensions . . . . . . . . . . . . . . . . . . . . . Andrey S. Yasinskiy, Sai Krishna Padamata, Peter V. Polyakov, Aleksandr S. Samoilo, Andrey V. Suzdaltsev, and Andrey Yu. Nikolaev Alumina Concentration Measurements in Cryolite Melts . . . . . . . . . . . . . . . . . . . Luis Bracamonte, Karoline Nilsen, Christian Rosenkilde, and Espen Sandnes The Influence of Polarisation on the Wetting of Graphite in Cryolite–Alumina Melts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Henrik Åsheim, Ingrid A. Eidsvaag, Asbjørn Solheim, Henrik Gudbrandsen, Geir M. Haarberg, and Espen Sandnes Oxidation Study of Zinc Sulfite on the Removal of Sulfur Dioxide from Aluminum Electrolysis Flue Gas by Zinc Oxide . . . . . . . . . . . . . . . . . . . . . . . . . Xuejiao Cao, Ting-an Zhang, Yan Liu, Weiguang Zhang, and Simin Li Electrolysis of Low-temperature Suspensions: An Update . . . . . . . . . . . . . . . . . . Andrey Yasinskiy, Andrey Suzdaltsev, Sai Krishna Padamata, Petr Polyakov, and Yuriy Zaikov Adapting Modern Industrial Operation Parameters in a Standardized Laboratory Cell for Measuring Current Efficiency for Aluminium Deposition: Unexpected Challenges and Lessons Learned . . . . . . . . . . . . . . . . . . . . . . . . . . . R. Meirbekova, O. Awayssa, G. M. Haarberg, and G. Saevarsdottir Aluminium Smelter Crust—Phase Distribution and Structure Analysis of Top Zone Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shanghai Wei, Jingjing Liu, George Allan, Tania Groutso, John J. J. Chen, and Mark P. Taylor Influence of Anode Cover Material Particle Size Composition on Its Physical Property and Insulation Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Changlin Li, Junqing Wang, Yunfeng Zhou, Bin Fang, Yanfang Wang, and Qingguo Jiao

579

591

600

608

620 626

637

644

653

Lab Scale Experiments on Alumina Raft Formation . . . . . . . . . . . . . . . . . . . . . . Sindre Engzelius Gylver, Asbjørn Solheim, Henrik Gudbrandsen, Åste Hegglid Follo, and Kristian Etienne Einarsrud

659

Mass- and Heat Transfer During Dissolution of Alumina . . . . . . . . . . . . . . . . . . Asbjørn Solheim and Egil Skybakmoen

664

The Rate of HF Formation During Addition of Alumina to NaF-AlF3 Melts . . . . Karen S. Osen, Dian Mughni Fellicia, Christian Rosenkilde, Camilla Sommerseth, and Ole Kjos

672

Validation of the Gravimetric Method to Properly Follow Alumina Dissolution in Cryolitic Bath . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jonathan Alarie, Thomas Roger, László I. Kiss, Sándor Poncsák, Sébastien Guérard, and Jean-François Bilodeau Development of a Mathematical Model to Simulate Raft Formation . . . . . . . . . . T. Roger, K. Fraser, L. Kiss, S. Poncsák, S. Guérard, J. F. Bilodeau, and G. Bonneau

680

688

xiv

Efficient Alumina Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jan Paepcke, Arne Hilck, Michael Altmann-Rinck, and Andrej Meinhardt Status Analysis of Particle Size Distribution and Attrition Index of the Smelter Grade Alumina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Youjian Yang, Xiaojuan Pang, Junfeng Qi, Wenju Tao, Zhaowen Wang, Fengguo Liu, Aimin Liu, Jiangyu Yu, Bingliang Gao, Zhongning Shi, and Xin Shu The Effect of Hard Scale Deposition on the Wall Heat Flux of a Cold Finger . . . Daniel Perez Clos, Sverre Gullikstad Johnsen, Petter Nekså, and Ragnhild Elizabeth Aune

Contents

696

704

710

The Application of Intelligent Breaking and Feeding Technology for Aluminium Reduction Pot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bo Hong, Qinghong Tian, Zhiyang Chen, Xiaotian Tan, and Shiping Yu

719

Reducing the Carbon Footprint: Aluminium Smelting with Changing Energy Systems and the Risk of Carbon Leakage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gudrun Saevarsdottir, Halvor Kvande, and Barry J. Welch

726

Measurement System for Fugitive Emissions in Primary Aluminium Electrolysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Håkon Aleksander Hartvedt Olsen Myklebust, Thor A. Aarhaug, and Gabriella Tranell Validation of QCL CF4 Gas Analyzer for Sensitivity and Selectivity . . . . . . . . . . Thor Anders Aarhaug

735

744

A Laboratory Study of the HF Generation Potential of Particulate Fluorides from Cell Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jenny H. Hung and James B. Metson

751

Method Development to Estimate Total Low Voltage and High Voltage PFC Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Luis Espinoza-Nava, Christine Dubois, and Eliezer Batista

758

Update on SO2 Scrubbing Applied in Primary Aluminium Smelters . . . . . . . . . . Stephan Broek Optimization of a Gas Treatment Center Equipped with Extended Surface Bag Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Julie Dontigny, Stephan Broek, Philippe Martineau, Mario Dion, and Raymond Emond Update on the Abart Gas Treatment and Alumina Handling at the Karmøy Technology Pilot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anders Sørhuus, Sivert Ose, Eivind Holmefjord, Håvard Olsen, and Bent Nilsen The Australian Energy Crisis, Its Impact on Domestic Aluminium Smelting and Potential Solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . David S. Wong, Geoff Matthews, Alton T. Tabereaux, Tim Buckley, and Mark M. Dorreen

766

777

785

791

Recycling of the Flue Gas from Aluminium Electrolysis Cells . . . . . . . . . . . . . . . Asbjørn Solheim and Samuel Senanu

803

Utilization of Waste Heat for Pre-heating of Anodes . . . . . . . . . . . . . . . . . . . . . . Martin Grimstad, Kim Ronny Elstad, Asbjørn Solheim, and Kristian Etienne Einarsrud

811

Contents

xv

Toward Minimizing the of Co-evolution of PFC Emission in EGA Smelter . . . . . Ali Jassim, Najeeba Al Jabri, Sergey Akhmetov, Daniel Whitfield, and Barry Welch Development and Application of GP500+ Energy Saving Aluminum Reduction Cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zhuojun Xie, Song He, and Hongmin Ao Part IV

817

827

Cast Shop Technology

Hands-Free Casting at AMAG Casting GmbH—It Is Possible! . . . . . . . . . . . . . . Bernd Prillhofer, Rudolf Dobler, and Thomas Mrnik

837

User-Friendly Surveillance Tools to Prevent Bleed-Out During Cast Start . . . . . M. Badowski, D. Krings, G. U. Gruen, W. Droste, Ph. Meslage, and B. Jaroni

844

Beryllium Reduction Potential in AlMg Cast Alloys . . . . . . . . . . . . . . . . . . . . . . J. Steglich, A. Basa, A. Kvithyld, N. Smith, and I. Zerbin

852

Accurate Real-Time Elemental (LIBS) Analysis of Molten Aluminum and Aluminum Alloys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sveinn Hinrik Gudmundsson, Jon Matthiasson, and Kristjan Leosson

860

Industrial Verification of Two Rotor Fluxing in Large Crucibles . . . . . . . . . . . . Terje Haugen, Arild Håkonsen, and Vegard Innerdal

865

Dynafeed: An Improved Crucible Transfer System . . . . . . . . . . . . . . . . . . . . . . . André Tremblay, Jean-Francois Desmeules, and Martin Dubois

868

Metal Transfer from Furnace to Furnace—A Case Study . . . . . . . . . . . . . . . . . . Olivier Dion-Martin, Pierre Jeanroy, Jean-Francois Desmeules, and Marek Varadinek

873

Heavily Loaded Areas in Aluminum Melting Furnaces and Possible Refractory Solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Thomas Schemmel, Rüdiger Pfaar, and Uwe Kremer Mold Shape Control for Direct Chill Ingot Casting . . . . . . . . . . . . . . . . . . . . . . . Craig Cordill Continuous Monitoring of Butt Curl Development During DC Casting—Development and Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Werner Ewald Droste, Daniel Krings, Gerd-Ulrich Gruen, Mark Badowski, and Markus Hagen Constellium’s Mould Technology for Al Alloy Slab DC Casting . . . . . . . . . . . . . Ph. Jarry, O. Ribaud, L. Jouët-Pastré, E. Waz, P. Delaire, P.-Y. Menet, M. Bertherat, and P. Celle

879 887

892

901

Fluid Flow Analyses and Meniscus Behavior During the Horizontal Single Belt Casting (HSBC) of Aluminum Alloy AA6111 Strips . . . . . . . . . . . . . . . . . . . . . . Roderick Guthrie, Mihaiela Isac, and Donghui Li

909

Effect of Water Flow Distribution on the Performance of Aluminium Small-Form Ingot Chains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lei Pan, Eric Laplante, and Francis Breton

917

Small Scale Oxidation Experiments on AlMg Alloys in Various Gas Fired Furnace Atmospheres . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Johansson, E. Solberg, M. Skramstad, T. Kvande, J. Lodin, N. Smith, M. Syvertsen, and A. Kvithyld

923

xvi

Study of the Oxidation of an Al-5Mg Alloy in Various Industrial Melting Furnace Atmospheres . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Johannes Lodin, Martin Syvertsen, Anne Kvithyld, Anders Johansson, Egil Solberg, and Thomas Kvande Batscan™, Constellium In-melt Ultrasonic Inclusion Detector: Industrial Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jean-Louis Achard, Nicolas Ramel, Guido Beretta, Pierre-Yves Menet, Jocelyn Prigent, and Pierre Le Brun Benchmark and Practical Application of State of the Art Hydrogen Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Pelss, J. Morscheiser, S. Radwitz, J. Kremer, and A. Gilles

Contents

930

936

944

Molten Aluminum Quality Evaluations for Thin Foil Products . . . . . . . . . . . . . . Çisem Doğan, A. Ulaş Malcıoğlu, Anıl Ozkaya, Eren Toraman, and Ali Ulus

951

Industrial Verification of One- and Two-Chamber Siphon Degassing . . . . . . . . . Arild Håkonsen and Terje Haugen

959

Evaluation of CFF and BPF in Pilot Scale Filtration Tests . . . . . . . . . . . . . . . . . M. Syvertsen, I. Johansen, A. Kvithyld, S. Bao, U. Eriksen, B. E. Gihleengen, S. Akhtar, A. Bergin, and A. Johansson

963

Dynaprime Filtration Technology Experience at Alcoa Baie-Comeau . . . . . . . . . Francis Caron and Jean-Francois Desmeules

972

Improving Ultrasonic Melt Treatment Efficiency Through Flow Management: Acoustic Pressure Measurements and Numerical Simulations . . . . . . . . . . . . . . . Tungky Subroto, Dmitry G. Eskin, Christopher Beckwith, Iakovos Tzanakis, Georgi Djambazov, and Koulis Pericleous Impact of TiB2 Particle Size Distribution on Grain Refining Effectiveness . . . . . Akihiro Minagawa Effect of Nucleant Particle Size Distribution on the Grain Refining Efficiency of 7xxx Alloys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G. Salloum-Abou-Jaoude, Ph. Jarry, P. Celle, and E. Sarrazin

981

988

994

Impact of Transition-Metal Elements on Grain Refiner Performance in AA6061 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1000 Elli Tindall, Samuel R. Wagstaff, and Kathleen Bennett Application Ultrasonic Technology Processing for Aluminum Treatment While Casting Slabs on Industrial Equipment of UC RUSAL . . . . . . . . . . . . . . . 1007 I. V. Kostin, A. Y. Krokhin, V. F. Frolov, S. G. Bochvar, I. V. Bobkov, and N. E. Laschukhin Influence of Liquid Jet Stirring and In-Situ Homogenization on the Intermetallics Formation During DC Casting of a 6xxx Al Alloy Rolling Ingot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1013 S. Kumar, J. Cracroft, and R. B. Wagstaff Digital Manufacturing for Foundries 4.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1019 Prateek Saxena, Michail Papanikolaou, Emanuele Pagone, Konstantinos Salonitis, and Mark R. Jolly

Contents

xvii

Integrating Fluid Simulation with Virtual Die Casting Machine for Industry 4.0 and Operator Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1026 John Moreland, John Estrada, Edwin Mosquera, Kyle Toth, Armin K. Silaen, and Chenn Q. Zhou Numerical Simulation of Wire Rod Casting of AA1370 and AA6101 Alloys . . . . 1032 Dag Lindholm, Shahid Akhtar, and Dag Mortensen Influence of Nozzle Shape on Near-Surface Segregation Formation During Twin-Roll Casting of Aluminum Strips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1039 Olexandr Grydin, Mykhailo Stolbchenko, and Mirko Schaper Effect of Ultrasonic Treatment on the Eutectic Phase and Cu Content in the Al Matrix of Large-Scale 2219 Al Alloy Ingot . . . . . . . . . . . . . . . . . . . . . . 1045 Li Zhang, Xiaoqian Li, Ripeng Jiang, Ruiqing Li, and Lihua Zhang Influence of Alloying Additives on the Electrochemical Behavior of Cast Al-5Zn Alloys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1052 Mohamed Eissa Moussa, Hoda Elkilany, Shimaa El-Hadad, and Madiha Shoeib Thermal Analysis and Microstructure of Al-12%Si-2.5%Cu-0.4%Mg Cast Alloy with Ce and/or La Rare Earth Metals . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1056 Mahmoud Tash, Waleed Khalifa, and Iman El-Mahallawi Numerical Simulation of Temperature Field in 6061 Aluminum Alloy Vertical Twin-Roll Casting Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1063 Chaopan Xie, Xiaoping Liang, and Yu Wang Part V

Cast Shop Technology: Recycling and Sustainability Joint Session

Constellium R&D Approach in Recycling, From Lab to Industrial Scale . . . . . . 1073 A. Pichat, A. Vassel, P. Y. Menet, and L. Jouët-Pastre Representative Sampling, Fractionation and Melting of Al-Scrap . . . . . . . . . . . . 1083 Stefan Wibner, Helmut Antrekowitsch, and Barbara Falkensammer Recycling of Aluminium from Mixed Household Waste . . . . . . . . . . . . . . . . . . . . 1091 Sigvart Eggen, Kurt Sandaunet, Leiv Kolbeinsen, and Anne Kvithyld An Assessment of Recyclability of Used Aluminium Coffee Capsules . . . . . . . . . . 1101 Mertol Gökelma, Fabian Diaz, Ilayda Elif Öner, Bernd Friedrich, and Gabriella Tranell Fractional Solidification for Purification of Recycled Aluminium Alloys . . . . . . . 1110 Susanna Venditti, Dmitry Eskin, and Alain Jacot A Rapid Method of Determining Salt Flux Melting Point and Composition . . . . 1119 Ray D. Peterson Recovery of Aluminium Metal Using Ultrasonic Technique and Production of Al–Si Hypereutectic Alloys from 6063 Alloy’s Black Dross Using Silicon Lumps and Flux . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1128 G. M. Taha, Ahmed S. Aadli, and A. A. Ebnalwaled Automatic Skimming Procedure for Reducing Aluminium Losses and Maintaining the Uniform Quality of the Molten Metal . . . . . . . . . . . . . . . . . 1137 Varužan Kevorkijan, Uroš Kovačec, and Sandi Žist

xviii

Contents

Evaluation of the Effect of CO2 Cover Gas on the Rate of Oxidation of an AlMgSi Alloy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1141 Cathrine Kyung Won Solem, Kai Erik Ekstrøm, Gabriella Tranell, and Ragnhild E. Aune Part VI

Electrode Technology for Aluminum Production

The Development of Anode Shape, Size and Assembly Designs—Past, Present and Future Needs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1151 Barry J. Welch 10 Years of Anode Research and Development: Alcoa and Université Laval Experience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1161 Jayson Tessier, Julien Lauzon-Gauthier, Mario Fafard, Houshang Alamdari, Carl Duchesne, and Louis Gosselin Carbon Anode Raw Materials—Where Is the Cutting Edge? . . . . . . . . . . . . . . . 1163 Les Edwards Solids Flow Considerations and Their Impact in Smelter Carbon Plant Operations and Product Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1166 Brian H. Pittenger and Andrés D. Orlando How to Improve the Environmental Efficiency of the Hall-Heroult Process While Producing and Using Carbon Anodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1171 Antti Koulumies, Ana Maria Becerra, Paul Merlin, Lasse Piechowiak, and Martin Zapke Trends in Anode Carbon Production Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . 1174 Derek Santangelo Development of a Soft Sensor for Detecting Overpitched Green Anodes . . . . . . . 1176 Adéline Paris, Carl Duchesne, Éric Poulin, and Julien Lauzon-Gauthier Diffusion Measurements of CO2 Within Carbon Anodes for Aluminium Smelting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1183 Epma Putri, Geoffrey Brooks, Graeme A. Snook, Lorentz Petter Lossius, and Ingo Eick Testing of SERMA Technology on Industrial Anodes for Quality Control for Aluminum Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1189 Yasar Kocaefe, Duygu Kocaefe, Dipankar Bhattacharyay, Abderrahmane Benzaoui, and Jean-François Desmeules Modelling of Gas Injection on Anode Baking Furnace and Application to Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1196 Sandra Besson, Solène Bache, Arnaud Bourgier, Jean-Philippe Schneider, and Thierry Conte Higher Baking and Production Levels in Anode Baking Furnaces and Associated Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1203 SyedArif Ali, Charles Lebel-Tremblay, Pierre-Yves Brisson, and Alexandre Gagnon

Contents

xix

Major Reconstruction of Central Casing of Open Top Baking Furnace with a View to Increase Its Lifespan and Reduce the Total Costs Comparing to Full Reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1210 Christos Zarganis, Eftychia Liantza, Harilaos Dolgyras, Giannakis Christos, Kosmetatos Dionysios, Christophe Molinier, and Arnaud Bourgier Regulation and Management of Anode Baking Furnace Production Cycle During Green Anode Crisis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1218 Kalpataru Samal and Suryakanta Nayak Sustainable Spent Pot Line Management Guidance . . . . . . . . . . . . . . . . . . . . . . . 1225 Pernelle Nunez Purification of Graphite by Thermal Vacuum Treatment of Spent Potlining . . . . 1231 Kristin Sundby, Ulf Sjöström, Ellen Myrvold, and Morten Isaksen The LCL&L Process: A Sustainable Solution for the Treatment and Recycling of Spent Pot Lining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1237 Laurent Birry and Stephane Poirier Experimental Study on the Collecting Agent for Spent Potlining Flotation Index Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1243 Nan Li, Lei Gao, and Kinnor Chattopadhyay Environmental Benefits of Using Spent Pot Lining (SPL) in Cement Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1251 Mohammad Al Jawi, Chun Man Chow, Srinivasa Pujari, Michael Pan, Tanvi Kulkarni, Mohamed Mahmoud, Heba Akasha, and Salman Abdulla Characteristic Analysis of Hazardous Waste from Aluminum Reduction Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1261 Mingzhuang Xie, Han Lv, Tingting Lu, Hongliang Zhao, Rongbin Li, and Fengqin Liu Energy Saving in Hall–Héroult Cell by Optimization of Anode Assembly Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1267 Abdul-Mageed M. Shamroukh, S. A. Salman, William Berends, W. A. Abdel-Fadeel, and G. T. Abdel-Jaber High Temperature Creep Behaviour of Carbon-Based Cathode Material for Aluminum Electrolysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1278 Wei Wang and Kai Sun Redesigning of Current Carrying Conductor—The Energy Reduction Initiative in Low Amperage Hall-Héroult Cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1283 Ved Prakash Rai and Vibhav Upadhyay Ready-to-Use Cathodes for the Hall-Héroult Process . . . . . . . . . . . . . . . . . . . . . . 1291 Markus Pfeffer, Oscar Vera Garcia, Louis Bugnion, and Laure von Kaenel Mechanism Understanding of Sodium Penetration into Anthracite Cathodes: A Perspective from Diffusion Coefficients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1299 Jiaqi Li, Hongliang Zhang, Jingkun Wang, and Yunrui Wang Anhydrous Carbon Pellets—An Engineered CPC Raw Material . . . . . . . . . . . . . 1309 Les Edwards, Maia Hunt, and Christopher Kuhnt Influence of Particle Shape and Porosity on the Bulk Density of Anode Grade Petroleum Coke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1319 Frank Cannova, Mike Davidson, and Barry Sadler

xx

Contents

An EXAFS and XANES Study of V, Ni, and Fe Speciation in Cokes for Anodes Used in Aluminum Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1327 Gøril Jahrsengene, Hannah C. Wells, Camilla Sommerseth, Arne Petter Ratvik, Lorentz Petter Lossius, Katie H. Sizeland, Peter Kappen, Ann Mari Svensson, and Richard G. Haverkamp Additive Selection for Coal Tar Pitch Modification in Aluminium Industry . . . . 1329 Julie Bureau, Armita Rastegari, Duygu Kocaefe, Yasar Kocaefe, and Hans Darmstadt Charcoal and Use of Green Binder for Use in Carbon Anodes in the Aluminium Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1338 Camilla Sommerseth, Ove Darell, Bjarte Øye, Anne Støre, and Stein Rørvik Correction to: Effect of Concentrations and Pressures of CO2 on Calcification–Carbonation Treatment of Bauxite Residue . . . . . . . . . . . . . . . . Xi Chao, Ting-an Zhang, Guo-zhi Lv, and Yang Chen

C1

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1349 Subject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1355

About the Editor

Alan Tomsett has been involved in research and industrial application of materials and metals for 40 years, with the majority of this time in the aluminium industry. He received his B.Sc. and Ph.D. in Chemical Engineering from the University of New South Wales in Sydney, Australia and worked as a Research Scientist at Kyoto University, Japan. He joined the Comalco Research Centre in Melbourne, Australia in 1987 and has held numerous technical and business improvement roles at Comalco/Rio Tinto including Carbon R&D Manager, Program Director for the global Rio Tinto Alcan Carbon R&D Team, and Carbon Technical Manager for the Rio Tinto Aluminium Pacific Region. He is now Technical Manager—Aluminium Smelting for Rio Tinto Pacific Operations, where he provides strategic direction, technical support and advice on carbon, aluminium reduction, casting, and raw material procurement to the Rio Tinto aluminium smelters in the Pacific region. He has been a member of TMS since 1996 and a regular attendee of the Annual Meeting since 2000. He has been a member of the Aluminum Committee since 2011 where his contributions include Electrode Symposium Chair (2011); Lead Editor of Essential Readings in Light Metals, Volume 4— Electrode Technology for Aluminum Production (2013); and Secretary (2011–2015). He has been an Electrode Technology Session Chair on four occasions and has coauthored several Light Metals and JOM papers. He was on the organising committee of the successful 12th Australasian Aluminium Smelting Conference in Queenstown, New Zealand, has been a guest lecturer for the University of New South Wales/ University of Auckland Graduate Program in Aluminium Smelting Technology, and a regular contributor to earlier Australasian Aluminium Smelting Conferences.

xxi

Program Organizers

Alumina and Bauxite James Vaughan is Head of the University of Queensland Hydrometallurgy Research Group within the School of Chemical Engineering. He obtained a bachelor’s degree in Metallurgical Engineering at McGill University (2001) followed by Master of Applied Science (2003) and Ph.D. (2008) degrees in Materials Engineering at The University of British Columbia. He recently served as Director of the University of Queensland Rio Tinto Bauxite & Alumina Technology Centre and previously worked as a research engineer in extractive metallurgy with Placer Dome (gold) and BHP (nickel).

Aluminum Alloys, Processing and Characterization Dmitry G. Eskin received his Engineering and Ph.D. degrees from Moscow Institute of Steel and Alloys (Technical University, Russia) in 1985 and 1988, respectively. After that, he worked as a Senior Scientist in the Baikov Institute of Metallurgy (Russian Academy of Sciences) with main research foci of alloy development and heat treatment and processing of aluminum alloys. In 1999–2011, he was a Senior Scientist and a Fellow in Materials Innovation Institute and after 2008 also held a position of an Associate Professor at Delft University of Technology (The Netherlands), where he conducted fundamental and applied research on solidification processing of metallic materials, with major contributions to direct-chill casting. In 2011, he joined Brunel University London (U.K.) as a Professor in Solidification Research. His current research concerns fundamentals and application of ultrasonic cavitation to melt processing as well as alloy development. He is a well-known specialist in physical metallurgy and solidification processing of light alloys, and is author or co-author of more than 250 scientific papers, 7 monographs, and a number of patents. Among his books are Iron in Aluminum Alloys (2002), Multicomponent Phase Diagrams: Applications for Commercial Aluminum Alloys (2005), Physical Metallurgy of DirectChill Casting of Aluminum Alloys (2008), Direct-Chill Casting xxiii

xxiv

Program Organizers

of Light Alloys: Science and Technology (2013), and Solidification Processing of Metallic Alloys Under External Fields (2018). He has been a member of TMS since 2000, and is a current member of TMS Aluminum Committee, an organizer of a number of symposia, and a regular speaker at TMS Annual Meetings.

Aluminum Reduction Technology Jayson Tessier is Pilot Operation Manager at Alcoa Corporation Aluminum Center of Excellence. After earning a Ph.D. in chemical engineering from Université Laval in Quebec City, Canada, he joined Alcoa in 2011 as a Research Engineer within the Aluminum Smelting Center of Excellence. Based on a mix of floor experience and research, he delivered different technological improvements related to alumina feeding for Hall-Héroult cells and worked on different process improvements and root cause analysis projects. In 2014, he took on the role of Pilot Operation Manager, leading a team carrying out test programs within Alcoa smelters, aimed at creeping and improving energy and metallurgical efficiency of reduction cells. He is also leading research activities between Alcoa and Université Laval. Since 2004, he has contributed to TMS and other international conferences and scientific journals and has also acted as session chairperson for the TMS Annual Meeting. With other Alcoa colleagues, he was the recipient of the Pr. Barry Welch Best Paper Award at the 10th Australasian Smelting Technology Conference in 2011.

Cast Shop Technology Johannes Morscheiser currently holds the position of R&D Manager Casting at Aleris. In this function, he is responsible for the casting technology group at Aleris including the pilot casting facility in Koblenz, Germany. After finishing his M.Sc. in metallurgy in 2008 at the RWTH Aachen University in Germany, he worked there as a research assistant and became group leader for vacuum metallurgy with a focus on vacuum induction melting, electroslag remelting and vacuum arc remelting. His work included extensive projects on superalloys, titanium and titanium aluminides, refractory metals, precious metals, and special aluminium alloys like Al-Li. In 2014, he graduated with a Ph.D. in Non-Ferrous Metallurgy from RWTH Aachen University after he had joined Aleris in 2013 as a research engineer. Since 2018 he has held his current position as R&D Manager Casting. In his work, he focuses on the global support of Aleris cast shops regarding questions about liquid metal processing, solidification, and homogenization of aluminium alloys. In this context, he has built expertise in the fields of melt cleanliness and respective

Program Organizers

xxv

measurement techniques, numerical process modelling, and in-depth analysis of technical processes. Other important aspects of his work are molten metal safety and helping people inside and outside his team to develop their potentials.

Cast Shop Technology: Recycling and Sustainability Joint Session Johannes Morscheiser (see above)

Electrode Technology for Aluminum Production Duygu Kocaefe is a Professor at the University of Quebec at Chicoutimi (UQAC). She has more than 25 years of experience in the fields of carbon, anode production, modelling and optimisation of industrial processes, heat and mass transfer, and reaction kinetics. She has a B.Sc.E. (Middle East Technical University (METU) in Turkey) and M.Sc.E. (University of New Brunswick (UNB) in Canada), and Ph.D. (UNB) in Chemical Engineering. She has worked with several companies on various aspects of aluminium production including many on carbon technology. She was the holder of the UQAC/ Aluminerie Alouette Research Chair on Carbon. Currently, she is the UQAC Chair on Industrial Materials (Chaire institutionnelle de recherche sur les matériaux industriels—CHIMI) and has many collaborative grants with industrial partners and government institutions. She has published extensively in the field of carbon, lectured in specialised conferences, and trained numerous graduate students. She is Director of Graduate Studies in Engineering (research) at UQAC, is responsible for the Production Axe of Regroupement Aluminium (REGAL), is Scientific Advisor to Fonds de recherche du Quebec-Nature et technologies (FRQNT), and is a Board member of the “Association de la francophonie à propos des femmes en sciences, technologies, ingénierie et mathématiques (AFFESTIM)”. Over the years, she has served The Minerals, Metals & Materials Society (TMS) as the session chair and the reviewer of many papers in the Electrode Technology Symposium during annual meetings. She also has authored and coauthored a large number of papers presented at these meetings.

Aluminum Committee 2019–2023

Chairperson Corleen Chesonis, Metal Quality Solutions LLC, Pennsylvania, USA Vice Chairperson Alan David Tomsett, Rio Tinto Pacific Operations, Queensland, Australia Past Chairperson Olivier Martin, Rio Tinto, Saint-Jean, France Secretary Stephan Broek, Hatch Ltd., Ontario, Canada JOM Advisor David Sydney Wong, University of Auckland, Auckland, New Zealand Light Metals Division Chair Eric Nyberg, Tungsten Parts Wyoming, Wyoming, USA

Members-at-Large Through 2020 Alexander Baker, Lawrence Livermore National Laboratory, California, USA Hunter Henderson, Oak Ridge National Laboratory, Tennessee, USA Orlando Rios, Oak Ridge National Laboratory, Tennessee, USA Sugrib Kumar Shaha, University of Waterloo, Ontario, Canada Stephan Broek, Hatch Ltd., Ontario, Canada Mohamed Hassan Ali, Masdar Institute of Science & Technology, Abu Dhabi, UAE Edward McRae Williams, Arconic, Pennsylvania, USA

Members-at-Large Through 2021 Ali Jasim Banjab, Emirates Global Aluminium, Dubai, UAE Kristian Etienne Einarsrud, Norwegian University of Science & Technology, Trondheim, Norway John Griffin, ACT LLC, New Jersey, USA Houshang Alamdari, Laval University, Quebec, Canada Mark Doreen, Energia Potior Ltd., Auckland, New Zealand Yanjun Li, Norwegian University of Science & Technology, Trondheim, Norway Arne Ratvik, SINTEF, Trondheim, Norway Barry Sadler, Net Carbon Consulting Pty Ltd., Victoria, Australia Zhang Tingan, Northeastern University, Shenyang, China

xxvii

xxviii

Members-at-Large Through 2022 Mark Badowski, Hydro Aluminium Rolled Products, Bonn, Germany Pascal Lavoie, Alcoa, Quebec, Canada Olivier Martin, Rio Tinto, Saint-Jean, France Linus Perander, Outotec Norway AS, Oslo, Norway Andre Phillion, McMaster University, Ontario, Canada Xiyu Wen, Secat Inc, Kentucky, USA

Members-at-Large Through 2023 Corleen Chesonis, Metal Quality Solutions LLC, Pennsylvania, USA Marc Dupuis, GeniSim Inc, Quebec, Canada Sebastien Fortin, Rio Tinto, Quebec, Canada John Grandfield, Grandfield Technology Pty Ltd., Victoria, Australia Lorentz Petter Lossius, Hydro Aluminium AS, Ovre Ardal, Norway Pierre-Yves Menet, Constellium Technology Center, Voreppe, France Horomi Nagaumi, Soochow University, Jiangsu, China Nigel Jeffrie Ricketts, Altrius Engineering Services, Queensland, Australia Alan David Tomsett, Rio Tinto Pacific Operations, Queensland, Australia Sam Wagstaff, Novelis Inc, Georgia, USA

Aluminum Committee 2019–2023

Part I Alumina and Bauxite

Impacts of Mineralogy on Soluble Phosphorus Concentrations During Low Temperature Processing of Jamaican Bauxites Michael D. Coley, Anthony M. Greenaway, and Khadeen E. Henry-Herah

Abstract

Jamaica has about 7.1% of world bauxite reserves. Traditionally, local refineries process good-settling low phosphorus bauxites. As these ores become scarce, mining areas with poor-settling high phosphorus bauxites are being explored. In preparation for having to process these bauxites, this study sought to identify the main minerals that influence soluble phosphorus concentrations. Four correlations for predicting soluble phosphorus during low temperature digestion were applied to both the currently-mined and future bauxite resources. Soluble phosphorus concentrations were successfully predicted from total phosphorus in the bauxite. A simple mine-specific correlation that adjusts based on the calcium to phosphorus (CaO:P2O5) ratio in the bauxites was able to predict soluble phosphorus to within ±15% of measured values. The correlation was applicable even to ores with highly variable compositions. If the phosphorus impurity in the future bauxite is taken as crandallite, a correlation that over-predicts the measured soluble phosphorus by about 20–30% can be used to assess lime requirements for phosphorus control. Crandallite, calcite and silica were the main minerals that influence soluble phosphorus concentrations.




Keywords

Goethite Hematite Caustic soluble




Crandallite




Phosphorus

M. D. Coley (&)
A. M. Greenaway
K. E. Henry-Herah Department of Chemistry, The University of the West Indies, Mona, Kingston 7, WI, Jamaica e-mail: [email protected] A. M. Greenaway e-mail: [email protected]




Introduction Jamaican bauxites are primarily gibbsitic (39–55%). They are traditionally classified as red, catchment ores if hematite is the main iron mineral or as yellow hillside bauxites if the iron mineral is goethite [1]. Both types of bauxite contain boehmite, kaolinite, anatase, calcite, crandallite and other impurities. The red bauxites have high extraction efficiencies and good settling properties under low temperature digestion conditions and result in alumina with low impurity levels [1]. These bauxites are becoming scarce however and Bayer plants may have to consider processing the poor-settling, high goethite bauxites. Both the red and yellow bauxites have similar total alumina and total iron concentrations. The yellow ores contain less gibbsite and significantly higher concentrations of easily dissolved phosphate minerals [2, 3]. Low temperature processing of these bauxites results in poor mud compaction and increased mud load. Their processing also results in higher caustic and alumina losses hence production rates are low and more energy is used. Bauxite deposits in Australia, Guinea and Venezuela have low phosphate concentrations of about 0–0.3% P2O5 on average [4, 5]. In Jamaica, The red, Harmons Valley bauxite deposit contains 0–0.6% P2O5. In contrast, yellow bauxite from the Blue Mountain deposits have 0.6–3.0% P2O5 [1, 6]. A deposit containing 0.06–28.99% P2O5 has also been reported [7]. Because of their low concentrations, it is difficult to identify the phosphorus minerals in the red Jamaican bauxites. Initially, apatites (Ca5(PO4,CO3)3 (F,OH,Cl) were considered as the main phosphorus minerals in these bauxites however crandallite was recently identified and is now regarded as the main P mineral [1, 8]. Crandallite (CaAl3(PO4)2(OH)5.H2O) dominates in the yellow bauxites however small amounts of apatites, wavellite (Al3(PO4)2(OH)3(H2O)5 and variscite (AlPO4.2H2O) may also be present.

K. E. Henry-Herah e-mail: [email protected] © The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_1

3

4

M. D. Coley et al.

Apatite minerals have low solubility in Bayer liquors however the other P minerals are quite soluble. Depending on mineralogy, about 20–90% of the phosphorus minerals in bauxite may dissolve during predesilication and digestion [9]. High dissolved P2O5 concentrations may slow mud settling rates, reduce filtration efficiency, contaminate alumina product and deposit as scale in heater systems [2]. In addition, alumina containing >15 ppm P2O5 is usually avoided by smelters as it significantly reduces current efficiency during the smelting process [10]. Phosphorus in Bayer liquor is usually controlled through reaction with lime (CaO). Hydroxyapatite (Ca5(PO4)3(OH)), is the main precipitate in pure caustic solutions. For industrial liquors, carbonate hydroxyapatite (Ca7Na2(PO4)3(CO3)3(H2O)3(OH)) is the main precipitate [11]. The equation below shows that 70% of the PO3 4 species released when crandallite dissolves remain in solution. Additional Ca2+ must be supplied to precipitate this soluble phosphate.

mining area while 30 were taken from the current mines. Details of the methodology were reported previously [7].

Bauxite Analysis Elemental concentrations of the bauxites were determined using either fused beads or pressed pellets. A PANalytical Magix Pro XRF instrument that operated at 40 kV and 60 mA was used. For mineralogy, ground bauxites were mounted on a front-load zero-background holder. Samples were analysed on a Bruker Analytical D5005 X-ray diffractometer. It was fitted with a scintillation detector and a copper anode X-ray tube and was operated at 45 kV and 40 mA. Most of the scans were collected between 4 and 75° 2h.

Phosphorus Determination 

5CaAl3 ðPO4 Þ2 ðOHÞ5
H2 O þ 36OH 3 ! 15AlðOHÞ 4 þ Ca5 ðPO4 Þ3 ðOHÞ þ 7PO4 þ 5H2 O For complete phosphorus control, sufficient lime has to be added. A ratio of 6 mol CaO:1 mol P2O5 is often used [6, 11, 12]. A simple approach is necessary to predict the amount of phosphorus in bauxite that will dissolve during processing; this will ensure better lime control and reduced alumina loss as tri-calcium aluminate. Inadequate lime dosage may result in phosphate concentrations exceeding the tolerable limit of 200 mg P2O5/L and to the various consequences mentioned earlier [2]. This report identifies the main minerals that influence phosphorus solubility during low temperature digestion. It also compares different approaches for predicting soluble phosphorus concentrations in digestion liquor from the % P2O5 in bauxites of various mineral compositions.

Bauxite samples were digested in 102 g/L NaOH (ACS grade; BDH Chemicals) at 145 °C for 30 min. Slurries were centrifuged and then filtered. After dilution, suitable aliquots were acidified (pH 2 with 5 M H2SO4) and then analysed for soluble phosphorus (mg/L P2O5) using the molybdenum blue ascorbic acid procedure [13].

Results and Discussion The chemical and mineralogical characteristics of bauxites from both the current and future mining areas are discussed below. The solubility of their phosphorus minerals are compared with predicted values using four correlation approaches. Total phosphorus in bauxite is expressed as % P2O5 and total calcium as % CaO while the soluble phosphorus concentrations in liquors are given in mg/L P2O5, as is the industry practice.

Materials and Methods Sample Selection

Bauxite Mine Characteristics

The samples used in this study were composite bauxites that were obtained during exploration of two different mining areas. Samples of red bauxite from a traditional mining area were studied alongside yellow bauxites from a future mining area. Samples were representative of the P2O5 concentrations across each mining area and most would be appropriate for mining if blending was to be carried out. About 20% of the bauxites had unusually high concentrations of different minerals. They were included to give information on how bauxite mineralogy may influence soluble phosphorus concentrations. Ninety three bauxites were selected from the future

Bauxite samples from the current mining areas are from blanket deposits that have relatively small variations in elemental compositions. The % P2O5 is 0.10–0.35%. In contrast, the future bauxite mines are pocket deposits and the compositions are highly variable. Although total alumina and iron concentrations of both mining areas are similar, the future bauxites have lower per cent available alumina and reactive silica. The future ores contain much higher % CaO and % P2O5 than the currently mined bauxites. To be considered suitable for processing, the future bauxites are expected to meet the following specifications: total Al2O3

Impacts of Mineralogy on Soluble Phosphorus Concentrations …

(43–53%), CaO (  2.0%), Fe2O3 (10–20%), SiO2 (  2%), TiO2 (  3%) and P2O5 (  2%). Most of the samples selected from the current bauxite mines are considered suitable for processing. About 20% had >2.0% SiO2 and would require careful blending. The bauxite samples from the future mines all had % total Al2O3 within the acceptable range. Four bauxites had 2% P2O5 and nineteen had >4% P2O5. Most of the high phosphorus ores had >2% CaO while about 18% of samples exceeded the 2% SiO2 target. About 23 of the future bauxite samples far exceeded the specifications for processing. Some had >4% P2O5, others >2.5% CaO while a few had unusual concentrations of Fe2O3 or SiO2. Ore samples with  4% P2O5 and which may be blended with high-quality bauxites to meet the processing specifications were considered as being processable. The yellow future bauxites were therefore divided into two categories: processable and non-processable bauxites.

Phosphate Minerals in Current and Future Bauxites XRD could not identify the P-minerals in the currently mined red bauxites however crandallite was readily identified in all the future ores. In addition to crandallite, fluorapatite (Ca10(PO4)6F2) was identified in two bauxites with >16% P2O5 while wavellite (Al3(PO4)2(OH)3(H2O)5) was

Fig. 1 Soluble phosphorus concentrations (LT digestion) for currently mined Jamaican bauxites as influenced by their CaO:P2O5 ratios

5

observed in a sample with 13.5% P2O5. As shown earlier, crandallite dissolves readily in Bayer liquor and contributes Al2O3 and P2O5 to the process liquor. The Al2O3 goes to product while the P2O5 precipitates as hydroxyapatite if carbonate is absent as was the case in this study. About 70% of the soluble phosphorus is expected to remain in solution. If wavellite is present, it also dissolves however since calcium is absent, all the P2O5 released remains soluble. Fluorapatite is only sparingly soluble during bauxite digestion.

Soluble Phosphorus in Currently Mined Bauxites Local low temperature Bayer plants have no difficulty with managing phosphorus impurities from currently mined bauxites. Phosphorus concentrations are consistently low ( 0.50) tend to have low soluble phosphorus concentrations. Calcite is usually present in these ores and it precipitates the dissolved phosphorus and low mg/L P2O5 values are observed. These samples are represented in Fig. 1 as diamond-shaped markers and most appear below the solid trendline. Only two of the thirty bauxites had soluble phosphorus concentrations that coincided with the theoretical crandallite line which plots solubility based on crandallite being the only P-mineral in the ores. All other samples had lower concentrations, due possibly to incomplete dissolution of crandallite or to adsorption of phosphate onto the red mud. These possibilities require confirmation. It was observed however that soluble phosphorus concentrations that were close to the crandallite line were typically from bauxites with low CaO:P2O5 and low % SiO2.

Soluble Phosphorus in the Future Bauxite Resources As reported previously [14], the soluble phosphorus concentrations of the future bauxites range from 246 to 15,475 mg/L P2O5 (i.e., XRF of 0.32–24.5% P2O5). The average concentration of samples with 8%) by weight are currently considered to be uneconomic to treat with the conventional Bayer process [1, 2]. Reactive silica in bauxite, mainly in the form of kaolinite (Al2O3
2SiO2
2H2O), reacts with the sodium hydroxide solution (Bayer liquor) to form aqueous silicate H. Ogilvie
J. Vaughan
H. Peng (&) School of Chemical Engineering, The University of Queensland, Brisbane, Australia e-mail: [email protected]

and aluminate as shown by Eq. 1. At various processing stages, the solution species re-precipitate to form insoluble hydrated sodium aluminosilicate DSP, typically sodalite as shown by Eq. 2 [3, 4]. Al2 O3
2SiO2
2H2 O þ 6NaOH þ H2 O Kaolinite þ 2 , 2H2 SiO4 þ 2AlðOHÞ 4 þ 6Na

ð1Þ

 6H2 SiO2 4 þ 6AlðOHÞ4 þ Na2 X þ 6NaOH Na6 ðAlSiO4 Þ6
Na2 X
2H2 O þ 10H2 O þ 18OH ð2Þ , Sodalite 2 where: X ¼ 2OH ; 2Cl ; CO2 3 and SO4 . Many processes have been proposed to deal with high silica bauxites and they can be classified into three general approaches: reducing reactive silica input, modification of the Bayer process, and soda recovery processes [1, 5–8]. One of the options is to reduce the kaolinite dissolution during bauxite digestion. A process was patented by the Sumitomo Chemical Company in Japan [9, 10] where digestion residence time was reduced to *10 min to preferentially extract aluminium from gibbsitic bauxite based on the relative leaching rates for gibbsite and reactive silica. For the process to work, the time for solid-liquid separation also needs to be shortened, increasing the complexity of process engineering, equipment and operation. The Improved Low Temperature Digestion Process (ILTD) also operates on the principle of differential extraction as used in the Sumitomo process [8]. The behaviour of lithium in the presence of aluminium hydroxide has been studied in the past. Most of these studies were carried out in the context of environmental issues and the primary extraction of lithium [11, 12]. Precipitated lithium aluminium layered double hydroxide chloride (Li/Al LDH, LiAl2(OH)7
2H2O) from saline water contains a considerable amount of lithium. The formation of Li/Al LDH is an intercalation reaction which involves the swelling of a lamellar crystal by the admission of an adduct into the

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_5

33

34

interlamellar space. The study conducted by Heidari et al., showed that lithium ions are adsorbed on aluminium hydroxide to recover the lithium from brines [13]. The adverse effect of lithium in sodium aluminate solutions on seed precipitation has also being investigated by different groups [14–16]. However, the effect of the lithium reactions, and more specifically in the Bayer process, to inhibit the kaolinite dissolution has not been explored to our knowledge. In this study, we investigate the effect of adding lithium chloride on kaolinite dissolution in synthetic Bayer liquor (5 M NaOH and 2 M NaAl(OH)4) at 90 °C. The concentration of lithium is varied and specified with respect to the Si in the system. Li:Si molar ratios of 0, 0.1, 0.5 and 1 are studied, and both the leaching solution and solid residue are characterised. This study reveals changes in dissolution kinetics as a function of lithium concentration and provides insights into possible dissolution reaction inhibition mechanisms.

Experimental Materials and Reagents AR grade kaolinite, lithium chloride (LiCl), sodium hydroxide (98% grade containing 1% Na2CO3) and aluminium hydroxide (Al(OH)3) was purchased from Sigma-Aldrich. Concentrated solution (1) of up to 12 M NaOH was prepared by dissolving analytical grade chemicals in DI water ( 8. As for kaolinite, due to the shortage of active site, the flotation recovery of kaolinite was lower than diaspore, the highest recovery of 27% was achieved near pH 7. However, Fig. 2a shows that NaCl had little effect on diaspore flotation whether at acidic or alkalic solution, but it activated the flotation of kaolinite at pH 4–8, which indicated that NaCl has a special effect on kaolinite, it may attributed to the intercalate effect of NaCl to the layer spacing of kaolinite according to Chen [7]. In addition, Fig. 2b shows that the flotation recovery of diaspore and kaolinite had few change with the addition of KCl whether at acidic or alkalic solution, which suggested that KCl had little effect on the adsorption of collector and the flotation of bauxite, the results is consistent with the report of Zhou [6]. Hence, it can be concluded that NaCl and KCl had little effect on diaspore flotation, but NaCl had the effect of activating the flotation of kaolinite.

Zeta Potential Measurements The charged situation of mineral surface can be measured by Zeta potential test. It is known that pH value has important effect on the zeta potential of diaspore and kaolinite [10],

42 Fig. 1 XRD pattern of a diaspore and b kaolinite

C. Fang et al.

(a) D-diaspore

Intensity/cps

D

D

D D D

10

20

D

30

D D D

D

40

D

D

D

50

60

D D

D

70

D

80

Two theta/deg

(b)

K-kaolinite K

Intensity/cps

K

K

10

K

K

K

20

30

K KK

K

K

40

K

K

50

60

70

80

Two theta/deg Table 1 Mineral chemical composition analysis results

Sample

Al2O3

SiO2

Fe2O3

TiO2

CaO

MgO

K2O

Na2O

LOI

Diaspore

81.96

0.82

0.24

2.28

0.01

0.08

0.02

0.04

4.55

Kaolinite

40.68

43.25

0.44

1.86

0.02

0.05

0.11

0.05

3.54

Ionic Effect of NaCl and KCl on the Flotation of Diaspore …

(a) 100 90 80 70

Recovery/%

60

Diaspore Diaspore+NaCl Kaolinite Kaolinite+NaCl

50 40 30 20 10 0

3

4

5

6

7

8

9

10

11

12

pH

(b) 100 90 80 70

Recovery/%

Fig. 2 The effect of a NaCl and b KCl on the flotation of diaspore and kaolinite (NaCl: 100 mg/L; KCl: 100 mg/L; NaOL: 5  10−4 mol/L)

43

60

Diaspore Diaspore+KCl Kaolinite Kaolinite+KCl

50 40 30 20 10 0

3

4

5

6

7

8

pH

9

10

11

12

44

C. Fang et al.

and some reports has shown that the isoelectric point (IEP) of diaspore is between 4 and 7, while the IEP of kaolinite is between 3 and 5 [11–14]. Figure 3a shows that the zeta potential of diaspore had a decrease with the increase of pH value, and the IEP of diaspore was about 5.5. However, whether NaCl or KCl was

(a)

Diaspore Diaspore+NaCl Diaspore+KCl

40

Zeta potential/mV

20

0

-20

-40

-60

2

4

6

8

10

12

pH

(b)

Kaolinite Kaolinite+NaCl Kaolinite+KCl

20

Zeta potential/mV

Fig. 3 Zeta potential of a diaspore and b kaolinite under different treatment (NaCl: 100 mg/L; KCl: 100 mg/L)

added, the zeta potential had little change, which indicated that either NaCl or KCl had little effect on the potential of diaspore. As for kaolinite in Fig. 3b, without NaCl or KCl, the zeta potential of kaolinite also had a decrease with pH increase, and the IEP of kaolinite was about 4.2. However, the zeta potential

0

-20

-40

2

4

6

pH

8

10

Ionic Effect of NaCl and KCl on the Flotation of Diaspore …

45

2-

-3

(OL) 2 HOL (l)

-4

OL

-

-5

logC

-6 -7

HOL (aq)

-

H(OL) 2

-8 -9 -10 -11 -12

0

2

4

6

8

10

12

14

pH Fig. 4 Species concentration logarithmic diagram of NaOL (NaOL: 5  10−4 mol/L) as a function of pH

of kaolinite had an increase at pH 4–8 when NaCl was added, and the IEP of kaolinite was increase to 4.7. By contrast, KCl had little effect on the zeta potential of kaolinite.

The Effect Mechanism of NaCl and KCl on Diaspore and Kaolinite Flotation Figure 4 shows the species concentration logarithmic diagram of NaOL as a function of pH, in which OL−, HOL (aq), and H(OL)−2 are the active component. In general, the interactions between mineral and NaOL are hydrogen bonding force and dipole-dipole interaction, in which the former is stronger and the latter is weaker. However, the hydrogen bonding force would not have any change when NaCl or KCl was added, therefore NaCl or KCl affected the flotation of diasporic bauxite by changing the dipole-dipole force between mineral and collector. The diaspore belongs to the orthorhombic system and has a close packed structure, and it is difficult for NaCl and KCl to enter the interior of the lattice. However, kaolinite is a layered silicate mineral with a layer spacing of 0.073– 0.093 nm, therefore smaller ions can enter the layer spacing and affects the zeta potential [15], which finally affects the

flotation of kaolinite. It is reported that the size of Na+, K+, and Cl− is 0.095 nm, 0.133 nm, and 0.181 nm, respectively [16]. Therefore, Na+ with a similar size to layer spacing of kaolinite, is more likely to enter the layer spacing of kaolinite, increasing the zeta potential of kaolinite and increasing the dipole-dipole force between kaolinite and NaOL, and finally promoting the flotation of kaolinite. However, K+ and Cl− are difficult to insert into the layer of kaolinite due to its larger size. In addition, Na+ is a cation and has a “salt effect” on the anionic collector NaOL [17]. Which reduces the critical micelle concentration of NaOL and improve the collection capacity of NaOL. Therefore, NaCl increases the zeta potential of kaolinite by the “intercalation effect” and improves the collection capacity of collector NaOL by the “salt effect”, which finally promotes the flotation of kaolinite.

Conclusions NaCl or KCl is inevitably exist in the flotation of diasporic bauxite, KCl has little effect on the flotation of diaspore and kaolinite, while NaCl has a promoting effect on kaolinite

46

flotation. The mechanism is that Na+ has “intercalation effect” and “salt effect”, which increases the zeta potential of kaolinite and improves the collection capacity of NaOL, and finally activating the flotation of kaolinite. Acknowledgements Authors acknowledge the financial support of the National Natural Science Foundation of China (No. 51474254, No. 51904096), and Henan special project of research and promotion (technology developing, No. 172102310641).

References 1. Barbosa, F.M.; Bergerman, M.G.; Horta, D.G. Removal of iron-bearing minerals from gibbsitic bauxite by direct froth flotation. Technol. Metal. Mater. Miner., São Paulo 2016, 13(1), 106–112. 2. Huang, G.; Zhou, C.C.; Liu, J.T. Effects of different factors during the de-silication of diaspore by direct flotation. Int. J. Min. Sci. Technol. 2012, 22(3), 341–344. 3. Liu, C.M.; Feng, A.S.; Guo, Z.X. Investigation and optimization of use of anionic collectors in direct flotation of bauxite ores. Physicochem. Probl. Miner. Process. 2016, 52(2), 932–942. 4. Massola, C.P.; Chaves, A.P.; Lima, J.R.B.; Andrade, C.F. Separation of silica from bauxite via froth flotation. Miner. Eng. 2009, 22(4), 315–318. 5. Zhong, H.; Liu, G.Y.; Xia, L.Y.; Lu, Y.P.; Hu, Y.Y.; Zhao, S.G.; Yu, X.Y. Flotation separation of diaspore from kaolinite, pyrophyllite and illite using three cationic collectors. Miner. Eng. 2008, 21(12–14), 1055–1061. 6. Zhou Y.L.; Hu Y.H.; Wang Y.H. Effect of metallic ions on dispersibility of diaspore. Trans. Nonferrous Met. Soc. China 2011, 21, 1166–1171.

C. Fang et al. 7. Chen X.Q. Study on enhanced recovery of silicate minerals and selective inhibition of diaspore. Doctor, Central South University, Changsha China, 2004. 8. Ma X.; Bruckard W.J.; Holmes R. Effect of collector, pH and ionic strength on the cationic flotation of kaolinite. Int. J. Miner. Process. 2009, 93: 54–58. 9. Li Y.D.; Bi E.P.; Chen H.H. Sorption behavior of ofloxacin to kaolinite: Effect of pH, ionic strength, and Cu (II). Water Air and Soil Pollution 2017, 228(1), 46. 10. Fuerstenau D.W.; Pradip. Zeta potentials in the flotation of oxide and silicate minerals. Advances in Colloid and Interface Science 2005, 9–26. 11. Zhou Y.L. Investigation of the influence of metal ions on selective dispersion of diaspore and silicate minerals. Doctor, Central South University, Changsha China, 2011. 12. Fang, C.J.; Chang, Z.Y.; Feng, Q.M.; Xiao, W.; Yu, S.C.; Qiu, G. Z.; Wang, J. The influence of backwater Al3+ on diaspore bauxite flotation. Minerals 2017, 7, 195. 13. Jiang H. Studies on solution chemistry of interactions between cationic collectors and aliminosilicate aluminum minerals in bauxite flotation desilica. Doctor, Central South University, Changsha China, 2004. 14. Lu Y.P. Research on bauxite desilication by selective grinding-aggregation flotation. Doctor, Central South University, Changsha China, 2012. 15. Thompson J.G.; Uwins P.J.; Whittaker A.K.; Mackinon I.D. Structural characterization of kaolinite: NaCl intercalate and its derivatives. Clays and Clay Minerals 1992, 40(4): 369–380. 16. Yin Y.J. Chemistry handbook. Shandong Science and Technology Press 1985. 17. Michelmore A.; Gong W.; Jenkins P.; Schumann R.; Ralston J. The influence of polyphosphates in modifying the surface behavior and interactions of metal oxide particles. In Polymers in Mineral Processing, ed J.S. Laskowski, Quebec City, 1999, 231–245.

Quantifying the Effect of Seeds on Gibbsite Crystallization—Mathematical Modelling of Particle Size Distribution Thiago T. Franco and Marcelo M. Seckler

Abstract

A critical step in the Bayer process is the crystallization of gibbsite (c-Al(OH)3) from the caustic aluminate solution. It is necessary to add small gibbsite crystals as seeds in the crystallization circuit, which act as sites for the crystal growth and as material for agglomeration. Mathematical models are particularly useful in this context because they provide the particle evolution of the crystals as a function of time, together with the mass balances and reaction kinetics of crystallization. This work presents the particle size distribution (PSD) modelling of the Companhia Brasileira de Alumínio (CBA) alumina refinery, developed in order to study seed effects, assisting the optimization and maximization of the process yield and alumina quality. Keywords








Particle size Modelling Process simulation Precipitation kinetics Crystallization




Introduction Gibbsite crystallization is a process widely studied in universities and research centers around the world, reflected in the large number of patents since Bayer process beginnings. Today, it exists in more than a hundred refineries with different production capacities that vary from 0.1 to 6.4 Mt per year. The residence time of crystallization processes is in the range of 30–100 h, where high yields are required to justify This study supported by Teknik Alüminyum Ltd. Company T. T. Franco (&) Companhia Brasileira de Alumínio, Alumínio, Brazil e-mail: [email protected] M. M. Seckler São Paulo University, São Paulo, Brazil e-mail: [email protected]

economically viability. To produce standard quality alumina with high plant yields is a challenge to every refinery, according to Stamatiou et al. [1]. Without a good understanding of process fundamentals, inefficient design of equipment could result. In this context, mathematical modelling and process simulation are important tools for process optimization. The Companhia Brasileira de Alumínio (CBA) alumina refinery is constantly developing models to predict operational behavior, projects evaluation, process control, maintenance prioritization, etc. In 2014, Franco and Seno [2] developed a steady state precipitation simulation with specific surface area modelling, that was successfully implemented with SysCAD with the support of Kenwalt Australia. This model also included automated controllers, to setup precipitation tanks and calibrate system kinetics, and statistical models for product and seed classification. The results obtained for production rate and yield had less than 7% deviation from reality. This work presents recent developments towards precipitation modelling utilizing particle size distribution, the mechanisms of nucleation, growth and agglomeration, with a focus on the variation of seed feeding a crystallizer chain.

Precipitation Process at CBA’s Alumina Refinery Pregnant liquor (PGL) from the Heat Interchange Departments (HIDs—stage responsible for cooling the red side liquor) flows to the first precipitation tanks, where agglomeration occurs after adding fine aluminum hydroxide seed. After this stage, the liquor and agglomerated solids flow to the growth stage, controlled to target temperature by cooling systems composed of flash tanks, barometric columns and cooling towers. The growth tanks also receive coarse seed from the classification system. The resulting suspension is pumped to the last growth tanks in the chain, without seed addition and later to the hydrocyclone classification system.

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_7

47

48

T. T. Franco and M. M. Seckler

Fig. 1 Flowsheet of the CBA precipitation process

The first hydrocyclone batteries separate the final product from the seed which, in turn, are separated between fine and coarse seed by new hydrocyclone batteries. Both product and seed are filtered to recover liquor, while the product is then sent to calciners and the fine seed to the agglomeration tanks and the coarse seed to the growth tanks. The precipitation and classification system at CBA are illustrated in Fig. 1.

Model Development In order to study aluminum hydroxide seed effects on the plant yield and product quality of the precipitation area, the following mathematical models were chosen for steady state process simulation:

k1 :½NaCl k2 :½Na2 CO3  k3 :½Na2 SO4  þ þ þ k4 :0:1887:TOC 58; 44 105; 99 142; 04

ð2Þ where, TOC is the total organic carbon concentration (g/L) and ki are correction factors. With extensive experimental analyses of 92 samples and huge parameters variation they obtained as result: a0 = −9.2082, a3 = −0.8743, a4 = 0.2149, k1 = 0.9346, k2 = 2.0526, k3 = 2.1714, k4 = 1.6734, DG = −30,960 kJ/mol. This model showed deviation of ±1.2 g/L and 95% correlation. b. Growth Kinetics Growth rate is presented in the open literature by numerous authors, among them White and Bateman [4]: G ¼ kG :e

a. Alumina Solubility Rosenberg e Healy [3] established the alumina equilibrium equation to caustic liquor as function of the ionic species present in the system: A ¼

I ¼ 0:01887:C þ

0:96197:C pffi 3 a0 I pffia3 Ia4 I 2 101 þ I 1þ DG

ð1Þ

DE RT

  1 A  A 2 : pffiffiffiffi : C C

ð3Þ

where, G is the crystal growth rate (m/s), kG is the growth constant (7,40.1012 on Na2O basis), DE activation energy (DE/R = 8500 ± 800 K), A is the alumina concentration in the liquor (g/L). c. Agglomeration Kinetics

e RT

where, A* is the equilibrium alumina concentration (g/L), C is the caustic concentration (g/L) on Na2CO3 basis, R is the universal gases constant (8,3145 J/K mol), T is the liquor temperature (K), a are the ionic constants, DG is the Gibbs dissolution energy (J/mol) and I is the solution ionic strength calculated by:

Lewis and Seckler [5] stated that agglomeration rate to particles with diameters Li and Lj is: ragg;ij ¼ bij :Ni :Nj

ð4Þ

where, bij is the agglomeration kernel, Ni and Nj are the number of particles with diameters Li and Lj.

Quantifying the Effect of Seeds on Gibbsite Crystallization …

49

Fig. 2 Correction factor (b4) function temperature to different shear intensity

Livk and Ilievski [6] defined the agglomeration kernel in agitated crystallizers with the expression: G bij ¼ b4 Sij

ð5Þ

where, b4 is the correction factor to shear and temperature and Sij is the sum of diameters Li e Lj. The b4 correction factor is estimated through the graph in the Fig. 2 obtained experimentally by Livk and Ilievski to different shear intensity. d. Nucleation Kinetics The primary nucleation rate considered was proposed by Misra and White [7]: BN ¼ KN :

  A  A 2 :SSA C

ð6Þ

where, KN is de nucleation constant and SSA is the specific superficial area (m2/g). The nucleation was studied in Misra thesis [8] and the curve in Fig. 3 was obtained to the nucleation constant, for which simple polynomial correlation could be fitted.

e. Population Balance A classical particle population balance was provided by Randolph and Larson [9] in 1988 and it expresses the relationship between the number of particles (N) in the product and the mechanisms of nucleation, agglomeration, growth and rupture: d Q ðG:N Þ þ ðN  Ni Þ ¼ ðB  DÞaggl þ ðB  DÞrup þ BN dL V ð7Þ where, Q is volume flow in the crystallizer (m3/h), V is the crystallizer volume (m3), Ni is the number of particle in the crystallizer inlet (B−D)aggl is the difference between birth and death of particle by agglomeration and (B−D)rup is the difference between birth and death of particle by rupture. The terms of agglomeration and rupture were deduced by Lewis and Seckler [5]: 1 ðB  DÞaggl ¼ 2

ZL baggl ði; L  iÞ:NðiÞ:N ðL  iÞ:di 0

Z1

 NðLÞ

baggl ði; LÞ:NðiÞ:di 0

ð8Þ

50

T. T. Franco and M. M. Seckler

Fig. 3 Nucleation constant function temperature obtained experimentally by Misra

Z1 ðB  DÞrup ¼

bði; LÞ:SðiÞ:NðiÞ:di  SðLÞ:NðLÞ

ð9Þ

0

where, b is the rupture constant and S is a selection function which describe the sizes L into which the selected particle size i breaks. The model was implemented in the SysCAD process simulator, using alumina library with PSD mode-on and some assumptions were made to run different scenarios: 1. Seed and crystals born from the liquor are perfect spheres with diameter L; 2. The only species that have influence on liquor solubility are NaOH, NaCl, Na2CO3, Na2SO4 and organics; 3. Nucleation mechanism occurs only at temperatures below or equal to 70 °C (Misra and White [7]); 4. A high shear rate is assumed for the correction factor b4;

5. It is assumed that birth and death only take place by agglomeration, they do not occur through rupture; 6. The only chemical reaction that occurs in the liquor is the aluminum hydroxide crystallization; 7. Natural evaporation from the crystallizers is not considered.

Results and Discussion The studied PSD system is presented in Fig. 4. Extensive plant data was collected, and the kinetic constants were adjusted to obtain minimal residual differences with process simulation. The calibration was chosen to set seed parameters in the simulation and track product PSD changes.

Quantifying the Effect of Seeds on Gibbsite Crystallization …

51

Fig. 4 Block diagram from studied PSD system

Table 1 Plant data for simulation calibration

Calibration d50 (µm)

Fine seed

Coarse seed

Product

63.3

83.9

91.1

−25 µm (%)

8.8

2.0

0.3

−44 µm (%)

26.9

10.4

4.6

Fig. 5 Result of precipitation product PSD calibration

Table 2 Yield and product comparison between data and simulation

Calibration Plant data

Simulation

Deviation

Total yield (g/L)

53.23

53.28

0.09%

Production (t/h)

98.9

96.9

2.0%

The granulometry calibration values for the simulation are found in Table 1. The residual difference found by minimum squares method applied to the PSD of precipitation product was 2.33 and the fitting is shown in Fig. 5.

Yield and alumina production results also showed good agreement (Table 2). Three scenarios were defined to simulate PSD variation, where all the other process parameters were maintained unchanged (Table 3).

52

T. T. Franco and M. M. Seckler

Table 3 PSD Scenarios to simulation d50 (µm)

1. Coarse system

2. Medium system

3. Fine system

Fine seed

Coarse seed

Fine seed

Coarse seed

Fine seed

Coarse seed

77.1

91.2

67.9

86.1

56.9

80.6

−25 µm (%)

0.00

0.00

4.00

1.00

8.00

2.00

−44 µm (%)

6.00

0.00

20.50

7.50

35.00

15.00

Table 4 Data from process simulation

Calibration

Scenario 1

Scenario 2

Scenario 3

d50 (µm)

91.1

117.2

109.7

100.1

Total yield (g/L)

53.28

48.66

49.37

50.90

Production (t/h)

96.9

89.3

90.48

93.0

Fig. 6 Result of precipitation product PSD scenarios

The result for precipitation product PSD, d50, yield and production are compared with calibration (Table 4, Fig. 6). In scenario 1, in the presence of coarser seeds, the precipitation product achieves better quality in terms of particle distribution, while the crystallizer chain does not have a good alumina production and yield. Conversely, in scenario 3, in the presence of the finest seed, the precipitation product has smaller particle size, but better performance for alumina production and yield.

Conclusions Modelling and simulating crystallizer chains can be important tools for decision making, especially when dealing with economic indicators such as productivity and production. In the presented case, the process simulation is helping CBA to choose the optimized hydrate classification settings on a daily basis.

There is opportunity to improve the simulation implemented of the CBA precipitation circuit by adding a breakage model inside the population balance and a closed circuit to hydrate classification to seed and product separation. Dynamic simulation is a future step in this development work.

References 1. Stamatiou, E., Chinloy, D.R., Çelikel, B., Kayaci, M. and Savkilioglu, E., “Hatch – ETI Aluminyum Precipitation Modeling” Light Metals (2013), 143–146. 2. Franco, T. and Seno, R., “Votorantim Metais – CBA Alumina Refinery Precipitation Modeling” Light Metals (2014), 33–27. 3. Rosenberg, S. P. and Healy, S. J., “A Thermodynamic Model for gibbsite Solubility in Bayer Liquors” Alumina Quality Workshop (1996). 4. White, E.T., and Bateman, S.H., “Effect of caustic concentration on the growth rate of Al(OH)3 Particles” Light Metals (1988), 157–162. 5. Lewis, A., Seckler, M., Kramer H., Rosmalen G.V., “Industrial Crystallization: Fundamentals and Applications” (2015).

Quantifying the Effect of Seeds on Gibbsite Crystallization … 6. Livk, I. and Ilievski, D., “A macroscopic agglomeration kernel model for gibbsite precipitation in turbulent and laminar flows”, Chemical Engineering Science 62 (2007), 3787–3797. 7. Misra, C. and White, E.T., “Kinetic of Crystaliization of Aluminum Trihydroxide from Seeded Caustic Aluminate Solutions” Chemical Engineering Progress Symposium 67 (1971), 53–65.

53 8. Misra, C., “The Precipitation of Bayer Aluminum Trihydroxide” PhD thesis at the University of Queensland (1970). 9. Randolph, A. D. and Larson, M. A., “Theory of Particulate Processes” 2nd ed., Academic Press, NY, (1988).

Experimental Study on Flow Field Characteristics in Seed Precipitation Tank and Influence on Physical Properties of Al(OH)3 Products Xiangyu Zou, Yan Liu, Xiaolong Li, and Ting’an Zhang

Abstract

Compared with the traditional air-mixing seed precipitation tank, the mechanical stirring seed precipitation tank has the characteristics of low energy consumption, less knot at the bottom of the tank, and uniform slurry mixing. In this paper, a new type of HSG/HQG combination impeller is used to study the liquid–solid two-phase mixing system in the mechanical stirring seed precipitation tank. The combination of PIV software technology and experimental tank test is used to study the internal flow of the stirred tank. The properties of the field and various types of agitator are tested, and the physical properties of the seed decomposition products are tested under different impeller types and speeds. The results show that under the same physical parameters, using new HQG/HSG impeller structure, the crystal morphology of the seed products is better, the average particle size is more uniform, and the wear index and specific surface area are improved. Keywords











New impeller structure PIV Seed decomposition product Crystal morphology Particle size distribution Wear index Specific surface area

seed crystal, decomposition time, agitation and impurities [1–4]. Stirring plays a role in keeping the seed crystals in suspension during the decomposition of the seed crystals, preventing the bottom material from accumulating and causing crusting [5, 6]; on the other hand, the seed crystals are in full contact with the solution, promoting the uniform mixing of the liquid and solid phases, and strengthening the transmission. The quality process accelerates the decomposition of the sodium aluminate solution and promotes the uniform growth of the gibbsite crystals [7, 8]. In recent years, with the introduction of flow field velocity measurement technology, especially the development of technology, the research on flow field has become more and more in-depth. The solid–liquid two-phase flow field was measured by PIV technology, and the dissipation rate of each region, as well as the impeller stirring zone and the blade flow zone were studied [9–12]. However, at present, there is very few research on the flow field and corresponding products of the liquid solid system in the seed crystal decomposition tank in the decomposition process of gibbsite seed crystal produced by Bayer process. In this paper, the vector diagram of the impeller structure type and the impeller speed flow field is discussed by PIV technology, and the related physical property analysis of the seed crystal decomposition product is carried out under the corresponding conditions.

Introduction

Experimental

Factors affecting the decomposition of the seed crystal are the decomposition of semen caustic ratio, decomposition of semen alumina concentration, decomposition temperature,

In the present study, the viscosity of the sodium aluminate system prepared by the wet experiment was 2 cp, and the solution density was about 1.33 g/ml, which was similar to the density and viscosity of water. Therefore, the system used in the physical simulation of PIV was water. The volume of the reactor in the wet experiment is small. If the water model with the same volume is used in the physical simulation of PIV, it is not conducive to shooting due to the shooting conditions. Therefore, the water model experiment

X. Zou
Y. Liu (&)
X. Li
T. Zhang Key Laboratory of Ecological Metallurgy of Multi-Metal Intergrown Ores of Ministry of Education, Special Metallurgy and Process Engineering Institute, Northeastern University, 110819 Shenyang, People’s Republic of China e-mail: [email protected]

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_8

54

Experimental Study on Flow Field Characteristics …

uses a larger volume of water model plexiglass reaction. Although the conditions of PIV physical simulation are slightly different from those in the wet experiment, it is possible to provide a general trend of the reaction flow field, which can still be used as a theoretical basis. As shown in Fig. 1, the flow field characteristics of HSG/HQG impeller, improved Intermig suspension impeller and CBY propulsion propeller at the same stirring line speed were investigated by PIV physical simulation. Then, three different kinds of impeller structures were used to prepare gibbsite samples by chemical precipitation method under the same impeller speed and chemical conditions respectively. According to the SEM morphology, particle size and specific surface area, the samples were selected to prepare hydrogen. The alumina impeller provides a theoretical basis for industrial production.

Results and Discussion Effect of Flow Field Distribution Under Different Impeller Structures As shown in Fig. 2a, for the HSG/HQG pad flow field diagram, the absolute velocity vector at the bottom of the reactor is the largest. When the material passes into the bottom of the reactor, it can be quickly mixed, which is beneficial to the formation of crystal nuclei and crystals. Growth reaches a state of mutual restraint. The absolute velocity vector in the middle and upper parts of the reactor is large, and the shearing force of the fluid is large, which will enhance the collision between the particles. The absolute

Fig. 1 Impeller structures

55

velocity vector distribution of the reactor is relatively uniform which is beneficial to the formation of gibbsite crystals with good particle size and uniformity of morphology. As shown in Fig. 2b, in order to improve the flow pattern of the Intermig impeller, the overall velocity vector of the reactor is larger and more evenly distributed. When the material passes into the bottom of the reactor, the mixing speed is faster, which is more favorable to the nucleus. Formation and crystal growth reach a mutually constrained steady state. The absolute velocity vector distribution of the reactor is relatively uniform, which is beneficial to the formation of gibbsite crystals with good particle size and uniformity of morphology. As shown in Fig. 2c, for the CBY propulsion propeller flow field diagram, the absolute velocity vector at the bottom of the reactor is large. When the material passes into the bottom of the reactor, the mixing speed is faster and the shearing force of the fluid is the largest. It will enhance the collision between particles, which is beneficial to the collision of large particles to break the secondary crystal and form small particles with uniform size. The upper middle velocity vector of the reactor is the smallest, which is not conducive to the formation of a crystal nucleus and the growth of the crystal to a mutually constrained stable state.

Effect of Flow Field Distribution Under Different Impeller Speeds Since the HSG/HQG impeller is better than the other two impellers at the same impeller speed, the impellers used below are all HSG/HQG.

56

X. Zou et al.

Fig. 2 Flow field distribution diagram of different impeller structures (speed: 300 r/min)

HSG/HQG When the impeller speed is 100 r/min, the absolute velocity vector at the bottom of the reactor is larger, which is beneficial to the collision of large particles with the secondary crystallization, but the middle and upper velocity vectors are the smallest, which is not conducive to the agglomeration of gibbsite grains and two. Secondary nucleation, as shown in Fig. 3a. When the impeller speed is 200 r/min, the overall velocity vector of the reactor is larger and the distribution is more uniform, which is more favorable for the formation of the crystal nucleus and the growth of the crystal to reach a mutually constrained stable state, as shown in Fig. 3b. When the impeller speed is increased to 300 r/min, the overall absolute velocity vector of the reactor is the largest and uniform, and the shearing force of the fluid is the largest, which will enhance the collision between particles, which is beneficial to the formation of hydroxide with good particle size and uniformity of morphology. The aluminum crystal is shown in Fig. 3c.

SEM Analysis of Products Under Different Impeller Structures The gibbsite was prepared by HSG/HQG impeller, improved Intermig impeller and CBY propelling propeller under the same seeding time and temperature and impeller speed respectively. The prepared samples were observed by SEM at 10 lm. As shown in Fig. 4a, when a sample is prepared using HSG/HQG impeller, the surface of the gibbsite seed crystal

Improved Intermig

CBY

becomes rough and grows into fine crystals protruding outward, and the crystals collide with each other and the fluid shears, fine crystals. The detached mother crystal falls into the solution and becomes a new crystal nucleus, which is favorable for nucleation of the surface of the seed crystal to cause crystal growth. A large number of fine crystal grains are agglomerated on the surface of the seed crystal, thereby obtaining an gibbsite product having high strength and coarse particle size. At the same time, when the gibbsite crystal is prepared by HSG/HQG impeller, the crystal structure of the seed product is relatively dense, the crystal structure is relatively perfect, and the intergranular void is relatively small. As shown in Fig. 4b, when a sample was prepared using an improved Intermig impeller, the gibbsite particles formed a plurality of agglomerated crystals of similar size and shape. Since the sheet is grown perpendicular to the spherical surface during the growth and crystallization of gibbsite, the crystal growth is not complete and continues to grow. This is because the formation of crystal nuclei of gibbsite crystals does not form a mutually restrictive balance with the growth of crystals, resulting in the formation rate of crystal nuclei much higher than the growth rate of crystals, and the growth of crystals is too slow, which is not conducive to large particles. Collision and crushing secondary nucleation. As shown in Fig. 4c, when a sample was prepared using a CBY propelling propeller, the gibbsite particles formed a plurality of agglomerated crystals of similar size and shape. Since the sheet is grown perpendicular to the spherical surface during the growth and crystallization of gibbsite, the

Fig. 3 Flow field distribution diagram of different impeller speeds (structure: HSG/HQG)

100r/min

200r/min

300r/min

Experimental Study on Flow Field Characteristics …

57

Fig. 4 SEM images of products under different impeller structures (speed: 300 r/min)

HSG/HQG crystal growth is not complete and continues to grow. This is because the mixing effect of the material is not good when it is introduced into the bottom of the reactor. The formation of crystal nucleus of gibbsite crystal does not form a mutually restrictive balance with the growth of crystal, resulting in the formation rate of crystal nucleus much higher than that of crystal. The growth rate and the growth of the crystal are too slow, which is not conducive to the collision of large particles to break the secondary nucleation, so the crystallinity of the product is not good in the same seeding time.

SEM Analysis of Products Under Different Impeller Speeds Due to the improved SEM morphology of the prepared Intermig and CBY impellers for HSG/HQG impellers at the same seed time and temperature and impeller speed, the impellers used below are all HSG/HQG impellers. When the impeller speed is 100 r/min, the gibbsite crystal forms only a small amount of agglomeration on the surface. This is because the impeller speed is too low, the rate of formation of the nucleus is much higher than the growth rate of the crystal, and the growth of the crystal is too slow. As shown in Fig. 5a. When the impeller speed is 200 r/min, the gibbsite crystal has formed a large amount of agglomeration on the surface, but the crystal growth is not complete enough and continues to grow, as shown in Fig. 5b. When the impeller speed is increased to 300 r/min, the crystal structure of the gibbsite crystal from the initial sheet shape to the structurally intact cylindrical gibbsite is relatively dense, the crystal structure is relatively perfect, and the intergranular void is relatively small, such as Fig. 5c.

Improved Intermig

CBY

Particle size measurement method: Particle size is measured by laser particle size measurement [13]. In the experiment, the particle size of the product gibbsite was expressed by 0.8 T) intensities [2]. All materials show magnetic properties at some intensity in the presence of a magnetic field due to the magnetic dipole moment of the electron (li). Restricting the present discussion to the three most common categories of materials, they can be classified as: paramagnetic, diamagnetic and ferromagnetic [3]. For paramagnetic materials, the atomic dipole moments are permanent and randomly oriented. In the presence of an external magnetic field, the dipoles align in the same direction as the field, when the magnetic field is removed, the randomness is resumed. Diamagnetic materials get magnetic dipole moment when subjected to an external magnetic field; however, the dipoles align in the opposite direction. On a macroscopic scale, strong paramagnetic materials are attracted to a magnet while diamagnetic materials are repelled by it. Ferromagnetic materials have permanent magnetic dipole moments and the stronger interaction between adjacent atomic dipole moments results in their alignment even when the external magnetic field is removed, so it remains magnetized [4].

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_14

98

Bayer Process Towards the Circular Economy—Metal Recovery … Table 1 Different forces and particle size dependence

99

Force

Equation

Particle size dependence

Magnetic

Fm ¼ lk VBrB

/ b3

Gravitational

Fg ¼ qVg

/ b3

Drag

Fd ¼ 6pgbvp

/b

0

The magnetic field generated by a material when it is magnetized (M) in the presence of an external magnetic field (H) contributes to the overall magnetic field (B), as described in Eq. (1) [5]. B ¼ l0 ðH þ M Þ

ð1Þ

where l0 is the permeability of free space ð4p  107 T m/AÞ. While H is associated with the magnetic field generating element, an electric current for example, B is related to the effects of initial magnetic field implementation. Therefore, the implementation of this physical principle resulted in the development of magnetic separators combining a strong magnetic field and an internal ferromagnetic matrix able to generate a very high local magnetic field, as well as a high magnetic gradient ðrBÞ [1]. Different mechanisms are associated to M for each category of materials. For paramagnetic and diamagnetic materials, M is directly proportional to the applied magnetic field where the proportionality constant is the volumetric magnetic susceptibility of the material (ҡ).1 For diamagnetic material ҡ is negative while it is positive for paramagnetic material [5]. There is no simple correlation that defines ҡ for ferromagnetic materials, but in terms of magnitude, the magnetic susceptibility of ferromagnetic materials is 104 higher than paramagnetic ones [6]. It is important to have in mind that, regardless of the material, M is limited to a saturation value, characteristic of each material. Looking at only to the magnetic susceptibility, according to Chen and Xiong [6], strongly magnetic minerals such as magnetite can be separated in a magnetic field of low intensity and gradient modules smaller than 0.2 T and 5 T/m, respectively. While paramagnetic minerals such as hematite can be separated only in a magnetic field of high intensity and gradient, i.e. higher than 0.6 T and 50 T/m, respectively. Magnetic separation is used for sorting materials based on its magnetic properties. However, magnetic properties only are not enough to guarantee an efficient process, once that magnetic separation consists of a physical separation between discrete particles resulting from a balance of competing forces, which can be: magnetic force, gravitational force, drag, force of attraction/repulsion between particles,

1

Magnetic susceptibility can be also reported as specific magnetic susceptibility (v) where v = ҡ/q where q is the density of the material.

among others [1]. A magnetic force ðFm Þ, as per Eq. (2), will act on a particle if it is in a non-constant magnetic field B, so rB 6¼ 0 [5]. Fm ¼

k VBrB l0

ð2Þ

where V is the particle volume. Particle size plays an important role in magnetic separation processes. The particle’s size defines the route of magnetic separation (dry or wet) and significantly affects the balance of forces (magnetic, gravitational, rotational, drag, etc.) acting on the material. Table 1 shows forces that could act on a particle during wet magnetic separation process. Note that the particle size (diameter b) is fundamental for separation efficiency, for small values of b, the third potency in b results in a sharply decrease in the magnetic force, while it does not affect the drag force with the same power. According to Svoboda and colleagues [1], considering two particles, where one is 10 times bigger than other, but has magnetic susceptibility 1000 smaller, both will suffer the same magnetic force [1]. Therefore, a particle will be segregated and will report to the “magnetic concentrate” if the magnetic force exceeds the others. The magnetic property of a material is one input in a complex force dispute. Today, applying magnetic separation principles to direct metals separation from tailings can be an alternative for increased sustainability in mining activities, contributing to reduction of disposal areas and tailing dam requirements. By definition, mining activities are excluded from the classical circular economy (CE) restorative loops (recycle, remanufacture, repair, reuse) since it is a primary industry. However, mining waste reprocessing reduces the need of new mines opening, providing environmental benefits and economical value, keeping resources in use for longer, a fundamental concept of CE [7]. The Bayer process applied to alumina refining from bauxite generates bauxite residue (BR) in a proportion ranging from 0.8 to 1.5 (alumina:BR). Aluminum is already one of the most global recycled metals, however, transforming the BR into a secondary source of raw materials is a promising environmental and economic solution, expanding the CE principles to Bayer process. Regardless the bauxite type (i.e. diasporic, gibbsitic or boehmitic), the major constituent of bauxite residue is iron (6.8–71.9% Fe2O3) [8]. The iron usually is present in two main phases, hematite (a-Fe2O3) and goethite (a-FeOOH), however

100

other mineral phases can be presented depending on bauxite origin. Many techniques have been investigated regarding iron recovery from BR, where the higher number of patents are related to direct magnetic separation, pyrometallurgical recovery and hydrometallurgical recovery [9]. The direct magnetic separation is a straightforward method, so it is a good approach for an initial iron removal option. In 2017, Brazil produced 11 million tons of alumina and around 8.8–16.5 million tons of RB with a potential to recover around 0.3–0.6 million tons/year of iron, when considering the average Fe value in Brazilian BR of 35% and an average efficiency rate of 10%. In the present work, a Brazilian BR sample was mineralogically characterized and tested for direct wet magnetic iron separation when submitted to a wet high intensity magnetic separator under different intensities. The aim of this study is to generate the bases for the development of an effective BR iron magnetic separation method contributing to the expansion of CE concepts in the Bayer process and a greener mining activity.

Materials and Methods

P. de Freitas Marques Araújo et al.

samples were prepared according to the powder method with backloading preparation. Chemical composition was determined by X-ray fluorescence (XRF). The XRF was carried out in an Epsilon 3XLE/PANalytical spectrometer equipped with Rh ceramic X-ray tube operating at maximum power level of 15 W. The powder samples were pressed. The samples (0.5 g) were calcinated at 1000 °C for 1 h in an oven for loss on ignition analysis (LOI). Particle size distribution (PSD) was determined by laser diffractometry in a Malvern Mastersizer 3000 using water as dispersant.

BR Wet Sieving The BR mass granulometric distribution was determined by wet sieving. Bauxite residue was fed to a sieve shaker with a measuring range of −38 to +150 lm into six fractions at Tyler screen equivalents: +100, +150, +200, +270, +400 and −400 mesh (#). Retained mass on each sieve and the residual phase were dried, weighed, and mineralogically and chemically characterized as described above.

BR Sample Preparation The BR sample was collected in 50 L plastic containers and sent to SENAI Innovation Institute for Mineral Technologies, in Brazil, for mineralogical, chemical and granulometric characterization and magnetic separation studies. The BR passed through a press filter at the alumina refinery and residual moisture was dried at room temperature. The dried BR was passed through a 1 mm vibrating sieve. The oversize lumps were fed in a Denver roll mill for a smooth de-agglomeration. All material was prepared using a Chevron stacker for homogenization and subdividing into representative aliquots.

Mineralogical, Chemical and Granulometric Characterization The mineralogy of unprocessed BR and processed BR fractions were determined by X-ray diffraction (XRD). The XRD was carried out in a divergent beam diffractometer Empyrean/PANalytical (XRD) with h–h goniometer and a cobalt X-ray tube (Ka1 = 1.78901 Å) with a fine long focus of 1800 W, a Fe kb filter, and a PIXel3D 1  1 area detector, operating in a linear scanning mode (1D), with active length of 3.3473° 2h (255 active channels). The

BR Wet Magnetic Separation The magnetic separator used in the test was a Wet High Intensity Magnetic Separator (WHIMS), type BoxMag Rapid Magnetic Separator LTD. The Boxmag Rapid Magnetic Separator is a lab scale equipment with variable magnetic field intensity designed for wet magnetic separation tests. Energised coils generate the magnetic field, achieving values up to 1.2 T (12.000 Gauss). A magnetic matrix (removable grid) of 2.5 mm openings, located between the poles, holds the particles attracted by the magnetic forces while the non-magnetic fractions flows through the equipment outlet. A BR slurry (30% solids) was directly fed into the feed hopper of the equipment. Increasing magnetic field intensity 0.2 T, 0.5 T, 0.75 T 1.00 T and 1.2 T (2.000, 5.000, 7.500, 10.000, 12.000 Gauss, respectively) was applied in batches. After each batch, both magnetic and the non-magnetic fractions were collected, and the non-magnetic fraction was fed to a new run in the next higher magnetic field. All the recovered magnetic fractions and the last non-magnetic products were dewatered, weighed and analysed for the determination of particle size distribution by laser diffractometry, mineralogical and chemical composition, as previously described.

Bayer Process Towards the Circular Economy—Metal Recovery …

101

Results and Discussion BR Sample Chemical and Mineralogical Characterization The initial BR sample’s chemical composition is given in Table 2, as well as, the values obtained by other researches in the past for the BR from Alunorte Refinery [10, 11]. The major elements were iron (Fe), aluminium (Al), silicon (Si), sodium (Na) and titanium (Ti). Although, the most elements were common in the referred studies, major differences were observed in the Fe, Al, Si and Na, probably due to bauxite quality and/or process condition at sampling time [10, 11]. Figure 1 presents the XRD pattern with the identified mineralogical peaks. The predominant mineralogical phases present in the BR were: hematite (Hem), aluminous goethite (Al-Gth), gibbsite (Gbs), sodalite (Sdl), anatase (Ant), quartz (Qz) and calcite (Cal).

BR Wet Sieving Wet sieving was carried out for assessing particle size fractions against the weighted contribution to the overall mass and chemical/mineralogical contents for each size range. Table 3 presents the retained and cumulative mass on each sieve, as well as, the chemical analysis. More than 80% of BR mass passed through the 38 µm sieve, confirming the fine BR granulometry (Table 3). Considering 100 lm as the reference particle size that limits the magnetic separation efficiency [9], only 8.34% w/w of the BR presented as particles greater than 100 lm (+150#). The iron contents were higher for the coarser sizes (Table 3), being mainly the hematite mineral (Fig. 2), although hematite was observed in all granulometric ranges (Fig. 2). The weighted average of the iron concentration was 60.2% for the +150#. If we Table 2 Chemical composition of evaluated BR sample

a

Fig. 1 XRD pattern for the BR sample. Sdl sodalite, Gbs gibbsite, Al-Gth aluminous goethite, Ant anatase, Hem hematite, Qz quartz, Cal calcite

consider that only particles bigger than 100 lm would effectively respond to a magnetic separation process, it is expected that a small mass of the BR would report as magnetic product after the magnetic separation tests. Looking at the elements Al, Na and Si, their concentrations increased sharply in the finest fraction (−400#), mainly associated to the minerals sodalite (Fig. 2). Al concentration between the ranges +270# and +400# was associated to the mineral Gibbsite (Al(OH)3) (Fig. 2). Although titanium (Ti) and zirconium (Zr) were not our main target metals, a higher concentration of these metals was observed between 74–106 µm and 53 µm size particles, respectively (Table 3). The other measured elements did not show a pronounced change in concentration associated with size distribution.

BR Magnetic Separation The mass balance after the magnetic separation is shown in Table 4. The overall mass balance indicated that 7.8% w/w of the total feed was recovered as the magnetic

BR (this work)

Snars and Gilkes [10]

Braga et al. [11]

%Fe2O3

40.80

45.6

33.0

%Al2O3

17.32

15.1

21.5

%SiO2

14.01

15.6

19.1

%Na2O

9.68

7.5

9.4

%TiO2

5.93

4.29

4.7

%CaO

1.43

1.16

–

%ZrO2

0.92

–

–

%V2O5

0.16

–

–

%SO3

0.14

0.21

–

%MnO

0.12

0.01

–

%P2O5

0.11

0.05

–

%LOIa

9.12

9.3

10.8

LOI loss on ignition

102

P. de Freitas Marques Araújo et al.

Table 3 Fraction by size, retained mass and chemical analysis Sieves and openings

a

Tyler

+100#

+150#

+200#

+270#

+400#

-400#

Aperture (lm)

−600/+150

−150/+106

−106/+74

−74/+53

−53/+38

−38

Retained (% weight)

–

5.30

3.04

3.89

3.81

2.54

81.42

Cumulative retained (%)

–

5.30

8.34

12.23

16.04

18.58

100.00

Feed

+100#

+150#

+200#

+270#

+400#

-400#

%Fe2O3

40.80

62.80

55.65

54.21

51.95

50.27

35.33

%Al2O3

17.32

8.00

7.82

9.04

10.69

12.34

21.46

%SiO2

14.01

14.86

11.15

8.97

9.60

10.09

16.60

%Na2O

9.68

2.99

3.16

3.54

3.90

4.55

9.71

%TiO2

5.93

2.69

13.41

13.66

10.46

8.06

4.77

%CaO

1.43

1.27

1.26

1.32

1.57

2.07

1.49

%ZrO2

0.92

0.18

0.81

2.95

4.89

4.29

0.45

%V2O5

0.16

0.19

0.26

0.25

0.22

0.19

0.13

%SO3

0.14

–

–

–

–

–

0.17

%MnO

0.12

–

0.53

0.48

0.31

0.20

–

%P2O5

0.11

0.17

0.37

0.26

0.28

0.19

–

%LOIa

9.12

6.55

5.24

4.99

5.81

7.44

9.56

LOI loss on ignition

(Mag) product. It is interesting to note that the total mass reporting to the Mag product was close to the retained cumulative mass at +150# (8.34% w/w) from the sieving assessment. Figure 3 presents the particle size distribution (PSD) of the feed, Mag and non-magnetic (Non Mag) products. The PSD of the feed sample presented two different population in the histogram, a “coarser family” and a predominant “finer family”, similar to that obtained by wet sieving. All Mag (0.5–1.2 T) recovered products were dominated by coarse particles (D90 98–216 µm) in contrast to the Non Mag product that showed 90% less than 34.1 µm. As expected, the coarser particles were attracted by the magnetic field, confirming that bigger particles have a better response to magnetic force. The very fine particles (around 1 lm) were detected in all streams, but only representing 10% of total BR particles. One hypothesis it that these very small particles were carried by the larger ones or consequence of material desegregation by sonication during the PSD analysis. Table 5 presents the chemical contents of the feed, Mag and Non Mag recovered products. Figure 4 shows the concentration variability of the major feed components: Fe, Al and Si. The Fe in the Mag product had an incremental concentration around 20% compared to the feed material. The overall magnetic product concentration was 59.6% Fe2O3 (weighted average) while the feed concentration was 40.08%. It is possible to observe that the feed and the Non

Fig. 2 XRD of BR size fractions obtained by wet sieving compared to feed BR. Sdl sodalite, Gbs gibbsite, Al-Gth aluminous goethite, Ant anatase, Hem hematite, Qz quartz, Cal calcite

Mag product had the same Fe range of concentrations; the consequence of the mass removed as Mag product (7.8% w/w) was not enough to have a pronounced impact on the bulk concentration of the Non Mag Material (92.2% w/w).

Bayer Process Towards the Circular Economy—Metal Recovery … Table 4 Mass balance of magnetic separation tests

Feed (g)

103

0.2 T

0.5 T

0.75 T

1.0 T

1.2 T

Overall balance

4699

4699

4621

4621

4443

4699

35

44

177

113

369

4664

4621

4443

4330

4330

0.7

0.9

3.8

2.5

7.8

Magnetic (g)

0

Non-magnetic (g)

4699

Mag/feed (%)

0

5

Frequency (%)

Fig. 3 Particle size distribution of feed material, non-magnetic (Non Mag) and magnetic (Mag— 0.5, 0.75, 1.0 and 1.2 T) fractions

4 3 2 1 0 0.01 5

Frequency (%)

4 3

0.1

1 10 Particle size (μm)

100

1 10 Particle size (μm)

100

Mag / 0.5 T D50: 35.6 μm D90: 167 μm

1000

Mag / 1.0 T D50: 31.4 μm D90: 171 μm

100

1000

1 10 Particle size (μm)

100

1000

1

100

1000

1

4 3

0.1

1000

0.01 5

Mag / 0.75 T D50: 20.9 μm D90: 98.0 μm

4 3

2

2

1

1

0 0.01

0.1

1

10

100

0.1

Mag / 1.2 T D50: 16.99 μm D90: 216 μm

0 0.01

1000

0.1

Particle size (μm)

Table 5 Chemical composition after magnetic separation

Feed

10

Particle size (μm)

Mag

Non mag

0.2 T

0.5 T

0.75 T

1.0 T

1.2 T

%Fe2O3

40.80

–

64.18

57.67

60.51

57.56

%Al2O3

17.32

–

8.89

10.89

9.83

10.88

19.03

%SiO2

14.01

–

6.90

8.42

7.78

8.99

15.40

%Na2O

9.68

–

3.52

4.51

4.02

4.23

8.35

%TiO2

5.93

–

9.23

10.87

10.09

9.57

5.34

%CaO

1.43

–

0.66

0.81

0.71

0.85

1.51

%ZrO2

0.92

–

0.52

0.57

0.63

0.62

0.97

%V2O5

0.16

–

0.25

0.24

0.24

0.23

0.15

%SO3

0.14

–

–

–

–

–

0.15

39.59

%MnO

0.12

–

0.36

0.42

0.39

0.37

–

%P2O5

0.11

–

–

–

–

–

–

a

9.12

–

5.11

5.24

5.44

6.37

9.19

%LOI a

1 10 Particle size (μm)

2

0 0.01 5

Frequency (%)

Non Mag D50: 5.95 μm D90: 34.1 μm

Feed D50: 9.99 μm D90: 43.7 μm

LOI loss on ignition

104

(a)

(b)

100

100

75 50 40.80

Al 2O3 (%)

Fe2O3 (%)

Fig. 4 a Iron (Fe2O3), b Aluminum (Al2O3) and c Silicon (SiO2) concentration in the feed material (feed), non-magnetic (non mag) and magnetic (mag at 0.5, 0.75, 1.0 and 1.2 T) fractions

P. de Freitas Marques Araújo et al.

39.59

25 0

Feed Non Mag

0.5

0.75 1.0 1.2 T Magnetic

75 50 25 0

17.32

19.03

Feed Non Mag

0.5

0.75 1.0 1.2 T Magnetic

(c) SiO 2 (%)

100 75 50 25 0

Hematite was also observed in the Non Mag product, probably due to small sizes not allowing for magnetic separation (Fig. 5). Al and Si were concentrated in the Non Mag product, mainly associated with sodalite and gibbsite minerals (Fig. 5). In general tailings have at least two aggravating factors: fine particle size and a complex mixture of different minerals including the phases present in the parent ore and the minerals formed during industrial processing. Several researchers have reported that the direct magnetic separation is not

Fig. 5 XRD pattern for the BR fractions after magnetic separation. Sdl: sodalite; Gbs: gibbsite; Al-Gth: aluminous goethite; Ant: anatase; Hem: hematite; Qz: quartz

14.01

15.40

Feed Non Mag

0.5

0.75 1.0 1.2 T Magnetic

efficient for fine particles (100 lm) corresponded to 8.34% in weight of the

105

feed, with 81.24% passing through 400# (38 lm) sieve. The chemical characterization of each size range (6 sieves) show that the Fe2O3 contents increased from the fine to the coarser fractions, achieving 62.8% in the fraction retained at +100# (+150 lm). After six magnetic separation stages (0.2, 0.5, 0.75, 1.0 and 1.2 T), 7.8% of the feed reported to the magnetic product. The overall iron recovery was 11.5% and the overall magnetic product concentration was 59.6% Fe2O3 (weighted average). Comparing the results to previous works [12, 14], the iron recovery and concentration achieved in the current work were expected considering the BR characteristics. The effect of particle size was dominant in determining the process efficiency for the evaluated material. The iron recovery from fines of bauxite residue by direct magnetic separation is still a challenge. At least three main areas can be explored to overcome the fine particle effect: equipment development, hematite phase transformation and selective agglomeration. For equipment development, possible studies include new internal matrices, usage of permanent magnets, pulsatile flow (among others), where the main goal is to improve material recovery, reduce energy consumption and obstruction issues [15, 16]. The hematite phase transformation requires hematite to be reduced to a ferromagnetic material, such as magnetite [17, 18]. Other examples of developments are related strictly to particle size, carrying out selective agglomeration to get a cluster of small particles to behave as one of bigger size. For instance, Huang et al. [19] tested bauxite residue and humic flocculant synthesized from brown coal for selective iron agglomeration. In addition, sodium silicate was used as dispersant for the other mineralogical phases [19]. The current work established the basis of direct magnetic wet Fe separation from a Brazilian BR, and future works will focus on pre-processing methods to increase magnetic separation efficiency. Acknowledgements The authors are grateful for the financial support of this study by Hydro Alunorte S/A and all technical and logistical support from Hydro’s R&D team.

References 1. Svoboda J, Fujita T (2003) Recent developments in magnetic methods of material separation. Minerals Engineering (16): 785– 792. 2. Tripathy SK, Singh V, Suresh N (2015) Prediction of separation performance of dry high intensity magnetic separator for processing of para-magnetic minerals. J. Inst. Eng. India Series D 96: 131–142. https://doi.org/10.1007/s40033-015-0064-x.

106 3. Malik H K, Singh A K (2010) Engineering Physics. Tata Mc Graw Hill Education Private Limited, New Delhi. 4. Halliday D, Resnik R, Krane K (ed) (1996) Física 3. LTC – Livros Técnicos e Científicos Editora S.A., Rio de Janeiro. 5. Stradling AW (1993) The physis of open-gradient dry magnetic separation. International Journal of Mineral Processing (39): 1–18. 6. Chen L, Xiong D (2015) Magnetic techniques for mineral processing. In: Tarleton, S (ed) Progress in Filtration and Separation, Loughborough, p 287–324. 7. Lèbre É;Corder G; Golev A (2017) The Role of the Mining Industry in a Circular Economy: A Framework for Resource Management at the Mine Site Level. J. Ind. Ecol.. 21. https://doi. org/10.1111/jiec.12596. 8. Gräfe M, Power G, Klauber C (2011) Bauxite residue issues: III. Alkalinity and associated chemistry. Hydrometallurgy (108): 60– 79. 9. Liu Y, Naidu R (2014) Hidden values in bauxite residue (red mud): recovery of metals. Waste Management (34): 2662–2673. 10. Snars K, Gilkes RJ (2009) Evaluation of bauxite residues (red muds) of different origins for environmental applications. Applied Clay Science (46):13–20. 11. Braga P et al. (2018) Use of bauxite residue (red mud) as CO2 absorbent. Paper presented at 5th International Seminar on Tailings Management, Santiago, Chile, 11–13 July 2018.

P. de Freitas Marques Araújo et al. 12. Jamieson E, Jone A, Cooling D, Stockton N (2006) Magnetic separation of red sand to produce value. Minerals Engineering (19): 1603–1605. 13. Bao L, Nguyen AV (2010) Developing a physically consistent model for gibbsite leaching kinetics. Hydrometallurgy (104): 86– 98. 14. Li Y, Wang J, Wang X, Wang B, Luan Z (2011) Feasibility study of iron mineral separation from red mud by high gradient superconducting magnetic separation. Physica C (471): 91–96. 15. Zeng S; Zeng W; Ren L; An D; Huiyue L (2015) Development of a high gradient magnetic separator (HGPMS). Minerals Engineering (71) 21–26. 16. Chen L, Qian Z, Wen S, Huang S (2013) High-gradient magnetic separation of ultrafine particles with rod matrix. Mineral Processing & Extractive Metall. Rev 34: 340–347. https://doi.org/10.1080/ 08827508.2012.695304. 17. Cardenia C, Balomenos E, Panias D (2018) Iron recovery from bauxite residue through reductive roasting and wet magnetic separation. Journal of Sustainable Metallurgy. (5): 9–19. 18. Li X, Wang Y, Zhou Q, Qi T, Liu G, Peng Z, Wang H (2018) Reaction behaviors of iron and hematite in sodium aluminate solution at elevated temperature. Hydrometallurgy (175): 257–265. 19. Huang Y, Han G, Liu J, Wang W (2016) A facile disposal of Bayer red mud based on selective flocculation desliming with organic humics. Journal of Hazardous Materials (301): 46–55.

Bayer Process Towards the Circular Economy —Soil Conditioners from Bauxite Residue Roseanne Barata Holanda, Patricia Magalhães Pereira Silva, Andre Luiz Vilaça do Carmo, Alice Ferreira Cardoso, Raphael Vieira da Costa, Caio César Amorim de Melo, Adriano Reis Lucheta, and Marcelo Montini

Abstract

Large-scale bauxite residue (BR) reuse is still a challenge for alumina producers worldwide. Agronomic applications for BR can be a sustainable and economically viable option for soil fertility improvement in countries where agriculture plays a crucial economic role, such as Brazil. This study reports a biological approach to partial BR alkalinity neutralization, allowing its safe application as a soil conditioner for fertility improvement in acidic tropical soils. Microcosm tests were established to assess the effect of incorporating local agro-industrial organic residues into the BR to generate acidity, while highly fertile undisturbed soil was added as a microbial inoculum. BR amendment with organic residues exhibited a fast pH neutralisation (from 10 to 6.5 at the second day of incubation). Results confirmed that the locally available organic residues and the soil added to BR improved its physical and chemical characteristics, allowing further research into its agronomic effects. Keywords





Bauxite residue Sustainability Green mining Zero waste




Soil amelioration




R. B. Holanda
P. M. P. Silva
A. L. V. do Carmo
A. F. Cardoso
R. V. da Costa
C. C. A. de Melo
A. R. Lucheta (&) SENAI Innovation Institute for Mineral Technology, Av. Com Brás de Águiar, 548, Bélem, PA 66035-405, Brazil e-mail: [email protected] M. Montini Hydro Alunorte S.A, Rodovia PA-481 km 12, Distrito de Murucupe, Barcarena, PA 68447-000, Brazil e-mail: [email protected]

Introduction The Bayer process used in the refining of alumina from bauxite ore generates a solid, highly alkaline saline-sodic by-product, referred as bauxite residue (BR), with a global estimated annual production of 150 million tons (Mt) and a total global inventory estimated at 4.6 billion tons to date [1]. The BR is currently disposed of in large purpose-built Bauxite Residue Disposal Areas (BRDA) and new technologies, such as dry disposal, have been applied to minimize land area use [1]. Adoption of technological innovations to reduce remaining sodium hydroxide (NaOH) and water content (press filter) are helping BRDA rehabilitation and facilitating BR utilization. The International Aluminium Institute (IAI) [2] established, at the Alumina Technology Roadmap, a goal to utilize 20% of BR by 2025, but currently, only 2–3% of BR produced annually is re-used [3]. Consequently, great effort has been directed at developing viable applications for the utilization of BR, aiming to transform it from a waste to a valuable product and a secondary source of raw materials, generating revenue, decreasing storage areas (and costs involved) in the process. Unfortunately, of all the BR utilization technologies developed until now, none has resulted in significant commercial scale application [3, 4]. Currently, the most promising areas for which BR has large scale potential utilization comprise construction, chemical, metallurgical, environmental and agronomic applications. Within those, agronomic applications represent a sustainable, environmentally beneficial and potentially economically viable approach [3, 4], particularly, when considering the high demand for fertilizers and soil conditioners in countries that are commodity exporters, such as Brazil. Agronomic applications of BR aims to address several soil issues such as acidity, low water holding capacity and phosphorus losses [4]. Incorporation of BR to degraded acidic sandy soil at 5% (m/v) significantly increased pH, improved soil texture and water holding capacity, and had

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_15

107

108

R. B. Holanda et al.

no significant detrimental effect on the tested plants and microorganisms [5]. Although, trials using raw BR as soil ameliorant have obtained positive results [5], remediation of BR prior to use may allow a more effective and safer application [6]. Rehabilitation strategies considered the organic and/or inorganic amendments to change the BR’s properties, and thus mitigating critical BR characteristics by decreasing pH to < 9, salinity, sodicity, electrical conductivity (EC) to < 4 mS cm−1 and exchangeable sodium percentage (ESP) [7–9]. Bioremediation strategies often aim to add beneficial properties to BR, transforming it into a soil-like material by improving particle aggregation and nutrient content (organic C, NH4+, NO3−, PO43− and K+). Microbial communities play a crucial role in bioremediation, and represent an important strategy for lowering BR reuse costs. Local microbial communities adapted to the conditions of the BR environment and able to metabolise a range of organic carbon substrates, including substrates containing a more recalcitrant carbon source such as cellulose and lignin-rich wastes from agro-industry (abundant in countries like Brazil) and available to nearby alumina plants, are an effective way of providing these microbial input. Complete microbial metabolization of organic substrates generates CO2, that under alkaline conditions reacts with hydroxide ion (OH−) generating bicarbonate (Eq. 1), that also will react with OH− producing carbonate (Eq. 2). Therefore, carbonation reactions consume two OH− for each CO2 generated. Moreover, incomplete microbial decomposition of organic material generates organic acids. Together, organic acids generation and carbonation are the potential mechanisms promoting pH acidification of BR amended with organic substrates and/or soil [4, 9]. OH þ CO2 ! HCO3 

ð1Þ

OH þ HCO3  ! CO3 2 þ H2 O

ð2Þ

Laboratory trials have shown that microbial fermentation of organic substrates dramatically reduce the BR’s pH from 11 to 7 after few days incubation [8, 10–12]. Considering that raw BR has a much less diverse microbial community and lower biomass compared to soil, bioaugmentation techniques (addition of a microbial inoculum) have been observed to promote more consistent and rapid BR bioremediation [10, 11]. This study investigated the effect of locally available agro-industrial organic residues and native fertile soil addition to the BR as carbon sources and microbial inoculum, respectively, by assessing changes in its physical and chemical properties. Microcosms tests containing different organic waste materials and soil were established in the laboratory to evaluate their effects on the rates of pH neutralisation and changes in mineralogical and chemical

composition of BR compared to untreated BR. Outcomes from this study will allow further development of a BR-based soil conditioner formulations for the improvement of fertility in acidic tropical soils.

Materials and Methods Microcosms Experiment The BR sample from an industrial alumina refining plant, located at Pará State, Northern Brazil, was collected in 50 L plastic containers direct after press-filter processing step, under non-sterile conditions, storage at room temperature and shipped to the SENAI Innovation Institute for Mineral Technologies (ISI-TM), in Belém, Brazil, where the study was conducted. Microcosm experiments were carried out to evaluate in situ pH neutralization of BR mixed with organic waste materials, used as carbon sources for microbial metabolization, and soil (microbial inoculum). Residues from a local Palm Oil processing plant: palm mesocarp fiber (PMF), empty (palm) fruit bunches (EFB), palm oil decanter cake (PODC); Palm Oil refinery: spent Fuller’s earth (SFE) from palm oil bleaching process; and spent seeds from Açaí (Euterpe oleracea) beverage processing facility (Fig. 1a) were selected for this study. Organic residues (except for PODC and SFE) were dried at 55 °C for 24 h and then ground in an industrial blender prior to use, to guarantee a uniform mixing with BR and soil. Fertile undisturbed soil collected from an area hosting native vegetation (classified as Tropical Lowland Ombrophilous Dense Forest), 400 km northwest of Belém, was added to the microcosm as a microbial inoculant. The microcosm’s setup was based on a modified version of those described by Santini and Peng [11]. It consisted of 5 treatments (one treatment for each organic residue) and 5 controls (3 negative and 2 positives) and were prepared in 150 mL polyethylene capped bottles (Fig. 1b). The treatments were performed in triplicate and are described in Table 1. All tests received 10 g of untreated BR and 100 mL of solution (H2O or nutrient medium). The water used was treated by reverse osmosis, pH adjusted to 10 with 2 M KOH and sterilized. The nutrient medium, sterilized prior to use, had the following composition: 0.15% (w/v) yeast extract and 0.12% (w/v) peptone, pH 10 (adjusted with 2 M KOH). The pH of organic residues and soil, measured in H2O (treated by reverse osmosis) at a ratio of 1:5, were: soil pH 4.4, PODC pH 4.7, SFE pH 3.6, PMF pH 6.5, EFB pH 6.9 and Açaí seeds pH 5.8. Treatments (T1–T5) consisted of 10 g BR, 15 g organic residue, 5 g soil and 100 mL H2O. To CN1 were added 10 g of BR and 100 mL of H2O. Both controls CN2 and CN3

Bayer Process Towards the Circular Economy—Soil Conditioners …

109

Fig. 1 a Organic residues used in the microcosm tests. PMF, EFB and Açaí seeds were dried and ground prior use. PODC and SFE were “in natura”. b Tests at time zero Table 1 Composition of controls and treatments used in the microcosm tests Identification

Microcosm composition BR

Controls

Treatments

Added carbon source

Medium

None

100 mL H2O

5 g soil

None

100 mL H2O

5 g soil

None

100 mL NM

10 g BR

5 g soil

1% sucrose

100 mL NM

10 g BR

5 g soil

2% sucrose

100 mL NM

a

CN1

10 g BR

CN2

10 g BR

CN3

10 g BR

CP1 CP2

Inoculum

T1

10 g BR

5 g soil

15 g PMF

100 mL H2O

T2

10 g BR

5 g soil

15 g PODCb

100 mL H2O

c

T3

10 g BR

5 g soil

15 g EFB

100 mL H2O

T4

10 g BR

5 g soil

15 g SFEd

100 mL H2O

T5

10 g BR

5 g soil

15 g AS

e

100 mL H2O

NM nutrient medium a Palm mesocarp fiber. bPalm oil decanter cake. cEmpty (palm) fruit bunches. dSpent fuller’s earth. eAçaí seeds

contained 10 g BR and 5 g soil, however 100 mL of H2O was added to CN2 and 100 mL of nutrient medium to CN3. Controls CP1 and CP2 also contained BR, soil and nutrient medium, however sucrose was added at 1% (w/v) and 2% (w/v), respectively. Tests were incubated at 30 °C in the dark without shaking.

Statistical Analysis

Physico-Chemical and Microbiological Analysis

Results

The pH of microcosm suspensions was measured until 28 days incubation using an Orion Star A211 pH meter (Thermo Scientific, Waltham, MA, USA) calibrated daily. Planktonic microbial cells were counted using a Neubauer chamber in an optical trinocular microscope (DM3000 400x, Leica, Wetzlar, Alemanha). Bauxite residue chemical and mineralogical compositions were determined by Energy Dispersive X-ray Fluorescence (EDXRF) spectrometry and X-ray Diffraction (XRD), respectively, as described by [13].

pH in the Microcosm Experiments

To assess the effect of organic residues and soil incorporation on microcosm tests final pH (on the 28th incubation day), one-way ANOVA was performed with Tukey’s Honestly Significant Difference (HSD) post hoc test.

Microcosm tests aimed to evaluate the efficacy of organic waste material in promoting BR’s pH partial alkalinity neutralisation. Treatments and controls showed distinct pH profile during the incubation time. Tests using organic residues (treatments T1–T5) were effective in promoting rapid pH neutralization and maintaining pH levels throughout the 28th days of experiment (although there were small

110 Table 2 Average pH values of microcosm tests after 28 days incubation

R. B. Holanda et al. Identification

pH

CN1

10.6 ± 0.1 a

CN2

10.4 ± 0.1 a

CN3

10.0 ± 0.04 ab

CP1

9.0 ± 2.1 abc

CP2

7.8 ± 1.7 bc

T1

6.6 ± 0.3 c

T2

7.30 ± 0.04 c

T3

6.6 ± 0.2 c

T4

7.90 ± 0.08 c

T5

6.9 ± 0.5 c

Values displayed are the means of three replicates and standard error of the mean. Significant differences (p < 0.05) between tests are indicated with lower case letters according to one-way ANOVA with Tukey’s HSD post hoc test

positive controls and treatments did not exhibit significant differences (Table 2; Fig. 2).

Biomass Growth Increases in microbial biomass (planktonic cells) during incubations were detected in all microcosms, including negative controls. In the second day of incubation, cell numbers measured at treatments (*1010 cells mL−1) were higher than controls (*109 cells mL−1). The observed microbial biomass content of all tests was maintained throughout incubation period, with cell numbers oscillating between 108 and 109 cells mL−1, indicating that the amount of BR used in the experiment did not inhibited the microbial community. Fig. 2 Variation in pH in the microcosm suspensions during incubation period. Values displayed are the mean of three replicates; error bars indicate the standard deviation of the mean

Mineralogical and Chemical Composition

variations in pH during this period). Positive controls (with sucrose) exhibited low rates of pH reduction (CP1 pH 9.0 ± 2.1 and CP2 7.8 ± 1.7), while no pH neutralisation was obtained in negative controls, as expected. Inversely, the pH of CN1 and CN2 increased from *pH 10 to pH 12 and pH 11, respectively, during the first days of incubation, while the increase in pH observed in the CN3 ceased by the fourth day. Negative controls pH decreased gradually in the following days, returning to baseline levels on the 28th day. Treatments (with organic residues) had faster rates of pH neutralization than CP1 and CP2 (as well as lower deviation), where pH decreased to values between 6 and 8 on the 2nd day of incubation, remaining in this range until completion of experiments. However, the final pH values of

Mineralogical composition of the microcosm treatments is shown in Fig. 3. Untreated BR, negative (CN1, CN2 and CN3) and positive (CP1 and CP2) controls and treatments T1, T2, T3 and T5 were predominantly composed of quartz (Qz), hematite (Hem), sodalite (Sdl), anatase (Ant), aluminous goethite (Al-Gth), gibbsite (Gbs) and calcite (Cal). The latter was not detected in CP2, T1, T2, T3 and T5. Figure 3d shows the mineralogical composition of the residue SFE before microcosm amendment and in treatment T4. While SFE composition was characterized by chlorite (Chl), illite (Ill), kaolinite (Kln), palygorskite (Plg) and quartz (Qz), the mineralogy of treatment 4 comprised a combination of minerals present in both SFE and BR, except for calcite that was not detected in this treatment. Quartz was the main mineral phase found in the soil sample.

Bayer Process Towards the Circular Economy—Soil Conditioners …

111

Fig. 3 Comparison of X-Ray diffraction patterns of microcosm treatments and raw materials (BR, soil, SFE). a Unamended BR, soil, CN1, CN2 and CN3; b unamended BR, soil, CP1 and CP2; c unamended BR, T1, T2, T3 and T5; d unamended BR, soil, SFE

and T4. Qz quartz, Hem hematite, Sdl sodalite, Ant anatase, Al-Gth aluminous goethite, Gbs gibbsite, Cal calcite, Chl chlorite, Ill illite, Kln kaolinite and Plg palygorskite

The chemical composition of all microcosm tests indicated iron (Fe), silicon (Si) and aluminum (Al) as the main elements (Table 3). Untreated BR contained 36.75% of Fe, 15.55% of Si and 20.09% of Al. While Fe, Al and Si contents of CN1 remained close to those of BR (36.07, 20.75 and 15.97%, respectively), the other tests exhibited a decreased in the Fe content (values ranging from 16.08% (T4) to 28.91% (CP2)), a decreased in the Al (values from

14.94% (T1) to 19.01% (CP2)) and increased Si with values between 31.24% (CP2) to 39.72% (T3). Except for CN1 that exhibited similar values to unamended BR, sodium (Na) and calcium (Ca) content decreased in all tests, of which T3 exhibited the lowest Ca content (0.56%) and T1 the lowest Na content (0.86%). The loss on ignition (LOI) measured for untreated BR, negative and positive controls and T5 ranged from 7.3 to 9.3%, while

0.16 0.64

2.43 0.34 – – 0.21 2

0.16

0.14

0.49

–

–

0.12

–

–

20.09

36.75

1.35

–

–

10.27

0.14

0.86

–

0.16

9.29

Fe2O3

CaO

MgO

K2O

Na2O

V2O5

ZrO2

P2O5

SO3

LOI*

44.39

1.32

1.9

4.93

10.92

8.79

0.11

0.38

9.68

0.16

–

1.39

36.07

20.75

7.32

0.17

–

0.53

0.11

7

0.22

–

1.01

28.6

18.67

4.13

31.99

CN2e

7.26

0.17

–

0.55

0.1

6.49

0.7

–

1

27.63

18.96

4.09

32.76

CN3f

7.91

0.15

–

0.56

0.1

6.38

0.55

–

0.97

27.2

18.55

4.14

33.21

CP1g

9.47

0.17

0.1

0.55

0.1

4.69

0.55

–

0.81

28.91

19.01

4.2

31.24

CP2h

15.77

0.14

0.58

0.47

–

0.86

0.84

–

0.58

23.22

14.94

3.48

38.89

T1i

15.23

0.25

0.55

0.48

0.1

2.18

0.92

–

1.16

24.29

17.23

4.12

33.32

T2j

11.94

0.12

0.55

0.64

–

1.29

1.25

–

0.56

23.72

16.21

3.72

39.72

T3k

24.85

0.53

0.17

0.25

–

2.05

2.22

0.8

1.27

16.08

14.96

2.18

34.4

T4l

10.84

0.14

0.49

0.58

–

1.64

0.58

–

0.68

25.93

17.22

3.94

37.71

T5m

*Loss on ignition. aBauxite residue, bsoil inoculum, cSpent Fuller’s Earth, dnegative control 1, enegative control 2, fnegative control 3, gpositive control 1 (1% sucrose), hpositive control 2 (2% sucrose), itreatment 1(palm mesocarp fiber), jtreatment 2 (palm oil decanter cake), ktreatment 3 (empty palm fruit bunche), ltreatment 4 (spent fuller’s earth), mtreatment 5 (Açaí seed)

5.23

3.66

8.92

5.66

15.97

Al2O3

0.49

30.87

5.18

1.27

79.74

15.55

SiO2

CN1d

TiO2

SFEc

Soilb

Content (% mass)

BRa

Constituent

Table 3 Chemical composition of microcosm treatments and raw materials

112 R. B. Holanda et al.

Bayer Process Towards the Circular Economy—Soil Conditioners …

113

T3 and T5 were slightly higher (11.9–10.8%). However, for T1, T2 and T4, LOI values were greater (15.77, 15.73 and 24.84%, respectively), in particular the latter that showed the highest LOI.

Positive effects of wheat straw, poultry manure compost and biosolids additions to BR were reported by Dong et al. [16]. Soil (at 5%) was incorporated into BR, and the organic material was mixed to BR + soil at three different rates: 3, 5 and 10%. The mixture was adjusted to 70% of water holding capacity, placed in 2 L plastic pots and incubated for one year at room temperature (25–30 °C). BR + soil was chosen as control treatment. BR bulk density decreased and the concentration of large aggregates increased, in all treatment and addition rates. At the highest rates (10%) of organic material addition, compared with the control, all treatments had a decrease in Na content (from 4% to 1.3–1.5%, in weight), pH (from 11 to *8) and electrical conductivity (from 1 to *0.3 mS cm−1). Microbial biomass increased in all treatments, but a lower extent than reference soil. Treatments’ enzymatic activity (invertase and catalase) reached the levels of reference soils, after one year of treatment. The amount of organic amendment used significantly improved the parameters measured, while no significant differences in values were obtained with the different organic material used. Treatments were effective in improving microbial activity, and consequently the authors emphasized the importance of establishing microbial ecological functions in rehabilitation practices for sustainable ecosystems. Incorporation of organic residues and soil affected the mineralogical and chemical composition of the microcosm tests when compared with unamended BR. The SFE amendment conferred to treatment T4 distinct mineralogical profile due its unique composition which possibly resulted in the marked differences exhibited in parameters such as, higher pH buffering capacity and greater LOI in comparison with the other treatments. The increase in Si content of controls and treatments, occurred due to the high content of Si in the soil (79.74%). Sodium content of the tests showed a positive correlation with pH values measured on the completion of incubation period, in which treatments exhibited considerably lower content in comparison with BR and controls. The rapid pH neutralization and marked decreased in Na content (from 10.3% to  2.2%) obtained in the treatments (T1–T5) are major improvements in the BR’s undesirable properties. These traits tend to inhibit plant growth, in particular the salinity stress, impairing the effectiveness of a BR-based soil conditioner. The native soil used as microbial inoculum provided microorganisms able to adapt to the BR characteristics and to metabolise cellulose and lignin-containing substrates (e.g. PMF, EFB and Açaí seeds), indicated by pH neutralization and the high biomass content of all treatments during the course of the experiment. Future research will focus in developing a synthetic inoculum based on the isolation of

Discussion The addition of organic residues to BR was effective in reducing the pH and maintaining levels throughout the 28 days of experiment. No statistically significant differences in final pH were determined when comparing treatments receiving organic wastes with the controls containing the disaccharide sucrose (CP1 and CP2), confirming the efficacy of these wastes in promoting microbial fermentation of organic carbon. The lowest pH value (pH 6.6) obtained after 28 days of microcosm incubation was observed in the treatments T1 and T3 (containing PMF and EFB, respectively). The treatment T4 (with SFE) was the least efficient, with a final pH of 7.9. Spent fuller’s earth is a sulfuric acid-treated bentonite used for carotenoid removal during refining of vegetable oils [14], and was the most acidic of the evaluated residues (pH 3.6). The less pronounced pH neutralization observed in T4 reflects the pH buffering capacity of SFE, that is superior to the other organic residues, exhibiting smaller pH value deviations during the experiment. Treatment with PMF reached the lowest pH value (5.86 ± 0.07) of all treatments after the 7th day of incubation, however increased on subsequent days, possibly due to sodalite dissolution, buffering the pH in the range of pH 6–8 [15]. Previous studies applying organic residues to the BR achieved reduction in the pH in a similar timeframe as that in the present study. Microcosm experiments conducted by Santini and Peng [11] evaluated BR leachate pH neutralization using distinct organic carbon sources (glucose, banana, eucalyptus and wood chips), which were compared with controls containing “BR + soil” or only BR (in solution with H2O). All tested carbon sources reduced the BR’s pH, with banana and glucose showing the best results (reaching pH 7.2 and pH 7.4, respectively), while wood chips had the lowest reduction (pH 9.0). The pH of “BR + soil” and only BR did not decrease, similarly to CN1 and CN2 that remained >10. Tests containing banana showed considerable reduction pH (from *10 to 7.5) in four days, while in this study microcosms amended with PMF and EFB had pH 6.9 and 6.7, respectively, in the second day. Santini and Peng [11] concluded that the extent of pH neutralization is determined by labile carbon content, which dictates the rates of microbial substrate metabolization. Differences in the pH neutralization observed in CN3, CP1 and CP2 confirmed the positive correlation between organic carbon concentration and the acidification of pH.

114

BR adapted microbes to establish a more robust and stable BR-based bioremediation systems.

R. B. Holanda et al.

3.

Conclusions 4.

The final pH of treatments and positive controls did not exhibit significant differences at the statistical level of significance adopted (p < 0.05), indicating that the source of organic carbon did not affect the extent of pH neutralization, after 28 days incubation. However, the speed of pH reduction was greatly influenced by the organic carbon source, where sucrose provided the slowest rates and PMF and EBF the fastest. The obtained results indicate that the selected organic waste material and the soil incorporated to the BR were adequate and efficient for partial residue alkalinity neutralization favouring its application as a soil conditioner. The evaluated organic amendments effectively improved the BR’s physical and chemical properties, alleviating its critical properties such as high alkalinity and sodium content, and demonstrating this as a promising biological approach to BR remediation. Further research into microbial community composition, dynamics and identification of organic metabolites will provide better understanding of transformations occurring on BR properties, contributing to the development of an effective soil conditioner formulation. Acknowledgements The authors are grateful for the financial support for this study by Hydro Alunorte S/A and all technical and logistical support from Hydro’s R&D team. The author also thanks Juliano Rodrigo de Paula, Industrial Manager of Biopalma S/A, for providing the Palm Oil Processing by-products, and Museu Paraense Emílio Goeldi for providing the soil samples used in this study.

References 1. Sheng-guo X, Yu-jun W, Yi-wei Li, Xiang-feng K, Feng Z, Hartley W, Xiao-fei L, Yu-zhen Y (2019) Industrial wastes applications for alkalinity regulation in bauxite residue: A comprehensive review. J. Cent. South. Univ. 268–288. https:// doi.org/10.1007/s11771-019-4000-3 2. International Aluminium Institute, Bauxite and Alumina Committee (2010) Alumina Technology Roadmap. http://bauxite.

5.

6.

7.

8.

9.

10.

11.

12.

13.

14.

15.

16.

worldaluminium.org/fileadmin/_migrated/content_uploads/ fl0000422_02.pdf. Accessed 7 September 2019 Ujaczki É, Feigl V, Molnár M, et al. (2018) Re-using bauxite residues: benefits beyond (critical raw) material recovery: Re-using bauxite residues. J. Chem. Technol. Biotechnol. 93:2498–2510. https://doi.org/10.1002/jctb.5687 Klauber C, Gräfe M, Power G (2011) Bauxite residue issues: II. options for residue utilization. Hydrometallurgy 108:11–32. https://doi.org/10.1016/j.hydromet.2011.02.007 Ujaczki É, Feigl V, Farkas É, et al. (2016) Red mud as acidic sandy soil ameliorant: a microcosm incubation study: Red mud as soil ameliorant. J. Chem. Technol. Biotechnol. 91:1596–1606. https://doi.org/10.1002/jctb.4898 Jones BEH, Haynes RJ, Phillips IR (2010) Effect of amendment of bauxite processing sand with organic materials on its chemical, physical and microbial properties. J. Environ. Manage. 91:2281– 2288. https://doi.org/10.1016/j.jenvman.2010.06.013 Courtney R, Harrington T (2012) Growth and nutrition of Holcus lanatus in bauxite residue amended with combinations of spent mushroom compost and gypsum. Land Degrad. Dev. 23:144–149. https://doi.org/10.1002/ldr.1062 Santini TC, Warren K, Raudsepp M, et al. (2019) Accelerating bauxite residue remediation with microbial biotechnology. In: Chesonis C (ed) Light Met. 2019. Springer International Publishing, Cham. 69–77 Bray AW, Stewart DI, Courtney R, et al. (2018) Sustained bauxite residue rehabilitation with gypsum and organic matter 16 years after initial treatment. Environ. Sci. Technol. 52:152–161. https:// doi.org/10.1021/acs.est.7b03568 Santini TC, Malcolm LI, Tyson GW, Warren LA (2016) pH and organic carbon dose rates control microbially driven bioremediation efficacy in alkaline bauxite residue. Environ. Sci. Technol.50:11164–11173. https://doi.org/10.1021/acs.est.6b01973 Santini TC, Peng YG (2017) Microbial fermentation of organic carbon substrates drives rapid ph neutralization and element removal in bauxite residue leachate. Environ. Sci. Technol. 51:12592–12601. https://doi.org/10.1021/acs.est.7b02844 Hamdy MK, Williams FS (2001) Bacterial amelioration of bauxite residue waste of industrial alumina plants. J. Ind. Microbiol. Biotechnol. 27:228–233. https://doi.org/10.1038/sj.jim.7000181 Silva PMP, Lucheta AR, Bitencourt JAP, et al. (2019) Covellite (CuS) production from a real acid mine drainage treated with biogenic H2S. Metals. 9:206. https://doi.org/10.3390/met9020206 Khoo LE, Morsingh F, Liew KY (1979) The adsorption of/3-carotene i. by bleaching earths. J. Am. Oil Chem. Soc. 56.7 (1979): 672–675 Silva, PMP, Carmo, ALV, Holanda, R, et al. (2019) Brazilian bauxite residue physical-chemical characterization and acidic neutralization potential. Light Met. This issue Dong Y, Shao Y, Liu A, et al. (2019) Insight of soil amelioration process of bauxite residues amended with organic materials from different sources. Environ. Sci. Pollut. Res. https://doi.org/10. 1007/s11356-019-06007-y

Brazilian Bauxite Residue Physical–Chemical Characterization and Acidic Neutralization Potential Patricia Magalhães Pereira Silva, Andre Luiz Vilaça do Carmo, Roseanne Barata Holanda, Fernando Gama Gomes, Emanuele Nogueira, Raphael Vieira da Costa, Caio César Amorim de Melo, Adriano Reis Lucheta, and Marcelo Montini

Abstract

Physical-chemical evaluation of Brazilian (Amazon region) bauxite residue (BR) and analysis of its acid neutralization capacity (ANC) using, hydrochloric (HCl), sulfuric acid (H2SO4) and citric acid (C3H8O7) were carried out to assess the potential application of BR as soil ameliorant. Analysis indicated a particle size average size (D50) of 6.04 lm, 1.65 g cm−3 density and 18.28 mS cm−1 electrical conductivity. Mineral phases determined by XRD showed hematite, aluminous goethite, anatase, sodalite, gibbsite and quartz, in agreement with XRF (%) elemental characterization: Fe (24.38), Al (11.20), Si (7.91), Na (8.11), Ti (3.24), Ca (0.79), Zr (0.71), S (0.06), V (0.07) and Mn (0.09). ANC analyses conducted after 21 days indicated a lower acid consumption and pH equilibrium for H2SO4 and HCl (1.75 and 1.00 mol H+ kg−1, respectively and *pH8) when comparing with C3H8O7 (2 mol H+ kg−1). Results validate and provide basis for an effective use of BR in agronomic applications. Keywords

Neutralization biotechnology









Bauxite residue Mineral Green mining Environment

P. M. P. Silva
A. L. V. do Carmo
R. B. Holanda
F. G. Gomes
E. Nogueira
A. R. Lucheta (&) SENAI Innovation Institute for Mineral Technologies, Avenida Com. Brás de Aguiar, 548, Belém, PA 66035-450, Brazil e-mail: [email protected] R. V. da Costa
C. C. A. de Melo
M. Montini (&) Hydro Alunorte S.A, Rodovia PA-481 km 12, Distrito de Murucupe, Barcarena, PA 68447-000, Brazil e-mail: [email protected]

Introduction Bauxite residue (BR) is a by-product of the Bayer process, the most widely used for alumina production, where bauxite ore is digested under pressure, at temperatures around 180 °C, using sodium hydroxide (NaOH). For each ton of alumina produced, around 0.9–1.5 tons of BR are produced, depending on the initial bauxite-ore grade and the Bayer process efficiency. It is estimated that annual global BR production is about of 150 million tons and there is a worldwide inventory of over 4.6 billion tons [1, 2]. The BR has different mineral phases depending on the bauxite origins and the Bayer process conditions. However, regardless of the differences in bauxite ore and process conditions, all BR is characterized by high alkalinity (pH > 10), high electrical conductivity (0.7–18.2 mS cm−1), clay-like texture, elevated sodium content (69%) and high density (2.5 g cm3) [3, 4]. Generally, the main mineral phases present in the BR inherited from the mother ore are hematite (Fe2O3), diaspore (a-AlO(OH), boehmite (c-AlO (OH) or gibbsite (Al(OH)3); goethite (FeO(OH)), quartz (SiO2), anatase/rutile (TiO2), among others. In addition, the Bayer process conditions also include the presence of alkaline phases such as sodium hydroxide (NaOH), sodium carbonates (Na2CO3), sodium aluminate (NaAl(OH)4). Besides, sodium silicate (Na2SiO3), zeolite sodium hydrate and amorphous aluminosilicates. Desilication products (DSP) are formed within the Bayer process through reactions with reactive silica (kaolinite) from the bauxite ore. Bayer sodalite (Na6Al6Si6O24
Na2CO3
yH2O) is the main DSP formed and it has a zeolite type structure able to incorporate sodium salts, carbonate, aluminate, and hydroxide ions, all of which are common anion impurities in the Bayer liquor. Incorporated ions inside Bayer sodalite, when leached, have buffering capacity from approximately pH 11–8.3, while the buffering capacity of DSP is around pH 8 [5]. General neutralization reactions are described below:

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_16

115

116

P. M. P. Silva et al.

OH þ þ H þ ! H2 O ðbuffers at  pH 10:3Þ þ ! AlðOH Þ þ H2 O ðbuffers at  pH 10Þ AlðOHÞ 4 þH þ ! HCO CO2 3 þH 3 ðbuffers at  pH 8:3Þ

DSP (e.g. sodalite) dissolution: Na6 Al6 Si6 O24
Na2 CO3:
yH2 O þ 18H2 O þ 7H þ  8Na þ þ 6AlðOHÞ3 þ 6SiðOHÞ4

þ HCO 3 þ yH2 O ðbuffers at  pH 8Þ The high inherent BR alkalinity may cause equipment corrosion and handling risks, thereby limiting its untreated direct utilization in agriculture and as building materials. It is also difficult to use as a secondary source of raw material for iron, titanium or rare earth elements (REE) exploration. Partial pH neutralization can change BR properties facilitating its utilization [6]. However, prior to developing a neutralization strategy, it is important to determine the BR acid neutralization capacity (ANC), estimate the acid consumption and the buffering levels. ANC is the capacity of a chemical system to react after adding strong or weak acid. The mechanism is the reaction between the acid and any Bronsted bases, such as:  2þ 2 HCO ; AlðOHÞ or organic 3 ; CO3 ; BðOHÞ ; AlðOHÞ 4 acid anions that might be present in the system [7]. Thus, to obtain the ANC for the BR, it is necessary to quantify how many protons are needed to neutralize it as a function of the added acid. The presence of buffering alkaline minerals (e.g. sodalite, calcite, tricalcium aluminate) is the biggest struggle for BR chemical neutralization. Snars and Gilkes [8] have evaluated the ANC of BR samples from several countries over a 28-day periods, including from Brazil. The buffering capacity of the evaluated BR varied between pH 8.5 and 4.5 and it was a function of the mineral phases present and BR origin (Bayer process conditions) [8]. In the present work, a Brazilian BR sample was physically, chemically and mineralogically characterized. The ANC curves were determined using three acids (hydrochloric, sulfuric and citric). This study will generate basis for the development of low-cost biotechnological neutralization methods that may enable the future residue utilization in agriculture as a soil conditioner.

24 h, disaggregated, and ground in an agate mortar and pestle. Elemental composition was determined by energy dispersive X-ray fluorescence (EDXRF) (Epsilon 3XLE, PANalytical Spectrometer) using an X-ray Rhodium (Rh) tube, and anode at 1.5 W. Mineral phases were determined by X-ray diffraction (XRD) (Empyrean; PANalytical Diffractometer, Almelo, The Netherlands). Powder XRD patterns were obtained (4°–75°2h, 40 mA, 40 kV, Ka 1.54 Å, step size 0.02°, 55 s/step). Particle size distribution was determined by Laser Diffraction using a Mastersize 3000 (Malvern-PANalytical) equipment and water as dispersant (RI = 1.33), particle refractive index (RI) = 2.25, and particle density = 1.56 g cm−3. Electrical Conductivity (EC) and Hydrogen Potential (pH) were determined in a 1:1 (BR:distilled water, w/v) solution in a HI Edge 2020 EC meter (Hanna Inst.) and in a Orion Star A211 pHmeter (Thermo Scientific), respectively, whereas density was determined by gravimetric method using a lab analytical balance (Mettler Toledo).

Acid Neutralization Capacity (ANC) The BR ANC curves were determined using hydrochloric acid (HCl, 0.5 mol L−1), sulfuric acid (H2SO4, 0.25 mol L−1), and citric acid (C6H8O7, 0.1667 mol L−1) separately, according to a modified Snars and Gilkes [8] protocol. 30 g of BR were weighed and transferred into 175 mL polypropylene capped bottles. Deionized water and several 7.5 mL (0.025 mol L−1) acidic inputs were added to the bottles to completed a 150 mL final volume, until reaching 150 mL of acid (2 mol H+ kg−1) (Fig. 1). A blank sample was prepared by adding 150 mL of distilled water to 30 g of BR, (Fig. 1). Suspensions were manually shaken for 1 min, and then pH (Thermo Scientific, Orion Star A211 pHmeter) was immediately measured. Subsequently, the flasks were transferred to a mechanical agitator (Eppendorf, Innova 44) operating at 130 rpm (30 °C), and supernatant pH was measured after 4 h, 1 day, 3 days, 7 days, and 21 days.

Results and Discussion BR Sample Characterization

Materials and Methods Bauxite Residue (BR) Physic-Chemical and Mineralogical Characterization The BR sample was received at the SENAI Innovation Institute for Mineral Technologies, in Brazil, where the study was conducted. The sample was dried at 96 °C during

A BR sample diffractogram is shown in Fig. 2. The main phases identified in BR sample were: hematite (Fe2O3), anatase (TiO2), sodalite (Na8(AlSiO4)6Cl2), gibbsite (Al (OH)3), quartz (SiO2) and aluminous goethite ((Fe, Al) OOH). Several studies shown that hematite is present in all bauxite residues [9–11]; other minerals commonly found are: boehmite (c-AlOOH), gibbsite (Al(OH)3), anatase, rutile/anatase (TiO2), ilmenite (FeTiO3), perovskite

Brazilian Bauxite Residue Physical–Chemical Characterization …

117

Fig. 1 Schematic procedure of ANC determination with crescent acid concentrations

Fig. 2 XRD diffractogram of BR from Brazil. Sdl sodalite, Gbs gibbsite, Al-Gth aluminous goethite, Ant anatase, Hem hematite, Qz quartz

(CaTiO3), and quartz (SiO2). The two main phases formed during the Bayer process are sodalite (Na8(Al6Si6O24)Cl2) and calcite (CaCO3), where sodalite is the most common DSP forming mineral during pre-desilication [12]. Calcite was not identified in the evaluated BR sample at the method detection limit. Calcite absence may be associated to low calcium input during the process. BR chemical analysis is presented in Table 1. The major BR constituent element was Fe (24.38%), followed by Al (11.20%), Na (8.11%), Si (7.91%) and Ti (3.24%). Other elements were also detected in BR at a lower percentage (e.g. Ca, Zr, Mn and S). The presence of these elements corroborate with XRD results, being mainly associated to hematite (Fe), gibbsite or aluminous goethite (Al), sodalite (Na, Al, Si) and quartz (Si). Similar chemical composition of Brazilian BR samples was found by Snars et al. [8] and Braga et al. [13]. The elements Fe and Al where described in higher concentrations by Snars et al. [8] and may probably be associated to differences in bauxite origins and industrial process conditions. Bauxite residue particle size distribution (PSD) is shown in Fig. 3. The PSD analysis indicated that the BR is

dominated by a mixture of very fine particles. It was found that 90% (D90) of particles were smaller than 22.5 µm, 50% smaller than 6.04 µm (D50) and 10% smaller than 1.65 µm (D10). An important remark is that the dominance of small particles and desegregated structure of BR may negatively impact its performance for agronomical application as it, may result in soil capillarity clogging or, cause difficult with water absorption and plant roots penetration.

pH, EC and ANC The BR determined pH and EC were 10.4 and 18.28 mS cm−1, respectively. These data confirm the high alkalinity characteristic of BR due to the addition of sodium hydroxide (NaOH), and presence of anions such as OH−, CO32−/ HCO3−, AlðOHÞ4  /Al(OH)3(aq) and H2SiO42−/H3SiO4− [12]. The EC values described in the literature ranges from 1.4 to 28.4 mS cm−1 and correspond to the EC found for the BR [12]. Usually ANC curves are determined using a strong acid, such as HCl, as described by Snars and Gilkers [8]. In this

118 Table 1 Chemical composition, expressed as percentage element (%) in the Brazilian bauxite residue samples

P. M. P. Silva et al. % Elem.

BR (this work)

Braga et al. [13]

Snars and Gilkes [8]

Fe

24.38

23.08

31.89

Al

11.20

11.38

7.99

Na

8.11

6.97

5.56

Si

7.91

8.93

7.29

Ti

3.24

2.82

2.57

Ca

0.79

0.86

0.83

Zr

0.71

–

–

Mn

0.09

–

0.01

V

0.07

–

–

S

0.06

–

0.08

LOI

7.99

10.80

9.30

LOI Loss on ignition

Fig. 3 Particle size distribution of bauxite residue

work, a modified protocol was developed to allow ANC curve determination using also H2SO4 and C6H8O7. These acids were evaluated due to our interesting in a future partial neutralization of BR by using biotechnologically produced sulfuric and organic acids by Acidithiobacillus sp. bacteria and Aspergillus niger fungus, respectively [14, 15]. A previous study determined the A. thiooxidans biogenic H2SO4 maximum production in 0.8 mol of H+ after 12.5 days cultivation with elemental sulfur as energy source [16]. The use of biogenic produced acid for partial BR neutralization is an alternative to reduce the process costs, making it economically viable, since it can potentially replace the need of expensive pure chemical acids, such as HCl. The buffering curves at different concentrations of HCl (0–2 mol H+ kg−1) were showed in Fig. 4. A strong decrease in pH (*pH 11.0 to pH 4.0) was observed after only 1-min reaction, probably due to the neutralization of free anionic species present in solution remaining from Bayer process, such as NaOH. After 4 h incubation, the slow chemical dissolution of the solid phases (e.g. sodalite) started to take place and new anionic species were released to the solution raising the pH again. A buffering region around

pH 8.0 was observed along time for 1.0 and 1.8 mol H+ kg−1 HCl concentration, probably generated by hydroxyls linked on the surfaces of oxides, mainly Fe and Al, as well as sodium structure – sodalite type dissolution. Between 1.8 and 2 mol H+ kg−1 the pH decreased due to the sodalite buffering capacity. Once sodalite/calcite is totally consumed at pH 6–8, the pH will decrease until the next mineral phase (e.g. iron and aluminum oxides) start to dissolve and buffer pH below 2 [8]. The BR neutralization difficulty was reported by Thornber and Binet [12] who observed a significantly pH increasing along a time frame from 1 min to 5 days and a high equilibration time dependent buffering curve [12]. XRD diffractograms of BR after 21 days treatment with HCl acid were demonstrated in Fig. 5. After 21 days, the calcite phase was identified in the treatment containing 0.75 mol of H+ kg−1, probably due to dissolution of Na2CO3 and NaOH which anions (CO32−/HCO3− and OH−) releasing for the system reaction, promoting interactions with calcium from Bayer process, contributing to calcite formation. The calcite mineral phase was completely dissolved around pH 6 with 1.63 mol H+ kg−1 of HCl. Despite XRD being a semi-quantitative method, we can observe a significant reduction of the sodalite peak, evidencing its dissolution at 2.0 mol H+ kg−1 of HCl, after 21 days incubation (Fig. 5). Calcite and sodalite dissolution are the main cause of Brazilian BR buffering around pH 6–8 [8]. Since BR will be tested in the future as a soil conditioner to replace limestone application, we assumed that a partial BR neutralization around pH 8.0 would be adequate to safe management during soil application, remaining the soil alkalinity power. Neutralization of bauxite residue to pH around 8.0 is advantageous because the chemically adsorbed Na is released to leaching, alkaline buffer minerals are partially neutralized and metals such as: Cu, Cd, Pb, Zn, Ni, Hg and Cr (i.e. environmental toxicity potentially) are insoluble

Brazilian Bauxite Residue Physical–Chemical Characterization … Fig. 4 Bauxite residue pH neutralization by different HCl concentrations along 21 days

Fig. 5 XRD diffractogram of BR solid phase after 21 days acid treatment with concentrations of hydrochloric acid of 0 mol H+ kg−1 (blank sample), 0.25 mol H+ kg−1, 0.75 mol H+ kg−1, 1.63 mol H+ kg−1 and 2.0 mol H+ kg−1. Sdl sodalite, Gbs gibbsite, Al-Gth aluminous goethite, Ant anatase, Hem hematite, Cal calcite

119

120

P. M. P. Silva et al.

at this pH [18]. Therefore, based on ANC, to keep pH 8.0 for a longer time will require about 1 mol H+ kg−1 of solids, evidencing the high BR buffer capacity (Table 2). The ANC behavior when using H2SO4 acid was similar to HCl acid (Fig. 6); however, other inflections points were observed indicating dissolutions of minerals phases (mainly sodalite). It was also observed a pH increasing after as soon as 4 h reaction. A smooth slope was observed in the range of 1.40–1.80 mol H+ kg−1 and range of pH 6–9, in Fig. 6, probably associated to the high proton consumption, since this area is recognized as sodalite buffering region. Chevdov et al. [18] argued that part of the buffering capacity of bauxite residues between pH 9 and 6 could be attributed to the titration of surface hydroxyl (OH−) groups from solid phases [19]. As previously show the ANC to pH 8 increase from about 0.5 H+ kg−1 mol H+ kg−1 solids at a 1 min to 1.75 mol H+ kg−1 solids at 21 days. XRD diffractograms of ANC with H2SO4 were shown in Fig. 7. The main buffering phases (sodalite and calcite) were also identified, occurring the complete calcite and partial Table 2 Concentration (Mol H+ kg−1) of hydrochloric (HCl), sulfuric (H2SO4) and citric (C6H8O7) acids necessary to acidify bauxite residue to pH 8 to over different times

Fig. 6 Bauxite residue pH neutralization by different H2SO4 concentrations along 21 days

sodalite dissolution after 21 days incubation. Despite H2SO4 is also a strong mineral acid, HCl was most effective, under the same H+ concentration, to promote sodalite dissolution. ANC of C6H8O7 is shown at Fig. 8. Unlike the mineral acids (HCl and H2SO4), even the highest concentration of C6H8O7 tested was unable to acidify BR below pH 5.0 for more than one minute (Fig. 8). Weaker organic acids, such as citric, ascorbic, malic, are known to operate in a two-fold manner concerning the dissolution of minerals. As reported to Stumm [19], proton promoted dissolution can be enhanced by the chelation of the released metal with excess organic acids in solution thereby lowering the activity of the free metal in solution. Alternatively, specific adsorption of the organic acid to the surface of the solid can destabilize bonds between the surface metal and the bulk mineral by either ligand-to-metal or metal-to-ligand charge transfers that ultimately promotes the dissolution of metals at the surface [19]. Considering the target BR pH 8, would be necessary more than 2 mol H+ kg−1 solid of C6H8O7 to keep it stable for a longer time (Table 2).

Mol H+ kg−1 Time

HCl

H2SO4

C6H8O7

1 min

0.50

0.50

0.88

4h

0.63

0.63

1.00

24 h

0.75

0.88

1.00

7 days

0.88

1.00

1.5

14 days

1.00

1.25

>2.00

21 days

1.00

1.5

>2.00

Brazilian Bauxite Residue Physical–Chemical Characterization … Fig. 7 XRD diffractogram of BR solid phase after 21 days acid treatment with concentrations of Sulfuric acid of 0 (blank sample), 0.25 mol H+ kg−1, 0.75 mol H+ kg−1, 1.63 mol H+ kg−1 and 2.0 mol H+ kg−1. Sdl sodalite, Gbs gibbsite, Al-Gth aluminous goethite, Ant anatase, Hem hematite, Cal calcite

Fig. 8 Bauxite residue pH neutralization by different C8H8O7 concentrations along 21 days

121

122

P. M. P. Silva et al.

Fig. 9 XRD diffractogram of BR solid phase after 21 days acid treatment with concentrations of citric acid of 0 (blank sample), 0.25 mol H+ kg−1, 0.75 mol H+ kg−1, 1.63 mol H+ kg−1 and 2.0 mol H+ kg−1. Sdl sodalite, Gbs gibbsite, Al-Gth aluminous goethite, Ant anatase, Hem hematite, Cal calcite

XRD diffractograms of BR samples treated with C6H8O7 were demonstrated in Fig. 9. Calcite was completely dissolved under C6H8O7 concentration of 0.75 mol H+ kg−1, even better than H2SO4. However, sodalite phase seems to remain unchanged (Fig. 9). Citric acid is unable to transform the chemical speciation of Na structure [20]. Kong et al. [20] described BR cancrinite and calcite dissolution after C6H8O7 reaction, by decreasing protonation and surface adsorption of H+, a primary buffering effect [20]. Table 2 summarizes the amount of acid necessary to partially neutralize BR to pH 8 along 21 days experiment. As expected, a lower concentration of HCl was required for partial neutralization of BR to pH 8 compared to H2SO4 and C6H8O7. However, there are many negative points by considering using HCl in large scale BR neutralization, such as elevated costs, dangerous transport, storage and handling and absence of biotechnological routes for its production. The determined BR ANC confirmed that sodalite and calcite dissolution were the main responsible for pH buffering. In general, Brazilian’s BR are richer in sodalite than calcite, and as observed, calcite is primarily solubilized,

hence sodalite is the main challenge to BR alkalinity neutralization.

Conclusions The BR evaluated sample was mainly composed by hematite, aluminous goethite, gibbsite, sodalite, anatase, with their associated elements: Fe, Al, Na, Si and Ti. The ANC results indicate that BR partial alkalinity neutralization was most effective with HCl > H2SO4 > C6H8O7. HCl reached pH below 5.0 even after 21 days reaction. Acid BR treatment showed a pH buffering between pH 6 and 8, were calcite and sodalite are most soluble. If we consider a long term partial biological BR alkalinity neutralization to pH 8.0, adequate to the soil conditioners development, bacterial and fungal cultures will need to produce at least 1.5 mol H+ of H2SO4 and >2.0 mol H+ of C6H8O7 per kg. These results indicate how efficient the microbial bioreactors for biogenic sulfuric and citric production would be will be to allow partial BR neutralization.

Brazilian Bauxite Residue Physical–Chemical Characterization …

123

Acknowledgements The authors are grateful for the financial support of this study by Hydro Alunorte S/A and all technical and logistical support from Hydro’s R&D team.

10.

References

11.

1. Sheng-guo X, Yu-jun W, Yi-wei Li, Xiang-feng K, Feng Z, Hartley W, Xiao-fei L, Yu-zhen Y (2019) Industrial wastes applications for alkalinity regulation in bauxite residue: A comprehensive review. J. Cent. South. Univ. 268–288. https:// doi.org/10.1007/s11771-019-4000-3 2. Hydro (2019). Hydro worldwide. In: Hydro worldwide. https:// www.hydro.com/en-BR/about-hydro/hydro-worldwide/southamerica/brazil/barcarena/alunorte/. Accessed 27 August 2019 3. Ujaczki É, Feigl V, Molnár M, Cusack P, Curtin T, Courtney R, O’Donoghue L, Davris P, Hugi C, Evangelou MW, Balomenos E, Lenz M (2018) Re-using bauxite residues: benefits beyond (critical raw) material recovery. J Chem Technol Biotechnol 2498–2510. https://doi.org/10.1002/jctb.5687 4. Santini TC, Fey MV (2018) From tailings to soil: long-term effects of amendments on progress and trajectory of soil formation and in situ remediation in bauxite residue. Journal of Soils and Sediments. 18:1935–1949 5. Kirwan LJ, Hartshorn A, McMonagle JB, Fleming L, Funnell D (2013) Chemistry of bauxite residue neutralisation and aspects to implementation. Int. J. of Mineral Processing. 119:40–50 6. Rai SB, Wasewar KL, Mukhopadhyay, J. (2012) Neutralization and utilization of red mud for its better waste management. Archives of Environmental Science 6:13–33 7. Cantrell KJ, Serkiz SM, Perdue EM (1990) Evaluation of acid neutralization capacity data for solutions containing natural organic acids. Geochimica et Cosmochimica. 54:1247–1254 8. Snars K, Gilkes RJ (2009) Evaluation of bauxite residues (red muds) of different origins for environmental applications. Applied Clay Science. 46:13–20 9. Qi X, Wang H, Huang C, Zhang L, Xu B, Li F, Junior JTA (2018) Analysis of bauxite residue components responsible for copper

12. 13.

14.

15. 16.

17.

18. 19.

20.

removal and related reaction products. https://doi.org/10.1016/j. chemosphere.2018.05.041 Young-Soo H, Sangwoo J, Pyeong-Koo L, Chamteut O (2017) Bauxite residue neutralization with simultaneous mineral carbonation using atmospheric CO2. Journal of Hazardous Materials. 87– 93 Gräfe M, Power G, Klauber C (2011) Bauxite residue issues: III Alkalinity and associated chemistry. Hydrometallurgy. 108: 60– 79. Thornber MR, Binet D. (1999) Caustic soda adsorption on Bayer residues. In 5th international alumina quality workshop. 498–507 Braga P et al. (2018) Use of bauxite residue (red mud) as CO2 absorbent. Paper presented at 5th International Seminar on Tailings Management, Santiago, Chile, 11–13 July 2018 Zhang Y, Zhang H, Zhang Z, Liu C, Sun C, Zhang W, Marhaba T (2018) pH Effect on Heavy Metal Release from a Polluted Sediment. Journal of Chemistry. doi:https://doi.org/10.1155/2018/ 7597640 Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures. Prokaryotic Nomenclature Up-to-date. Checklist dataset https://doi.org/10.15468/oclygu Accessed 10 August 2019 Rahman MM, Huque KS (2002). Study on voluntary intake and digestibility of banana foliage as a cattle feed. J. Biol. Sci. 2:49–52 Hsuan-Liang L, Yann-Wen L (2003) Optimal production of sulphuric acid by Thiobacillus thiooxidans using response surface methodology. Process Biochemistry 39: 1953–1961 Hanahan C, McConchie D, Pohl J, Creelman R, Clark M, Stocksiek C (2004) Chemistry of seawater neutralization of bauxite refining residues (red mud) Env. Eng. Science 21: 125–138 Chevdov D, Ostap S. Le T. (2001) Surface properties of red mud particles from potentiometric titration, Colloid Surfaces A, 2:131–141. Stumm W, Sulzberger B. (1992) The cycling of iron in natural environments: Considerations based on laboratory studies of heterogeneous redox process. Geoq. et Cosmochimica Acta. 56: 3233– 3257 Xiangfeng K, Chu-Xuan L, Jun J, Long-Bin H (2019) Improvement of alkaline electrochemical characteristics of bauxite residue amendment with organic acid and gypsum. Journal of central south University 26: 43–439.

Effect of Concentrations and Pressures of CO2 on Calcification–Carbonation Treatment of Bauxite Residue Xi Chao, Ting-an Zhang, Guo-zhi Lv, and Yang Chen

Abstract

The calcification-carbonization process is attracting attention as a new, feasible method for clean production of alumina and treatment of red mud. The carbonization stage within the overall process was investigated, and the effects of CO2 concentration and pressure on the recovery of sodium oxide and alumina from red mud were studied in detail. The results showed that when the CO2 total pressure is 1.2 MPa and the CO2 concentration is 99.99%, the recovery of alumina and sodium oxide reached 40.08% and 93.16%, respectively. Similar results can also be achieved when the CO2 partial pressure is 1.2 MPa and the CO2 concentration is only 60%. And the main phase of solid slag is converted from hydrogarnet to CaCO3. This study aims to provide a theoretical basis for the industrialization of calcification-carbonization method. Keywords












Bayer process residue Carbonation CO2 concentration Alumina Sodium oxide Recovery

Introduction Bauxite residue (red mud) is the main solid waste originated from the Bayer process in the production of alumina. According to different types of bauxite and treatment, about The original version of this chapter was revised: The figure 2 is updated with the correct figure. The correction to this chapter is available at https://doi.org/10.1007/978-3-030-36408-3_184 X. Chao
T. Zhang (&)
G. Lv
Y. Chen 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]

1–1.5 tons of red mud is produced per ton of alumina produced on average [1]. With the rapid development of the global alumina industry, the amount of red mud emissions continue to increase, and by 2017 the global red mud reserves have reached 3.9 billion tons [2, 3]. The pH of red mud is about 9.2–12.8 due to the addition of alkaline solution in the production of alumina by Bayer process, which is usually regarded as a solid hazardous waste [4]. Due to its unique mineralogy and strong alkalinity, the global average utilization rate of red mud is only around 15%, of which is only 4% in China, its comprehensive utilization rate is very low [5]. The main treatment method of red mud is outdoor storage, but because of its high alkalinity, long-term storage not only occupies a large number of land resources, but also causes many serious environmental problems, so it is of great significance to remove alkali and extract alumina from red mud [6]. At present, substantial research has been undertaken on the comprehensive utilization of red mud worldwide, mainly focusing on the following aspects: as structural materials, such as using red mud to prepare cement, unburned bricks and other building materials [7– 10]; as filling materials for roadbed or embankment [11, 12]; as an adsorbent material after modification, to adsorb pollutants in water or gas pollutants [13, 14]; and recover valuable metals (Al2O3, Na2O, rare earth elements and so on) [3, 15, 16]. Previous research has shown that bauxite residue can be treated by a sinter-leach process for alkali recovery and alumina extraction [17, 18]; however, its high energy consumption and high operating cost has caused difficulties during implementation. This has led to the development of a low-cost and mild calcification and carbonization method proposed by Northeastern University, China, as an alternative processing method [19]. In this study, we investigate the carbonization process within the calcification-carbonization method to recover sodium oxide and alumina from bauxite residue. This research aimed to investigate the effects of parameters such as CO2 concentration and pressure in this process for

© The Minerals, Metals & Materials Society 2020, corrected publication 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_17

124

Effect of Concentrations and Pressures of CO2 …

125

optimization, thereby providing theoretical basis for method industrialization.

Experimental Raw Materials The bauxite residue used in this study was supplied by an alumina refinery in China. This residue was produced following the digestion of diasporic bauxite. Prior to use as feed material, the residue sample was dried in an oven at 70 °C for 12 h. After the X-ray fluorescence spectrometry (XRF) detection, the chemical compositions of the red mud are shown in Table 1. The red mud is mainly composed of Al2O3, SiO2, CaO, Na2O and Fe2O3. The Al2O3 and Na2O contents are 25.52 wt% and 5.8 wt%, respectively. The X-ray diffraction (XRD) pattern of the red mud is shown in Fig. 1. The identified mineral phases were Cancrinite, hydrogarnet, and sodium calcium silicate. Sodium hydroxide (NaOH) and calcium oxide (CaO) used in this study were analytical-grade chemical reagents (Sinopharm Chemical Reagent Co., Ltd., China, NaOH  96%, CaO  98%), and different concentrations of CO2 was supplied from a gas cylinder (40 L, Shuntai Chemical Gas Co., Ltd., Shenyang, China).

Experimental Method The calcification-carbonization process consists of three steps. The first is calcification to recover the sodium oxide in the red mud, followed by the carbonization process to decompose the calcification residue. In the final stage, the carbonized residue is dissolved to recover the alumina. The calcification experiment was performed in a 2 L stainless steel autoclave equipped with a magnetic agitator and a proportional-integral-derivative (PID) temperature controller. The bauxite residue, alkaline solution, and CaO were charged into the autoclave and heated, liquid-solid ration is 3:1, the ratio of CaO to SiO2 is 2.5:1, liquid is 22 g/L Na2O solution, the stirring speed 300 r/min. After the temperature reached 160 °C, and then held for 1 h. Until the end of the reaction, the cooling water was introduced to reduce the temperature in the reactor autoclave below 50 °C, and the solution was separated from the calcified residue by filtration with a vacuum filter, the filter paper size is 12.5 cm and the material is cotton fiber. The calcified residue was

Table 1 Chemical composition of red mud used in the experiments (wt%)

Fig. 1 XRD pattern of red mud used in the experiments

washed with water until the pH of the filtrate reached neutral. The calcified residue obtained by filtration was baked in a drying oven at 70 °C for 12 h. The carbonization experiments were performed in a KCFD-2 stainless steel autoclave. The distilled water and calcified residue were mixed into the reaction autoclave and heated, liquid-solid ration is 5:1. After the temperature reached 120 °C, the CO2 valve was immediately switched on and continuously supplied to maintain a certain pressure in the reactor autoclave for 1.5 h, the concentrations of CO2 ranges from 20 to 99.99% (volume fraction), and the pressure of carbonization ranges from 1.2 to 4 MPa, the stirring speed 300 r/min.. Until the end of the reaction, the cooling water was introduced to reduce the temperature in the reactor autoclave to below 50 °C, and the solution was separated. Then the carbonized residue obtained by filtration was baked in a drying oven at 70 °C for 12 h. The alumina dissolving experiments were performed in a thermostatic magnetic stirrer. The 100 g/L NaOH solution and carbonized residue were mixed into the beaker. After the temperature reached 60 °C, liquid-solid ration is 10:1, the stirring speed is 300 r/min and then held for 2 h. After digestion, the solution was separated, and the residue washed with deionized water until the pH of washing solution reached neutral. The residue obtained by filtration was baked in a drying oven at 70 °C for 12 h. The SiO2 in red mud hardly participate in the reaction, so the recovery of sodium oxide (gNa2 O ) and that of alumina (gAl2 O3 ) from red mud were calculated using SiO2 as a standard. The formulae are expressed as follows:

Components

Al2O3

CaO

SiO2

Na2O

TFe

Content

25.52

18.52

18.5

5.80

5.32

126

X. Chao et al.

gAl2 O3 ¼

ðA=SÞRM  ðA=SÞLS  100% ðA=SÞRM

ð1Þ

gNa2 O ¼

ðN=SÞRM  ðN=SÞLS  100% ðN=SÞRM

ð2Þ

where (A/S)RM and (A/S)LS are the mass ratios between Al2O3 and SiO2 in raw red mud and the leached slag after digestion by the NaOH solution, respectively; (N/S)RM and (N/S)LS are the mass ratios between Na2O and SiO2 in raw red mud and the leached slag.

Solids Characterization The chemical compositions of the solid samples were analyzed by X-ray fluorescence spectrometry (XRF, ZSX100e, Rigaku, Japan). The mineralogy of the samples used in the experiments was characterized by XRD (D8 Advance, Bruker Company) operating at 40 kV, 40 mA with a Cu Ka X-ray source and step-size of 0.0095°, the 2h range from 10° to 90°. The morphology of the samples was observed by scanning electron microscopy (SEM, Zeiss, Ultra Plus).

Results and Discussion Effect of CO2 Concentration and Pressure

Fig. 3 Effect of CO2 concentration and pressure on recovery rate of Al2O3

the partial pressure of CO2 is 1.2 MPa, the recovery of sodium oxide increased with the increase of CO2 concentration and reached a maximum value of 93.16% at 100% CO2. This is because the chemical reaction of sodium oxide recovery mainly occurs in the calcification process, the reaction equation is as follows: Na2 O  Al2 O3  xSiO2  ð6 - 2x)H2 O + 3CaO + H2 O ð3Þ ! 3CaO  Al2 O3  xSiO2  ð6-2x)H2 O + 2NaOH

As shown in Fig. 2, CO2 concentration and pressure affected the recovery rate of sodium oxide. When the total pressure of CO2 is 1.2 MPa, the recovery of sodium oxide decreased first and then increased slightly, but they are all higher than 92%, the maximum can reach 93.88% at 20% CO2. When

It can be seen that the recovery rate of sodium oxide is mainly affected by the calcification process, and the concentration and pressure of CO2 in the carbonization process have little effect on it. As shown in Fig. 3, CO2 concentration and pressure affected the recovery rate of alumina. When the total pressure and partial pressure of CO2 is 1.2 MPa, the recovery of

Fig. 2 Effect of CO2 concentration on recovery rate of Na2O

Fig. 4 XRD analysis of calcified residue

Effect of Concentrations and Pressures of CO2 …

127

recovery of alumina at 1.2 MPa of partial pressure of CO2 is higher than that at 1.2 MPa of total system pressure, which means that the increase of pressure in the whole system will also promote the carbonization process.

XRD Analysis of Solid Samples

Fig. 5 XRD analysis of carbide residue with different concentration of CO2 partial pressure 1.2 MPa

alumina increased with the increase of CO2 concentration and reached a maximum value of 40.08% at 100% CO2. It indicated that increasing CO2 concentration is beneficial to the recovery of alumina in red mud. This is because the carbonization process is mainly the reaction of CO2 and hydrogarnet. When the total pressure is constant, the partial pressure of CO2 increases with the increase of CO2 concentration. According to Henry’s law, the higher pressure of CO2 in the gas phase, the more CO2 is dissolved in the liquid phase, making the extraction rate of alumina is gradually increased. In addition, at the same concentration of CO2, the Fig. 6 SEM analysis of carbide residue with different concentration of CO2 partial pressure 1.2 MPa with a 30% CO2; b 40% CO2; c 60% CO2; d 100% CO2

It can be seen from the comparison between Figs. 1 and 4, after calcification, the main phase of residues changed from Na6Ca1.5Al6Si6O24(CO3)1.6 to Ca2.93Al1.97Si0.64O2.56(OH)9.44. After carbon dioxide carbonization at different concentrations and pressures, it can be seen from Fig. 5 that under the condition of 30% CO2 concentration and the partial pressure of CO2 is 1.2 MPa, there is still a hydrogarnet phase in the XRD diffraction peak, which indicates that the carbonization under this condition is incomplete. When the partial pressure of CO2 is 1.2 MPa, the diffraction peak of hydrogarnet disappears with the increase of CO2 concentration during carbonization. The main phase of carbonized slag is CaCO3, indicating that the hydrogarnet is basically completely decomposed with the increase of CO2 concentration.

SEM Analysis of Solid Samples Figure 6 shows SEM images of carbonized residue obtained under different concentration of CO2 carbonization at the partial pressure of CO2 is 1.2 MPa. It can be seen from (a) that there are spherical particles, identified to be

128

hydrogarnets [1]. As the concentration of CO2 increases during carbonization, the decomposition degree of hydrogarnet particles increases, the spherical particles are reduced and more and more small-sized angular bulk solids appear. When the CO2 concentration is 100%, a large number of closely packed regular massive cubic morphologies are apparent, which are identified as calcite [20].

X. Chao et al.

3.

4.

5.

Conclusion 6.

(1) The carbonization process of calcification-carbonization method to recover sodium oxide and alumina from Bayer red mud was investigated. The recovery rate of alumina increases with the increase of CO2 concentration. When the CO2 concentration is 100% and the CO2 total pressure is 1.2 MPa, the alumina recovery rate reaches 40.08%, the sodium oxide recovery rate reaches 93.16%. When the CO2 concentration is 60% and the CO2 partial pressure is 1.2 MPa, the alumina recovery rate reaches 39.83%, the sodium oxide recovery rate reaches 93.08%. The recovery rates of sodium oxide and alumina are very similar, and CO2 at lower concentrations may be easier to implement in industrial engineering. (2) The XRD patterns show that the major chemical reaction that occurs in calcification is the conversion of sodium aluminosilicate to hydrogarnet. And the main solid product of the carbonization process is CaCO3. And when the partial pressure is 1.2 MPa, the hydrogarnet is basically completely decomposed with the increase of CO2 concentration. (3) With the increase of CO2 concentration during carbonization, the destruction degree of hydrogarnet particles increases and the cubic structure of calcium carbonate is formed.

7.

8.

9.

10.

11.

12.

13.

14.

15. Acknowledgements We acknowledge assistance provided by the National Natural Science Foundation of China (Nos. U1710257, 51874078, U1202274), the State Key Laboratory of Pressure Hydrometallurgical Technology of Associated Nonferrous Metal Resources (YY2016006), Fundamental Research Funds for the Central Universities (N182505038), and the Shenyang Science and Technology Project (17-500-8-01, Z18-5-022).

References 1. Guanting Liu, Yan Liu, Ting’an Zhang. Approaches to improve alumina extraction based on the phase transformation mechanism of recovering alkali and extracting alumina by the calcificationcarbonization method [J]. Hydrometallurgy, 2019, 189. 2. Zhu X F, Zhang T A, Wang Y X, et al. Recovery of alkali and alumina from Bayer red mud by the calcification–carbonation method [J].

16.

17.

18.

19. 20.

International Journal of Minerals, Metallurgy, and Materials, 2016, 23(3):257–268. Wang Y, Zhang T A, Lyu G, et al. Recovery of alkali and alumina from bauxite residue (red mud) and complete reuse of the treated residue [J]. Journal of Cleaner Production, 2018, 188:456–465. Chen X, Guo Y, Ding S, et al. Utilization of Red Mud in Geopolymer-based Pervious Concrete with Function of Adsorption of Heavy Metal Ions [J]. Journal of Cleaner Production, 2019, 207:789–800. Zhang T A, Wang Y, Lu G, et al. Comprehensive Utilization of Red Mud: Current Research Status and a Possible Way Forward for Non-hazardous Treatment [C]// Tms Meeting & Exhibition. 2018, 135–141. Li R, Zhang T, Liu Y, et al. Calcification-carbonation method for red mud processing [J]. Journal of Hazardous Materials, 2016, 316:94–101. Pontikes Y, Angelopoulos G N. Bauxite residue in cement and cementitious applications: Current status and a possible way forward [J]. Resources, Conservation and Recycling, 2013, 73:53–63. Kong I, Khoo K M, Buddrick O, et al. Synthesis and Characterization of Red Mud and Sawdust Based Geopolymer Composites as Potential Construction Material [C]// Materials Science Forum. 2018, 923:130–134. Wang X, Luo Z, Zhang L, et al. Utilization of red mud as raw material in the production of field road cement [J]. Journal of Wuhan University of Technology-Mater Sci Ed, 2016, 31(4):877–882. Ying-tang Xu, Bo Yang, Xiao-ming Liu, Shuai Gao, Dong-sheng Li, Emile Mukiza, Hua-jian Li. Investigation of the medium calcium based non-burnt brick made by red mud and fly ash: durability and hydration characteristics [J]. International Journal of Minerals Metallurgy and Materials, 2019, 26(08):983–991. Mangen Mu, Xiaozhen Gao, Taoming Guo, Xinping Hu. Experimental Study of Goaf Filling Materials Based on Red Mud [J]. IOP Conference Series: Materials Science and Engineering, 2018, 301(1). Ruifeng Chen, Guojun Cai, Xiaoqiang Dong, Dongyun Mi, Anand J. Puppala, Wei Duan. Mechanical properties and micro-mechanism of loess roadbed filling using by-product red mud as a partial alternative [J]. Construction and Building Materials, 2019, 216:188–201. Xinfeng Z, Shanjiao Y, Guizhi J. Progress in research and application of red mud in water treatment [J]. Inorganic Chemicals Industry, 2010, 42(2):4–8. Xinke Wang, Yihe Zhang, Fengzhu Lv, Qi An, Rongrong Lu, Pan Hu, Shaobin Jiang. Removal of alkali in the red mud by SO2 and simulated flue gas under mild conditions [J]. Environmental Progress & Sustainable Energy, 2015, 34(1):81–87. Borra C R, Blanpain B, Pontikes Y, et al. Recovery of Rare Earths and Other Valuable Metals From Bauxite Residue (Red Mud): A Review [J]. Journal of Sustainable Metallurgy, 2016, 2(4):365–386. Guo Y, Li J, Yan K, et al. A prospective process for alumina extraction via the co-treatment of coal fly ash and bauxite red mud: Investigation of the process [J]. Hydrometallurgy, 2019, 186:98–104. Gao F, Zhang J, Deng X, et al. Comprehensive Recovery of Iron and Aluminum from Ordinary Bayer Red Mud by Reductive Sintering-Magnetic Separation-Digesting Process [J]. JOM, 2019, 71(9):2936–2943. S.N. Meher, A.K. Rout, B.K. Padhi. Recovery of Al and Na Values from Red Mud by BaO-Na2CO3 Sinter Process [J]. E-Journal of Chemistry, 2011, 8(3):1387–1393. Pan Lu. Basic research on lime-carbonization treatment of low-grade bauxite and red mud [D]. Northeastern University, 2011. Zhu Xiaofeng. Basic research on calcification-carbonization treatment of medium and low grade gibbsite and red mud [D]. Northeastern University, 2016.

Comprehensive Utilization of Red Mud Through the Recovery of Valuable Metals and Reuse of the Residue Fei Lyu, Li Wang, Jiande Gao, Honghu Tang, Wei Sun, Yuehua Hu, Runqing Liu, and Lei Sun

Abstract

An integrated technological route for comprehensive utilization of red mud through the extraction of valuable components and reuse of the magnetic residue is proposed. In this study, inductively coupled plasma atomic emission spectroscopy, X-ray fluorescence, X-ray powder diffraction, and vibrating sample magnetometer were used to characterize the process. The process includes sintering, alkaline leaching to recover Na and Al, and removal of lead ions from wastewater by magnetic residue containing magnesium ferrite. The effects of various parameters were systematically investigated, and the optimal conditions were determined as: sintering temperature of 1150 °C and duration of 60 min, the mole ratio of CaO/SiO2 of 3, Na2O/Al2O3 of 1.2, and MgO/Fe2O3 of 1 in the raw material. Under the conditions, the results showed that approximately 74% Al and 95% Na were recovered from red mud by this route. The leach residue exhibits magnetic and adsorption properties, its adsorption capacity reaching about 70 mg/g at the initial Pb2+ concentration of 80 mg/L. Therefore, it may be a promising candidate in wastewater treatment and other fields.





Keywords







Red mud Comprehensive utilization Valuable metals Magnesium ferrite Adsorption

F. Lyu
L. Wang
J. Gao
H. Tang
W. Sun
Y. Hu
R. Liu
L. Sun School of Minerals Processing and Bioengineering, Central South University, Changsha, 410083, China F. Lyu
L. Wang (&)
J. Gao
H. Tang
W. Sun (&)
Y. Hu
R. Liu
L. Sun Key Laboratory of Hunan Province for Clean and Efficient Utilization of Strategic Calcium-Containing Mineral Resources, Central South University, Changsha, 410083, China e-mail: [email protected] W. Sun e-mail: [email protected]

Introduction Red Mud (or “Bauxite Residue”) is a by-product of the alumina refining using the Bayer process, and it is considered a highly alkaline waste solid (pH 10–13) [1]. Generally, 1–2 tons of red mud are discharged per tonne of alumina produced [2–4]. It is estimated that over 150 million tons of red mud are generated every year worldwide, of which China produces nearly 60% [5–7]. At present, the global inventory of red mud stored in landfills has exceeded 4.6 billion tons [8]. Unfortunately, the average utilization of these wastes worldwide is less than 15% [9]. The safe disposal and storage of such a large amount of red mud presents a big challenge and poses serious environmental challenges worldwide [10, 11]. Over the last few decades, numerous approaches have been studied to reuse the red mud in different areas including adsorbents, catalysis, building materials, and other applications [12–16]. Due to its high alkalinity, neutralization before utilization is necessary by acid [17], seawater [18], SO2 [19], or CO2 [20], increasing the cost of any recycling process. New approaches are therefore needed for reducing the large quantities of red mud in storage. Due to its mineral components, including Fe2O3, Al2O3, TiO2, and Na2O, and various other metals, red mud can be considered a precious secondary resource [21]. In recent years, various strategies have been investigated for recycling these valuable components through pyrometallurgical and hydrometallurgical methods [22–25]. For example, Li et al. [26] recovered Fe from red mud by reduction roasting followed by magnetic separation and a magnetic concentrate containing 90.2% iron with iron recovery of 95.0% was obtained. Zhang et al. proposed a novel calcification-carbonization method to recover aluminum and sodium from Bayer red mud [9]. However, most of the prior studies were just focused on the recovery of value components from red mud, and little attention has been paid to preparing functional materials based on these value components. Due to its high metallic

© A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_18

129

130

oxide content, the synthesis of magnetic materials attracted a great deal of attention. Different types of magnetic zeolite have been synthesized by Belviso et al. using colloidal silica and red mud as an aluminium source [27]. Similar work has been done by Xie et al. and they further confirmed their excellent adsorption behavior for mixed heavy metal removal [28]. Ferrite, an important magnetic material, is a kind of compound oxide mainly composed of iron oxides. Due to its unique pore size and framework structure, ferrite has widely been used in adsorbents. In this paper, red mud is first considered as an iron oxide source to synthesize magnesium ferrite (MgFe2O4), a ferrite bearing Mg [23]. The magnetic material was explored as an adsorbent in removal of lead ions from wastewater. In this process, sodium and alumina can also be extracted, which has the potential to realize fuller component utilization of red mud. This is an exploration in achieving sustainable development, and therefore of great potential significance.

Experimental Materials and Reagents The red mud samples were obtained from residue storage areas in Shandong Province, China, without any pretreatment. Analytical grade sodium carbonate (Na2CO3), magnesium oxide (MgO) and pure mineral calcite (CaCO3) were used as sources of Na, Mg and Ca, respectively. The calcite sample was ground before further utilization, and the analytical reagents were used without any pretreatment. The digesting solution was prepared with analytical sodium hydroxide (NaOH) and sodium carbonate (Na2CO3). Tap water was used in the leaching experiments, and deionized water used in the adsorption of lead ions experiments and all the measurements.

F. Lyu et al.

cooled to room temperature. The clinker sample was ground in a vibrating mill before determination of Al and Na, and extraction in a mixed NaOH and Na2CO3 solution with 15 g/L of Na2Ok and 5 g/L of Na2Oc. The extraction experiments were conducted in a flat bottom flask equipped with a condenser, which was agitated by magnetic stirrer and heated in a water bath with thermostatic heating. In extraction experiments, the liquid-solid ratio of 6:1, temperature of 80 °C and a reaction time of 20 min were adopted based on previous studies. After extraction, the slurries were filtered and rinsed to neutral with water at 80 °C. The filter cakes were dried and weighed before determining the Al and Na. The extraction rates of aluminum and sodium are calculated by Eq. (1).   mh e¼ 1  100% ð1Þ Ma where e represents the extraction rate of aluminum or sodium; M and m represent the mass of the clinker before extraction and the leach residue, respectively; a and h represent the grade of aluminum or sodium of the clinker and the leaching residue, respectively.

Removal of Lead Ions from Wastewater Synthetic wastewater was prepared by dissolving lead nitrate to a target concentration of Pb2+ in solution. A certain amount of synthetic magnetic material was added into the 50 mL of Pb2+ solution, adjusting the pH with dilute HCl or NaOH bulk solutions. After mechanical stirring for a prescribed time, the suspensions were filtered with 0.45 lm syringe filter, and the Pb2+ concentration of the filtrate was determined by ICP-AES. The Pb2+ removal rate was calculated according to Eq. (2).   C1 g¼ 1  100% ð2Þ C0

Methods

where η represents the removal rate of Pb2+; C0 and C1 represent the Pb2+ concentration of the wastewater before and after treatment, respectively.

Recovery of Aluminum and Sodium In the study, the improved soda-lime sintering process was carried out to recover aluminum and sodium. In the sintering process, the raw mixture was prepared by intensive mixing 30 g red mud with sodium carbonate, calcite and magnesium oxide, to meet the target mole ratio of Na2O/Al2O3, CaO/SiO2 and MgO/Fe2O3. Then, the raw mixture was added into a 100 mL corundum crucible, which was sintered in a vertical lifting furnace for a specified time in the range of 20–60 min under an air atmosphere. After the completion of the sintering, the sample was taken out and naturally

Sample Characterization The aluminum and sodium content of the clinker and leach residue was determined by inductively coupled plasma atomic emission spectroscopy (ICP-AES, SPECTRO BLUE SOP, Germany) after digestion, which was also used to determine Pb2+ concentration in solutions. The chemical compositions and crystalline phases of red mud, clinker, leach residue were analyzed by X-ray fluorescence (XRF, Panalytical B.V-AxiosmAX, Netherlands) and powder X-ray diffraction (XRD, Bruker-D8 Advance, Germany), using Ni-filtered Cu Ka radiation operated at 40 kV and

Comprehensive Utilization of Red Mud Through the Recovery …

100 mA, respectively. The hysteresis loop of magnetic material (leach residue) was detected by vibrating samples magnetometer (VSM, Quantum Design PPMS DynaCool).

Results and Discussion Characterization of Red Med The chemical composition of the red mud is shown in Table 1. Fe, Al, Si and Na are the major constituents in the sample. The X-ray powder diffraction (XRD) pattern of the red mud is presented in Fig. 1. The phase analysis indicate that the red mud contains mainly hematite, gibbsite, calcite and quartz. Referring to two results, Fe in red mud samples mainly occurs in hematite, while Na mainly occurs in complex aluminosilicate species. Al and Si exist in not only complex aluminosilicate species, but also independent minerals such as gibbsite and quartz.

Recovery of Aluminium and Sodium To determine the optimum conditions in the sintering process, various parameters were considered as the factors affecting the recovery of Al and Na, including sintering temperature and time, as well as the mole ratio of CaO/SiO2 (calcium ratio), Na2O/Al2O3 (alkali ratio), and MgO/Fe2O3 Table 1 Chemical composition (major constituents) of the red mud (wt%) Element

Na

Al

Si

Ca

Fe

Mg

Content

4.6

11.23

5.14

3.27

26.01

0.096

Fig. 1 XRD pattern of the red mud sample

131

(magnesium iron ratio) in the raw material. The experiments were carried out to investigate the effect of these parameters and the results are illustrated in Fig. 2. The sintering temperature experiments were conducted in the range of 1050–1250 °C under the following conditions: sintering duration of 60 min, CaO/SiO2 of 2, Na2O/Al2O3 of 1 and MgO/Fe2O3 of 1. As shown in Fig. 2a, the extraction rate of both Al and Na increased gradually with increasing temperature from 1050 to 1150 °C, after which it slightly decreased with increasing temperature. The clinker sample began to melt at 1250 °C, which led the clinker to be dense and hard, so that it is laborious to crush and grind the clinker. Because of this effect, the maximum extraction rate was obtained at the temperature of 1150 °C, which was selected as the optimal sintering temperature in the subsequent experiments. The sintering time experiments were carried out in the range of 20–60 min at the sintering temperature of 1150 °C, CaO/SiO2 of 2, Na2O/Al2O3 of 1 and MgO/Fe2O3 of 1. The effect of sintering duration on the recovery of Al and Na is illustrated in Fig. 2b. It indicates that the extraction rates of Al and Na leveled off in the sintering duration range of 20– 50 min, and slightly higher when sintering duration reached 60 min. Therefore, in the subsequent experiments, the sintering duration was maintained at 60 min. The effect of the mole ratio of CaO/SiO2 (calcium ratio) in raw material on extraction of Al and Na was investigated in the range of 2.2–3.6 at sintering temperature of 1150 °C, duration of 60 min, mole ratio of Na2O/Al2O3 of 1 and MgO/Fe2O3 of 1. As shown in Fig. 2c, it can be observed that the extraction rate of Al was correlated with the calcium ratio. Within a certain range, the extraction rate of Al and Na kept increasing with the increased calcium ratio until 3. In the case of calcium ratios above 3, the extraction of Al slightly increased, while that of Na was almost constant. As the larger dose of additives means higher energy consumption, the calcium ratio of 3 was determined as the optimum condition in the sintering process. The effect of mole ratio of Na2O/Al2O3 (alkali ratio) in the raw material on extraction of Al and Na was studied by changing the alkali ratio in the range of 0.8–1.3, while keeping other parameters constant as following: sintering temperature of 1150 °C, duration of 60 min, CaO/SiO2 of 3 and MgO/Fe2O3 of 1. The result presented in Fig. 2d revealed that the extraction rate of both Al and Na increased gradually with the alkali ratio increasing from 0.8 to 1.2. When the alkali ratio was out of the range, there was no significant increase in the extraction of Al and Na. Therefore, the alkali ratio of 1.2 was regarded as a rational condition in the sintering process. In order to investigate the effect of MgO addition on the recovery of Al and Na, a MgO dose test was carried out at magnesium iron ratio of 0.6–1.6, and the result was

132

F. Lyu et al.

Fig. 2 Effects of a sintering temperature, b sintering duration, c calcium ratio, d alkali ratio, e magnesium ratio on the extraction of aluminum and sodium

presented in Fig. 2e. There is no significant effect on the recovery of Al and Na as the mole ratio of MgO/Fe2O3 (magnesium iron ratio) varied from 0.6 to 1.6. Therefore, it is possible to synthesize magnesium ferrite while recovering aluminum and sodium by once sintering. Through a series of conditional optimization experiments, the optimal parameters of the sintering process were determined as follows: sintering temperature of 1150 °C and duration of 60 min, the CaO/SiO2 of 3, the Na2O/Al2O3 of 1.2, and the MgO/Fe2O3 of 1. Finally, the extraction rates of Al and Na were obtained at approximately 74% and 95%, respectively.

Characterization of Samples XRD Pattern Analysis To understand the phase transformation of red mud during the sintering-leaching process, the sintered clinker under optimized conditions and the leach residue were analyzed by XRD. The XRD patterns were presented in Fig. 3. Comparing the XRD pattern of sintered clinker with that of the raw red mud presented in Fig. 1, it can be found that the main phase peaks of hematite, gibbsite, calcite and quartz disappeared completely. But the peaks of target product such as NaAlO2, magnesium ferrite and olivine appeared

Fig. 3 XRD patterns of the sintered clinker and leach residue

simultaneously. Given the solubility of NaAlO2 in alkaline conditions, it is probable that the Al and Na could be recovered by alkali extraction, which was performed in extraction experiments shown in Fig. 2. In addition, the phases of NaAlSiO4, garnet, perovskite, hedenbergite, and wollastonite were generated in the sintering process, which resulted in the low recovery of Al. Fe was transferred from

Comprehensive Utilization of Red Mud Through the Recovery …

the hematite phase to the magnesium ferrite phase, which could be obtained through magnetic separation more easily. The various new phases indicated that in the sintering process, the main components of red mud and additives reacted with each other through complex chemical reactions. In comparison with the XRD pattern of sintered clinker, it can be seen that the peaks of NaAlO2 and other related sodium aluminate disappeared completely, and the peaks of NaAlSiO4 lowered in the XRD pattern of leach residue, which indicated that sodium aluminate in the sintered clinker was dissolved in the extraction process. The peaks of other phases are basically unchanged except for slightly stronger intensity. These results also revealed that Al can be easily dissolved into an alkali solution only by converting it into sodium aluminate phases. Therefore, the formation of undesired aluminum-containing phases was responsible for the fact that the recovery of Al in the extraction test is not very high.

XRF Analysis The chemical composition of the process products was analyzed by XRF, of which the major constituents are listed in Table 2. Compared with the chemical composition of the raw red mud sample, the contents of Na, Ca and Mg were higher in the clinker sample due to the addition of Na2CO3, CaCO3 and MgO. Correspondingly, the content of other elements was lower than that in red mud. After extraction, the Na and Al contents in the leach residue were reduced to 0.44% and 3.23%, respectively, which further confirmed the relatively high recovery of Na and Al. As a result, the contents of other elements rose significantly. Such a low level of Na content of the residue indicated its promising prospects for reutilization. VSM Analysis The VSM measurement was performed on the leach residue of the sintered clinker, and the result was illustrated in Fig. 4. As MgO was added into the raw meal, it reacted with Fe2O3 in red mud during sintering process as per the following Eq. (3) [29, 30], which was confirmed by XRD pattern analysis subsequently. MgFe2O4 was known as ferrite with a spinel structure, which exhibits magnetic properties. Due to its insolubility, magnesium ferrite remained with the leach residue during the dissolution process, which

Table 2 Chemical composition (major constituents) of the clinker and leach residue (wt%) Sample

Na

Al

Si

Clinker

15.9

9.82

2.85

3.23

5.42

Leach residue

0.44

Ca 9.11 19.9

Fe

Mg

14.68

0.48

30.89

1.98

133

Fig. 4 Hysteresis loop of leach residue of sintered clinker

leads to the magnetism of leach residue. Leach residue also contained other insoluble phases, such as perovskite, olivine and garnet, leaving the leach residue with weak magnetic properties. As the hysteresis loop of leach residue shown in Fig. 4, its saturation magnetization was about 7.24 emu/g. Fe2 O3 þ MgO ¼ MgFe2 O4

ð3Þ

Removal of Lead Ions from Wastewater The leach residue contained spinel-type magnesium ferrite and low alkalinity, which gives it the potential as an adsorbent and as a refractory or thermal storage material. If it was further separated and purified, it could also be used in the fine chemical industry, gas-sensitive materials, and other fields. The magnetic properties of the leach residue is advantageous in the subsequent separation processes, so it has been studied as an adsorbent for heavy metal ions (Pb2+) in wastewater. The adsorption performance of the leach residue and the de-alkalized red mud on the lead ions in the solution were compared in Fig. 5. It can be seen from Fig. 5a that the removal rate of Pb2+ increased gradually with the increase of pH, but the performance of magnetic composite was significantly better than that of de-alkalized red mud. The magnetic composite almost completely removed Pb2+ from the solution at pH of 4. However, the higher the pH, the higher the probability of Pb2+ hydrolysis, so the adsorption of Pb2+ by two materials was investigated at different initial concentrations under pH of 4. Figure 5b shows that the removal rate still reached nearly 100% at the initial Pb2+ concentration of 50 mg/L when the dosage of the magnetic composite was 1 g/L. At the initial concentration of 80 mg/L, the adsorption capacity of Pb2+ by the magnetic

134

F. Lyu et al.

Fig. 5 Adsorption performances of the magnetic composite and de-alkali red mud for Pb2+ in aqueous solution: a the effect of pH; b the effect of initial Pb2+ concentration

composite was about 70 mg/g. Under the same conditions, the de-alkalized red mud performed much less satisfactorily, the adsorption capacity being only about 8 mg/g. The results of Pb2+ adsorption experiments indicate the magnetic composite’s potential in adsorption of heavy metal ions, and its promise in realizing the full utilization of red mud.

Conclusions In this study, a technical route was proposed to realize more comprehensive utilization of red mud. The process included sintering, alkaline leaching to recover Na and Al, and reutilization of the magnetic residue in removal of lead ions from wastewater. The main conclusions drawn were as follows: The systematic experiments indicated that the optimal conditions for aluminum and sodium recovery were determined as a sintering temperature of 1150 °C and duration of 60 min, the mole ratio of CaO/SiO2 of 3, Na2O/Al2O3 of 1.2, and MgO/Fe2O3 of 1 in the raw sinter feed material. Under these conditions, the recovery of aluminum and sodium reached 74% and 95%, respectively. The XRD analysis showed that in the sintering process, sodium aluminate, magnesium ferrite spinel, and olivine were formed by the reaction of aluminum and sodium, iron and magnesium, and calcium and silicon, respectively. Meanwhile, side reactions inevitably occurred among the species present. In the alkali leaching, sodium aluminate was recovered as a result of its solubility in hot alkali solution, and other products remained in the leaching residue. The XRF analysis supported these conclusions. The saturation magnetization of the leaching residue was determined as about 7.24 emu/g by VSM. The magnetic leaching residue exhibits excellent adsorption properties, and its adsorption capacity reached about 70 mg/g at the initial Pb2+ concentration of 80 mg/L. It may

be a promising candidate in wastewater treatment and other fields. Acknowledgements This work was supported financially by the National Key Research and Development Program of China (No. 2018YFC1901901), Natural Science Foundation of China (No. U1704252, 51704329), the Open Sharing Fund for the Large-scale Instruments and Equipments of Central South University, and Key Laboratory of Hunan Province for Clean and Efficient Utilization of Strategic Calcium-containing Mineral Resources (No. 2018TP002).

References 1. B.E.H. Jones, R.J. Haynes, I.R. Phillips (2015) Influence of amendments on acidification and leaching of Na from bauxite processing sand. Ecological Engineering 84: 435–442 2. Y. Zhao, J. Wang, Z. Luan, X. Peng, Z. Liang, L. Shi (2009) Removal of phosphate from aqueous solution by red mud using a factorial design. J Hazard Mater 165(1–3): 1193–1199 3. N. Deihimi, M. Irannajad, B. Rezai (2018) Characterization studies of red mud modification processes as adsorbent for enhancing ferricyanide removal. J Environ Manage 206: 266–275 4. C.R. Borra, Y. Pontikes, K. Binnemans, T. Van Gerven (2015) Leaching of rare earths from bauxite residue (red mud). Minerals Engineering 76: 20–27 5. K. Evans (2016) The History, Challenges, and New Developments in the Management and Use of Bauxite Residue. Journal of Sustainable Metallurgy 2(4): 316–331 6. P.B. Cusack, M.G. Healy, P.C. Ryan, I.T. Burke, L.M.T. O’ Donoghue, É. Ujaczki, R. Courtney (2018) Enhancement of bauxite residue as a low-cost adsorbent for phosphorus in aqueous solution, using seawater and gypsum treatments. Journal of Cleaner Production 179: 217–224 7. J. Zhang, S. Liu, Z. Yao, S. Wu, H. Jiang, M. Liang, Y. Qiao (2018) Environmental aspects and pavement properties of red mud waste as the replacement of mineral filler in asphalt mixture. Construction and Building Materials 180: 605–613 8. T. Tian, J. Zhou, F. Zhu, Y. Ye, Y. Guo, W. Hartley, S. Xue (2019) Effect of amendments on the leaching behavior of alkaline anions and metal ions in bauxite residue. Journal of Environmental Sciences 85: 74–81

Comprehensive Utilization of Red Mud Through the Recovery … 9. Y. Wang, T.-a. Zhang, G. Lyu, F. Guo, W. Zhang, Y. Zhang (2018) Recovery of alkali and alumina from bauxite residue (red mud) and complete reuse of the treated residue. Journal of Cleaner Production 188: 456–465 10. G. Liang, W. Chen, A.V. Nguyen, T.A.H. Nguyen (2018) Red mud carbonation using carbon dioxide: Effects of carbonate and calcium ions on goethite surface properties and settling. Journal of Colloid and Interface Science 517: 230–238 11. F. Lyu, N. Sun, W. Sun, S.A. Khoso, H.-h. Tang, L. Wang (2019) Preliminary assessment of revegetation potential through ryegrass growing on bauxite residue. Journal of Central South University 26(2): 404–409 12. Y. Hua, K.V. Heal, W. Frieslhanl (2017) The use of red mud as an immobiliser for metal/metalloid-contaminated soil: A review. Journal of Hazardous Materials 325: 17–30 13. S. Liu, X. Guan, S. Zhang, C. Xu, H. Li, J. Zhang (2017) Sintering red mud based imitative ceramic bricks with CO2 emissions below zero. Materials Letters 191: 222–224 14. Ujaczki, Eacute, Y. Zimmermann, C. Gasser, M. Molnár, V. Feigl, M. Lenz (2017) Red mud as secondary source for critical raw materials – Extraction study. Journal of Chemical Technology & Biotechnology 92 15. S. Rai, K.L. Wasewar, A. Agnihotri (2017) Treatment of alumina refinery waste (red mud) through neutralization techniques: A review. Waste Management & Research 35(6): 0734242X1769614 16. T. Guo, H. Yang, Q. Liu, H. Gu, N. Wang, W. Yu, Y. Dai (2018) Adsorptive removal of phosphate from aqueous solutions using different types of red mud. Water Science & Technology: wst2018182 17. X. Kong, M. Li, S. Xue, W. Hartley, C. Chen, C. Wu, X. Li, Y. Li (2017) Acid transformation of bauxite residue: Conversion of its alkaline characteristics. J Hazard Mater 324(Pt B): 382–390 18. S. Rai, K.L. Wasewar, D.H. Lataye, J. Mukhopadhyay, C.K. Yoo (2012) Feasibility of red mud neutralization with seawater using Taguchi’s methodology. International Journal of Environmental Science and Technology 10(2): 305–314 19. X. Wang, Y. Zhang, F. Lv, Q. An, R. Lu, P. Hu, S. Jiang (2015) Removal of alkali in the red mud by SO2and simulated flue gas

135

20. 21.

22.

23.

24.

25.

26.

27.

28.

29. 30.

under mild conditions. Environmental Progress & Sustainable Energy 34(1): 81–87 R.C. Sahu, R.K. Patel, B.C. Ray (2010) Neutralization of red mud using CO2 sequestration cycle. J Hazard Mater 179(1–3): 28–34 B. Deng, G. Li, J. Luo, Q. Ye, M. Liu, Z. Peng, T. Jiang (2017) Enrichment of Sc2O3 and TiO2 from bauxite ore residues. Journal of Hazardous Materials 331: 71–80 M.K. Hamdy, F.S. Williams (2001) Bacterial amelioration of bauxite residue waste of industrial alumina plants. Journal of Industrial Microbiology & Biotechnology 27(4): 228–233 D.Y. Liu, C.S. Wu (2012) Stockpiling and Comprehensive Utilization of Red Mud Research Progress. Materials (1996– 1944) 5(7): 1232–1246 K. Hyeok-Jung, S.-P. Kang, G.-C. Choe (2018) Effect of Red Mud Content on Strength and Efflorescence in Pavement using Alkali-Activated Slag Cement. International Journal of Concrete Structures and Materials 12(1) C. Liu, S. Ma, S. Zheng, Y. Luo, J. Ding, X. Wang, Y. Zhang (2018) Combined treatment of red mud and coal fly ash by a hydro-chemical process. Hydrometallurgy 175: 224–231 G. Li, M. Liu, M. Rao, T. Jiang, J. Zhuang, Y. Zhang (2014) Stepwise extraction of valuable components from red mud based on reductive roasting with sodium salts. Journal of Hazardous Materials 280: 774–780 C. Belviso, A. Kharchenko, E. Agostinelli, F. Cavalcante, D. Peddis, G. Varvaro, N. Yaacoub, S. Mintova (2018) Red mud as aluminium source for the synthesis of magnetic zeolite. Microporous and Mesoporous Materials 270: 24–29 W.-M. Xie, F.-P. Zhou, X.-L. Bi, D.-D. Chen, J. Li, S.-Y. Sun, J.Y. Liu, X.-Q. Chen (2018) Accelerated crystallization of magnetic 4A-zeolite synthesized from red mud for application in removal of mixed heavy metal ions. Journal of Hazardous Materials 358: 441– 449 M. Grayson, Kirk-Othmer encyclopedia of chemical technology. Volume 9, Enamels, porcelain or vitreous to ferrites, 1980 M. Zenger (1994) Modern ferrite technologies and products. International Journal of Materials & Product Technology (4–5): 265–280

A Review of Research on Alumina Extraction from High-Alumina Fly Ash and a New Method for Preparing Alumina by Electrotransformation Xiu-xiu Han, Ting-an Zhang, Guo-zhi Lv, Xi-juan Pan, and Da-xue Fu

Abstract

When bauxite and alumina resources are limited, high-alumina fly ash becomes a potential aluminum resource. The comprehensive utilization of high value-added elements in high-alumina fly ash is of great significance to resource circulation. In order to solve the difficult comprehensive utilization of valuable components in high-alumina ash problem, the existing traditional research methods of high-alumina ash are firstly summarized and compared in this paper. Following the review, a new method for the treatment of high-alumina fly ash by electrotransformation is proposed. This new method can realize reduction in slag volumes, with no waste acid, no alkali input required. It can be concluded that this new method can effectively treat high-alumina fly ash and realize the comprehensive utilization of valuable components of high-alumina fly ash. Keywords




High-alumina fly ash Alumina Electrotransformation




Research process




Overview of High-Alumina Fly Ash Properties of High-Alumina Fly Ash High-alumina fly ash is one of the largest emission of industrial solid wastes which is mainly produced by coal-fired power plants in China at the present stage [1]. Fly ash is a rich alumina resources with the alumina content up to 40–60%, which is equivalent to China’s medium-low grade bauxite [2–4], and is an important non-traditional X. Han
T. Zhang (&)
G. Lv
X. Pan
D. Fu Key Laboratory of Ecological Metallurgy of Multi-metal Intergrown Ores of Ministry of Education, Northeastern University, Shenyang, 110819, Liaoning, China e-mail: [email protected]

secondary alumina resource [5, 6]. With the electric power industry continuously developing, untreated high-alumina fly ash concentrated in Northern Shanxi and Northwest Inner Mongolia is discharged and deposited in large quantities every year [7, 8]. Presently, the high-alumina ash annual emission is about ten of million tonnes, and the cumulative amount exceeds 100 million tonnes [1, 9], which provides a stable and reliable resource guarantee for the large-scale alumina production. The chemical composition of high-alumina fly ash for a power plant in Inner Mongolia mainly includes alumina, silica, iron oxide, calcium oxide, etc. An example of a specific composition is shown in Table 1 [10]. In recent years, with the alumina industry continuous development, the demand for bauxite resources in China has been increasing year by year, and the excessive exploitation situation has become increasingly serious. At present, China’s bauxite mining and storage ratio is the highest in the world. And the bauxite has become one of the major minerals in short supply in China. By the end of 2016, China’s bauxite reserves accounted for less than 3% of the world’s bauxite reserves. However, its mining output accounted for more than 15% of the world’s total, ranking the 2nd in the world [11]. With the aggravation of the bauxite resource shortage in China, the import volume of bauxite in China reached 69 million t in 2017 [12]. Therefore, as a valuable secondary alumina-containing resource with high economic development value, high-alumina fly ash has become the focus of comprehensive utilization research at home and abroad. Such high-value utilization of non-traditional secondary resources can alleviate the contradiction between supply and demand of alumina in China, reduce the environmental burden brought by the high-alumina fly ash emission, and curb the trend of accelerated exhaustion of bauxite resources in China [13], and also have important significance for the economic cycle and sustainable development [14].

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_19

136

A Review of Research on Alumina Extraction …

137

Table 1 Chemical composition of high-alumina fly ash for a power plant in Inner Mongolia Composition

Al2O3

SiO2

Fe2O3

CaO

TiO2

Na2O

Others

Contents/%

41

40

2.4

3.7

1.4

0.2

11.3

(e) Containing radioactive elements such as uranium, and causing radioactive contamination. High-alumina fly ash contains a certain amount of radioactive elements such as U and Th, causing significant radioactive pollution to the surrounding environment and human health.

Hazard of High-Alumina Fly Ash As a kind of industrial solid waste, a large amount of high-alumina fly ash accumulated by thermal power plants in Inner Mongolia and Shanxi has caused great harm to human health and the surrounding environment.It can be concluded that the accumulation and emission of high-alumina fly ash mainly cause the following damage and influence. (a) Occupying a large area of agricultural land and resulting in the land resources waste. Large accumulation and emission of high-alumina fly ash produced by coal-fired power plants have caused a great waste of local agricultural land. At the same time, it also caused a great waste of human and financial resources. (b) Producing dust resulting in air pollution. The particle size of high-alumina fly ash is very small. In dry environments, the wind force above level 4 can make it produce secondary raise dust, which has a great impact on air quality and air visibility. As a result, PM2.5 levels in the region have increased to a large extent, causing serious air pollution in Inner Mongolia, Shanxi and other regions, and bringing great impact on the living environment of local residents. (c) Affecting water quality resulting in water pollution. Because of the rain water leaching effect, piled high-alumina fly ash pollutes the ground water. At the same time, a large amount of high-alumina fly ash is directly discharged into the nearby rivers and lakes from the power plant, which increases water turbidity, causes the sediment to block the river channels, makes the lakes shallow, deteriorates the water quality. (d) Contaminating soil and alkalinizing the soil. The part of high-alumina fly ash settling from the air, causes local soil alkalinization, destroys the ecological balance, and then affect the crop growth [15].

Comprehensive Utilization of High-Alumina Fly Ash In high-alumina fly ash and fly ash components, a large part of which are useful materials. Its use is increasingly widespread, and the utilization rate is also gradually increasing. According to the statistical data, the fly ash average comprehensive utilization rate in the world is about 25%, the utilization rate in Europe has exceeded 90%, the Netherlands’ is about 100%, France’ is about 75%. The utilization rate of fly ash in China is increasing year by year. It is estimated that the utilization rate of fly ash has increased from 24% in the 1980s to 70% in recent years [9, 16–18]. At present, high-alumina fly ash in China is mainly used in construction engineering, agriculture, cement, glass ceramics and new building materials, etc. [15, 19]. Meanwhile, as a potential secondary resource, high-alumina fly ash can also be used for extraction of high-value-added products such as alumina according to specific characteristics of its composition [20–22].

Traditional Process of Preparing Alumina from High-Alumina Fly Ash Summary and comparative analysis of the main alumina production processes, research progress and deficiency are taking out from high-alumina fly ash in this article. The problems need to be solved in extracting alumina from high-alumina fly ash are discussed. It is pointed out that slagging reduction, no waste acid, no alkali, recyclable and no secondary pollution production is the important development direction of alumina extraction technology from high-alumina fly ash, so as to realize high value resource utilization of high-alumina fly ash. As a high value-added utilization method of high-alumina fly ash, alumina extraction from high-alumina fly ash has long been concerned by many domestic and foreign scientific researchers [10]. At present, technologies for extracting alumina from high-alumina fly ash include the sintering method, acid-base combination method and acid leaching method, etc. [23–25].

138

X. Han et al.

Specific technical process, principle, progress and inadequacies are shown as follows.

large amount of local land resources. At the same time, this process also has high energy requirements, large limestone consumption, large silicon calcium residue discharge, and large cost, and other disadvantages.

Sintering Method The sintering process of extracting alumina from high-alumina fly ash mainly includes limestone sintering method [18], alkali lime sintering method [14, 26], pre-desilication—alkali lime sintering method [27], and so on. The technical principles are all to use the sintering process to destroy mullite in high-alumina fly ash and form mineral phases that can be dissolved in acid or alkali in order to realize the separation of aluminum-silicon [28]. The specific processes of these three sintering methods are shown as follows.

Limestone Sintering Method Limestone sintering method is the earliest method proposed at home and abroad to extract aluminum from high-alumina fly ash, and its technological method is relatively mature [29]. Meanwhile, limestone sintering method is also an important method for the treatment of medium-low grade bauxite and high-alumina fly ash [30]. And it has been industrialized at present. The limestone sintering process takes high-alumina fly ash and limestone as raw materials and mixes them in a certain proportion. After high temperature sintering, the silica and alumina in high-alumina fly ash produce calcium aluminate and dicalcium silicate respectively. The separation of aluminum and silicon is realized through the dissolution process. The main process of limestone sintering method includes desilication, carbonization, and so on. And the main chemical reactions of the limestone sintering process are shown as follows. 7Al2 O3 ðsÞ þ 12CaCO3 ðsÞ ¼ 12CaO
7Al2 O3 ðsÞ þ 12CO2 " ð1Þ 2SiO2 ðsÞ þ 2CaCO3 ðsÞ ¼ 2CaO
SiO2 ðsÞ þ 2CO2 " ð2Þ 12Na2 CO3 ðsÞ þ 12CaO
7Al2 O3 ðsÞ þ 5H2 OðlÞ ¼ 14NaAlO2 ðaqÞ þ 12CaCO3 # þ 10NaOHðaqÞ

ð3Þ

Al(OH)3 is obtained by desilication, carbon separation and filtration of sodium aluminate solution. The final Al2O3 product was obtained by roasting. While the process is mature, it also has some defects. That is, a large amount of solid waste residue is produced in the process of industrial production, which leads to the occupation and pollution of a

Alkali Lime Sintering Method Alkali lime sintering method takes high-alumina fly ash, lime and sodium carbonate as raw materials, and sintering at high temperature to produce soluble sodium metaaluminate and insoluble dicalcium silicate. Alumina is obtained by dissolution, separation, desilication, carbonation, roasting, and so on. And the main chemical reactions of alkali lime sintering method are shown as follows. 3Al2 O3
2SiO2 ðsÞ þ 3Na2 CO3 ðsÞ ¼ 2NaAlSiO4 ðsÞ þ 4NaAlO2 ðsÞ þ 3CO2 "

ð4Þ

Al2 O3 ðsÞ þ Na2 CO3 ðsÞ ¼ 2NaAlO2 ðsÞ þ CO2 "

ð5Þ

Na2 CO3 ðsÞ þ CaOðsÞ þ NaAlSiO4 ðsÞ ¼ Na2 CaSiO4 ðsÞ þ NaAlO2 ðsÞ þ CO2 "

ð6Þ

It is concluded that alkali lime sintering method has the advantages of simple process and low requirement for equipment. At the same time, it also has the problem of alkali content and lime content, as well as the disadvantages of high energy consumption, large cost, large slag discharge and large alkali content. Due to these reasons, some enterprises such as Datang Group have been losing money year after year in recent years and are facing the risk of bankruptcy [31].

Pre-desilication-Alkali Lime Sintering Method Pre-desilication-alkali lime sintering method is a new technology after the improvement of alkali lime sintering method [30]. The process mainly includes pre-desilication, sintering, dissolution, carbonization, roasting, and so on. And the main chemical reactions of pre-desilication-alkali lime sintering method are shown as follows. Al2 O3 ðsÞ þ 2NaOHðaqÞ ¼ 2NaAlO2 ðaqÞ þ H2 OðlÞ

ð7Þ

Al6 Si2 O13 ðsÞ þ 10NaOHðaqÞ ¼ 6NaAlO2 ðaqÞ þ 2Na2 SiO3 ðaqÞ þ 5H2 OðlÞ ð8Þ SiO2 ðamorphous stateÞ þ 2NaOHðaqÞ ¼ Na2 SiO3 ðaqÞ þ H2 OðlÞ

ð9Þ

A Review of Research on Alumina Extraction …

139

Al2O3 products were obtained by desilication, carbonation decomposition, seed separation and roasting of sodium aluminate solution. The conclusion of pre-desilication-alkali lime sintering shows that this process can not only reduce silica content, but also reduce the amount of silica calcium slag production. However, it also has some disadvantages, such as the alkaline slag formed in pre-desilication process is difficult to deal with, and a certain amount of aluminum loss would be caused in pre-desilication process [10]. At the same time, it also has high energy consumption, high slag alkali content, huge amount of silicon by-products such as active calcium silicate, and other shortcomings.

Acid-Base Combination Method [32] Anhydrous Na2CO3 and high-alumina ash are firstly mixed and roasted in a certain proportion with the acid-base combined method [10] to destroy the mullite and aluminosilicate glass phases in high-alumina ash. Then the aluminium is dissolved out by inorganic acid (hydrochloric acid or sulfuric acid), filtered and calcined to obtain alumina products. And the main chemical reactions of acid-base combination method are shown as follows. 3SiO2 ðsÞ þ Al2 O3 ðsÞ þ 2Na2 CO3 ðsÞ ¼ 2NaAlSiO4 ðsÞ þ Na2 SiO3 ðsÞ þ 2CO2 "

ð10Þ

2NaAlSiO4 ðsÞ þ 4H2 SO4 ðaqÞ þ mH2 OðlÞ ¼ Na2 SO4 ðaqÞ þ Al2 ðSO4 Þ3 ðaqÞ þ 2SiO2
ðm þ 4ÞH2 OðcolloidÞ

ð11Þ

Al2 ðSO4 Þ3 ðaqÞ þ 3Na2 CO3 ðaqÞ þ 3H2 OðlÞ ¼ 3Na2 SO4 ðaqÞ þ 2AlðOHÞ3 # þ 3CO2 "

ð12Þ

A summary of the acid-base combination method shows that the advantages of this process are high Al2O3 purity, high Al extraction rate and low energy consumption. At the same time, it also has the disadvantages of complex process, large acid and alkali consumption, difficult recycling, secondary pollution, and difficult impurity ion separation.

Acid Leaching Method High-alumina fly ash is firstly dissolved using inorganic acid (hydrochloric acid or sulfuric acid) by acid leaching method to produce the corresponding aluminum salts such as aluminum chloride and aluminum sulfate. Then the Al2O3 product is obtained through solid-liquid separation, filtration, evaporation crystallization, baking and other sections. The technological process of acid leaching is shown in Fig. 1 [18].

Fig. 1 Schematic diagram of technological process for acid method

The main chemical reactions of acid leaching method are shown as follows (taking hydrochloric acid as an example). Al2 O3 ðsÞ þ SiO2 ðsÞ þ 6HClðaqÞ ¼ 2AlCl3 ðaqÞ þ SiO2
H2 OðcolloidÞ # þ 2H2 OðlÞ ð13Þ Al2 O3 ðsÞ þ SiO2 ðsÞ þ 12HClðaqÞ þ 6NH4 FðaqÞ ¼ H2 SiF6 " þ 6NH4 ClðaqÞ þ 2AlCl3 ðaqÞ þ 5H2 OðlÞ ð14Þ It is concluded that acid leaching method is a relatively superior process for extracting alumina from high-alumina fly ash. And the main advantages of acid leaching method are simple production process, low unit energy consumption and low cost. However, its disadvantages are large amount of circulating acid, serious equipment corrosion, and environment by acid steam pollution, complex ion separation procedures, and so on.

Study on Alumina Extraction from High-Alumina Fly Ash by Electrotransformation [33, 34] In conclusion, it is urgent to find the replacement resources of bauxite and develop a new more economical and environmentally friendly process for extracting alumina from high-alumina fly ash. Based on the traditional hydrochloric

140

X. Han et al.

economy and environment sustainable development. On the other hand, it is of great significance to the high-valuable comprehensive utilization of high-alumina fly ash and the existing scientific research. At the same time, the challenges faced by this new method in the future industrialization mainly include difficult recovery of chlorine gas, serious corrosion of equipment, and so on. The schematic diagram of electrotransformation AlCl3 solution to prepare alumina is shown in Fig. 3. The main reactions involved in the electrotransformation process are: Cl− loses electrons and is oxidized to Cl2 gas; H+ and Al3+reacts with CO2 gas injected in solution to form aluminum salt precipitation containing carbon. At the same time, H+ gains electrons and is reduced to H2. Then Al2O3 product can be obtained by roasting aluminum salt precipitation containing carbon in muffle furnace. The main chemical reactions of electroconversion are shown as follows. Fig. 2 Process flow of extracting alumina from high-alumina fly ash by electrotransformation

mAl3 þ þ xCO2 þ ðn þ 2ÞH þ þ ð3m þ n þ 2Þe ¼ Alm Hn Cx Oy # þ ðn=2ÞH2 2Cl  2e ¼ Cl2 "

acid leaching method for extracting alumina, and inspired by chlor-alkali industry [35], a new method for preparing alumina by electrotransformation AlCl3 solution was proposed at Northeastern University. Electrotransformation is a new method that is different from traditional process. This new method combines chemical processes with metallurgical processes. And the method has entered the preliminary experimental stage. Experimental data [33] shows that alumina can be obtained from AlCl3 solution by this method. The conceptual process flow diagram is shown in Fig. 2. Compared with the traditional methods of extracting alumina from high-alumina fly ash, the electrotransformation new method has the advantages of short process, simple operation, simple equipment, slag reduction, no waste acid, no alkali and recycling. On the one hand, this technology reduces the capital investment and is of great significance to

ð15Þ ð16Þ

mAlCl3 þ xCO2 þ ðn þ 2ÞH þ þ ðn þ 2Þe ¼ Alm Hn Cx Oy # þ ð3m=2ÞCl2 þ H2 ð17Þ Alm Hn Cx Oy þ ð3m=4 þ n=4ÞO2 ¼ ðm=2ÞAl2 O3 þ xCO2 þ ðn=2ÞH2 O

ð18Þ

Notice: In above reaction Eqs. (15), (17), and (18), y = 2x.

Conclusions and Prospects From the summary and comparative analysis of traditional alumina extraction processes, following conclusions can be drawn.

Fig. 3 Schematic diagram of alumina preparation by electrotransformation AlCl3 solution

A Review of Research on Alumina Extraction …

(1) The traditional alumina processes have some shortcomings such as large amount of slag discharge, large amount of waste acid and alkali discharge, and complex technological process. (2) In view of the shortcomings existing in the traditional alumina extraction process, the new electrotransformation method proposed by Northeastern University has the advantages of slag reduction, no waste acid, no waste alkali, recycling and no secondary pollution. (3) This electrotransformation method is of great significance to high-value comprehensive utilization of high-alumina fly ash and environment sustainable development. It is believed that in the near future, electrotransformation new methods would have better research progress and would play an indispensable role in environmental protection.

Acknowledgements We very acknowledge the National Natural Science Foundation of China (Nos. U1710257, U51874078, U1508217), and the State Key Laboratory of Pressure Hydrometallurgical Technology of Associated Nonferrous Metal Resources (YY2016006).

References 1. Wang LP, Li C. New progress in technology of extracting alumina from fly ash [J]. Chemical Management, 2017, (21): 118. 2. Li XW. Production theory and technology of alumina [M]. Central south university press, 2010. 3. Yang ZY. Technology of alumina production [M] (revision). Technology of alumina production (revision). Central South University of Technology, 1993. 4. R.W. Bartlett. Alumina production process [J]. Comprehensive Utilization of Mineral Resources, 1989(5): 54–58. 5. Zhang ZJ. Research on alumina and other useful resources extraction from high-alumina fly ash [D]. Northwest University, 2007. 6. Shao LY, Chen JF, Shi YZ, et al. Composition of prefurnace coal mine and its contribution to the formation of high alumina coal ash in junge power plant [J]. Journal of China Coal Society, 2007(4): 411–415. 7. Wang LJ. Process progress of extracting alumina from fly ash [J]. Anhui Chemical Industry, 2018, 44(4): 6–8. 8. Li XG, Ding SQ, Zhuo JD, et al. Research status and industrial development of alumina extraction technology from fly ash [J]. Clean Coal Technology, 2018, 24(05): 5–15. 9. Zhao LJ. Non-bauxite alumina extraction and China’s fly ash resources [J]. Shenhua Science and Technology, 2017(4). 10. Yang QC, Ma SH, Xie H, et al. Research progress on alumina extraction from high-alumina fly ash [J]. Multipurpose Utilization of Mineral Resources, 2012(3): 3–7. 11. Ji FY, Liu M, Du XD, et al. Standardization study on recycling of alumina extracted from high-alumina powder coal ash [J]. China Standardization, 2017(23).

141 12. State Statistics Bureau. China Statistical Yearbook(2017) [M]. Beijing: China statistics press, 2018. 13. Sun L, Li HB. The development and utilization significance and technology comparative analysis of high-alumina fly ash [J]. Environment and Development, 2013(5): 47–49. 14. Pu W, Liang J, Lei ZM, et al. Current situation and technological progress of extracting alumina from fly ash [J]. Inorganic Salt Industry, 2016(2): 9–12. 15. Gao GQ, Li SC. Industrialization progress of alumina extraction from high-alumina fly ash in China [J]. Inner Mongolia science and technology and economy, 2012(1): 19–20. 16. Ou Yang XQ, Xia WM, Nai L. Comprehensive utilization current situation of fly ash resources [J]. Jiangxi Energy, 2002(4): 24–26. 17. Yao ZT, Ji XS, Sarker PK, et al. A comprehensive review on the applications of coal fly ash [J]. Earth-Science Reviews, 2015, 141: 105–121. 18. Liu LH. Study on the process and mechanism of alumina extraction from high-alumina fly ash [D]. 2015. 19. Hang HD. A new producing high purity alumina and cement method from fly ash or coal gangue [J]. Sichuan Building Materials, 1990(3): 45–47. 20. Mao WJ. Comprehensive utilization of fly ash: it is used to produce cement after extracting alumina [J]. New Building Materials, 1989(4): 27–31. 21. Ji HM, Wu P, Zhang Z, et al. Study on high purity alumina nanometer powders preparation using fly ash [J]. Earth Science Frontiers, 2005, 12(1): 220–224. 22. Gu DS, Hu JG. Application research status of fly ash [J]. Mining Technology, 2002, 2(2): 1–4. 23. Huang SW, Liu B, Li YS, et al. Study on germanium and aluminum extraction from fly ash by acid leaching [J]. Journal of nanchang university (engineering edition), 1999(3): 85–90. 24. Zhang XY, Ma HW, Wang JL. Experimental study on alumina preparation from high-alumina fly ash [J]. China Non-Metallic Mining Industry Herald, 2005(4): 27–30. 25. Huang JT, Yang JZ, Zhao K, et al. Technology of extracting alumina from high-alumina fly ash [C]. Academic seminar on efficient utilization of nonmetallic mineral resources, nonmetallic mineral resources branch, Chinese silicate society. 2008. 26. Tang Y, Chen FL. Alumina extraction from fly ash by alkali lime sintering method [J]. Mining and metallurgy engineering, 2008, 28 (6): 73–75. 27. Wang MW, Yang J, Ma HW, et al. Extraction of aluminum hydroxide from coal fly ash by pre-desilication and calcination methods [J]. Advanced Materials Research, 2011, 396–398: 706– 710. 28. Hui JB. Basic research on alumina extraction using water-thermal method from high-alumina fly ash [D]. 2015. 29. Wang YW, Qi XH, Li SJ, et al. Comparative study on alumina extraction technology from high-alumina fly ash [J]. Chemical Enterprise Management, 2015(22): 168–170. 30. Wang J. Technical analysis of alumina extraction process from high-alumina fly ash [J]. Jiugang technology, 2016(3): 32–36. 31. Wang AA. Research status on alumina extraction technology from high-alumina fly ash [J]. Contemporary chemical engineering research, 2019, 38(02): 136–138. 32. Liu J, Guo R, Shen YW, et al. Technical progress in extracting alumina from fly ash [J]. Henan Building Materials, 2017(6). 33. Han XX, Zhang TA, Lv GZ, et al. Investigation of alumina preparation from aluminum chloride aqueous solution by electrical transformation [J]. Hydrometallurgy, 2019(185): 30–37.

142 34. Han XX, Zhang TA, Lv GZ, et al. Effects of Additives on Alumina Preparation from Aluminum Chloride Solution by Electrolytic Transformation [J]. JOM, 2019, 71(4): 1574–1580.

X. Han et al. 35. Zhang AH. The present situation and development of China’s chlor-alkali industry [J]. Petrochemical technology and economy, 2004, 20(2): 40–49.

Effect of Sodium Alkali Concentration on Calcification–Carbonization Process Yang Chen, Ting-an Zhang, Guo-zhi Lv, and Xi Chao

Abstract

The calcification-carbonization method is a recently developed hydrometallurgical treatment process which can effectively realize the scale of Bayer process residue for aluminium and sodium recovery. In order to reduce the water consumption in the process, and increase extraction efficiency of the low alkali concentration solution generated in the process, the effects of varying alkali concentration of the calcification reaction solution and the alkali concentration of the carbonization reaction solution on the calcification carbonization process were investigated. The experimental results showed that at low alkali concentration (Na2O < 50 g/L), the solution had no significant effect on the calcification-carbonization process, as Al2O3 recovery rate fluctuates between 34–37%. As the alkali concentration of the solution increases (Na2O > 50 g/L), the Al2O3 recovery rate decreases to less than 20%. Keywords

Bauxite residue Alkali solution





Calcification-carbonation process Al2O3 recovery rate




Y. Chen
T. Zhang (&)
G. Lv
X. Chao 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] Y. Chen e-mail: [email protected] G. Lv e-mail: [email protected] X. Chao e-mail: [email protected]

Introduction Bauxite residue (also termed red mud by the alumina industry) is an alkaline solid waste byproduct produced during the refinement of alumina. An estimated 1–1.5 tons of residue is produced per ton of alumina production depending on bauxite mineralogy and production conditions [1, 2]. With the rapid growth demand of alumina worldwide, the estimated stockpiles of bauxite residue reached 3.6 billion tons by 2018, and the annual growth rate is about 120 million tons [3]. The effective management of bauxite residue storage areas remains a global problem faced by the alumina industry and regulators [4]. Although many strategies for improving bauxite residue management have been studied, such as extracting valuable metals [5, 6], using bauxite residue as raw materials for construction [7], and its use as an adsorbent for environmental treatment [8, 9], there is still lacking an implementable, scaled, cost-effective approach. Our previous research on low-grade bauxite and Bayer process residue has resulted in a proposed calcification-carbonization method as a bauxite residue treatment technique [10]. The calcification-carbonization method can realize the batch utilization of bauxite residue, and has the advantages of being a simple process with low cost. The thermodynamics and kinetics of the calcification carbonization process [11,12], the use of gibbsite-type residue and diaspore-type residue in different regions [13, 14], simulation and amplification of the reactor have been extensively and meticulously studied with promising results [15]. For further industrialization experiments, it is necessary to optimize the existing calcification carbonization process conditions to achieve the highest utilization of materials and energy. Figure 1 highlights the technological process of calcification and carbonization for residue treatment. We have found that the water consumption of the calcification carbonization process is substantial, as large amounts of

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_20

143

144

Y. Chen et al.

returned to the calcification and carbonization process as the reaction solution. Therefore, it was necessary to further study the influence of alkali concentration in the reaction solution on the calcification and carbonization process, particularly at low Na2O ( 99%, Shenyang Gas Manufacturing Co. Ltd.); CaO (Purity  98%, Sinopharm Chemical Reagent Co. Ltd, Shanghai, China) and NaOH (Purity  96%, Sinopharm Chemical Reagent Co. Ltd, Shanghai, China). All water used in this work was de-ionized.

Experimental Methods The effect of alkali concentration of the reaction solution on calcification and carbonization process is the principal focus of this study. Calcification experiments were performed in a ZRY-K01-0.5/10 autoclave (Weihai, China) with temperature controlled through a PID feedback control loop and agitation maintained at 300 rpm. Bauxite residue and lime were mixed in the vessel to achieve a 2.5:1 ratio of calcium to silicon, before the addition of alkali solution to achieve a 1:3 solid-liquid ratio. The Na2O concentrations of the reaction solution used in the calcification process were set to 10, 22, 50, 77.5, 100, and 200 g/L. The autoclave was heated to 160 °C and maintained at temperature for 60 min to allow for reaction. After the time was reached, the autoclave was air-cooled to 100 °C and then the cooling water was passed into the cooling pipe in the autoclave for rapid cooling to room temperature. The resultant slurry was filtered and washed with deionized water until filtrate pH was neutral, and dried (80 °C, 10 h) for use. Carbonization experiments were carried out in the same autoclave under the conditions of temperature 120 °C, CO2 partial pressure 1.2 MPa, and rotary speed 300 rpm. The previously calcined slag was mixed with alkali solutions of different concentrations as the liquid phase with a 1:5 solid-liquid ratio. The CO2 was injected into the autoclave when the temperature reached 120 °C and reaction was allowed to proceed for 90 min. When the time was reached, the cooling water was passed into the cooling pipe in the autoclave for rapid cooling to room temperature. The resultant slurry was filtered and dried (80 °C, 10 h) for use. Digestion experiments of the carbonated slag were performed in a DZKW-5-4 constant temperature water bath. NaOH (100 g/L) solution was placed in the water bath and heated to 60 °C, before adding the carbonated slag to the system. The slurry was allowed to react for 90 min. XRD analysis on powdered solids was carried out with a D8 Advance diffractometer (Bruker, Germany), operating at 40 kV and 40 mA with a Cu Ka radiation source, and the pattern data were collected in a 2h range from 10° to 90°. A field-emission scanning electron microscope (SEM, SU-8010, Hitachi, Japan. Conditions: Scan Speed = Capture CSS (80), Calibration Scan Speed = 21, voltage = 3 kV,

145

working distance = 8.5 mm) was used to analysis the morphology of the reaction products.

Calculation Method The ratio of calcium to silicon refers to the mass ratio of CaO to SiO2. The liquid-solid ratio refers to the ratio of the liquid phase volume (mL) to the solid phase mass (g). In the process of calcification and carbonization of bauxite residue, almost all of SiO2 enters the solid slag phase. Therefore, SiO2 can be used as a reference standard to measure the degree of variation of other components. gAl ¼

ðA=SÞP ðA=SÞL  100% ðA=SÞP

ð1Þ

In the formula, gAl (A/S)P (A/S)L

the extraction rate of Al2O3, %; the ratio of aluminum to silicon in the material before the aluminum stripping process; the ratio of aluminum to silicon in the material after the aluminum stripping process.

Results and Discussion Effect of Sodium Alkali Concentration on Calcification Process Figure 3 shows the recovery rate of alumina from the bauxite residue after treatment with different calcification alkali concentrations. It was seen that increasing alkali concentration in the reaction solution led to a general decrease in alumina recovery rate. However, when the alkali concentration is less than 50 g/L, the recovery of alumina is relatively stable around 35%. Subsequently increases in alkali concentration leads to a rapid decrease in alumina recovery rate. This suggests that it is feasible to realize the recycling of low alkali concentration solution while maintaining high extraction efficiency. The main purpose of the calcification transformation process is to convert the sodalite in the residue into calcium aluminosilicate hydrate phase (mainly garnet family minerals, i.e.) with Ca, Al and Si as the main combination elements through calcium oxide addition. During the reaction, Na enters the liquid phase as a result of sodalite dissolution, so the sodium alkali concentration in the liquid phase can reflect the degree of calcification transformation. Ca3Al2(SiO4)(OH)8 The sodium alkali concentration in the liquid phase after calcification transformation with different alkali

146

Y. Chen et al.

Fig. 3 The recovery rate of Al2O3 under different calcification alkali concentrations

concentrations was examined, and the results are shown in Table 2. It can be seen from the data in the table that when the initial reaction solution alkali concentration is not higher than 50 g/L, the alkali concentration of the solution increases after reaction, indicating that Na in the sodium aluminosilicate hydrate is replaced by Ca. When the initial reaction solution alkali concentration is higher than 50 g/L, the alkali concentration in the solution after the reaction decreases. It is indicated that the excessive concentration of alkali hinders the transformation of calcification, and some Na enters the solid phase. XRD analysis of calcified slag obtained under different reaction alkali concentration was performed and presented in Fig. 4. It can be seen that the phase of the calcified slag is basically the same under different alkali concentrations, mainly Ca3Al2(SiO4)(OH)8 (hydrated garnet), as the sodalite has undergone phase transformation. At low alkali concentration, in addition to Ca3Al2(SiO4)(OH)8 phase, some Ca3Fe2 (Si1.58Ti1.42O12) (Titanium iron garnet) are found in calcified slag. This is because the formation of hydrated garnet destroys the surface structure of the residue particles, forming a loose product layer, allowing Fe3+, Ti3+ ions to enter the hydrated garnet and produce isomorphic

Table 2 Alkali concentration in solution before and after calcification

substitution [16, 17]. With the increase of alkali concentration, an increasing amount of unreacted sodium aluminosilicate hydrate phase (Na8(Al6Si6O24)(OH)2.04(H2O)2.66) was detected in the calcified slag. This supports the Na2O results, indicating that excessive alkali concentration hindered the transition process of calcification. At the same time, the diffraction peak of Ca3Fe2(Si1.58Ti1.42O12) phase decreases with the increase of alkali concentration. The morphology of calcified slag produced at different alkali concentrations was observed and shown in Fig. 5. From the SEM images of calcified slag, the phase transformation during calcification is more sufficient at low alkali concentration, resulting in calcified slag mainly comprised of spherical hydrated garnet particles with complete morphology. With the increase of alkali concentration, it can be seen that there is a certain agglomeration phenomenon in the calcified slag: the individual particle size becomes larger, the morphology of the hydrated garnet particles becomes irregular, and there are many small particles attached to the surface, blocking further reactions of internal bauxite residue and affecting the formation of hydrated garnet. At the same time, according to the liquid phase analyses, it is speculated that the small particles attached to the surface of hydrated

Reaction stage

Na2O concentration in solution (g/L)

Before reaction

10

22

50

77.5

100

200

After reaction

22.10

35.48

65.91

75.07

98.34

192.74

Effect of Sodium Alkali Concentration …

147

1---Ca3Al2(SiO4)(OH)8 2---Ca3Fe2(Si1.58Ti1.42O12) 3--- Na8(Al6Si6O24)(OH)2.04(H2O)2.66 Fig. 4 XRD analysis of calcified slag at different alkali concentrations

Fig. 5 Morphology of hydrated garnet in calcified slag under different alkali concentrations

148

Y. Chen et al.

garnet may be formed due to some incomplete crystalline Na containing phases were formed.

Effect of Sodium Alkali Concentration on Carbonization Process In order to investigate the effect of the alkali concentration of the solution on the carbonization process, a comparative experiment was carried out. Under the same conditions of other experiments, only the alkali concentration of the reaction solution was changed. The experimental results of these tests are shown in Table 3. From the results, it can be seen that the change of alkali concentration during the carbonization process has an insignificant effect on the final recovery of Al2O3. Compared with the carbonization process, the alkali concentration in the calcification process has a greater impact on Al2O3 recovery. After the low alkali concentration calcification, even

if the carbonization solution is added with alkali, the final alumina recovery rate is 34.59%. However, after the high alkali concentration calcification, even if the carbonization solution is water, the final alumina recovery rate of Al2O3 is only 28.49%. The XRD pattern of the carbonized slag under different conditions is shown in Fig. 6. It can be seen from the figure that the phase of carbide slag has an unremarkable change under different alkali concentration. The phases are mainly calcium carbonate and a small amount of unreacted hydrated garnet under every condition. The intensity of the diffraction peak of the CaCO3 phase in sample A is higher than other conditions, indicating that the phase crystallinity is better under this condition. Figure 7 presents SEM micrographs of the carbide slag under different conditions. It can be seen from the figure that the hydrated garnet in the carbide slag decomposes completely under the condition of low alkali concentration calcification, and the morphology of the sodium carbonate

Table 3 Extraction rate of Al2O3 under different calcification and carbonization conditions Alkali concentration in carbonization (g/L)

Extraction rate of Al2O3 (%)

Sample

Alkali concentration in calcification (g/L)

Sample A

22

0

Sample B

22

30

34.59

Sample C

77.5

0

28.49

Sample D

77.5

30

25.75

Fig. 6 XRD patterns of carbonized slag under different conditions

35.02

Effect of Sodium Alkali Concentration …

149

Fig. 7 SEM images of carbonized slag at different alkali concentrations

particles is regular. Under the condition of high alkali concentration calcification, the carbonization decomposition of hydrated garnet in carbide slag is not obvious, and the agglomeration of particles is obvious. At the same time, a small amount of rod-like substances appeared in the phase formed by adding alkali during the carbonization process. The rod-like substances should be incomplete crystalline calcium sodium silicate hydrate (NaCa(HSiO4)) [18, 19].

decreases rapidly. According to the results, filtrate with low alkali concentration can be effectively recycled in the process of calcification or carbonization. Compared with the calcification process, the extraction rate of alumina was not significantly affected when the alkali concentration of carbonization reaction solution was 30 g/L. The low alkali concentration solution produced in the process can be recycled to reduce water consumption in the carbonization process.

Conclusion The effects of varying the alkali concentration of reaction solution on the calcification-carbonization process were investigated in this study. The experimental results showed that the low alkali concentration solution (Na2O < 50 g/L) has no obvious influence on the calcification and carbonization process, and can still achieve excellent recovery of alumina. The final Al2O3 recovery rates fluctuated between 34.11 and 36.74% at low Na2O. As the alkali concentration of the solution increased beyond 50 g/L, the Al2O3 recovery rate

References 1. Lv G Z, Zhang T A, Zhu X F (2014) Calcification-carbonation method for cleaner alumina production and CO2 utilization. JOM 66 (9):1616–1621. 2. Zhu X F, Zhang T A, Wang Y X (2016) Recovery of alkali and alumina in Bayer red mud by the calcification-carbonation process. International Journal of Minerals, Metallurgy, and Materials 23 (3):257–268. 3. Klauber C, Gräfe M, Power G (2011) Bauxite residue issues: II options for residue utilization. Hydrometallurgy 108:11–32.

150 4. Lv G Z, Zhang T A, Zhu X F (2016) Research on the phase transformation and separation performance in calcification-carbonation method for alumina production. TMS Light Metals 245–250. 5. Liu Y, Naidu R (2014) Hidden values in bauxite residue (red mud): recovery of metals. Waste Management 34(12):2662–2673. 6. Borra C R, Blanpain B, Pontikes Y (2016) Recovery of rare earths and other valuable metals from bauxite residue (red mud): a review. Journal of Sustainable Metallurgy 2(4):365–386. 7. Tsakiridis P E, Agatzinileonardou S, Oustadakis (2016) Red mud addition in the raw meal for the production of Portland cement clinker. Journal of Hazardous Materials 116(1):103–110. 8. Wang S, Ang H M, Tadé M O (2016) Novel applications of red mud as coagulant, adsorbent and catalyst for environmentally benign processes. Chemosphere 72(11):1621–1635. 9. Lopez, Soto, Arias (1998) Adsorbent properties of red mud and its use for wastewater treatment. Water Research 32(4):1314–1322. 10. Zhang T A, Lv G Z, Liu Y, et al. (2015) Method for recovering alkali and aluminum in course of treatment of Bayer red mud by using calcification-carbonization method[P]. United States Patent: US 9,963,353 B2.

Y. Chen et al. 11. Xie L Q, Zhang T A, Lv G Z, Zhu, X. F (2018) Direct calcification–carbonation method for processing of Bayer process red mud. Russian Journal of Non-Ferrous Metals 59(2):142–147. 12. Li R B, Zhang T A, Liu Y (2017) Characteristics of red mud slurry flow in carbonation reactor. Powder Technology 33:66–76. 13. Zhu X F, Zhang T A, Lv G Z, Guo, F F, Zhang, W G, Wang Y X (2017). Processing Diasporic Red Mud by the Calcification-Carbonation Method. Light Metals. 14. Xie L Q, Zhang T A, Lv G Z (2017) Treatment of diaspore bayer red mud with calcification-carbonation continuous process. Nonferrous Metals. 15. Li R B, Li X, Wang D (2018) Calcification reaction of red mud slurry with lime. Powder Technology 333:277–285. 16. Lu K Q, Dong J (1991) Non-cubic symmetry of garnet crystal structure. Journal of Synthetic Crystals 21(3):24–27. 17. H. B. Buergi (1993). Acta Crystall graphica B 49:832–838. 18. Zheng C Z (2015). Study on the formation process and carbonization decomposition of hydrated garnet:25–45. 19. Zhao X G, Lv L N (2010) Effect of Ca/Si Ratio on Morphology of Calcium Hydrate Prepared by Solution Method. The World of Building Materials 31(2):7–8.

Part II Aluminum Alloys, Processing and Characterization

Stress Characterization of Bore-Chilled Sand Cast Aluminum Engine Blocks in As-Cast and T7 Condition with Application of Neutron Diffraction J. Stroh, D. Sediako, G. Byczynski, A. Lombardi, and A. Paradowska








Abstract

Keywords

In an effort to improve vehicle fuel efficiency, aluminum (Al) alloys have been gaining upward momentum for use in automotive powertrain components such as engine blocks. Al alloys are lightweight and have good mechanical strength at engine operating temperatures; making them a suitable choice for engine block production. However, during the manufacturing process factors such as inhomogeneous cooling rates and/or coefficients thermal expansion mismatches in multi-material castings can lead to the development of residual stress. This is of particular concern for the relatively thin cylinder bridges, which are exposed to large thermo-mechanical loading during engine operation. The casting process used at Nemak for I6 engine block production does not utilise cast-in liners and therefore may be also be suitable for future mass-produced linerless blocks. This paper utilizes neutron diffraction and SEM/EDS to determine how the elimination of cast-in liners as well as a T7 heat treatment effects the magnitude of residual stress in cast Al (A319 type alloy) engine blocks. It was observed that the T7 treatment resulted in a significant reduction of the strain/stress in the Al cylinder bridge (up to *50% of the radial stress at the top of the bridge). In addition, the absence of the cast-in Fe liners allowed for unrestricted natural contraction of the Al bridge; leading to a combination of low tension and moderate compression as compared to the typically high tensile stress.

Stress characterization Neutron diffraction Bore-chilled engine block Aluminum alloys

J. Stroh
D. Sediako (&) University of British Columbia – Okanagan, 3333 University Way, Kelowna, V1V 1V7, Canada e-mail: [email protected] G. Byczynski
A. Lombardi Nemak of Canada Corporation, 4655 G.N. Booth Drive, Windsor, ON N9C 4G5, Canada A. Paradowska ANSTO, New Illawarra Rd, Lucas Heights, NSW 2234, Australia

Introduction In an effort to improve vehicle fuel efficiency, lightweight aluminum (Al) alloys have been replacing their heavier ferrous predecessors for use in automotive powertrain components such as engine blocks and cylinder heads. Al alloys have a high strength-to-weight ratio and have good casting characteristics; making them an excellent choice for engine block production [1]. However, generation of residual stresses during processing limits efficacy of Al alloys for service applications. The root cause for residual stress development is a thermal gradient that is produced by non-homogenous cooling, localized placement of the chilling system (Chills), and a coefficient of thermal expansion (CTE) mismatch due to varying material compositions [2]. For example, Al engine blocks typically require protective iron (Fe) cylinder liners to resist the reciprocating piston wear during operation. These Fe liners are typically cast-in and result in the development of tensile stresses along the cylinder bores during casting and post-heat treatment cooling due to the CTE mismatch between the gray Fe liners and the Al engine block. Lombardi et al. [3] characterized the residual stress in a six cylinder engine block manufactured with cast-in Fe liners. The results from this study indicated that high levels of tensile stresses (*170 MPa) were present in the aluminum cylinder bridge. The residual stresses measured in the study led to the conclusion that this magnitude of stress may induce permanent dimensional distortion or cracking in the engine block during in service operation, which can result in reduced engine efficiency, increased carbon emission or complete engine break down. Fortunately, this unwanted residual stress can be reduced by post processing techniques such as solution heat treatment

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_21

153

154

(SHT), annealing and artificial ageing [4–6]. For example, Godlewski et al. [7] used strain gauges to show that aging at 260 °C for 1 h reduced the residual stresses by approximately 50% in an aluminum E319 Residual Stress Test Casting (specific casting process that utilizes a copper chill to induce a large thermal gradient in “plate” specimen; resulting in repeatable residual stress development). In addition, solution heat treatment of A319 (hypoeutectic Al-Si-Cu alloy) Al engine blocks has also been carried out to analyze the relief in the residual axial strain via in-situ neutron diffraction [8]. The results from this study indicate that soaking the engine block at 470–500 °C for 8 h led to a significant reduction of the relatively large tensile stress present in the cylinder bridges; reducing the stress by approximately 50%. Furthermore, after applying a commercial T4 heat treatment, the stress in certain locations of the cylinder bridge were observed to be in compression rather than in tension. This transition from tension to compression is particularly beneficial; though it may still contribute to possible engine block distortion, it doesn’t cause cracking. Lombardi et al. [9] also confirmed that the magnitude of residual stress in the cylinder bridges of a V6 cast A319 Al alloy engine block was relieved significantly by a T7 heat treatment, machining and service testing. It was noted that the solutionizing part of the T7 treatment caused complete relief of residual stress at the bottom of the cylinder and partial relief at the top and middle, which was attributed to non-uniform cooling throughout the cylinder bore following solution treatment. Moreover, the over aging (T7) treatment caused the tensile residual stress to redistribute from the top of the cylinder to the bottom; corresponding to regions with coarse and fine microstructure, respectively. Consequently, upon completion of the T7 treatment, the residual stress was reduced by *90 and 10% at the top and bottom of the cylinder as compared to pre-heat treatment state (i.e. after thermal sand reclamation process). Moreover, the results from the study suggested that an increase in the cooling rate along the cylinder caused a significant refinement in the microstructure at the bottom of the cylinder relative to the top. This refinement leads to a higher strength at the bottom of the cylinder; likely reducing the susceptibility of the cylinder to rapid relief of residual stress at increased temperatures. In addition, the solution heat treatment and ageing (T7 temper) led to the precipitation of fine h-Al2Cu platelets within the interdendritic regions of the Al dendrites; which resulted in further increasing the materials yield strength and ultimate tensile strength [9]. The engine blocks described in the current article were produced using a precision sand casting technique that is based on the Cosworth process [10]. The modified Nemak-Cosworth casting process addresses the primary pitfall of the Cosworth process; the inherent poor microstructure caused by the relatively slow cooling rate in sand cast components. Microstructure refinement is achieved through the

J. Stroh et al.

implementation of bore chills in the cylinders of the engine block during casting. The high degree of cooling attributed to the chill effect, produces a near fully homogenous microstructure along the entire depth of the cylinder bridge [11]. Consequently, the mechanical properties of the cylinder bridges, which are exposed to the greatest level of thermo-mechanical loading during in-service operation, remain consistent along the entire depth of the cylinder (yield strength is approximately 210 [11] and 271 MPa [10] in the as-cast and T7 heat treated state, respectively). In addition to the incorporation of bore chills, Nemak has introduced a cooling channel (located approximately 10–20 mm below the deck head of the engine block) which passes through the middle of cylinder bridge; resulting in an in-service operation temperature reduction at the top the cylinder and consequently reduces the susceptibility of bridge failure. In addition to microstructural refinement, alternative manufacturing methods were necessary to minimize to development of residual stress during casting. For this, Nemak redesigned the manufacturing process by excluding the cast-in Fe liners from the casting process. Alternatively, following heat treatment of the cast engine blocks, the new manufacturing process incorporates pressed-in Fe liners. The removal of the cast-in Fe liners shall allow the molten Al to solidify more naturally around the cylinder bridges and consequently lead to a decrease in the magnitude of stresses present as compared the cast-in Fe lined engine block described in [8, 12]. The effect that these changes have on the microstructure and mechanical properties have been described in [11]; however, further investigation is necessary into the influence that these modifications have on the magnitude of stress present in the new cast engine blocks. This paper utilizes neutron diffraction to characterize the residual strain/stress profiles in two cast Al, inline six-cylinder engine blocks prior to mechanical insertion of the Fe liners. The first engine block is in the as-cast condition and the second block has been exposed to a T7 heat treatment. Both engine blocks described in this study have had the integrated bore chills removed prior to obtaining the strain measurements.

Experimental Procedure Two ex-situ neutron diffraction (ND) experiments were performed to determine the residual strain/stress profiles in Nemak’s precision sand cast, bore-chilled A319 Al engine blocks. The first experiment was performed on an as-cast engine block and was conducted at the High Flux Isotope Reactor at Oak Ridge National Laboratories (ORNL) in Oak Ridge, Tennessee. An identical experiment was performed on a T7 block on the Kowari beamline at the Australia Nuclear Science and Technology Organization (ANSTO) in Lucas

Stress Characterization of Bore-Chilled Sand Cast …

155

Fig. 1 Location of scan lines

Heights, New South Wales. The non-destructive scans were performed for each of the engine blocks (in as-manufactured state), a monochromatic neutron beam with a gauge volume of 2 mm  2 mm  10 mm was used to measure the strain along the entire depth (approximately 150 mm) of two cylinder bridges (i.e. bridge closest to edge of the block and the middle bridge, see Fig. 1). Two of the five bridges were measured to determine the uniformity of the strain/stress magnitude and profiles throughout the entire engine block. The strain was measured in the radial (perpendicular to cylinder), axial (direction of length of cylinder) and hoop (tangential to cylinder) orientations of the cylinder bridges. Utilizing generalized Hooke’s law (Eq. 1), the three orientations of strain (i.e. eR, eA, eH) were used to determine the stress (r) in each orientation, where E is the modulus of elasticity and m is poisson’s ratio. The methodology and theory is described in more detail in [12]. rR;H;A ¼

i E h v eR;H;A þ ðeR þ eA þ eH Þ 1þt 1  2v

ð1Þ

Results and Discussion Strain Profiles The strain measurements from the middle and edge bridge of the as-cast engine block are shown below in Fig. 2. It should be noted that Nemak has introduced a cooling channel (approximately 10–20 mm from the top) between the cylinder bridges to reduce the operating temperature at the top of the cylinder bridge and therefore the strain could not be measured at this location. The top of the cylinder bridge is typically the location of primary concern for manufacturers, since it is typically exposed to the greatest level of thermo-mechanical stress during in-service operation. Comparing the profiles presented in Fig. 2a, b, it is clear that both bridges experience very similar strains in the radial and axial orientation. The highest magnitude of tensile strain was measured in the radial orientation for both bridges in the as-cast block, reaching

upwards of +1500 µe. Conversely, the axial strain remained purely in compression throughout the entire length of the cylinder bridge; reaching approximately −1500 µe. The hoop strain in the edge bridge was less in magnitude below 25 mm as compared to the radial (tension) and axial (compression) orientations with the exception of the top two locations (i.e. 6 mm and 25 mm below the top of the engine block, see Fig. 2a). The hoop orientation of strain was not measured for the middle bridge of the as-cast engine block. The strain profiles from the T7 engine block are presented in Fig. 3. Comparing the results to the as-cast profiles in Fig. 2 it is clear that Nemak’s T7 heat treatment successfully alleviated a notable portion of the strain in each of the cylinder bridges that were measured. For example, the radial strain at the top of the cylinder bridge has been reduced by approximately 70% (from *+1300 to *+400 µe) and was observed to transition to compressive strain towards the second half of the bridge (i.e. below 70 mm position). In addition, a significant reduction in the already low magnitude hoop strain can also be observed from 25 to 100 mm below the top of the cylinder (reduced from *(−1000 to −500 µe) to *±50 µe). These results indicate that the T7 heat treatment caused a partial relaxation of the strain in all three orientations. Furthermore, the absence of cast-in Fe liners reduced the re-generation of strain during cooling of the engine block after heat treatment.

Stress Profiles The stress profile for the edge bridge of the as-cast engine block is present in Fig. 4. Similar to the as-cast strain profiles (see Fig. 2), the radial orientation at the top of the cylinder bridge (i.e. 6 mm position) shows the largest magnitude of stress, reaching approximately 100 MPa. Unlike the stress profiles presented in the work of Sediako, Lombardi et al. [12], which indicates that all three orientations of stress are in tension, the axial and hoop orientations remain purely in compression. Compressive stresses are typically of lesser concern for the engine block manufacturing, as these don’t cause cracking. These stresses however, may contribute to the possible distortion of the product.

156

J. Stroh et al.

Fig. 2 Strain profiles for as-cast aluminum engine block

Fig. 3 Strain profiles for T7 heat treated aluminum engine block

Fig. 4 Stress profile for the as-cast aluminum engine block

The stress profiles shown in Fig. 5a suggest that the T7 heat treatment partially alleviated the stress in the engine block, particularly the top of the cylinder bridge which reduced the radial strain from approximately 100 to 50 MPa. The relatively small change of stress for the rest of the cylinder bridge is likely the result of the already low magnitude of stress present in this section. The stress from approximately 25–50 mm in the T7 edge bridge is reduced

in larger magnitude as compared to the middle bridge (i.e. approximately −140 MPa versus −175 MPa, respectively); it has been postulated that the larger mass of Al at the very front of the engine block (i.e. due to structural support for ignition timing infrastructure and approximately twice as large wall thickness) causes the edge bridge to cool moderately slower than middle bridge after the T7 heat treatment. The slower cooling of the edge bridge results in a lower magnitude of contraction and therefore compressive stress as compared to the middle bridge. The combined effects of Nemak’s T7 heat treatment and unique integration of bore chills has led to the production of a cast Al engine block with significantly reduced stress development, notable increase in mechanical properties [10] and a highly refined and homogenized microstructure [11]. As a result, it is likely that engine’s susceptibility to premature failure (distortion or cracking) will decrease significantly (increased service life) and the operating pressures may increase now that useable strength has been improved. An increase in operating pressure and/or temperature will result in greater efficiency and lead to the production of “greener” vehicles.

Stress Characterization of Bore-Chilled Sand Cast …

157

Fig. 5 Stress profiles for T7 heat treated aluminum engine block

Conclusion This article presented the results from a residual stress analysis of the cylinder bridges in as-cast and T7 heat treated precision sand cast aluminum engine blocks. The engine blocks presented in this study were cast using a modified Nemak-Cosworth casting process which focused on improving microstructural properties (integration of bore and crankshaft girdle chills) and reducing the development of residual stress during casting (removal of cast-in iron liners). The following conclusions can be drawn from this work: (1) The removal of the cast-in iron liners from the casting process results in a significant reduction of the residual strain/stress development in cast aluminum engine blocks. This is partially attributed to the largely reduced restriction of aluminum contraction during the casting’s cooling down upon complete solidification. (2) Similar strain/stress profiles were observed in the edge and middle bridge of the as-cast and T7 engine blocks; indicating that Nemak’s specific manufacturing process produces uniform cooling with similar thermal gradients through each of the bridges. (3) T7 heat treatment was successful in alleviating a significant portion of strain from the cylinder bridges, particularly in the radial orientation which experienced the greatest magnitude of strain/stress. Specifically, the radial stress was reduced from 100 to 50 MPa at the top of the cylinder bridge (i.e. the location most prone to cracking and distortion, and exposed to the greatest level of thermo-mechanical loading).

References 1. J. Davis & Associates. and ASM International. Handbook Committee.. ASM International, 1993.

2. J. Robinson and D. Tanner, “The Magnitude of Heat Treatment Induced Residual Stresses and the Thermal Stress Relief of Aluminium Alloys,” Mater. Sci. Forum, vol. 404–407, pp. 355– 360, 2009. 3. A. Lombardi, C. Ravindran, D. Sediako, and R. MacKay, “Determining the Mechanism of In-Service Cylinder Distortion in Aluminum Engine Blocks with Cast-In Gray Iron Liners,” Metall. Mater. Trans. A Phys. Metall. Mater. Sci., vol. 45, no. 13, pp. 6291–6303, 2014. 4. B. Chen et al., “In situ neutron diffraction measurement of residual stress relaxation in a welded steel pipe during heat treatment,” Mater. Sci. Eng. A, 2014. 5. D. Lados, D. Apelian, and L. Wang, “Minimization of residual stress in heat-treated Al-Si-Mg cast alloys using uphill quenching: Mechanisms and effects on static and dynamic properties,” Mater. Sci. Eng. A, vol. 527, no. 13–14, pp. 3159–3165, 2010. 6. J. Rolph, A. Evans, A. Paradowska, M. Hofmann, M. Hardy, and M. Preuss, “Stress relaxation through ageing heat treatment - a comparison between in situ and ex situ neutron diffraction techniques,” Comptes Rendus Phys., vol. 13, no. 3, pp. 307– 315, 2012. 7. L. Godlewski, X. Su, T. Pollock, and J. Allison, “The effect of aging on the relaxation of residual stress in cast aluminum,” Metall. Mater. Trans. A Phys. Metall. Mater. Sci., vol. 44, no. 10, pp. 4809–4818, 2013. 8. Lombardi A, Sediako D, Machin A, Ravindran C and MacKay R (2017) Effect of solution heat treatment on residual stress in Al alloy engine blocks using neutron diffraction, Mater. Sci. Eng. A, 697(May): 238–247. 9. Lombardi A, D’Elia F, Ravindran C, Sediako D, Murty B and MacKay R (2012) Interplay Between Residual Stresses, Microstructure, Process Variables and Engine Block Casting Integrity, Metall. Mater. Trans. A, 43(13): 5258–5270. 10. Byczynski G and Mackay R (2019) The nemak cosworth casting process latest generation, Shape Casting 7th International Symposium, Springer International Publishing: 179–185. 11. Stroh J, Piche A, Sediako D, Lombardi A, and Byczynski G (2019) The Effects of Solidification Cooling Rates on the Mechanical Properties of an A319 Inline-6 Engine Block, The Minerals, Metals & Materials Society (TMS), vol. Light Metals 2019: 505– 512. 12. Sediako D, D’Elia F, Lombardi A, Machin A, Ravindran C, Hubbard C and Mackay R (2011) Analysis of Residual Stress Profiles in the Cylinder Web Region of an As-Cast V6 Al Engine Block with Cast-In Fe Liners Using Neutron Diffraction, SAE Int. J. Mater. Manuf., 4(1): 138–151.

Molecular Dynamics Simulations of the Solidification of Pure Aluminium Michail Papanikolaou, Konstantinos Salonitis, and Mark Jolly

Abstract

Despite the continuous and remarkable development of experimental techniques for the investigation of microstructures and the growth of nuclei during the solidification of metals, there are still unknown territories around the topic of nucleation during solidification. Such nanoscale phenomena can be effectively observed by means of Molecular Dynamics (MD) simulations which can provide a deep insight into the formation of nuclei and the induced crystal structures. In this study, MD simulations have been performed to investigate the solidification of Aluminium melt and the effects of process parameters such as the cooling rate and hydrostatic pressure on the final properties of the solidified material. A large number of Aluminium atoms have been used in order to investigate the grain growth over time solidification. The population of the Face Centred Cubic (FCC) and amorphous (or non-crystalline) phases has been recorded during the evolution of the process to illustrate the nanoscale mechanisms during solidification. Finally, the exothermic nature of the solidification process has been effectively captured by measuring the temperature of the Al atoms during grain formation. Keywords







Molecular dynamics Solidification Pressure Aluminium




Nucleation




Introduction In the early 1950 s Hall and Petch made the revolutionary observation that the grain size of metallic materials is correlated to their mechanical properties [1, 2]. More specifically, M. Papanikolaou (&)
K. Salonitis
M. Jolly Manufacturing Theme, Cranfield University, Cranfield, MK430AL, UK e-mail: m.papanikolaou@cranfield.ac.uk

1 they stated that smaller grain sizes lead to higher yield stress and mathematically described the relation between the yield stress and the average grain diameter, which is widely known as the Hall-Petch equation [1]. Later on, researchers expanded the research area around this topic and suggested that the grain size can also be correlated to the ductile-brittle transition, hardness, fatigue and creep behaviour [3]. The reason for the improvement of the mechanical strength for smaller grain sizes is that smaller grains hinder the movement of dislocations while higher external stress needs to be applied for their propagation. Several ways of improving the grain structure have been reported over the past decades. Three of the most popular ones for reducing the grain size are: (a) the use of alloying elements such as grain refiners [4], (b) controlling the cooling rate [5] and (c) controlling the pressure during casting [6]. More specifically, grain refiners foster heterogeneous nucleation and increase the number of nucleation sites in the melt. For high values of the cooling rate, the melt is quenched to a lower temperature than the equilibrium melting point. This circumstance promotes the formation of additional nuclei in the melt which in turn lead to grain refinement upon solidification [7]. The mechanism of grain refinement under high external pressure can be explained by considering the Clausius-Clapeyron relation which relates the slope of the temperature-pressure equilibrium for coexisting phases, e.g. liquid and solid, to the specific enthalpy for phase change and the specific volume change of the phase transition [8]. After some algebraic manipulation it can be concluded that the critical radius for nucleation decreases for higher values of pressure [9]. As a result, nuclei can be quickly formed when pressure is applied and the number of nuclei/grains per unit volume increases. The real time observation of the nucleation and grain refinement processes is not trivial as extremely high resolution is required. Although the experimental equipment and the adopted measurement techniques have remarkably evolved, there are still challenges associated with the real time observation of the nuclei formation during solidification

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_22

158

Molecular Dynamics Simulations of the Solidification …

in the bulk material [10]. Obtaining atomic resolution images from scattering and diffraction experiments is not yet feasible. On the other hand, the Classical Nucleation Theory (CNT) [11] frequently fails to accurately predict experimental nucleation rates [12] as it is based on the assumption that nucleation can occur with equal probability at any point within the melt, which does not hold in reality [13]. The aforementioned shortcomings can be addressed via the Molecular Dynamics (MD) simulation technique. This computer simulation method provides high resolution information while no ab initio assumptions are required for the physical system under examination. The first MD simulations on this topic considered quite small atom populations and were limited to two dimensions [14]. However, as suggested by Streitz et al. [15], in order to reproduce realistic and size-independent solidified structures via means of MD simulations large atom populations should be considered. The evolution of the computational power and the development of high-performance computing clusters has allowed for large scale MD simulations of solidification. Large MD simulations have significantly contributed to the in-depth understanding of the phenomena taking place during solidification and the process parameters affecting the structural properties of the solidified structure. Some of the topics investigated include the effect of the cooling rate on the solidified structure [16], the structural and dynamical properties of rapidly quenched metals [17], nucleation and grain growth [18]. The largest MD simulation ever reported has been performed by Shibuta et al. [19] who investigated homogeneous nucleation from an undercooled iron melt containing 1 billion atoms. Based on their observations, the authors proposed a novel nucleation model, which is based in heterogeneity. In contrast to the classical nucleation models (spontaneous and sporadic) they found that small satellite-like grains are formed in the vicinity of earlier formed grains. Considering the challenges encountered during the real-time experimental observation of the nucleation process during solidification, it is clear that MD simulations offer some significant advantages compared to other computational methods and experimental techniques, which lack atomic resolution and make ab initio assumptions. In this

Table 1 Simulation parameters

159

study, MD simulations have been employed to investigate the effects of the cooling rate and pressure on the properties of solidified aluminium. The obtained results suggest that the cooling rate significantly affects the grain nucleation and growth as well as the grain distribution in the solidified structure. Therefore its value should be thoughtfully controlled in order to obtain the desired material properties. On the other hand, pressure increases the melting point, increases the growth rate but does not significantly alter the final average grain size.

Methodology The simulation setup consists of a simulation box with periodic boundary conditions containing 1,000,188 Aluminium (Al) atoms. The Al atoms are initially arranged in a FCC lattice with a lattice constant equal to 4.046 Å. The Finnis-Sinclair (FS) potential [20] has been employed to model the interatomic interactions between the Al atoms. The FS potential has been extensively used to investigate nucleation and solidification via MD simulations [19, 21, 22]. The FS potential takes into account the local density dependence of the interatomic forces by considering a repulsive term and an attractive term (square root) which is dependent on the forces exerted on a specific atom by its neighbours: Etot ¼

N X N N X   1X pffiffiffiffi qi Vij rij  A 2 i¼1 j¼1 i¼1

ð1Þ

where Vij is the potential energy for the atom pair ij, rij the distance between the atoms i and j, A is the binding energy and qi the local electronic charge in the vicinity of atom i. The Al melt was prepared by isothermally heating the Al crystal up to 1173 K using the isothermal-isobaric ensemble (NPT) ensemble. The melt was subsequently equilibrated for 20,000 timesteps; at the end of the equilibration process there were no FCC atoms left in the domain. Following the equilibration stage, the melt was quenched under three cooling rates (1, 2 and 4 K/ps) and three values of pressure (0, 0.5 and 1 GPa), i.e., 9 simulations were performed in total. Following the quenching process, the simulation

Number of atoms

1,000,188

Material

Aluminium

Ensemble

NPT

Potential

Finnis-Sinclair (FS)

Timestep (fs)

2

Pressure (GPa)

0, 0.5 and 1

Cooling rate (K/ps)

1, 2 and 4

160

M. Papanikolaou et al.

Fig. 1 Solidified structure for a cooling rate of a 1 K/ps, b 2 K/ps and c 4 K/ps

domain was further equilibrated for 100,000 timesteps (2 ns) at 273 K in order to allow for some additional time for the FCC grains to grow and obtain the final solidified structure. The values of the simulation parameters are summarised in Table 1.

In this study, the per-atom temperature was evaluated in order to visualise the temperature distribution over the simulation domain. The per atom temperature has been measured using the equipartition theorem [23] as stated below:

Molecular Dynamics Simulations of the Solidification …

161

Fig. 2 Nucleation for a cooling rate of 1 K/ps at a 543 K, b 525 K, c 507 K and d 489 K

KE T ¼ dim 2 NkB

ð2Þ

where N is number of atoms, kB = 1.38
10−23 m2 kg s−2 K−1 the Boltzmann constant and dim ¼ 3 the number of dimensions of the simulation. The kinetic energy (KE) is given by:

KE ¼

N 1X mi v2i 2 i¼1

ð3Þ

where mi and vi are the mass and velocity of the atom i at a specific timestep. With regard to structural properties, the Radial Distribution Function (RDF) has been employed as a metric of the

162

M. Papanikolaou et al.

Fig. 3 Normalised potential energy versus temperature for a cooling rate of a 1 K/ps, b 2 K/ps and c 4 K/ps

local ordering of atoms. The RDF has been calculated as follows:   V NðrÞ gðrÞ ¼ 2 ð4Þ N 4pr 2 Dr where V is the system volume, N the population of the simulation atoms, and NðrÞ the number of atoms lying within the spherical shell r  Dr=2\ri \r þ Dr=2: The open source LAMMPS Molecular Dynamics Simulator [24] has been used to perform the large scale MD simulations. Each simulation was performed on 32 cores of the Delta HPC facility of the Cranfield University while the corresponding running time ranged between 6 and 24 h. The OVITO open source software [25] along with its integrated modifiers and some in house post processing scripts were utilised for the post-processing and visualisation of the results.

Results and Discussion As mentioned in the previous section, the prepared Al melt was quenched under 3 different cooling rates (1, 2 and 4 K/ps). The effect of the cooling rate on the solidified structure is illustrated in Fig. 1. It is evident that the cooling rate significantly affects the number of grains in the final structure. More specifically, additional grains are formed during rapid quenching; this is because solidification occurs in a wider range of temperatures compared to lower cooling rates and additional nucleation points are generated. This result is in agreement with previous investigations [16]. In order to visualise the nucleation process, the cluster analysis modifier of the OVITO software [25] was employed. Clusters were identified via a distance based neighbour criterion, according to which two atoms separated by a distance smaller than a specified value belong to the

Molecular Dynamics Simulations of the Solidification …

Common Neighbour Analysis

163

Potential Energy Distribution

(a)

(b)

Fig. 4 Common neighbour analysis and potential energy distribution for a cooling rate of 1 K/ps a T = 543 K and b T = 489 K

same cluster or grain. This critical value was set equal to the lattice constant of Aluminium (4.046 Å). The grain formation for a cooling rate of 1 K/ps is shown in Fig. 2. It can be observed that grains grow in a sphere-like manner while the atoms of the liquid/melt phase get attached to the potential FCC sites of the grain boundary interface. Nucleation and solidification are accompanied by the release of the latent heat of crystallisation and a steep reduction of the potential energy; this is because the FCC crystal phase is energetically favourable. The effects of pressure and cooling rate on the potential energy have been investigated. As shown in Fig. 3, the potential energy drops linearly with temperature for all cooling rates under examination. However, lower cooling rates contribute to a steeper reduction of the potential energy when solidification

commences, i.e. solidification occurs over a shorter range of temperatures. As expected, the magnitude of the potential energy of the system increases with pressure. This is more pronounced when the Al atoms are in the melt phase. Finally, it can be observed that solidification commences at higher temperatures when pressure is high; this is in agreement with previous investigations which suggest that the melting point of metals strongly depends on the static pressure [26]. Figure 3 provides a quantitative estimate of the potential energy evolution during the process. However, in order to obtain a clearer understanding of the local potential energy evolution during the solidification process, the per atom potential energy was calculated and averaged over time windows of Nts =50 timesteps. Nts is the total number of

164

M. Papanikolaou et al.

Fig. 5 Evolution of Face Centred Cubic (FCC) and amorphous (AMO) populations over time for a cooling rate of a 1 K/ps, b 2 K/ps and c 4 K/ps

timesteps of the quenching process, being dependent on the cooling rate. In Fig. 4, the results of the Common Neighbour Analysis (CNA) and the local potential energy are being compared for identical temperature values. As expected, the potential energy is not uniformly distributed over the simulation domain but lower values (blue colour) can be observed at the areas occupied by grains, where the energetically favourable FCC and HCP phases are dominant. For the identical reason, the potential energy of the atoms at the grain boundaries or the ones corresponding to the liquid phase, which are non-crystalline, is higher. In Fig. 5 the populations of the Face Centred Cubic (FCC) and amorphous (AMO) structures have been plotted over time. As expected, the population of the amorphous structures is initially (Timestep = 0) equal to the total

number of atoms (106), because Al is in the molten state. As the simulation temperature drops, the population of the amorphous phase undergoes a steep decay. This abrupt change corresponds to the point in time when the first nuclei (grains) are generated. At the same timestep and for the same reason, the population of the FCC phase starts to sharply rise. Towards the end of the quenching and equilibration processes, the populations of both phases asymptotically reach a constant value. It has to be mentioned that high cooling rates lead to high populated FCC phase and consequently to low populated amorphous phase. This is because of two main reasons: (a) high cooling rates lead to the rapid immobilisation of atoms while there is no sufficient time to obtain the favourable FCC/HCP structure and (b) high cooling rates lead to the formation of a high number of

Molecular Dynamics Simulations of the Solidification …

165

Fig. 6 Average grain size for a cooling rate of a 1 K/ps, b 2 K/ps and c 4 K/ps

grains resulting in increased area of grain boundaries and additional atoms being in amorphous state. As stated in the introduction, a large variety of mechanical properties of metals depend on the average grain size. In Fig. 6 the average grain size is plotted as a function of the timestep for various cooling rates (1, 2, 4 K/ps). During quenching, the average grain size starts sharply increasing when the first grains are formed. This sharp increase is followed by a linear and an asymptotic one, as the grains obtain their final size during equilibration. In Fig. 6 it can be observed that the cooling rate plays a significant role on the average grain size. For the lowest cooling rate (1 K/ps), the average grain size is about equal to 1000 atoms. The corresponding equivalent diameters (dg ) were calculated (assuming spherical grains) as follows:

sffiffiffiffiffiffiffiffi 3 Nm dg ¼ 2
4 3 pq

ð5Þ

where N is the number of the grain atoms, m ¼ 4:48
1026 kg the mass of an Al atom and q ¼ 2710 kg/m3 the Aluminium density. On the other hand, although pressure increases the melting point and boosts nucleation it does not appear to significantly affect the final grain size. The final part of this investigation is focused on measuring the local temperature over the simulation domain and exploring the exothermic nature of the nucleation process. The local (per atom) temperature has been measured using Eqs. (2) and (3). Similarly to the estimation of the local potential energy, in order to obtain an accurate measurement,

166

M. Papanikolaou et al.

Common Neighbour Analysis

Temperature distribution

(a)

(b)

Fig. 7 Common Neighbour Analysis and local temperature distribution for a cooling rate of 1 K/ps at a T = 525 K and b T = 507 K

the temperature of each atom was calculated and averaged over time windows of Nts =50 timesteps, where Nts is the total number of timesteps of the quenching process, being dependent on the cooling rate. In Fig. 7 the results of the Common Neighbour Analysis are being compared to the corresponding temperature profiles when the average domain temperature is equal to (a) 525 K and (b) 507 K. It is apparent that the temperature in the vicinity of the formed grains is much higher compared to the surrounding melt. The elevated temperature at the region of the grains is a result of the release of the latent heat of crystallisation. As quenching proceeds (Fig. 7b), it can be observed that the temperature of

the simulation domain (melt and grains) drops while the more recently formed grains can still be spotted due to their elevated temperature.

Conclusions In this study, Molecular Dynamics (MD) simulations have been employed to investigate the effects of both the cooling rate and the applied pressure on the solidification of pure Aluminium (Al). The interactions between the Al atoms were modelled using the Finnis-Sinclair (FS) potential.

Molecular Dynamics Simulations of the Solidification …

A simulation domain containing 1 million Al atoms arranged in a FCC lattice was initially heated up to 1173 K and equilibrated. Subsequently, the prepared Al melt was quenched to 273 K under various cooling rates (1, 2 and 4 K/ps) and values of pressure (0, 0.5 and 1 GPa). Quenching was followed by a final equilibration stage in order to allow the simulation domain to obtain its final solidified structure. The main conclusions drawn from this study are summarised below: • In this investigation, the exothermic nature of the solidification process (release of the latent heat of crystallisation) has been effectively captured via MD simulations, which do not make any ab initio assumptions (unlike CFD or coarse grained models). According to the results, solidification occurs in a wider range of temperatures when the cooling rate is high. • MD offers the advantage of atomic resolution, which allows for the real time observation of the solidification/ nucleation kinetics and dynamics. The grain size has been found to be dependent on the cooling rate. More specifically, high cooling rates contribute towards the formation of a large number of small grains while low cooling rates lead to fewer but larger ones. • This is the first investigation on the effects of pressure on the solidification of pure Al via means of MD. The obtained results suggest that although high pressure boosts nucleation and increases the melting point, the average grain size appears to be independent of the applied pressure. Acknowledgements The authors would like to acknowledge the UK EPSRC project “Energy Resilient Manufacturing 2: Small Is Beautiful Phase 2 (SIB2)” for funding this work under grant EP/P012272/1.

References 1. E.O. Hall, The Deformation and Ageing of Mild Steel: III Discussion of Results, Proc. Phys. Soc. Sect. B. 64 (1951) 747– 753. https://doi.org/10.1088/0370-1301/64/9/303. 2. N.J. Petch, The cleavage strength of polycrystals, J. Iron Steel Inst. 174 (1953) 25–28. 3. R.W. Armstrong, The influence of polycrystal grain size on several mechanical properties of materials, Metall. Mater. Trans. B. 1 (1970) 1169–1176. https://doi.org/10.1007/bf02900227. 4. K.T. Kashyap, T. Chandrashekar, Effects and mechanisms of grain refinement in aluminium alloys, Bull. Mater. Sci. 24 (2001) 345–353. 5. M.A. Easton, D.H. StJohn, Improved prediction of the grain size of aluminum alloys that includes the effect of cooling rate, Mater. Sci. Eng. A. 486 (2008) 8–13. https://doi.org/10.1016/j.msea.2007.11. 009. 6. P. Ma, Z.J. Wei, Y.D. Jia, C.M. Zou, S. Scudino, K.G. Prashanth, Z.S. Yu, S.L. Yang, C.G. Li, J. Eckert, Effect of high pressure solidification on tensile properties and strengthening mechanisms of Al-20Si, J. Alloys Compd. 688 (2016) 88–93. https://doi.org/10. 1016/j.jallcom.2016.07.016.

167 7. S. Shabestari, M. Malekan, Thermal analysis study of the effect of the cooling rate on the microstructure and solidification parameters of 319 aluminum alloy, Can. Metall. Q. 44 (2005) 305–312. https://doi.org/10.1179/cmq.2005.44.3.305. 8. Y.A. Cengel, M.A. Boles, Thermodynamics: an engineering approach, Sea. 1000 (2002) 8862. 9. J.J. Sobczak, L. Drenchev, R. Asthana, Effect of pressure on solidification of metallic materials, Int. J. Cast Met. Res. 25 (2012) 1–14. 10. N. Iqbal, N.H. van Dijk, S.E. Offerman, M.P. Moret, L. Katgerman, G.J. Kearley, Real-time observation of grain nucleation and growth during solidification of aluminium alloys, Acta Mater. 53 (2005) 2875–2880. https://doi.org/10.1016/j.actamat. 2005.02.045. 11. M. Volmer, A. Weber, Keimbildung in übersättigten Gebilden, Zeitschrift Für Phys. Chemie. 119 (1926) 277–301. 12. E.D. Zanotto, P.F. James, Experimental tests of the classical nucleation theory for glasses, J. Non. Cryst. Solids. 74 (1985) 373– 394. 13. J. Russo, H. Tanaka, The microscopic pathway to crystallization in supercooled liquids, Sci. Rep. 2 (2012) 505. 14. F. Celestini, J.-M. Debierre, Nonequilibrium molecular dynamics simulation of rapid directional solidification, Phys. Rev. B. 62 (2000) 14006–14011. https://doi.org/10.1103/physrevb.62. 14006. 15. F.H. Streitz, J.N. Glosli, M. V Patel, Beyond finite-size scaling in solidification simulations, Phys. Rev. Lett. 96 (2006) 225701. 16. Z.Y. Hou, K.J. Dong, Z.A. Tian, R.S. Liu, Z. Wang, J.G. Wang, Cooling rate dependence of solidification for liquid aluminium: a large-scale molecular dynamics simulation study, Phys. Chem. Chem. Phys. 18 (2016) 17461–17469. https://doi.org/10.1039/ c6cp02172g. 17. B. Shen, C.Y. Liu, Y. Jia, G.Q. Yue, F.S. Ke, H.B. Zhao, L.Y. Chen, S.Y. Wang, C.Z. Wang, K.M. Ho, Molecular dynamics simulation studies of structural and dynamical properties of rapidly quenched Al, J. Non. Cryst. Solids. 383 (2014) 13–20. 18. A. Mahata, M.A. Zaeem, M.I. Baskes, Understanding homogeneous nucleation in solidification of aluminum by molecular dynamics simulations, Model. Simul. Mater. Sci. Eng. 26 (2018) 025007. https://doi.org/10.1088/1361-651x/aa9f36. 19. Y. Shibuta, S. Sakane, E. Miyoshi, S. Okita, T. Takaki, M. Ohno, Heterogeneity in homogeneous nucleation from billion-atom molecular dynamics simulation of solidification of pure metal, Nat. Commun. 8 (2017) 10. https://doi.org/10.1038/s41467-01700017-5. 20. M.W. Finnis, J.E. Sinclair, A simple empirical N-body potential for transition metals, Philos. Mag. A. 50 (1984) 45–55. 21. Y. Watanabe, Y. Shibuta, T. Suzuki, A molecular dynamics study of thermodynamic and kinetic properties of solid–liquid interface for bcc iron, ISIJ Int. 50 (2010) 1158–1164. 22. J. Liu, R.L. Davidchack, H.B. Dong, Molecular dynamics calculation of solid–liquid interfacial free energy and its anisotropy during iron solidification, Comput. Mater. Sci. 74 (2013) 92–100. https://doi.org/10.1016/j.commatsci.2013.03.018. 23. K. Huang, Statistical mechanics, Wiley, 1987. https://www.wiley. com/en-gb/Statistical+Mechanics,+2nd+Edition-p9780471815181 (accessed August 14, 2019). 24. LAMMPS Molecular Dynamics Simulator, (n.d.). https://lammps. sandia.gov/. 25. A. Stukowski, Ovito Open Visualization Tool, (2015). 26. H. Schlosser, P. Vinet, J. Ferrante, Pressure dependence of the melting temperature of metals, Phys. Rev. B. 40 (1989) 5929– 5935. https://doi.org/10.1103/physrevb.40.5929.

Nanoindentation and Cavitation-Induced Fragmentation Study of Primary Al3Zr Intermetallics Formed in Al Alloys Abhinav Priyadarshi, Tungky Subroto, Marcello Conte, Koulis Pericelous, Dmitry Eskin, Paul Prentice, and Iakovos Tzanakis

Abstract

Mechanical properties of primary Al3Zr crystals and their in situ fragmentation behaviour under the influence of a single laser induced cavitation bubble have been investigated using nanoindentation and high-speed imaging techniques, respectively. Linear loading of 10 mN was applied to the intermetallics embedded in the Al matrix using a geometrically well-defined diamond nanoindenter to obtain the mechanical properties at room temperature conditions. Primary Al3Zr crystals were also extracted by dissolving the aluminium matrix of an Al-3wt% Zr alloy. The extracted primary crystals were also subjected to cavitation action in deionized water to image the fracture sequence in real time. Fragmentation of the studied intermetallics was recorded at 500,000 frames per second. Results showed that the intermetallic crystals fail by brittle fracture mode most likely due to the repeatedly-generated shock waves from the collapsing A. Priyadarshi (&)
I. Tzanakis Faculty of Technology, Design and Environment, Oxford Brookes University, Oxford, OX33 1HX, UK e-mail: [email protected] T. Subroto
D. Eskin Brunel Centre for Advance Solidification Technology (BCAST), Brunel University London, Uxbridge, UB8 3PH, UK M. Conte Anton Paar TriTec SA, Rue de la Gare 4, 2034 Peseux, Switzerland K. Pericelous Computational Science and Engineering Group (CSEG), Department of Mathematics, University of Greenwich, London, SE10 9LS, UK P. Prentice Cavitation Laboratory, School of Engineering, University of Glasgow, Glasgow, G12 8QQ, UK D. Eskin Tomsk State University, Tomsk, 634050, Russia I. Tzanakis Department of Materials, University of Oxford, Oxford, OX1 3PH, UK

bubbles. The results were interpreted in terms of fracture mechanics using the nanoindentation results. Keywords












Ultrasonic melt treatment Cavitation Fragmentation Intermetallic crystal Nanoindentation High-speed imaging

Introduction Ultrasonic melt treatment (UST) offers an economical and environment friendly approach to liquid metal processing with benefits of improved cast structure and properties resulting in production of high quality light metal alloys [1]. Specifically, mechanical properties in various aluminium alloys can be significantly altered by the formation and refinement of the primary intermetallic particles. Refined intermetallics can act as reinforcing particles to produce metal matrix composites (MMC’s) in Al–Si [2] or Al–Ti alloys [3] systems resulting in considerable improvements in terms of elastic modulus, hardness, thermal stability, low density and high corrosion resistance [4, 5]. Even though the resulting effect of UST on the as-cast metallic alloys is quite reproducible [6, 7], understanding the in situ fragmentation mechanisms of free floating primary crystals is still a work in progress. Research in this field is now considerably enhanced by the possibility of in situ high-speed-optical imaging or X-ray assisted imaging of transparent organic alloys [8–10]. Chow et al. [10] found out that nucleation of grains was considerably enhanced through ultrasonic vibrations and subsequent fragmentation of the dendrites caused by oscillation, and collapse of stable and inertial cavitation bubbles. Wagterveld et al. [11] observed the effect of cavitation bubbles on the fragmentation of suspended calcite crystals in a calcium carbonate solution. It was found out that the fracture of these calcite crystals was initiated by the continuous collapse of formed bubble

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_23

168

Nanoindentation and Cavitation-Induced Fragmentation Study …

clusters. Lately, synchrotron X-ray imaging has been widely applied to the studies of in situ solidification of real liquid metals and alloys under the influence of different external fields [12–15]. Wang et al. [14] investigated the fragmentation of Al2Cu intermetallic dendrites in an Al-35% Cu alloy by ultrasonic treatment using X-ray radiography. Other studies on alloy melts include the dynamic behaviour of cavitation bubbles in an Al-10wt% Cu alloy [15] as well as interaction between the acoustic bubble/flow and solidifying phases in an Bi-8%Zn alloy [12, 16] Recently, Wang et al. [2] developed an efficient method of observing the real time interaction of ultrasonic induced cavitation bubbles with various primary intermetallic phases such as Si, Al3Ti, and Al3V crystals. Although, this work shed some light on the mechanisms of cavitation-induced fragmentation, a discernible gap exists in relating; (1) the relation of the fragmentation of the crystal to its mechanical properties and (2) associated fracture mechanisms caused by the collapsing bubbles. It is believed that a combination of acoustic streaming [14] with liquid jet impingement and shock waves propagation from the collapsed cavitation bubbles are responsible for the fragmentation of crystals in liquid melts; similar to the pitting mechanism on solid surfaces [17]. In this study, we revealed for the first time that fragmentation of intermetallic particles is mainly driven by the propagation of shock waves from the collapsing bubbles. Specifically, the mechanical properties of primary Al3Zr crystals extracted from an Al-3%Zr alloy have been evaluated using a depth sensing indentation technique at ambient conditions. Subsequently, fragmentation experiments of extracted Al3Zr crystals have been conducted in deionized water by laser-induced cavitation with in situ high-speed imaging. Experimental results were explained using stress-fracture mechanics.

Fig. 1 Thermal-cycle of an Al-3wt%Zr alloy formation

169

Experimental Methodology Intermetallics Extraction and Sample Preparation Approximately 350 grams of an Al-3wt% Zr alloy were produced by smelting pure Al (99.97%) and an Al-5wt% Zr master alloy. The formed alloy was re-melted in an electrical furnace and solidified in a cylindrical graphite mould (Ø = 50 mm) with a thermal cycle as illustrated in Fig. 1. 5  5  5 mm cubes were then cut using a SiC rotating blade out of the ingot. To extract Al3Zr intermetallics from the sample, the Al-3wt% Zr, a cube sample was immersed in 15% NaOH water solution for 24 h. Dissolution of Al matrix was carried out through the following chemical reaction: 2Al þ 2NaOH þ 2H2 O ! 2NaAlO2 þ 3H2 The resulting solution was filtered out and the extracted intermetallics were then collected and thoroughly rinsed using ethanol and left to dry out for the following studies. Figure 2a shows the morphological image of an extracted Al3Zr crystal. These extracted primary intermetallics exhibit a well-facetted and thin tabular crystals as also observed by Zhen and Davies [18]. Additionally, a part of the cast ingot was cut longitudinally and sectioned along the central axis from the bottom where the primary intermetallics tend to settle during slow cooling because of the high density of Al3Zr. These sectioned sample was then ground and polished for optical microscopic examination and nanoindentation studies. Figure 2b shows embedded intermetallics (indicated by the red dashed lines) in the alloy matrix.

170

A. Priyadarshi et al.

Fig. 2 Optical micrographs of Al3Zr a extracted crystal, and b intermetallics embedded in Al matrix

Experimental Setup Depth Sensing Indentation (DSI) The embedded intermetallic specimen (Fig. 2b) was staged on a high temperature ultra nanoindentation system (UNHT HTV, Anton Paar, Switzerland) based on the principle of active surface referencing (note that we used only room-temperature measurements in this study). The detailed information related to the instrumentation is provided elsewhere [19]. A series of indents were employed onto the embedded intermetallics using a Berkovich diamond indenter at a constant loading and unloading rate of 20 mN/min with a dwell period of 5 s. The indentations were performed at room temperature conditions with data acquisition rate of 10 Hz. The load-displacement measurement of the Al3Zr crystal was obtained for maximum load of 10 mN at room temperature. Other indentation types such as fracture mode were also performed over the specimen using a geometrically well-defined diamond cube corner indenter with a maximum load of 100 mN. Minimum 5 indents were performed for each measurement mode to provide statistically meaningful results. Single Laser-Induced Bubble (LIB) A single 10.5 ± 1 mJ (instrumental error), 6–8 ns high energy laser pulse using Nd:YAG laser system (Nano S 130-10, Litron Lasers, UK) was focused into deionised water, with enough energy to cause optical breakdown and subsequent generation of a laser bubble within a chamber of dimension 420 mm  438 mm  220 mm. Detailed information of the experimental setup can be found elsewhere [20]. The extracted intermetallic crystals were fixed on top of a steel base using a cyanoacrylate adhesive. The fixed Table 1 Measured mechanical properties of Al3Zr crystal using DSI technique

crystals were then placed on a custom-built xyz manipulator and adjusted such that the laser bubble forms just beside the crystal. In situ recordings of the crystal-single bubble interaction were captured with high-speed shadowgraphic imaging with 500,000 frames per second using HPV X2 (Shimadzu, Japan) camera generating 256 frames per image sequence. The images shown in this paper have been confirmed after 5 repeated observations and are considered to be representative.

Results and Discussion Depth Sensing Indentation of Primary Al3Zr Crystal Mechanical properties such as elastic modulus, hardness and fracture toughness of the Al3Zr crystals were measured. The mechanical properties have been evaluated using the method introduced by Oliver and Pharr [21]. The maximum displacement of the indenter (hmax) was found to be around 237 nm upon loading and final depth after unloading the indenter was close to 181 nm. The contact stiffness during the unloading stage was 0.235 mN/nm. The mechanical properties such as the hardness (H) and elastic modulus (E) were found to be in the range of 7.2–7.6 GPa and 194–206 GPa respectively. These values of H and E were found to be in good agreement with the existing data in the literature [20, 21]. Fracture toughness (Kc) of the crystal was found to be close to 1 MPa√m. Table 1 summarizes the material properties of Al3Zr determined using the indentation measurements.

Mechanical properties

Measured value

Std. dev.

Hardness (GPa)

7.4

0.2

Elastic modulus (GPa)

200

5.8

Fracture toughness (MPa√m)

1.1

0.1

Nanoindentation and Cavitation-Induced Fragmentation Study …

Fragmentation of Al3Zr Crystal Figure 3a-l shows the sequence of images captured during the fragmentation of a primary Al3Zr crystal by a generated single LIB. Only selective images have been shown for the best representation of fragmentation mechanism. The first image at t = 0 ls shows the primary crystal of dimension approximately 5.7 mm  4.7 mm  0.1 mm with two pre-existing notches of length 0.4 mm and 0.35 mm (indicated with dashed arrows). At t = 2.5 ls, a laser bubble released a continuous band of shock waves that propagated through the liquid as shown in Fig. 3b, c and caused a crack of the length  0.4 mm to form at the encircled (yellow) position (at a distance of 4.8 mm from the emission centre). The laser bubble undergoes the expansion phase from t = 2.5 ls to t = 152.5 ls in reaction to energy disposition of the host medium and reached a maximum radius of 1.5 mm encircled in blue (Fig. 3d). After this, as the inertia of the bubble wall started to decelerate, the contraction phase of the laser bubble initiated, eventually causing the bubble to collapse at t = 332.5 ls thereby releasing another cycle of shock wave bands spreading over the liquid and ultimately attenuating over the distance from the emission centre. This is followed by multiple rebound oscillation and release of shock waves up to t = 617.5 ls until the bubble completely collapses. It is interesting to note that after the release of the second cycle of shock wave bands upon the bubble collapse phase i.e. t = 335 ls (Fig. 3g) and subsequent growth of a rebound bubble i.e. t = 410 ls (Fig. 3h), a clear crack growth

171

(encircled in red) can be seen. Crack initiated at one of the notches and propagated towards the other notch as shown in Fig. 3j causing complete fragmentation of the primary Al3Zr crystal in Fig. 3l. Since there was no direct interaction of the laser bubble directly with the crystal, it seems that the whole fragmentation process was a result of generated and repeated shock waves emitted from the nucleation and collapse phase of the laser bubble.

Fracture Mechanism It is important to quantify the fragmentation mechanism in order to have a better understanding of the observed phenomena discussed in section “Fragmentation of Al3Zr Crystal”. The fragmentation mechanics can be interpreted in terms of a critical stress required to completely fracture the crystal with a pre-existing crack/notch. This section describes the typical Griffith crack growth analysis observed for the Al3Zr crystal fragmented using the laser-induced bubble by the emitted shock waves. The basic mechanism underlined through the imaging observations points clearly towards the involvement of two-stage fracture that involves fatigue mechanism at the initial stages of crack growth until the crack size reaches its critical length followed by the brittle fracture mechanism in the final stages as has been also observed by Wang et al. [2]. Hence, it is of interest to understand the strength of shock wave in terms of associated pressure amplitude (Pr). The magnitude of the pressure amplitude variation over the distance from the

Fig. 3 Real time captured images of interaction of a laser nucleated single bubble inducing crack and subsequent fragmentation of primary Al3Zr crystal recorded at 500,000 fps

172

A. Priyadarshi et al.

Fig. 4 Images of Al3Zr crystal just a before crack propagation and b after crack propagation caused by bubble collapse shock waves

shock wave emission centre has been considered to follow the relation suggested by Vogel et al. [22]. It has been observed that the shock pressure decays over distance, r following the relation:
 Pr ¼ c1 qo us 10ðus co Þ=c2  1 þ P1 ð1Þ where qo is the density of the medium (water) before shock wave emission, us is the shock wave velocity derived from the r(t) curve, co is the speed of sound in water, c1 is an empirical constant equal to 5190 m/s, c2 = 25306 m/s and P∞ denotes the hydrostatic pressure. It has been observed that the pressure amplitude close to 100 MPa is roughly proportional to r−1 near the shock front [23, 22]. Using the Griffith fracture criterion [24] for brittle materials, the applied stress needed for a given crack length of the notch was evaluated from the following expression: pffiffiffiffiffiffi Kc ¼ Cr pa ð2Þ where Kc is the fracture toughness of the material taken as 1.1 from the DSI measurements mentioned in section “Depth Sensing Indentation of Primary Al3Zr Crystal”, a is the notch length (0.4 mm), C is the constant depending on the crack length taken as 1.12 and r is the stress required to cause complete fracture of material. For notch 1 formed during repeated expansion and collapse of a cavitation bubble (Fig. 4a), the stress needed to induce complete fracture was found to be 27 MPa as estimated by Eq. 2. Based on the distance of notch 1 from the bubble centre, pressure amplitude of the propagating shock front from a similarly collapsing bubble was determined to be 39 MPa considering that shock pressure decays as r−1 [22]. As a result, it can be confirmed that the shock wave emission from the expansion and collapse phase of a single bubble is adequate to cause brittle failure of a crystal in the vicinity.

Conclusions Depth sensing indentation technique was used to evaluate the mechanical properties of the primary Al3Zr crystals at room temperature. The hardness, elastic modulus and fracture toughness values indicated the extreme brittle nature of the intermetallic with values more or less consistent with data present in the literature. The primary Al3Zr crystals were then extracted from a heavily etched Al-3wt% Zr alloy and in situ imaging of their fragmentation behaviour upon interaction with a laser induced singe bubble was conducted. Upon examining the in situ recorded high-speed images, the fragmentation mechanism of the crystal was explained both qualitatively and quantitatively using fracture mechanics. The fragmentation of the crystal occurs primarily by the emitted shock waves from the collapsing bubble. The fracture happens in two stages: (i) shock wave bands interact with the crystal present nearby periodically inducing a low cycle fatigue until a critical size crack is formed; (ii) the fracture happens shortly after, following a typical brittle failure mechanism. Pressure amplitudes in the range of 30– 40 MPa were estimated to cause fragmentation of the studied crystals. Future work includes the investigation of sonofragmentation and the associated mechanisms under ultrasonic excitation. Based on the current results we envisage that shock wave propagation should still be the dominant fracturing mechanism of intermetallics. Acknowledgements The authors are sincerely thankful to the UK Engineering and Physical Sciences Research Council (EPSRC) for the financial support received from the UltraMelt2 project (grant EP/R011044/1, EP/R011095/1 and EP/R011001/1). The authors also acknowledge the help received from Anton Paar, Switzerland for the nanoindentation experiments.

Nanoindentation and Cavitation-Induced Fragmentation Study …

References 1. D. G. Eskin, I. Tzanakis, F. Wang, G. S. B. Lebon, T. Subroto, K. Pericleous, and J. Mi, “Fundamental studies of ultrasonic melt processing,” Ultrason. Sonochem., vol. 52, pp. 455–467, Apr. 2019. 2. F. Wang, I. Tzanakis, D. Eskin, J. Mi, and T. Connolley, “In situ observation of ultrasonic cavitation-induced fragmentation of the primary crystals formed in Al alloys,” Ultrason. Sonochem., vol. 39, no. March, pp. 66–76, 2017. 3. F. Wang, D. Eskin, T. Connolley, and J. Mi, “Effect of ultrasonic melt treatment on the refinement of primary Al3Ti intermetallic in an Al-0.4Ti alloy,” J. Cryst. Growth, vol. 435, pp. 24–30, 2016. 4. G. I. Eskin and D. G. Eskin, “Production of natural and synthesized aluminum-based composite materials with the aid of ultrasonic (cavitation) treatment of the melt,” Ultrason. Sonochem., vol. 10, no. 4–5, pp. 297–301, Jul. 2003. 5. T. V. Atamanenko, D. G. Eskin, L. Zhang, and L. Katgerman, “Criteria of Grain Refinement Induced by Ultrasonic Melt Treatment of Aluminum Alloys Containing Zr and Ti,” Metall. Mater. Trans. A, vol. 41, no. 8, pp. 2056–2066, Aug. 2010. 6. G. I. Eskin and D. G. Eskin, “Some control mechanisms of spatial solidification in light alloys,” Zeitschrift für Met., vol. 95, no. 8, pp. 682–690, Aug. 2004. 7. G. I. Eskin, “Broad prospects for commercial application of the ultrasonic (cavitation) melt treatment of light alloys,” Ultrason. Sonochem., vol. 8, no. 3, pp. 319–325, Jul. 2001. 8. G. M. Swallowe, J. E. Field, C. S. Rees, and A. Duckworth, “A photographic study of the effect of ultrasound on solidification,” Acta Metall., vol. 37, no. 3, pp. 961–967, Mar. 1989. 9. D. Shu, B. Sun, J. Mi, and P. S. Grant, “A High-Speed Imaging and Modeling Study of Dendrite Fragmentation Caused by Ultrasonic Cavitation,” Metall. Mater. Trans. A, vol. 43, no. 10, pp. 3755–3766, Oct. 2012. 10. R. Chow, R. Blindt, A. Kamp, P. Grocutt, and R. Chivers, “The microscopic visualisation of the sonocrystallisation of ice using a novel ultrasonic cold stage,” Ultrason. Sonochem., vol. 11, no. 3– 4, pp. 245–250, May 2004. 11. R. M. Wagterveld, L. Boels, M. J. Mayer, and G. J. Witkamp, “Visualization of acoustic cavitation effects on suspended calcite crystals,” Ultrason. Sonochem., vol. 18, no. 1, pp. 216–225, Jan. 2011. 12. B. Wang, D. Tan, T. L. Lee, J. C. Khong, F. Wang, D. Eskin, T. Connolley, K. Fezzaa, and J. Mi, “Ultrafast synchrotron X-ray imaging studies of microstructure fragmentation in solidification under ultrasound,” Acta Materialia, vol. 144. pp. 505–515, 2018.

173 13. W. W. Xu, I. Tzanakis, P. Srirangam, S. Terzi, W. U. Mirihanage, D. G. Eskin, R. H. Mathiesen, A. P. Horsfield, and P. D. Lee, “In Situ Synchrotron Radiography of Ultrasound Cavitation in a Molten Al-10Cu Alloy,” in TMS 2015 144th Annual Meeting & Exhibition, 2015, pp. 61–66. 14. F. Wang, D. Eskin, J. Mi, C. Wang, B. Koe, A. King, C. Reinhard, and T. Connolley, “A synchrotron X-radiography study of the fragmentation and refinement of primary intermetallic particles in an Al-35 Cu alloy induced by ultrasonic melt processing,” Acta Materialia, vol. 141. pp. 142–153, 2017. 15. I. Tzanakis, W. W. Xu, G. S. B. Lebon, D. G. Eskin, K. Pericleous, and P. D. Lee, “In situ synchrotron radiography and spectrum analysis of transient cavitation bubbles in molten aluminium alloy,” Phys. Procedia, vol. 70, no. 0, pp. 841–845, 2015. 16. W. W. Xu, I. Tzanakis, P. Srirangam, W. U. Mirihanage, D. G. Eskin, A. J. Bodey, and P. D. Lee, “Synchrotron quantification of ultrasound cavitation and bubble dynamics in Al-10Cu melts,” Ultrason. Sonochem., vol. 31, pp. 355–361, 2016. 17. I. Tzanakis, D. G. Eskin, A. Georgoulas, and D. K. Fytanidis, “Incubation pit analysis and calculation of the hydrodynamic impact pressure from the implosion of an acoustic cavitation bubble,” Ultrason. Sonochem., vol. 21, no. 2, pp. 866–878, 2014. 18. S. Zhen and G. J. Davies, “Observations of the growth morphology of the intermetallic compound Al3Zr,” J. Cryst. Growth, vol. 64, no. 2, pp. 407–410, Nov. 1983. 19. M. Conte, G. Mohanty, J. J. Schwiedrzik, J. M. Wheeler, B. Bellaton, J. Michler, and N. X. Randall, “Novel high temperature vacuum nanoindentation system with active surface referencing and non-contact heating for measurements up to 800 °C,” Rev. Sci. Instrum., vol. 90, no. 4, p. 045105, Apr. 2019. 20. K. Johansen, J. H. Song, K. Johnston, and P. Prentice, “Deconvolution of acoustically detected bubble-collapse shock waves,” Ultrasonics, vol. 73, pp. 144–153, 2017. 21. W. C. Oliver and G. M. Pharr, “An improved technique for determining hardness and elastic modulus using load and displacement sensing indentation experiments,” J. Mater. Res., vol. 7, no. 06, pp. 1564–1583, Jun. 1992. 22. A. Vogel, S. Busch, and U. Parlitz, “Shock wave emission and cavitation bubble generation by picosecond and nanosecond optical breakdown in water,” J. Acoust. Soc. Am., vol. 100, no. 1, pp. 148–165, Jul. 1996. 23. D. De Fontaine, “Cluster Approach to Order-Disorder Transformations in Alloys,” Solid State Phys., vol. 47, pp. 33–176, Jan. 1994. 24. M. Janssen, J. Zuidema, and R. Wanhill, Fracture mechanics. Spon Press, 2004.

In Situ Neutron Diffraction Solidification Analyses of Rare Earth Reinforced Hypoeutectic and Hypereutectic Aluminum–Silicon Alloys J. Stroh, D. Sediako, D. Weiss, and V. K. Peterson

Abstract

The recognised potential of rare earth (RE) additions such as cerium (Ce) and lanthanum (La) for strengthening aluminum alloys has led to an area of research focused on the development of new alloys, targeting powertrain applications that require high temperature strength and creep resistance. In an attempt to further improve the mechanical properties of the Al–Si system, this paper addresses the effects that RE additions have on the microstructure and phase evolution during solidification. This study presents the results of in situ solidification studies using neutron diffraction and microstructural analyses using scanning electron microscopy with energy-dispersive spectroscopy of Al7Si3.5RE and Al18Si8RE alloys, where numerical notation indicates composition in wt%. We find that the RE additions lead to the formation of globular Al20Ti2(Ce6LaNd) and rod-like Si3Al2(Ce3La2Nd) intermetallics in the Al7Si3.5RE alloy. We also find that Si and Cu additions in the Al18Si8RE alloy transforms the solid structure of the rod-like Si3Al2(Ce3La2Nd) intermetallic to a fibrous twin-layered material comprised of alternating Si3Ce1Al1(La6Nd3Cu2Pr) and Al5Si4CeCu(La6Nd3Pr) constituents. Furthermore, the high RE content in the Al18Si8RE alloy leads to a prolonged solidification range which may increase the alloy’s susceptibility to porosity formation. Keywords






Aluminum alloys Rare earth Neutron diffraction Solidification kinetics Phase evolution J. Stroh (&)
D. Sediako University of British Columbia – Okanagan, 3333 University Way, Kelowna, V1V 1V7, Canada e-mail: [email protected] D. Weiss Eck Industries, 1602 N 8th St, Manitowoc, WI 54220, USA V. K. Peterson Australian Nuclear Science and Technology Organisation, New Illawarra Rd, Lucas Heights, NSW 2234, Australia




Introduction Technological advancements in the automotive industry have allowed manufacturers to significantly improve the handling and performance of automobiles. This has been commonly achieved by a combination of weight reduction of individual components as well as an increase in operating pressure inside the combustion chamber of the engines. The elevated internal pressure during combustion results in a proportional increase in temperature which can lead to a weakening of the mechanical properties of the currently used powertrain alloys (i.e. A206, A319, A356 or A390). Typically, 3xx series aluminum (Al) alloys are used for powertrain applications such as engine blocks, as well as engine heads and pistons, due to their high strength to weight ratio, low coefficient of thermal expansion, and their improved castability and wear resistance associated with silicon (Si) additions. For example, hypoeutectic Al–Si alloys (i.e. with less than 12.6 wt% Si in Al) such as A319 and A356, are commonly used for cast engine blocks, cylinder heads, and transmission gearcases [1, 2]. Furthermore, in applications where higher wear resistance is desired (i.e. monolithic engine blocks or pistons), a hypereutectic Al–Si alloy such as A390 is generally preferred [3, 4]. However, increasing Si content may result in a decrease in fracture toughness and ductility [5]. The mechanical properties of Al–Si alloys are strongly correlated to the morphology, size and dispersion of the eutectic Al–Si, primary Si particles and secondary intermetallics. Therefore, research has been performed to evaluate methods of refining the microstructure of cast Al–Si alloys [6– 10]. More recently, E. Elgallad et al. performed a comprehensive microstructural analysis using scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), and differential scanning calorimetry (DSC) to characterize the effects of 1 wt% additions of lanthanum (La) and cerium (Ce) on the hypoeutectic Al–Si (A356, *Al7Si0.35Mg) and a eutectic Al–Si (A413, *Al12Si) alloy (wt% will be used for

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_24

174

In Situ Neutron Diffraction Solidification Analyses …

the remainder of this article unless otherwise stated) [11]. The primary observations from the study were that neither La or Ce had a positive effect in refining the eutectic silicon microstructure, but instead coarsened the Si particles. Furthermore, both Ce and La poisoned the Si refining effects of strontium (Sr), particularly in the La case. Ce and/or La additions to the A413 alloy resulted in a significant suppression of the eutectic temperature, leading to a 20 °C increase in the solidification range of the primary a-Al. Consequently, the solidification range of the A413 was significantly increased, rendering it susceptible to porosity formation [12]. M. Mahmoud also found that increasing La and Ce content up to approximately 1.5 wt% of RE in an A356 alloy led to a substantial increase in shrinkage porosity [13]. It appears that RE additions have little positive affect on microstructure refinement and may contribute detrimentally to porosity. However, if properly manufactured, the mechanical properties of REcontaining Al alloys may soon outperform the currently used powertrain alloys. For example, Z. Sims, D. Weiss et al. achieved room temperature tensile strengths up to approximately 250 MPa in cast Al–Ce–Si–Mg and Al–Ce–Mg alloys [14, 15]. Further, these alloys retained more than 50% of their strength at 260 °C, attributed to the high thermal stability of the Ce bearing intermetallics. The potential for improved high temperature strength of Al–RE based alloys has led to the current study which uses neutron powder diffraction (ND), as well as SEM and EDS to characterize electron microscopy (SEM), and energy dispersive X-ray spectroscopy (EDS) to characterize the effects of RE addition on the microstructure and the temperature-dependent phase evolution of both hypoeutectic and hypereutectic Al–Si alloys.

Experimental Procedure and Results Microstructure Characterization The samples described in this article, A356-3.5RE (*Al7Si3.5RE) and A390-8RE (*Al18Si8RE), were extracted from ASTM standard [16] tensile samples that were cast in a permanent mold at Eck Industries’ manufacturing facility. To characterize the size, shape, and morphology of the primary and secondary phases present in the alloy, SEM and EDS analyses were performed. Following the principles outlined in ASTM standard E3-11 [17], each sample was mounted in acrylic resin and sequentially ground with silicon-carbide paper, before polishing with a 9, 6, 3, and 1 µm colloidal diamond suspension. To further reveal the microstructure, each sample was electro-etched at 30 V in Barkers etchant (2.5 ml of fluoroboric acid in 200 ml of distilled water) for 15 s.

175

Fig. 1 SEM micrograph of Al7Si3.5RE alloy (500 x)

Figure 1 displays the microstructure of the A356 alloy with 3.5% RE (*1.8 wt% Ce, 0.9 wt% La, 0.6 wt% Nd, and 0.2 wt% Pr). Similar to observations described by Elgallad et al. [11], who characterized the effects of 1% additions of Ce and La on the microstructure of A356, the microstructure of the A356-3.5% RE alloy consisted of plate-like eutectic Si in the interdendritic regions of Al dendrites and a globular Al20Ti2(Ce6LaNd) intermetallic. Elgallad et al. also observed a rod-like intermetallic Al1.74Si1.77 (La,Ce) [11]; however, in this study we observe a Si3Al2(Ce3La2Nd) phase with a similar morphology (Fig. 1). Figure 2 displays the microstructure of the A390 alloy with 8% RE (consisting of 4.2 wt% Ce, 2.1 wt% La, 1.3 wt % Nd, and 0.4 wt% Pr), which is significantly different from the Al7Si3.5RE alloy (compare Figs. 1 and 2a) with the majority of Si present as large clusters of primary crystals. The additional 11 wt% Si and 4 wt% Cu in the Al18Si8RE alloy, as compared to the hypoeutectic alloy, may have been the primary factor that transformed the solid structure of the white Si3Al2(Ce3La2Nd) intermetallic (see Fig. 1) to a fibrous twin-layered structure comprised of alternating Si3CeAl(La6Nd3Cu2Pr) and Al5Si4CeCu(La6Nd3Pr) layers. A relatively small volume fraction of Chinese script Al5Mg8Cu2Si6 and Al15(Fe,Mn)3Si2 intermetallics are also observed.

Neutron Powder Diffraction ND was used to characterize the phase evolution during solidification of the Al–Si alloys. Temperature dependent neutron data were collected on the high-resolution neutron powder diffractometer, Echidna, at the Australian Nuclear

176

J. Stroh et al.

Fig. 2 SEM micrograph of Al18Si8RE a 500 x, b 2000 x

Table 1 Temperatures of neutron data collection

Alloy

Temperature (°C)

Al7Si3.5RE

830, 645, 630, 615, 600, 575, 565, 550, 520, 510, 500, 450, 350, 200

Al18Si8RE

920, 800, 675, 665, 655, 575, 565, 555, 520, 510, 500, 400, 250

Science and Technology Organization (ANSTO) at the OPAL reactor source in Australia [18] using a neutron beam of wavelength *2.44 Å) over the 2h range 4–164°. Each sample was placed in a graphite crucible and mounted onto a sample stick, which was inserted inside a high temperature vacuum furnace featuring a niobium element. The machined samples were heated above the melting temperature at a heating rate of 60 °C/min and ND data collected for approximately 0.5 h at the temperatures shown in Table 1. Peaks could be indexed to a-Al (face centered cubic structure type, space group Fm3m [19]) and Si (diamond structure type, space group Fd 3m [20]), as presented in the inorganic crystal structures database [21] and their temperature-dependent evolution was characterized. A more in depth explanation of the procedure and methodology of the experiment is described in [7, 22–26]. Figure 3a displays the Al 111 reflection during cooling of the Al7Si3.5RE alloy, revealing a shift to higher angles as

(a) 4000 3000 2000 1000 0 61

61.5

62

62.5

63

63.5

615 510oC

1 0.8 0.6 0.4 0.2 0 700 650 600 550 500 450 400 350 300

2 Theta (Degrees) oC

FracƟon Solid of Al 111 in Al7Si3.5RE

1.2

FracƟon Solid

Intensity (A.U.)

(b)

Al 111 Al7Si3.5RE

5000

consistent with thermal contraction during cooling. For clarity, not all of the data collected are shown in Fig. 3a. Evaluating the area of the peak to the background allows for the characterization of the solidification process, as explained in detail in [23, 26]. Similar to previous differential scanning calorimetry results [11], the liquidus and solidus temperatures of primary a-Al are approximately 610 and 550 °C, respectively (see Fig. 3b). Therefore, it appears the additional Ce (*0.9% increase), Nd (*0.6% increase), and Pr (*0.2% increase) in this alloy had a negligible effect on the solidification temperature of Al, as compared to the Al7SiCeLa alloy described in [11]. Figure 3c, d show the Si 111 reflection during cooling of the Al7Si3.5RE alloy, where the additional RE content also had a negligible effect on the eutectic temperature of Si (*565–550 °C). Contrary to the gradual solidification of the Al in the Al7Si3.5RE alloy, the complete solidification of Al in the Al18Si8RE alloy is nearly instantaneous (*565–550 °C, see Fig. 4a, b). Conversely, it was observed that the solidification

600oC

575 oC

565 oC

550oC

500oC

450 oC

350 oC

250oC

520

oC

Temperature (°C)

Fig. 3 Temperature dependent neutron powder diffraction data of the Al7Si3.5RE alloy showing the a Al 111 and c Si 111 reflections and the corresponding solid fraction of these in (b) and (d), respectively. Data are shown as points with the solid and dashed line a guide to the eye

In Situ Neutron Diffraction Solidification Analyses …

(a)

(b)

Al 111 in Al18Si8RE

8000 6000

FracƟon Solid

Intensity (A.U.)

Fig. 4 Temperature dependent neutron powder diffraction data of the Al18Si8RE alloy showing the a Al 111 and c Si 111 reflections and the corresponding solid fraction of these in (b) and (d), respectively. Data are shown as points with the solid and dashed line a guide to the eye

177

4000 2000 0 61

61.5

62 62.5 2 Theta (Degrees)

575 oC 510 oC

(c)

63

555 oC 400 oC

63.5

700 650 600 550 500 450 400 350 300 Temperature (°C)

520 oC 250 oC

(d)

Si 111 in Al18Si8RE

2000 1500 1000 500 0

FracƟon Solid of Si 111 in Al18Si8RE 1.2

FracƟon Solid

Intensity (A.U.)

565 oC 500 oC

FracƟon Solid of Al 111 in Al18Si8RE 1.2 1 0.8 0.6 0.4 0.2 0

44

44.5

45

45.5

46

46.5

47

575oC 500oC

565oC 400oC

of Si occurred in two stages. First, the relatively slow solidification of primary Si crystals occurred from approximately 650–565 °C. Following this, the remaining Si rapidly solidifies in the form of eutectic Si between approximately 565 and 550 °C (see Fig. 4c, d). This prolonged solidification of the alloy increases the susceptibility to porosity formation which is deleterious to the alloy’s mechanical properties [12]. Moreover, the addition of large amounts of RE significantly increases the volume fraction of RE-based intermetallics (see Fig. 2), leading to a reduced feedability of the Al during solidification and further resulting in the formation of shrinkage porosity. Therefore, additional care should be taken to minimize the formation of porosity during casting.

Conclusions This study investigated the microstructural effects of RE additions on a hypoeutectic Al7Si3.5RE and a hypereutectic Al18Si8RE alloy. In situ neutron powder diffraction was performed to characterize the solidification of the Al and Si phases within each alloy. The following conclusions may be drawn from this research: (1) The microstructure of the Al7Si3.5RE alloy primarily consisted of plate-like eutectic Si in the interdendritic regions of the Al matrix. SEM/EDS analysis revealed the presence globular intermetallics and irregular rod-like constituents with approximate stoichiometry of Al20Ti2(Ce6LaNd) and Si3Al2(Ce3La2Nd), respectively. (2) The additional 11 wt% Si and 4 wt% Cu in the Al18Si8RE alloy resulted in the transformation of the irregular rod-like Si3Al2(Ce3La2Nd) phase to a twin-layered

555oC 250oC

0.6 0.4 0.2 0

2Theta (Degrees) 655oC 510oC

1 0.8

520oC

700

650

600

550

500

450

400

350

300

Temperature (°C)

fibrous structured intermetallic comprised of alternating layers of Si3CeAl(La6Nd3Cu2Pr) and Al5Si4CeCu (La6Nd3Pr). It is presumed that this bi-layered, non-homogenous constituent will have a negative effect on the fitness-for-service properties of this alloy. (3) The solidification range for primary a-Al in the Al7Si3.5RE alloy is approximately 610 °C (liquidus) to 550 °C (solidus), with eutectic Si evolving in the temperature range 565–550 °C. (4) The solidification range for primary Al in the Al18Si8RE alloy is approximately 575 °C (liquidus) to 550 °C (solidus). The growth of Si occurs seems to occur is two stages, the first being the slow growth of primary Si crystals from 650 to 565 °C and the second being primarily rapid eutectic Si formation from 565 to 550 °C. The long solidification range and high RE content in this alloy may result in excessive shrinkage porosity.

References 1. Stroh J, Piche A, Sediako D, Lombardi A, and Byczynski G (2019) The Effects of Solidification Cooling Rates on the Mechanical Properties of an A319 Inline-6 Engine Block, The Minerals, Metals & Materials Society (TMS), vol. Light Metals: 505–512. 2. Vandersluis E, Lombardi A, Ravindran C, Bois-Brochu A, Chiesa F, and MacKay R (2015) Factors influencing thermal conductivity and mechanical properties in 319 Al alloy cylinder heads. Mater. Sci. Eng. A, 648: 401–411. 3. Kasprzak W, Sahoo M, Sokolowski J, Yamagata H, and Kurita H (2009) The Effect of the Melt Temperature and the Cooling Rate on the Microstructure of the Al-20%Si Alloy Used for Monolithic Engine Blocks, International Journal of Metal Casting 3(3):55–71.

178 4. Yamagata H, Kurita H, Aniolek M, Kasprzak W, and Sokolowski J (2007) Thermal and metallographic characteristics of the Al-20% Si high-pressure die-casting alloy for monolithic cylinder blocks, Journal of Materials Processing Technology 199 (2008):84–90. 5. YU W, YUAN A, GUO Z, and XIONG S (2017) Characterization of A390 aluminum alloy produced at different slow shot speeds using vacuum assisted high pressure die casting Trans. Nonferrous Met. Soc. 27(2017):2529–2538. 6. Bogdanoff T, Dahle A, and Seifeddine S (2018) Effect of Co and Ni Addition on the Microstructure and Mechanical Properties at Room and Elevated Temperature of an Al–7%Si Alloy, International Journal of Metal Casting 12(3):434–440. 7. Sediako D, Kasprzak W, Swainson I, and Garlea O (2011) Solidification Analysis of Al-Si Alloys Modified with Addition of Cu Using In-Situ Neutron Diffraction, The Minerals, Metals & Materials Society (TMS) 2(Materials Fabrication, Properties, Characterization, and Modeling):279–289. 8. Liu W, Xiao W, Xu C, Liu M, and Ma C (2017) Synergistic Effects of Gd and Zr on Grain Refinement and Eutectic Si Modification of Al-Si Cast Alloy, Material Science and Engineering A 693(2017):93–100. 9. Xu C, Xiao W, Hanada S, Yamagata H, and Ma C (2015) The effect of scandium addition on microstructure and mechanical properties of Al-Si-Mg alloy: A multi-refinement modifier, Materials Characterization, 110(2015):160–169. 10. Samuel A, Doty H, Valtierra S, and Samuel F (2014) Effect of grain refining and Sr-modification interactions on the impact toughness of Al-Si-Mg cast alloys, Materials and Design 56 (2014):264–273. 11. Elgallad E, Ibrahim M, Doty H, and Samuel F (2018) Microstructural characterisation of Al-Si cast alloys containing rare earth additions Microstructural characterisation of Al-Si cast alloys containing rare earth additions, Philosophical Magazine 98 (15):1337–1359. 12. Samuel A, Samuel F, Doty H and Valtierra S (2017) Porosity formation in Al-Si sand mold castings, International Journal of Metal Casting 11(4):812–822. 13. Mahmoud M, Elgallad E, Ibrahim M, and Samuel F (2018) Effect of Rare Earth Metals on Porosity Formation in A356 Alloy, International Journal of Metal Casting 12(2):251–265. 14. Sims Z, Weiss D et al. (2016) Cerium-Based, Intermetallic-Strengthened Aluminum Casting Alloy: High-Volume Co-product Development, JOM 68(7):1940–1947.

J. Stroh et al. 15. Weiss D (2017) Development and Casting of High Cerium Content Aluminum Alloys, Modern Casting 107(12):35–38. 16. ASTM (009) E8M Standard Test Methods for Tension Testing Wrought and Cast Aluminum- and Magnesium-Alloy Products, ASTM B 1–16. 17. ASTM (2001) E3-11 Standard Guide for Preparation of Metallographic Specimens 1, ASTM 1–12. 18. Liss K, Hunter B, Hagen M, Noakes T, and Kennedy S (2006) Echidna-the new high-resolution powder diffractometer being built at OPAL, Phys. B: Condensed Matter 385–386: 1010–1012. 19. Cooper A (1962) Precise lattice constants of germanium, aluminum, gallium arsenide, uranium, sulphur, quartz and sapphire, Acta Crystallographica 15(6):578–582. 20. Többens D, Stüßer N, Knorr K, Mayer H, and Lampert G (2001) E9: The New High-Resolution Neutron Powder Diffractometer at the Berlin Neutron Scattering Center, Mater. Sci. Forum 378– 381:288–293. 21. Karlsruhe F (2018) Inorganic Crystals Structures Database, Leibniz Institute for Information Infrastructure [Online]. Available: https://icsd.fiz-karlsruhe.de/search/index.xhtml;jsessionid= BDB6DC046A694F77D5D5C443909832EF. 22. Kasprzak W, Sediako D, Walker M, Sahoo M, and Swainson I (2010) Characterization of hypereutectic Al-19% Si alloy solidification process using in-situ neutron diffraction and thermal analysis techniques, Light Metals 2010(Advances in Materials and Processes):121–132. 23. Kasprzak W, Sediako D, Walker M, Sahoo M, and Swainson I (2011) Solidification analysis of an Al-19 Pct Si alloy using in-situ neutron diffraction, Metall. Mater. Trans. A 42(7):1854–1862. 24. Stroh J, Davis T, McDougall A, and Sediako D (2018) In Situ Study of Solidification Kinetics of Al–Cu and Al–Ce–Mg Alloys with Application of Neutron Diffraction, The Minerals, Metals & Materials Society (TMS) Light Metals 2018:1059–1065. 25. Sediako D and Kasprzak W (2015) In Situ Study of Microstructure Evolution in Solidification of Hypereutectic Al-Si Alloys with Application of Thermal Analysis and Neutron Diffraction, Metall. Mater. Trans. A 46(9):4160–4173. 26. Vandersluis E, Elsayed A, D’Elia F, Emadi P, Sediako D, and Ravindran C (2018) Crystalline-Phase Solidification Analysis Using In-Situ Neutron Diffraction, Trans. Indian Inst. Met 71 (11):2777–2781.

Influence of TiB2 Particles on Modification of Mg2Si Eutectic Phase in Al–Zn–Si–Mg–Cu Cast Alloys Byung Joo Kim, Sung Su Jung, Yong Ho Park, and Young Cheol Lee

Abstract

In this study, the effect of TiB2 particles on the modification of eutectic phase in Al–Zn–Si–Mg–Cu system alloys is investigated. The microstructure showed that an excellent effect can be achieved after the addition of TiB2 particles. The morphology of eutectic Mg2Si changed from large Chinese script to fine polygonal shape with a significant reduction in size. Modified eutectic Mg2Si particles were investigated using an optical microscope and field emission scanning/transmission electron microscope, and it was confirmed that TiB2 particles acted as nucleation sites for the eutectic Mg2Si phase, and the grain size change of Al–Zn–Si–Mg–Cu alloy with increasing TiB2 contents was analyzed by polarizing microscope. The mechanical properties were also improved by the modified of eutectic Mg2Si phase. This manuscript also investigated the reason for the improvement in mechanical properties with the modification of the microstructures. Upon these results, a possible mechanism of eutectic Mg2Si phase modification by the addition of TiB2 particles is proposed. Keywords





Aluminum alloys Phase modification compound Mechanical properties




Intermetallic

B. J. Kim (&)
S. S. Jung
Y. C. Lee Energy Plant Group, Korea Institute of Industrial Technology, Busan, 46938, Korea e-mail: [email protected] S. S. Jung e-mail: [email protected] Y. C. Lee e-mail: [email protected] Y. H. Park Department of Materials Science and Engineering, Pusan National University, Busan, 46241, Korea e-mail: [email protected]

Introduction The transition of the intermetallic compound morphology in aluminum alloys, also called phase modification, is commonly used in industry to improve mechanical properties, especially ductility. Intermetallic compounds that form during solidification appear in various shapes and sizes, and there are three general morphologies, namely as needles, Chinese script and polyhedral or star-like crystals. Due to the edges or tips of these morphologies serious stress concentration is induced in the matrix, which leads to brittleness of the material. Conversely, the spherical or polygonal type does not concentrate the force and has minimal adverse effect on the elongation of the material. Thus, modification of intermetallic compounds is usually required to improve the mechanical properties of cast components. Mg2Si intermetallic compounds are used as core hardened phases in aluminum alloys containing Mg and Si (like as 6XXX) because of their high hardness (4500 MNm−2), low density (1.99  103 kgm−3), high elastic modulus (120 GPa), high melting temperature (1085 °C), and low coefficient of thermal expansion (7.5  10−6 K−1) [1, 2]. The shape and size of intermetallic compounds have a great influence on the mechanical properties of aluminum alloy [3]. However, in general casting conditions, the final microstructure of Mg2Si intermetallic compound became coarse with dendritic morphology. This morphology of the Mg2Si phase is a weakness of the aluminum alloys. To solve this problem, many studies of the Mg2Si phase modification have been carried out such as P [4, 5], Sr [6], Na [7] and TiB2 [8, 9] addition. In our previously study, large amount of TiB2 particles (about 1 wt% Ti contents) were shown to be very effective in modifying the shape of eutectic Mg2Si intermetallic [8]. However, the effect of TiB2 particles during solidification on the eutectic Mg2Si crystal growth, and why a large amount of TiB2 is needed to modify eutectic Mg2Si, are unclear. The purpose of this study is to study the relationship of TiB2 and Mg2Si phases in Al–8Zn–6Si–4Mg–2Cu cast

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_25

179

180

B. J. Kim et al.

Fig. 1 Microstructure of the eutectic Mg2Si phase of Al–8Zn– 6Si–4Mg–2Cu alloy; a and c without Al–5Ti–1B master alloy; b and d with the Al–5Ti– 1B master alloy at 1 wt% Ti content

alloys. The mechanism of change in the direction of Mg2Si crystal growth during the solidification process is also discussed.

Experiments Al–8Zn–6Si–4Mg–2Cu–xTi (x = 0, 0.1, 0.5, 1 wt%) alloys were produced by gravity-casting. A 20 kHz high frequency furnace was used for melting the alloys. These alloys were prepared by adding pure Zn (99.99%), Mg (99.9%), Cu (99.997) ingot, Si (99.9%) crystalline and Al–5Ti–1B master alloy rods to aluminum molten (99.7%) held at 710 ± 5 °C. After adding the elements, the molten alloys were held for 10 min to assure alloying additions dissolution and melt homogenization. Cast for metallographic specimens were prepared using a cylinder mold (32 Dia.  70 mm, FC25 cast iron) preheated to 250 °C. Microstructures were examined using a polarizing microscope, a FE-SEM, FIB and a 200 kV FE-TEM. Deep etching was carried out in 20% NaOH water solution to confirm the 3-dimensional morphology of the eutectic Mg2Si phase. 2% Fluoboric acid water solution was used as etchant to electrolytic etching, and grain size measurement was according to ASTM E1382. The tensile test were carried out according to the ASTM E8 M using the universal testing machine.

Results Figure 1a, b show the morphology of the eutectic Mg2Si phase when Al–5Ti–1B master alloy was added to Al–8Zn– 6Si–4Mg–2Cu alloy at 0, 1 wt%. Ti contents. Figure 1c, d

shows the change of morphologies of eutectic Mg2Si before and after modification by deep etching. In Fig. 1a, c, without Al–5Ti–1B addition, coarse Chinese script type eutectic Mg2Si phase can be clearly observed. When Ti was added, eutectic Mg2Si morphology changed to a polygonal shape, less than 10 lm in size (Fig. 1b, d). TiB2 particles with bright contrast were also observed inside and outside the modified eutectic Mg2Si in the same figure. Optical microscope images of microstructure after electrolytic polishing of Al–Zn–6Si–4Mg–2Cu alloy with different Al–5Ti–1B addition amounts are shown in Fig. 3. It can be seen that the grains are clearly determined according to the different color contrast of grains. When 0.1 wt% of Ti was added, the grain size decreased from about 322– 120 lm, and there was no further grain refinement, even when the Ti addition amount was increased to 1 wt%. In the Al–8Zn–6Si–4Mg–2Cu alloy, the eutectic Mg2Si phase was observed at the inner edge of the aluminum grain (Fig. 2b). As the amount of Ti was increased, more modified eutectic Mg2Si phases were observed. Interestingly, polygonal shaped Mg2Si phases were observed in the grain boundaries, as opposed to Chinese script type morphology (Fig. 2h). Figure 3 shows the change of mechanical properties of aluminum alloy with different contents of Ti wt% [8]. As the content of Ti increases to 1 wt%, the mechanical properties also increase. Yield strength increased from 175–206 MPa and tensile strength increased from 195–253 MPa. The highest increase was the elongation, increasing from 0.63 to 1.05%. Shapes like Fig. 1a are brittle to mechanical load, because the stress is easily concentrated at the tip. This stress concentration is reduced as the shape of the intermetallic

Influence of TiB2 Particles on Modification of Mg2Si …

181

Fig. 2 Optical microscope images of the Al–8Zn–6Si–4Mg–2Cu alloys after electrolytic polishing; a, b no Ti, c, d 0.1 wt% Ti, e, f 0.5 wt% Ti, g, h 1 wt% Ti

Fig. 3 Mechanical properties of Al–8Zn–6Si–4Mg–2Cu alloys with different Ti contents [8]

compound becomes smaller and rounder. As the added TiB2 particles, the eutectic phase of Chinese script shape changes to polygonal shape. As the Ti content was added by 1 wt%, Most of the eutectic phases were modified, which greatly increased the mechanical properties. Figure 4 shows a cross-section of the modified eutectic Mg2Si phase measured by TEM/EDS. Al, Mg, Si, Ti and B elements were detected by EDS. It confirms that a phase containing Ti, B is observed inside of the modified Mg2Si. Analysis of the crystal orientation of Mg2Si and TiB2 by HR-TEM is shown.

Discussion As shown in Fig. 1, the eutectic Mg2Si phase was modified by the addition of Al–5Ti–1B master alloys. In previous studies, it was reported that TiB2 particles in the Al–5Ti–1B master alloy modified the eutectic Mg2Si phase [8]. Figure 2b, d show that the eutectic Mg2Si phase was observed at the inner edge of the aluminum grains. Figure 5 shows the solidification mechanism of the eutectic Mg2Si phase in the Al–8Zn–6Si–4Mg–2Cu alloy. Figure 5a shows the

182

B. J. Kim et al.

Fig. 4 TEM/EDS analysis data of modified eutectic Mg2Si phase

Fig. 5 Schematic illustrations presenting the stages in microstructural evolution during solidification of eutectic Mg2Si with no TiB2 particles

nucleation and growth of primary aluminum dendrite. Figure 5b shows the growth of secondary dendrite arms (SDA) due to growth and coarsening of aluminum dendrites. Segregation of the solute element (Mg, Si) occurs during the growth of aluminum grains. In SDA where Mg and Si elements are segregated, the Mg2Si nuclei form due to the compositional supercooling. Therefore, nuclei of eutectic Mg2Si generate around the SDA and grow into Chinese script morphology (Fig. 5d). While the eutectic Mg2Si phase grows near the SDA, the a-Al also grows and these two phases come into contact during solidification. Segregation of solvent elements (Al) occurs around the growing eutectic Mg2Si phase, the edge of Chinese script morphology has a

low potential for the contacted a-Al. For this reason, a-Al will easily engulf the eutectic Mg2Si, and as a result, the eutectic Mg2Si phase solidifies at the edge of the grain as shown in Figs. 2b, d, and 5d. The solidification path of the Al–8Zn–6Si–4Mg–2Cu alloy has been reported to proceed in the order of a-Al ! Mg2Si ! Si ! Al5Cu8Si6Mg2 [8]. The particle pushing of TiB2 particles by a-Al is known in many research [10, 11]. Particularly, the agglomerated TiB2 particles have a high potential at the interface with the growing aluminum, and they are easily pushed by the growing aluminum [11]. TiB2 particles also act as good nucleation sites on Mg2Si because the crystal arrangement at the interface between the

Influence of TiB2 Particles on Modification of Mg2Si …

183

Fig. 6 Schematic illustrations presenting the stages in microstructural evolution during solidification of eutectic Mg2Si with TiB2 particles

(001) of TiB2 and the (200) of Mg2Si is similar [9]. In previously studies, and in Figs. 1 and 2 of this work, the modified eutectic Mg2Si located at grain boundaries and the TiB2 particles present in and around it suggest the following mechanism: TiB2 particles were pushed into grain boundaries during the growth of the a-Al grain, and the TiB2 particles agglomerated in the grain boundaries acted as nucleation sites for eutectic Mg2Si. Figure 6 shows the solidification mechanism of the eutectic Mg2Si phase of the Al– 8Zn–6Si–4Mg–2Cu alloy with enough TiB2 particles added. Figure 6a shows the nucleation and growth of primary aluminum as shown in Fig. 5a. As solidification progresses, the agglomerated TiB2 particles are easily pushed out while the aluminum SDA is growing, because they have a high potential for aluminum (Fig. 6b). At the temperature where the magnesium phase forms, the eutectic Mg2Si phase nucleate easily from the TiB2 particles as shown in Fig. 6c. It means that the eutectic Mg2Si phase nucleates on the TiB2 substrates and grows in polygonal shape. During the growth of the eutectic Mg2Si phase with TiB2 particles, aluminum also grows and these two phases come into contact. Unlike the Chinese script eutectic Mg2Si, the polygonal eutectic Mg2Si and the agglomerated TiB2 particles have a high potential for a-Al and are easily pushed into the grain boundaries. As shown in Figs. 2f, g and 6d, modified Mg2Si and TiB2 particles are located in the aluminum grain boundaries. Another discussion point is the effect of grain refinement with TiB2 addition on the morphology of eutectic Mg2Si phase. Al-5Ti-1B master alloy is known as a good grain refiner for aluminum alloys. In this work, Al–5Ti–1B master alloy of 0.1, 0.5, 1 wt% Ti contents were added. With 0.1 wt % Ti addition, the grain size was greatly decreased from 322 to 122 lm. However, further refinement was not observed with addition of 0.5, 1 wt% Ti contents. As shown in Fig. 2b, d, the morphology and position of eutectic Mg2Si did not change due to the grain refinement. From these

results, it can be concluded that grain refinement does not affect the solidification mechanism of eutectic Mg2Si.

Conclusion 1. The eutectic Mg2Si phase of Al–8Zn–6Si–4Mg–2Cu alloy was modified by adding 1 wt% content of Al–5Ti– 1B alloy. TiB2 particles were observed inside the modified eutectic Mg2Si phase. The good match of crystal growing orientation between TiB2 and Mg2Si was confirmed by TEM analysis. It was confirmed that TiB2 particles cause modification of eutectic Mg2Si. 2. The Chinese script type eutectic Mg2Si was observed at the inner edge of the a-Al grains. Mg2Si phase of polygonal shape, modified by addition of TiB2, was observed at grain boundaries. It is believed that heterogeneous nucleation of eutectic Mg2Si phase take place on the TiB2 particles and they are pushed into grain boundaries during the growing process. When 1 wt% Ti content of Al–5Ti–1B was added to Al–8Zn–6Si–4Mg–2Cu alloy, there were enough TiB2 particles to modify most of the eutectic Mg2Si phase. Acknowledgements This work was supported by the Korea Evaluation Institute of Industrial Technology (No. 20006644 Development and Infrastructure for Hydrogen Fuel Cell Propulsion Ship of Fuel Storage and Supplying System with Core Technology).

References 1. Lu L, Lai MO, Hoe ML(1998) Formation of nanocrystalline Mg2Si and Mg2Si dispersion strengthened Mg-Al alloy by mechanical alloying. Nanostructured Mater. 10:551–563. 2. Wang L, Qin XY(2003) The effect of mechanical milling on the formation of nanocrystalline Mg2Si through solid-state reaction. Scr. Mater. 49:243–248. 3. Seifeddine S, Johansson S, Svensson IL (2008) The Influence of cooling rate and manganese content on the b-Al5FeSi phase

184

4.

5.

6.

7.

B. J. Kim et al. formation and mechanical properties of Al-Si-based alloys. Mater. Sci. Eng. A 490:385–390. Tebib M, Samuel AM, Ajersch F, Chen XG (2014) Effect of P and Sr additions on the microstructure of hypereutectic Al-15Si-14Mg-4Cu alloy. Mater. Charact. 89:112–123. Qin QD, Zhao YG, Zhou W, Cong PJ, (2007) Effect of phosphorus on microstructure and growth manner of primary Mg2Si crystal in Mg2Si/Al composite. Mater. Sci. Eng. A 447:186–191. Jiang W, Xu X, Zhao Y, Wang Z, Wu C, Pan D, Meng Z (2018) Effect of the addition of Sr modifier in different conditions on microstructure and mechanical properties of T6 treated Al-Mg2Si in-situ composite. Mater. Sci. Eng. A 721:263–273. Zhang J, Fan Z, Wang Y, Zhou B (2000) Microstructural development of Al–15 wt%Mg2Si in situ composite with mischmetal addition. Mater. Sci. Eng. A 281:104–112.

8. Kim BJ, Jung SS, Hwang JH, Park YH, Lee YC (2019) Effect of Eutectic Mg2Si Phase Modification on the Mechanical Properties of Al-8Zn-6Si-4Mg-2Cu Cast Alloy. Metals (Basel) 9(1):32. 9. Li C, Liu X, Zhang G (2008) Heterogeneous nucleating role of TiB2 or AlP/TiB2 coupled compounds on primary Mg2Si in Al– Mg–Si alloys. Mater. Sci. Eng. A 497:432–437. 10. Schaffer PL, Arnberg L, Dahle AK (2006) Segregation of particles and its influence on the morphology of the eutectic silicon phase in Al–7 wt% Si alloys. Scr. Mater. 54:677–682. 11. Han Y, Li K, Wang J, Shu D, Sun B (2005) Influence of high-intensity ultrasound on grain refining performance of Al–5Ti– 1B master alloy on aluminium. Mater. Sci. Eng. A 405:306–312.

A Statistical Analysis to Study the Effect of Silicon Content, Surface Roughness, Droplet Size and Elapsed Time on Wettability of Hypoeutectic Cast Aluminum–Silicon Alloys Amir Kordijazi, Swaroop Kumar Behera, Omid Akbarzadeh, Marco Povolo, and Pradeep Rohatgi








Abstract

Keywords

In this study, the effect of silicon content, surface roughness, water droplet size, and elapsed time on contact angle (CA) of Aluminum-Silicon alloys were examined. To study wettability the static water contact angle was measured on a given sample using a goniometer. A laser confocal microscopy was used for measuring surface roughness. A full factorial design was utilized for the design of the experiment that includes all possible combinations of the independent factors and their levels (120 combinations). CA for each combination was measured three times, so in total 360 CA measurements were performed. To find the significant factors in CA variation and correlation between the significant factors and CA, Analysis of Variance (ANOVA) and Regression Analysis were performed, respectively. A significance level (a) of 0.05 was used for all statistical analyses. Contact angle values averaged 77° ± 5° with maximum value of 90º and minimum value of 64º, respectively. ANOVA results show that surface roughness and droplet size are significant factors. Regression analysis shows that CA increases by increasing surface roughness and water droplet size.

Cast Al–Si alloys Contact angles Factorial design Analysis of variance Regression analysis

A. Kordijazi (&) Department of Industrial and Manufacturing Engineering, University of Wisconsin Milwaukee, Milwaukee, 53211, USA e-mail: [email protected] S. K. Behera
P. Rohatgi Department of Material Science and Engineering, University of Wisconsin Milwaukee, Milwaukee, 53211, USA O. Akbarzadeh Nanotechnology and Catalysis Research Center, University of Malaya, 50603 Kuala Lumpur, Malaysia M. Povolo Department of Industrial Engineering, University of Bologna, 40132 Bologna, Italy




Introduction The properties of pure metals such as hardness, tensile strength, corrosion resistance, wear behavior, wettability, castability, etc. can be modified and enhanced by alloying it with other metal or nonmetal [1–8]. There are increasing demand for smaller, lighter-weight high-performance aluminum alloys. The primary factors involved to achieve these optimum mechanical properties for Al–Si alloys or any other system castings are the microstructure and alloying constituents. Al–Si castings are characterized by its low specific gravity and melting point, negligible gas solubility (excluding H2), excellent castability, good corrosion & wear resistance, and a high strength-to-weight ratio which has made this alloy system replace iron and steel in many components [9]. These properties have led Al–Si to be used in multiple lightweight automotive, aerospace, and marine applications. Al can dissolve a maximum of 1.6 wt% of Si while Si cannot dissolve any Al. The Si content usually ranges from 1.65 to 25 wt% with the eutectic point occurring at 12.6 wt%. Depending on the amount of Si, the Al–Si alloys are divided into three groups: hypoeutectic (  10 wt % Si), eutectic (11–13 wt% Si), and hypereutectic (  14 wt % Si) alloys. The casting quality and mechanical properties are determined by the size of the microstructure’s morphology and distribution of microstructural features caused by the casting process (solidification rate). The binary eutectic and hypoeutectic alloys are characterized by having good corrosion resistance, while the hypereutectic alloys exhibit excellent wear resistance and low coefficient of thermal expansion; their machinability is improved as the Si particles become finer and more evenly distributed.

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_26

185

186

A. Kordijazi et al.

The microstructure of hypoeutectic Al–Si alloys contains primary (a-Al) dendrites as the main constituent surrounded by Al–Si eutectic particles and intermetallic phases. a-Al is used instead of “pure Al” because 1.6 wt% Si is dissolved within and grows more easily in its non-faceted manner than Si crystal. The eutectic Al–Si is formed by Si distributed in the Al-rich matrix, as an irregular phase, with the amount of eutectic dependent on the wt% Si. With hypereutectic alloys, the primary reaction involves the precipitation of Si particles until the eutectic composition is reached [10, 11] Much practical application such as anti-corrosion and anti-fouling properties of a solid surface is controlled by the wettability of the surface [12]. Reports have shown that corrosion rate of aluminum and aluminum alloys decreases by decreasing surface wettability [13, 14]. To the date there are few research have been conducting focusing on effect of physical and chemical characteristics on wettability of hypoeutectic Al–Si alloys. Contact angle measurement is a method used to quantify the wettability of a surface. The contact angle is defined by the relationship among solid-liquid, solid-vapor and liquid-vapor interfacial energies as shown in Eq. (1) [15] and Fig. 1. cs=v ¼ cs=1 þ c1=v cos hY

ð1Þ

According to the value of the contact angle, surface are classified as hydrophobic (h > 90°) and hydrophilic (h < 90°). When the water contact angle is greater than 150° surface is called superhydrophobic [16]. There are different parameters that affect surface contact angle. These parameters can be categorized into two main classes: chemical and physical properties of the surface. Wenzel [17] studied the effect of surface roughness on the contact angle. Based on his research roughness makes hydrophobic surface more hydrophobic and hydrophilic surface more hydrophilic [18]. The contact angle is also dependent on surface chemistry. For heterogeneous surfaces, the contact angle is proportional to the fraction of the surface for each phase [19, 20]. The aim of this work is to study the effect of Si content, surface roughness, droplet size and elapsed time on CA of

γLV γSL

Water

θ

Vapor γSV

as-cast hypoeutectic Al–Si alloys using a statistical approach. A full factorial design was utilized including independent factors and their levels. By using Analysis of Variance (ANOVA) and regression analysis effect of each factor was studied on contact angles.

Experimental Methods Pure aluminum and three commercially-available hypoeutectic Al–Si alloys are tested for this project as listed in Table 1. Manual grinding machines using SiC grinding papers with water as the lubricant was used to achieve the desired surface roughness. The grit sizes, number of particles per inch, of interest were 240 (roughest), 400, 600, 800, and 1200 (finest). All samples were polished starting at the roughest grit at 200 rpm until a single mirror-like surface was obtained for each grit size. Each sample was cleaned, dried, and stored in a desiccator for 24 h to allow the development of a uniform oxide layer. Once the desired tests were completed the samples were then polished with the next highest grit size with 1200 being the final step before electro-etching. Increasing the polishing grit of surface results in the decrease of roughness. Olympus LEXT OLS4100 laser confocal microscopy was then used for measuring surface roughness. To minimize the formation and influence of any passive film on the contact angle, the experiment has been done with a Rame-Hart 250 model goniometer directly after polishing. Once the goniometer has been calibrated at room temperature for each sample, the contact angles were measured trying to minimize standard deviation error calculated by the Rame-Hart goniometer. For each sample, three data points for droplets sized 4, 6, 8, and 10 lL were applied randomly to the sample’s surface through a syringe sourced from a DI water tank. To limit contamination, sample’s surface was only wiped with a lint-free tissue once three data points were recorded or if there was no more available spacing for a droplet to be applied without interference from another droplet or the edges of the sample. All samples were tested under standard temperature and pressure with care taken to limit bouncing and any external vibrations of the droplets. Four independent parameters including silicon content, surface roughness, droplet size and elapsed time were used Table 1 Al–Si alloys used for this study

Solid

Fig. 1 The contact angle between water droplet and surface

Sample

%Al

%Si

Al

100

0

AlSi356

93

7

AlSi360

91

9

AlSi368

90.5

9.5

A Statistical Analysis to Study the Effect of Silicon Content … Table 2 Factors and levels in the factorial design

187 Table 3 ANOVA result for effect of Si content, grit size, droplet size and elapsed time on CA

Factor

Type

Levels

Values

Si (wt%)

Fixed

3

7, 9, 9.5

Grit Size

Fixed

5

240, 400, 600, 800, 1200

Grit Size

Source

DF

P-Value

Adj SS

Adj MS

F-Value

4

1492.08

373.02

31.64

0.000

2

50.10

25.05

2.12

0.124

Droplet Size (µL)

Fixed

4

4, 6, 8, 10

Si (wt%)

Elapsed time (h)

Fixed

2

0, 24

Time (h)

1

53.79

53.79

4.56

0.035

Droplet size (µL)

3

645.44

215.15

18.25

0.000

109

1285.10

11.79

Error

for contact angle measurement. Table 2 lists independent Total 119 3526.50 parameters for CA measurement. A full factorial design was utilized for the design of experiments where combinations of all factors and their levels were considered for CA measurements [21]. It resul- concluded all factors are significant except silicon content as ted in 120 combinations of all independent variables and listed in Table 3. their levels. Each combination was repeated 3 times. So in Hypothesis Test total 360 contact angle measurements were performed. To H0 : l1 ¼ l2 ¼ l3 ¼


interpret data ANOVA, multi linear regression and multi H1 : l1 6¼ l2 6¼ l3 ¼


polynomial regression were performed. Hypothesis testing was used to find the relationship between parameters, where After obtaining the significant factors it was necessary to the null hypothesis (Ho) and the alternative hypothesis (H1) study correlation between significant factors (independent assume no relationship and relationship, respectively. variable) versus CA (dependent variables). Multi Linear A significance level (a) of 0.05 was used for all statistical Regression analysis was performed for this purpose. The analyses. P-value method was used to either reject or fail to result is listed in Table 4. reject the null hypothesis. If the P-value was less than or equal to a, the null hypothesis was rejected in favor of the Regression Equation alternative hypothesis. If the P-value was greater than a, the CAðhÞ ¼ 75:31  0:00887 Grit Size þ 0:0558 Time ðhÞ null hypothesis fails to be rejected [22, 23]. þ 1:033 Droplet Size ðlLÞ Data elaboration and interpolation was performed using Minitab 16 and MATLAB R2019a software with Curve Fitting Toolbox, polyfit and polyfitn are functions which Table 4 MLR analysis result allowed for the creation of polynomial regression models in Source DF Adj SS Adj MS F-Value P-Value n dimensions with one independent variable. The Symbolic 3 1747.35 582.45 37.98 0.000 Math Toolbox and the polyvaln function helped to convert Regression Grit size 1 1053.92 1053.92 68.72 0.000 the regression polynomial into their symbolic form. The evaluation of R-squared, which is a statistical mea- Time (h) 1 53.79 53.79 3.51 0.064 sure of how close the data are to the fitted regression line Droplet size (µL) 1 639.65 639.65 41.70 0.000 [21] (also known as the coefficient of determination, or the Error 116 1779.15 15.34 coefficient of multiple determination for multiple regres- Lack-of-fit 36 747.05 20.75 1.61 0.040 sion), allowed for the creation of the quality of the interPure error 80 1032.10 12.90 polation. For plotting 3D graphs, Wolfram Mathematica Total 119 3526.50 11.2 was utilized. Coefficients

Results and Discussion Wettability Analysis Table A.1 in Appendix A shows CA values for all combinations of independent factors and their levels. In order to find parameters that are statistically significant in the variation of contact angle values, ANOVA was performed. Using P-values obtained from ANOVA analysis it can be

Term

Coef

SE Coef

T-Value

PValue

Constant

75.31

1.41

53.40

0.000

VIF

Grit size

−0.00887

0.00107

−8.29

0.000

1.00

Time (h)

0.0558

0.0298

1.87

0.064

1.00

Droplet size (µL)

1.033

0.160

6.46

0.000

1.00

Model summary S

R-sq

R-sq (adj)

R-sq (pred)

3.91631

49.55%

48.24%

46.14%

188

A. Kordijazi et al.

Fig. 2 Main effect plot for effect of grit size, Si%, elapsed time and droplet size on CA

Main Effects Plot for CA (ϴ) Data Means

Time (hr)

Si %

Grit Size

Droplet Size (μL)

81 80

Mean

79 78 77 76 75 74 73 72 240

400

600 800 1200

The regression equation shows that CA values decrease by increasing grit size and increases by increasing droplet size. In regression result time also turned out to be a non-significant factor. In our other work we studied the effect of time on hypereutectic Al–Si alloys up to 72 h and it turned out to be a significant factor. We showed that the best fit for relationship between CA and Time is rational fit. The reason for change in CA versus time is formation of oxide layer that changes homogeneity of surface. But based on the result of the present work it can be concluded that 24 h is not long enough for formation of oxide layer that makes a significant variation in CA values. The effect of all factors on CA is shown in mean effect plot, Fig. 2. As can be seen relationship between CA and Si content is not following a trend, and in the cases of CA versus time, CA slightly increases. Low R2 value (48.24%) and having a P-value of lack-of-fit less than a (Table 4) for MLR analysis show that linear regression is not an accurate fit for variation of CA. Therefore, multi polynomial regression was performed only on significant factors, i.e., grit size, and droplet size. R2 values of quadratic and cubic polynomial regression are listed in Table 5. From the table it can be seen that relationship between CA versus Grit Size and Droplet Size is better described by cubic fit compared to quadratic and linear regression. To visualize the effect of grit size and droplet size on CA, 3D graph for each combination was plotted and shown in Fig. 3. The same trend can be seen from the figures for all combinations where CA increases by decreasing grit size

7.0

9.0

0

9.5

4

24

6

8

10

Table 5 R2 values of Multiple Polynomial Regression for three Si percentages and two different elapsed time Si% 7

9

9.5

n

R2

0

2

0.6502

0

3

0.8414

24

2

0.9034

24

3

0.9357

0

2

0.5568

0

3

0.7767

24

2

0.1954

24

3

0.2624

0

2

0.6757

0

3

0.8333

24

2

0.913

24

3

0.9521

Time (h)

and increasing droplet size. It should be noted that change in grit size basically affects the surface roughness. Using confocal microscopy, surface roughness was measured for each grit size. Figure 4 shows that the values of surface roughness decrease by increasing grit size. Therefore, it can be concluded that CA increases by increasing surface roughness. Wenzel developed a model (Eq. 2) for relationship between CA and surface roughness [17]. cos hw ¼ r cos hY

ð2Þ

where hw and hY are Wenzel contact angle and ideal Young contact angle (Eq. 1), respectively, and r is the average

A Statistical Analysis to Study the Effect of Silicon Content …

189

Fig. 3 3D graphs of contact angle versus grit size and droplet size for a and b Al 7%Si (0 and 24 h), c and d Al 9%Si (0 and 24 h), e and f Al 9.5%Si (0 and 24 h)

(a) 1.2

(b) 0.5 0.4

0.8

Ra (μm)

Ra (μm)

1 0.6 0.4

0.2 0.1

0.2 0

0.3

0

500

1000

1500

0

0

500

1000

1500

Grit Size

Grit Size

(c) 0.5

Ra (μm)

0.4 0.3 0.2 0.1 0 0

500

1000

1500

Grit Size Fig. 4 Surface roughness measured by confocal microscopy versus grit size for a pure Al, b Al 7%Si and c Al 9.5%Si

190

A. Kordijazi et al.

Topography (µm)

(a)

Distance (µm) Topography (µm)

(b)

Distance (µm) Topography (µm)

(c)

Distance (µm)

Fig. 5 The surface roughness and roughness line profile of a pure Al, b A356, c Al A368

roughness ratio which is defined as the ratio between the true and apparent surface area of solid. Based on his model for hydrophilic surfaces (CA 15° and 1.5° : dD2 ðtÞ dt ¼ Ha ðI2 ðtÞÞ þ Hc ðI2 ðtÞÞ þ BM2 ðtÞ

ð1Þ It is noted that the process of alumina dissolution is simplified by separating it into two parts [16, 17]: a large portion of alumina can dissolve into the electrolyte quickly without forming agglomerates and the dissolution rate is k1 , while the rest of alumina dissolves slowly with dissolution rate k2 . Both processes are modeled by first-order differential equations, where Cf 2 ðtÞ is the undissolved alumina concentration for the fast process and Cs2 ðtÞ is the undissolved alumina concentration for the slow process. The proportion of fast dissolved alumina is represented by r and the total alumina addition for zone 2 is g2 ðtÞ. m2 is the bath mass for zone 2. The concentration of dissolved alumina is determined by several parts: fast and slow alumina dissolution process, alumina consumption, and alumina addition induced by bath flow from the neighboring zones. The alumina consumption is governed by Faraday’s law of electrolysis, where I2 ðtÞ is the total anode currents in zone 2, M is the molar mass constant of alumina, g is the current efficiency, F is Faraday’s constant and z is the number of electrons transferred. The impact of neighboring zones is modeled by two terms: M1 ð
Þ is a function of dissolved alumina concentration Cd1 ðtÞ in zone 1 while M3 ð
Þ is a function of dissolved alumina concentration Cd3 ðtÞ in zone 3. The dynamic of ACD is also determined by the material balance, where Ha ð
Þ and Hc ð
Þ are the distances caused by metal accumulation and anode consumption, and both terms are a function of local anode current I2 ðtÞ. The ACD for zone 2 is controlled by the adjustment of beam movement, which is represented by BM2 ðtÞ.

558

J. Shi et al.

Since the proposed control method is model-based, several assumptions have been made when developing this model, such that it is implementable for real-time computation. The dissolution process is simplified with constant dissolution rate though its actual mechanism is more complex and can be affected by a number of factors, such as bath temperature, alumina concentration, alumina particle size, alumina density, etc. [16] The bath temperature is also assumed to be constant and uniformly distributed, which may have 10–20 °C variation in the industrial reduction cell. In addition, the bath flow between neighboring zones is assumed to be invariant with constant bath velocity. Among these mass balance equations in Eq. (1), the local anode current I2 ðtÞ is a highly nonlinear term, which depends on the local cell conditions, including the local alumina concentration Cd2 ðtÞ, the local ACD D2 ðtÞ and a few cell design parameters.

Cell Voltage and Anode Current Distribution According to [2], although the individual anode current can be measured [18, 19] continuously, there is no explicit differential or algebraic equation that can describe its dynamics. Instead, it is implicitly related to the cell voltage model, which is normally described by several semi-empirical nonlinear equations [3], and can be generalized as below: Vcell ðtÞ ¼ Vf ðIline ðtÞ; DðtÞ; Cd ðtÞ; hÞ

ð2Þ

where, Vf ð
Þ is a highly nonlinear function for cell voltage, and Cd ðtÞ and DðtÞ means the average alumina concentration and ACD for the whole cell. h means a set of cell design parameters, which are all constant. According to this form, the following equations for each zone of the cell can be obtained and described by Fig. 1: 8   Þ; Di ðtÞ; Cd;i ðtÞ; h < Vcell;i ðtÞ ¼ Vf Ii ðtP i ¼ 1; 2; . . .; 5 I i ðt Þ Iline ¼ j ¼ 1; 2; . . .; 4 : Vcell;j ðtÞ ¼ Vcell;j þ 1 ðtÞ

19

20

F5 18

21

22

v54

v45 17

23

16

15

24

F4 14

25

26

13

12

11

Fig. 1 An example of discretised industrial aluminum smelter

A Nonlinear State Space Model In order to develop an advanced distributed control scheme, the dynamic models for each zone can be combined into a full state space model, which is basically a system described by differential algebraic equations (DAEs). This DAE model can be written in a general compact form as follows:  X_ ðtÞ ¼ f ðt; X ðtÞ; Z ðtÞ; U ðtÞÞ ð4Þ 0 ¼ gðt; X ðtÞ; Z ðtÞ; U ðtÞÞ where, the differential states X ðtÞ 2 Rn are accompanied by the algebraic states Z ðtÞ 2 Rnz , and the algebraic states are implicitly determined by the algebraic equations. Here, the number of differential states is n and the number of algebraic states is nz . For each zone of the reduction cell, there are 4 differential states (local concentration of the fast and slow undissolved alumina, local concentration of dissolved alumina and local ACD) and one algebraic state (local anode current). Therefore, X ðtÞ and Z ðtÞ can be defined as follows:  X ð t Þ ¼ ½ X1 ð t Þ X 2 ð t Þ X 3 ð t Þ X 4 ð t Þ X 5 ð t Þ  T ð5Þ Z ðtÞ ¼ ½ Z1 ðtÞ Z2 ðtÞ Z3 ðtÞ Z4 ðtÞ Z5 ðtÞ T and 

Xi ðtÞ ¼ ½ Cf ;i ðtÞ Zi ðtÞ ¼ Ii ðtÞ

Cs;i ðtÞ

Cd;i ðtÞ Di ðtÞ T

i ¼ 1; 2; . . .; 5

ð6Þ

ð3Þ

Therefore, for the whole cell described in Fig. 1, n ¼ 20 and nz ¼ 5. It is noted that f ð
Þ is a vector of mass balance equations for each zone, while gð
Þ is a vector of constrained algebraic equations defined as below:

27

28

v43

v34

where, Ii ðtÞ; Di ðtÞ and Cd;i ðtÞ are the local anode current, ACD and alumina concentration in zone i. Therefore, the local conditions in each zone is coupled through the constrained algebraic equations of cell voltage and anode current.

F3 10

29

30

v32

v23 9

31

8

7

32

F2 6

33

34

v12 5

35

v21 4

3

36

F1 2

1

An Advanced Nonlinear Control Approach for Aluminum …

559

Formulation of Nonlinear Control Problems In the previous section, a state space model has been built to describe the distributed dynamics of process variables in an industrial aluminum reduction cell. Based on this model, a nonlinear approach will be proposed to control the cell, aiming to achieve more uniform cell conditions with less variations in local alumina concentration, ACD and individual anode current. These can be formulated into different control targets for the nonlinear model predictive control (MPC), and an online constrained nonlinear optimization problem will be solved to calculate the control inputs to the aluminum reduction process.

Control Scheme Based on Nonlinear MPC Benefiting from the measurement of individual anode current, more advanced distributed control methods can be developed to control and monitor the local conditions in the cell. In this work, the control of the aluminum reduction process is studied under the framework of NMPC, which is an advanced process control method used to control a process while satisfying a set of constraints. The main feature of NMPC is its ability to predict the future behavior of the process while optimizing the current control actions, which is achieved by repeatedly solving an optimization problem within a receding finite-time horizon. For the aluminum smelting process, the objective function can be formulated into different ways by incorporating both mass and thermal dynamics in the cell. As an example, assuming the goal of the NMPC is to minimize the spatial variations in the cell, which is characterized by controlling alumina concentration and cell voltage to their setpoints. The controlled variables include local alumina concentration and cell voltage, while the manipulated variables include alumina feeding rate and beam movement. The control objective for the aluminum smelter can then be formulated as a squared error objective as follows: min J ¼

X;DBk ;DFk

 N  X Ck  Ck;sp Q1

Vk  Vk;sp 0    DFk R1 0 ½ DFk þ 0 R2 DBk k¼1

 0 ½ Ck  Ck;sp Q2  DBk 

Vk  Vk;sp 

Some Discussions on Control Targets With the advances in mathematical modeling and fast evolution of computer technology, the control systems for the aluminum reduction process have improved accordingly and have succeeded in achieving better cell condition and performances. However, most of the control structure and algorithms are designed for a single control target or restricted to a specific aspect of the process [20], and hence only suboptimal solutions can be obtained. The reasons include: (1) the aluminum reduction process is a complex process with extensive nonlinearities; (2) there exist interactions between thermal and mass balance throughout the cell; (3) various dynamics and responses for different process variables. Therefore, the control of this process is essentially a multivariable control problem, and it becomes even more critical and challenging when a cell is discretized for the study of its spatial distribution. • Objective Function

ð7Þ subject to:   0 ¼ f dX dt ; X; DF; DB 0 ¼ gðX; V; DF; DBÞ DFL  DF  DFU DBL  DB  DBU DTB;L  DTB

here J is the objective function and consists of the weighted output and input error by the weighting matrix Q1 ; Q2 ; R1 and R2 . At time k, Ck is vector of local alumina concentration and Ck;sp is its setpoint, whereas Vk is the cell voltage and Vk;sp is its setpoint. DFk is the increment of alumina feeding rate, while DBk is the increment of beam movement. This objective is subject to the constraints listed in Eq. (8), where f ð
Þ is the dynamic discretized cell model, gð
Þ is the algebraic equations describing anode current distribution. X is the vector of all state variables and V is cell voltage. DFL is the lower bound of alumina feeding rate change, whereas DFU is the upper bound of alumina feeding rate change. Similarly, DBL means the lower bound of beam movement, whereas DBU means the upper bound of beam movement. In the existing control method, the beam is normally adjusted in a discontinuous manner, which is moved up by a certain height every 2–3 h. Therefore, a constraint on DTB is assumed, which means the time period between two beam movement actions, and it is limited by a minimum period DTB;L .

ð8Þ

Under the framework of MPC, it becomes possible to develop optimal control for the aluminum reduction process, aiming to achieve optimal cell performance by incorporating multiple control targets and process constraints. A good example is the tighter control of alumina concentration and individual anode current, which is believed to minimize the spatial variations in the cell and thus improve current efficiency and reduce greenhouse gas emission. Some simulation results will be presented in the following section.

560 Table 1 Summary of inputs, outputs, disturbances for the aluminum reduction process

J. Shi et al. Control Inputs

Alumina feeding Beam movement and anode adjustment AlF3 addition Electric power input, including line current Other bath mass compositions

Measurements

Cell voltage and line current (automatic and continuous) Individual anode current (automatic and continuous) Beam position (automatic and continuous) Bath temperature (manual, once a day or a week) Bath acidity (manual, once a week) Alumina concentration (only subject to experiments)

Disturbances

Anode setting, dressing/redressing Metal tapping Additional alumina Inconsistent quality of alumina sample, such as particle size distribution and bulk density Varying alumina mass dumping weight Various bath flow pattern and velocity Anode effect

Control targets

Less variations in process conditions, including uniform distribution of alumina concentration, ACD, individual anode current, bath temperature, etc. Better cell performances, including higher current efficiency, lower energy consumption and lower PFC emission More stable cell conditions and less abnormalities, such as anode effect, anode shorting, sludge formation, etc.

From the viewpoint of process control, the aluminum reduction process can be regarded as a dynamic system having numerous inputs, outputs, measurements, and disturbances. These can be summarized as below: According to the Table 1, the development of optimal cell control systems should not only deal with the multivariable and nonlinear characteristics of the process, but also needs to take into account the various disturbances that may perturb the nominal operations. This addresses the importance of building more sophisticated mathematical models, upon which the objective function of the MPC can be customized. The objective function is allowed to include multiple weighted control targets, which are to be minimized with different performance indexes. Another advantage of the MPC approach is to involve constraints, and this feature makes the control algorithms more applicable for the physical plants. • Nonlinear State Observer Since most of the process variables, e.g. local alumina concentration and ACD, cannot be directly measured, a state observer is needed to provide estimates for the NMPC. Besides, the importance of state observer is addressed [12] from the viewpoint of NMPC design, where the quality of estimates is closely related to the complexity and efficiency of control algorithm. In [2], a multi-level nonlinear state observer is proposed to estimate the spatial distribution of alumina concentration, and this approach has been verified

by experimental studies. Therefore, it can be a good candidate of state observer that can be incorporated with NMPC.

Results and Discussion In this section, some simulation results will be presented as an example to show the effectiveness of the proposed control method, where the objective is to improve current efficiency. According to a previous work [21], the current efficiency of an industrial smelting cell is related to several factors and can be described by the following empirical model: %CE ¼ 103:68  134:85  Cal  50:438ð%alumina  3:463Þ  ðCal  0:0357Þ  0:969  %alumina  1:192  Cal  0:0638  %Anode balance þ 0:0978  ð%Anode balance  17:719Þ  ðnoise  0:3815Þ ð9Þ where, %CE means % current efficiency, %alumina is average alumina concentration, Cal is the solubility of aluminum in bath, Anode balance is the standard deviation of the anode current divided by the average anode current, and noise is the difference between the maximum and minimum pseudo-resistance measured at the predominate metal pad roll period. It is not difficult to find that the %CE can be improved if the cell has low %alumina or more stable conditions (reduced noise and %Anode balance).

An Advanced Nonlinear Control Approach for Aluminum …

In this paper, the coefficient %alumina and noise are investigated. The aluminum reduction cell is divided into 5 zones to simulate the spatial distribution of alumina concentration, ACD, anode current, etc. In each zone, the local alumina concentration can be controlled at a certain target by individually manipulating each feeder, which feeds alumina in a continuous manner. In the meanwhile, cell voltage is controlled with less variation by optimizing beam movement.

Control of the Local Alumina Concentration In this simulation study, the plant data of an industrial cell is used to simulate the spatial distribution of process variables. As shown in Fig. 2, the cell is initially controlled by the existing control method in the first 12 h, and the proposed control method takes over for the next 12 h. It is noted that uniformity of alumina concentration is achieved by using this new control method. Also, the alumina concentration can be controlled at different targets, which are Target 1: 2.7 wt% (from 12 to 16 h), Target 2: 2.2 wt% (from 16 to 20 h) and Target 3: 3.0 wt% (from 20 to 24 h). The corresponding feed control actions for each control target are shown in Fig. 3, whereas the curves for feed rate overlap each other. It is noted that the proposed control method

561

requires alumina to be fed into each zone continuously, whereas the existing control method is based on the ‘demand feed’ principle [22].

Control of the Cell Voltage The cell voltage is also controlled at a certain target, which is shown by the horizontal dotted line in Fig. 4. It is noted that the cell voltage is a highly nonlinear function of many process variables and parameters, including alumina concentration, ACD, anode current, bath temperature, etc. However, the most sensitive variable is ACD, and thus the beam movement dominates the control actions of the NMPC. At time t = 12 h, there is a sudden change in cell voltage, which is caused by the alteration of controller. Similarly, the variation in cell voltage is also reduced, which is basically achieved by more frequent beam movements shown in Fig. 5. Consequently, the changes of anode current and ACD are shown in Figs. 6 and 7 respectively.

Improvement of the Current Efficiency According to Eq. (9), the current efficiency in each zone can be calculated using nominal values, whereas the coefficient

Fig. 2 Comparison of alumina concentration between existing control and nonlinear control

562

J. Shi et al.

Fig. 3 Comparison of alumina feeding rate between existing control and nonlinear control

Fig. 4 Comparison of cell voltage between existing control and proposed control

of variation of the current distribution %Anode balance is typically around 15% [23], noise is 0.3 and solubility of aluminum in bath (Cal) is 3.7% [21]. The results are summarized in the following table. From Table 2, it is shown that the CE varies in different zones due to the uniform distribution of process variables, and higher CE can be achieved when the cell is controlled by the proposed method. During the existing control period, the average alumina concentration over 12 h is about 3.0%, and the corresponding average CE is 94.68%. However, the CE can be increased by 0.49% when the alumina concentration

is controlled at 2.7% and then further increased by 1.02% when the alumina concentration decreased to 2.2 wt%. It is noted that this increase in CE is mainly due to the reduced alumina concentration rather than ACD, because the setpoint for cell voltage is consistent for the whole control period.

Future Work As the simulation results presented in this paper, the proposed nonlinear control approach has the potential to

An Advanced Nonlinear Control Approach for Aluminum …

Fig. 5 Comparison of beam movement between existing control and proposed control

Fig. 6 Comparison of anode current distribution between existing control and proposed control

563

564

J. Shi et al.

Fig. 7 Comparison of ACD between existing control and proposed control

Table 2 Summary of calculated current efficiency for existing control and proposed control

Control method

Time (h)

Location

Avg. Alumina concentration (wt% )

Avg. ACD (cm)

CE (%)

Avg. CE (%)

Existing control method

0–12

Zone 1

3.10

2.58

94.54

94.68

Zone 2

3.05

2.93

94.62

Zone 3

2.83

2.40

94.71

Zone 4

2.96

2.75

94.84

Zone 5

3.03

2.84

94.63

Zone 1

2.70

2.57

95.05

Zone 2

2.70

2.87

95.11

Zone 3

2.70

2.42

95.03

Zone 4

2.70

2.72

95.07

Zone 5

2.70

2.79

95.09

Zone 1

2.20

2.61

95.68

Zone 2

2.20

2.88

95.72

Zone 3

2.20

2.46

95.66

Zone 4

2.20

2.74

95.70

Zone 5

2.20

2.81

95.72

Zone 1

3.00

2.61

94.85

Zone 2

3.00

2.87

94.89

Zone 3

3.00

2.48

94.83

Zone 4

3.00

2.73

94.87

Zone 5

3.00

2.80

94.88

Proposed control method

12–16 (Target 1)

16–20 (Target 2)

20–24 (Target 3)

95.07

95.70

94.86

An Advanced Nonlinear Control Approach for Aluminum …

increase CE for the aluminum smelter. Therefore, the next stage is to study the implementation of the proposed control method and conduct experimental studies.

Conclusion In this paper, a nonlinear control approach for the aluminum reduction process is presented. This approach is different with the existing control method in several aspects: (1) it is designed based on a dynamic nonlinear mathematic model; (2) it is able to provide optimal local control actions; (3) it is a flexible control approach and can achieve multiple control targets by customizing the objective function. The superiority of this approach is illustrated by a simulation example, where the current efficiency can be improved by reducing the cell variations, including local alumina concentration and cell voltage. Acknowledgements The authors wish to acknowledge the technical and financial support from Emirates Global Aluminum, Jebel Ali Operations.

References 1. Grjotheim K, Welch BJ (1988). Aluminium smelter technology–a pure and applied approach. Aluminium-Verlag, Konigsallee. 2. Yao Y, Cheung CY, Bao J, Skyllas-Kazacos M, Welch BJ, Akhmetov S (2017) Estimation of spatial alumina concentration in an aluminium reduction cell using a multilevel state observer. AIChE 68(7): 2806–2818. 3. Haupin W (1998) Interpreting the components of cell voltage. Light Metals 1998, TMS, p 531–537. 4. Jessen SW (2008) Mathematical modelling of a Hall-Héroult aluminium reduction cell. Master thesis, Technical University of Denmark. 5. Jens B (1992) A method for the control of alumina concentration in aluminium reduction cells. Modeling, Identification and Control 13(1): 41–49. 6. Johannes A (1986) Adaptive control of alumina. MIC 7: 45–56. 7. Kvande H, Moxnes BP, Skaar J, Solli PA (1997) Pseudo resistance curves for aluminium cell control - alumina dissolution and cell dynamics. Light Metals 1997, TMS, p 403–409.

565 8. McFadden FJS, Bearne GP, Austin PC, Welch BJ (2001) Application of advanced process control to aluminium reduction cells–a review. Light Metals 2001, TMS, p 1233–1242. 9. Gran E (1980) A multi-variable control in aluminum reduction cells. Modeling Identification and Control. 1(4): 247–258. 10. Moore KL, Urata N (2001) Multivariable control of aluminum reduction cells. Light Metals 2001, TMS, p 1243–1249. 11. McFadden FJS, Welch BJ, Austin PC (2006) The multivariable model-based control of the non-alumina electrolyte variables in aluminium smelting cells. JOM 58(2): 42–47. 12. Kolås S, Wasbø SO (2010) A nonlinear model-based control strategy for the aluminium electrolysis process. Light Metals 2010, TMS, p 501–505. 13. Kolås S (2009) Method and means for controlling an electrolysis cell. International Patent WO 2009/067019A1, 28 May 2009. 14. Moxnes B, Solheim A, Liane M, Svinsås E, Halkjelsvik A (2009) Improved cell operation by redistribution of the alumina feeding. Light Metals 2009, TMS, p 461–466. 15. Shi J, Wong CJ, Yao Y, Bao J, Skylla-Kazacos M, Welch BJ (2018) Advanced feeding control of the aluminium reduction process. Paper presented at the 12th Australasian Aluminium Smelting Technology Conference, Queenstown, New Zealand. 16. Biedler P (2003) Modeling of an aluminum reduction cell for the development of a state estimator. PhD thesis, West Virginia University. 17. Haverkamp RJ, Welch BJ (1997) Modelling the dissolution of alumina powder in cryolite. Chemical Engineering and Processing. 3: 177–187. 18. Potocnik V, Arkhipov A, Ahli N, Alzarooni A (2017) Measurement of DC busbar currents in aluminium smelters. Proceedings of 35th International ICSOBA Conference, Hamburg, Germany, Travaux 46, 1113–1128. 19. Cheung CY, Menictas C, Bao J, Skyllas-Kazacos M, Welch BJ (2013) Characterization of individual anode current signals in aluminum reduction cells. Industrial & Engineering Chemistry Research. 52(28): 9632–9644. 20. Zhang H, Li T, Li J, Yang S, Zou Z (2016) Progress in aluminum electrolysis control and future direction for smart aluminum electrolysis plant. JOM 69(2): 292–300. 21. Tarcy GP, Tørklep K (2005) Current efficiency in prebake and Søderberg cells. Light Metals 2005, TMS, p 319–324. 22. Robilliard KR, Rolofs B (1989) A demand feed strategy for aluminium electrolysis cells. Light Metals 1989, TMS, p 269–273. 23. Guérard S, Côté P (2019) A transient model of the anodic current distribution in an aluminum electrolysis cell. Light Metals 2019, TMS, p 595–603.

Model Based Approach for Online Monitoring of Aluminum Production Process Lucas José da Silva Moreira, Gildas Besançon, Francesco Ferrante, Mirko Fiacchini, and Hervé Roustan

Abstract

In Hall-Heroult process for aluminium production, estimating the alumina concentration and the anode-cathode distance (ACD) remains a challenge. One of the difficulties arises from the fact that it is not possible to measure those quantities continuously during the pot operation. This article presents a novel approach for an online estimating alumina concentration and ACD in a regular aluminumreduction pot cell using a Linear Kalman Filter. This is done by using an appropriate dynamical model for the pot, which is obtained by combining the first principle modeling and experimental identification of alumina concentration behavior from irregularly sampled data. Moreover, a dynamical model for the pot resistance is identified as a function of the alumina concentration and ACD data. The proposed approach is validated on an industrial platform. Keywords

Aluminum electrolysis • State estimation • Kalman filter

L. J. da Silva Moreira (B) · G. Besançon · F. Ferrante · M. Fiacchini University of Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab Grenoble, Grenoble, France e-mail: [email protected] G. Besançon e-mail: [email protected] F. Ferrante e-mail: [email protected] M. Fiacchini e-mail: [email protected] H. Roustan Rio Tinto, Laboratoire de Recherche des Fabrications, Saint-Jean-de-Maurienne, France e-mail: [email protected]

Introduction Aluminum manufacturing is a challenging industrial area based on the Hall-Heroult process [1,2]. In this setting, model and control challenges arise from the limitations in the process information continuously available, which can lead to inaccurate results [3]. Moreover, this restrains the process production efficiency since it is risky to work with uncertainties or imprecise data [4]. During the electrolysis reaction which is the basis of the process, the anode-cathode distance (ACD) is continuously affected by liquid aluminum production, and carbon consumption. Other aspects affect the ACD as the electric perturbations and changes in the composition of the bath. An inappropriate ACD can impact in the efficiency of the process and safety conditions. In fact, a large ACD decreases the pot cell production and a small value can cause a short-circuit between the produced aluminum and the anode [5]. Unfortunately, it is not possible to measure it during the process operation, and its dynamical behaviors is very difficult to represent in full details. See [3,6] for more details. Another essential variable in aluminum production is the dissolved alumina concentration (w Al2 O3 ). Generally, it is required to keep it in a specific range to avoid the formation of sludge or the onset of anode effect [7]. Although monitoring importance, measurements this quantity continuously is costly. In common operation, just a few samples per week are manually taken, which makes it difficult to obtain an experimental model. In practice, to monitor and regulate aluminum production, an indirect measurement is used: the pseudo-resistance. This signal is computed using the line current and pot voltage direct measurements. Other important variables for the Hall-Heroult process like aluminum fluoride concentration, bath temperature, metal height, etc. are only sporadically measured. The pseudo-resistance is used to determine the alumina feed rate injected in the system. The alumina feeding rate is based on the alternation of slower (underfeeding) and faster (overfeed-

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_78

566

567

Model Based Approach for Online Monitoring …

ing) periods than the rate corresponding to normal consumption of the cell [8]. The feeding periods alternation occurs when the rate of variation of pseudo-resistance exceeds a set value. Moreover, it is usually defined a setpoint resistance and thermal balance to ensure control stability and obtain a good current efficiency. This value is adjusted by the ACD regulation [8]. Many authors indicate that the pseudo-resistance could not be a good indicator for the operation [9,10]. Because of this lack of continuous measurements, nonlinear estimatorshavebeendevelopedbyafewresearchers[3,11,12]. All of them are focused on a two-step procedure: Obtain a nonlinear model and apply an estimator strategy. However, an imprecise model can generate inaccurate results. As the Hall-Heroult process has a complex dynamics, it is not easy to find a proper model that reproduces its behavior. Moreover, it is necessary to have an initial ACD measurement which is not possible during operation. To overcome these limitations, some authors have been working on iterative filtering procedures yet, these require more computation effort [4]. In this paper, an online monitoring technique based on Linear Kalman filtering state-estimation is proposed. It uses a model that combines physical-chemical preliminary knowledge and experimental identified aspects. This system representation enables a real-time overall alumina concentration and ACD monitoring which can be used to avoid anode effects and improve the production. This procedure is validated with operational collected data and tested for different conditions in APXe50 pot cell localized in Laboratoire de Recherches de Fabrications (LRF) in Saint Jean de Maurienne, France. The paper is organized as follows: The modeling approach and validation are presented in section “Modeling”. The online monitoring and experimental results are explained in section “Online Monitoring”. The conclusions are discussed in section “Conclusion”.

Modeling The process description of this paper is based on dynamical equations using the manipulated and process variables available in modern aluminum reduction cells. Initially, the ACD modeling is explained based on a chemical balance. Moreover, some simplified models for the alumina concentration and the pot resistance are developed. At the end of this section, an overall state-space model for the aluminum process is given. It is assumed that the pot is always in regular operation. In particular, it is assumed that line current and alumina pot feeding do not undergo on a significant overshoot.

Anode-Cathode Distance The ACD is defined as the difference between the heights of aluminum produced (Al H eight ) and carbon consumed (C H eight ). Its dynamics depends on the anodes busbar beam movement

(BM) and the initial distance (AC Dini ) as follows: AC D(t) = Al H eight (t) − C H eight (t) + B M(t) + AC Dini (1) The beam movement derivative is considered as one of the system inputs (u 1 ): u 1 (t) =

d B M(t) dt

(2)

Using the electrochemical relations of chemical balance it is possible to compute the ACD and its variation in discretetime for computer implementation by the following equation structure: AC D[n + 1] = AC D[n] + Ts (u 1 [n] + β I [n])

(3)

where Ts is the sampling time, β is a combination of pot physical-chemical parameters and I is the line current applied to the system. As it is not possible to measure the ACD during the operation, the value of β is computed using theoretical values for a regular pot operation. Moreover, during the metal tapping, it is not considered that the beam is moving.

Alumina Concentration d The variation of the alumina concentration ( dt w Al2 O3 ) is given by the difference between the concentration amount of dissolved alumina (w Al2 O3in ) that is resulted from the alumina injected in the pot by the feeders and the amount of alumina that is consumed by the chemical equation (w Al2 O3cons ). Hence the following chemical balance can be considered:

d w Al2 O3 (t) = w Al2 O3in (t) − w Al2 O3cons (t) dt

(4)

It can be assumed a quick alumina solving [13]. This approach does not consider any agglomeration of the alumina powder since the dissolution constant is 0.099s −1 and the sampling rate is 1 min. The frequency of the feeders (F) is considered as one of the system inputs (u 2 ): u 2 [n] = F[n − D]

(5)

where D is a constant time-delay due to alumina diffusion lag. Therefore, Eq. (4) can be rewritten in discrete-time as: w Al2 O3 [n + 1] = w Al2 O3 [n] + Ts (α1 u 2 [n] − α2 I [n]) (6) where α1 and α2 are a combination of pot physical-chemical parameters.

568

L. J. da Silva Moreira et al.

Alumina Concentration

Pot Resistance

%

ACD =4.2 cm ACD =4.3 cm ACD =4.4 cm ACD =4.5 cm ACD =4.6 cm ACD =4.7 cm ACD =4.8 cm

Simulation Measurements 1500

2000

2500

3000

Time(min) Fig. 1 Alumina concentration model validation

As in LRF pots the aluminum concentration is measured a few times a day and in the same pot position, it is possible to identify an experimental model from the collected data and obtain values of α1 and α2 for regular operation. Initially, the time delay D is estimated using unconstrained nonlinear optimization techniques and validated for different data set. Equation (6) needs a previous value of w Al2 O3 to calculate the next concentration. Then, the model is initialized with a measurement and the simulation is started using the signals of u 2 and I. Every time that there is a new alumina concentration data collection, the model is reinitialized to improve the simulation results. In Fig. 1, it is shown a comparison between the model simulation using parameters α1 and α2 estimated with the collected alumina concentration and the respective inputs. It is possible to verify that the model provides a very good prediction of the plant behavior. The mean absolute relative error between the model and the measurements is 3.5176%. Hence, this model can be considered validated and used to simulate and predict alumina concentration over long time horizons.

Pot Resistance

1

2

3

4

5

Alumina Concentration (%) Fig. 2 Typical pot resistance curve as function of alumina concentration and ACD

regular operational specification, the low and high alumina concentrations plot regions i.e. the anode effect and sludge formation areas are avoided. Then, the curves shown in Fig. 2 can be parameterized by the following equation: R(t) = c × w Al2 O32 (t) + (d + e × AC D(t))w Al2 O3 (t) + ( f + g × AC D(t))

(7)

where c, d, e, f and g are constant parameters to be determined. Equation (7) can be derived to compute the resistance variation in discrete-time by the following relation: R[n + 1] = R[n] + (e × w Al2 O3 [n]AC D[n] + (2c × w Al2 O3 [n] +e × AC D[n])w Al2 O3 [n] + d × w Al2 O3 [n] + g

The pot resistance is an indirect measurement calculated via the pot voltage and line current. The pot voltage is modeled by a complex relation that uses ACD and alumina concentration [14]. Besides that, it is taken into account other system operational parameters that cannot be measured continuously or that are not measured. Therefore, this makes it difficult to obtain a precise model. Aiming to obtain a simpler resistance model, it is assumed that all these unknown factors are constant during the pot operation . Moreover, it is not necessary to know any information about them, only the ACD and w Al2 O3 values are required. It is known that the resistance model generates curves as shown in Fig. 2 for different ACD and w Al2 O3 . During the

×AC D[n])

(8) where: AC D[n] = w Al2 O3 [n] =

AC D[n] − AC D[n − 1] Ts

w Al2 O3 [n] − w Al2 O3 [n − 1] Ts

(9)

(10)

Notice that Eq. (8) needs an initial ACD value and this values is not measurable. Only the ACD variation is calculated by Eq. (3). This problem can be solved by re-arranging Eq. (8)

569

Model Based Approach for Online Monitoring …

a13 [n] = (2c(α1 u 2 [n] − α2 I [n]) + e(u 1 [n] + β I [n]) (14)

Pot Resistance

Measured Simulation

700

800

900 1000 Time (min)

1100

b1 [n] = (d(α1 u 2 [n] − α2 I [n]) + g(u 1 [n] + β I [n])) (15)

1200

Fig. 3 Resistance model validation

to set as the identifiable parameter the initial ACD combined by the other unknown variables. In Fig. 3, a comparison between the model output simulation and real measurements is shown. The mean absolute error index computed for this data set is 2.2054%. However, it can be seen a small drift in Fig. 3. This happens because the model structure from Eq. (8) reproduces the resistance variation and needs an initial value.

State-Space Model From the results described in previous sections, it is possible to obtain a discrete-time state-space model of the plant, with state vector defined by: ⎤ ⎡ ⎤ R[n] x1 [n] x[n] = ⎣x2 [n]⎦ = ⎣ AC D[n] ⎦ w Al2 O3 [n] x3 [n] ⎡

(11)

The current intensity is not considered as a control input because, due to the operational constraints, it cannot be manipulated. Hence, this signal is considered as a measured disturbance in the system. Organizing Eqs. (3), (6) and (8) results in the following description: ⎧ ⎡ ⎤ ⎡ ⎤ 1 a12 [n] a13 [n] b1 [n] ⎪ ⎪ ⎪ ⎥ ⎢ ⎥ ⎪ ⎨x[n + 1] = ⎢ 0 ⎦ x[n] + ⎣b2 [n]⎦ ⎣0 1 0 0 1 b3 [n] ⎪ ⎪ ⎪ ⎪ ⎩ R[n] = 1 0 0 x[n]

b2 [n] = (u 1 [n] + β I [n])

(16)

b3 [n] = (α1 u 2 [n] − α2 I [n])

(17)

which all the parameters known. This model representation permits to design a Linear Kalman filter usage [15], even with a nonlinear model. This is justified because Eq. (12) is affine in the state. Hence, it is possible to recover the state vector for a given input set. This makes it possible to use the valid model for online ACD and w Al2 O3 monitoring.

Online Monitoring As the model is valid and it is possible also to organize it in a state-space form, the states can be estimated using a linear observer fed with the plant inputs and outputs. The schematic implementation is shown in Fig. 4. The estimation ˆ alumina concentraof the state signals for pot resistance ( R), ˆ tion (w Al2 O3 ), and anode-cathode distance ( ACˆ D) are calculated in real-time from inputs and output signals. Therefore, this makes it possible an online state monitoring. The observer selected is a Kalman Filter. It requires first to tune the noise matrices to perform the estimations. As the chosen sampling time is 1 min, the noise covariance level is set in small value for the process and measurement matrices. The covariance matrix has to be tuned as well. According to the chosen matrix values, the convergence can be faster or slower. In this case, it is recommended a higher value for the ACD covariance than other states since it is not possible to measure it. Further details in Kalman Filter can be found in [16]. To ensure the performance, the filter was tested using different initial values of ACD and w Al2 O3 . The resulting estimations for each of them, labeled as 1, 2, 3 and 4, are compared with real measurements of R and values computed by

(12)

where: a12 [n] = e(α1 u 2 [n] − α2 I [n])

(13)

Fig. 4 Schematic observer implementation

570

L. J. da Silva Moreira et al. Alumina Concentration

Pot Resistance

700

800

900

1000

1100

%

1 2 3 4 Sim. Meas.

Simulation Measurements

1200

1.5

ACD

9.77

1.52

1.53

1.54

900 1000 1100 Alumina Concentration

1200

Nominal Value (%)

800

1.55 4 10

Individual Anode Current 1 2 24 23 3 4 22 21

8.79

cm 700

1.51

7.81 6.84 5.86 4.88 3.90 1.5

1.51

1.52

1.53

1.55 4 10

%

Time(min)

1.54

Fig. 6 Anode effect monitoring

700

800

900 1000 Time (min)

1100

1200

the individual current anodes measurements many peaks. This characterizes an anode effect in the pot cell that was noticed by model based monitoring model based system.

Fig. 5 States estimations

Conclusion the model for all states, as shown in Fig. 5. Notice the fast convergence for all state estimations, less than 1 hour, even with different initial conditions. As R is measured, it converges faster than other states variables. The other signals estimations take more time to converge to a value closer to those computed by the model. Therefore, the efficiency of the state estimations can be guaranteed and they can be used for online monitoring of a regular pot cell. This online monitoring can be used to predict local anode effects as well, around the alumina collection area. This is done by monitoring a small concentration of alumina. In Fig. 6, it is shown the alumina concentration model simulation between the measurements and the surrounding anodes currents measurements which is labeled with the respective position number. It is possible to verify that after alumina concentration reaches small values, the currents start in anode 21 to have a disturbance behavior. After some time, it is verified in

In this article, a novel approach for online monitoring of aluminum reduction cells based on the model is proposed. This approach combines the available signals in the pot cell, physical-chemical knowledge, and system identification methods to obtain a state-space model. This representation captures only the regular operation dynamics. Then, it is possible to obtain a simple model that captures the desired operational dynamics, neglecting complex relations. This model structure can be applied to a Linear Kalman Filter and used it to estimate two important signals for the pot operation: ACD and w Al2 O3 . The estimation results were tested using experimental data, which showed good accuracy for ACD, and alumina concentration estimation, as well as resistance prediction. Moreover, it can allow to detect local anode effects based on the alumina concentration monitoring. In conclusion, the proposed method seems to provide promisingly efficient results without

Model Based Approach for Online Monitoring …

knowing much about the pot dynamics. Then, it can be used for pot monitoring during regular operation. Acknowledgements The authors wish to acknowledge project PIANO funded by the French Fonds Unique Interministériel (FUI).

References 1. K. Grjotheim, Aluminium Electrolysis: Fundamentals of the HallHéroult Process. Aluminium-Verlag, 1982. 2. K. Grjotheim and B. J. Welch, Aluminium Smelter Technology: A Pure and Applied Approach. Aluminium-Verlag; 2nd edition, 1980. 3. S. R. Jakobsen, K. Hestetun, M. Hovd, and I. Solberg, “Estimating alumina concentration distribution in aluminium electrolysis cells,” IFAC Proceedings Volumes, vol. 34, no. 18, pp. 303–308, 2001. 4. Y. Yao and J. Bao, “State and parameter estimation in Hall-Héroult cells using iterated extended Kalman filter,” IFAC-PapersOnLine, vol. 51, no. 21, pp. 36–41, 2018. 5. J. T. Keniry, G. C. Barber, M. P. Taylor, and B. J. Welch, “Digital processing of anode current signals: an opportunity for improved cell diagnosis and control,” Light Metals, pp. 1225–1232, 2001. 6. Y. Yao, C.-Y. Cheung, J. Bao, M. Skyllas-Kazacos, B. J. Welch, and S. Akhmetov, “Estimation of spatial alumina concentration in an aluminum reduction cell using a multilevel state observer,” AIChE Journal, vol. 63, no. 7, pp. 2806–2818, 2017.

571 7. G. P. Bearne, “The development of aluminum reduction cell process control,” JOM, vol. 51, no. 5, pp. 16–22, 1999. 8. P. Homsi, J.-M. Peyneau, and M. Reverdy, “Overview of process control in reduction cells and potlines,” in Essential Readings in Light Metals, pp. 739–746, Springer, 2016. 9. Y. Yao, C.-Y. Cheung, J. Bao, and M. Skyllas-Kazacos, “Monitoring local alumina dissolution in aluminum reduction cells using state estimation,” in Light Metals 2015, pp. 577–581, Springer, 2015. 10. W. Haupin and E. J. Seger, “Aiming for zero anode effects,” in Essential Readings in Light Metals, pp. 767–773, Springer, 2016. 11. S. Kolås, B. Foss, and T. S. Schei, “State estimation is the real challenge in NMPC,” in International workshop on assessment and future directions of nonlinear model predictive control, Pavia, Italy, 2008. 12. K. Hestetun and M. Hovd, “Detecting abnormal feed rate in aluminium electrolysis using extended kalman filter,” IFAC Proceedings Volumes, vol. 38, no. 1, pp. 85–90, 2005. 13. P. Biedler, Modeling of an aluminum reduction cell for the development of a state estimator. PhD thesis, West Virginia University, 2003. 14. W. Haupin, “Interpreting the components of cell voltage,” in Essential Readings in Light Metals, pp. 153–159, Springer, 2016. 15. R. E. Kalman, “A new approach to linear filtering and prediction problems,” Journal of basic Engineering, vol. 82, no. 1, pp. 35–45, 1960. 16. D. Simon, Optimal state estimation: Kalman, H infinity, and nonlinear approaches. John Wiley & Sons, 2006.

Predictive Analytics for Enhancing Productivity of Reduction Cells Shanmukh Rajgire, Abhijeet Vichare, Amit Gupta, and Devendra Pathe

Abstract

With increasing energy prices and lower LME, aluminum smelters across the globe are focusing on reducing specific energy consumption. Increasing current efficiency (CE) not only reduces energy but also increases productivity. Since, early 1990s, fundamental studies and lab-scale experiments have provided insights on CE and its dependence on process parameters, however these were based on ideal conditions and actual plant data should also be considered. This article presents a predictive model for CE utilizing machine learning algorithm (random forest regressor) on 360 kA pot-line data. The model helps in identifying the optimal parameter range to maximize CE of individual pot. Results are compared with fundamental and lab-scale experiments published in literature, showing good agreement in most cases along with few insights. Impact of parameters such as cathode drop, bath height, composition, etc. has been discussed. Keywords









Machinelearning Predictivemodel Manufacturing Current efficiency Process parameters Aluminium smelter




S. Rajgire (&)
A. Gupta Aditya Birla Science and Technology Company (P) Ltd, MIDC, Taloja, Panvel, 410208, Maharashtra, India e-mail: [email protected] A. Vichare Presently Affiliated with Meritus Interlytics Private Limited, Gachibowli, Hyderabad, 500084, India D. Pathe Hindalco Industries Ltd, Mahan, Badokhar, 486892, Madhya Pradesh, India

Introduction Aluminium is commercially produced through the electrochemical decomposition of alumina, schematic of electrolytic cell/pot is shown in Fig. 1a. It is a highly energy intensive process with electricity comprising 30–40% of the cost of production. During the process, aluminium formed, reacts with carbon dioxide to form alumina, this phenomenon is generally termed as the back reaction. The extent of back reaction is dependent on the distance between the anode and the metal pad, and the extent of reaction zone having diffused CO2 gas, as shown in Fig. 1b. Thus, reducing the actual aluminium production that is quantified in terms of current efficiency (CE). Modern smelters run at current efficiencies close to 94% with the benchmark of 96% [1]. An improvement in current efficiency corresponds to direct benefit in production without any additional cost except alumina. CE is an important performance indicator for aluminium smelter. Therefore, over the last few decades, extensive research has gone into understanding the fundamental factors affecting the CE and its correlation with process parameters. Sternten et al. studied the cathodic process and cyclic redox reactions in aluminium electrolysis cells [2], describing the chemical reactions and transport processes leading to loss of CE. An electrochemical CE model was derived considering earlier established models, with selected rate-determining steps [3]. It also states necessary precautions to study the parameters affecting CE both in commercial and in laboratory cells. Solli et al. [4, 5] and Haarberg [1] studied the influence of electrolyte impurity species on CE in a specially designed laboratory cell. Dewing developed current efficiency model based on plant data generated from factorial-design experiments for 3 months. He performed this in a carefully controlled section of 32 cells of a Horizontal Stub Soderberg potline operating in the range of 45–65 kA. The model was based on linear regression equations against the independent variables to

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_79

572

Predictive Analytics for Enhancing Productivity …

573

Fig. 1 a Schematic cross-sectional view of aluminium smelter; b Anode to metal pad region representing back reaction zone

predict CE between 85–90% and loss functions were defined for coefficients beyond 90% CE. In this study, the variation of one parameter at a time was considered for analyzing their impact on CE but the interaction effect of parameters has not been considered [6]. Later, Tarcy et al. discussed the development of statistical regression models for current efficiency but the volume of data was quite limited [7, 8]. In the present study, Machine Learning (ML) algorithms have been used for the development of CE prediction model, since they are better equipped to handle high dimensionality present in the available data. ML helps to address the challenges of complex and dynamic processes that are usually faced by the manufacturing industry. Also, ML can capture the inherent characteristics of individual smelting cell, arising due to factors related to process, material, start-up and operation.

Machine Learning for CE Prediction Earlier studies [6–8] on CE model development were carried out in the 1990s when the cost of data acquisition and storage was quite high, limiting the availability of quantum of data, also, ML was not trditionally preferred tool in the manufacturing industry. Hence, linear regression were adopted, which have limited attributes for capturing the high dimensionality of the aluminium smelting process. With the advent of computers and low cost of data storage, aluminium industries are generating huge amount of data. This data should be used wisely to draw inferences on process parameters. Individual parameters that are readily available and have an impact on CE, are also considered. Model performance is improved by considering the parameters in combination such as the ratio of bath temperature

and AlF3 as an additional parameter for model training, this is known as feature cross. After pre-processing or data cleaning, it was used for the development of a model using a machine learning algorithm. Following subsection would provide insight about the data acquisition, pre-processing and model development.

Data Acquisition First step of machine learning based model development is to ensure good quality of data in sufficient quantity and breadth. Around 2-years of data was captured at a daily frequency for 360 cells of Mahan smelter, which has been used for the ML model development. The higher the variations of process parameters in training dataset, the better equipped is the model for prediction. The model would not be reliable for data that are lying outside the range of training dataset. But there are certain operational anomalies like power disturbance that cause variation in cell behavior and cannot be predicted. Further, there are events such as anode effect, sludge, coking and anode spike, which do not reflect instantaneously on the process. Hence, a suitable time-shift was incorporated in the relevant data for improvement in the model performance. Additionally, it has been assumed that there is no man-to-man error in the measurement of process parameters.

Data Pre-processing Machine learning is a tool which can take any kind of dataset and produce corresponding output. Hence, it is very important to ensure that properly processed data after

574

S. Rajgire et al.

removal of process anomalies is used for training of the ML model. In the present study, the last 2 year of data had been used, which had few instances of very low amperage operation due to problem in power plant. It is difficult to predict cell behavior during power disturbance and hence, operational days having amperage lower than 360 kA have been removed. Similar case is with the cells that are quite young. Therefore, cells in normal operation i.e. age greater than 100 are considered for model training. To better identify outliers, data visualization tools were used to check the density of data, showing normal distribution for most of the parameters (bath temperature, bath height, AlF3 etc.) except for metal height and CaF2. Therefore, 3-sigma filtering was applied to remove the outliers and the outliers which could not be assigned to any particular reason were also removed. All these together led to the removal of about 10% of data, which is not significant to ML model development. The model performance was further improved by providing appropriate delays in case of certain events. The effect of anode effect on production might be delayed. This was determined with help of individual pot data analysis and specific measurements. For anode spike, the effect on production might be prior to the actual observation. Hence, anode spike instance has been advanced. In the present study, only voltage, noise, and amperage are available in real-time, other critical parameters such as bath temperature, bath ratio, CaF2, metal height and bath height are measured periodically at a frequency of 32 h. Whereas few parameters such as cathode drop and anode spike are measured/observed sporadically. For the development of any type of model, it is essential to have all involved parameters at a similar frequency. To achieve this appropriate averaging of the dataset is required, at the same time ensuring that there is no significant loss of information. Hence, for parameters measured in real-time, one-day average was considered. For

Fig. 2 Current efficiency (red) of one cell over 18 months and its moving average (black)

parameters measured periodically, 3 measurements are available in 4 days and hence moving average in multiple of 4 (4, 8, 12, 16… days) has been taken to obtain these values at a daily frequency. Block average was also considered, and it was observed that there is no significant difference in the overall means by considering either block or moving average. However, block averaging lead to a drastic decrease in data points available and leading to loss of information. Hence, moving average has been preferred. For parameters measured sporadically, they were considered to be constant until the next measurement is taken. There are some other limitations in the available data, therefore certain additional pre-processing was required. One such case is the least count of metal height, which is 1 cm that is usually used to determine the extent of metal tapping. The least count corresponds to nearly 300 kg of liquid metal or a possible variation of 8% CE. In addition, a change in thermal balance can lead to variation of ledge thickness in the cell and hence a variation in metal height. Thereafter tapping is a manually operated process and hence prone to a little error, with sometimes over-tapping leading to a decrease in total metal reserve and under-tapping leading to an increase in total metal reserve of the cell. These limitations can lead to high variation in CE that is computed at a frequency of 32 h, as shown in Fig. 2. The process of taking day-wise moving average helps in reducing these errors as can be seen in Fig. 2, depicting a 16 day moving average of CE (black) for the raw CE data discussed above (red). Similar averaging was carried out for rest of the parameters, barring anode effect and anode spike. The data was then stacked, first based on date and second based on the cell number. For example, starting from 1st Jan 2019, all 360 cells sorted by cell number. Then for 2nd Jan 2019, again data of all 360 cells was taken and then for 3rd Jan 2019, and so on. This sorted and pre-processed data was then used for training of machine learning model.

120

Current Efficiency Average Current Efficiency

Current Efficiency (%)

110

100

90

80

70

60 3/10/2016

9/16/2016

3/25/2017

Time (Days)

10/1/2017

Predictive Analytics for Enhancing Productivity …

575

Fig. 3 A schematic depiction of the decision tree

Model Training Post principle component analysis, voltage, noise, bath temperature, bath composition, metal height, bath height, anode spike, anode effect, cathode voltage drop and cross feature of these parameters were selected for development of CE predictive model. Various machine learning algorithms were tested with the available data, and decision tree (DT) and its ensembles gave better prediction results compared to others, based on the root mean square (MSE) and computation time. DT works on simple theory but is very powerful in analyzing and capturing complex high dimensional relationships among features. The tree is created by introducing conditions for each feature. The final leaf node contains the output that is to be predicted. To explain the concept of DT, a simplified example of predicting the current efficiency of a reduction cell based on only two parameters voltage (V) and bath temperature (BT) is described below. Figure 3 shows schematic of DT, where based on the “BT” feature the tree will create a new layer (L1) with three nodes N1, N2 and N3. Based on the “Voltage” feature the tree will create a second

Fig. 4 Comparison of predicted and actual current efficiency

layer (L2) with three nodes N4, N5, and N6. Like BT, the tree will also create conditions for Voltage layer. Other algorithms that are the ensemble of DT i.e. Random Forests and Gradient Boosting, where multiple DTs are combined either in parallel or series, to improve the overall performance of the model. Random forest creates multiple trees in parallel combining all the result from the individual trees by aggregating the results it provides a single output. Random forest ensemble algorithm gave the best results and its validation has been discussed in the following section.

Model Validation Model based on machine learning is like a black box, and any input would produce an output, however the output depends on the training data. Therefore, it becomes very important to properly assess and validate the data. The ML model was trained based on 70% of the available data and tested with the remaining 30% data, to check the prediction accuracy. In Fig. 4, prediction results of random forest regressor based ML model can be seen. There is a good agreement

102

Actual Current Efficiency Predicted Current Efficiency

Current Efficiency (%)

99

96

93

90

87

84 122790

122820

122850

122880

Observation Number

122910

122940

576

S. Rajgire et al.

Impact of Individual Parameters/Model Inferences

Fig. 5 Correlation matrix depicting relations between various process parameters

between the model results and actual CE obtained from the smelter.

Concurrence with Theoretical Analysis The linear variation of current efficiency with process parameters and their inter-dependence was obtained through the correlation matrix as shown in Fig. 5. In the correlation matrix, ± sign depicts direct/inverse correlation and magnitude depicts the significance of the correlation between the parameters. This was used to verify the dependence of CE on process parameters and their correspondence with physics as reported in the literature [9, 10]. Inter-relation between process parameters can be a subject of interest for further study.

Fig. 6 Current efficiency variation with cell voltage

In the present study the impact of process parameters, on current efficiency has been captured through random forest regressor. This model was subsequently used to analyze the dependence of individual process parameters on the current efficiency. In Fig. 6, current efficiency is seen to be increasing with an increase in voltage and then slowly saturating after 4.27 V. For a particular plant, assuming the fixed drops to be constant an increase in voltage during normal operation represents an increase in the anode-to-cathode distance (ACD). This would increase the separation between the molten aluminium pad and back reaction zone containing diffused CO2 as shown in Fig. 1b, thus reducing the probability of back reaction and increasing the current efficiency [10]. But this phenomenon doesn’t seem to have a significant impact for voltage more than 4.27 V (present case) and thus the impact on current efficiency is not significant. An economic analysis for the benefit should be derived from an increase in current efficiency with increase in the voltage. Increased noise or instability has adverse effect on CE as depicted in Fig. 7. An increase in noise by 50 mV leads to 1% decrease in CE. This is synonymous with the theory as increase in noise, enhances the disturbance in the bath-metal interface. This would increase the back reaction zone and hence decrease the CE. There is almost a linear decrease in CE of 1% with increase in bath temperature of about 8 °C, as seen in Fig. 8. An increase in bath temperature increases the mass transfer rate of the species, promoting the back reaction and thus decreasing the current efficiency. Anode effects have an obvious detrimental impact on efficiency but the impact is not as significant as seen in Fig. 9. Rise in concentration of AlF3 and/or CaF2 also increases the current efficiency as highlighted in Figs. 10 and 11. But the impact is not significant as 6% increase in AlF3 enhances

Predictive Analytics for Enhancing Productivity …

577

Fig. 7 Current efficiency variation with cell noise

Fig. 10 Current efficiency variation with AlF3

Fig. 8 Current efficiency variation with bath temperature (BT)

Fig. 11 Current efficiency variation with CaF2

Fig. 9 Current efficiency variation with anode effect (AE)

Fig. 12 Current efficiency variation with metal height

CE by 0.7%, whereas 0.5% increase in CaF2 enhances the CE by about 0.6%. This is mainly attributed to decrease in the liquidus temperature thereby increasing the ledge thickness and lowering the bath temperature. A decrease in bath temperature, in turn, increases the current efficiency. Thus, it has an indirect impact on CE. A techno-economic analysis of maintaining higher AlF3 and CaF2 in smelter cell to increase in CE need to be carried out to find an optimum level of AlF3 and/or CaF2.

The increment in metal height between two consecutive tapping is a direct indicator of CE. Therefore, this has significant impact on CE and thereby was taken as input for training of the model [9]. This can be seen in Fig. 12, as a two cm increase in metal height corresponds to a significant 2% jump in CE but beyond 19 cm the gain becomes less significant. This might be attributed to the fact that smelting cells should have a minimum level of metal pad for smooth operation with higher efficiency, which seems to be around

578

S. Rajgire et al.

increase in current efficiency, whereas increase in noise, bath temperature, anode effect and bath height are detrimental to CE. Most of the inferences are in line with earlier reported literature. Apart from inferences, the model provides the exact impact in numerical terms, with insights into parameters such as bath height which were not extensively studied earlier. The insight provided by model, could be useful to determine the optimal operating range for maximizing the current efficiency. This is planned for testing in Hindalco’s Mahan smelter.

Fig. 13 Current efficiency variation with bath height

References

19 cm for present case study. Interestingly, an increase in bath height seems to have a significant negative impact on CE as shown in Fig. 13. A three cm increase in bath height decreases the CE by almost 3%. Increased bath height can imply lower ledge thickness and higher bath temperature. From correlation matrix in Fig. 5, it was verified that high bath height is corresponding with high bath temperature, low AlF3 and CaF2 that are indicators of lower ledge thickness. This is feasible at higher bath temperature which may be the cause for lower CE.

1. G. M. Haarberg, “Effects of electrolyte impurities on the current efficiency during aluminium electrolysis,” in ICSOBA, 2015. 2. A. Sterten and P. A. Solli, “Cathodic process and cyclic redox reactions in aluminium,” Journal of Applied Electrochemistry, pp. 809–816, 1995. 3. A. Sterten and P. A. Solli, “An electrochemical current efficiency model for aluminium electrolysis cells,” Journal of Applied Electrochemistry, pp. 187–193, 1996. 4. P. A. Solli, T. Eggen, E. Skybakmoen and A. Sterten, “Current efficiency in the Hall-Heroult process for aluminium electrolysis: experimental and modelling studies,” Journal of Applied Electrochemistry, pp. 939–946, 1997. 5. A. Sterten, P. A. Solli and E. Skybakmoen, “Influence of electrolyte impurities on current efficiency in aluminium electrolysis cells,” Journal of Applied Electrochemistry, vol. 28, pp. 781– 789, 1998. 6. E. W. Dewing, “Loss of Current Efficiency in Aluminum Electrolysis Cells,” Metallurgical Transactions B, pp. 177–182, 1991. 7. G. P. Tarcy and K. Torklep, “Current Efficiency in Prebake and Soderberg Cells,” Light Metals, pp. 319–324, 2005. 8. G. P. Tarcy and J. Sorensen, “Determination of Factors affecting Current Efficiency in Commercial Hall Cells,” Light Metals, pp. 453–459, 1991. 9. B. J. Welch and K. Grjotheim, Aluminium Smelter Technology, A Pure and Applied Approach 2nd edition, Düsseldorf: Aluminium-Verlag, 1988. 10. K. Grjotheim and H. Kvande, Introduction to Aluminium Electrolysis, 2 ed., Düsseldorf: Aluminium-Verlag, 1993.

Conclusion The present study analyzes the combined impact of variation in process parameters on current efficiency through a machine learning algorithm. For, machine learning models good quality of data in sufficient quantity and breadth is a necessary requirement. In addition, the predictive model is valid only within the range of dataset that was used for training. Post analysis of the developed model provides inferences into the influence of individual process parameters on current efficiency. It can be concluded that an increase in voltage, AlF3, CaF2 and metal height lead to

Restart of Shutdown Pots: Troubles, Solutions and Comparison with Normal Pots to Improve Results Ved Prakash Rai and Vibhav Upadhyay

Abstract

It is recognized that the premature failure of the pots is a big challenge and worked on the projects to do sidelining and repairing of the shutdown pots to restart. This “Pioneering Work” was carried out at Hindalco Industries Limited, Renukoot, which is recognized as a worldwide leader in this field of Aluminium Production. This paper provides failure analysis of low amperage Hall-Heroult cell and an overview of the sidelined pot. It provides method of sidelining, cathode change, baking, and performance of sideline pots. The paper also makes comparisons for new pots of same life with the sidelined pots, benefits and way forwards. One of the main objectives of this project is the comparison of the sidelined pot with normal pots. The present work is a part of the project “Side-Lining of low amperage Hall-Héroult cell”. The experiments were performed in some selected pots to observe and analyze the parameters like baking conditions, cell noise, cell voltage and cathode lining drop. Keywords

Hall-Héroult cell Relining




Cell failures




Side lining




Introduction The electrolysis cell, or “pot,” is shaped like a shallow rectangular basin is made of an outer steel shell; bottom and sidewalls are covered with different layers of thermal insulating and refractory materials to reduce heat loss [1]. Carbon anode is suspended on anode ring bus bar, and dip into the electrolyte. Current from the anode flows to the V. P. Rai (&)
V. Upadhyay Reduction Technical, Hindalco Industries Limited, Renukut, 231217, India e-mail: [email protected]

electrolyte in which 2–8% of alumina (Al2O3) is dissolved to metal pad located between carbon cathode and anode, and exits the pot by the carbon cathodes connected to the collector bar (see Fig. 1a, b). The current exiting from a pot is directed to the next pot electrically connected in series through a bus bar network. Over time, the cathode blocks bottom and side brick layers deteriorate. In most of the cases due to deterioration cathode cells are either preventively stopped or failed in operation. Pot life is the period between start-up and shutdown which is reported in days. For the same technology and cathode type (graphitized, semigraphitized, semi-graphitic or amorphous), pot life varies within smelter [1]. These variations are caused by problems occurring during construction, preheating, start-up and/or normal operation or by pot materials properties variations [1]. But some pot failed due to abnormal operation. Failure of a Hall-Héroult cell is shown in Fig. 1b. In Hindalco-Renukoot, the total numbers of pots are 2138 and the rate of pot failure is 30 pots/month, these pots are lined with new materials to make a new pot. The process is known as full lining. All these failed pots are expected to achieve its life of more than 3000 days for cost economy but some pots fails prematurely in the life range of 1200– 1600 days.The thumb rule is that pot life depends on the condition of cathode blocks. It is expected that the cathode blocks of a pot are not damaged if the pots are failed prematurely while a repair of side lining is conducted according to a predefined criteria. If pot is failed prematurely then it can be restarted by partial lining i.e. side lining. Side lining means that cathode blocks of failed pots are not remove though a dig out and remove only the lining materials around the periphery. These peripheral parts of cathode blocks are lined with new materials. A new standard criteria for side lining and full lining of pots was developed. The criteria was conceptualized and implemented at Reduction Plant—Pot Relining successfully without affecting the quality of pot lining and could be replicated at all Smelters across the globe. The performance

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_80

579

580

V. P. Rai and V. Upadhyay

(A)

(B)

(C)

Fig. 1 a Joint between collector bar and cathode. b Metal coming out from failed pot (J50). c Image of a low amperage Hall-Heroult cell

of side lined pots is monitored regularly. It was found that the pots which were side lined are almost as energy efficient as normal pots. Other advantages of this initiative is the reduction in transportation due to reduced handling and shifting of dig out material, reduced physical labour, reduction in pot ramming time and operation of pots at optimum voltage. Normal pots have an average life of about 2800– 3000 days in Renukoot smelter while operating at much higher anode current density than most of the modern smelter (see Fig. 1c). During operation, few pots get failed prematurely in the life range of 1200–1600 days. If this pot is full lined, it costs 21179 Dollars per pot. To reduce the cost of pot lining, a new innovative solution was developed of repairing premature failed pot which called “Side Lining”. Side lining of low life pot costs only 5000 Dollars per pot. It provides a chance to increase life of pot and reduce cost of production. At the same time, lining design was modified to ensure operating pots as energy efficient as normal pots are.

Experiments and Discussion To make the strategy for restart of shut down pots, the first step was to study the types of pot failures, to understand the effect of failure on cathode blocks.

Failure Analysis of Low Amperage (70 KA) Hall-Héroult Electrolytic Cell Effect of Blackout on Hall-Héroult Cell Operating pot line on lower amperage than the design capacity is exceptionally challenging [2]. In pot room, on 19/5/2017 one case occurred. Due to thundering rectifier developed a serious fault and current was dropped to zero for five hours. To keep all the pots running during a blackout, the main challenge was to maintain heat balance. Bath

temperature suddenly decreased due to blackout and sudden drop of amperage from 70 kA to zero. The Stability of the pot was impacted. Average bath temperature of the pot room was dropped to 920 °C from 950 °C. Even in some pots, the temperature reached up to 900 °C. During the blackout, weak pots were not able to survive due to which failure rate increased after the load revival. Most of the pot failed due to thermal shock but some pot also failed due to extended anode effect and bath freezing. Total number of cell Failure per day vs. Average Current (KA) in pot room (per day) are shown in Fig. 2.

Autopsy of Pot.no-T91,Which Failed After Few Days of Blackout of 4 H To investigate the effect of thermal shock on cathode of blackout, an autopsy of an aluminum electrolysis cell T91 was conducted, which shut down after a few days of the outage. Visual investigation and images demonstrated that crack was present along the cathode block. Variation in temperature causes thermal shock in the cathode. In brittle materials like carbon cathode block, it causes breakage. From Fig. 3 it is observed that due to blackout on 19/5/2017, the temperature of the pot was dropped to 920 °C. Thermal shock caused the cathode failure and pot failed after a few days. Failure Due to Multiple Anode Effects In the Aluminum industry, the term Anode Effect is used to describe a sudden increase in cell volt during electrolysis above 8 V. During the Anode Effect, arcing and oscillation of cell volt occur. In most of the cases, due to poor operational control, blockage of alumina feeder or due to any other reason the alumina concentration decreased below required levels. Due to the decrease in Alumina concentration resistance of pot increases which increase the cell voltage. Disturbance in thermal balance has an impact on anode effect frequency. Blackout has an impact on thermal equilibrium resulting in affecting Anode effect rate. An example is the pot failure

Restart of Shutdown Pots: Troubles, Solutions and Comparison …

Current (KA)

581

Eīect of Blackout on Pot Failure

Number of Pot Failure

75.00

7

70.00

6 5

65.00

4

60.00

3

55.00

2

50.00

1

45.00

0

No of failed pot

Fig. 2 Showing pot failure and average current in the pot room

Fig. 3 Effect of thermal shock after blackout on cathode

Plant average current

582

V. P. Rai and V. Upadhyay

occurred in cell P22 due to repeated prolonged anode effect. Due to the power outage of 4 h, the thermal balance of the pot got disturbed which lowered the temperature of the cell. Main causes for the excess anode effects after blackout was freezing of bath probably some of the anodes were not submerged in bath and an increase in cell resistance due to insufficient dissolved alumina. Due to the lower temperature and not feeding of alumina, the concentration of dissolved Alumina in electrolyte as well as amount of electrolyte decreased below critical level after the revival of the load because of this reason five anode effects came in pot in a single day (see Fig. 4). Five anode effects were much severed and pot was not able to survive, and pot leaked from the corner collector bar.

Failure Due to Over Feeding Muck is the un-dissolved Alumina, which gets deposit on the cathode. Alumina act as an insulator, when deposited on cathode, it gets accumulating and prevent passing current from that area. The temperature of the bath also increased because of the increased resistance due to alumina deposit on the cathode. In cell G-41, pot failure occurred due to overfeeding and muck formation. Muck and sludge formation is directly related to duration, rate and the batch of fed alumina. In cell G-41, a considerable amount of alumina fed into the pot on 5/03/2018, due to alumina leaking in the outlet point feeder. Excessive muck formation increased the electrical resistance of the pot which led to very high noise, high instability in the pot resulting in an increasing of cell voltage requirements (see Fig. 5). Due to extra voltage given to improve cell stability heat balance disturbed which caused temperature increased to 980 °C which adversely affected

the pot resulting in form red shell near many stalls. After the few hours of operating at red shell, pot failed near two centers stalls.

Failure Due to Over Tapping The pot contains liquid metal; the quantity of metal in the pot is measured by its height in the pot which is called as metal Pad. Stability of pot strongly depends on the metal pad. Metal in the pot is not totally flat because of magneto hydrodynamic (MHD) effects and velocity of metal is inversely proportional to metal pad. If the metal pad is very low, then magneto hydrodynamic stability becomes unstable causing high voltage fluctuation called “MHD noise.” Frequent change in the metal pad and voltage fluctuation in pot disturb the thermal equilibrium. Excessive change in metal pad and applied voltage result into thermal shock penetrates cathode. Mechanical stress develops in cathode due to sudden thermal expansion or contraction. If the cathode is weak and thermal stroke exceeds the threshold value, then cathode fails. In cell G15, a case of pot failure occurred because of excessive over tapping and noise. Due to the problem in metal tapping siphon, excess metal was tapped during schedule tapping, on 21/7/2017, after which cell became highly unstable. Excessive metal tapping led to very high noise resulting into disturbing the anode to cathode distance which disturbed the heat equilibrium of pot after few days where consequentially the pot failed near two corners stalls. Failure Due to High Superheat The ledge formed on the sidewall of Hall-Héroult cell because side is the coldest area of the pot. Ledge has very

Anode Eīect (P22)

Number of Anode Eīect

6

Five Anode eīect in a single day

5 4 3 2 1 0

Date Fig. 4 Anode effect frequency in P22

Restart of Shutdown Pots: Troubles, Solutions and Comparison …

583

Excess Voltage due to

VariaƟon of Voltage in G41

over feeding

Average Used Voltage

4.60 4.55 4.50 4.45 4.40 4.35 4.30 4.25 4.20 4.15 4.10 4.05

Fig. 5 Voltage versus date in G41

high impact on cell life and heat balance. Frozen electrolyte ledge is made of Cryolite. In fact, Bath ratio of pot increases or decreases with any change in superheat because a change in superheat, changes Cryolite percentage in the bath which changes composition and ratio of the bath. Thickness of side ledge changes with the temperature of the pot. Pot with low superheat have thicker ledge than with higher temperature (Fig. 6). Thickness of side ledge changes with the temperature of the pot. Pot with low superheat have thicker ledge than with higher superheat. Excessively thin ledge due to prolong operating at high superheat may cause pot failure. In L78 a pot with an age of 1600 days failed in pot room because of operating at high temperature (see Fig. 7). Protecting layer of ledge got melted and electrolyte and molten metal came in

After the Failure Analysis, We Can Concluded that The following parameters can be highlighted as critical for life of low amperage (70KA) Hall-Héroult electrolytic cell:Input parameters (1) (2) (3) (4) (5)

Over Feeding in the pot. Over Metal Tapping. Power Fluctuation. Power Outage (Black Out). Over Voltage.

Over Tapping 0.0450 0.0400 0.0350 0.0300 0.0250 0.0200 0.0150 0.0100 0.0050 0.0000

20 18 16 14 12 10 8 6 4 2 0

Metal Pad

Avg Noise

Noise (V)

Metal Pad & Noise

Metal Pad (CM)

Fig. 6 Variation of metal pad and Noise w.r.t date

direct contact with lining which led to bath and metal tap out from the middle collector bar. Autopsy of the cell demonstrated that one of the collector bars was in direct contact with metal due to which it melted (see Fig. 8).

584

V. P. Rai and V. Upadhyay

Temperature(°C)

Temperature VariaƟon in (L78) 990 980 970 960 950 940 930

974°C

970 °C

980°C

948°C

Date Fig. 7 Variation of temperature w.r.t date

• If pot failed without high iron and reason for the failure was any of one stated in Sect. 2.1.7 except high iron attack, then historical performance of the pot is analyzed. If the average lining drop of three readings were higher than 500 mV or average used voltage was higher than 4.5 V, then the pot will not undergo sidelining. If lining and average used voltage are less than the defined value, then dry digging of the pot will be conducted to visualize the condition of cathode blocks. If two cathodes block needs to be replaced, then sidelining will be conducted otherwise full lining.

Method of Side Lining Bottom insulation Step 1: Filling of Alumina powder, 20–30 mm, to fill the wave depth in the bottom of the shell. Step 2: Two layers of Insulation Board each of 40 mm are used. Step 3: Two layers of Firebrick each of 65 mm thickness are used. Ensure low porosity and specified characteristic of fire bricks. Step 4: Before placing the Blocks a layer of ½ inch thickness of glass power is spread and levelled through a leveller. Fig. 8 Missing collector bar

Output parameters (1) (2) (3) (4) (5)

Extended anode Effect or duration of Anode Effect. Multiple Anode Effect. Repetitive High Temperature. High Noise. High Iron in the pot.

After Understanding the Pot Failure Behavior, the Criteria Developed After Failure Analysis of Side Lining of the Pots Are • If the pot failed or shunted after 2500 days, then the pot will be fully relined. It is assumed that pot has completed its working life, and cathode lining have degraded or damaged. • If pot failed due to high iron, then sidelining will be avoided even if the age is less than 2500 days. It is assumed in this case that the collector bars and cathode block have entirely damaged, and full lining of the pot will be more economical than sidelining.

In normal re-lining, bottom insulation and block placing but in case of side-lining. Replace cathode block maximum up to two blocks. So in the case of side-lining of the pots, the bottom insulation part is done maximum for two blocks. Block Placing Pre-baked Bottom Blocks duly collector bars fixed in its grooves by pouring cast iron is placed on the bed of glass power. Proper precaution is taken for levelling, spacing, and firm placement of Blocks. Side Insulation (1st Phase) Sealing of collector bars hole with mouldable castable, sealing of collector bars underneath with refractory castable and insulation work in carried out in block periphery zone. The thickness of insulation is 65 mm all around. A layer of fine bricks is provided to protect the insulation material from coming in direct contact with lining material, i.e., Carbon Paste. Side Insulation (2nd Phase) In this stage, installation of Molar brick is done in the side, and 80 mm thick insulation is done in ends. Silicon Carbide

Restart of Shutdown Pots: Troubles, Solutions and Comparison …

585

is installed inside, and anthracite plate is installed in ends using phosbond mortar as jointing material. Ensure proper firm placement of silicon carbide brick and anthracite plate. Pot Ramming Preheating of bottom blocks is done around 90 °C (+ – 10) and intermediate block seams filled with carbon paste using specified procedure. The block periphery is rammed, and the fillet is made all around the edge. Topping and Deck Plate Fitting Before fixing the deck plate, air setting SiC mortar is laid on the top side and end lining. The deck plate is fixed. Excess mortar is removed. Super Structure and Mechanical Fitting After lining the pot, it is ready for mechanical fitting. When the mechanical fitting is over, the pot is checked properly as per specified checklist. When pot is taken into potline, it is preheated for about 32–40 h before molten bath material is poured in the cathode cavity. It should be done taking required precaution as it directly contributes to pot life. (Figs. 9, and 10). Baking and Loading for Restarting the Pot

Fig. 10 Side lined pot

Results and Discussion To see the performance of sideline pot, a comparison was made with different pots of same age group. Three pots which were started recently by sidelining have been compared with same life pots. To compare the performance average of ten days of used voltage, noise and lining drop are taken. In Figs. 12, 13, 14, 15, 16, 17, 18, 19 and 20, S. No represent periods shown in the Fig. 11.

Case-1

A uniform layer of anthracite coke of 3/4” thickness used as resister material for spreading on the cathode block. It is ensured after the first 4 h of baking, all anodes should take uniform current. If the anodes don’t take consistent current, then interchange the low-temperature anode with a higher one take place. It is ensured Pot preheating time must be 30– 34 h. The cathode surface temperature should be higher than 900 °C at the chain side, tap side as well as centre at the time of loading. Extra precaution is taken to ensure that molten metal doesn’t pour with liquid bath.

Cell G29 which failed after 1150 days was started by sidelining. The age after side lining of the pot is 532 days, and todate age, which is the age after the first lining of the pot, is 1692 days. To compare the performance of pot, two full lined pots of age near to 532 and 1692 days were selected in the same line. Comparison of average used Voltage, noise, and lining drop of sidelined pot G29 with G17 and G31 are shown in the Figs. 12, 13, and 14. The performance of sideline pot is nearly equivalent to cell G31

Fig. 9 Full lined pot

Fig. 11 In Figs. 12 to 20, S. No represent periods shown in this figure

586

in terms of the three parameters, but the performance of cell G17 is better than cell G29 and cell G31.

V. P. Rai and V. Upadhyay

The performance of side line pot is nearly equivalent to G83 in terms of all the three parameters but the performance of G88 in all the three parameters is better than G41 and G83.

Case-2 Case-3 The comparison of G41 was done with G88 and G83 in same manner as done in case-1. Comparison of used Voltage, noise and lining drop of side lined pots G41 was done with G88 and G83 are shown in the Figs. 15, 16, and 17.

The comparison of cell P90 was done in same manner as done in case-1 and 2. Comparison of average used Voltage, noise and lining drop of side-lined pots P90 was done with

Fig. 12 Showing voltage comparison of three pots of different age group

Fig. 13 Showing noise of three pots of different age group

Restart of Shutdown Pots: Troubles, Solutions and Comparison …

Fig. 14 Showing lining drop of three pots of different age group

Fig. 15 Showing voltage comparison of three pots of different age group

587

588

Fig. 16 Showing noise of three pots of different age group

Fig. 17 Showing lining drop of three pots of different age group

V. P. Rai and V. Upadhyay

Restart of Shutdown Pots: Troubles, Solutions and Comparison …

589

Fig. 18 Showing voltage comparison of three pots of different age group

Fig. 19 Showing noise of three pots of different age group

pots P22 and P38 which is shown in Figs. 18, 19, and 20. The average used voltage of pot P90 is higher than the average used voltage of both pot P22 and P38. The average

noise of all the three pots is nearly same. The lining drop of pots P90 and P38 is comparable but higher than P22.

590

V. P. Rai and V. Upadhyay

Fig. 20 Showing lining drop of three pots of different age group

Conclusion • It can be concluded that the performance of sidelined pots in terms of voltage consumptions, noise and lining drop are comparable to pots of equivalent age or pot of todate age and performance of new pot is better than sideline pots. • Complete relining or sidelining of failed pots is a decision which should be taken on a case to case basis. The type of pot failure and the age of failure is an important parameter which should be taken into consideration. If the life of Hall-Héroult cell is low and the effect of failure is only local, it will be a good decision to change one to two cathode blocks and then repair the side part.

• The pot life in some cases can be increased several years by side lining method, until finally the entire side-lining pot has reached a critical life.

References 1. ØyvindØstrem, “Cathode wear in Hall-Héroult Cells”, Thesis for the degree of Philosophies Doctor, Department of Materials Science and Engineering, Norwegian University of Science and Technology, February 2013. 2. Roman Düssel, Till Reek, “Surviving an Extended Power Outage after a Breakdown in the Sub Station”, Travaux 46, Proceedings of 35th International ICSOBA Conference, Hamburg, Germany, 2–5 October, 2017.

Electrochemical Behaviour of Cu-Al Oxygen-Evolving Anodes in Low-Temperature Fluoride Melts and Suspensions Andrey S. Yasinskiy, Sai Krishna Padamata, Peter V. Polyakov, Aleksandr S. Samoilo, Andrey V. Suzdaltsev, and Andrey Yu. Nikolaev

Abstract

Cu-based alloys have been considered as promising candidates (along with the Fe-Ni alloys) for the inert anodes material in aluminium reduction cells with low-temperature electrolytes. However, low purity of aluminium due to the contamination by anode corrosion products is a problem yet to be solved. Introduction of alumina suspension as an electrolyte has been presented recently as a possible solution for providing commercial purity aluminium produced with the metallic anode. An attempt to characterize the CuAl-based anodes electrochemical performance in KF-AlF3-Al2O3 melts and suspensions has been made and presented. The effects of the suspension (or melt) properties, the anode composition and the temperature on the electrochemical behaviour of the anode and the kinetics of the oxide layer formation during polarization are studied. The 90Cu-10Al anode in the KF-AlF3-Al2O3 suspension with the cryolite ratio 1.3 and the dispersed phase volume fraction not more than 0.12 is found to be the good option for further investigations.






Keywords











Inert anode Potassium cryolite KF-AlF3 Aluminium bronze Voltammetry Polarization curves Corrosion Oxygen-evolving electrode Suspension Mass transfer







Introduction In the Hall-Heroult process, use of carbon anodes leads to the greenhouse gases evolution, in particular, carbon dioxide and carbon monoxide according to the reactions [1] 6F

Al2 O3ðdisÞ þ 3=2CðsÞ ) 2AlðlÞ þ 3=2CO2ðgÞ

with the electromotive force (EMF) E0 ¼ 1:168 V at T ¼ 1273 K and 6F

Al2 O3ðdisÞ þ 3CðsÞ ) 2AlðlÞ þ 3COðgÞ

12F

4AlF3ðdisÞ þ 3CðsÞ ) 4AlðlÞ þ 3CF4ðgÞ

ð3Þ

with E0 ¼ 2:155 V and 6F

2AlF3ðdisÞ þ 2CðsÞ ) 2AlðlÞ þ C2 F6ðgÞ

ð4Þ

with E0 ¼ 2:378 V. For over a hundred years, the possibility of replacing carbon anodes with carbon-free ones and creating a technology for aluminium production with oxygen as the anode product according to the reaction 6F

A. V. Suzdaltsev
A. Yu. Nikolaev Institute of High-Temperature Electrochemistry UB RAS, Yekaterinburg, Russia

ð2Þ

with E0 ¼ 1:033V, and also perfluorocarbons according to the reactions

Al2 O3ðdisÞ ) 2AlðlÞ þ 3=2O2ðgÞ A. S. Yasinskiy (&)
S. K. Padamata
P. V. Polyakov
A. S. Samoilo School of Non-Ferrous Metals and Materials Science, Siberian Federal University, Krasnoyarsk, Russia e-mail: [email protected]

ð1Þ

ð5Þ

was a subject of thorough search [2–4]. The absence of carbon leads to a significant increase in the decomposition voltage [5]. The standard electrode potential E0 for reaction (5) is 2.195 V at = 1273 K. A decrease in the electrolyte temperature by 150–200 K significantly increases the corrosion resistance of many materials [6, 7], but leads to an increase in the decomposition voltage by 0.10–0.15 V.

A. Yu. Nikolaev Ural Federal University, Yekaterinburg, Russia © The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_81

591

592

Even at relatively low temperatures (973–1123 K), the choice of materials for creating a carbon-free anode is very limited, and these limitations are mainly associated with their cost and corrosion resistance [4]. Alloys based on the Fe–Ni–Cu (Co, Cr, Zn also) system and materials based on the products of their interaction with oxygen are promising candidates [8–23]. During the polarization of metals (with the exception of Pt and other noble metals) in a melt containing oxygen ions O2− (k), their surface is oxidized, therefore, the problem comes down mainly to finding conditions, under which a dense oxide layer having a low solubility or dissolution rate in the melt and low electrical resistance would be formed. In the previous works [24, 25], the possibility of using a suspension as an electrolyte was investigated. The rheological properties [26, 27], the kinetics and mechanism of the cathodic process [28] were studied. The aim of this work is to study the anodic process on several Cu-Al-based alloys in melts and suspensions by the stationary galvanostatic polarization and cyclic voltammetry. The criteria for the selection of aluminium bronze were: • high electrical conductivity of the alloy and of copper aluminates, which are formed during oxidation by oxygen and electrochemically in melts contained oxygen ions; • low solubility of copper aluminates in fluoride melts saturated with oxygen ions; • high melting point of the alloy (near 1050 °C), allowing significant proper electrolysis overheating. The high corrosion resistance of aluminium bronzes has been experimentally confirmed by Tkacheva et al. [2] during electrolysis for 82 h in a 1.3KF-AlF3 melt at T = 750 °C (the copper content in the cathode metal was 0.15 wt%). However, significant diffusion limitations of the cathodic process arise in the studied melts. The limiting current of aluminium reduction is 0.3–0.6 A/cm2 in the studied temperature range. A decrease in temperature leads to a decrease in the alumina dissolution rate. The solubility of oxides in cryolite melts is decreased with an increase in alumina concentration [1]. One of the challenges in inert anode development is the necessity to maintain high alumina concentration to prevent catastrophic corrosion of the anode. The oxide layer dissolution products are transferred towards the cathode metal mostly by the convection and then are easily reduced by dissolved aluminium in catholyte. The use of suspension as an electrolyte, obviously, can solve the problem of maintaining the melt saturated with oxygen ions (alumina) and significantly slow down the transfer of anode corrosion products to the cathode due to the depressed convection [29]. In this way, the suspension protects produced aluminium from the

A. S. Yasinskiy et al.

contamination by the anode components. The interelectrode distance can be set lower than 2 cm without a significant risk of current efficiency and aluminium purity drops. This can highly contribute to energy saving. However, the introduction of suspensions arises problems that need to be resolved. For example, negative effect of the dispersed phase on the electrode processes kinetics, the higher true current density, higher interpolar resistivity required to be compensated. This article is addressed to some of these issues. The behaviour of some copper-based alloys in melts has been studied in sufficient detail [30–36], but at the same time, the mechanism of formation and dissolution of oxide layers on these anodes is still the subject of attention. There is no information on the effect of the suspension properties on the anodic process parameters (in sources available to the authors). The studies were carried out on the anodes of three compositions: Cu-9Al-5Fe (designated here as A1), Cu-10Al (A2), and Cu-10Al-1.7Be (A3) in melts and suspensions based on KF-AlF3-Al2O3 at 1023 K (750 °C). During the oxidation of these alloys, the reactions shown in Table 1 are possible (the change in the thermodynamic potentials is given for T = 1023 K, the standard electrode potential is given relative to the Al/Al3+ reference electrode, the calculations were carried out in the HSC Chemistry v.9.6.1 software). The reactions shown in Table 1 represent the sum of the electrode half-reactions of oxidation-reduction, and changes in the corresponding Gibbs energies, which are known to be associated with the potential difference (standard EMF) by the ratio: E0 ¼ 

DG0 z
F

ð19Þ

where z is the number of electrons, F ¼ 96585 ½C=mol is the Faraday constant. Calculated standard potentials are placed on the scale in Fig. 1. The standard electrode potential of the oxygen electrode at 1023 K is 2.34 V. Oxidation of the anode metals significantly shifts the anode potential to the region of more negative values (relative to the oxygen electrode). According to the thermodynamic analysis, the most negative potential is expected at the anode A3. The formation of copper aluminates is likely at all the anodes. At the anode A1 iron aluminates and copper ferrite are expected (with an equilibrium shift towards the formation of FeAl2O4), because the formation of complex oxides occurs at more negative electrode potentials in comparison with binary compounds. At the anode A3, the formation of beryllium and copper aluminates and oxides is expected. In the experimental part of work the polarization characteristic of the anodes A1, A2 and A3 is the subject of an

Electrochemical Behaviour of Cu-Al Oxygen-Evolving Anodes …

593

Table 1 Possible reactions, electrode potentials and changes in thermodynamic potentials at 750 °C per 1 mol of Al DG01023K , kJ/mol

Reaction

0 DH1023K , kJ/mol

DS01023K , kJ/mol K

E0 , V

6F

(6)

580.21

621.63

40.48

2.00

6F

(7)

535.79

595.54

58.40

1.85

(8)

393.77

453.57

58.44

1.36

(9)

513.90

58.44

44.19

1.78

6F

(10)

380.32

449.40

67.52

1.31

6F

(11)

399.87

443.17

42.31

1.38

12F

(12)

383.10

439.09

54.73

1.32

3F

(13)

309.00

364.41

54.17

1.07

(14)

462.15

507.25

44.08

1.60

(15)

–86.55

–65.05

21.02

–0.30

(16)

100.09

177.44

75.60

0.35

2Al2 O3ðdisÞ þ 1:5BeðsÞ ) 1:5BeAl2 O4ðsÞ þ AlðlÞ

3F

(17)

–113.84

–89.31

23.98

–0.39

3F

(18)

–84.55

–47.29

36.42

–0.29

Al2 O3ðdisÞ þ 3CuðsÞ ) 2AlðlÞ þ 3CuOðsÞ Al2 O3ðdisÞ þ 6CuðsÞ ) 2AlðlÞ þ 3Cu2 OðsÞ 3F

2Al2 O3ðdisÞ þ 1:5CuðsÞ ) 1:5CuAl2 O4ðsÞ þ AlðlÞ 3F

2Al2 O3ðdisÞ þ 3CuðsÞ ) 1:5Cu2 Al2 O4ðsÞ þ AlðlÞ Al2 O3ðdisÞ þ 3FeðsÞ ) 2AlðlÞ þ 3FeOðsÞ Al2 O3ðdisÞ þ 2FeðsÞ ) 2AlðlÞ þ Fe2 O3ðsÞ 2Al2 O3ðdisÞ þ 4:5FeðsÞ ) 4AlðlÞ þ 1:5Fe3 O4ðsÞ 2Al2 O3ðdisÞ þ 1:5FeðsÞ ) AlðlÞ þ 1:5FeAl2 O4ðsÞ 6F

Al2 O3ðdisÞ þ FeðsÞ þ 3CuðsÞ ) 2AlðlÞ þ Cu2 OðsÞ þ CuFeO2ðsÞ 6F

Al2 O3ðdisÞ þ 3BeðsÞ ) 3BeOðsÞ þ 2AlðlÞ 12F

2Al2 O3ðdisÞ þ 6BeðsÞ ) Be6 O6ðgÞ þ 4AlðlÞ

5Al2 O3ðdisÞ þ 1:5BeðsÞ ) 1:5BeAl6 O10ðsÞ þ AlðlÞ

Fig. 1 Scale of standard equilibrium electrode potentials for possible anodic reactions on the studied alloys

electrochemical study by stationary and non-stationary techniques. The effect of alumina volume fraction u on the electrochemical properties (open circuit potential, current-potential curves) is also of primary interest. Cu-Al-based alloys anodic potentials measurements are necessary to clarify the oxidation patterns and current-voltage characteristics. Understanding of the suspension properties influence on anode electrochemical behaviour can ultimately contribute to the development of an energy-efficient environmentally friendly technology for aluminium production [37–39].

Experimental Samples of a commercial alloy (A1) and cast in a ceramic mold A2 and A3 samples were used as anodes. The electrolyte was synthesized from individual salts KF and AlF3

(both analytical grade) previously dried at 673 K for 2 to 4 h. As the dispersion phase, alumina (analytical grade) was used with an average particle size less than 5 lm (Fig. 2). The experiments were carried out in a three-electrode cell (Fig. 3) with an aluminium reference electrode in an alundum case under air atmosphere. The cell was placed in a electric furnace. The electrolyte temperature was measured with a k-thermocouple connected to a multimeter. Cylindrical samples were placed in the center of a graphite crucible that acted as a cathode. The upper part of the samples was placed in a boron nitride tube for active surface area fixation. The end part of the tube immersed into electrolyte had a conical surface to facilitate the removal of anode gases. The current was supplied by the Autolab PGSTAT302n potentiostat, controlled by Nova 2.1.2 software. The current interruption technique was used to determine the ohmic voltage drop.

594

A. S. Yasinskiy et al.

Fig. 2 Differential and cumulative particle size distribution of Al2O3

Stationary polarization was carried out at current densities from 0.005 to 1.5 A/cm2. In the potentiodynamic mode, the potential sweep was performed at a rate of 0.05 V/s. During the experiments, electrolyte samples were taken to determine the phase composition and identification of the anode corrosion products by XRD technique. All the experiments were performed in (1.3KF-AlF3)-Al2O3(sat) melts and suspensions at 750 °C.

Results and Discussion

Fig. 3 Cell. Symbols: 1—furnace; 2—graphite crucible h = 110 mm, dint = 76 mm, dext = 92 mm; 3—electrolyte/suspension KF-AlF34—thermocouple; 5—anode sample dext = 30 mm, Al2O3; h = 10 mm; 6—reference electrode; 7—steel current leads, 8—potentiostat, 9—BN shields

Before recording the stationary potential-current curves, the electrodes were polarized for 1.5 – 2 h at a current density ia = 0.4 A/cm2 (I = 3.7 A). The change in voltage during the electrolysis in melt and suspension with volume fraction of solid particles u = 0.12 presented in Fig. 4. Polarization in melts (Fig. 4, u = 0) occurred with cell voltage U = 2.5…3.1 V. The voltage was changing due to the oxide layer formation and the changes of its structure and composition. In some cases (A2) the high oscillations were observed. After increasing u till 0.12 the voltage increased for samples A1 and A2 and became equal 3.4…3.5. The initial voltage for A3 sample was 2.6 and gradually

Electrochemical Behaviour of Cu-Al Oxygen-Evolving Anodes …

595

Fig. 4 Stationary polarization of the electrodes in melts (u = 0) and suspensions (u = 0.12)

Fig. 5 Stationary polarization curves for the anodic process in the melt and suspensions on alloys of three different compositions

increased to 3.9…4.0 V in 1.5 h. The sample A1 passivation was observed after 1800 s. The stationary galvanostatic polarization curves (Fig. 5) were recorded in melts (u = 0) and suspensions with u = 0.12 and 0.15. The time to reach the quasi-stationary state was about 100 s. Several sections were naturally observed in the pre-oxygen and oxygen regions of the polarization curves (Fig. 5):

2y
F

• metal oxidation (ab) xMe þ yO2 ) Mex Oy þ 2ye or z
F

Me þ ) Mez þ þ ze ; • apparent metal oxidation limiting current section (bc) caused by the low active surface area available for metal oxidation (low Me concentration at the interface); 4F

• oxygen ions oxidation (cd) 2O2 ) O2 þ 4e ;

596

• apparent oxygen ions oxidation limiting current section (de) caused by low O2 concentration and screening of the anode surface by bubbles and particles. The pre-oxygen and oxygen regions are divided by (c) at potentials 2.1…2.3 in melts and at potentials 2.3…2.5 in suspensions. Polarization in the melt at low current densities occurred at potentials 1.3…2.0 V. At anode A1, a potential close to that of the FeAl/FeAl2O4, Fe/Fe3O4, and CuAl/CuAl2O4 electrodes under standard conditions was observed. Moreover, the anode was oxidized without significant diffusion and kinetic difficulties (ab) up to a current density of about 0.1 A/cm2. With increasing current density, the potential started to shift towards the oxygen electrode potential (2.3 V). As for the anode A3, polarization at low current densities (abc) proceeded at potentials of about 2 V. Such potentials are close to the standard potential of the Cu/CuO electrode. The role of beryllium in establishing such potential is not clear. Oxidation of the anode A3 occurred without significant overvoltages up to 0.1–0.2 A/cm2. Alloy A1 has the highest current density at potentials lower than necessary for oxygen evolution, which is associated with high iron content in the alloy, which transforms into readily soluble oxides. High current densities in the pre-oxygen potentials region indicate significant dissolution rates of anode oxidation products and a high partial current density of the anode oxidation in the oxygen potential region. The anode A2 has the lowest current density of the onset of oxygen evolution (c), which indicates a low solubility or dissolution rate of its oxidation products. After introduction of solid particles into the melt, the potentials shift toward values corresponding to oxygen evolution even at low current densities, which may be due to diffusion difficulties in removing the products of dissolution of the oxide layer into the suspension bulk. At a potential of about 3 V in a suspension with u = 0.12, anodes A1 and A3 have similar current densities (0.1 and 0.07 A cm−2 respectively) while much higher value (0.5 A cm−2) is observed on the anode A2. With an increase in u up to 0.15, a decrease in the apparent limiting current densities (de) is observed for anodes A1 and A2. Drastic increase in resistance (passivation) was observed on the anode A3 at u = 0.15 and it was not possible to complete the recording of the polarization curve. The increase in current density was observed on anode A2 (c’d) at 2.6 V. In general, in a stationary study (Fig. 5), we can conclude that the A2 anode is more promising than A1 and A3. The following facts favor this conclusion: • low current density of the anode oxidation in the pre-oxygen region (abc) of the potentials in the melt; • low partial current density of the anode oxidation in the oxygen region (cde) of the potentials in the melt; • high apparent limiting current density (de) in suspension.

A. S. Yasinskiy et al.

In an non-steady study at a low sweep rates (Fig. 6), the anode A1 has the highest current density, which contradicts expectations, because an alloy of this composition is more prone to passivation due to the formation of dielectric oxides, in the presence of significant transport difficulties that may be created by the presence of a concentrated suspension. The plateau (Fig. 6a–1) is observed at potentials 1.9– 2.1 V and a current density of 0.10–0.15 A∙cm−2, which is associated with the diffusion-controlled metal oxidation. The high current density confirms the possibility of the anode oxidation products dissolution. The oxygen evolution current (Fig. 6a–2) is observed after the plateau. The open circuit potential during the sweep is close to the potential corresponding to the Cu/Cu2O and CuAl/Cu2Al2O4 electrode potentials (1.85 V and 1.78 V, respectively). The same is true for the anode A2 (Fig. 6b), however, no peaks and limiting oxidation currents are observed on the scan curve. The open circuit potential during the sweep for anode A3 is close to the standard equilibrium potential of the Cu/CuO electrode, and a peak corresponding to the oxidation of the anode is observed on the curve. The oscillations (Fig. 6c–3) are associated with the bubble phenomena. In suspensions with u = 0.12, gradual increase in resistance (4) on the A2 anode (Fig. 6b) was observed at ia near 0.5–0.6 A/cm2 and E of about 2.9–3.1 V. Anode A3 undergoes partial passivation at lower ia and Ea. With an increase in u from 0.12 to 0.15, passivation (5) of the anodes A2 and A3 is observed, while the anode A1 continues to pass a current with a high density (about 1 A/cm2) even with a strong potential bias towards positive values. A comparison of non-stationary and stationary polarization curve patterns allows us to conclude that the increase in the resistance on the A1 anode occurs under stationary conditions with long-term polarization, and the reason is associated with the accumulation of non-conductive anode oxidation products in the anode layer saturated with these products. The resistance increase on the anodes A2 and A3 is probably caused by an increase in the oxide layer thickness and the bubbles accumulation in the anode space due to the high hydrodynamic resistance to their movement, associated with a high apparent viscosity. Under the same conditions, the A1 anode has a larger partial oxidation current, which makes the specific gas evolution rate lower, and the active surface area is larger than on the A2 and A3 anodes. The results of non-stationary polarization indicate that u should be no more than 0.12, which is confirmed for particles less than 5 lm. With an increase in u, diffusion difficulties in the anode layer increase, which can lead to drastic increase in the resistance. From both stationary and non-stationary studies it can be observed that with increase in u the anodic potential (and oxygen evolution potential) shifts towards more positive values despite that electrochemical preoxidation were

Electrochemical Behaviour of Cu-Al Oxygen-Evolving Anodes …

597

Fig. 6 Cyclic voltammograms for anodic polarization in melts and in suspensions with u = 0.12 and u = 0.15 on alloys A1 (a), A2 (b) and A3 (c) at m = 0.05 V/s

performed for all the samples for 1–1.5 h. This observation deserves further investigation and will be discussed in a separate publication. After polarization, anode samples were studied by XRD. The initial XRD graphs are presented in Fig. 7. The oxide layers phase compositions are shown in Table 2. The products of crystallization of the electrolyte are not displayed. The oxide layers of different anodes vary greatly. In all samples, significant amounts of Cu2O and CuAlO2 compounds are present. Radiographs showed no peaks corresponding to many expected compounds: copper ferrites, aluminates and iron oxides at anode A1, aluminates and beryllium oxides at anode A3. It is assumed that the contents of these compounds are below the detection limit or their

volume distribution is uneven. The thermodynamic stability at 1023 K decreases in the order CuAl2O4 – CuAlO2 – Cu2O – CuO. The most stable compound CuAl2O4 was found only in samples of the A2 anode. Peaks of the relatively stable compound Cu2Al2O4 were not detected in X-ray diffraction patterns. It is observed, that the transition from saturated melt to suspension naturally leads to a decrease in the proportion of copper aluminates and an increase in the proportion of monovalent copper in the oxide layer. Compounds CuO and CuAl2O4 were found only in the oxide layers of A2 anodes. The current-voltage characteristics in suspension (high open-circuit potentials and low current densities in the pre-oxygen potential region) indicate a non-electrochemical mechanism of the CuAl2O4 formation by reactions: CuO þ Al2 O3 ) CuAl2 O4

ð20Þ

4CuAlO2 þ 2Al2 O3 þ O2 ) 4CuAl2 O4

ð21Þ

After polarization during 4–5 h, the samples were coated with a dense oxide layer ( 0.5–1 mm). Visible cracks and traces of deep corrosion were not observed. In the future, it seems expedient to continue the study of electrode processes on the A2 anode at different electrolyte and suspension compositions, temperatures, and to study in more detail the dependence of the limiting currents, overvoltage, and structure of the formed oxide layer on the volume fraction of the dispersed phase in the suspension. The advantage of the anode A2 is confirmed by the phase composition of the oxide layer:

Fig. 7 XRD radiographs: a electrolyte phases, b Cu2O, c CuAlO2, d Cu, e CuAl2O4, f CuO, g Al2O3

• a high proportion of relatively stable copper aluminate CuAl2O4 in the oxide layer structure; • the appearance of copper monoxide in the oxide layer structure during the transition from melts to suspensions.

598 Table 2 Phase composition of the samples of the oxide layer of the anodes after polarization in the melt and in suspension 1.3KFAlF3-Al2O3 at 750 °C

A. S. Yasinskiy et al. Anode

u

CuO

Cu2O

CuAlO2

CuAl2O4

A1

0.00

0

54.91

45.09

0

0.15

0

83.08

16.92

0

0.00

0

30.34

53.63

16.03

0.15

31.16

42.84

11.77

14.22

0.00

0

57.38

42.62

0

0.15

0

62.57

37.43

0

A2 A3

Conclusion The influence of the dispersed phase volume fraction and the anode material on the current-voltage characteristics at stationary and non-stationary polarization, the phase composition of the oxide layer and the features of the formation of the oxide layer on the surface of the material are studied. It is found that an increase in volume fraction leads to an appreciable decrease in apparent limiting current density of the oxygen evolution and the metal oxidation as well. It also leads to the drastic increase in the resistance due to several reasons: accumulation of anode oxidation products and bubbles in the anode layer, growth of oxide layer and structural changes, decrease in the active surface area. The most abundant compounds in all oxide layers are Cu2O and CuAlO2. The 90Cu-10Al anode, the aluminium oxide suspension based on the KF-AlF3-Al2O3 system with a volume fraction no more than 0.12 (with 5 lm Al2O3) at a temperature of at least 1023 K are recommended for further studies. Acknowledgements The reported study was funded by Russian Foundation for Basic Research, Government of Krasnoyarsk Territory, Krasnoyarsk Region Science and Technology Support Fund according to the research project № 18-48-243014.

References 1. Galasiu, I., Galasiu, R., Thonstad, J. (2007) Inert Anodes for Aluminium Electrolysis, Aluminium-Verlag, Düsseldorf: 212. 2. Tkacheva, O., Spangenberger, J. Davis, B. and Hryn, J. (2014) Chapter 1.6 Aluminium Electrolysis in an Inert Anode Cell. Molten Salts Chemistry and Technology, First Edition. Edited by Marcelle Gaune-Escard and Geir Martin Haarberg. John Wiley & Sons, Ltd: 53–69. 3. Haraldsson, J., Johansson, M.T. (2018) Review of measures for improved energy efficiency in production-related processes in the aluminium industry – From electrolysis to recycling. Renewable and Sustainable Energy Reviews, 93: 525–548. 4. Pawlek, R.P. (2014) Inert anodes: an update. Light Metals: 1309– 1313. 5. Solheim, A. (2018) Inert Anodes—the Blind Alley to Environmental Friendliness?. Minerals, Metals and Materials Series, Part F4: Light Metals: 1253–1260.

6. Cassayre, L., Patrice, P., Pierre, C., Laurent, M. (2010) Properties of low-temperature melting electrolytes for the aluminium electrolysis process: a review. J. Chem. Eng. Data, 55: 4549–4560. 7. Lebedev, V.A., Shoppert, A.A. (2018) Efficient Assessment of Physico-Chemical Properties of the Cryolite Melts for Research on the Improvement of Low-Temperature Aluminium Electrolysis. Solid State Phenomena, 284: 839–844. 8. Jucken, S., Schaal, E., Tougas, B., Davis, B., Guay, D., Roué, L. (2019) Impact of a post-casting homogenization treatment on the high-temperature oxidation resistance of a Cu-Ni-Fe alloy. Corrosion Science, 147: 321–329. 9. Jucken, S., Tougas, B., Davis, B., Guay, D., Roué, L. (2019) Study of Cu-Ni-Fe Alloys as Inert Anodes for Al Production in Electrolyte. Low-Temperature KF-AlF3 METALLURGICAL AND MATERIALS TRANSACTIONS B, https://doi.org/10.1007/s11663-019-01695-w. 10. Galasiu, I., Galasiu, R. (2014) Aluminium electrolysis with inert anodes and wettable cathodes and with low energy consumption. in: M. Gaune-Escard, G.M. Haarberg (Eds.), Molten Salts Chemistry and Technology, John Wiley & Sons, Ltd, 27–37. 11. Gavrilova, E., Goupil, G., Davis, B., Guay, D., Roué, L. (2015) On the key role of the Cu content on the oxidation behaviour of Cu-Ni-Fe anodes for Al electrolysis. Corrosion Science, 101: 105– 113. 12. Wang, Y. and He, H.B. (2018) The Ion Structure of NiFe2O4– 10NiO-Based Cermet Anode in the Electrolyte. Materials Science Forum, 921: 119–127. 13. Oudot, M., Cassayre, L., Chamelot, P., Gibilaro, M., Massot, L., Pijolat, M. Bouvet S. (2014) Layer growth mechanisms on metallic electrodes under anodic polarization in cryolite-alumina melt. Corrosion Science, 79: 159–168. 14. Ndong G., Xue J., Feng L., Zhu J. (2015) Effect of Anodic Polarization on Layer-Growth of Fe-Ni-Cr Anodes in Cryolite-Alumina Melts. In: Jiang T. et al. (eds) 6th International Symposium on High-Temperature Metallurgical Processing. Springer, Cham, 83–90. 15. Kovrov, V.A., Khramov, A.P., Zaikov, Y.P., Chumarev V.M., Selivanov E.N. (2014) Anodic behaviour of the NiO-Fe2O3Cr2O3-Cu composite during the low-temperature electrolysis of aluminium. Russ. J. Non-ferrous Metals. 55: 8–14. 16. Meyer, P., Gibilaro, M., Massot, L., Pasquet, I., Tailhades, P., Bouvet, S., Chamelot P. (2018) Comparative study on the chemical stability of Fe3O4 and NiFe2O4 in molten salts. Materials Science and Engineering: B. 228 117–122. 17. Allanore, A., Yin, L., Sadoway, D.R. (2013) A new anode material for oxygen evolution in molten oxide electrolysis. Nature. 497: 353–357. 18. Gunnarsson, G., Oskarsdottir, G., Frostason, S., Magnusson, J.H. (2019) Aluminium electrolysis with multiple vertical non-consumable electrodes in a low temperature electrolyte. Minerals, Metals and Materials Series: Light metals: 803–810.

Electrochemical Behaviour of Cu-Al Oxygen-Evolving Anodes … 19. Bao, S., Chai, D., Shi, Z., Wang J., Liang, G., Zhang, Y. (2018) Effects of current density on current efficiency in low temperature electrolysis with vertical electrode structure. Minerals, Metals and Materials Series, Part F4: Light Metals: 611–619. 20. Guan, P.P.; Liu, A.M.; Shi, Z.N.; Hu, X.W.; Wang, Z.W. (2019) Corrosion Behaviour of Fe-Ni-Al Alloy Inert Anode in Cryolite Melts. Metals, 9 (4): 399. 21. Gupta, A., Basu, B. (2019) Sustainable Primary Aluminium Production: Technology Status and Future Opportunities. Transactions of the Indian Institute of Metals, https://doi.org/10.1007/ s12666-019-01699-9. 22. Mohammadkhani, S., Schaal, E., Dolatabadi, A., Moreau, C., Davis, B., Guay, D., Roue, L. (2019) Synthesis and thermal stability of (Co,Ni)O solid solutions. Journal of the Americal Ceramic Society, 102: 5063–5070. 23. Li, Z., Shi, Z., Zhang, Z., Liu, R., Liu, Y., Li, J., Qiao, G. (2018) Corrosion resistance of the ZnCr2O4 spinel in NaF-KF-AlF3 bath. Corrosion Science. 131: 199–207. 24. Polyakov, P.V., Klyuchantsev, A.B., Yasinskiy, A.S. Popov, Y.N. Conception of “Dream Cell” in aluminium electrolysis. Light Metals, 283–288. 25. Yasinskiy, A.S., Vlasov, A.A., Polyakov, P.V., Solopov, I.V. (2016) Impact of alumina partial density on the process conditions of aluminium reduction from cryolite-alumina slurry parameters. Tsvetnye Metally, 12: 33–38. 26. Yasinskiy, A.S., Polyakov, P.V., Voyshel, Y.V., Gilmanshina, T. R., Padamata, S.K. (2018) Sedimentation behaviour of high-temperature concentrated colloidal suspension based on potassium cryolite. Journal of Dispersion Science and Technology, 39, 10: 1492–1501. 27. Yasinskiy, A.S., Polyakov, P.V., Yushkova, O.V., Sigov, V.A. (2018) Spatial particle distribution during stokes sedimentation of alumina in high temperature concentrated suspension-electrolyte for aluminium production. Tsvetnye Metally, 2: 45–50. 28. Nikolaev, A.Yu., Suzdaltsev, A.V., Polyakov, P.V., Zaikov, Yu. P. (2017) Cathode process at the electrolysis of KF-AlF3-Al2O3 melts and suspensions. Journal of the Electrochemical Society, 164, 8: H5315–H5321.

599 29. Keller, R., Rolseth, S., Thonstad J. (1997) Mass transport considerations for the development of oxygen-evolving anodes in aluminum electrolysis. Electrochimica acta, 42 (12): 1809–1817. 30. Hryn, J., Tkacheva, O., Spangenberger, J. (2016) Initial 1000A Aluminium Electrolysis Testing in Potassium Cryolite-Based Electrolyte. In: Sadler B.A. (eds) Light Metals (2013). The Minerals, Metals & Materials Series. Springer, Cham 1289-1294. 31. Khramov, A.P., Kovrov, V.A., Zaikov, Y.P., Chumarev, V.M. (2013) Anodic behaviour of the Cu82Al8Ni5Fe5 alloy in lowtemperature aluminium electrolysis. Corrosion Science, 70: 194–202. 32. Shao, W.Z., Feng, L.C., Zhen, L., Xie, N. (2009) Thermal expansion behaviour of Cu/Cu2O cermets with different Cu structures. Ceram. Int, 35: 2803–2807. 33. Shao, W.Z., Xie, N., Li, Y.C., Zhen, L., Feng L.C. (2005) Electric conductivity and percolation threshold research of Cu–Cu2O cermet. Transactions of Nonferrous Metals Society of China (English Edition), 15(SPEC. ISS. 2): 297–241. 34. Feng, L.-C., Xie, N., Shao, W.-Z., Zhen, L., Ivanov, V.V. (2014) Exploring Cu2O/Cu cermet as a partially inert anode to produce aluminium in a sustainable way. Journal of Alloys and Compounds, 610, 15: 214–223. 35. Feng, L.C., Shao, W.Z., Zhen, L., Xie, N. (2008) Microstructure and mechanical property of Cu2O/Cu cermet prepared by in situ reduction-hot pressing method. Mater. Lett., 62: 3121–3123. 36. Windisch, C.F.J., Marschman, S.C. (1987) Electrochemical polarization studies on Cu and Cu-containing cermet anodes for the aluminium industry. Light Met. 351–355. 37. Padamata, S.K., Yasinskiy, A.S., Polyakov, P.V. (2019) Electrolytes and its Additives Used in Aluminium Reduction Cell: a Review. Metallurgical research and technology 116, 4: 410. 38. Yasinskiy, A.S., Padamata, S.K., Polyakov, P.V., Vinogradov, O. O. (2019) Anodic process on aluminium bronze in low-temperature cryolite-alumina melts and suspensions, Tsvetnye Metally, 9: 42–49. 39. Yasinskiy, A., Suzdaltsev, A., Padamata, S.K., Polyakov, P., Zaikov, Yu. (2020) Electrolysis of low–temperature suspensions: an update. Minerals, Metals and Materials Series: Light metals, current issue.

Alumina Concentration Measurements in Cryolite Melts Luis Bracamonte, Karoline Nilsen, Christian Rosenkilde, and Espen Sandnes

Abstract

The alumina dissolution is one of the most important processes for advanced aluminium electrolysis. For a better understanding and improvements on the dissolution process, it is important to find an effective and reliable method to perform in situ measurements in the cryolite melt, obtaining in this way the variation in alumina concentration during the entire electrolysis process. Electromotive force (emf) measurements between an electrochemical alumina sensor made of graphite and two reference electrodes (a graphite quasi-reference electrode and an aluminium reference electrode), were performed during the addition of alumina and throughout the entire process of dissolution. Cell reactions between the alumina sensor and the two reference electrodes were derived, and the theoretical cell voltages were calculated. The cell voltage measurements were analyzed and compared with the theoretical calculations to determine the reliability of the electrochemical sensor and verify the validity of the basis and assumptions used in this work for the determination of alumina concentration. Keywords




Alumina dissolution Electrochemical probe Alumina concentration measurements




L. Bracamonte (&)
K. Nilsen
E. Sandnes Department of Materials Science and Engineering, Norwegian University of Science and Technology (NTNU), Sem Saelands Vei 12, 7491 Trondheim, Norway e-mail: [email protected] E. Sandnes e-mail: [email protected] C. Rosenkilde Norsk Hydro ASA, Hydro’s Corporate Technology Office, Oslo, Norway

Introduction The Hall–Héroult process involves electrolytic reduction of aluminium oxide (Al2O3) dissolved in molten cryolite (3NaF-AlF3) at temperatures in the range of 970 °C [1]. The primary electrochemical reaction can be one of the following: Al2 O3 ðlÞ þ 3C ! 2AlðlÞ þ 3COðgÞ

ð1Þ

2Al2 O3 ðlÞ þ 3CðsÞ ! 4AlðlÞ þ 3CO2 ðgÞ

ð2Þ

The cathode product is liquid aluminium, and the gaseous anode product is a CO2-CO mixture. As a result, carbon anodes are consumed. The primary anode product is CO2 (g), but some CO can be formed at low current densities 0.05–0.1 A cm−2 [2]. One of the most crucial mechanisms during the electrolysis process is the dissolution of alumina in cryolite melts. This dissolution can be described by different steps, from the release of alumina powder during the addition until the formation of a homogeneous solution in the electrolyte. These steps include: the crust formation when the bath freeze around the alumina particles, heating and remelting of the bath, the conversion of gamma-alumina to alpha-alumina and the dissolution of alpha-alumina to lastly have the completely dissolved alumina and uniform electrolyte composition. Chemical reactions and physical processes strongly influence the dissolution process and both heat and mass transfer can be rate determining [3, 4]. Due to the complexity of all the steps of the dissolution process mentioned above, a continuous, reliable and simple measurement of the alumina concentration could be beneficial in extracting information on the dissolution process. Also, continuous alumina concentration measurements could be beneficial during operation of industrial cells in order to avoid formation of muck, bottom sludge or crust which give an increase in resistance and temperature and decrease in current efficiency [5]. Technology for continuous measurements has not yet been implemented in industry.

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_82

600

Alumina Concentration Measurements in Cryolite Melts

Several attempts have been made to achieve reliable and continuous alumina concentration measurements in lab scale. Some studies are based on the correlation between the alumina concentration profiles and the current distribution in the electrolysis cell [6] and some based on electrochemical methods such as chronopotentiometry or fast linear sweep voltammetry, often termed critical current density [7, 8]. Electromotive force measurements (emf) based on an electrical voltage difference, is one of the electrochemical methods that can also be used to study the dissolution process. Vasyunina et al. studied the solubility and the dissolution rate of alumina in acidic cryolite aluminous melts using an electrochemical method based on a measurement of the equilibrium electromotive force of a concentration galvanic cell. The objective of the present work is to study the performance of an electrochemical alumina sensor made of carbon. emf measurements between the alumina sensor and two different reference electrodes is to be explored. The alumina sensor is based on the reaction between oxide species in the bath and carbon. Thus, the measured emf is a result of the activity of oxide in the bath. This type of sensor has previously not been reported. A new quasi-reference carbon electrode has also been made and tested. Since the sensor and reference electrode are based on carbon, the principle is expected to function for long periods in the corrosive cryolite bath. This can potentially make the principle applicable in an industrial setting.

601

tube ensures electrical contact between the alumina saturated bath inside the tube (chamber I) and the bath in the crucible (chamber II). The half-cell reactions between the graphite probe and the graphite quasi-reference electrode taking place in the chambers are shown in Eqs. (3) and (4). Equation (5) represents the migration of sodium ions from chamber I to chamber II in order to maintain charge neutrality. The addition of the half-cell reactions is shown in Eq. (6).  O2 ðIÞ þ CðIÞ ¼ 2e þ COðIÞ

Chamber I Chamber II

ð3Þ

COðIIÞ þ 2e ¼ CðIIÞ þ O2 ðIIÞ

ð4Þ

þ þ NaðIÞ ¼ NaðIIÞ

ð5Þ

CðIÞ þ COðIIÞ þ Na2 OðIÞ ¼ COðIÞ þ CðIIÞ þ Na2 OðIIÞ

ð6Þ

As E0 is equal to 0, the Nernst equation for the cell reaction becomes as written in Eq. (7), where n is equal to 2. In Eq. (5), it is implicitly assumed that tNa+ = 1, which is not far from reality [9]. E¼

RT PCOðIÞ
aNa2 OðIIÞ
aCðIIÞ ln nF PCOðIIÞ
aNa2 OðIÞ
aCðIÞ

ð7Þ

V

Method The cell reactions between the alumina sensor and a reference electrode are derived together with the corresponding Nernst equations and theoretical emf values. As the alumina sensor is based on a graphite material it is also referred to as a graphite probe. Two different reference electrodes are used. One of the reference electrodes is the well-known aluminium reference electrode, and the other reference electrode is a quasi-reference electrode which applies the same principle as the alumina sensor but with an internal chamber with a bath saturated with alumina. Calculated emf values were compared to experimental measurements to explore the reliability of the electrochemical alumina sensor.

Graphite probe

Graphite reference

Graphite Probe Versus Graphite Quasi-Reference Electrode A carbon crucible containing cryolite melt, a graphite probe and a graphite quasi-reference electrode are shown in Fig. 1. The graphite quasi-reference is a graphite electrode placed inside a boron nitride tube. A small hole in the boron nitride

Fig. 1 Illustration of the electrochemical cell with the graphite probe and the graphite quasi-reference electrode

L. Bracamonte et al.

0.12

0.12

0.09

0.09

E (V)

E (V)

602

0.06 0.03 0

0.06 0.03

0

2

4

6

8

10

12

Al2O3 (wt%)

The activity of CO is expressed as the partial pressure of CO above the melt since the adsorbed CO is believed to be in equilibrium with partial pressure of CO in the melt which is also in equilibrium with the pressure of CO above the melt. The expression in Eq. (7) can be simplified to Eq. (8) as aCðIÞ is equal to aCðIIÞ because the same graphite material is used in both electrodes, and with the assumption that the CO pressure is constant and equal in chamber I and II. RT aNa2 OðIIÞ ln 2F aNa2 OðIÞ

ð8Þ

By using data from FactSage (ThermFact Inc., Montreal, Canada) it can be found that the aNa2 O versus the alumina concentration is roughly linearly related. This implies that the activity coefficient of Na2O is approximately constant if the bath composition (exclusive of alumina) is the same in chambers I and II. This gives another simplification of the Nernst equation, Eq. (9). E¼

RT wt% Al2 O3ðIIÞ ln 2F wt% Al2 O3ðIÞ

960

980

1000

Temperature (°C)

Fig. 2 Calculated values of the potential of a graphite electrode versus a graphite quasi-reference electrode as a function of alumina concentration (T = 975 °C, 11 wt% Al2 O3ðIÞ )

E¼

0 940

ð9Þ

Finally, the potential of the graphite probe can be expressed as a function of the alumina concentration. The calculated values are given in Fig. 2. Moreover, Eq. (9) shows that the relation between the cell potential and the temperature is linear at constant alumina content. In Fig. 3 this relation is plotted for different alumina concentrations. There is a minor effect on the potential at low alumina content, while it is almost negligible at concentrations close to saturation.

Fig. 3 Calculated values of the potential of a graphite electrode versus the graphite quasi-reference electrode as a function of the temperature at different alumina concentrations. Concentration of alumina: 1 wt% (circular dots), 3 wt% (square dots), 6 wt% (triangles), 9 wt% (rhombus), and 11 wt% (small dashes)

Graphite Probe Versus Aluminium Reference Electrode Applying the same reasoning as for the case with the graphite reference showed in Fig. 1, the half-cell reactions between the graphite probe and the aluminium reference electrode are shown in the Eqs. (10) and (11). Equation (12) represents the migration of sodium ions between chamber I and chamber II in order to maintain charge neutrality. Chamber I 2AlðIÞ ¼ 6e þ 2Al3ðIÞþ Chamber II

3COðIIÞ þ 6e ¼ 3CðIIÞ þ 3O2 ðIIÞ

ð10Þ ð11Þ

þ þ 6NaðIÞ ¼ 6NaðIIÞ

ð12Þ

2 3O2 ðIÞ ¼ 3OðIÞ

ð13Þ

2AlðIÞ þ 3COðIIÞ þ 3Na2 OðIÞ ¼ Al2 O3ðIÞ þ 3CðIIÞ þ 3Na2 OðIIÞ ð14Þ E0ðTÞ 6¼ 0

ð15Þ

Equation (13), i.e. the addition of 3 oxide ions to chamber I at each side of the reaction, is introduced to avoid complications to determine the reference state of ionic species in the Nernst equation. The total cell reaction is shown in Eq. (14). As E0ðTÞ is different to cero as it is shown in Eq. (15), the Nernst equation for the cell can be written as in Eq. (16).

Alumina Concentration Measurements in Cryolite Melts

E ¼ E0ðTÞ 

3 3 RT aAl2 O3ðIÞ
aCðIIÞ
aNa2 OðIIÞ ln 2 6F aAl
P3COðIIÞ
a3Na2 OðIÞ

603

ð16Þ

It can be simplified to Eq. (17) by assuming the activity of the liquid aluminium equal to 1. E ¼ E0ðTÞ 

RT aAl2 O3ðIÞ RT aNa2 OðIIÞ ln ln  6F P3COðIIÞ 2F aNa2 OðIÞ

ð17Þ

At saturation, the activity of alumina is 1, so aAl2 O3ðIÞ is assumed to be 1 in Eq. (17). The aNa2 O versus the alumina concentration is roughly linearly related, so the aNa2 O can be replaced with the alumina concentration. Equation (17) therefore simplifies to Eq. (18). Given an empiric cell potential of *1 V at 1 wt% Al2 O3 , the partial pressure of CO was estimated to 0.022 atm. Eð0T Þ was found from FactSage at T = 975 °C. E ¼ E0ðTÞ 

RT 1 RT wt% Al2 O3ðIIÞ ln ln  6F P3COðIIÞ 2F wt% Al2 O3ðIÞ

ð18Þ

Then, the potential of the graphite probe can be expressed as a function of the alumina concentration. The calculated values are given in Fig. 4.

Design of the Graphite Quasi-reference Electrode The graphite quasi-reference electrode is shown in Fig. 5b. A carbon rod (Ø 5 mm, height 50 mm) was screwed to a graphite connector and put inside a boron nitride tube (Ø 10/22 mm). A hole (1.5 mm) was drilled above the bottom of the tube. A steel rod connector bar (height 50 cm) was screwed to the graphite connector. Alumina (3 g) was added inside the boron nitride tube in order to make an alumina saturated bath (10–12 wt%).

Design of the Aluminium Reference Electrode An illustration of the aluminium reference electrode is shown in Fig. 5c and is mainly based on the reference electrode described by Sommerseth et al. [10]. A boron nitride tube (Ø 5/10 mm) was screwed to a steel tube. Pure aluminium metal (0.65 g) was added inside the boron nitride tube. A hole was drilled above the metal surface to allow bath to enter the tube. A tungsten wire in contact with the molten aluminium was used for electrical contact.

Apparatus Setup

Experimental Design of the Graphite Probe The graphite probe is shown in Fig. 5a. The electrode is a graphite rod. The graphite electrode was made of the same carbon material as the graphite rod used in the graphite quasi-reference electrode.

1

E (V)

0.97

Results and Discussion

0.94 0.91 0.88 0.85

A carbon crucible (Ø 85 mm, height 130 mm) with cryolite (500 g) was place inside a closed furnace as it is showed in Fig. 6. The furnace was heated until the temperature inside the melt reached 975 °C. Experiments were done under N2 or CO2 atmosphere. All electrodes and a thermocouple type S were put inside the melt and were fixed by plugs to the top lid of the furnace. Additions of 3 wt% of primary alumina were performed using a feeding tube. emf measurements between the graphite probe and the two references electrodes were performed during the addition of alumina and throughout the entire dissolution process. A logger (Keithley 2000 multimeter) was used to acquire the emf data and temperature.

0

2

4

6

8

10

12

Al2O3 (wt%) Fig. 4 Calculated values of the potential of a graphite electrode versus an aluminium reference electrode as a function of alumina concentration (T = 975 °C)

The variation in potential between the graphite probe and the graphite quasi-reference electrode versus time during 5 additions of alumina is shown in Fig. 7. The temperature variation is also shown. The variation in potential can be divided into two characteristic stages for each addition of alumina. The first stage is a very sharp drop followed by a second stage characterized by a slow increase until stabilization at a constant potential. Immediately after the first addition of 3 wt% of alumina at 5742 s the potential dropped quickly, followed by a slow increase and stabilization around –0.033 V. The 0.059 V difference in potential from

604 Fig. 5 Sketch of: a Graphite probe b Graphite quasi-reference electrode c Aluminium reference electrode Apparatus setup

L. Bracamonte et al.

(a)

(b)

(c) Steel tube with treads

Steel rod connector bar

Steel rod connector bar

Graphite connector Boron nitride tube

60 mm

Boron nitride tube Graphite rod

Alsint tube

Graphite rod

Hole for electrolyte penetration

Hole for electrolyte penetration

Tungsten wire 10 mm

22 mm

Fig. 6 Principal sketch of the cell setup. From left to right: graphite probe, graphite quasi-reference electrode, alumina feeding tube, aluminium reference electrode and thermocouple

the starting value at 0.026 V to the final value at –0.033 V is similar to the 0.068 V difference in potential expected from theoretical values shown in Fig. 2. The temperature dropped about 20 °C immediately after the addition of alumina followed by a continuos increase and stabilization back to the starting temperature around 975 °C. This drop of approximately 20 °C in temperature corresponds to a 2 mV theoretical decrease in the potential. This decrease is small compared to the 0.059 V decrease observed. The temperature decrease associated with alumina addition is therefore

Cryolite/Alumina pool

5 mm

Aluminium pool

10 mm

considered to have only a small effect on the measured potential value. This effect gets smaller when approaching alumina saturation as shown in Fig. 3. The drop in the potential after the second addition of 3 wt% of alumina was about 0.046 V which is also relatively consistent with the 0.037 V decrease in potential expected from the calculations. After the fourth additions the bath became saturated and the potential stabilized around –0.102 V. The potential before the first addition (0.026 V) was not the same as the calculated (0.14 V). However, the total decrease in the potential was around 0.13 V at saturation which is comparable to the 0.14 V decrease in potential expected from the calculations. The variation in potential between the graphite probe and the aluminium reference electrode versus time during 5 additions of alumina is presented in Fig. 8. These variations in the potential can also be divided into two characteristic stages for every addition of alumina. Contrary to the initial potential drop observed using the graphite reference electrode, the first stage is characterized by a rapid increase in the potential followed by a second stage characterized by a slow and continuos decrease. Furthermore, no plateaus or constant values are reached in the potential after any addition of alumina. After the first addition of 3 wt% alumina was done, a rapid increase in the potential was observed followed by a continuos decrease until the potential reached 0.84 V. This change of approximately 0.11 V in the potential from 0.95 V to 0.84 V is comparable to the 0.13 V difference in potential expected from calculations and shown in Fig. 4. The behaviour of the temperature was the same as previously observed, i.e. a rapid decrease immediately after the alumina was added followed by an increase and stabilization back to the initial temperature. After the second addition of 3 wt% of alumina the potential reached a value of 0.82 V. This decrease of 0.02 V is somewhat lower than the 0.03 V

Alumina Concentration Measurements in Cryolite Melts

0.05 980 7300

9300

13300 970

-0.15

960

-0.25

950

Time (s)

1.1

1 970

0.9

0.8 5400

960

Temperature ( )

980

emf (V)

Fig. 8 Emf between the graphite probe and the aluminium reference electrode versus time (circular dark dots). Temperature versus time (square light dots). Addition of 3 wt% alumina (triangles)

11300

Temperature

5300 -0.05

emf (V)

Fig. 7 Emf between the graphite probe and the graphite quasi-reference electrode versus time (circular dark dots). Temperature versus time (square light dots). Addition of 3 wt% alumina (triangles)

605

950 7400

9400

11400

13400

Time (s) difference in potential expected from calculations. The total change in the potential was around 0.14 V at saturation which is consistent with the calculated 0.14 V change in potential shown in Fig. 4 The expected plateaus of the potential were not observed after additions of alumina. Important challenges were faced during the experiments such as non-stabilized potential in experiments where the aluminium reference electrode was applied, potential noise, and sudden drops and jumps in potential just after alumina addition. In order to understand these events, some experiments were performed. Nitrogen was normally the gas flowing through the furnace during experiments. When a plug in the lid was opened air could enter the furnace. The emf measurements were strongly affected during such an operation. An example is shown in Fig. 9. The potential increased from 0.907 V when the plug of the lid was closed to 0.917 V when the plug was opened Substitution of N2 by CO2 was done in order to study the influence of having a gas composition rich in CO2 above the melt. The result is presented in the Fig. 10. It seems that

when using CO2 air entering the furnace does not affect the measurement. The potential value was around 0.856 V when the lid of the oven was closed and remained constant when it was opened. The reactions shown in Eqs. (19), (20) and (21) may alter the partial pressures of CO and CO2 in the cell and cause an increase in the potential. CðS;anodeÞ þ O2ðgasÞ ¼ CO2ðgasÞ

ð19Þ

CðS;anodeÞ þ O2ðgasÞ ¼ 2COðgasÞ

ð20Þ

2COðgasÞ þ O2ðgasÞ ¼ 2CO2ðgasÞ

ð21Þ

A constant flow of CO2 into the cell is believed to prevent large variations in the partial pressures of CO and CO2. The added CO2 will establish a buffer system with respect to small amounts of air entering the cell. Another important factor that is believed to affect the potential and which may be responsible for the continuous drifting in the potential as seen in Fig. 7, was the dissolution

606

L. Bracamonte et al.

0.92

0.8

995

0.91

975

0.905

0.9 1900

965

2100

955 2500

2300

0.6 995

emf (V)

985

Temperature( )

emf (V)

0.915

0.4

0.2

0 177000

Time (s)

985

Temperature (°C)

1005

975

177100

965 177200

Time (s)

Fig. 9 Influence of exposure of the cell to atmosphere on the potential (circular dark dots) when the gas composition above the melt was N2. Temperature versus time (square light dots). Lid opening (triangle). Lid closing (rhombus)

1005

Fig. 11 Influence of the addition of pure aluminium on the potential (circular dark dots). Temperature (square ligth dots)

Conclusion

1003

emf (V)

0.856 1001 0.853

0.85 80250

999

Temperature( )

0.859

997 80350

80450

Time (s) Fig. 10 Influence of exposure of the cell to atmosphere on the potential (circular dark dots) when the gas composition above the melt was CO2. Temperature versus time (square light dots). Lid opening (triangle). Lid closing (rhombus)

of aluminium from the reference electrode into the melt. Dissolved aluminium is a strong reducing agent. To confirm this assumption, a few grams of aluminium was added to the bath. The effect of the addition was a drop in the potential of more than 0.3 V as Fig. 11 shows. This drop can be due to the reaction between aluminium and CO2 or CO as shown in Eq. (22). 4AlðdissÞ þ 6COðgasÞ ¼ 2Al2 O3ðdissÞ þ 6CðsÞ

ð22Þ

The electrochemical alumina sensor has been tested. The decrease in potential associated with alumina additions is comparable to the calculated values. The total decrease in potential at saturation is also corresponding with calculated values. However, some potential measurements are sometimes not in agreement with the calculated values. There are some factors that cause sudden variations and drifting in the potential. The reactions between dissolved aluminium and CO and CO2 are believed to be one of the main reasons for the drifting in potential when using the aluminium reference electrode. The entering of oxygen from the air into the furnace can cause changes in the partial pressures of CO and CO2 which might affect the potential values of the electrodes.

References 1. Thonstad J, Fellner P, Haarberg GM (2001) Aluminium Electrolysis: Fundamentals of the Hall-Heroult Process. Aluminium-Verlag. 2. Thonstad, J (1964) On the anode gas reactions in aluminium electrolysis, II. J. Electrochem. Soc. Vol. 111, No. 8, 959–965. 3. Grjotheim K, Kvande H (1993) Introduction to aluminium electrolysis: understanding the Hall-Heroult process. Aluminium-Verlag, Dusseldorf. 4. Thonstad J, Solheim A, Rolseth S, Skar O (1988) The dissolution of alumina in cryolite melts. Essential Readings in Light Metals, 105–111.

Alumina Concentration Measurements in Cryolite Melts 5. Zhan SQ, Mao LI, Zhou JM, Yang JH, Zhou YW (2015) Analysis and modeling of alumina dissolution based on heat and mass transfer. Transactions of Nonferrous Metals Society of China, 25 (5):1648–1656. 6. Jakobsen S (2001) Estimating alumina concentration distribution in aluminium electrolysis cells. IFAC Automation in Mining, Mineral and Metal Processing. Tokyo. 7. Richards NE, Rolseth S, Thonstad J, Haverkamp RG (1995) Electrochemical analysis of alumina dissolved in cryolite melts. Light Metals 1995, 391–404.

607 8. Vasyunina NV, Vasyunina IP, Mikhalev YG, Vinogradov AM (2009) The solubility and dissolution rate of alumina in acidic cryolite aluminous melts. Russian Journal of Non-Ferrous Metals, 50(4):338–342. 9. Frank WB, Foster LM (1957) Investigation of transport phenomena in the cryolite-alumina system by mean of radioactive tracers. J.Phys. Chem. 61, 1531–1536. 10. Sommerseth C (2016) The effect of production parameters on the performance of carbon anodes for aluminium production. Ph.D. thesis, Norwegian University of Science and Technology, NTNU.

The Influence of Polarisation on the Wetting of Graphite in Cryolite-Alumina Melts Henrik Åsheim, Ingrid A. Eidsvaag, Asbjørn Solheim, Henrik Gudbrandsen, Geir M. Haarberg, and Espen Sandnes

Abstract

The wetting properties of graphite were measured with the immersion/emersion technique in a high temperature alumina reduction cell. The wetting was measured at untreated, polarised and anode effect polarised samples. Most measurements were made in melts with 1 wt% alumina, although some measurements were performed at higher alumina content. As long as passivation (i.e. anode effect) was not initiated polarisation improved the wettability significantly and the wetting increased with increased polarisation. Anodes polarised to anode effect exhibited consistently very poor wetting. Most of the decrease in wetting occurred during the first few seconds of the anode effect, with full de-wetting from about 60 s.





Keywords




Wetting Graphite Cryolite Polarisation Anode effect




Alumina




H. Åsheim
I. A. Eidsvaag Hydro Alumininum AS, Verksvegen 1, 6884 Øvre Årdal, Norway e-mail: [email protected] e-mail: [email protected] A. Solheim
H. Gudbrandsen SINTEF Industry, SINTEF, 7465 Trondheim, Norway e-mail: [email protected] e-mail: [email protected] G. M. Haarberg
E. Sandnes (&) Department of Materials Science and Engineering, Norwegian University of Science and Technology, 7491 Trondheim, Norway e-mail: [email protected]

Introduction Many industrial processes take place at interfaces and it is therefore important to understand how they are affected by different phenomena. Within these processes common phenomena include Marangoni flow, wettability (contact angle), emulsification, foam formation jets, and surface waves, according to Mills et al. [1]. Several reactions in the Hall-Heroúlt process take place at interfaces. The reduction of aluminium containing ions to aluminium metal takes place at the metal/bath interface and the oxidation of carbon takes place at the anode/bath interface. Other processes include the formation and dissolution of sideledge and wear of the carbon cathode and dissolution of alumina in the bath [2]. The wetting between the anode and bath is important as it affects the anode gas coverage, and bubble size. The gas coverage and bubble thickness cause additional voltage drop in the cell, increasing the energy consumption. Additionally, flow induced by bubbles is the main contributor to bath convection in the cell, thus partially responsible for the dissolution and distribution of alumina [3]. The anode effect is joined by de-wetting and researchers have suggested that deterioration of wetting properties of the anode/electrolyte interface could advance the onset of the anode effect [4, 5]. A handful of variables influence the wetting of the carbon anode by the melt. It is heavily dependent on melt composition, physical properties of the carbon substrate (mainly structure), temperature and composition of gas phase [6, 7]. Matiašovský et al. [8] reported an angle of wetting for both graphite and amorphous carbon towards cryolite to be between 120 and 130 , with almost no change with increasing AlF3 content and decreasing with increasing temperature. The contact angle was found to decrease with increasing alumina content, approaching 110(5) at saturation. Wetting has been found to improve with current, attain a maximum, and then decrease with diminishing surface active ions combined with a transition of

e-mail: [email protected] © The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_83

608

The Influence of Polarisation on the Wetting of Graphite ...

609

anode gas from one that only contains CO and CO2 , to one that also contains CF4 [7, 9].

Theory Surface Tension and Wetting Angles Surface tension can be regarded as the tendency of a fluid to occupy the lowest surface area possible. It is e.g. what makes it possible for small insects to walk on water. In the bulk of a fluid cohesive forces between molecules are completely balanced by neighbouring molecules, while towards the surface there is an increasing influence from adhesive forces with the gas-phase. The cohesive force is largest and the net effect is an inward force for surface molecules which makes the surface to come under tension. If free to move the fluid will contract to minimize area [10]. The interfacial tension depends on the chemical nature of the phases and is distinct for a specific system. Chemically similar media require less energy to form an interface between them. Adding surfactants can greatly lower interfacial tension and improve mixing/wetting between phases. Contact angle is the inclination observed at a three-phase boundary between a liquid, a vapour and a solid. It is conventionally measured through the liquid and the angle provides information about the wettability of the system. A low contact angle (90 ) represents a system with unfavourable wetting and the liquid will minimize its contact area and form droplets on the surface [10], as illustrated in Fig. 1. The balance between the contact angle and the three interfacial tensions is described by Young’s equation [11, 12], clv cos h ¼ csv  csl

ð1Þ

where clv , csv and csl represent the liquid-vapour, solid-vapour and solid-liquid interfacial tensions, respectively, and h is the contact angle. Young’s equation assumes a completely homogeneous and smooth surface and its equilibrium angle is often not obtained, even after long

equilibration time. Most surfaces have some surface curvature (roughness) which will give rise to a static hysteresis of contact angles [13]. A series of metastable contact angles can be obtained, ranging from a maximum denoted the advancing contact angle, ha , to a minimum referred to as the receding contact angle, hr . The concept of advancing and receding angles can be understood by imagining a droplet of liquid on a solid surface with an equilibrium contact angle. Introducing more liquid into the droplet will increase its size and contact angle, but the contact point will not change before its advancing contact angle is reached. Similarly, liquid can be removed from the droplet without changing the contact point until the receding angle is obtained. This effect can be quite large, e.g. water droplets on a smooth homogeneous glass surface can have ha in the range of 40–60 with hr of approximately 0–5 [13]. There are several methods used for measuring contact angles and in most cases it either involves direct visual inspection of the angle, or indirect measurement of the force acting upon a solid sample. The present paper only considers a method from the latter group.

The Immersion-Emersion Technique The immersion-emersion technique is a method for measuring the contact angle through indirect measurement of force acting upon a solid substrate being pushed and pulled into and out of a liquid. It can be considered a dynamic variant of the Wilhelmy balance method [14, 15] which has been extensively used to determine surface tension of liquids. The detected force change on the balance is a combination of buoyancy from the displaced liquid combined with that of wetting and is given by the following relation, F ¼ clv p cos h  VDqg

ð2Þ

where the first term comes from weight changes due to wetting and the second stems from buoyancy. In this equation clv is the surface tension of the liquid, p is the perimeter of the solid being dipped into the liquid, h is the contact angle, V is the volume of displaced liquid, Dq is the difference in density between the liquid and the gas, and g is

Fig. 1 Contact angles and surface tensions of liquids on a flat homogeneous surface. The droplets represent wetting, non-wetting and de-wetting examples from left to right

610

H. Åsheim et al.

the gravitational constant [10]. The force observed in Eq. (2) is also affected by viscosity but it can be neglected when the capillary number Ca  1 [16, 17], Ca ¼

lm clv

ð3Þ

where l is the viscosity of the liquid (kgm1 s1 ) and m the characteristic velocity (m s1 ), which in this case corresponds to the immersion-emersion cycling speed. Cycling velocity was typically set to 0.2 mm s1 with occasional tests at 1 mm s1 . With viscosity l ¼ 2:07E  3 kgm1 s1 [18] and surface tension clv ¼ 110 mNm1 [19] the capillary number becomes Ca  105 at its highest.

Experimental Apparatus and Equipment The apparatus used for measurements of anode wetting was a slightly modified version of what has been used previously by Martinez et al. [3] and Solheim et al. [2], with the largest difference being that the load sensor had been moved on top of the furnace as it sometimes malfuntioned at elevated temperatures. The furnace was water-cooled, with a vertical and replaceable mullite inner tube, and sealed on each side by water-cooled steel lids with O-rings. A stepper motor (ROBO Cylinder RCP2W-RA4C-I-42-P-5-150-P1-M-B) was fixed below the base of the furnace with an attached shaft penetrating the bottom lid. This allowed the crucible containing the melt to be moved in the vertical direction. The anode was suspended by a steel rod hanging from a load cell (FUTEK LSB200 (FSH02665)). Electrical connection was provided by a heavily stranded wire to minimise its interference on the force readings from the load cell. It was connected directly to the steel rod and a ring of alumina was used to insulate it from the load cell. Additional weights were added upon the anode to improve stability and ensure that it stayed level. Temperature was measured at the base of the crucible from a thermocouple that was placed inside the shaft. It was also possible to record temperature beside the anode from a thermocouple passing through the upper lid, however, it added noise to the load cell data. All wires and cables were fastened to the supporting structure to reduce noise. Electric current was supplied with a system power supply (HP 6032A, 50 A/60 V). Current was measured using a shunt resistor (0.01 X), whereas cell voltage was measured between the wire and shaft, as close to the anode and cathode as possible. To be able to reach voltages of about 30 V without saturation of the logging equipment a

voltage divider was added in parallel with the system. With a total resistance of approximately 30 kX a negligible error of 1 mA may at worst be realised from this change. All equipment was controlled through LabView. The signal from the load cell was converted through an ADC micro-controller (FUTEK IMP650), while current and voltage were recorded with an NI cDAQ 9174 data acquisition unit with an NI 9205 module. Thermocouple data was recorded with the NI 9211 module. All data were recorded at 5 Hz, although the thermocouple data was up-sampled from 3.5 Hz. The temperature was 1000  C at the start of a polarisation, increasing a few degrees when current passed through the cell. Argon was flowing through the cell with an inlet at the top lid and outlet at the bottom to ensure that the furnace was kept under an inert atmosphere and remove CO and CO2 produced during polarisation. The agron gas flow rate was approximately 0.5 lmin1 . As CO2 was produced during electrolysis and CO mainly through the Boudouard reaction, the gas composition changed during the experiments. The effect of this is commented on in the discussion. The off-gas composition was not analysed.

Materials The crucibles were made from graphite (Schunk-Tokai, £ 76.5/90 mm) with an inner height of 110 mm. An inner shield of Si3 N4 (£ 65/74 mm, height 80 mm) was employed. The anodes had some horizontal surface area. Two different anode shapes were used, both made from graphite (Schunk-Tokai). The first being an inverted cup (£ 26/30 mm, height 45/55 mm). The top part of the anode included two £ 3 mm gas vent holes and M8  1 threads for connection to the steel current collector. The second anode shape consisted of a graphite cylinder sandwiched between two boron nitride (hot-pressed, Kennametal) cylinders, all with a diameter of 16 mm. The carbon cylinder measured 10 or 30 mm in height. A sketch of the anodes can be viewed in Fig. 2. The inverted cup anode provides a long perimeter for the meniscus, which minimises the experimental error. Additionally, when insulating the sidewalls of the crucible with a Si3 N4 or Al2 O3 tube, most of the current passing the anode is distributed to the bottom horizontal surface, somewhat similar to the industrial anodes [20]. The bubble noise observed during polarisation depends on the wall thickness, as a larger fraction of the total current is distributed to the horizontal bottom surface and also bubbles might grow larger with the larger horizontal surface area. The wall thickness should thus be kept low if the aim is to minimise the bubble noise, however, machining very thin anodes can be difficult, especially when using the industrial

The Influence of Polarisation on the Wetting of Graphite ... Steel

611

Steel

Graphite

Sample material

Ø30

(a) Cup anode.

Boron nitride

11

Ø26

15

Graphite 10/30

45

55

Boron nitride

15

Graphite

Ø3

M8x1

Ø3 M8x1

Ø16

(b) Vertical anode.

Fig. 2 The two main types of anodes used in the present work. a The cup anode with 2 mm wall thickness and b the vertical anode with sample graphite material of either 10 or 30 mm in height. All units in millimeters

coke/pitch blend. The vertical anode reduces the bubble noise and can make it possible to extract useful wetting data also from the polarisation period. Furthermore, when the meniscus is placed on the upper boron nitride (BN) part of the vertical anode, the electrode has a very well defined active geometric surface area. The electrolyte was prepared by mixing cryolite (Na3 AlF6 , Aldrich), aluminium fluoride (AlF3 , industrial grade, sublimed at 1090  C) and alumina (Al2 O3 , Merck/ Aldrich). The alumina concentration was in most cases chosen to be 1 wt% as the power supply is not powerful enough to completely passivate the anode at higher concentrations, at least without reducing the surface area significantly. Nonetheless a few experiments were conducted at 3, 5 and 11 wt% (saturated). All melts were prepared with a cryolite ratio (CR, nNaF =nAlF3 ) of 2.3.

Measuring Sequence An example of an immersion/emersion cycle can be viewed in Fig. 3 for a weight against time plot and in Fig. 4 for a weight against position plot. A typical immersion/emersion cycle begins 10 mm above the melt and reverse direction 10 mm into the melt. The contact point of anode/electrolyte surface can be determined from both a change in force observed by the load cell, but also by a change in voltage from 0 V when separated to open circuit potential (OCP) when in contact. The two methods were never more than 0.2 mm apart. The anode is in contact with the surface in point (a), and until point (b) the meniscus is pinned at this same anode position. During this time the contact angle h is changing towards the advancing contact angle ha which is reached at point (b). As this is the limiting angle that may be reached during immersion it has to be kept and all changes in force from further immersion is due to

buoyancy so the angle is the same from (b) to (c). From (c) to (d) there is a 15 s dwell time that in some systems might show a move towards an equilibrium contact angle, not visible here. Often with the transition from immersion to emersion there is a gradual change from ha to hr and during this time the liquid is pinned at the same point on the solid anode. Figure 4 shows little hysteresis between (c) and (d) and the advancing and receding contact angles are in this case very similar, with the odd case that hr [ ha . Once the contact angle reaches the receding angle (d) the contact line again depins and the resulting force varies linearly between (d) and (e). When the contact line reaches (e) it is again pinned to the surface and from (e) to (f) the meniscus curvature decreases until the sample is completely extracted from the melt. By correcting for buoyancy (measured mass, mm , minus theoretical mass, mt ) the advancing and receding wetting weights can be observed as straight horizontal lines, given a homogeneous and smooth surface.

Increased Polarisation A typical measurement with polarisation is presented in Fig. 5. The anode sample is first retracted before it is submerged into the melt at a speed of 0.2 mms1 all the way down to 10 mm below the bulk electrolyte surface. This point is designated “After reimmersion” and it refers to the previous measurement. This is because some bubbles from polarisation may stick to the sample surface, thus making it necessary to retract and submerge it again to “clean” it from unaccounted buoyancy. The sample then dwells in this position for 120 s. After the reimmersion step the sample is polarised for 60 s at one specific voltage. 1 V for the first measurement and in steps of 1 V up to 10 V for subsequent measurements. After polarisation it dwells for 180 s before being emersed at 0.2 mms1 to 10 mm relative to electrolyte level. The whole procedure is then repeated with the next polarisation voltage. Increased Passivation Time The effect of how increased time at passivating potentials affected wettability was conducted on the vertical anode with a graphite sample section of 30 mm. The electrode was first immersed to 21 mm (10 mm onto carbon phase) and held in that position for 60 s, before it was immersed an additional 5 mm onto carbon where it was held for another 60 s. It was then polarised before again being kept at the same position for another 60 s, subsequently retracted from the electrolyte. The wetting weight is the average recorded over the two 60 s periods that follow after the sample immersion and subsequent reimmersions. The extra holding spot is there to be sure that wetting is measured at a surface that has been completely covered by liquid during polarization.

612

H. Åsheim et al.

Fig. 3 Example of an immersion/emersion versus time procedure without polarisation on an inverted cup anode. The sample was immersed to 10 mm at 0.2 mms1 . Upper: Movement of electrode versus time (position positive when immersed). Middle: Raw weight data. Lower: Net weight data with buoyancy correction divided by sample perimeter

Position / mm

10

Movement relative to liquid surface

5 0 -5 -10

Weight / g

198

(mm - mt) over

(f)

194 192 0.05

perimeter / g cm-1

(a)

196

(b)

(c)

(d)

(e)

100

120

Before buoyancy correction After buoyancy correction

0 -0.05 -0.1 -0.15

0

20

40

60

80

140

160

180

200

220

Time / s

Fig. 4 Example of immersion/emersion versus position procedure with no polarisation on an inverted cup anode. Upper: Raw weight data during immersion to 10 mm at 0.2 mms1 . Lower: Net weight data with buoyancy correction divided by sample perimeter

(a)

Weight / g

198

Immersion Emersion

(f)

196

(b) (e)

194

(c) 192

(d)

(mm - mt) over

perimeter / g cm-1

0.05 0 -0.05 -0.1 -0.15

-10

-8

-6

-4

-2

0

2

4

6

8

10

Position / mm

0.15

(mm - mt) over perimeter / g cm-1

Fig. 5 Typical buoyancy corrected immersion/emersion procedure with polarisation of sample. The arrows indicate where the different wetting weights are collected

0.1 0.05

After During reimmersion Polarisation

0

After polarisation

Retracted

Retracted

-0.05 -0.1 -0.15 -0.2 Immersed -0.25

0

100

200

300

Time / s

400

500

600

The Influence of Polarisation on the Wetting of Graphite ...

613

The electrode was first polarised for 60 s at both 3 and 4 V to give good wetting. Later polarisations took place at the anode effect inducing potential of 20 V. The polarisation time started with 1 s and increased incrementally, ending with an accumulated time of 1 h.

Results and Discussion Wetting Behaviour of Polarised Carbon Samples in General Polarisations at both common electrolysis potentials (3–4 V) and anode effect inducing potentials were carried out on both inverted cup anodes and purely vertical anodes. Figure 6a, b

Electrolysis - 5 V

0.15 0.1

(mm - mt) over perimeter / g cm-1

0.05 0 -0.05 -0.1 -0.15 0.15

Anode effect - 8 V

Immersion Emersion

0.1 0.05 0 -0.05 -0.1 -0.15 -10

-8

-6

-4

-2

0

2

4

6

8

10

Position relative to liquid surface / mm

(a) Buoyancy corrected weight vs. position. 0.15

Electrolysis - 5 V

0.1 0.05

(mm - mt) over perimeter / g cm-1

Fig. 6 Buoyancy corrected weight versus position and time on inverted cup anode in a melt containing 1 wt% Al2 O3 . The upper plots show normal polarisation at 5 V, while the lower plots present anode effect polarisation at 8 V. Both samples were previously pretreated with polarisations at non-AE inducing voltages

illustrate the general weight change behaviour for normal electrolysis (upper plots) and anode effects (lower plots) in a melt with 1 wt% Al2 O3 at 1000  C. both cases the anode had previously been polarised at normal electrolysis potentials. The immersion depths are somewhat lower than 10 mm since some of the electrolyte has evaporated or splashed onto the crucible walls by agitation from the gas produced by the series of polarisations. The immersion part of the figures are similar, as expected from a similar pretreatment. However, from the polarization step and onwards they differ. The upper plots with regular electrolysis show a large drop in weight stemming from gas production. The drop slowly levels off with time, likely because of increased circulation in the melt from the produced gas. The drag force

Pol.

0 -0.05 Retracted

Retracted

-0.1 Immersed

-0.15 Anode effect - 8 V

0.15 0.1 0.05

Pol.

0 -0.05 Retracted

Retracted

-0.1

Immersed

-0.15 0

100

200

300

400

Time / s

(b) Buoyancy corrected weight vs. time.

500

600

614

observed by the bubbles is initially small, and bubbles get to grow large before detaching. With increasing convection the drag force is larger and bubbles will detach at an earlier growth stage. Immediately after the current is turned off the wetting weight is increased. This “after polarisation” regime has some variance due to the fact that bubbles might still be attached to the anode, which strongly influences the recorded weight. The fact that it already shows better wetting after polarization than its previous “after reimmersion” treatment at 4 V is uncommon (see Fig. 5 for an example of the more general behavior). With the sample that got polarised to anode effect voltages (lower part of Figs. 6a, b the wetting behaviour is completely different. The weight drop during polarisation is smaller than in the case of regular electrolysis, and from the fact that the wetting weight after polarisation (and also after next reimmersion) is almost the same as during polarisation it can be assumed that the anode surface has changed characteristics and the interfacial tension between solid and liquid, csl , has changed and accounts for most of the change in weight. The current during anode effect is small, in the present case dropping from 6 to 0.5 A over the polarisation timespan. For regular electrolysis low current density is associated with the slow growth of large bubbles [21], however, large bubbles are not visualized in the weight trace. CO2 produced during electrolysis changes the gas composition inside the crucible above the melt by replacing the inert argon gas. Thus, clv and csv can both change and the recorded weight change is therefore not necessarily a result of only a change of csl arising from the new carbon surface produced during electrolysis. CO2 can react with carbon material situated above the melt surface, i.e. the crucible wall and anode, through the Boudouard reaction forming CO. It is believed that the inert argon gas interacts to a small degree with the melt and anode. The Boudouard reaction proceeds through a COads intermediate as does the electrolytic anode reaction itself. Also, it is assumed that the CO/CO2 mixture has little interaction with the melt, while the COads should lower csv as the adsorption stabilises the interface. Thus, regular polarisation with formation of CO2 and consequently COads should contribute in the direction of de-wetting as csv is reduced. However, what is observed is a net increased wetting indicating that the contribution from the electrochemical polarisation is larger. Pure CO2 could be used as furnace gas but the Boudouard reaction with the electrolysed surface would be severe as the Boudouard equilibrium is shifted strongly towards CO at 1000  C. Alternatively the argon gas inlet could be positioned inside the crucible to more effectively displace the formed CO2 /CO. Regarding polarisation causing anode effect the perfluorocarbons are stable and assumed not to interact strongly with the carbon surface, and the associated

H. Åsheim et al.

de-wetting is more likely a consequence of adsorbed fluoride and polishing effect due to the electrochemical reaction. The changing gas composition is further complicated by the anode being exposed to melt vapor sticking to the surface and csv is therefore ill-defined. Figures 7a, b show similar treatment on a purely vertical anode (see Fig. 2b). Polarisation at 3 and 10 V was applied with the meniscus at the upper boron nitride cylinder, previously pretreated at 2 and 9 V, respectively. Since the anode consists of several layers of different materials the weight against time and position traces differ from one made solely out of carbon and will vary with the wettability of the material. To further complicate matters the wettability of carbon is influenced by polarisation. During immersion the anode was first passed through the lower BN-phase, then past the carbon-phase before it was immersed 7 mm up on the second BN-phase, which is were the meniscus was held during polarization. Boron nitride is well wetted by the electrolyte while carbon is poorly wetted in the upper plot (electrolysis) and very poorly wetted in the lower plot (anode effect). When the electrolyte surface is touched by the lower BN-phase there is an abrupt rise in weight stemming from the positive wetting between the electrolyte and BN. The meniscus is at this position elevated compared to the bulk electrolyte. When approaching the carbon phase, which is negatively wetted, the elevation of the meniscus will drop and pass through a zero in the transition region between the phases. Continuing on carbon the meniscus is lowered compared to the bulk electrolyte. When the second BN-phase is approached the very negatively wetted sample that had undergone anode effect polarisation does not “see” the BN until it is below bulk electrolyte level as is evidenced in the lower trace of Fig. 7a. The upper trace with the less negatively wetted carbon could also be expected to touch the BN-phase at a position lower than the bulk electrolyte level, yet, it is realised before as could be expected from a positively wetted material. The reason for the discrepancy is unknown, however, it may stem from previous immersions leaving a thin electrolyte layer connecting the two phases. Polarisation at regular voltages produced a weight trace not unlike the one observed on the cup anode. At first there is a large drop due to initial bubble production with little convection, however, with increasing convection the bubble buoyancy is almost cancelled (upper plot of Fig. 7b). At anode effect voltages a regular cyclic weight trace is produced during polarisation. It is very similar to gas production and release on a horizontal surface during normal polarisation, although this sample exhibits a purely vertical surface. It is believed that gas is very slowly produced, sticking to the surface and gets entrapped at the boundary between the carbon phase and the upper BN-phase. Once enough gas has coalesced the buoyancy is adequate to detach the gas from

The Influence of Polarisation on the Wetting of Graphite ... Electrolysis - 3 V

0.4

Lower BN-phase

Carbon-phase

Upper BN-phase

0.3

(mm - mt) over perimeter / g cm-1

Fig. 7 Buoyancy corrected weight versus position and time on a vertical anode in a melt containing 1 wt% Al2 O3 . The upper plots show regular polarisation at 3 V, while the lower plots present anode effect polarisation at 10 V. The upper and lower anode samples were previously pretreated with polarisations at 2 and 9 V, respectively. The samples were polarised with the meniscus on the BN-phase

615

0.2 0.1 0 -0.1 0.4

Anode effect - 10 V

Immersion Emersion

0.3 0.2 0.1 0 -0.1 -10

-5

0

5

10

15

20

25

Position relative to liquid surface / mm

(a) Buoyancy corrected weight vs. position. Electrolysis - 3 V

0.4

(mm - mt) over perimeter / g cm-1

0.3

L. BN

C-phase

Upper BN

0.2

C-phase

L. BN

Pol.

0.1 0 -0.1 0.4

Anode effect - 10 V

0.3 0.2

Pol.

0.1 0 -0.1 0

100

200

300

400

500

600

700

Time / s

(b) Buoyancy corrected weight vs. time. the anode sample. The current reaches peak values with the low points of the weight trace, further suggesting small bubbles to be released revealing area to be re-passivated. The average polarization current decays from 2 A to 0.5 A, which largely explains the decreasing gas release frequency. After polarisation the wetting weight is largely the same as before, which is expected with the meniscus on BN. Removal of bubbles is also better facilitated at a completely vertical surface. During emersion there is little change in the wetting weight for the normally polarised sample (Fig. 7a), even difficult to detect when the meniscus passes between the different surfaces. Carbon is not generally expected to have the same wetting properties as BN, however, the receding wetting angle might approach the same values. The emersion part of the sample polarised to anode effect show

that the meniscus is hanging on to the well wetted BN far past it has been emersed above the liquid level. When the meniscus has been passed across the BN/C junction it is rapidly dropping below the liquid surface due to the badly wetted carbon. Polarisation was also conducted with the meniscus on the carbon layer of the vertical samples and this is presented in Figs. 8a, b with wetting weight against immersed position and wetting weight against time, respectively. Both samples had previously undergone regular electrolysis at a cell voltage of 3 V. Initially the melt contained 1 wt% Al2 O3 , however the anode effect appeared at a later time with a somewhat decreased alumina content. The wetting behaviour observed during immersion is similar to that of the vertical sample with polarisation on the upper BN-phase

616 0.4

Electrolysis - 5 V

Lower BN-phase

Carbon-phase

0.3

(mm - mt) over perimeter / g cm-1

Fig. 8 Buoyancy corrected weight versus position and time on a vertical anode in a melt containing *1 wt% Al2 O3 . The upper plots show regular polarisation at 5 V, while the lower plots present anode effect polarisation also at 5 V, albeit at a later time. Both samples were previously treated with regular polarisations at 3 V. The samples were polarised with the meniscus on the C-phase

H. Åsheim et al.

0.2 0.1 0 -0.1 0.4

Anode effect - 5 V

Immersion Emersion

0.3 0.2 0.1 0 -0.1 -10

-5

0

5

10

15

Position relative to liquid surface / mm

(a) Buoyancy corrected weight vs. position. Electrolysis - 5 V

0.4

L. BN

(mm - mt) over perimeter / g cm-1

0.3

C-phase

L. BN

Pol.

0.2 0.1 0 -0.1 0.4

Anode effect - 5 V

0.3 0.2

Pol.

0.1 0 -0.1 0

50

100

150

200

250

300

Time / s

(b) Buoyancy corrected weight vs. time. (Fig. 7). The first BN-phase is well wetted by the electrolyte while carbon is somewhat less wetted. Normal polarisation produced an equal weight behaviour to that of polarisation the upper BN-phase (Fig. 7). The more positive weight after polarisation relative that before can be attributed to the higher polarisation voltage, which improves wetting as long as passivation is avoided. The anode effect polarisation instantly gave a passivated surface. The liquid level was placed in the middle of the carbon-phase creating a smaller active surface than when polarising on the upper BN-phase Additionally, the meniscus is lowered from the de-wetting anode effect producing an even smaller surface area. This is also evidenced by the current which only averaged 0.1 A during the polarisation time. Any gas produced during polarisation is expected to release freely and not make much

impact on the weight trace. No change in wetting weight was observed when the polarisation was terminated.

Increased Polarisation Wetting was observed on cup anodes with large total perimeter (outer plus inner), over polarisations ranging from Ucell = 1 to 10V and the results are presented in Fig. 9. Two voltage rampings were carried out consecutively in a 1 wt% Al2 O3 melt. The wetting weight during polarisation is lowered as bubbles with high buoyancy are produced. The curve has substantial noise due to the gas formation. The “after polarisation” data show a much improved wetting which increased with polarisation until full passivation and

The Influence of Polarisation on the Wetting of Graphite ...

0.05

(mm - mt) over perimeter / g cm-1

Fig. 9 Wetting weight for polarisations at different voltages in a 1 wt% Al2 O3 melt. The upper and middle graph show the wetting weight of the first and second polarisation ramp, while the lower graph presents the average current passed during the polarisations

617

First ramp

During polarisation After polarisation After reimmersion

-0.05 -0.15 -0.25 0.05

Second ramp

-0.05 -0.15 -0.25

Current / A

35

First ramp Second ramp

25 15 5 1

2

3

4

5

6

7

8

9

10

Cell voltage / V

anode effect was encountered. The measured wetting was further improved after reimmersion, likely because some bubbles were still attached to the surface before it was emersed and reimmersed. All polarisations improved the wetting, although positive wetting was only observed for the highest polarisations that do not end up with an anode effect. With only 1 wt% Al2 O3 polarisations with 7 V cell voltage or higher instantly passivated the sample. The second voltage ramping is very similar to the first, however one of the samples used in this ramp was passivated already with a cell voltage of 6 V. This is both evidenced by the moderately lower wetting weight at 6 V as well as the big shift in current at this voltage. The improved wetting from polarisation can likely be related to the electrical double layer which will vary with electrification [22]. Also, the surface morphology could change with polarisation as the surface gets worn differently at different current densities. Impedance measurements were not conducted in the present work, however, literature data indicate that the capacitance of the electrified interface decreases with potential and current density, sometimes passing through a minimum value before slightly increasing again [23–25]. This new electrified interface was “permanent” over a time frame of several minutes, only changing when another potential was applied to the cell. The data obtained provide a good resolution of the potential dependent wetting properties of the graphite-melt interface and agrees well with earlier wetting data presented [7, 9]. During regular polarisation the wetting increases up to the conditions corresponding to 5–6 V in the present work. Applied to industrial aluminium electrolysis under regular polarisation the anode process benefits

from the relatively good wetting by lower bubble coverage, easier bubble movement, coalescense and detachment. When the anode has been on anode effect the anode surface shows permanent de-wetting properties, probably due to the polishing and teflonisation of the surface, causing the high voltage characteristic for anode effects in smelters. Data for wetting at Al2 O3 concentrations 1, 3, 5 and 11 wt% is presented in Fig. 10. Only the 1 wt% alumina melt became passivated during the measurements. At 3 wt% Al2 O3 the PSUs current capabilities was exceeded at Ucell = 10 V while 5 and 11 wt% were limited by current already at 8.2 and 9.2 V, respectively. The latter result is a bit odd as it would have been expected that the melt saturated in alumina reached the PSUs current capabilities at lower voltage than for the 5 wt% Al2 O3 containing melt. Sample surface area could likely have been reduced by a lower immersion depth to decrease critical total current of passivation. However, the immersion/emersion depth is already quite small, considering the meniscus height which can be several millimetres at full wetting/de-wetting. Weight drop observed during polarisation was higher for melts lower in alumina, even though the current passed is quite similar for all concentrations. A change in the bubble release process was likely facilitated by the different wetting properties of the melt, probably causing smaller bubbles with increasing alumina content. The wetting data after polarisation was, for the most part, similar between the different Al2 O3 melt contents and rose with increasing polarisation, however the saturated melt deviated from this and showed an almost similar weight throughout the different polarisations. The wetting weight of the 1 wt% Al2 O3 melt dropped as expected on the 7 V polarisation as it was

618 0.05

(mm - mt) over perimeter / g cm-1

Fig. 10 Wetting weight of polarisations at different voltages in melts with 1, 3, 5 and 11 wt% Al2 O3

H. Åsheim et al. During polarisation

-0.05 -0.15 -0.25 After polarisation

0.05 -0.05 -0.15 -0.25 0.05

After reimmersion

-0.05 -0.15

Current / A

-0.25 45

1 wt% 3 wt% 5 wt% 11 wt%

35 25 15 5 1

2

3

4

5

6

7

8

9

10

Cell voltage / V

passivated. The wetting weight after reimmersion increased similarly for all but the saturated melt. The wetting of the melt containing 1 wt% naturally stayed low after it was passivated, while the wetting of the 3 and 5 wt% melts continued to improve with increased polarisation. The saturated melt again showed strange and unexpected behaviour, not following or surpassing the wetting of the rest, even though some improvement in wetting weight is observed with increasing polarisation. One possible reason for the odd behaviour could be a very slight supersaturation of alumina, creating a heterogeneous melt with undissolved alumina particles.

Figure 11 shows the development of the wetting weight with increased time at anode effect inducing potentials in a 1 wt% Al2 O3 melt. The two points on the lower left describe the immersion wetting of an untreated sample, which is equivalent to a very large wetting angle. After the sample was pretreated with 60 s polarisations at 3 and 4 V huge improvements in wetting were obtained (upper points at left side). Wetting after pretreatment at 10 mm has a much lower contact angle than observed at 15 mm, which can likely be ascribed to the local current density at the different planes.

0.15

(mm - mt) over perimeter / g cm-1

Fig. 11 Wetting weight obtained on an inverted graphite cup electrode with increasing anode effect time. Lower points on left y-axis represent wetting weight of untreated electrode, while the upper points represent wetting weight of graphite pretreated with 60 s polarisations at 3 and 4 V (value after both treatments)

Increased Passivation Time

AE polarisation plane (15 mm) AE surface (10 mm)

0.1 0.05 0 -0.05 -0.1 -0.15

10

-1

10

0

10

1

10

Duration / s

2

10

3

10

4

The Influence of Polarisation on the Wetting of Graphite ...

The upper plane was in line with the meniscus during polarisation. The current density observed at 10 mm is likely higher and more preferred from a wetting perspective. Qiu et al. [26] also found wetting to improve with anodic current density up to about 1 Acm2 at which point it started to decrease again. For anode effect polarisations the cell potential was set to 20 V. The wetting was severely decreased already after the first few seconds of anode effect, and after about 60 s no further significant reduction in wettability was observed. The current during passivation ranged from 0 to 1A. The data shows that de-wetting is not necessarily linked too strongly to the surface polish that takes place during long anode effects [27]. However, surface polish may still affect the effort needed to convert an anode effect back to regular electrolysis as a smooth and polished surface has a low surface area.

Conclusions Untreated graphite mostly show poor wettability by the cryolite-alumina electrolyte. Polarisation improved the wettability significantly and the wetting increased with increased polarisation as long as passivation (AE) was not initiated. Positive wetting on immersion were exhibited only at the highest polarisations and longest polarisation duration, although all polarisations were shifted in the positive direction when compared to untreated graphite. Anodes polarised to anode effect showed a consistent de-wetting behaviour. The de-wetting during anode effect was mostly established during the first ten seconds and after 60 s no additional decline in wetting was observed.

References 1. K.C. Mills, E.D. Hondros, Z. Li, Journal of Materials Science 40 (9–10), 2403 (2005). https://doi.org/10.1007/s10853-005-1966-z 2. A. Solheim, H. Gudbrandsen, A.M. Martinez, K.E. Einarsrud, I. Eick, in Light Metals 2015 (John Wiley & Sons, Inc., Hoboken, NJ, USA, 2015), pp. 671–676. https://doi.org/10.1002/ 9781119093435.ch113 3. A.M. Martinez, O. Paulsen, A. Solheim, H. Gudbrandsen, I. Eick, in Light Metals 2015 (John Wiley & Sons, Inc., Hoboken, NJ, USA, 2015), pp. 665–670. https://doi.org/10.1002/97811190 93435.ch112 4. J.B. Metson, R.G. Haverkamp, M.M. Hyland, J. Chen, in Light Metals 2002 (The Minerals, Metals and Materials Society, Warrendale, PA, USA, 2002), pp. 239–244 5. H. Vogt, Journal of Applied Electrochemistry 29(7), 779 (1999). https://doi.org/10.1023/A:1003575232103

619 6. E. Laé, V. Sahajwalla, B. Welch, M. Skyllas-Kazacos, Journal of Applied Electrochemistry 35(2), 199 (2005). https://doi.org/10. 1007/s10800-004-6201-0 7. K. Grjotheim, C. Krohn, M. Malinovský, K. Matiašovský, J. Thonstad, Aluminium Electrolysis: Fundamentals of the Hall-Héroult Process, 2nd edn. (Aluminium-Verlag, Düsseldorf, 1982) 8. K. Matiašovský, M. Paučírová, M. Malinovský, Chemické Zvesti 17, 181 (1963). http://www.chemicalpapers.com/file_access.php? file=173a181.pdf 9. L. Wasilewski, L. Piszczek, Zeszyty Naukowe Politechniki Ślaskiej 24(106), 51 (1964). http://delibra.bg.polsl.pl/Content/31768/ BCPS_35087_1964_Wplyw-dzialania-sil-.pdf 10. Y. Yuan, T.R. Lee, in Surface Science Techniques, Springer Series in Surface Sciences, vol. 51, ed. by G. Bracco, B. Holst (Springer Berlin Heidelberg, Berlin, Heidelberg, 2013), pp. 3–34. https://doi. org/10.1007/978-3-642-34243-1_1 11. T. Young, Philosophical Transactions of the Royal Society of London 95(0), 65 (1805). https://doi.org/10.1098/rstl.1805.0005 12. R. Finn, J. McCuan, H.C. Wente, Journal of Mathematical Fluid Mechanics 14(3), 445 (2012). https://doi.org/10.1007/s00021-0110079-5 13. V.M. Starov, M.G. Velarde, C.J. Radke, in Wetting and Spreading Dynamics (CRC Press, 2007), pp. 1–30. https://doi.org/10.1201/ 9781420016178.ch1 14. D. Teeters, J.F. Wilson, M.A. Andersen, D.C. Thomas, Journal of Colloid And Interface Science 126(2), 641 (1988). https://doi.org/ 10.1016/0021-9797(88)90167-1 15. J.A. Kleingartner, S. Srinivasan, J.M. Mabry, R.E. Cohen, G.H. McKinley, Langmuir 29(44), 13396 (2013). https://doi.org/10. 1021/la4022678 16. F.Y. Lewandowski, D. Dupuis, Journal of Non-Newtonian Fluid Mechanics 52(2), 233 (1994). https://doi.org/10.1016/0377-0257 (94)80053-7 17. L. Landau, B. Levich, Acta Physicochimica U.R.S.S. 17(1–2), 42 (1942) 18. W. Brockner, K. Tørklep, H.A. Øye, Berichte der Bunsengesellschaft für physikalische Chemie 83(1), 12 (1979). https://doi. org/10.1002/bbpc.19790830103 19. R. Fernandez, T. Østvold, Acta Chemica Scandinavica 43, 151 (1989). https://doi.org/10.3891/acta.chem.scand.43-0151 20. H. Gudbrandsen, A. Solheim, A.M. Martinez, Wetting Measuring Device. Tech. rep., SINTEF, Trondheim, Norway (2014) 21. Z. Zhao, Z. Wang, B. Gao, Y. Feng, Z. Shi, X. Hu, in Light Metals 2015 (John Wiley & Sons, Inc., Hoboken, NJ, USA, 2015), pp. 801–806. https://doi.org/10.1002/9781119093435.ch135 22. J.O. Bockris, A.K.N. Reddy, Modern Electrochemistry: An Introduction to Interdisciplinary Area, Volume 2 (Plenum Press, New York, 1970) 23. S. Jarek, J. Thonstad, Journal of Applied Electrochemistry 17(6), 1203 (1987). https://doi.org/10.1007/BF01023604 24. A. Kisza, J. Thonstad, T. Eidet, Journal of The Electrochemical Society 143(6), 1840 (1996). https://doi.org/10.1149/1.1836913 25. W. Gebarowski, C. Sommerseth, A.P. Ratvik, E. Sandnes, L. P. Lossius, H. Linga, A.M. Svensson, in Light Metals 2016 (John Wiley & Sons, Inc., Hoboken, NJ, USA, 2016), pp. 883–888. https://doi.org/10.1002/9781119274780.ch149 26. Z.X. Qiu, Q.B. Wei, K.T. You, in 7th International Leichtmetalltagung (Leoben-Wien, 1981), pp. 256–257 27. I.A. Eidsvaag, The Influence of Polarization on the Wetting of Anodes in the Hall-Héroult Process. Master’s thesis, Norwegian University of Sceince and Technology (2016)

Oxidation Study of Zinc Sulfite on the Removal of Sulfur Dioxide from Aluminum Electrolysis Flue Gas by Zinc Oxide Xuejiao Cao, Ting-an Zhang, Yan Liu, Weiguang Zhang, and Simin Li

Abstract

As the high sulfur petroleum coke consumption gradually increase in the production of pre-baked anode, SO2 is produced higher than the new environmental protection standard at the process of aluminum electrolysis. Aiming at this problem, zinc oxide desulfurization process is put forward to remove low concentration SO2 and zinc sulfate heptahydrate is obtained as the final desulfurization product in this paper. The effects of the concentration of zinc sulfite, initial pH value, temperature, stirring speed and gas flow rate on the oxidation rate of zinc sulfite oxidation were investigated by orthogonal experiment. The results showed that the stirring speed was the greatest effect on the oxidation rate of zinc sulfite, followed by the initial pH value, the gas flow rate, the temperature and the initial concentration of zinc sulfite. The optimal experimental conditions were 1% of zinc sulfite, initial pH 3, temperature 30 °C, oxygen flow rate 0.5 L/min, and stirring speed 360 r/min. Keywords




Desulfurization Oxidation Aluminum electrolysis




Zinc sulfite




Introduction Electrolytic aluminum industry is one of the basic industries in China. In 2018, China produced approximately 35.80 million tons of aluminum [1]. In the aluminum producing process, a mass of toxic and noxious substances including fluoride, sulfur dioxide, and dust are produced and emitted X. Cao (&)
T. Zhang
Y. Liu
W. Zhang
S. Li Key Laboratory of Ecological Metallurgy of Multi-Metal Intergrown Ores of Ministry of Education, Northeastern University, Special Metallurgy and Process Engineering Institute, Shenyang, 110819, China e-mail: [email protected]

[2]. The discharge of these harmful materials not only causes serious harm to the operator’s health, but also pollutes the surrounding environment [3]. Therefore, aluminum electrolytic enterprises must build a flue gas purification system to prevent pollution. At present, the dry purification technology used widely in the current aluminum industry is mainly targeted at fluoride and dust in the flue gas, but it has no effect on sulfur dioxide. Sulfur dioxide is mainly produced from the electrolysis anode, most of which is the petroleum cokes containing 0.5–4% of sulfur [4]. After the current dry de-fluorination process, the SO2 concentration in the exhaust gas is about 230–380 mg Nm−3 [5], which has serious hazards on environment and human by way of damaging the lungs and respiratory system [6–9]. However, the new standard imposed higher requirements on environmental standards for aluminum electrolytic plants in 2013. Emission limitation of SO2 decreased from 400 to 100 mg Nm−3. The removal of SO2 after dry de-fluorination has become an important environmental and safety issue. There are many ways of capturing SO2, such as seawater scrubbing method, double alkali method, ammonia method, and limestone-gypsum method. Seawater scrubbing process is widely used to remove sulfur dioxide, but it is only applicable along the coast and marine diesel engine [10]. However, most aluminum electrolytic factory is not near the coast in China. The double alkali method is excellent in reactivity between the absorbent and SO2, but the sodium compounds used are relatively expensive [11]. Wet ammonia flue gas desulfurization is prevalent for its byproduct of ammonium sulfate fertilizer recently, but it is swept aside for the ammonia escape and the constraint of the discharge of wastewater containing the ammonia nitrogen [12]. At present, limestone-gypsum process has been widely used to remove the SO2, because it has the advantages of low raw materials cost and low operation cost [13]. But during the desulfurization process, about 2.69 tons of gypsum is formed by treating 1 ton of SO2 in theory, leading to the huge piles of gypsum production. However, the desulfurization waste

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_84

620

Oxidation Study of Zinc Sulfite on the Removal of Sulfur …

621

gypsum is hard to sell in China due to the abundant and high quality of gypsum. Therefore, desulfurization gypsum waste has to be stored by damming, which is bound to cause secondary pollutant and land waste. Compared with limestone-gypsum technique, zinc oxide is also an excellent absorbent for low concentration of SO2, with the advantages of low cost, high desulfurization efficiency, recyclable desulfurization products and no secondary pollutants [14]. In zinc-based wet flue gas desulfurization process, zinc oxide as an absorbent is used to react with SO2 in flue gas to form zinc sulfite so as to achieve sulfur fixation. Subsequently, zinc sulfite is converted to zinc sulfate by oxidation or by acid decomposition. The chemical equations for absorption and commonly used oxidation methods are as follows. ZnO þ SO2 þ 2:5H2 O ¼ ZnSO3
2:5H2 O

ð1Þ

ZnO þ 2SO2 þ H2 O ¼ ZnðHSO3 Þ2

ð2Þ

ZnSO3 þ SO2 þ H2 O ¼ ZnðHSO3 Þ2

ð3Þ

ZnO þ ZnðHSO3 Þ2 þ 4H2 O ¼ 2ðZnSO3
2:5H2 OÞ 2ZnSO3
2:5H2 O þ O2 ¼ 2ZnSO4 þ 5H2 O

the oxidation rate of zinc sulfite. In this note, factors such as concentration of zinc sulfite, temperature, initial pH value, gas flow rate, and stirring speed were investigated by an orthogonal experiment.

Experimental Section Materials The zinc sulfite in the experiment was synthesized in lab scale, by mixing a solution of ZnCl2 and Na2SO3 at 298.15 K. Zinc sulfite was quickly formed, and then the solid was filtrated, washed and dried in the baker for 24 h at 333.15 K. The products obtained above were characterized by X-ray diffraction (XRD), and the result was shown in Fig. 1. The result indicated that the product was mainly in the form of ZnSO3
2.5H2O.

Experiment Methods

ð4Þ ð5Þ

Low concentration of SO2 is absorbed by zinc oxide in the spray tower. The absorption efficiency is generally higher than 98%. After that, the purified flue gas meets the national emission standard. The process is simple, unimpeded, and easy to operate, easy to master the technical conditions and little energy consumption. In this process, no secondary pollution is produced. And, zinc sulfite as an absorbent product can be oxidized to produce soluble zinc sulfate, which can be recovered and utilized with high value. However, the oxidation efficiency is low, which causes some problems such as scale formation and pipe plugging [15, 16]. Aiming at the existing problems, an injection blow method combined with oxygen oxidation in a stirred tank was proposed to remove SO2 from aluminum fuel gas by zinc oxide in our previous research [17]. During the process, intermediate product ZnSO3
2.5H2O was forced to oxidize into soluble ZnSO4 directly, and no ZnSO3
2.5H2O was formed in the desulfurization process. When the concentration of ZnSO4 reached to a certain value, ZnSO4
7H2O can be produced by evaporation and concentration. As the raw materials for electroplating and coating industries, ZnSO4
7H2O can be sold in the market easily. Obviously, the oxidation of ZnSO3
2.5H2O plays an important role in zinc oxide desulfurization. Literatures on the oxidation of zinc sulfite are still scarce. The oxidation of ZnSO3
2.5H2O is a complex process, including gas, liquid and solid. Many factors would affect

The oxidation rate of zinc sulfite was measured using the laboratory-scale apparatus sketched. A 1000 ml five-neck flask with stirrer and a water bath were employed in the oxidation experiments, as shown in Fig. 2. An axial stirrer was used to provide thorough mixing in the liquid phase. The initial pH value was adjusted by 1.2 mol/L HCl solution. The orthogonal experiments were carried out under the conditions in Tables 1 and 2. The concentration of Zn2+ in the solution at different points of time was determined by inductively coupled plasma atomic emission spectrometry (ICP-AES).

Fig. 1 X-ray diffraction patterns of zinc sulfite samples

622

X. Cao et al.

Fig. 2 Oxidation apparatus of zinc sulfite

1.Stirring paddle 2. Five-neck flask 3.Aerator 4.Water bath 5. Glass rotameter 6. Buffering tank 7.Mass flow controller; 8. Pure oxygen or nitrogen; 9. Computer; 10. PHS-3F pH meter;

Table 1 Five factors and their corresponding level

Table 2 L16(45) orthogonal experimental conditions

Concentration of zinc sulfite (%)

Initial pH value

Temperature (°C)

Gas flow rate (L/min)

Stirring speed (r/min)

(A1) 1

(B1) 3.0

(C1) 20

(D1) 0.3

(E1) 180

(A2) 5

(B2) 4.0

(C2) 30

(D2) 0.4

(E2) 240

(A3) 10

(B3) 5.0

(C3) 40

(D3) 0.5

(E3) 300

(A4) 15

(B4) 5.5

(C4) 50

(D4) 0.6

(E4) 360

No.

Concentration of zinc sulfite (A) (%)

Initial pH value (B)

Temperature (C) (°C)

Gas flow rate (D) (L/min)

Stirring speed (E) (r/min)

1.

1

3.0

20

0.3

180

2.

1

4.0

30

0.4

240

3.

1

5.0

40

0.5

300

4.

1

5.5

50

0.6

360

5.

5

3.0

30

0.5

360

6.

5

4.0

20

0.6

300

7.

5

5.0

50

0.3

240

8.

5

5.5

40

0.4

180

9.

10

3.0

40

0.6

240

10.

10

4.0

50

0.5

180

11.

10

5.0

20

0.4

360

12.

10

5.5

30

0.3

300

13.

15

3.0

50

0.4

300

14.

15

4.0

40

0.3

360

15.

15

5.0

30

0.6

180

16.

15

5.5

20

0.5

240

To investigate the effect of different factors on the oxidation process of zinc sulfite, level and factor in L16(45) orthogonal experimental design is listed in Table 1 and 2. The parameters

of the concentration of zinc sulfite(A), initial pH value (B), temperature (C), gas flow rate (D) and stirring speed (E) on the oxidation rate of zinc sulfite were investigated.

Oxidation Study of Zinc Sulfite on the Removal of Sulfur …

623

Results and Discussion Reaction Mechanism The oxidation process of zinc sulfite is a complex process including the dissolution of zinc sulfite, the dissolution of oxygen, and the dissolved sulfite reacts with the dissolved oxygen. The main reactions happened in the process were as follow: (1) Dissolution process þ ZnSO3
2:5H2 OðsÞ ¼ Zn2ðaqÞ þ SO2 3 ðaqÞ þ 2:5H2 OðaqÞ ð6Þ   SO2 3 ðaqÞ þ H2 O ¼ HSO3 ðaqÞ þ OH ðaqÞ

ð7Þ

O2 ðgasÞ ¼ O2 ðaqÞ

ð8Þ

Fig. 3 Dissolution process of zinc sulfite

Oxidation Process (2) Oxidation process 2 SO2 3 ðaqÞ þ 1=2O2ðaqÞ ¼ SO4 ðaqÞ

ð9Þ

2 þ HSO 3 þ 1=2O2ðaqÞ ¼ SO4 þ HðaqÞ

ð10Þ

In the dissolution process, the zinc sulfite dissolved into the water and was in the form of Zn2+, SO32− and HSO3−. In the oxidation process, the SO32− and HSO3− react with oxygen, and this will promote the dissolution of zinc sulfite. Therefore, more and more zinc sulfite will dissolved into the solution with continuation of the reaction. And the concentration of Zn2+ will increase during the process.

Under the same conditions in Table 2, the oxidation process was studied, and the results were shown in Fig. 4. The variation of Zn2+ concentration during the oxidation process was showed in Fig. 4. Under the experimental conditions, the Zn2+ concentration increased with the increase of reaction time. Before the oxidation process was completed, the Zn2+ concentration increased linearly. When the oxidation was finished, the Zn2+concentration did not change any more. By regressing the Zn2+ concentration with time, the slope is the oxidation rate of zinc sulfite that sig  nifies the relationship between y CZn2 þ ;t and reaction time x(t), and the results were shown in Table 3.

Dissolution Process As mentioned above, the zinc sulfite was dissolved into the solution firstly during the oxidation process. In order to better understand the dissolution behavior of zinc sulfite, the dissolution experiments were conducted firstly by blowing N2 into the system, under the experiments conditions in Table 2. The experimental results were shown in Fig. 3. As can be seen from Fig. 3, the zinc sulfite can be dissolved into the solution as soon as it contacts with water. The zinc sulfite dissolved into solution quickly and achieved to balance within 1 to 3 min under the experiment conditions. Therefore, it can be concluded that zinc sulfite was saturated during the oxidation process. Meanwhile, the variation of Zn2+ concentration was caused by the oxidation process not the dissolution process.

Fig. 4 Variation of Zn2+ concentration in the oxidation process of zinc sulfite

624

X. Cao et al.

Table 3 Orthogonal experiment results of oxidation process

No.

Regress equations

R2

Oxidation rate (g/L/min)

1

y = 0.053x + 0.8216

0.985

0.053

2

y = 0.077x + 1.161

0.983

0.077

3

y = 0.106x + 1.248

0.990

0.106

4

y = 0.130x + 1.475

0.979

0.130

5

y = 0.168x + 4.791

0.999

0.168

6

y = 0.0892x + 2.618

0.996

0.0892

7

y = 0.0488x + 8.423

0.996

0.0488

8

y = 0.0191x + 12.72

0.937

0.0191

9

y = 0.0990x + 5.029

0.995

0.0990

10

y = 0.0689x + 5.007

0.995

0.0689

11

y = 0.0929x + 4.689

0.999

0.0929

12

y = 0.0491x + 18.795

0.989

0.0491

13

y = 0.0826x + 4.682

0.997

0.0826

14

y = 0.112x + 7.176

0.998

0.112

15

y = 0.073x + 13.889

0.993

0.073

16

y = 0.058x + 6.399

0.992

0.058

According to the experiment conditions, every factor has four levels. Ki was defined as the mean value of the oxidation rate in i level of each factor. Taking factor 1 and factor 2 for example, the mean value of the level was calculated as follow: K11 ¼ 1=4ðy1 þ y2 þ y3 þ y4 Þq K21 ¼ 1=4ðy5 þ y6 þ y7 þ y8 Þq K31 ¼ 1=4ðy9 þ y10 þ y11 þ y12 Þ K41 ¼ 1=4ðy13 þ y14 þ y15 þ y16 Þ K12 ¼ 1=4ðy1 þ y6 þ y10 þ y13 Þ K22 ¼ 1=4ðy3 þ y6 þ y10 þ y14 Þ K32 ¼ 1=4ðy3 þ y7 þ y11 þ y15 Þ K42 ¼ 1=4ðy4 þ y8 þ y12 þ y16 Þ K42 ¼ 1=4ðy4 þ y8 þ y12 þ y16 Þ

Table 4 Intuitive analysis of different factors on the oxidation rate of zinc sulfite

where yj (j = 1*16) is the oxidation rate of zinc sulfite under the experiment conditions. Likewise other level’s mean value was calculated, and the results were shown in Table 4. Rj was calculated by the difference between the maximum and minimum value of Ki. The results showed that range order was RE > RB > RD > RC > RA. The results indicated that the stirring speed has the most dominant effect on the oxidation rate of zinc sulfite, followed by the initial pH value, the gas flow rate, the temperature and the initial concentration of zinc sulfite. Thus, increasing the stirring speed is an easy way to improve the oxidation rate. According to the maximum level mean value, the optimal experimental conditions were 1% of zinc sulfite (A1), initial pH value of 3 (B1), temperature of 30 °C (C2), gas flow rate of 0.5 L/min (D3), and stirring speed of 360 r/min (E4).

No.

A

B

C

D

E

K1

0.0917

0.100

0.0735

0.0658

0.0535

K2

0.0814

0.0869

0.0920

0.0680

0.0710

K3

0.0775

0.0802

0.0841

0.1006

0.0818

K4

0.0817

0.0643

0.0826

0.0978

0.1260

Range

0.0142

0.0365

0.0185

0.0348

0.0725

Optimal condition

A1

B1

C2

D3

E4

Order

E>B>D>C>A

Oxidation Study of Zinc Sulfite on the Removal of Sulfur …

625

References

Fig. 5 Effect of factors of orthogonal experiments

Effect of factors in the orthogonal experiment was shown in Fig. 5. The results indicated that the stirring speed and the initial pH had a great effect on the oxidation rate of zinc sulfite. The oxidation rate decreased with the increase of concentration of zinc sulfite and the initial pH value. The oxidation rate increased with the increase of the gas flow rate and stirring speed.

Conclusion The absorption efficiency is generally higher than 98% in the absorption process of the low concentration of SO2 by zinc oxide. But during the process, oxidation efficiency is low, and scale is forming. In order to improve the oxidation efficiency, the effects of the concentration of zinc sulfite, initial pH value, temperature, gas flow rate and stirring speed on the oxidation rate of zinc sulfite were investigated by orthogonal experiments in this paper. The results showed that the stirring speed has the most dominant effect on the oxidation rate of zinc sulfite, followed by the initial pH value, the gas flow rate, the temperature and the initial concentration of zinc sulfite. The optimal experimental conditions were 1% of zinc sulfite, initial pH value of 3, temperature of 30 °C, gas flow rate of 0.5 L/min, and stirring speed of 360 r/min. Acknowledgements This study was financially supported by the National Natural Science Fund Committee (U1402271, 51874078, and U1760120), and the Fundamental Research Funds for the Central Universities (N182504018).

1. Ministry of Industry and Information Technology. China’s aluminum production growth rate dropped by 7 percentage points year on year in 2018. http://www.sohu.com/a/299676886_642643, Accessed 7 March 2019. 2. Cassayre, L., Palau, P., Chamelot, P., et al. (2010) Properties of low-temperature melting electrolytes for the aluminum electrolysis process: a review. J. Chem. Eng. Data 55: 4549–4560. 3. Hou, J.F., Shi, D., Wang, Z.W., et al. (2017) Influence of additives on bath analysis in aluminum electrolysis. JOM 69(10): 2057–2064. 4. Tapan K. S., Saleh A. R., Amer A. M. (2015) Strategy for sustaining anode quality amidst deteriorating coke quality. Paper presented at the 33 rd ICSOBA Meeting, Dubai, 9 December 2015. 5. Du, J. J., Zeng, P., Long, H. Y., et al. (2014) The Study on the New Technology of Exhaust Gas Cascade Utilization from Electrolytic Aluminum Industry. Adv. Mat. Res. 1010–1012: 891–894. 6. He, Y. M., Tao, H. W., Ou, G. N., et al. (2013) Technical research on cryolite production process by recycling utilization of low concentration SO2 and fluorine-containing gas generated from aluminum electrolysis. Yunnan Metallurgy 42(5): 40–43(In Chinese). 7. Martin, S. C., Larivière, C. (2014) Community health risk assessment of primary aluminum smelter emissions. JOEM 56 (5s): S33–39. 8. Strømmen, S. O., Bjørnstad, E., Wedde, G. (2000). SO2 emission control in the aluminium industry. Paper presented at the 129st TMS Annual Meeting, Nashville, Tennessee, 12–16 March 2000. 9. Wesdock, J. C., Arnold, I. M. (2014) Occupational and environmental health in the aluminum industry: key points for health practitioners. JOEM 56(5s): S5–11. 10. Flagiello D., Erto A., Lancia A., et al. (2018) Experimental and modelling analysis of seawater scrubbers for sulphur dioxide removal from flue-gas. Fuel 214: 254–263. 11. Wang W. Z., Yang C. G., Zhang J. R. (2011) Absorption of sulphur dioxide from flue gas with sodium alkali solution in packed columns. Adv. Mater. Res. 383–390: 6409–6415. 12. Wang Z. K., Peng Y., Ren X. C., et al. (2015)Absorption of sulfur dioxide with dodium hydroxide solution in spray columns. Ind. Eng. Chem. Res. 54: 8670–8677. 13. Bravo R. V., Camacho R. F., Moya V. M., et al. (2002) Desulphurization of SO2–N2 mixtures by limestone slurries. Chemical Engineering Science 57: 2047–2058. 14. Lin D. S. (2011) Industrial application of zinc oxide method desulphurization technology. Sulphuric Acid Ind. 2: 43–47. 15. Huang M., Zhang J. F. (2007) SO2 removal with ash containing zinc oxide. Chem. Ind. Eng. Pro. 26(5): 720–724. 16. Huang L. M. (2015) Application and improvement of zinc oxide method desulphurization technology in lead and zinc smelters. Sulphuric Acid Ind 5: 42–45. 17. Cao X.J., Zhang T. A., Liu Y. et al. (2018) Bubble dispersion states in the zinc oxide desulfurization injection blow tank. Paper presented at the 147st TMS Annual Meeting, Phoenix, Arizona, 11–15 March 2018.

Electrolysis of Low-temperature Suspensions: An Update Andrey Yasinskiy, Andrey Suzdaltsev, Sai Krishna Padamata, Petr Polyakov, and Yuriy Zaikov

Abstract

Among different “novel” technologies for eco–friendly aluminium production with zero greenhouse gas emissions, the electrolysis of alumina suspension (or slurry) based on halide melts deserves more attention than it got recently. The original idea of the slurry was first proposed by Theodor R. Beck and has been modified and developed basically by Petr V. Polyakov. This paper presents a comprehensive analysis of the current status of this technology, future opportunities, and the new experimental results, which have not been published yet. This overview covers the properties of high-temperature suspensions, including sedimentation behaviour and apparent electrical conductivity; anodic process on oxygen-evolving electrodes, including the polarization characteristics and the bubble behaviour at vertical anodes; cathodic process on wettable substrates; primary electrolysis results; and the general considerations touching upon the possible cell designs and the thermal balance. The future scope of the technology and possible applications are discussed. Keywords











Alumina suspension Slurry Low-temperature melts Electrode processes Bubble dynamics Sedimentation Inert anodes

A. Yasinskiy
S. K. Padamata
P. Polyakov School of Non-Ferrous Metals and Materials Science, Siberian Federal University, Krasnoyarsk, Russia A. Suzdaltsev (&)
Y. Zaikov Institute of High-Temperature Electrochemistry UB RAS, Yekaterinburg, Russia e-mail: [email protected]

Introduction The CO2-free aluminium reduction technology creation is considered as one of the hardest challenges in aluminium industry up to date. It is known that: • high alumina concentration in the bath should be maintained to prevent catastrophic corrosion of the anode; • the solubility of oxides in cryolite melts is decreased with an increase in alumina concentration; • oxide layer dissolution products are transferred towards the cathode metal mostly by the convection and then are easily reduced by dissolved aluminium in catholyte. The use of suspension as an electrolyte rather than undersaturated melt can solve the problem of maintaining the melt saturated with oxygen alumina. The suspension also protects produced aluminium from the contamination by slowing down the transfer of anode corrosion products to the cathode. The method of electrolytic production of aluminium from oxide–halide melts containing dispersed alumina (Al2O3) was first patented by T. R. Beck in 1986 [1]. The systems BaCl2–AlF3–NaF–NaCl and BaCl2–AlF3–CaF2–BaF2– MgF2 with a density higher than the density of aluminium and lower than the density of alumina at 700–800 °C were proposed as an electrolyte. Both factors: the low temperature and the melt density make it possible to use inert electrode materials [2–5] and new effective cell designs. According to Beck, oxygen bubbles are evolved during electrolysis at the anode located at the cell bottom and maintain alumina slurry. Cathodic product (Al) is accumulated on the surface of the melt and periodically removed from the cell. After the laboratory and pilot industrial electrolysis tests, the NaF–AlF3 and KF–LiF–AlF3 melts with a liquidus temperature of less than 700 °C were chosen [6–9]. Despite the prospects and obvious relevance of the development of new energy-efficient methods for aluminium production

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_85

626

Electrolysis of Low-temperature Suspensions: An Update

[10–13], the proposed method has not been implemented yet. Interest in the electrolytic production of aluminium from high–temperature alumina suspensions based on fluoride and chloride melts of a wide composition in the temperature range from 700 to 965 °C was renewed by Polyakov et al. [14, 15]. According to the results of a series of electrolysis tests in suspensions, the stability of the anodic and cathodic processes was shown at current densities not higher than 0.2 A cm−2 with a cathodic current efficiency (CE) more than 90%. Later, the authors focused on a deeper study of the processes during the electrolysis of alumina suspension in the low–temperature KF–AlF3 systems [16]. In this paper, we consolidate the available data regarding the properties, electrochemical characteristics, and the behaviour of alumina suspensions in these systems, and also present new experimental results. This information seems to be necessary for the selection of the cell design and the optimal electrolysis parameters.

Properties of KF–AlF3–Al2O3 Suspensions Due to the low liquidus temperatures and the relatively high solubility of Al2O3 the KF–AlF3-based melts are the promising media for the alumina suspensions electrolysis with oxygen-evolving anodes and aluminium–wetted cathodes [17–22]. Since the suspension provides the saturated concentration of the electroactive component in the anode layer, the main criteria for the effectiveness and stability of the suspension electrolysis are the dissolution rate of Al2O3, the electrical conductivity of the suspensions, and the sedimentation stability (and velocity) of alumina particles in suspension. In terms of dissolution rate, c–Al2O3 with a large specific surface area seems to be the best for use. On the other hand, such particles can form agglomerates and settle faster on the bottom. We suppose that the behaviour of various grades of alumina upon dissolution in the KF–AlF3based melts are similar to their behaviour in molten cryolite [23–25]. The only favourable difference is that the transition of the c–phase to the a–phase at 700–800 °C will be significantly inhibited. The suspension properties should provide the synchronization of the alumina flows as follows: • feeding flow, which is easily controllable by an operator; • sedimentation flow, which is desired to be as low as possible; • dissolution flow, which is the complicated function of the suspension composition, alumina properties and the temperature;

627

• dissolved alumina consumption flow, which occurs at anode–suspension interface and can be controlled both by the operator and a cell designer as well.

Sedimentation of Al2O3 The velocity Usp of the single particle in the liquid is described by the Stokes equation: 2 a2p
g
ðqs  ql Þ Usp ¼
9 g

ð1Þ

where ap is the particle radius, g is the gravity acceleration, q is the density (subindexes s and l denote solid and liquid), g is the dynamic viscosity. The collective (or batch) sedimentation velocity Uc is complicated by the kðuÞ coefficient, which depends on the particles and medium properties and the suspension composition (and particles volume fraction u): Uc ¼

1u kðuÞ

ð2Þ

The distribution of smelter grade alumina (SGA) solid particles versus the height of the suspension in the crucible is shown in Fig. 1. It was shown that with an increase in the volume fraction u in the KF–AlF3–Al2O3 suspension at 700 °C, the sedimentation velocity decreases and becomes close to zero at 32 vol%, which is considered as maximum packing fraction. A decrease in the alumina average particle size and the

Fig. 1 The distribution of the alumina particles over the height of suspensions with 24, 28, and 32 vol% of solid Al2O3 after 15 min of sedimentation in (1.3KF–AlF3)–Al2O3 melt at 700 °C [26]

628

A. Yasinskiy et al.

temperature also leads to a decrease in the sedimentation velocity. The Stokesian nature of sedimentation was indicated by the Reynolds number (Re = 0.006…0.022), which is considered to be the important hydrodynamic parameter and can be calculated according to the equation: Re ¼

ql
Uc
dp ql
Q
dp ¼ g g
S

ð3Þ

where dp is the average particle diameter, Q is the volumetric flow rate, S is the crucible cross-section area. The uniformity of the average alumina particles size spatial distribution rdp ¼ f ðsÞ was evaluated in [27]. Figure 2 shows the dependences of the average alumina particle size distribution versus their location in the crucible (coordinates) after 15 min sedimentation and a typical micro photo of the suspension. It is seen that in the middle of the suspension bulk (30 mm from the wall), sedimentation occurs less uniformly (@dp =@z  0 where z is the distance from the bottom), while near the crucible wall dp slightly depends on z according to the linear law. Apparently, this is due to surface phenomena at the boundaries melt–wall–solid particles, which leads to an increase in the local viscosity of the suspension, high resistance to the dispersion medium layered shear relative to the wall, and stability of the suspension. Thus, the suspension stability will be contributed by a decrease in the interelectrode distance. According to Fig. 2b the particles are separated from each other with a thin layer (5–50 lm) of electrolyte. In the present work, the sedimentation velocity of alumina with different particle size distribution depending on u was also estimated by dynamically measuring the ohmic resistance of the suspension in a volume placed between flat vertical parallel electrodes. The relative change in resistance was used to evaluate the sedimentation of alumina particles

Fig. 2 Distribution of the average particle size of alumina in frozen suspension based on the KF–AlF3–Al2O3 system with 24 vol% of solid alumina particles at 700 °C (a) and the typical photo of frozen suspension (b)

Fig. 3 Dependence of normalized ohmic resistance versus time for sedimentation of SGA in (1.3KF–AlF3)–Al2O3(sat) suspension at 800 °C

in suspensions with different alumina volume fractions. Typical results are shown in Fig. 3. The change in normalized resistance was associated with the change in local u. The sedimentation velocity can be
estimated with the @ Rs
R1 0 =@s value. It can be seen that, in general, the results are comparable with those presented above: a decrease in the sedimentation velocity is facilitated by an increase in particles volume fraction in suspension and a decrease in their average size. Typical sedimentation velocities were in the range of 0.8–3.1 cm/s, k(u) function in the range of 0.024–0.038. Mechanical activation of alumina enhanced sedimentation stability and can allow performing sustainable electrolysis with low alumina volume fractions (0.10–0.15). More details will be presented in further publications.

Apparent Electrical Conductivity The presence of Al2O3 particles increases the resistance of the electrolyte by reducing its specific volume and the

Electrolysis of Low-temperature Suspensions: An Update

629

stability and removal of electrolysis products from the interelectrode space. At present, only the data on the corresponding molten systems KF–AlF3–Al2O3 and NaF–AlF3– Al2O3 [16–20, 30–32], which are summarized in Table 1, are present in the literature. It can be assumed that a change in these properties upon introducing Al2O3 particles into these melts will be determined by their properties, as in the case with a change in their electrical conductivity.

Fig. 4 The dependence of the electrical conductivity of the oxide– fluoride melts (u = 0) and alumina suspensions at 700–720 °C

cross-section area for the charge transfer. Figure 4 shows the primary results of the experimental apparent electrical conductivity measurement of the alumina suspensions based on the (1.3KF–AlF3)–Al2O3 melt at 700 °C. The solid phase fraction increase logically reduces the apparent electrical conductivity of the system. Comparative analysis (Fig. 4) shows the conductivity of an Al2O3–saturated 1.3KF–AlF3 melt [28] and the calculated values of the electrical conductivity of the (1.3NaF–AlF3)–CaF–Al2O3 melt at 720 °C [29]. It can be seen that from the electrical conductivity point of view, a system based on NaF–AlF3– Al2O3 looks preferable for the suspension electrolysis. We assume that the current densities of aluminium and oxygen evolution will be several times lower than those of traditional cells. In this case, a decrease in the electrical conductivity of the system can even be positive in terms of heating the suspension to operating temperature.

Density, Viscosity and Surface Tension In addition to the electrical conductivity, properties such as density, apparent viscosity and apparent surface tension of suspensions are important in terms of the suspension Table 1 Comparison of the basic physicochemical properties of electrolytes for the preparation of alumina suspensions [16–20, 30–32]

Electrode Processes in KF–AlF3–Al2O3 Melts and Suspensions Design of a novel electrochemical technology makes the electrode processes being of primary interest because they affect the electrolysis sustainability, the major indicators (energy consumption, CE, cathodic metal purity) and determine the operating parameters.

Anodic Process The Anodic process anodic processes on glassy carbon and platinum, as well as degradation processes on oxygen-evolving anodes in low–melting NaF–AlF3–Al2O3 and KF–AlF3–Al2O3 systems are discussed in [2–5, 33–37]. On the basis of resource tests, it was shown that lowering the temperature to 750–800 °C favourably affects the corrosion resistance of oxygen-evolving anodes, and the study of the anodic process on them seems relevant. The experiments and theoretical modelling of the process on platinum anodes during the electrolysis of the KF–AlF3– Al2O3 melts are presented in [34, 35]. Figure 5 shows typical current-voltage dependences obtained under argon and oxygen atmosphere at different temperatures. During anodic polarization of platinum, a peak appears on voltammograms, after which the evolution of gaseous oxygen starts. Moreover, even with a slight increase in temperature, the peak in the voltammograms is not recorded, which may indicate a

Melt/property −1

KF–AlF3

NaF–AlF3

[MF]/[AlF3] ratio (mol mol )

1.22

1.3

Liquidus temperature (°C)

575

715–720

Al2O3 solubility (wt%)

4.5 at 700 °C

1.2 at 702 °C

Density at 750 °C (kg m−3)

1 770

1 910

Kinematic viscosity (m2 s−1)

1.53  10−6

0.72  10−6

2.71

1.38

Surface tension at 750 °C (mN m )

138

89

Interfacial tension at 750 °C (mN m−1)

701 ± 10

796 ± 5

0.95–1.0 at 700 °C

1.2 at 720 °C

Dynamic viscosity (mPa s) −1

Electrical conductivity (Ohm

−1

−1

cm )

630

A. Yasinskiy et al.

change in the stability of the intermediate products of the anode process. Based on the results of a comparative analysis of experimental data and theoretical calculations, it was concluded that the process under study includes the stage of formation of an intermediate oxide compound on the surface of platinum with its subsequent physical and electrochemical decomposition [34]. In stationary mode the limiting current of oxygen evolution on platinum reaches 2 A cm−2 [35] in the KF–NaF–AlF3–Al2O3 melt (([KF] + [NaF])/[AlF3] = 1.3 mol mol−1) at 780 °C. Pt is known to be a proper model electrode for the study of the mechanisms and kinetics of oxygen evolution; however, it obviously cannot be applied in the industry due to economic reasons. Cu-based alloys have been considered as promising candidates for inert anodes. The effect of alumina particles in the melt on the kinetic parameters of the process at the Cu–Al oxygen-evolving anode is shown in Fig. 6. Under the stationary and non-stationary polarization, the oxygen evolution currents are consistent with the results obtained for platinum. The non–stationary polarization of the Cu–Al anode leads to the appearance of the anode components oxidation section (B1) on the voltammogram 1

Oxygen is believed to be the major anodic product during sustainable electrolysis with inert anodes in oxide–fluoride melts and suspensions. Oxygen bubbles are generated from the saturated liquid on the preferable nucleation sites and growth by absorption of dissolved gas and coalescence. Based on the results of electrolysis tests in suspension [40], gas evolution in an H2SO4 suspension with properties close to that of the suspensions studied and model calculations [41], a motion scheme and patterns of anode gas bubbles formed on an oxygen-evolving electrode as a result

1

750 °C

i/A cm-2

0,6

Ar

0,4

0 2,1

780 °C

0,8

O2

0,2

Fig. 6 Stationary polarization dependences (A) and voltammograms (B) obtained on a Cu–Al alloy in the saturated (1.3KF–AlF3)–Al2O3 melt and suspension at 750 °C (sweep rate —0.05 V s−1)

Gas Evolution Regularities

0,8

i/A cm-2

Fig. 5 Voltammograms recorded on platinum in the saturated 1.3(KF–NaF)–AlF3– Al2O3 melt under argon (Ar) and oxygen (O2) atmosphere at 750 and 780 °C (sweep rate— 0.1 V s−1) [35]

before oxygen evolution (B2). The introduction a–Al2O3 particles (u = 0.12) into the melt leads to a 1.5–2-fold decrease in the oxygen evolution currents, which can be explained by a screening of the anode surface with alumina particles and bubbles, and by the appearance of additional difficulties in the desorption of oxygen bubbles [38]. More details on the anodic process at Cu–Al-based electrodes can be found in the article published in the current issue [39].

2,3

O2

0,4 0,2

E vs. EAl / V 2,2

Ar

0,6

2,4

2,5

0 2,1

E vs. EAl / V 2,2

2,3

2,4

2,5

Electrolysis of Low-temperature Suspensions: An Update

Fig. 7 Scheme of movement (arrows) of bubbles, alumina particles and electrolyte volumes in the anodic space of suspension [40]: (1) anode top layer, (2) top part of gas channel, (3) top layer, (4) anodic liquid layer, (5) gas channel, (6) interslug three-phase layer, (7) moving two-phase layer, (8) motionless two-phase layer, (9) slug

of suspension electrolysis were demonstrated. The interfacial tension of the melt is almost 2 times higher than that of an aqueous solution, which will affect the interfacial energies at the electrode-gas-electrolyte boundaries. We assume that the presence of alumina solid particles levels the influence of surface energy and the viscosity and density of suspensions become the main criteria for the dynamics of bubble growth. Two different kinds of bubbles could be observed at the same time (Fig. 7): the slugs (9) and the small bubbles. The slugs move through the channel (2, 5, 6) with less density than that of the other layers. The channel is formed by the slugs itself through the particles transport to the top layer (1, 2, 3) where the small bubbles and the particles are accumulated. After the bubble is grown in anodic liquid (less dense) layer (4) and detached from the surface it moves down due to the electrolyte backflow till it coalesces with the slug or other small bubbles or enters the interslug three-phase layer (6). Movement of the slugs transmits the motion to the moving two-phase layer (7), which stays bubble-free while another two-phase layer (8) remains motionless. An increase in the alumina fraction in the

Fig. 8 Dependence between the three-phase layer thickness and the distance from the bottom (height) for anodic evolution of oxygen bubbles in H2SO4 solution at 0.1 and 0.2 A cm−2 (a) and the frames with recorded gas evolution (b) at 0.05 A cm−2

631

suspension enhances the hydrodynamic resistance and complicates the convective transfer of anode gases, increases the electrical resistivity due to an increase in the volume of the non–conducting phase (gas bubbles and alumina particles). The dependence of the three-phase layer thickness versus distance from the bottom and the frames of the recorded bubble movement at the gas–evolving electrode obtained on the water model are presented in Fig. 8. The water model was designed for dimensionless similarity criteria: modified Reynolds number Re* = 16.24, Galileo number Ga = (1.78…2.00)  1010, Weber number We = (5.96…9.8)  1010, geometrical simplex h/l = 7.5 (h and l denote the electrode height and interelectrode distance respectively) and u = 0.3. The alumina suspension based on 20% H2SO4 water solution was used as an electrolyte at 50 °C. It was shown that due to a decrease in temperature, current density, and the appearance of the hydrodynamic resistance, the velocity of anodic gas bubbles in suspensions decreases by 10 times to be as low as 1.0–2.3 cm s−1. The width of the bubbles is comparable (0.8–2.3 mm) to the one in Hall–Heroult cell [17], however, the length can reach more than 20 mm. Due to the low velocity, increased gas fraction and hydrodynamic resistance, a significant horizontal component of the bubble velocity appears in the direction away from the vertical anode. All this leads to the fact that the main mechanism of the anode gases motion in the suspension becomes to be the slug flow. The observations follow to the conclusion that forced gas removal (through some kind of porous electrode) is highly desirable for the technology.

Cathodic Process Much attention was paid to the study of cathode polarization in melts and suspensions [42, 43]. The effect of the temperature (670–800 °C), cathode material (tungsten, glassy carbon), ratio [KF]/[AlF3] (1.3 and 1.5 mol mol−1), u (0;

632

A. Yasinskiy et al.

Fig. 9 Stationary polarization curves (a) and voltammograms (b) obtained on tungsten in a saturated (1.3KF–AlF3)–Al2O3 melt and suspension at 750 °C [43]

0.18 and 0.30) on the kinetic parameters of the aluminium reduction from the KF–AlF3–Al2O3 melts and suspensions were studied both under stationary and non–stationary conditions. Figure 9 shows typical stationary and non-stationary polarization curves on tungsten. On the stationary polarization curves (Fig. 9a) aluminium reduction section (a–b) followed by limiting currents of aluminium section (b–c) found ranged from 0.15 to 0.70 A cm−2 depending on the conditions and then followed by the potassium evolution section (c–d). According to non-stationary voltammograms (Fig. 9b) aluminium reduction starts at a potential of about 0 V relative to the aluminium electrode potential with the appearance of a cathode peak (Al) in the potential region of −0.3…−0.45 V. With a further potential shift, the negative current of aluminium reduction persists up to the wave of potassium evolution (K) at potentials more negative than −1.1 V. On the anodic part of the curve the peaks of potassium (K′) and aluminium (Al′) oxidation are observed. Based on these observations, a scheme of the cathodic process in KF–AlF3–Al2O3 melts is proposed, which includes parallel electrochemical stages of the discharge of fluoride and oxide–fluoride ions, as well as the probability of partial salt passivation of the cathode and the interaction of reduced aluminium with KF. Introduction of Al2O3 particles and increases in its proportion in the suspension increases cathodic overvoltage and decreases the limiting current density of aluminium reduction under stationary conditions for all investigated temperatures and [KF]/[AlF3] ratios. The using KF–AlF3 systems widens the electrochemical window for the aluminium electrodeposition without an alkali metal reduction. In (1.3NaF–AlF3)–Al2O3 melts at 860 °C sodium is reduced at a potential 0.2…0.25 V more

negative than the aluminium reduction potential [44–47]. This can be a significant obstacle to the sustainable electrolysis of the suspension since the recirculation of the cathode layer in suspensions is extremely difficult.

Electrolysis Tests The longest successful test was performed by Simakov [46] in alumina suspension based on NaAlF4–LiF melt with cermet Cu2O–Cu anode and protective graphite cathode at 750 °C at the cathodic current density of 0.15 A cm−2 with CE of more than 90% (which is extraordinary high for laboratory cell) and the specific energy consumption of less than 12.8 kW h/kg Al. Figure 10 represents the cell voltage change during electrolysis of melt for 3 h (A), a gradual increase of alumina volume fraction till *0.24 for 6 h (B) and electrolysis of suspension for 39 h (C). The cathode had channels for the removal of aluminium from interelectrode space (D). The voltage slightly increased during the test that was explained by the increase in the contact resistances. However, the highest value was between 3.9 and 4.0 V which is rather low due to the low current densities resulted in low over voltages and low voltage drop in the suspension layer, which was 2.5 cm. The channels inside the cathode were filled with aluminium that confirms the possibility to remove aluminium through the electrode body. The results obtained up to date [43] support the idea of aluminium production in alumina suspension at 750–800 °C at low current densities of 0.1–0.3 A cm−2. Higher values often lead to the anode or cathode passivation, uncontrollable change in cell voltage and temperature. Another

Electrolysis of Low-temperature Suspensions: An Update

633

Fig. 10 The voltage versus time during the electrolysis of melt and suspension (see description in the text)

phenomenon, which has been observed (mostly for SGA) is Ostwald ripening (or recrystallization) of alumna that forms huge agglomerates of a–Al2O3. It contributes to the cell voltage increase and makes the operation of the cell difficult. This phenomenon was not observed in suspensions with mechanically activated alumina.

• electrolysis at permissible current densities (see section “Electrode Processes in KF–AlF3–Al2O3 Melts and Suspensions”); • electrodes dimensional stability; • cathode aluminium and anode gases removal; • maintaining alumina suspension physically stable (without local densification).

Simulations of Suspension Behaviour at Electrolysis

From the works [7, 15], two basic concepts of the cell are known, which differ in the method of cathode aluminium removal from the electrolysis zone. In the cell concept by Beck and Brooks [7] prevention of alumina sedimentation is achieved by using an anode with vertical and horizontal gas– evolving surfaces (Fig. 11a). Moreover, the gas evolution under the cathode should contribute to the accumulation of cathode aluminium above the horizontal surface of the anode. However, the release of anode gases under the cathode and aluminium provides significant convection in the interelectrode space, which will not allow separating the electrolysis products, to achieve high CE and low specific energy consumption [48]. For the removal of liquid metal from the cell Polyakov et al. proposed cathodes with channels (Fig. 11b). During the electrolysis of suspension (6…40 vol%) gases released at the anode move the electrolyte up along the anode surface and down along the cathode surface. Additionally, the flow of electrolyte along the surface of the cathodes improves the removal of metal (aluminium) through the channels under the “false” bottom of the cell. In the described concept, the main volume of the suspension in the interelectrode space should not take part in the electrolyte circulation, while it should be in suspension effectively separating the electrolysis products. Variants of cell designs with inclined bipolar electrodes are also known [12], which, however, seems less promising due to the complexity of their arrangement and maintenance.

All the above results and patterns of alumina suspensions behaviour are necessary for the development of both the cell design and for the technology parameters determination. To increase the efficiency of such developments and to obtain the fastest practically important results, thermal and electrical fields in the cell with vertical bipolar electrodes (20 in a row) were calculated [16]. The model cathodic current density was 0.4 A cm−2. It was shown that aluminium can be obtained by electrolysis of alumina suspensions in melts based on the KF–AlF3 system with productivity of 5–7 kg Al/h with energy consumption of 12.8–13.5 MW h/t Al. The high temperatures at the surfaces show that artificial cooling or current density reduction may be required for the sustainable process. It is worth to remark that at the time of the modelling [16], many of the data presented in this paper were not available, and the model may require optimization.

Cell Designs An interesting idea is the development of the commercial cell for the electrolysis of alumina suspensions in oxide– fluoride melts. Mandatory conditions for sustainable cell operation are:

634

A. Yasinskiy et al.

Fig. 11 Schematic representation of the electrode arrangement for alumina suspensions electrolysis: a—Beck and Brooks [7], b—Polyakov, Simakov [15]

From the above information, we can conclude that there are quite a few options for the cell design for the alumina suspensions electrolysis in the scientific and technical literature, but so far they have not even found laboratory use.

Conclusion A significant amount of reproducible data has been obtained in a wide range of experimental conditions to date. Based on the available data, experiments on the alumina suspensions electrolysis in laboratory cells were conducted and the fundamental possibility of aluminium production by this method was shown. The laboratory-scale electrolysis of alumina suspensions in melts based on the NaF–KF–AlF3 system was performed with cathodic CE > 90% and specific energy consumption of 12.8–13.5 kW h/kg Al. The laboratory-scale results displayed that the technology can be operated at the parameters: • anodic and cathodic current densities of 0.1–0.3 A cm−2; • the 10–15 vol% alumina with the average particle size less than 10 lm (mechanical activation seems to be the promising solution); • the 28–32 vol% alumina with SGA (can lead to Ostwald ripening); • electrolyte composition 1.3(KF–NaF)–AlF3 + L iF (optional); • the temperature of 750–800 °C (higher current densities naturally require higher temperature); • continuous removal of electrolysis products from the interelectrode space through porous electrodes; • Cu90Al10 anode (or other with high corrosion resistance);

• the wettable cathode (TiB2–based); • the interelectrode distance of 1.0–2.5 cm (higher current densities naturally require higher spaces). Proper design of the gas–removing electrode and maintaining suspended alumina particles are of high importance. The first one appears to be a challenging problem, whereas the second one can be solved by choosing the proper cell design and the suspension composition, as well as the electrolysis parameters. Mechanical activation seems to be able to provide high resistance towards sedimentation, Ostwald ripening and to increase the dissolution rate. Acknowledgements The reported study was funded by RFBR according to the research project no 19–38–50018.

References 1. Beck Th.R. and Brooks R. (1986) Method and apparatus of electrolytic reduction of alumina, Patent US4592812. 2. Pawlek R.P. (2013) In “Essential readings in light metals: Electrode technology for aluminium production, 4:1126–1133. https://doi.org/10.1002/9781118647745.ch157. 3. Beck Th.R., MacRae C.M., and Wilson N.C. (2011) Metal anode performance in low–Temperature electrolytes for aluminium production, Met. & Mat. Trans. B, 42: 807–813. 4. Kovrov V.A., Khramov A.P., Zaikov Yu.P., Nekrasov V.N., and Ananyev M.V. (2011) Studies on the oxidation rate of metallic inert anodes by measuring the oxygen evolved in low–temperature aluminium electrolysis, J. Appl. Electrochem., 41:1301–1309. 5. DeYoung D.H. (1986) Solubilities of oxides for inert anodes in cryolite–based melts, Light Metals 1986:299–307. 6. Beck Th.R. and Brooks R. (1989) Electrolytic reduction of alumina, Patent US4865701.

Electrolysis of Low-temperature Suspensions: An Update 7. Beck Th.R. and Brooks R. (1991) Electrolytic reduction of alumina, Patent US5006209. 8. Beck Th.R. (1994) Production of aluminium with low temperature fluoride melts, Light Metals 1994:417–423. 9. Beck Th.R. (1995) A non–consumable anode for production of aluminium with low–temperature fluoride melts, Light Metals 1995:355–360. 10. Brown C.W. (2000) Laboratory experiments with low–temperature slurry–electrolyte alumina reduction cells, Light Metals 2000:391– 396. 11. Brown C.W. (1998) The wettability of TiB2–based cathodes in low–temperature slurry–electrolyte reduction cells, JOM, 50(5): 38–40. 12. Welch B.J. (1999) Aluminium production paths in the new millennium, JOM, 51(5):24–28. 13. Tabereaux A. (2007) Aluminium industry upgrade set in motion by new wave of high amperage prebakes, Light Metal Age, 2007: 28–30. 14. Polyakov P.V., Blinov V.A., Voinich A.L., Simakov D.A., and Gusev A.O. (2008) Electrolysis of thickened alumina slurry as a method of Hall–Heroult process update, J. Siberian Federal University. Engineering & Technologies, 2008(1):135–154. 15. Polyakov P.V. and Simakov D.A. (2004) Method of production of metals by electrolysis of the molten salts, Patent RU2274680C2. 16. Polyakov P.V., Klyuchantsev A.B., Yasinskiy A.S., and Popov Y. N. (2016) Conception of “Dream Cell” in aluminium electrolysis, Light Metals 2016:283–288. 17. Thonstad J., Fellner P., Haarberg G.M., Hives J., Kvande H., and Sterten A. (2001) Aluminium electrolysis. Fundamentals of the Hall–Heroult process. 3 ed. Dusseldorf, Aluminium–Verlag Marketing & Kommunikation GmbH, 354 p. 18. Danielik V. (2005) Phase equilibria in the system KF–AlF3– Al2O3, Chemical Papers, 59(2):81–84. 19. Apisarov A., Dedyukhin A., Nikolaeva E., Tinghaev P., Tkacheva O., Redkin A., and Zaikov Y. (2010) Liquidus temperatures of cryolite melts with low cryolite ratio, Light Metals 2010: 395–398. 20. Robert E., Olsen J.E., Danek V., Tixhon E., Ostvold T., and Gilbert B. (1997) Structure and thermodynamics of alkali fluoride– aluminium fluoride–alumina melts. Vapor pressure, solubility, and Raman spectroscopic studies, J. Phys. Chem. B, 101:9447–9457. 21. Apisarov A.P., Dedyukhin A.E., Redkin A.A., Tkacheva O.Yu., and Zaikov Yu.P. (2010) Physicochemical properties of KF–NaF– AlF3 molten electrolytes, Rus. J. Electrochem., 46:633–639. 22. Frazer E.J. and Thonstad J. (2010) Alumina solubility and diffusion coefficient of the dissolved alumina species in low–temperature fluoride electrolytes, Met. & Mat. Trans. B, 41:543–548. 23. Isaeva L.A., Mikhalev Yu.G., Polyakov P.V., and Muratov A.M. (1999) The dissolution rate of alumina with various properties and the temperature responses of the electrolyte, Tsvetnye metally, 1999(10):40–43. 24. Isaeva L.A., Braslavskii A.B., Polyakov P.V. (2009) Effect of the content of the a–phase and granulometric composition on the dissolution rate of alumina in cryolite–alumina melts, Rus. J. Non– Ferrous Metals, 50(6):600–605. 25. Haverkamp R.G., Welch B.J., and Metson J.B. (1992) Models of alumina dissolution in cryolite, Proc. Electrochemical Society, PV 1992–16:646–659. 26. Yasinskiy A.S., Polyakov P.V., Yushkova O.V., and Sigov V.A. (2018) Spatial particle distribution during Stokes sedimentation of alumina in high temperature concentrated suspension–electrolyte for aluminium production, Tsvetnye Metally. 2018(2):45–50. 27. Yasinskiy A.S., Polyakov P.V., Voyshel Y.V., Gilmanshina T.R., Padamata S.K. (2018), Sedimentation behaviour of high–

635

28.

29.

30.

31.

32.

33.

34.

35.

36.

37.

38.

39.

40.

41.

42.

43.

temperature concentrated colloidal suspension based on potassium cryolite, J. Dispersion Sci. & Tech., 39:1492–1501. Kryukovsky V.A., Frolov A.V., Tkatcheva O.Yu., Redkin A.A., Zaikov Yu.P., Khokhlov V.A., and Apisarov A.P. (2006), Electrical conductivity of low melting cryolite melts, Light Metals 2006:409–413. Bakin K.B., Simakova O.N., Polyakov P.V., Mikhalev Yu.G., Simakov D.A., and Gusev A.O. (2011) Electroconductivity slurry– electrolyte of the molten system NaF–AlF3–CaF2–Al2O3, J. Siberian Federal University. Engineering & Technologies, 2011(4):162–169. Vaskova Z., Kontrik M., Mlynarikova J., and Boca M. (2015) Density of low–temperature KF–AlF3 aluminium baths with Al2O3 and AlPO4 additives, Met. & Mat. Trans. B, 46:485–493. Cassayre L., Palau P., Chamelot P., Massot L. (2010) Properties of low–temperature melting electrolytes for the aluminium electrolysis process: A review // J. Chem. Eng. Data, 55:4549–4560. Silny A., Chrenkova M., Danek V., Vasiljev R., Nguyen D.K., and Thonstad J. (2004) Density, viscosity, surface tension, and interfacial tension in the systems NaF(KF) + AlF3, J. Chem. Eng. Data, 49:1542–1545. Thonstad J., Kisza A., and Hives J. (2006) Anode overvoltage on metallic inert anodes in low–melting bath, Light Metals 2006:373– 377. Nekrasov V.N., Limanovskaya O.V., Suzdaltsev A.V., Khramov A.P., and Zaikov Yu.P. (2014) Stationary anodic process at platinum in KF–NaF–AlF3–Al2O3 melts, Rus. Met. (Metally), 2014(8):664–670. Suzdaltsev A.V., Khramov A.P., Kovrov V.A., Limanovskaya O. V., Nekrasov V.N., and Zaikov Yu.P. (2016) Voltammetric and chronopotentiometric study of nonstationary processes at the oxygen–evolving anodes in KF–NaF–AlF3–Al2O3 melt, Mat. Sci. Forum, 844:19–26. Padamata S.K., Yasinskiy A.S., and Polyakov P.V. (2018) Progress of inert anodes in aluminium industry: Review, J. Siberian Federal University. Chemistry, 2018(11):18–30. Nekrasov V.N., Suzdaltsev A.V., Limanovskaya O.V., Khramov A.P., and Zaikov Yu.P. (2012) Theoretical and experimental study of anode process on carbon in KF–AlF3–Al2O3 melts, Electrochimica Acta, 75:296–304. Yasinskiy A.S., Padamata S.K., Polyakov P.V., and Vinogradov O.O. (2019) Anodic process on aluminium bronze in low–temperature cryolite–alumina melts and suspensions, Tsvetnye Metally, 2019(9):37–44. Yasinskiy A.S., Padamata S.K., Polyakov P.V., Samoilo A.S., Suzdaltsev A.V., Nikolaev A.Yu. (2020) Electrochemical behaviour of Cu–Al oxygen–evolving anodes in low–temperature fluoride melts and suspensions, TMS Light metals, https://doi.org/ 10.1007/978-3-030-36408-3_81. Yasinskiy A.S., Vlasov A.A., Polyakov P.V., and Solopov I.V. (2016) Impact of alumina partial density on the process conditions of aluminium reduction from cryolite–alumina slurry parameters, Tsvetnye Metally, 2016(12):33–38. Yasinskiy A.S., Polyakov P.V., and Klyuchantsev A.B. (2017) Motion dynamics of anodic gas in the cryolite melt– alumina high–temperature slurry, Rus. J. Non–Ferrous Metals, 58 (2):109–113. Nikolaev A.Yu., Suzdaltsev A.V., and Zaikov Yu.P. (2019) Cathode process in the KF–AlF3–Al2O3 melts, J. Electrochem. Soc. 166(15):D784–D791. Nikolaev A.Yu., Suzdaltsev A.V., Polyakov P.V., and Zaikov Yu. P. (2017) Cathode process at the electrolysis of KF–AlF3–Al2O3 melts and suspensions, J. Electrochem. Soc., 164(8):H5315– H5321.

636 44. Wei Zh., Peng J., Wang Y., Liu K., Di Yu., and Sun T. (2019) Cathodic process of aluminium deposition in NaF–AlF3– Al2O3 melts with low cryolite ratio, Ionics, 25:1735–1745. 45. Yasinskiy A.S., Padamata S.K., Polyakov P.V., Varyukhin D.Yu. (2019) Electrochemical characterization of the liquid aluminium bipolar electrode for extraction of noble metals from spent catalysts, Non–Ferrous Metals, 2: in press. 46. Simakov D.A. (2006) Studying peculiarities of electrolysis of alumina suspensions in fluoride melts in purpose of improving the

A. Yasinskiy et al. Hall–Heroult process [In Russ], dissertation…cand.sc. Krasnoyarsk. 47. Padamata, S.K.; Yasinskiy, A.S., Polyakov, P.V. (2019) Electrolytes and its additives used in aluminium reduction cell: a review, Metallurgical Research & Technology, 116(4):410. 48. Yasinskiy A.S., Polyakov P.V. (2016) Investigation of bubble behaviour at cryolite melt—alumina slurry electrolysis, J. Siberian Federal University. Engineering & Technologies, 9 (6): 854–871.

Adapting Modern Industrial Operation Parameters in a Standardized Laboratory Cell for Measuring Current Efficiency for Aluminium Deposition: Unexpected Challenges and Lessons Learned R. Meirbekova, O. Awayssa, G. M. Haarberg, and G. Saevarsdottir

Abstract

“Current efficiency” is an important cell parameter which shows how efficiently current is used to produce aluminium. Operational parameters that affect current efficiency have been widely studied in the aluminium industry, and factors like electrolyte composition and superheat have been changed to improve the current efficiency. However, the industrial cell is a complex system where all parameters are closely interrelated, which makes it difficult to change any parameter independently. Sterten and Solli developed a laboratory cell specifically designed to study current efficiency. Many studies have been made using the cell to study the effect of various operational parameters on current efficiency. As a result of improved understanding, the operational parameters presently used by the industry have changed, which is reflected by new operating condition standards for the laboratory cell. This study focuses on the challenges faced when implementing new standards in the current efficiency laboratory cell; these standards (11.5% AlF3, 5% CaF2, 4% Al2O3, cryolite ratio 2.2, temperature 965 °C) are comparable to typical parameters in the aluminium industry today. Keywords

Current efficiency




Alumina reduction

R. Meirbekova (&)
G. Saevarsdottir School of Science and Engineering, Reykjavik University, Menntavegur 1, 101, Reykjavik, Iceland e-mail: [email protected] G. Saevarsdottir e-mail: [email protected] O. Awayssa
G. M. Haarberg Department of Materials Science and Engineering, NTNU, 7491 Trondheim, Norway

Introduction Aluminium is produced industrially in the Hall-Héroult process, an electrochemical process that uses electric current to produce aluminium. The price of electricity is one of the most important cost factors for the process, so the efficiency with which it is used is one of the process’ most important operational parameters. Current efficiency is defined as a percentage derived from the ratio between the actual metal output and the theoretical amount [1]. The theoretical amount is calculated using Faraday’s law shown below: m theory ¼

M It zF

ð1Þ

F is Faraday’s constant (96,485 C mol−1), M is molar mass, z is valence of the product, I is current, and t is time. Current efficiency is the ratio of the actual mass of metal produced and the mass theoretically derived from Faraday’s law [2]: CE% ¼

mactual mtheory

ð2Þ

Today, current efficiency values can reach up to 96% in the industry; but even a reduction in current efficiency as small as 1% can have a significant impact on operational costs. Therefore, the factors that contribute to loss of current efficiency, including small contributors such as impurities have been widely studied in the industry and academia. As the industrial cells are continuously operated, short term trends in current efficiency are not easy to monitor. It is difficult to study the independent effects of different parameters in an industrial cell due to its complexity and because all parameters are closely interrelated. For this reason, most studies of fundamentals are carried out in a laboratory cell. A well known laboratory cell to study current efficiency was developed by Solli [3]. Many studies have been made

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_86

637

638

R. Meirbekova et al.

using the cell, but using old operational standards [3–11]. Meanwhile, the current operational parameters used by the industry have changed. Therefore, new standards that are more comparable to typical parameters used presently by the industry have been adopted for the laboratory studies [7–9]. The recent studies with new standards investigated the effect of various additives on current efficiency. From time to time during the experiments, the shape of the metal pad deviated from the previously expected flat meniscus giving deformed appearance [12]. Any deviation from the flat surface is considered deformed as the flat surface is important for current efficiency studies. The deformation of metal pad has not been reported before using same cell set-up with old standards [3–11]. This study is a part of a bigger project focusing on the effect of titanium dioxide and silicon dioxide on current efficiency [13], where SiO2 and TiO2 additions were made into the electrolyte and the same problems as mentioned above were observed. There was an irregular aluminium deposit surface along with more scatter in measured current efficiency than seen in the same type of experiments on cells using old standards. It is important to study these phenomena to understand the origin of these deviations and whether they have any effect on the estimate of current efficiency. In this study, we ran a set of experiments which gave some insight into the possible mechanisms behind the deformation.

The Experimental Set-up and Methodology The present study used the dedicated laboratory cell design developed by Solli [3] to study current efficiency (see Fig. 1). The main differences between this cell and other experimental cells are its specifically-designed anode and the presence of a steel plate for good wetting of aluminium, as a result giving a flat metal pad. The anode has a vertical central hole and horizontal channels to facilitate convection in the cell. The bottom of the anode has a 10° inclination upwards to the center hole; thus, gas bubbles should rise towards the center hole of the anode and pass out to the sides through horizontal channels. This cell convection plays an important role in mass transport conditions. The increase of convection in the electrolyte Table 1 Comparison between old and new standard conditions

Fig. 1 Current efficiency cell developed by Solli

decreases the diffusion layer thickness, which in return increases the mass transfer rate. The mass transfer of dissolved metal (Al, Na) through the cathode diffusion layer is the rate-determining step in the current efficiency loss [1]. The stainless-steel plate helps to maintain an almost flat cathode shape, and the anode maintains good convective patterns. As a result, cathodic current density should be even and stay constant. This is important for current efficiency studies because current efficiency is sensitive to the cathodic current density. In the absence of the steel plate, the deposited aluminium will not be wetted by the graphite crucible, which may result in a hemispherical or spherical shape of the metal deposit, which may disturb the results due to the decreased current density at the sides of the sphere. The same cell set-up with the electrolyte new operational parameters was used in the experiments. To understand the changed parameters between old and new standards, we have constructed Table 1.

Results and Discussion In the study, TiO2 and SiO2 were added to the electrolyte to observe their effect on current efficiency of aluminium electrolysis. Aluminium samples were deposited, wetting the

Operational parameters

Old standards

New standards

Temperature (°C)

980

965

Current density (A/cm2)

0.8

0.9

Cryolite ratio

2.5

2.2

AlF3 (%)

7

11.5

CaF2 (%)

5

5

Al2O3 (%)

4

4

Adapting Modern Industrial Operation Parameters …

639

Fig. 2 Aluminium deposited on top of steel plate and pin. Spherical shapes are collected from the electrolyte. From left to right: 0.5 wt% Si added into the electrolyte and 0.6% Ti added to the electrolyte

steel plate, but in some cases irregular surface shape occurred. In addition, spherically-shaped aluminium spheres were found (see Fig. 2). One of the possible reasons for the deformed surface might be cooling and solidification of the electrolyte while the metal is still molten. The electrolyte will start cooling from the outside of the cell inwards. As new standards electrolyte composition are further from the cryolite composition than for old standards, more rapid dendrite growth from the sidewalls, leaving a liquid in the center to crystalize last, might contribute to the deformed surface. However, running the experiment with initial metal addition, using the same experimental conditions as in new standards, but without electrolysis, showed no deformation of the surface after cooling. The experimental result is shown in Fig. 3. The absence of deformation indicates that the deformed surface shape is a result of mechanisms related to the electrolysis process. This observation is of consequence because

Fig. 3 Aluminium collected from the experiment where aluminium was added before the experiment, using new experimental conditions but without electrolysis

it is important to obtain a flat surface during experiments as it will affect the current efficiency results. To eliminate the spheres, we ran some experiments without the addition of alumina during the electrolysis. Since the experiments were carried at a lower temperature compared to the studies using old standards, alumina might not be completely dissolved and may precipitate below aluminium and therefore affect the wetting. This could, in turn, create spherical balls in the electrolyte, though a similar electrolyte composition at 950 °C (in current study, the operating temperature is 965 °C) can dissolve up to 6.6% of alumina [14, 15]. As the electrolyte contains 4 wt% alumina at the beginning of the experiment and the inside lining of the cell is made of alumina, there should be enough alumina for the electrolysis without feeding. Several studies have concluded that the alumina concentration did not affect current efficiency [2, 3], but one study, in contrast, reported that low concentrations were beneficial in increasing current efficiency [16]. We also implemented a longer duration (running the test for 5 h instead of the 4 h of our prior test). The assumption was that if we have more mass of aluminium then we should be able to deposit it uniformly. After these changes, the separate spheres were not formed; however, deformation in aluminium surface continued. The most probable explanation for the observed deformation is that cryolite may precipitate during electrolysis rather than alumina. The electrolyte will be higher in NaF at the interface and thus increase the liquidus temperature. It was observed after electrolysis with new standards on some of the deformed metal surfaces, that it was not clean metal but seemed to be mixed with electrolyte or oxide. It is known that as Na+ is the main charge carrier in the cathode boundary layer (as well as the electrolyte bulk), and as the aluminium containing anions are consumed, the layer is enriched in NaF compared to the bulk, which leads to a locally higher CR and thus a higher liquidus [1]. This may result in the following chain of events: A higher liquidus can cause a partial solidification of the layer. This interrupts the electrolysis in that area, leading to the charge transfer being pushed towards the warmer more central regions of the metal pad. Next, the metal pad winds up being thicker in the center

640

with a thinner deposit towards the sides of the cell. This NaF enrichment is further enhanced by increasing current density from 0.8 to 0.9 A/cm2 with new standards. In order to test this hypothesis, some experiments were run with a higher superheat (the difference between operating and liquidus temperature), in an attempt to prevent the freezing of the boundary layer. The cell temperature was increased while keeping the electrolyte composition unaltered; thus, the superheat was increased by 5° (from 13 to 18 °C), for a given electrolyte composition [17]. In addition, increased superheat should improve alumina dissolution. We should note that the experiments with old standards were done at 11–12 °C superheat. Despite the increase in superheat, deformation in aluminium surface continued (see Fig. 4); however no separate spheres were found. It might be that the addition of TiO2 lowered the liquidus temperature of the electrolyte [1], preventing the separation of the spheres. The density of electrolyte and the surface tension between aluminium and the electrolyte influence the separation of the Fig. 4 Aluminium samples collected from TiO2 addition experiments. a 0.2% Ti, b 0.2% Ti c 0.6% Ti and d 1% Ti

R. Meirbekova et al.

liquid aluminium from the electrolyte. The lower the operating temperature, the higher the density of the electrolyte. The lower the operating temperature, the higher the surface tension between the electrolyte and aluminium [18]. For the present study at the given electrolyte composition (11.5% AlF3, 5% CaF2, and 4% Al2O3), the electrolyte density should be 2.08 g/cm3 [17] which is only slightly lower than that of old standards (2.10 g/cm3) [3]. It is unclear why in implementing new standards we observed a reverse effect where the buoyancy of the aluminium was affected. However, suspension of aluminium with electrolyte was also observed in the industry during a 1.5 h power outage as reported earlier [6]. The temperature of the electrolyte in that event dropped about 31 °C. To find out if the deformation was related to additions of TiO2, we ran some blank tests. The experiments had the same electrolyte composition and were run at the same current density of 0.9 A/cm2. The results are shown in Fig. 5 and their estimated current efficiencies are shown in Table 2.

Adapting Modern Industrial Operation Parameters …

641

Fig. 5 Aluminium deposited on top of stainless steel plate in the experiments without any impurity additions. Numbers refer to the experiments shown in Table 2

Table 2 Summary of the blank experiments obtained at 11.5% AlF3, 5% CaF2 and 4% Al2O3, 965–970 °C and at 0.9 A/cm2

No.

T (°C)

Alumina

Duration (h)

Current efficiency (%)

Deformation

1

965

Yes

4

94.1

Yes

2

965

Yes

4

95.7

No

3

965

Yes

5

94.6

No

4

965

No

5

91.4

Yes

5

970

No

5

90.5

No

6

970

No

4

89.1

Yes

The current paper is restricted to reporting the current efficiencies obtained without any addition of impurities. Some of the tests were run without adding alumina, longer durations, and higher operating temperatures. As can be seen from Fig. 5, deformation also occurred in the blank tests. It suggests that the origin is the change to new standards rather than the oxide impurities. The current efficiency results also show significant scatter. If we correct current efficiency for the temperature decrease from 965 to 970 °C according to the literature [1], for 5° we should add 1% (0.2% increase in current efficiency per °C) and the standard deviation between experiments can be found to be 2.3%. To compare this value to the works using old standards, we constructed Table 3. As most common experiments performed by studies using old standards operated at a current density of 0.8 A/cm2, we could look at standard deviations between experiments. We considered experimental results from different authors to increase the number of experiments. There might be some change in material properties from different suppliers and variations due to different persons running the experiments. Despite that

variability, the standard deviation for the works using old standards is comparatively low, 0.8%. By constructing a current efficiency versus current density plot from the works using old standards [3–11], we can Table 3 Current efficiencies obtained by old standards at 6.75% AlF3, 5% CaF2 and 4% Al2O3, 980 °C and 0.8 A/cm2 Literature

Current efficiency (%)

[6]

91.4 93.4 93.0

[3]

93.3 93.0 92.8

[10]

92.1 92.7 92.2

[11]

92.0 91.5 91.1

642

R. Meirbekova et al.

Fig. 6 Current efficiency versus current density constructed using old standards

97 96

Current efficiency, %

95 94 93 y = 4.86x + 88.40 R² = 0.80

92 91 90 89 88

87 0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Current density, A/cm2 estimate the expected value for current efficiency for new standards (see Fig. 6). According to the given linear equation, expected current efficiency at 0.9 A/cm2 is 92.8%, and considering temperature effects according to [1], and increased AlF3%, the expected current efficiency should be in the range of 96– 97%. As mentioned above alumina concentration should not affect current efficiency. Therefore, it is not clear why current efficiencies without the addition of alumina during the process have lower current efficiencies, as observed in Table 2. However, if we look at the pictures (Fig. 5) we can see that some experiments have deformed shapes that could have affected the results. Observed deformation of the metal pad is worse in blank experiments compared to TiO2 addition experiments. As mentioned previously, the deformation may be diminished due to TiO2 lowering the liquidus temperature of the electrolyte. Therefore, the observation of deformation is most likely due to the change in electrolyte composition and operating temperature, and not due to impurity additions. Working at increased current density with new standards may also enhance the enrichment of NaF in the cathode boundary layer.

Conclusions Experiments in the standardized current efficiency cell, applying new standard conditions in compliance with industry standards, showed that the metal shape deformation observed was not related to the addition of the impurities but

due to changing to new industry standards for both composition and temperature. The most likely cause is the raising of the liquidus in the cathode boundary layer from the NaF enrichment associated with charge transfer and higher current density, which may cause partial freezing interrupting the charge transfer and, therefore, deposition. The observed deformation happens during electrolysis; therefore, they affect obtained results and should be further investigated. Acknowledgements This work was financed by the Icelandic Technology development fund. We thank Aksel Alstad at NTNU for the fabrication of experimental parts for the furnace. A huge thank you Asbjørn Solheim at SINTEF for the discussions. Also, thanks are due to Guðjón Atli Auðunsson, Jón Matthíasson and Birgir Jóhannesson at Innovation Center Iceland and Cari Covel from Reykjavik University for their contributions. Special thanks to Christopher Alexander Mathews for proofreading the article.

References 1. Thonstad, J., Fellner, P., Haarberg, G.M., Hives, J., Kvande, H., and Sterten, Å. (2001) Aluminium electrolysis 3rd edition ed., Breuerdruck, Germany: Aluminium-Verlag Marketing & Kommunikation GmbH 2. Grjotheim K. and Kvande H. (1993) Introduction to aluminium electrolysis, Aluminium-Verlag GmbH, Düsseldorf, Germany 3. Solli P.A. (1993) Current efficiency in aluminium electrolysis cell, Ph.D. thesis, NTNU 4. Sterten Å., Solli P. A., & Skybakmoen E. (1998) Influence of electrolyte impurities on current efficiency in aluminium electrolysis cells, J. of Applied Electrochem., 28(8), p 781–789 5. Meirbekova, R., Haarberg, G. M., Thonstad, J., & Saevarsdottir, G. (2016) Influence of sulfur species on current efficiency in the

Adapting Modern Industrial Operation Parameters …

6. 7.

8.

9.

10.

11. 12.

aluminium smelting process. Metallurgical and Materials Transactions B, 47(2), p 1309–1314 Meirbekova, R. (2016) Impurities and current efficiency in aluminium electrolysis. Ph. D. thesis, NTNU Meirbekova, R., Haarberg, G. M., Thonstad, J., & Saevarsdottir, G. (2017). Influence of phosphorus on current Efficiency in Aluminium Electrolysis at Different Current Densities. Journal of The Electrochemical Society, 164(7), E161–E165 Meirbekova, R., Thonstad, J., Haarberg, G. M., & Saevarsdottir, G. (2014) Effect of current density and phosphorus species on current efficiency in aluminium electrolysis at high current densities. In Light Metals 2014, The Minerals, Metals & Materials Society, Pittsburgh, Springer, Cham., p 759–764 Armoo, J. P. (2010). The current efficiency for aluminium deposition from cryolite alumina melts at high current density. MSc. Thesis. NTNU Cui, P., Qin, B., & Haarberg, G. M. (2019). The behavior of additives LiF, MgF2 and KF on current efficiency in aluminium electrolysis. Journal of The Electrochemical Society, 166(13), D559–D563 Thisted E.W. (2003) Electrochemical properties of phosphorus compounds in fluoride melts cells. Ph.D. thesis. NTNU Silva, P. (2017) The performance change of aluminium electrolysis in standard cryolite electrolyte with cathodic current density. MSc thesis. NTNU

643 13. Awayssa, O., Meirbekova, R., Saevarsdottir, G., Audunsson, G. A., Haarberg, G. M. (2020), Current efficiency for direct production of an aluminium- titanium alloy by electrolysis in a laboratory cell. In Light Metals, The Minerals, Metals & Materials Society, Pittsburgh, Springer, New York 14. Dewing, E. W. (1970). Liquidus curves for aluminium cell electrolyte V. Representation by regression equations. Journal of The Electrochemical Society, 117(6), p 780–781 15. Skybakmoen, E., Solheim, A., & Sterten, Å. (1997). Alumina solubility in molten salt systems of interest for aluminium electrolysis and related phase diagram data. Metallurgical and materials transactions B, 28(1), p 81–86 16. Tarcy, G. P. (1995, October). Strategies for maximizing current efficiency in commercial Hall-Heroult cells. In Fifth Australian Aluminium Smelting Technology Workshop, p 22–27 17. Solheim, A., Rolseth, S., Skybakmoen, E., Støen, L., Sterten, Å., & Støre, T. (1996). Liquidus temperatures for primary crystallization of cryolite in molten salt systems of interest for aluminium electrolysis. Metallurgical and Materials Transactions B, 27(5), p 739 18. Fernandez, R., & Ostvold, T. (1989). Surface-tension and density of molten fluorides and fluoride mixtures containing cryolite. Acta Chemica Scandinavica, 43(2), p 151–159

Aluminium Smelter Crust—Phase Distribution and Structure Analysis of Top Zone Layer Shanghai Wei, Jingjing Liu, George Allan, Tania Groutso, John J. J. Chen, and Mark P. Taylor

Abstract

Anode cover material (ACM) partly fuses at the bottom where it interacts with anode and bath in the aluminium reduction cell. This consolidated material is defined as the top crust in the cell, and plays a crucial role in maintaining heat balance, protecting the carbon anode from air-burning and absorbing the fluorides evaporation in the cells. Previous studies have been conducted to illustrate the crust formation and properties. However, there is rarely a systematic structural analysis of crust in the vertical direction due to the complexity and inhomogeneity of industrial crust. In the present study, the phase composition of crust was systematically analysed in the vertical direction, and five zones were identified based on the phase composition. Furthermore, two types of particles are identified in top zone (1) namely: smelter grade alumina (SGA) and crushed bath particles (CBPs). A systematic analysis on CBPs have shown four types of structural features.





Keywords

Structure materials

Aluminium smelting Crust




Anode cover

S. Wei (&)
J. Liu
G. Allan
J. J. J. Chen
M. P. Taylor Department of Chemical & Materials Engineering, University of Auckland, Auckland, New Zealand e-mail: [email protected] S. Wei
J. Liu
M. P. Taylor NZ Product Accelerator, Faculty of Engineering, University of Auckland, Auckland, New Zealand T. Groutso Department of Chemistry, Faculty of Science, University of Auckland, Auckland, New Zealand T. Groutso Light Metal Research Centre, Department of Chemical & Materials Engineering, University of Auckland, Auckland, New Zealand

Introduction The aluminium smelting process is a highly energy intensive process. A typical aluminium smelter consists of many cells/pots connected in series to form potlines. The potlines operate at very high amperages (up to 500 KA) to keep the molten electrolyte in the range of 930–970 °C to dissolve alumina [1–8]. However, about 50% of electrical energy input is lost as heat flux to the surroundings from the top, the side and the bottom of cell, as shown in Fig. 1. The heat loss from the top of the cell accounting for the largest (*50%) heat loss. Bulk granular anode cover materials (ACM) are used to protect anodes from air burn and control top heat balance. The raw ACM progressively undergoes complex reactions which vary with distance above the molten bath. The ACM closest to the bath becomes fused and consolidated, which is known as “crust”. The crust and the loose cover materials above, as shown in Fig. 1, are replaced after about 25– 30 days anode operation. Taylor [9] reviewed the development of ACM since the 1950s, and categorized the top cell cover into three periods: 1950–1970 Alumina-based crust, 1970–1990 alumina-based crust with feeding crushed bath; and 1990–2007 crushed bath-based crust. The raw ACM has been changed from being alumina-based to a mixture of crushed bath and alumina based materials [3, 4, 9, 10]. Modern crushed bath is a blend of recycled materials from the cleaning of anode butts, metal crucibles, basement cleanings and failed cells etc. Early researchers have systematically studied the formation mechanism and properties of alumina based crust in laboratory cells since the 1970s. These studies showed that the crusting behaviour depended on the alumina type [11– 21]. Liu et al. [22] first studied the formation and deterioration of crust made from secondary alumina and also from a mixture of ACM with 50% crushed bath and 50% alumina, and concluded that liquefaction and melting of crust is a major cause of crust deterioration in both cases. Since then, a few researchers have studied the crust formation mechanism

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_87

644

Aluminium Smelter Crust—Phase Distribution and Structure …

645

Fig. 1 Schematic cross section view of modern aluminium reduction cell showing the main components of cells including ACM and crust, and also the heat loss from top, side and bottom of cells [1, 3]

(b)

of modern crushed bath based ACM, including its thermochemical behaviour and stability [4, 23–32], and the effects on cell energy balance [3]. However, none of these studies were concerned with the structure of the crust, and in particular the relationship among temperature gradient, phase composition, the structure and the crusting behaviour. Liu et al. [33] recently observed that understanding the structure of crust could provide a new insight into its formation and behaviour. Crust failure problems may also be explained. In this present study, a systematic analysis on industrial crust samples has been conducted to examine the phase composition and structure of crust from the top to the bottom. We will characterise the representative structure of the upper-most layer of the crust referred to as Zone 1 in this paper. This will be the starting point for understanding the structure of the lower zones, and the microstructure evolution in ‘full’ industrial crust.

Experimental Methodology Sample Preparation Large crust pieces were initially collected from six industrial cells (AP 30 technology) during scheduled anode change.

(a)

All crusts were removed after the anodes scheduled 27 days cycle. The raw ACM was made of *33% Al2O3 and *66% crushed, recycled cover (*45% chiolite and *20% cryolite) from the anode rodding operations. The particle size distribution is about 80% in 150 µm. These large crust pieces were indexed to document their positions in the industrial cells. One set of crust pieces was selected for current study. Figure 2 shows this typical ‘full’ crust section sampled from between the sidewall and the side of the anode, viewing from top (a), bottom (b) and side elevation of the crust (c), respectively. The complete crust sample has been fractured into 7 pieces, but they has been re-assembled as a block according to the representative pattern on the fracture surface. The width and length of the whole crust sample are 32 and 21 cm. The top and bottom of crust can be easily determined visually. Due to the apparent inhomogeneity of the material [34], sampling from industrial crust pieces is a major challenge. Extra care was exercised in identifying representative samples [35]. These representative crust pieces were then cut into vertical slices using a concrete diamond saw. Macroscopic examination of the crust pieces reveals a layered structure, denoted here as zone 1 to zone 5 from top to bottom of the crust, as shown in Fig. 2c. The bottom of the

646 Fig. 2 Top view (a) and bottom view (b) of crust pieces, (c) cross-section view of crust showing a layered structure with defined zones and the sampling location in an industrial cell

S. Wei et al.

(b)

(a)

21cm 32cm

Crust pieces

(c)

crust is closest to bath, while the top of the crust is loosely consolidated materials.

Microscopy (TEM) analysis was also conducted on a FEI Tecnai F20 operating at 200 kV. For the TEM analysis, a small amount of zone 1 crust samples only were placed on a copper grid coated with a thin amorphous carbon film.

Materials Characterisation Phase analysis was conducted with using X-ray diffractometer (XRD), and quantitative phase analysis was determined by the Rietveld Refinement method. HighScore Plus software was used to identify the phases present and perform Rietveld Refinement [36]. XRD analysis was performed by Rigaku Ultima IC XRD operating at 40 kV and 30 mA Cu X-rays with 2h scanning range from 20° to 80°. Crust samples were ground into fine power samples with using a mortar and pestle. Cross sections of the crust samples were mounted in epoxy resin, then ground and polished for microstructure characterisation and microanalysis. Microstructure analysis was carried out using optical microscopy (OM) and scanning electron microscopy (SEM). The SEM analysis was conducted on both FEI Quanta 200FEG SEM and Philips XL30SFEG SEM. Energy dispersive spectroscopy (EDS) was used to analyse the elemental composition of the samples. SEM samples were coated in platinum with the Plaron SC7640 Sputter Coater. Transmission Electron

Results and Discussion Phase Analysis in the Vertical Direction Three ground samples collected from each zone of the crust were analysed for phase structure. These three ground samples were taken from various locations which were used to obtain a satisfactory sampling size. In total, six crystal phases have been identified in the crust samples. Chiolite, Cryolite and a–Al2O3 are the three major phases, and a very small amount of AlF3, calcium cryolite (Na2Ca3Al2F14) and anhydrite (CaSO4) have also been found in certain zones of the crust. These phases have been reported in other industrial crust samples [4, 24, 27, 31]. Minority phases, transition alumina and CaF2, have been identified in Groutso et al. [27] and Allard et al. [31] study but not in the present investigation. Quantitative analysis was conducted on each of XRD results obtained, and the composition of each phase is

Aluminium Smelter Crust—Phase Distribution and Structure … Table 1 Phase concentration in crust samples

Zone

647

Phase concentration wt% Chiolite

a–Al2O3

Cryolite

AlF3

Na2Ca3Al2F14

CaSO4

1

68.5–78.2

0.2–1.1

17.7–31.5

1.6–2.2

–

2.3–3.8

2

71.1–75.9

0.1

22.9–28.9

1.1–1.2

–

–

3

57.3–65.6

10.7–22.5

20.2–23.7

–

–

–

4

37.6–51.8

24.4–38.2

21.8–24.2

–

0.7–1.0

–

5

14–17.8

38.7–58.4

23.6–40.1

–

2.7–5.2

–

summarised in Table 1. It can be seen that phase content varies between the zones, and also within the same zone. Table 1 nevertheless shows a clear trend of changing chiolite and cryolite contents in the vertical direction. The average phase concentrations and their standard deviation in the different zones are shown in Fig. 3. A typical temperature profile of industrial crust has been reported by Liu et al. [22]. This was reproduced as a temperature profile from the bottom of the crust to the top, in Fig. 3 for comparison. Chiolite and a–Al2O3 are the two main phases in zone 1, with average concentration 75.2 ± 3.3 wt% and 23 ± 4.3 wt%, respectively. Three minor crystal phases: cryolite, AlF3 and anhydrite (CaSO4); have also been identified with average content 0.7 wt%, 1.9 wt% and 3 wt%, respectively. The phase composition in zone 2 is close to that in zone 1, mainly chiolite and a–Al2O3 phase with minor cryolite and AlF3 content. However, the zone regions below this level in the crust show a profound change in phase composition. In zone 3, chiolite and a–Al2O3 are still the main phases, but cryolite is becoming more prominent. The average percentage of cryolite phase increases from 0.1 to 16 wt%, while the concentration of main phase chiolite decreases from 73.3 ± 2.0 to 62.4 ± 3.7 wt%. Another interesting phenomena in this zone is that no other minor phases, such as AlF3 and calcium cryolite, have been identified. Closer to the bottom of the crust, chiolite concentration continues to decrease from the average percentage of 62.4 ± 3.7 wt% in zone 3 to 43.6 ± 6 wt% in zone 4, while the percentage of cryolite phase dramatically increases from 16 ± 4.9 wt% in zone 3 to 33.1 ± 6.2 wt% in zone 4. In the bottom of the crust—zone 5, cryolite becomes the majority phase with highest concentration 46.7 ± 8.4 wt%, a–Al2O3 is the second highest phase 33.8 ± 7.3 wt% and chiolite only has 15.7 ± 1.6 wt%—which is approximately the same chiolite content as in the molten bath below the crust. Furthermore, both AlF3 and anhydrite (CaSO4) minor phases have not been identified in the zone 3, 4 and 5 samples, but calcium cryolite phase has been found in zone 4 and 5 samples. The concentration of calcium cryolite increases from about 1 wt% to 3.8 wt% in zone 5.

As stated in section “Sample Preparation”, six boxes of large crust pieces were initially collected from six industrial cells. Phase distribution and structure analysis on two large crust pieces, which were from two different cells, have been conducted. The phase composition varied with different cells in each zones, but the trend of changing chiolite, cryolite and corundum contents in the vertical direction is similar to present study.

Typical Structure in Top Zone—Zone 1 Crust samples from industrial cells are inhomogeneous with voids, cracks and non-uniform distribution of phases and microstructure [16]. It is very challenging to represent the complex structure of industrial crust samples, and this is consistent with our investigation. In this paper, we shall attempt to identify the representative features of the microstructure in the top layer—zone 1, since these structures are the starting point for the temperature-time transformation (TTT) undergone by zones 2–5, leading to the structures seen there. The general features of the five zones in these and other crust samples have been summarised in our previous paper [33]. The OM and SEM images in that study show that the structure of zone 1 is very powdery, and it experienced the lowest temperature exposure within the crust. Thus, we hypothesis that there is no, or very limited, phase transformation and microstructure evolution in this zone. Accordingly it has been possible to identify the representative structural features of the constituent ACM materials in zone 1. Once the representative features in Zone 1 are clear, it should then be possible to identify the features in the other zones as TTT products of the zone 1 structures. The structure evolution and phase transformation in the rest of crust during the anode life cycle can then be hypothesised. The particles observed in zone 1 are categorised into two main types: crushed bath particles (CBPs) and smelter grade alumina (SGA). As shown in OM and SEM images in Fig. 4, most of the crushed bath particles are not bonded together and there is no obvious linkage to SGA particles

648

S. Wei et al.

Fig. 3 Schematic diagram showing multi-layered crust samples and their average phase concentration along the simulated temperature gradient in the industrial cell

Fig. 4 OM and SEM images of crust samples from zone 1

either. In addition, they exhibit different size distribution and morphologies. The size of SGA is 50–150 lm, while the size of crushed bath particles shows a much wider distribution from *50 lm to *3 mm. Figure 5a, b show typical cross-sectioned morphology of SGA grains at low and high magnification. These are consistent with Wijayaratne et al. [37] and Perander et al. [38] investigations

of SGA grains in secondary alumina. The EDS result in Fig. 6a shows the atomic percentage of aluminium and oxygen elements which confirms the SGA phase. These SGA phases have not been identified by the XRD analyses because SGAs are amorphous or semi-crystalline lacking long-range order [38]. Four typical crushed bath particles have been identified after a wide systematic microstructural analysis in zone 1.

Aluminium Smelter Crust—Phase Distribution and Structure … Fig. 5 SEM images shows the typical cross-section morphology of SGA particles in zone 1

(a)

The morphology and phase structure of these four typical crushed bath particles are shown in Fig. 6: • Type I—chiolite combined with small a–alumina platelets and large SGA particles (chiolite + a– Al2O3 + SGA), • Type II—chiolite combined with large SGA particles (chiolite + SGA), • Type III—cryolite with small calcium cryolite inclusions (cryolite + calcium cryolite), • Type IV—a large amount of a-alumina platelets which encompassed by the boundary of calcium cryolite linked to chiolite (a–Al2O3 + calcium cryolite + chiolite). Chiolite is the main phase in first two types of crushed bath particles, while cryolite is the main phase in type III CBP and a–Al2O3 is the main phase in type IV CBP. It can be seen from Fig. 6 SEM images that chiolite grains have a clean and smooth surface with randomly distributed micro-cracks, while a–Al2O3 shows a typical platelet morphology, and calcium cryolite shows irregular morphology with different contrast which can be easily identified using the back scattered SEM technique. EDS point and line analyses have been used to illustrate the elemental composition of these phases. The representative structural features and the phases of four typical crushed bath particles in zone 1 crust samples are summarised in the Table 2. Furthermore, nano-size fume particles have been observed around large chiolite grains with using bright field TEM and SAED techniques as shown in Fig. 7.

Impact on Pot Operation The crust ‘layer’ phase composition, structure and properties will have an impact on the heat transfer itself and ultimately on the performance of pot operation. In principle, we believe a smart composition and structure controlled Crust/ACM will be sealing against fluoride emissions release, reduction of the heat loss through a high crust integrity to the thermal

649

(b)

conduction minimum and ease of fracture from the cooled anode butts for recycling. These goals are in general not achieved by the present crust system today. At present we have evidence that the colliding transfer processes lead to a multi-layered crust, the bottom of which is dominated by cryolite from the bath (zones 4 and 5), the middle by chiolite and corundum from the remaining fractional crystallisation of the bath (zones 2 and 3), and the top by corundum and untransformed crushed bath but with AlF3 and other volatilisation products from the bath below (zone 1). It has been observed that this layering is also sidewall/anode position dependent (i.e. varying between the anode and the sidewall) and the hypothesis is that this is a function of the horizontal temperature gradient across this space. At or near the top of the crust (e.g. zone 2), it is evident that a super-tough agglomerated structure of corundum and chiolite can be produced where chiolite is still molten and is able to mineralize and combine with the alumina platelets. This occurs particularly if sufficient heat is unable to be conducted out of the top of the cover—driving internal temperature up and encouraging chiolite to remain liquid, and if the content of blended alumina is high enough (greater than 30% from our earlier studies). Such a structure leads to substantial problems with crust recycling in the smelter due to its ability to resist fracture propagation—the so called ‘hard bath’ problem. Near the bottom of the crust (e.g. zone 4/5) a thermally unstable situation can occur due to an excess of liquid phase. The crust in this location then melts and hollows out rapidly from the bottom causing crust collapse in some cases. This has been observed to occur mainly when there is an excessive content of chiolite in the crust layers plus finer (*200 µ) granulometry in the anode cover which prevents heat transmission from the top of the cover. The layered structure of the crust shows that the microstructure and composition are obviously different from the bottom to the top of the crust. This is due to heat treatment of the crust material by the liquid bath penetrating into the solidified crust at the bottom (zones 5–3) and also by the

650 Fig. 6 SEM images and EDS results showing four different crushed bath particles in zone 1 crust samples. a and b type I crushed bath particle, c Type II crushed bath particles, d and e Type III crushed bath particles, f and g Type IV crushed bath particles

S. Wei et al.

Type I: Chiolite + α-Al2O3 + SGA

Type II: Chiolite + SGA

Chiolite + α-Al2O3 platelets

(a)

(c)

(b)

SGA particles Element O F Na Al

Type III: cryolite + calcium cryolite

Chiolite

at.% 45.14 1.07 0.88 52.91

Element F Na Al Ca

(e)

(d)

Element F Na Al Ca

at.% 52.76 18.56 18.46 9.05

at.% 44.31 37.43 17.39 0.31

Type IV: α-Al2O3 + calcium cryolite + chiolite

(f) chiolite

(g)

α-Al2O3 Calcium cryolite along boundary

evaporation of the liquid to the top sintered layer (zone 1). The fractional crystallization of liquid bath causes a higher concentration of the chiolite in the crust which is then recycled to cause a potential increase of the chiolite content in the ACM, which is a mixture of the crushed crust and other recycled bath streams.

Phase transformation of the blended alumina in the ACM to a-alumina platelets and their interlocking with chiolite and/or cryolite, with effects on the crust stability and hardness, still needs further investigation, as does the effect of the initial ACM bath composition and particle size distribution. Efforts to re-design of the ACM and formation of a more

Aluminium Smelter Crust—Phase Distribution and Structure … Table 2 Main phases and structure features in zone 1 crust samples

651

Representative structure

Phases

Main structure features (MF)

Abbreviation

Type I crushed bath particles (CBPs)

chiolite, a– Al2O3, and SGA

(a) Granular SGA particles surrounded with chiolite phases;

MF-I-(a)

(b) a–Al2O3 platelets encompassed as irregular circular shape in chiolite phases

MF-I-(b)

(c) Granular SGA particles next to a–Al2O3 platelets

MF-I-(c)

Type II CBPs

Chiolite, SGA

(a) Same as feature MF-I-(a) in Type I CBPs

Type III CBPs

cryolite, calcium cryolite

(a) Cryolite phase with irregular calcium cryolite

MF-III-(a)

Type IV CBPs

a–Al2O3, chiolite, calcium cryolite

(a) A large amount of a–Al2O3 platelets encompassed as irregular shape by the boundary of calcium cryolite

MF-IV-(a)

(b) Same as feature MF-I-(b) in Type I CBP

material just above the molten electrolyte bath, and has only 15.7 ± 1.6 wt% of chiolite but 46.7 ± 8.4 wt% of cryolite. A systematic structure analysis has been performed to understand the changing structural features as the bottom of the crust is approached. Industrial crust samples are inhomogeneous, and it is a major challenge to observe of all the representative structural features in these five zones. In this paper, we have focused on the top of the crust—zone 1, because it represents the ACM materials before any significant liquefaction and melting occurred. There are two types of particles in zone 1: SGA and CBPs. Four types of representative structural features of CBPs have been identified here. Each type of CBP shows very different phase concentration and structural features. When these four types CBPs and SGA meet with each other, it gives rise to numerous possibilities of structural features in zones 2–5, which will be studied further in the future. Fig. 7 Bright field-TEM image and SAED showing the typical nano-size fume particles around large chiolite particles

Acknowledgements MBIE funding is gratefully acknowledged for this work, under Grant UOAX 1309. The authors would like to thank generous support from our smelter partner.

stable crust for smelters will follow. This may be especially important for cells which operate at very low bath temperatures.

References

Conclusion A systematic phase analysis has been conducted on industrial crust samples. Five zones have been identified and their phase distribution from top to bottom of the crust has been revealed in the present study. The upper-most, Zone 1 shows very high concentration of chiolite phases 75.2 ± 3.3 wt%. This concentration decreases as the bottom of crust is approached. The bottom of the crust, zone 5, is the crust

1. K. Grjotheim and B.J. Welch, Aluminium Smelter Technology (second edition), 1988, Aluminium-Verlag. 2. H. Kvande and P.A. Drablos, The Aluminum smelting process and innovative alternative technologies, JOEM, 56(2014) s23–s32. 3. X. Shen, Top cover and energy balance in Hall-Heroult cell, PhD thesis, University of Auckland, 2004. 4. Q. Zhang, Thermochemical Behaviour and Stability of Aluminium Smelter Crust, Auckland: University of Auckland, 2015. 5. J.N. Bruggeman, Pot heat balance fundamentals. 6th Australasian Aluminium Smelting Technology Conference and Workshop, 1998: pp. 167–190. 6. W. Haupin, Interpreting the components of cell voltage. Light Metals, 1998: pp. 531–537.

652 7. W. Haupin, and H. Kvande, Thermodynamics of electrochemical reduction of alumina. Light Metals, 2000: pp. 379–384. 8. M.P. Taylor, Challenges in optimising and controlling the electrolyte in aluminium smelters. In Molten Slags, Fluxes and Salts’97 Conference. 1997. 9. M.P. Taylor, Anode cover materials—Science, practice and future needs, Proceedings of 9th Australasian Aluminium smelting technology conference, 2007. 10. S. Wilkening, P. Reny, and B. Murphy, Anode cover material and bath level control. Light Metals, 2005: pp. 367–372. 11. L.N. Less, The crusting behaviour of smelter alumina, Met. Trans., 8B, 1977, pp. 219–225. 12. A.R. Johnson, Alumina Crusting and Dissolution in Molten Electrolyte, Journal of Metals, 1982, pp. 63–68. 13. T.J. Johnston and N.E. Richards, Correlation between alumina properties and crusts. Journal of Metals, 1983: pp. 48–52. 14. D.W. Townsend and L.G. Boxall, Crusting behaviour of smelter aluminas. Light Metals, 1984: pp. 613–621. 15. R. Oedegard, S. Roenning, S. Rolseth and J. Thonstad, Crust formation in Aluminium cells, Journal of Metals, (1985) 25–28. 16. R. Oedegard, S. Roenning, S. Rolseth and J. Thonstad, On alumina phase transformation and crust formation in aluminium cells. Light Metals, (1985) 695–709. 17. G. Hatem, M. Llavona, T. Log, J.P. Sancho and T. Ostvold: Thermal conductivity of some of alumina powders and synthetic Hall-Heroult crust, Light Metals, AIME, 1989, pp. 365–370. 18. M.A. Llavona, L.F. Verdeja, R. Zapico, F. Alvarez, J.P. Sancho, Density, hardness and thermal conductivity of hall-heroult crusts, Light Metals, (1990) 429–437. 19. T. Eggen, S. Rolseth, K.A. Rye, and J. Thonstad, Alumina crusting in cryolitic melts. Part I: Penetration of molten electrolyte into alumina. Light Metals, 1992: pp. 495–502. 20. K.A. Rye, Alumina crusting in cryolitic melts. Part II: Bulk properties of crust. Light Metals, 1992: pp. 503–509. 21. K.A. Rye, J. Thonstad and X. Liu, Heat transfer, thermal conductivity, and emissivity of Hall-Heroult top crust, Light Metals, (1995) 441–449. 22. X. Liu, M. Taylor, and S. George, Crust formation and deterioration in industrial cells. Light Metals, 1992: pp. 489–494. 23. M.P. Taylor, G.L. Johnson, E.W. Andrews and B.J. Welch, Impact of anode cover control and anode assembly design on reduction cell performance, Light Metals, (2004) 199–206. 24. Q. Zhang, M.P. Taylor, J.J. Chen, D. Cotton, T. Groutzo, X. Yang, Composition and Thermal Analysis of Crust Formed from Industrial Anode Cover, Light Metals 2013. pp. 675–680.

S. Wei et al. 25. Q. Zhang, M.P. Taylor, and J.J. Chen, The Melting Behaviour of Aluminium Smelter Crust, Light Metals 2014. pp. 591–596. 26. Q. Zhang, M.P. Taylor, and J.J. Chen, Computational Modeling of Thermochemical Evolution of Aluminum Smelter Crust. Metallurgical and Materials Transactions B, 2015. 46(3): pp. 1520– 1534. 27. T. Groutso, M. Taylor, and A.K. Hudson, Aspects of Crust Formation from Today’s Anode Cover Material. Light Metals, 2009: pp. 405–410. 28. H. Gudmundsson, Improving Anode Cover Material Quality at Nordural—Quality Tools and Measures, Light Metals, (2009) 467–472. 29. H. Wijayaratne, M. Hyland, M. Taylor, A. Grama, and T. Groutso, Effects of Composition and Granulometry on Thermal Conductivity of Anode Cover Materials, Light Metals, 2011, pp. 399–404. 30. M. LeBreux, M. Désilets, A. Blais, and M. Lacroix, On the Prediction of the Crust Inside Aluminum Electrolysis Cells, Light Metals, (2014) 655–660. 31. F. Allard, M. Desilets, M. Lebreux, A. Blais, Chemical characterisation and thermodynamic investigation of anode crust used in aluminium electrolysis cells, Light Metals, (2015) 565–570. 32. M. LeBreux, M. Desilets, F. Allard and A. Blais, Modeling and measurements of anode cover behaviour inside aluminium electrolysis cells, Numerical Heat Transfer, Part A: Application, 69 (2016)2, 128–145. 33. J.J. Liu, S. Wei, M.P. Taylor, Understanding the structure of ledge and crust in modern cells, 12th Australasian Aluminium smelting technology conference, 2018. 34. V. Khokhlov, et al., Thermal conductivity in cryolitic metls-new data and its influence on heat transfer in aluminium cells, Light Metals, 1998: pp. 501–506. 35. ASM Metal Handbook: volume 10, Materials Characterisation, 1986, Page 34. 36. PANalytical, B., Pert HighScore Plus software, version 3.0 e. Almelo: Netherlands, 2012. 37. H. Wijayaratne, G. Mcintosh, M. Hyland, L. Perander, and J. Metson, Relationships between smelter grade alumina characteristics and strength determined by nanoindentation and ultrasound-mediated particle breakage, 48A(2017) 3046–3059. 38. L.M. Perander, Z.D. Zujovic, T.F. Kemp, M.E. Smith and J.B. Metson, The nature and impacts of fines in smelter-grade alumina, 61(2009) 33–39.

Influence of Anode Cover Material Particle Size Composition on Its Physical Property and Insulation Performance Changlin Li, Junqing Wang, Yunfeng Zhou, Bin Fang, Yanfang Wang, and Qingguo Jiao

Abstract

Main physical property and service performance on aluminum electrolysis cell of five groups anode cover materials with different particle composition was examined. The results showed that with the decrease of particle size, bulk density increased from 1.56 to 1.62 g/cm3 and then decreased to 1.52 g/cm3, and repose angle decreased from 41.2° to 38.3°. On the whole thermal conductivity at working temperature decreased as particle size decreased, it decreased from 1.21 to 0.91 W/m K and then decreased slowly. Covering material surface average heat dissipation decreased when used on cell as particle size decreased, when particle size of covering material reduced to a certain extent, covering material surface average heat dissipation decreased to 2100–2200 W/m2, continuing decreasing particle size, no obvious insulation improving was got. Through the study, one cover materials was choen, and it particle composition was: 8 mm 10.21%. Keywords








Aluminum electrolysis Anode cover material Particle size Insulation Physical property




Introduction In aluminum electrolysis smelter, anode covering materials should be covered on new anode after anode change. The performance of covering material has great influence on heat C. Li (&)
J. Wang
Y. Zhou
B. Fang
Y. Wang
Q. Jiao Zhengzhou Nonferrous Metals Research Institute Ltd of Chalco, Zhengzhou, 450041, China e-mail: [email protected]

dissipation in the anode zone, and also affects the cell operation [1, 2]. One of the important functions of covering material is to reduce the heat loss in the upper part of the cell, to ensure heat balance of the cell, and to reduce the energy consumption [3]. The particle size distribution, the chemical composition of covering material and the thickness of covering material on the anode significantly affect heat dissipation in the anode zone and the operation of the electrolysis cell [4–6]. For one smelter, the composition of the covering material is generally relatively stable, and the thickness varies slightly with the seasonal variation, appropriate adjustments mainly are made according to the climate conditions, then the particle size distribution becomes the most important influencing factor to determine the thermal insulation performance of the covering material. The research work on the influence of the particle size distribution on the physical properties and the thermal insulation performance of the anode covering material has been carried out by the foreign researchers, and it is found that with high proportion of the fine material in the covering material, heat conductivity of the covering material is small, and the fluidity of the covering material is good, and thicker covering material layer is not readily formed on the anode [6, 7]. The research results provide theoretical support for selecting covering materials. In this paper, effects of particle size distribution on the bulk density, the covering performance, the surface temperature of the anode, the properties of the crust, the thermal conductivity and the heat dissipation from the surface of the anode are studied in the light of laboratory research and industrial field experiment. The experimental data is analyzed and can provide reference and guidance for improving the service performance of the covering material by optimizing the particle size distribution of covering material.

C. Li
J. Wang
Y. Zhou
B. Fang
Y. Wang
Q. Jiao China National Engineering and Technology Research Centre for Aluminium, Zhengzhou, 450041, China © The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_88

653

654 Table 1 The composition of the original covering material

C. Li et al. Composition

Al2O3

LiF

NaF

KF

CaF2

MgF2

AlF3

Mole ratio

Other

Weight (%)

32.41

3.56

28.76

2.07

2.96

0.69

26.34

2.18

3.21

The covering material used in the experiment came from industrial field, and the composition of the original covering material (recorded as covering material 0) was shown in Table 1. Based on the original covering material, the particle size composition of the covering material was adjusted by the combination of grinding and screening, and four groups of covering materials with different particle size distribution were obtained, which were recorded as covering material 1, covering material 2, covering material 3 and covering material 4, respectively. The particle size distribution of each covering materials was shown in Table 2.

taken every 2 days during the first 10 days and every 4 days in the later stage. The measured data included the surface heat flux density of the covering material, the thickness of crust covering material of the anode and the temperature of the bottom of the iron pipe. The heat flow density of the covering material was measured by a heat flow meter, and the temperature of the bottom of the iron pipe was tested by a thermocouple, and the detailed description was provided in the Ref. [5]. The component of the covering material was analyzed by the method of the national standard for the elements and the compound in the aluminum fluoride, the particle size composition was tested by standard sieve screening method, the bulk density and the repose angle was measured based on method in Ref. [8], and the heat conductivity coefficient of the covering material was tested by hot wire method.

Experiment Method

Results and Discussion

Five electrolysis cells with stable cell voltage in 3.75–3.80 V were selected. Two groups of intermediate anodes were selected on each cell to carry out the covering material experiment, and one group of covering material was used on each electrolysis cells. After the new anode set on the cell, the anode was covered with covering material, and the thickness of the covering material was controlled at 28 ± 0.5 cm. When the covering material added onto the anode, a steel pipe of 450 mm length was buried on the anode, and the lower end of the steel pipe reached to the upper surface of the anode. The outer diameter of the steel pipe was 10 mm and the inner diameter was 8 mm. The position of steel pipe was shown in Fig. 1.

The effects of particle size distribution on bulk density, covering performance, anode surface temperature, crust thickness, thermal conductivity and heat dissipation performance of anode surface were investigated experimentally below in detail.

Experiment Experiment Material

Analysis and Detection The measurement was started from the next day after the new anode change, and one group of measured data was

Table 2 The particle size distribution of each covering materials (%)

The Effects of Particle Size Distribution on Bulk Density It can be seen from Table 2 that the particle size of the covering material decreased from covering material 0 to covering material 4 in turn, and the weight fraction of fine materials with particle size less than 0.25 mm increased gradually, which was 19.06%, 24.86%, 29.85%, 35.09% and 39.86%, respectively. The covering material 0 came from the industrial field, and the particle size of the largest bulk material was about 50 mm. The covering material 1, the covering material 2, the covering material 3 and the covering

Covering material number

8 mm

0

19.06

19.53

39.52

21.89

1

24.86

23.15

36.65

15.34

2

29.85

30.29

29.65

10.21

3

35.09

40.73

19.84

4.34

4

39.86

45.36

14.78

0

Influence of Anode Cover Material Particle Size Composition …

steel pipe steel claw

covering material

anod block

45 1.62 40 1.60 35 1.58 30 1.56 25 1.54 20 15

weight fraction of particle size < 0.25mm bulk density

0

1

2

3

bulk density/g/cm3

weight fraction of particle size < 0.25mm/%

Fig. 1 Position of embedded steel pipe on anode surface

1.52 4

covering material number

Fig. 2 Weight fraction of fine material and bulk density of covering materials

material 4 were particle that passed through the pore size of 30 mm, 15 mm, 8 mm and 4 mm screen respectively. The bulk density was an important apparent property of the covering material. The bulk density of the five groups of covering materials was shown in Fig. 2. It can be seen from the figure that with the decrease of the particle size of the covering material, the bulk density first increased from 1.56 to 1.62 g/cm3 and then decreased to 1.52 g/cm3, and the bulk density of covering material 2 was the largest, reaching 1.62 g/cm3. The bulk density of particulate materials generally increases first and then decreases with the increase of the proportion of fine materials [9]. When the proportion of fine material is low, there is a certain gap between large particles that is not filled with fine material, and the bulk density can be increased by increasing the proportion of fine material. When the fine material reaches a certain proportion, the gap

between the particles is completely filled with the fine material, and the bulk density of the covering material reaches the maximum. According to the changing trend of bulk density with its particle size, when the proportion of fine material with particle size less than 0.25 mm reaches about 30%, the fine material is just enough to fill the gap between particles, so the bulk density is the highest.

The Effects of Particle Size Distribution on Covering Performance The repose angle of the five groups of covering materials was shown in Fig. 3, from which it can be seen that as the particle size of the covering material reduced, the repose angle of the covering material reduced from 41.2° to 38.3°. The covering material with the great repose angle can form thicker covering layer on the surface of the anode, and had potential of increasing the thickness of covering material and improving heat insulation effect. The fine covering material had small repose angle, and it was difficulty to increase the thermal insulation effect by increasing the thickness of covering material on the anode. Covering material 4 was the finest, the repose angle was the smallest, covering layer of only 28 cm thick can be formed on the anode surface, and it was much difficulty to increase thickness on the surface of the anode. The repose angle of the covering material 0 was the largest, and the covering layer with thickness of 38 cm can be formed on the surface of the anode, so that it was possible to further reduce the heat dissipation from the upper part of the cell. The other three covering materials can also form cover layer with thickness of up to 30 cm or more relatively easily.

42 41 40

repose angle/

guide rod

655

39 38 37 36 35

0

1

2

3

covering material number

Fig. 3 Repose angle of covering materials

4

656

C. Li et al.

The Effects of Particle Size Distribution on Anode Upper Surface Temperature The covering material can reduce the heat dissipation from the surface of the anode, increase the heating speed of the anode, reduce the resistance of the anode carbon block, increase the anode current, and provide conditions for stable operation of the electrolysis cell. The upper surface temperature of the anode was an important embodiment of the thermal insulation performance of the covering material. The variation of the upper surface temperature of the anode with time was shown in Fig. 4. With the prolongation of anode on cell, the upper surface temperature of the anode increased totally, and the surface temperature of the anode and the electrolyte temperature were close a few days before the electrode change. In six days after the anode change, when covering material 2, covering material 3 and covering material 4 used, the upper surface temperature of anode was close, which was obviously higher than that of covering material 0 and covering material 1. At the end of the anode life cycle, the upper surface temperature of the anode with five groups of covering materials was almost the same. The average temperature of the anode upper surface using the five covering materials was 743 °C, 765 °C, 798 °C, 803 °C and 791 °C, respectively. The average value also showed that the heat preservation effect of covering material 2, covering material 3 and covering material 4 was better than that of covering material 0 and covering material 1.

The Effects of Particle Size Distribution on Crust Thickness The crust thickness on the upper surface of the anode was measured in the experiment, and the test results were shown

in Fig. 5 (the thickness of the crust in this paper was the distance from the upper surface of the crust to the upper surface of the anode). The thermal conductivity of the covering material with coarse particle size was large, and the bottom temperature of the covering material increased slowly at the initial stage of the anode on cell, and the crust was relatively thin. With the prolongation of the anode on cell, the upper surface position of the anode carbon block decreased, the bottom temperature of the covering material increased, and the crust thickness increased rapidly. At the end of the anode service cycle, the crust thickness was larger than that of the covering material with small particle size.

The Effects of Particle Size Distribution on Thermal Conductivity In the experiment, the upper surface temperature of the anode cover material was measured, and the surface temperature of the covering material was between 120 and 170 °C. The upper surface temperature of the crust layer was also measured by thermocouple. The upper surface temperature of the crust layer was between 450 and 520 °C. According to the surface temperature of the covering material and the upper surface temperature of the crust layer, the average temperature of the loss covering material on the electrolysis cell was 300–370 °C. In order to compare the thermal conductivity of the covering material in the working state, the thermal conductivity of the covering material at 350 °C was tested. The thermal conductivity of the five groups of covering material was shown in Fig. 6. The thermal conductivity of the covering material 0 was the highest, which was 1.21 W/m K, the covering material 2, the covering material 3 and the covering material 4 was 0.91 W/m K, 0.86 W/m K and 0.82 W/m K, 30

25

900 800 700 600 0 1 2 3 4

500 400 0

5

10

15

20

time/day

Fig. 4 Upper surface temperature on anode with time

25

30

crust thickness/cm

upper surface temperature of the anode/

1000

20

15

10

0 1 2 3 4

5

0 0

5

10

15

time/day

Fig. 5 Crust thickness on anode with time

20

25

30

Influence of Anode Cover Material Particle Size Composition …

3000

the surface heat dissipation/W/m 2

respectively. The particle size of the covering material had great influence on the thermal conductivity. Some studies showed that when the proportion of the fine material in the covering material was low, there was still visible gap between the particles, when the temperature above 320 °C, the radiation heat transfer was significant, and the thermal conductivity was high. When the proportion of fine material was much, the thermal conductivity of fine material was low, when the proportion of fine material increased, and the thermal conductivity of covering material decreased [7]. The proportion of coarse particles in covering material 0 and 1 was relatively high and the thermal conductivity was large. The proportion of fine materials from covering material 2 to covering material 4 increased continuously, and the thermal conductivity decreased in turn.

657

2500

2000 0 1

1500

2 3 4

1000

0

5

10

15

20

25

30

time/day

Fig. 7 Surface heat dissipation of the covering materials with time

The Effects of Particle Size Distribution on Heat Dissipation Performance One of the important functions of the covering material was to reduce the heat dissipation in the upper part of the electrolysis cell. The surface heat dissipation of different covering materials in an anode service cycle were shown in Fig. 7. It can be seen that in one cycle, the heat dissipation on the surface of the covering material increased totally, but sometimes fluctuated. It may due to the shape change of the covering material on the anode while the position decline of the anode carbon block. In the early stage of an anode service cycle, the heat dissipation of different covering materials was quite different. With the prolongation of anode on cell, due to the formation of crust at the bottom of the covering material, the difference of thermal conductivity of the crust was small, which lead to decrease of the total thermal conductivity difference of the covering layer [9], and

the difference of surface heat dissipation between the covering material was also reduced. The average surface heat dissipation of the five covering materials during one anode service cycle was 2479 W/m2, 2382 W/m2, 2119 W/m2, 2194 W/m2 and 2177 W/m2, respectively. The average heat dissipation on the surface of the covering material decreased with the decrease of the particle size. When the particle size of the covering material decreased to a certain range, the surface heat dissipation of the covering material was basically stable. The average surface heat dissipation of the five covering materials had a certain relation with its thermal conductivity (as shown in Fig. 8), and generally the thermal conductivity of the covering material was large and the heat dissipation was large too. But when the thermal conductivity of the covering material was reduced to a certain extent, the surface heat dissipation of the covering material was substantially unchanged.

1.3 1.3 1.2

thermal conductivity/

thermal conductivity/

1.1 1.0 0.9 0.8 0.7

1.1

0

1

2

3

covering material number

Fig. 6 The thermal conductivity of covering materials

4

2500

1.0 0.9

2000

0.8 0.7

0.6

3000

thermal conductivity surface heat dissipation

0

1

2

3

4

surface heat dissipation/W/m2

1.2

1500

covering material number

Fig. 8 Surface heat dissipation and thermal conductivity of the covering materials

658

Through the analysis above, the particle size composition of the covering material 2 was relatively reasonable, the field operation was convenient, it had good thermal insulation, the preparation cost was relatively low, and adoption of covering material 2 was the most economical and reasonable.

C. Li et al.

economical and reasonable. The particle size composition of the covering material 2 was: 8 mm 10.21%.

Conclusions

References

1. The particle size of the covering material had significant effect on its physical properties. With the decrease of particle size, bulk density increased from 1.56 to 1.62 g/cm3 and then decreased to 1.52 g/cm3, and repose angle decreased from 41.2° to 38.3°. The thermal conductivity of the covering material decreased with the decrease of the particle size, after the thermal conductivity decreased from 1.21 to 0.91 W/m K, the effect of the fine material proportion in the covering material on the thermal conductivity decreased. 2. When five groups covering material used on cell, as particle size of the covering material reduced, the average temperature of anode surface increased, the heat dissipation from the surface of covering material reduced and the thermal insulation performance improved. When particle size of covering material reduced to a certain extent, covering material surface average heat dissipation decreased to 2100–2200 W/m2, continuing decreasing particle size, no obvious insulation improving was got. 3. Considering the actual situation, the covering material 2 has advantages of convenient operation, good thermal insulation performance, relatively low preparation cost, and adoption of the covering material 2 was the most

1. Liu YX, Li J (2008) Modern aluminum electrolysis. Metallurgical industry press, Beijing. 2. Ali JB et al. (2012) Improved energy management during anode setting activity. Paper presented at the 141st TMS Annual Meeting, Orlando, Florida, 11–15 March 2012. 3. Siegfried et al. (2005) Anode cover material and bath level control. Paper presented at the 134th TMS Annual Meeting, San Francisco, California, 13–17 February 2005. 4. Halldor G (2009) Improving anode cover material quality at Nordural– Quality tools and measures. Paper presented at the 138th TMS Annual Meeting, San Francisco, California, 15–19 February 2009. 5. Shen XC (2008) Top heat loss in Hall-Heroult cells. Paper presented at the 137th TMS Annual Meeting, New Orleans, Louisiana, 9–13 March 2008. 6. Taylor MP et al. (2004) The impact of anode cover control and anode assembly design on reduction cell performance. Paper presented at the 133rd TMS Annual Meeting, Charlotte, North Carolina, 14–18 March 2004. 7. Wijayaratne H et al. (2011) Effects of composition and granulometry on thermal conductivity of anode cover materials. Paper presented at the 140th TMS Annual Meeting, San Diego, California, February 27–March 3 2011. 8. Yue JS (2007) Exploit dry damming mixture use for aluminum electrolysis cell and study on the mechanism of prevent penetrate. M.S. thesis, Xi’an University of Technology. 9. Zhou YF, Li CL, Chai DP, Qiu SL, Zhang YL, Wang YF, Liu Z (2015) Discussion on properties of anode overlay in aluminum reduction. Light Metals, 9:32–35.

Lab Scale Experiments on Alumina Raft Formation Sindre Engzelius Gylver, Asbjørn Solheim, Henrik Gudbrandsen, Åste Hegglid Follo, and Kristian Etienne Einarsrud

Abstract

During feeding of alumina into a Hall-Héroult cell, rafts floating on the bath surface may be formed. In this study, rafts were created in a laboratory furnace by adding 4 g secondary alumina in industrial bath. Samples were withdrawn from the bath in a time interval between 30 and 300 s. The experiments show that at 970 ◦ C, rafts will be formed within 30 s, and then slowly dissolve again with a constant rate of 0.8 g/min. Pores were found in the samples, giving extra buoyancy to the raft, thus increasing the floating time. Same experimental setup was used to investigate the effect of preheating of alumina, where it was found that coherent rafts will form up to at least 500 ◦ C. Keywords

Alumina feeding • Rafts • Aluminum

Introduction Alumina is the principal raw material used in the Hall-Héroult process in order to produce aluminum. As smelters reduce their bath volume and anode-cathode distance, efficient feeding and dissolution of alumina becomes more important. S. E. Gylver (B) · Å. H. Follo · K. E. Einarsrud Department of Material Science and Engineering, NTNU, Trondheim, Norway e-mail: [email protected] Å. H. Follo e-mail: [email protected] K. E. Einarsrud e-mail: [email protected] A. Solheim · H. Gudbrandsen SINTEF Industry, Trondheim, Norway e-mail: [email protected] H. Gudbrandsen e-mail: [email protected]

When alumina is added into the molten bath, it will have temperature below the liquidus of the bath. Temperature differences will lead to freezing of bath around the alumina particles, which will create floating agglomerates known as rafts. Formation of rafts is unfortunate, as it hinders dissolution of alumina, which might lead to anode effects. In addition, rafts may sink to the metal pad, or even further below, creating sludge. A better understanding of the mechanisms behind formation and dissolution of rafts is therefore crucial in order to obtain a more efficient feeding. Formation of rafts in industrial cells has been observed in earlier work [1], where rafts were formed with floating times varying from 5 to 140 s. Anode age and thus available bath surface and circulation, as well as the acidity of the bath were suggested to have a significant effect on the floating time of the rafts. However, achieving detailed observations and recordings on industrial scale are difficult to accomplish due to the high temperature and hazardous gases. Laboratory experiments give more controllable and reproducible conditions for raft formation. For instance, as demonstrated by Kaszás et al. [2], image analysis can be used to estimate thickness and surface area of rafts following alumina addition. See-through cells, where one can observe addition of alumina from the side is also a promising approach, and has been used to observe the behavior of alumina upon addition and the dissolution [3,4]. X-ray furnaces have also been used for observations [5], demonstrating together with the other examples above that formations of rafts and agglomerates can be studied in detail. Artificially produced agglomerates have been used as an alternative to alumina powder by several authors in order to achieve constant geometry and reproducible results. Walker et al. [5] packed alumina in a thin layer of aluminum foil, creating cylindrical shaped agglomerates. The agglomerates were immersed in bath and the mass gain as well as the thickness of the frozen layer as a function of time, temperature and AlF3 concentration were measured. Increasing temperature and AlF3 concentration yielded a smaller layer of frozen

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_89

659

660

bath, which was explained with the increase of superheat, i.e the difference between the liquidus of the bath and temperature. The same setup has been adapted by several researches [6,7], and also tested in industrial cells [8]. Use of cylindrical discs of compressed alumina is also a way of achieving a constant geometry, as demonstrated by Kaszás et al. [9]. Discs were removed after a certain floating time, and found that the density of the raft exceeded the bath’s density, illustrating the effect surface tension will have on the floatability of rafts. A comparison of agglomerates generated from both secondary and primary alumina shows that there will be more pores when secondary alumina is used [10]. The porosity was studied in the work by Yang et al. [4], whose samples contained porosities in 6–8 explained by rapid release of hydroxyl and moisture upon additions into the bath. Computed Tomography (CT) on industrial samples revealed that the distribution and size of pores will vary within a raft [11]. Pores will reduce the apparent density of rafts, thus contributing to buoyancy. Pre-heating of alumina is a possibility to avoid raft formation. By adding hotter alumina, less bath will freeze around the particles, which may reduce raft formation. Hot exhaust gas has been investigated as a possible source of heat [12]. Experiments by Kobbeltvedt [6] suggest that preheating will result in more dispersed alumina, which will dissolve rapidly. For the alumina that will agglomerate, preheating had no positive effect, which was explained by decreased moisture content. Preheating will not assist the dissolution itself, which is suggested to be limited by mass transfer [13]. The current work investigates the behavior of alumina rafts, by adding alumina into an industrial bath, and removing agglomerates after a certain time. The goal is to create a setup that is closer to actually feeding in industrial cells, while still giving reproducible results. In such a setup, individual factors affecting dissolution can be studied in detail. In the present study, the effects of holding time as well as alumina temperatures on raft mass are investigated. Samples obtained from this setup were characterized with CT, which can be compared with samples of rafts from industrial cells [11].

Experimental Details Setup The experiments were conducted in a custom-made open top furnace, consisting of a steel pipe with an inner diameter of 15 cm and a height of 41 cm. The furnace can be used for temperatures up to 1200 ◦ C, and it is heated by a heating element that winds around the pipe. During experiments, the top of the pipe was thermally insulated in order to preserve heat.

S. E. Gylver et al.

Fig. 1 Left: Vertical cross section of the furnace, equipped with thermocouple (T), feeding pipe (F), raft sampler (S), carbon crucible (C) and gas purge (G). Right: Image of the furnace seen from above Table 1 Physical data for the materials in the first set of experiments Bath properties

Value

Bath acidity Alumina content at start Alumina properties >152.5 µm 44–152.5 µm 152.5 µm 44–152.5 µm 170 lm

Fig. 4 Particle size parameters Dv(10), Dv(50) and Dv(90) of SGA (14 fresh SGA and 7 secondary SGA samples) versus attrition index, before and after attrition test

708 Table 2 A simple correlational relationship of the particle size and the attrition index determines the SGA performance in practice

Table 3 The rating of SGA sample and its degradation condition after the attrition test

Y. Yang et al. Cases

Particle size of new-bought SGA

Attrition index

SGA performance in practice

A

Good

Good

Good

B

Good

Poor

Unknown

C

Poor

Good

Poor

D

Poor

Poor

Poor

Sample No.

Before attrition test

After attrition test

Attrition Index/%

Particle size degraded or not?

Dv* (10)

Dv* (50)

Dv* (90)

Rating

Dv (10)

Dv (50)

Dv (90)

Rating

1.1

F*

F

G*

F

F

F

G

F

7.49

No

1.2

F

G

G

F

F

G

G

F

12.89

No

1.3

F

G

G

F

P

F

G

P

27.85

Yes

1.4

G

G

G

G

F

G

G

F

27.45

Yes

1.5

F

G

G

F

P

G

G

P

16.43

Yes

1.6

F

G

G

F

P

F

G

P

24.15

Yes

1.7

G

G

F

F

F

G

G

F

13.52

No

1.8

G

G

G

G

F

G

G

F

14.26

Yes

1.9

G

G

G

G

F

G

G

F

11.31

Yes

1.10

G

G

F

F

F

G

G

F

10.25

No

1.11

F

G

G

F

F

G

G

F

8.32

No

1.12

G

G

G

G

F

G

G

F

5.78

Yes

1.13

G

G

G

G

P

G

G

P

23.38

Yes

1.14

G

G

F

F

F

G

G

F

14.12

No

2.1

G

G

G

G

F

G

G

F

12.91

Yes

2.2

F

G

F

F

F

G

G

F

9.33

No

2.3

P

G

G

P

G

G

F

F

0.23

No

2.4

F

G

G

F

F

G

G

F

14.44

No

2.5

F

G

G

F

F

F

G

F

15.47

No

2.6

F

G

G

F

F

G

G

F

8.43

No

2.7

F

G

G

F

F

G

G

F

1.52

No

*The Dv(10), Dv(50) and Dv(90) values indicate the critical diameters below which the small particles account for 10%, 50% and 90%, respectively, of the total particles. Abbreviation ‘P’ means ‘poor’, ‘F’ means ‘fair’, ‘G’ means ‘good’

The attrition test is normally performed by the alumina plant with fresh SGA as the test object. For the fresh SGA samples #1.1 to #1.14 in Table 3, when the attrition index is greater than 15%, especially when it’s greater than 20%, the SGA sample tends to be degraded after attrition. While for the sample with an attrition index of less than 15%, the particle size properties of the SGA would probably maintain quite stable during the production process. The attrition test is not usually performed on secondary SGA, because the secondary SGA is the byproduct of the dry scrubbing system in the aluminum smelting plant. However, from the results listed in Table 3, the samples #2.1 to #2.7 do not show frequent degradation condition, but it also reflects that the abrasion effect of the dry scrubbers on

SGA is quite remarkable. This phenomenon is also confirmed by the reluctantly accepted rating of the secondary SGA—of all the seven secondary SGA samples included in this investigation, only sample #2.1 gets a ‘Good’ rating.

Conclusion With the experiments carried out above, the following conclusions can be reached: • It should be emphasized again that both of the particle size distribution and the attrition index are important for the evaluation of SGA particle size during the smelting

Status Analysis of Particle Size Distribution and Attrition …

process. In order to maintain the particle stability, the attrition index of SGA should be controlled at less than 20%, preferably below 15%. • The abrasion effect of the dry scrubbing system on SGA is still significant. With the attrition tests on 14 fresh SGA samples and 7 secondary SGA samples, the average attrition index of secondary SGA is 44.8% lower than that of the fresh SGA. • Future work should be concentrated on increasing sampling numbers, and introducing more detailed analysis on −20 lm fine particles.

Acknowledgements The authors would like to acknowledge financial support from the Fundamental Research Funds for Northeastern University [grant no. N172503015] and the National Natural Science Foundation of China [grant no. 51804069, 51434005 and 51529401].

709

References 1. Forsythe W. L. and Hertwig W. R., Attrition characteristics of fluid cracking catalysts. Industrial & Engineering Chemistry, 1949, p. 1200–1206. 2. Matocha C. K., Crooks J. H. and Plazio P. P., Alumina attrition and dustiness – an extension of the attrition index method, Light Metals, 1987, p. 129–137. 3. Braun D. J., The abrasion of alumina, Light Metals, 1984, p. 257– 268. 4. Rodriguez E. and Mendoza R. and Song Y., Evaluation of precipitation process parameters on the alumina attrition index, Aluminum and Magnesium Communications (China), 2002, 02, p. 18–20. (in Chinese). 5. Tan J., Chen Q., Yin Z., and Li J., Studies on alumina microstructure and abrasion performance, Proceeding of national conference of physical chemistry of metallurgy, 2004. (in Chinese). 6. Perander L., Zujovic Z., Kemp T., Smith M. and Metson J., The nature and impacts of fines in smelter grade alumina, JOM, 2009, 61 (11), p. 33–39.

The Effect of Hard Scale Deposition on the Wall Heat Flux of a Cold Finger Daniel Perez Clos, Sverre Gullikstad Johnsen, Petter Nekså, and Ragnhild Elizabeth Aune

Abstract

A cylindrical cooled probe (cold-finger placed in cross-flow) has been used to investigate fouling in the off-gas duct located upstream from the gas cleaning system during primary aluminium production. Hard scale was formed on the front side of the probe whereas loose deposits accumulated on the rear side, causing inhomogeneous fouling resistance along the cold-finger circumference. Thermocouples and heat flux sensors allowed for the monitoring of the global and local heat transfer on both the front and rear sides of the probe. Additionally, the off-gas velocity upstream of the probe was monitored. Regression analysis of the heat transfer data produced was performed to calculate the fouling resistances from multiple experiments. Finally scale thickness was measured after the experiments and used to estimate its thermal conductivity. Keywords







Aluminium industry Cold-finger Scaling Heat transfer




Fouling




Introduction The accumulation of unwanted material on the surfaces of process industry equipment, also known as fouling, is a widespread problem that has a large economic impact worldwide. In the aluminum production industry a type of D. P. Clos (&)
S. G. Johnsen
R. E. Aune Department of Materials Science and Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway e-mail: [email protected] S. G. Johnsen SINTEF Industry, Trondheim, Norway P. Nekså SINTEF Energy Research, Trondheim, Norway

particulate fouling occurs, which generates hard layers that strongly adhere to the surfaces of different components. These deposits are known as “hard scale” since their hard and compact nature is similar to the scale layers which are formed by crystallization of saturated solutes in a fluid [1]. It is a well known fact that the formation of scale causes clogging of transport pipes, reduces the lifetime of off-gas filters, and requires expensive periodic cleaning procedures among other issues. In addition, it hinders the implementation of heat recovery systems that could help recovering part of the waste energy lost through the off-gas, which represents up to 40% of the overall energy loss in the production of aluminium [2]. Despite the problems that scale causes in the aluminium industry, not much has been published on the subject. However, scale is known to occur in high attrition areas where the off-gas impacts a surface where it can grow with large aspect ratios against the flow. The effect of fouling on heat transfer in aluminium production was investigated in a master thesis work by Fleer [3] in 2010, where a cooled fouling probe equipped with heat flux sensors on the front and rear sides of the probe (upstream and downstream from the off-gas, respectively) was installed in cross-flow in an off-gas duct for 11 days. The heat transfer coefficient obtained on the front side was reduced by 3% after 11 days, whereas a 29% reduction was observed in the rear side. In another study by Næss et al. [4] in 2006, the off-gas from aluminum production industry was iso-kinetically extracted and circulated through a test section where a cylindrical probe was installed in cross-flow and tests were run for up to 80 days. Asymptotic fouling resistances were observed with lower values and faster stabilization times at larger off-gas velocities. In this case, for the largest off-gas flux equivalent to around 15 m/s off-gas velocity, stable heat transfer coefficients were reached after 9 days with a heat transfer coefficient reduction of approximately 11%. In the same study, thin hard scale layers were formed on the front side of the probe, whereas much thicker layers offluffy deposits that were easy to remove were formed at the rear side.

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_96

710

The Effect of Hard Scale Deposition on the Wall Heat Flux …

A cold-finger was also used in particle deposition lab experiments in a study by Temu et al. [5] in 2002. In this study, particles from the Fe–Si industry were used with a carrying air gas velocity of 7.3 m/s. Contrary to the study by Næss et al. [4], larger deposition rates and fouling resistances were measured in the front side than in the rear side by means of heat flux sensors. The densities and thermal conductivities of the deposits were calculated from measurements of the total weight and volume of the deposits in combination with measured fouling resistances. Similar densities and almost identical thermal conductivities were obtained for both deposits, i.e. for the front- and rear side deposits, and no morphology differences were reported. In the present study, a cylindrical cooled probe (cold-finger) is used to investigate the fouling in the off-gas duct located upstream from the gas cleaning system during primary production of aluminium. The probe, placed in the cross-flow from the off-gas, allows for deposits on both its front and rear side to be studied, as well as the effect of different variables on the evolution of the local and total heat transfer coefficients. Data from several experiments varying in length is collected and analysed. The impact of the variability in the off-gas conditions in view of the accuracy of the measurement is discussed with special focus on the velocity and temperature variations. Moreover, a regression study is performed in order to calculate fouling resistances. The thermal conductivities of hard scale deposits are calculated from the fouling resistances and the measured deposit thicknesses. To the knowledge of the present authors, the thermal conductivity of hard scale from aluminium production has not been reported in the open literature before, and such data gives useful information that needs to be considered during the design and optimization of heat exchangers that are prone to scaling. Fig. 1 Schematic drawing visualising the location of the different thermocouples (TC) and heat flux sensors (HF) on the cold-finger, as well as the segmented tube (in 3 parts) which covers them

711

Methodology Different experiments, with the aim of collecting both scale samples and heat transfer data using a cold-finger, have been carried out in a duct transporting off-gas fumes from more than hundred aluminium pot cells. An opening flange located upstream of the gas treatment center was used to insert the cold-finger into the off-gas duct. Experiments with durations ranging from a few hours to several months were performed, however, only the experiments with durations of two weeks or more will be reported here as the effect of fouling on the heat transfer can then be clearly appreciated.

Data Acquisition and Experiments Description The cold-finger used in the present study consists of a concentric tube-in-tube-in-tube configuration where pressurized air, acting as the coolant, flows inside the inner tube and out into the annular space between the inner tube and the middle tube. Thermocouples and heat flux sensors are placed at the outer surface of the middle tube, as can be seen in Fig. 1, where the outer tube protects the sensors and is the substrate where deposition occurs. The heat flux sensors are placed on the front (HF1) and rear sides (HF2) of the probe (up- and downstream, respectively). A detailed description of the design of the cold-finger can be found elsewhere [6]. The thermocouples measuring the off-gas temperature and the inlet and outlet coolant temperatures allows for the monitoring of the total heat flux absorbed by the cold-finger. L200 units from Labfacility Ltd. were used to record data from the thermocouples (type T from Labfacility Ltd.) and from the heat flux sensors (from Fluxteq Solutions Inc.)

712

D. P. Clos et al.

every two seconds. To ensure a large enough heat transfer coefficient on the coolant side of the probe, a flow and pressure control system from Bronkhorst High-Tech B.V. was used. This system secured a uniform coolant flow rate of 60 l/min and a pressure of 4 bar throughout each experiment, allowing the main heat resistance to be allocated on the fouling side of the probe. The off-gas velocity was initially measured with a Pitot tube inserted in the same flange as the cold-finger. Twenty readings at different distances from the flange inlet were used to calculate average off-gas velocities and standard deviations due to turbulent effects at those points. A proprietary device was recently installed in the duct in order to monitor time-averaged off-gas velocity on a minute basis, which has been available only for the last experiment.

Analyses of Deposits After each experiment the outer tube’s centre section of the probe, which is in the heat flux sensors area, was embedded in epoxy and sliced to enable analysis by Electron Probe Micro Analyser (EPMA) of deposits cross-sections. An automatic saw was used to slice the samples, which thereafter were polished to expose a smooth surface. A JEOL JXA-8500F EPMA was used to measure the thickness of the deposit layers.

Heat Transfer Model Regression analyses have been used to fit the heat transfer data to different variables with the objective of separating variable off-gas contributions from the fouling resistance. From integration of the heat equation at steady state, Eq. (1) is obtained where the heat transfer coefficient U is calculated from the monitored heat flux q and the temperature difference DT between the off-gas and the cold-finger inner wall. U¼

q DT

ð1Þ

The percentage reduction of U over time, Udif , is calculated as shown in Eq. (2) with Uin equal to the initial heat transfer coefficient. Udif ¼

U  Uin
100% Uin

ð2Þ

The measured heat transfer resistance, U 1 , can further be expressed as the sum of the (constant) internal heat transfer resistance, U01 , the (fluctuating) contribution from the thermal boundary layer in the off-gas, Uof1 , and the

time-dependent fouling resistance due to accumulated deposits, Rf  Rf ðtÞ, as expressed by Eq. (3) U 1 ¼ U01 þ Uof1 þ Rf

ð3Þ

The off-gas heat transfer resistance is mainly a function of its velocity, temperature and pressure, when neglecting variations in off-gas composition. Both off-gas pressure and velocity are controlled by the fans and kept at relatively constant values. The temperature has a wider range in the long term due to atmospheric variations (90–130 °C) and short-term sharp oscillations (10 °C step changes), producing inversely proportional responses to the measured heat transfer coefficient. Therefore, the internal and off-gas heat transfer resistances have been fitted to a bias parameter accounting for the constant terms, a term to account for off-gas velocity variations (v1 of ) and a term to account for the step changes in temperature. The last term is calculated as the ratio between the off-gas temperature (Tof) and the time-centered temperature average (T^of ) (1 h interval). Velocity measurements have, in the present study only been implemented for the last experiment (E16). Therefore, for the rest of the experiments the impact of the off-gas velocity has been assumed to be constant and therefore absorbed in the bias term. U01 þ Uof1 ¼ w0
bias þ w1
v1 of þ w2


Tof T^of

ð4Þ

The fouling resistance (Rf) is defined as the ratio of the deposit thickness (lf) to the mean deposit thermal conductivity (kf); Rf ¼

lf kf

ð5Þ

Since no direct correlation with the measured variables can be assigned to the fouling resistance, at a given time, different time correlations have been used considering the trends from previous studies and the seemingly constant scale growth on the front side of the probe observed from scale thickness measurements. As the fouling resistance from the work by Næss et al. [4] showed logarithmic trends for the overall fouling resistance as a function of time, the fouling resistance has in the present study been modelled as the sum of a linear and an exponential function of time t as can be seen in Eq. (6). The exponential term can capture both logarithmic and exponential behaviors as function of time.   t Rf ¼ w3
t þ w4
1  ew5 ð6Þ

The Effect of Hard Scale Deposition on the Wall Heat Flux …

713

Numerical Approach The “Trust Region Reflective Algorithm” from the “scipy” python numerical library has been used to perform a non-linear regression analysis to solve Eq. (3) with the help of regression Eqs. (4) and (6). Moreover, in order to study the interdependence of different variables, their normalized values xnorm were calculated using Eq. (7) and plotted together. These values are obtained by subtraction of the variable time average µ and division by the standard deviation r yielding a vector with variance equal to 1. xnorm ¼

xl r

ð7Þ

corresponding values for the recorded off-gas velocity. As can be seen from the figure, the velocity values show sharp short-term variations in the range of 1–2 m/s, which is believed to be the effect of turbulence, but are constant in average. The obtained values are in agreement with the Pitot measurements of the off-gas velocity initially measured, which is displayed in Fig. 4. As can be seen from the figure, the Pitot results show a larger velocity close to the wall which is believed to be due to non-fully developed flow given a 90 degrees duct bending 4 meters upstream of the cold-finger. According to the correlation suggested by Churchill and Bernstein [7] in regards to heat transfer from fluids in cross-flow to a cylinder, velocity variations of 2 m/s would result in a change in the off-gas heat transfer coefficient of 7.5%, which is in the range of the noise measured in the cold-finger during the different experiments.

Calculation of Scale Thermal Conductivity In the present study the point of maximum thickness of scale (at the stagnation point) has been used to calculate the maximum deposit growth rates. In order to calculate the thermal conductivity from Eq. (5), an average scale thickness from the stagnation point to the edge of the heat flux sensor area has been used together with the fouling resistance calculated from Eq. (6) for the front heat flux sensor.

Results and Discussion Off-Gas Variability Effect on Heat Transfer Significant short-term oscillations in both off-gas velocity and temperature introduce notable noise in the measurement of the heat transfer coefficient. This can be seen in Fig. 2, which shows the normalized values (Eq. 7) for measured heat transfer coefficients as well as the off-gas temperatures and velocity for a period of 2 h. It can be observed that the off-gas temperature shows step changes of between 5 and 10 °C at irregular but frequent occasions. This results in an inversely proportionate response for the different heat transfer coefficient values. These changes do, however, not seem correlated with off-gas velocity. Two independent thermocouples, one placed at the cold-finger flange and another next to the device monitoring the off-gas velocity, confirmed the temperature jumps. It is believed that the fluctuations can be explained by the increased suction of the fans when operations on individual cells are performed in order to minimize emissions to the pot room. The consistent response of the heat transfer coefficient to the temperature jumps can be explained by capacitive effects as the cold-finger absorbs or releases heat to adjust to the new temperatures. The agreement between the off-gas temperatures from the two thermocouples for a period of two weeks can be seen in Fig. 3, together with the

Determination of Fouling Resistances In the present study the heat flux sensors proved to be operational in only two of the experiments, i.e. in experiments E10 and E16. The variation in percentage of the heat transfer coefficients (Eq. 2) measured as a function of time for these two experiments are presented in Figs. 5 and 6. A reduction of the total heat transfer coefficient of 15% is achieved in both cases after one week. The scatter is, however, significant—especially for the total heat transfer measurement which relies on heat flux measurement based on temperature measurements in the coolant, which is generally less accurate than the heat flux sensors. The regression results for the front, rear, and total heat transfer coefficients from experiment E16 are presented in Figs. 7, 8 and 9, respectively. As can be seen from the figures, the measured heat transfer coefficient values are plotted together with the output from regression Eq. (6) on the left ordinate axis, and the resulting fouling resistance on the right ordinate axis. It can also be seen that the large-scale variations in measured data are well reproduced by the regression model. The effect of the off-gas velocity has not been captured by the minute average values, as the velocity term has a negligible effect in the total output of the different regression equations. This is not surprising considering that the average value of the heat transfer coefficient has not varied substantially, and that the time scale of turbulent eddies is well below one minute. The temperature term has substantial weight as it captures the spiky nature of the signal produced by the cold-finger due to the inhomogeneity of the off-gas temperature discussed in the previous section. The fouling resistances after 14 and 40 days for various experiments are displayed in Tables 1 and 2, respectively. In Table 1, data from the two experiments with functional heat flux sensors have been used to estimate the thermal

714

D. P. Clos et al.

Fig. 2 Normalized values for the different heat transfer coefficients, as well as the off-gas temperature and velocity, as a function of time during a period of *2 h

Fig. 3 Off-gas temperatures from 2 thermocouples (left) and velocity (right) as a function of time during a period of 14 days

conductivity of scale at the initial stages by measuring the averaged scale thickness in the front side and using Eq. (5). The maximum thickness obtained during the two experiments can be seen in Fig. 10. Based on these results, the values obtained for the thermal conductivity of hard scale are 0.18 and 0.26 W/(m K), respectively. These values are 4 times higher than the once previously reported by Temu et al. [5], which is reasonable since it appears that the deposit layers they created were less dense than those from the compact scale. The fouling resistances on the rear side of the probe show larger values than the front side, i.e. 21 and 88% larger,

which indicates large different relative deposition on the front and rear sides between the two experiments. In both cases the total heat transfer coefficient is larger than the values provided by the heat flux sensors, which is due to a non-homogeneous growth along the axis of the cold-finger with larger growth rates towards the base. This has been observed by inspecting the deposits obtained on the probe after more than 1 month of exposer in the off-gas duct, where the thickness of the deposit layer is over 1 mm and variations in the deposit thickness can be readily appreciated. The rear deposits are also thicker at the base of the cold-finger. The differences in flow velocity along the duct

The Effect of Hard Scale Deposition on the Wall Heat Flux …

715

Fig. 4 Measured off-gas velocity (blue) as a function of the distance to the wall with a Pitot tube at the cold-finger flange opening. Standard deviation given by the green curve

Fig. 5 Percentage variation of the heat transfer coefficients measured as a function of time by the coolant (Udif_tot), the front heat flux sensor (Udif_HF1) and the rear heat flux sensor (Udif_HF2) during experiment E10

cross-section measured by the Pitot tube (see Fig. 2) could explain the obtained variations in the deposition rate. The overall fouling resistances after 40 days are comparable to the asymptotic ones measured by Næss et al. [4] for the largest off-gas velocity range, which is comparable to the present case. However, some of the data from the experiments deviate from the apparent asymptotic behavior of the first two weeks and become more irregular even with periods where the heat transfer coefficients show a steady increase. In some of the experiments a linear increase in the fouling resistance is achieved with time. These differences between the different experiments are difficult to justify, but it is believed that there might be other factors that influence the

off-gas side heat transfer coefficient than those taken into consideration in the present study. This is also observed by the reduction in the curve fit quality for the regression analysis of some of the longer experiments and even in some of the shorter ones showing effects that are not captured by the regression equation. The relative constant off-gas velocity measured during the first weeks in the last experiment might deviate in some periods of time, masking the fouling effect in the previous studies. Moreover, differences in pot operation and raw materials leading to different off-gas dust concentration and particle size distribution are other uncontrolled variables that might explain the different fouling behaviors observed.

716

D. P. Clos et al.

Fig. 6 Percentage variation of the heat transfer coefficients measured as a function of time by the coolant (Udif_tot), the front heat flux sensor (Udif_HF1) and the rear heat flux sensor (Udif_HF2) during experiment E16

Fig. 7 Front side heat transfer coefficient (left) measured (blue solid) and predicted after regression (blue dotted), and predicted fouling resistance (green dot-dashed, right) as a function of time

Regarding the growth rate of scale layers, the values obtained for experiments ranging from 1 day to 6 months have shown a general steady increase in deposit thickness, as can be seen in Table 1, which suggests that a linear increase in fouling resistance should be expected at least on the front side of the probe (without considering possible ageing effects that might affect the density and the deposit layer thermal conductivity over time). The rear deposits have also been observed to increase in thickness during the first weeks,

but as time passes the deposit accumulation in the flange has resulted in a wash out of the rear deposits on the probe during its extraction from the duct due to sub-atmospheric suction of the flange deposits towards the probe. This made it impossible to assess a possible stagnation in the growth thickness of these loosely attached deposits. The longest experiment (E6) with a maximum scale thickness of ca 7 mm produced a maximum fouling resistance of 0.025 (m2 K)/W with a linear fouling resistance increase over time.

The Effect of Hard Scale Deposition on the Wall Heat Flux …

717

Fig. 8 Rear side heat transfer coefficient (left) measured (blue solid) and predicted after regression (blue dotted), and predicted fouling resistance (green dot-dashed, right) as a function of time

Fig. 9 Total heat transfer coefficient (left) measured (blue solid) and predicted after regression (blue dotted), and predicted fouling resistance (green dot-dashed, right) as a function of time

Table 1 Fouling resistances calculated based on data from different experiments after 2 weeks

Exp. #

Duration days

Rf total (m2 K)/ W  103

Rf HF1 (m2 K)/ W  103

Rf HF2 (m2 K)/ W  103

Average scale growth rate µm/day

E6

175

2

–

–

36.1

E8

45

4

–

–

28.4

E9

13

2.3

–

–

31.9

E10

14

2.5

1.4

1.7

30.7

E12

42

1

–

–

37.8

E13

98

3.5

–

–

35.7

E16

29

2.5

0.8 (1 week)

1.5 (1 week)

51.7

Scale kW/ (m K)

0.18

0.26

718 Table 2 Fouling resistances calculated based on data from different experiments after 40 and 175 days

D. P. Clos et al. Experiment

Rf total 40 days (m2 K)/W  103

Rf total 175 days (m2 K)/W  103

E6

4

25

E8

4

–

E12

3

–

E13

4

–

Fig. 10 Measurement of deposit layer thickness in the front side stagnation point for samples E10 (left) and E16 (right)

Conclusions Heat transfer data from a cold-finger has been analyzed by non-linear regression to study the effect of different variables on the evolution of the local and total heat transfer coefficients. Off-gas velocities have been monitored on a minute basis for over two months showing constant average values and fluctuations of ca. 2 m/s. Irregular but frequent jumps in off-gas temperature have been shown to introduce rather large bias in the measure of heat transfer coefficients, which have been captured by the regression model. The local fouling resistance on the scale side together with scale thickness measurements have been used to estimate a value for the heat conductivity of hard scale in the range 0.18–0.26 W/(m K). Acknowledgements The present work has been funded by the SFI Metal Production, (Centre for Research-based Innovation, 237738), and the authors gratefully acknowledge the financial support from the Research Council of Norway and the partners of the SFI Metal Production.

References 1. S. N. Kazi, “Fouling and Fouling Mitigation on Heat Exchanger Surfaces,” in Heat Exchangers - Basics Design Applications, J. Mitrovic, Ed. InTech, 2012, pp. 507–532. 2. K. Grjotheim and H. Kvande, Introduction to Aluminium Alectrolysis: Understanding the Hall-Hérloult process. Düsseldorf: Aluminium-Verlag, 1993. 3. M. Fleer, “Heat Recovery From the Exhaust Gas of Aluminum Reduction Cells,” 2010, pp. 1–110. 4. E. Nass, T. Slungaard, B. Moxnes, and O. K. Sonju, “Experimental Investigation of Particulate Fouling in Waste Heat Recovery From the Aluminium Industry,” in Fouling, 2006, pp. 1–11. 5. A. K. Temu, E. Næss, and O. K. Sønju, “Development and Testing of a Probe to Monitor Gas-Side Fouling in Cross Flow,” Heat Transf. Eng., vol. 23, no. 3, May 2002, pp. 50–59. 6. D. P. Clos, H. Gaertner, P. Nekså, S. G. Johnsen, and R. E. Aune, “Design of a Cooled Fouling Probe to Investigate Scaling Mechanisms from the Aluminium Production Off-gas,” in Heat Exchanger Fouling and Cleaning, 2017, pp. 261–264. 7. S. W. Churchill and M. Bernstein, “A Correlating Equation for Forced Convection From Gases and Liquids to a Circular Cylinder in Crossflow,” J. Heat Transf., vol. 99, no. 2, 1977, pp. 300–306.

The Application of Intelligent Breaking and Feeding Technology for Aluminium Reduction Pot Bo Hong, Qinghong Tian, Zhiyang Chen, Xiaotian Tan, and Shiping Yu

Abstract

Reducing voltage to achieve lower energy consumption has been a constant goal for aluminium pot line operators. However, voltage reduction could be accompanied with breaker jam and elephant leg, having many disadvantages. In this paper, three different breaker jam identification solutions have been tested based on analysis of the core parameters that have the greatest impact on breaker jam and elephant leg. On the foundation of site practices and experiments, a new intelligent breaking and feeding technology, which consists of following key features, has been developed: breaking in groups + single-point feeding + use pressure sensor to identify breaker jam + unlink breaking and feeding sequence + intelligent feeding technology + energy compensation technology. This technology has been applied to some Chinese smelters and has achieved good results. Hence, breaker jam and elephant leg can be reduced by 80%, breaker and cylinder life can be prolonged by 20–30% and energy consumption can be saved by 0–50kWh/t-Al. Keywords

Breaker jam




Elephant leg




Breaking




Feeding

B. Hong (&)
Q. Tian
Z. Chen
X. Tan
S. Yu Guiyang Aluminum Magnesium Design and Research Institute, Guiyang, China e-mail: [email protected] Q. Tian e-mail: [email protected] Z. Chen e-mail: [email protected]

Introduction During the production of aluminium reduction, breaking and feeding are two of the most essential working procedures intelligently controlled by computer. Also, it’s the most vital factor relating the normalization and stability of pot. In China, due to the low voltage production style [1] and complex metal ingredient [2], the bath has lower superheat and higher viscosity, in this case, the existing traditional breaking and feeding system will not meet the demand for further cost reduction and efficiency improvement and will bring about following disadvantages: (1) Adopting the mode of one breaking before one feeding, which means breaking keeps going when feeding point is unobstructed, so it will increase wear-out of device and waste compressed air. (2) Cannot automatically inspect and deal with beaker jam, which not only increases manpower but also easily leads to voltage fluctuation, anode effect, power consumption and more energy wastes. (3) Time for breaker in the bath is fixed and cannot be changed according to varied statues of feeding point, which will increase the frequency for elephant leg and reduce breaking efficiency. To solve the above issues, research on reduction process optimization, breaker device and pot control system strategy were studied [3–5], but few of which were applied to full potlines. Based on MPPIC (multivariate process parameter intelligent control system) [6, 7], an intelligent breaking control technology and corresponding device has been developed, successfully solving the deficiencies of existing breaking and feeding system. This new intelligent breaking system has been applied to potlines now.

X. Tan e-mail: [email protected] S. Yu e-mail: [email protected] © The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_97

719

720

B. Hong et al.

Breaker Jam and Elephant Leg Breaker jam & elephant leg (as Fig. 1 shows) are the two most commonly-seen troublesome issues in aluminium production, especially for low-voltage production style, which will easily lead to uneven alumina concentration, voltage fluctuation and anode effect, increased energy consumption and reduced current efficiency. After the occurrence of breaker jam & elephant leg, it needs to be handled by manual strike with heavy iron tools. It is very labor-consuming in such a high-intensity magnetic field. There are two main reasons for breaker jam: one is breaker cannot penetrate crust so the alumina cannot enter bath, and another one is breaker can penetrate crust but alumina cannot fully dissolve in bath, instead, accumulates at feeding point. The affecting factors of breaker jam may be represented by the Eq. (1): F1 ¼ fðp; DTÞ ¼ fðtd ; d; DTÞ

ð1Þ

where F1 is the probability of breaker jam, p is breaking pressure, td is breaking duration time, d is breaking depth and DT is superheat. Insufficient breaking pressure is the main reason why breaker cannot penetrate bath. The affecting factors of breaking pressure are td, d and compressed air pressure. But this paper excludes compressed air pressure’s affect, for it is the basic premise for normal production. Reasons for elephant leg are more complex. Elephant leg has two interface layers, one is contact layer of breaker and bath, which is the basis for elephant leg formation, and another one is solidified layer of bath and bath liquid, which is the key for elephant leg enlargement. Normally, wettability between bath and breaker is small, so the contact layer formed by breaker contacting bath will solidify and drop after breaker leaving bath, therefore no elephant leg will generate. When breaker has high temperature and bath has high viscosity, or bath is mixed with metal, the wettability between breaker and bath will sharply grow [8]. Bath will be tightly adsorbed to the surface of breaker and will not drop after breaker leaving bath, hence contact layer of elephant

leg formed. Once the contact layer is formed, it’s hard to stop elephant leg growing, as the main ingredient of solid layer of elephant leg is bath and solid layer is formed by bath solid repeatedly adsorbing bath liquid. Bath solid and bath liquid are basically the same substance, so the wettability and adsorption force of solid layer of elephant leg is stronger. The larger the bath viscosity is, the more solid the solidified layer is, and the larger the elephant leg grows. The affecting factors of elephant leg may be represented by the Eq. (2): F2 ¼ fðTb ; DTÞ ¼ fðti ; td ; d; DTÞ

where F2 is probability of elephant leg, Tb is breaker temperature, ti is breaking interval time. Affecting factors for breaker jam and elephant leg are common in breaking duration time, breaking depth and superheat. The comprehensive affecting factor of breaker jam and elephant leg may be represented by the Eq. (3): F ¼ fðt; d; DTÞ

ð3Þ

where F is probability of breaker jam and elephant leg, t is breaking time, indicating the proportion of breaking interval time and breaking duration time (ti/td). From analysis of plenty of production data (For continuous 30 days, collected data and conducted analysis on 180 feeding points of 45 pots at a 240 kA pot section—keeping record of breaker jam, elephant leg, breaking depth and breaking time of each feeding point for 3 times per day respectively in the morning, afternoon and evening, and sampling bath once for analyzing the liquidus temperature to calculate superheat), results of Eq. (3) are shown in Figs. 2 and 3. Within a certain range, there is a linear relationship between DT and breaker jam and elephant leg: increasing DT is favorable for reducing breaker jam and elephant leg. Breaking time t is a relatively more uncontrollable parameter in production with much more complex influence on breaker jam and elephant leg: values of t differentiate according to device and technical conditions of smelters. In general, t is controlled within 30–80 (namely ti 90–120 s, td 1.5–3 s),

Fig. 1 Phenomenon of breaker jam and elephant leg

(a) breaker jam

ð2Þ

(b) elephant leg

The Application of Intelligent Breaking and Feeding Technology …

721

Fig. 2 Effect of breaking depth on breaker jam and elephant leg

Fig. 3 Effect of breaking time on breaker jam and elephant leg

which is adaptive controlled area,increasing t is conducive for reducing elephant leg, but aggravates breaker jam. Some Chinese smelters choose to double t (breaking once and feeding twice) to reduce elephant leg, while some other smelters choose to cut t by half (breaking twice and feeding once) to prevent breaker jam. Breaking depth d changes frequently in production. Fluctuation of metal level and bath level will lead to change of d. In general, d is controlled within 4–13 cm, which is adaptive controlled area. The smaller d is, the more frequent breaker jam happens and less frequent elephant leg occurs. Most of time, elephant leg is caused by big d value. Apart from breaking time, breaking depth and superheat, material & shape of breaker and operation also have impacts on breaker jam and elephant leg, but not as significant as what caused by the factors mentioned above, so this paper do not discuss them specifically.

Identification Technology of Breaker Jam and Elephant Leg At present, there is no perfect method to detect elephant leg, and only manual operation to be conducted when elephant leg generates, so it’s better pay attention to prevent elephant leg beforehand. Compared to elephant leg, breaker jam is more harmful because it will cause obstruction for alumina entering bath. Therefore, it’s much more significant to identify and deal with breaker jam. This paper studies three breaker jam identification solutions as shown in Fig. 4. Solution A applies intelligent cylinder to identify breaker jam. The cylinder is deployed with a movement detecting device, which is used to detect the breaker’s movement to see whether it penetrate the crust or not. By controlling the

722

B. Hong et al.

Fig. 4 Breaker jam identification proposals

Table 1 Contrast among 3 solutions

Advantages

Flaws

Solution A

Save more air

High cost, difficult maintenance

Solution B

Time for breaker contacting bath is shorter, relieving elephant leg effect is better

Higher requirement for insulation, more workload for maintenance

Solution C

Lower cost, easy operation and maintenance

Higher requirement for sensor quality

breaker’s movement, breaking depth can be reasonably controlled and hence reduce elephant leg. Solution B applies electric signal to detect breaker jam. When breaker breaks through the bath, it will be current passing to bath and metal through breaker to detect if there is any breaker jam. Meanwhile, if electric potential difference between cathode busbar and breaker has been detected, breaker will withdraw immediately so as to reduce breaking depth and duration time. By this way, elephant leg can be reduced as well. Solution C applies pressure detecting method to identify breaker jam. By identifying pressure changes of breaking through or not to identify breaker jam. At the same time, intelligently adjust breaking duration time to reduce elephant leg. These three solutions have respective advantages and flaws, with the contrast result to be seen as Table 1. Taking cost, maintenance and effect into consideration, we developed intelligent breaking and feeding technology based on solution C.

Pressure Sensor to Identify Breaker Jam The key of pressure sensor to identify breaker jam is the stability of breaking pressure. During practical production, due to problems like device aging, pipe leakage, valve fault and unstable pressure, breaking pressure will fluctuates accordingly. As Fig. 5 shows, neighbouring pots in one section present as three different pressure statues: (a) pressure is stable, and breaker jam can be intelligently identified; (b) intermittent pressure dropping, affecting breaker jam identification preciseness; (c) pressure fluctuates obviously, and breaker jam cannot be identified. In light of the difference between pressure value of breaker jam and that of without breaker jam is small, how to precisely identify pressure changes and eliminate interference becomes the core of this technology. The pressure sensor works in an environment with high temperature, strong magnetic field and full of fluoride dust, so the quality requirement for it is very strict. We conducted

The Application of Intelligent Breaking and Feeding Technology …

723

(b) intermittent pressure dropping

(a) stable

(c) fluctuation

Fig. 5 Breaking pressure statues of neighbouring pots at the same time

breaker lifting device

pressure sensor

Fig. 6 Pressure sensor and breaker lifting device

trials for testing the performance of pressure sensors and selected a specially-made one (Fig. 6). It’s to be expected to stably run at pot for two years. Up to now, the first batch of pressure sensors installed on pot has been running for nearly two years and still in good condition.

Intelligent Breaking and Feeding Technology We have developed full-set of intelligent breaking and feeding technology, consisting of breaking in groups + single-point feeding + use pressure sensor to identify breaker jam + unlink breaking and feeding sequence + intelligent feeding technology + energy compensation technology. Breaking in groups + single-point feeding: at present, most pots have 4–6 feeding points, and usually fixed 2–3 feeding points work in turn to conduct breaking and feeding simultaneously. With the development of technology, Chinese potlines recently put into production gradually adopt

single-point breaking and feeding. Considering costs, intelligent breaking and feeding technology recommends to adopt breaking in groups plus single-point feeding. Single-point feeding aims at controlling feeding at breaker jam feeding point and breaking in groups is to reduce pipe network at upper pot for more convenient maintenance. Meanwhile, add breaker lifting device, as Fig. 6 shows: three gears to adjust the depth in bath, achieving a breaking depth of 5–13 cm. Unlink breaking and feeding sequence: intelligently breaking according to superheat and breaker jam status, altering traditional method that is one feeding following one breaking. When breaking is unobstructed, reduce breaking time, extend breaking interval time, and shorten breaking duration time, so as to reduce elephant leg. When breaker jam occurs, increase breaking times (as Fig. 7 shows, B is to be seen at the voltage curve when breaker jam occurs, which means increase breaking), at the same time, increase breaking duration time to enlarge breaking pressure so as to deal with breaker jam. Intelligent feeding technology: shown as Fig. 7, N is to be seen at the voltage curve when breaker jam occurs, which means only breaking without feeding. Prevent alumina accumulation caused by breaker jam is conducive to rapidly dredging breaker jam. Energy-compensation technology: for breaker jam caused by low superheat, if good effect cannot be reached after several times of breaking and feeding handling, energy will be compensated intelligently in order to change pot superheat. Intelligent breaking and feeding technology is a combination of above technologies. The control strategy is shown in Fig. 8, regarding which we strongly suggest being integrated on MPPIC system (or independent control cabinet). With this technology, core parameters as t, d and DT in Eq. (3) can be rationally adjusted and breaker jam and elephant leg can be controlled within the adaptive controlled area as Figs. 2 and 3 shows.

724

B. Hong et al.

Fig. 7 Unlink breaking and feeding sequence control strategy

Fig. 8 Intelligent breaking and feeding control strategy

Application There are many trials of intelligent breaking and feeding technology going through, among which one trial on 10 pots of a 500 kA potline has been conducted. The result comparison of total 6 months before and after trail is shown in Table 2, and breaker jam and elephant leg reduction conditions are shown in Table 3.

Table 2 Comparison of intelligent breaking and feeding trail for 500 kA pot

Project Before After Difference

Voltage (V)

Meanwhile, based on a good result of 6 trail pots, we popularize this technology to one section of 400 kA pots for half a year’s trail, and the result is shown in Table 4. Intelligent breaking and feeding technology can balance alumina concentration, reduce sludge, lower anode effect, alleviate voltage deviation and improve pot stability; all these contribute to the reduction of consumption. From Tables 2 and 4, we can tell that intelligent breaking and feeding technology has certain energy-saving effect of 0–50kWh/t-Al. From Table 3 we can tell that with this technology, breaker Metal level (mm)

Excess AlF3 (%)

TMP (°C)

AE (Nos./day)

CE (%)

DC (kWh/t-Al)

Section

3.997

310

7.9

960

0.16

91.8

12981

Trail pot

4.025

318

8.0

960

0.34

92.7

12937

Section

4.004

314

9.0

959

0.15

92.6

12886

Trail pot

4.017

324

8.8

960

0.13

93.4

12822

0.007

4

1.1

−1

0.00

0.8

−95

Trail pot

−0.008

6

0.8

0

−0.21

0.7

−115

Difference

−0.014

2

−0.3

1

−0.21

−0.2

Section

−20

The Application of Intelligent Breaking and Feeding Technology … Table 3 Results of intelligent breaking and feeding trail for 500 kA pot

Table 4 Comparison of intelligent breaking and feeding for one section of 400 kA pots

725

Pot No.

Feeding times

Breaking times

N times

B times

Breaking times reduction (%)

Breaker jam and elephant leg reduction (%)

1716

1741

1182

0

0

32.1

89.3

1717

1750

1236

0

0

29.4

87.5

1718

1585

1191

12

7

24.9

74.4

1719

1555

1317

18

28

15.3

65.4

1720

1675

1152

0

0

31.2

85.4

1721

1781

1274

6

3

28.5

76.7

1722

1721

1215

6

3

29.4

81.5

1723

1662

1223

0

4

26.4

76.5

1724

1509

1055

0

0

30.1

85.3

1725

1755

1226

0

0

30.1

84.2

Avg

1673

1207

4.2

4.5

27.7

80.6

Section

Voltage (V)

Before After Difference

Metal level (mm)

Excess AlF3 (%)

TMP (°C)

AE (Nos./day)

CE (%)

DC (kWh/t-Al)

4.051

335

9.5

955

0.03

94.2

12815

4.040

336

9.8

954

0.03

94.3

12767

−0.011

1

0.3

−1

0.1

−48.4

jam and elephant leg can be reduced by 81.5%, and breaking times can be reduced by 27.7%. It’s conducive to relieving wear-out of breaker and cylinder, and extending cylinder service life. Also, it helps to lower on-site manpower. At present, based on the foundation of low-voltage production route of China, this technology is very welcomed at Chinese smelters, being deployed to multiple 240–500 kA potlines for verification, and being applied to one 400 kA and one 300 kA potline. And another two 500 kA potlines are going to put into production. We estimate that by the end of 2020, it will be put into use on 3000 pots.

Conclusion Breaker jam and elephant leg can bring many disadvantages for reduction production, which will be significantly relived by intelligent breaking and feeding technology. The main factors for breaker jam and elephant leg are breaking time, breaking depth and superheat. Increasing superheat helps to reduce breaker jam and elephant leg. Increasing breaking time and reducing breaking depth lead to higher frequency of breaker jam and lower frequency of elephant leg, and vice versa. Intelligent breaking and feeding technology consists of unlink breaking and feeding sequence + intelligent feeding + energy compensation control strategy, which jointly

0

contribute to optimize the core parameters factors of breaker jam and elephant leg, alleviate wear-out of device, reduce energy consumption for reduction production and manpower.

References 1. Zhang Tianhua, Huang Shuwen and Wu Wei, Practices on energy saving of high amperage pre-bake aluminum reduction pots under low voltage process, Light Metals 2013(05): 31–34. 2. Huang Haibo, Qiu Shilin, Influences of rich –lithium alumina on aluminum reduction production, Light Metals 2014(08): 26–28. 3. Wang Peng, Hazard and treatment of bath sticking to chisel, Light Metals 2012(11), 36–38. 4. Nursiani Indah Tjahyono, Yashuang Gao, et al, Detecting, identifying and managing systematic potline issues with generation 3, TMS Light Metals 2017, 615–622. 5. Zhou Hong, Jia Yongjian, Mao Yongqin, A method for eliminating elephant leg of 180 kA reduction pot, CN201420609245.X, 2014-06-04. 6. Yi Xiaobing, Tian Qihong, Development and application of a multivariate process parameters intelligence control technology for aluminum reduction cells, TMS Light Metals 2010, 523–527. 7. Hong Bo, Tian Qinghong, Yi Xiaobing, The Application of the “Remote Data-Diagnosis Technology Service” (RDTS) for Aluminum Pot Line, TMS Light Metals 2019, 929–935. 8. Yuan Ribing, Wu Dianjun, Wang Weiming, Progress in research of wetting between liquid & solid phase of metal, China Foundry Machinery & Technology, 1999, 11–14.

Reducing the Carbon Footprint: Aluminium Smelting with Changing Energy Systems and the Risk of Carbon Leakage Gudrun Saevarsdottir, Halvor Kvande, and Barry J. Welch





Abstract

Keywords

This paper presents an analysis of the smelting trends and potential opportunities to reduce the overall greenhouse gas emissions from the primary aluminum industry in total, both direct emissions from the production processes and indirect emissions from the electric power used. Presently, 71% of the aluminum is produced with electricity from fossil fueled power plants, and while the introduction of wind and solar generation of electricity is accelerating, these have technical constraints and limitations. On average, indirect emissions from the power used dominate as emission source, so de-carbonizing the electricity production through low-emission power sources is crucial for the primary aluminum production in order to meet carbon emission targets. Globally the best result will be achieved by maximizing aluminum production in regions that can provide low emission power. However, national or political objectives can sometimes counter this by re-directing the use of existing hydro power used by aluminum smelters to eliminate local emissions from the process, in order to meet national goals. While this may reduce carbon emissions regionally, the result may be an increase in the industry’s global emissions through increased production capacity using non-renewable high emission level power sources in other regions. Indeed, the carbon footprint of primary aluminum production has increased significantly this century due to an increasing transition of the energy mix towards fossil based power.

Aluminum smelting Greenhouse gas emissions Specific emissions Carbon footprint Carbon leakage

G. Saevarsdottir (&) Department of Engineering, Reykjavik University, 101 Reykjavík, Iceland e-mail: [email protected] H. Kvande The Norwegian University of Science a Technology, Trondheim, Norway B. J. Welch University of New South Wales, Sydney, Australia B. J. Welch Welbank Consulting Ltd, Whitianga, New Zealand







Introduction The demand, production and use of aluminum are increasing, and the annual global production has doubled during the last ten years, but the emissions of greenhouse gases have also increased significantly. The emissions are growing not only because of the growing demand for aluminum but also the limited supply of electrical energy generated from renewable sources. In 2018, 71% of the aluminum production came from electricity from fossil fuels, mainly coal (61%) and natural gas (10%). In the most recent report from IPCC [1] it is stated that in order to prevent 1.5 °C of global temperature increase, the total greenhouse gas emissions must fall by 45% from 2010 levels by 2030, and reach “net zero” around 2050. The aluminum industry has to contribute to reach this ambitious goal. They can do many things, as will be discussed here, but the most important is to de-carbonize the electrical energy production for aluminum smelters by maximizing the use of emission free power sources and minimizing the use of low-grade coal. This can be obtained by increasing the aluminum production in regions where CO2-emission free electricity is available.

Greenhouse Gas Emission Sources from Aluminum Production From the bauxite mine to the aluminum ingot the total global average emissions are now between 14 and 17 metric tonnes of CO2-equivalents per tonne of aluminum produced (t CO2e/t Al), based on both direct process and indirect

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_98

726

Reducing the Carbon Footprint: Aluminium Smelting with Changing …

emissions (mainly from energy sources), depending on the various estimates and assumptions made in the literature [2, 3]. In any case these emissions are high and the industry will surely face pressure to reduce them in the near future. The four main contributions to this total value are [2]: • Alumina production by the Bayer process, where an average of 1.5 t CO2e/t Al come from conversion of bauxite to smelter-grade alumina, with a variability of ± 0.4 t CO2e/t Al, depending on the source of the fuel used to provide the thermal energy for heating and steam in alumina refining. • Production of prebaked carbon anodes and their raw materials, where about 0.6 t CO2e/t Al are released. • The electrolysis step, where an average of 1.5 t CO2e/t Al come from the use of prebaked carbon anodes for the electrochemical extraction conversion, and 0.2 t CO2e/t Al come from perfluorocarbon (PFC) gas emissions, mainly during anode effects in the prebaked anode cells. • The remainder, and by far the largest contribution are indirect emissions from aluminum production, with a global average of about 10.2 t CO2e/t Al coming from generation of the electrical energy used in the electrolysis step. Globally this category spans from practically zero when using geothermal, nuclear or renewable power sources such as hydro, wind or solar, and up to 12–15 t CO2e/t Al when low-grade coal is used for power production.

Reduction of Direct Greenhouse Gas Emissions from the Aluminum Production Processes In a world that now is searching for and publicly demanding a low-carbon future, it is clear that these emissions must be reduced dramatically in the coming years. So what can the aluminum industry do here? Refining bauxite to alumina offers little potential for reducing the carbon dioxide emissions level because of the linkage between the mining and refining processes, and also global distribution. One option for improving the alumina refining process is to replace rotary kilns with circulating fluidized bed kilns that uses only about one-third of the fuel demand of rotary kilns [3]. For the electrolysis step the variability in the emissions generated by the use of carbon anodes ranges from a low of 1.40 t CO2e/t Al using Best Available Technology (BAT) for prebaked anode cells, to about 1.85 t CO2e/t Al for the remaining smelters operating aged Søderberg anode cell designs, which are steadily being phased out. The electrolysis process emits a range of products from the anode,

727

depending on purity of the raw materials and operating cell conditions, with the dominant gases being CO2 and CO, with the latter also ending up in the atmosphere as CO2. Although a limited amount of the carbon consumption also arises from direct access of air to hot anode surfaces, the potential to reduce carbon emissions here is by achieving lower net anode consumption rate, which is measured in kilogram of anode carbon consumed per tonne of aluminum produced (kg C/t Al). Because of the qualities of the raw materials available for smelting and the physics of the electrochemical process, the contribution from the anode is unlikely ever to be lower than 1.33 t CO2/t Al produced. Through limitations in the design, operation and control practices of the electrolysis cell, the electrochemical processes at each anode can change, enabling co-evolution of the perfluorocarbon (PFC) gases CF4 and C2F6 [4]. These potent greenhouse gases are co-evolved at a much higher rate during anode effects (AE) when the interfacial potential of all the anodes in the cell have exceeded that necessary to enable co-oxidation of the fluoride anion of the electrolyte. Then the cell energy input has increased through a voltage rise sufficiently to provide the necessary interfacial heat at a rate that satisfies the thermodynamic requirements of the overall reactions at the electrode interface. Most commonly the AE will initiate through depletion of the dissolved alumina concentration in the electrolyte, with the level at which it occurs being dependent on the localized anode current density, electrolyte temperature and other factors. In recent years, there have been many design variations in modern large prebaked anode cell technologies to achieve low energy consumption. Many of these have introduced greater spatial variations in cell conditions and with re-distribution of current between anodes, PFCs can be co-evolved at low rates without the normal cell voltage signal giving an indication of an individual anode (or part thereof) is at an electrode potential that enables PFC co-evolution. Consequently, there has been a rise in the tendency for the cells sometimes continuously to co-evolve low quantities of CF4 and in rare cases, smaller amounts of C2F6 are detected (often close to the detection limits of instrumentation). Individual anode current monitoring offers the potential for early detection, but elimination will also require more advanced alumina feeding control and logic. The successful development and use of inert anodes, which have been under intense investigation for about 75 years, have the potential of bringing direct CO2 and CO emissions from the electrolysis step to zero, because then only oxygen gas is formed. Such cells would not emit any PFC gases either. However, it carries the penalty that the electrochemical reaction demands an electrode potential around 1.0 V higher than using a carbon anode. Thus, if it were retrofitted to an existing cell design with a similar heat loss, the energy consumption per unit production would increase approximately

728

25%, and this would decrease the probability that the technology can be retrofittable to existing cell technologies. Furthermore, the result could be a net increase in emissions, if the electricity is from coal power. Revolutionary cell designs will be needed, which also implies successfully developing new corrosion resistance high-temperature electrically conducting materials that the conventional smelting industry has been striving for in the same period of time. Thus, the aluminum smelting industry faces three challenges: 1. The general global challenge of obtaining an adequate supply of “emission-free” electricity to meet their requirements, 2. Reduction in the unit energy consumption (kWh/t Al) so that aluminum production can be carried out without the need for coal-fired electrical energy and reduction of process related emissions.

Electrical Power Sources for Aluminum Production—The Indirect CO2e Emissions Historically, the deciding factor for the location of aluminum plants was to be close to hydro-power electrical energy because of the reliability of the supply, low transmission costs, and low-cost renewable energy. The strategic importance of aluminum that developed through the World Wars, combined with advances in the designs for thermal power generation, resulted in a shift towards coal-fired power stations utilizing the vast coal resources that existed. This coincided with a reduced availability of renewable green energy, and contributed to the acceleration of awareness of the need for managing the environment. Because aluminum production is very energy intensive, the highest potential to impact total emissions is to reduce the indirect emissions due to the production of electric power used in the electrolytic process. In 2000 about 49% of the aluminum was produced with electricity from non-renewable fossil sources, coal, natural gas and oil, while 46% came from hydro-electricity and 5% from nuclear power [5]. For the most recent data available, from 2018, the ratio had changed to 71% of the aluminum being produced with electric power from fossil fuels and only 27% from hydro power plus other renewables, while the contribution of the nuclear power plants was only 1.3%. So, in this period, the development has gone in the wrong direction with increasing power related greenhouse gas emissions. This trend must change very soon! The data in Table 1 includes electric power sources used for electrolysis by the Hall-Héroult process, including rectification from AC to DC and normal smelter auxiliaries

G. Saevarsdottir et al.

including pollution control equipment up to the point where the molten aluminum is tapped from the cells. The volume of aluminum production by hydro power has increased in all regions, except in North and South America, and 60% more aluminum is now produced globally by this energy source compared to 2000. The production by hydro-power has, however, declined in Europe and the Americas since 2010. In China, about ten times as much aluminum is now produced by hydro power compared to 2000. The regions with the largest part of green energy used for aluminum production are North and South America, Europe and Africa, where between 50 and 83% of the power comes from hydroelectricity. Europe has also about 20% that comes from other renewable sources, mainly wind and solar power, and geothermal energy in Iceland. However, because of the large increase in total annual production, the world percentage of aluminum from hydro power has decreased from 46 to 26% in this 18-year period. Europe dominates in the use of nuclear power. However, the aluminum production by nuclear power in Europe has been reduced by 20% since 2000. Nuclear power is not much used for aluminum production in North America any longer and in other regions it is zero. For the fossil fuel power sources coal is the largest. Its use has been increased dramatically in China and also in Asia ex. China. Asia now produces 90% of their electricity for aluminum production from coal. Aluminum production from coal has been reduced in North America (by 70%), Europe (by 44%) and Oceania (by 11%) since 2000. The world production of oil-based electricity for aluminum production has been reduced considerably since 2000 and it is now only 0.02%, mainly in Europe. About 90% of the aluminum production by natural gas occurs in the Gulf Cooperation Council (GCC) member countries, with a few percent only in South America, North America and Europe. There has been a 50% reduction in Europe and a strong reduction to zero in Asia, while it has increased in North and South America. In the GCC countries natural gas used to be “flared off” and simply burnt while they produced their crude oil. The use of the gas for electricity generation had the benefit that they could use the waste heat to drive desalination plants and thus provide necessary water for general habitation and increasing vegetation. Thus, while the smelting industry there contributes to the industry’s figure it is probable that the global emission increase has been lowered because of the use of natural gas (instead of coal) to produce aluminum. These trends are shown in Fig. 1. It is seen how Europe (including Russia) first increased the amount of electric power used for aluminum production and then decreased it after 2010. China has increased the aluminum production tremendously, mainly based on coal-fired power. From 2000 to 2018 the total annual global production of aluminum made from electricity from coal-fired power

Reducing the Carbon Footprint: Aluminium Smelting with Changing …

729

Table 1 Global data for the electric power used for aluminum production (GWh) and the total annual aluminum production (t/year) in different regions of the world in 2000, 2010 and 2018. Data is taken from Ref. [5] Power source and year

World region Europe (GWh)

North America (GWh)

South America (GWh)

Africa (GWh)

China (GWh)

Asia, ex. China (GWh)

GCC (GWh)

Oceania (GWh)

World reported (GWh)

Hydro (2018)

91,969

45,921

14,337

12,088

48,530

4,787

0

7,971

225,603

Hydro (2010)

97,271

50,355

29,145

9,181

24,227

4,817

ND

5,211

220,207

Hydro (2000)

28,449

59,324

30,491

6,914

4,325

3,400

ND

7,328

140,231

Nuclear (2018)

11,225

182

0

0

0

0

0

0

11,407

Nuclear (2010)

10,677

320

0

0

0

0

ND

0

10,997

Nuclear (2000)

14,004

1,826

99

0

0

0

ND

0

15,929

Coal (2018)

8,015

7,514

0

11,735

436,766

39,450

0

19,225

522,705

Coal (2010)

13,856

16,095

0

11,844

218,043

8,171

ND

17,932

285,941

Coal (2000)

14,286

25,292

0

10,844

38,923

9,437

ND

21,697

120,479

Natural gas (2018)

2,328

1,639

4,312

0

0

0

79,954

193

88,426

Natural gas (2010)

5,015

316

5,591

0

0

15,510

ND

0

26,432

Natural gas (2000)

4,894

587

2,119

0

0

15,381

ND

0

22,981

Oil (2018)

176

6

0

0

0

5

5

0

192

Oil (2010)

238

7

0

0

0

138

ND

6

389

Oil (2000)

1,052

150

518

0

0

378

ND

0

2,098

Total Al prod. in 2018 (t/year)

7,829,170

3,774,000

1,171,713

1,668,000

36,485,000

4,415,000

5,331,000

1,919,701

64,336,000

Total Al prod. in 2010 (t/year)

8,053,000

4,689,000

2,305,000

1,742,000

17,331,000

5,224,000

ND

2,277,000

42,353,000

Total Al prod. in 2000 (t/year)

7,490,000

6,041,000

2,167,000

1,178,000

2,794,000

2,221,000

ND

2,094,000

24,657,000

Change in Al prod from 2000 to 2018

+4.5%

−38%

−46%

+42%

+1306%

+199%

+

−8.3%

+261%

730

plants increased from 40 to 61%. These changes have consequences for the carbon footprint from aluminum production in the world. Figure 2 shows how the CO2e emissions from the electrical energy production for aluminum electrolysis have changed in the same regions, as well as globally. From Figs. 2 and 3 it can be seen that the carbon footprint, here described in terms of intensity per tonne Al, (kg CO2e/kg Al) from the electrical energy used in aluminum production, has decreased significantly in Europe and North America as the energy production has on average shifted mostly to green power. At the same time the overall production has decreased in these regions since 2010, so this is of limited benefit to the world climate. China’s production footprint has improved slightly as their hydro-to-coal ratio has increased, but still their carbon footprint remains high, and this contributes significantly to the rise of the carbon footprint of the world energy mix for aluminum production from 7 to 10 t CO2e/t Al in this period. The increase in hydro power in China from 2010 to 2018 still does not compensate for the reduction in use of hydro power in Europe and the Americas in terms of TWh, and globally the fractional contribution of renewables in the aluminum energy mix has been dramatically reduced. The resulting increase in the average carbon footprint in this period is around 3 kg CO2e and significantly higher than the footprint from the electrolysis process itself. The data presented and discussed above are taken from World Aluminium [5], the website of the International Aluminium Institute (IAI). Regarding data integrity the IAI considers their data to be reliable, but they may be subject to revision. The IAI data is combined with IPCC data [6] and LCA analysis from IAI [3, 7] and Kvande et al. [8] for the specific emissions from both different sources of energy, needed for Fig. 2, as well as process specific emissions in

Fig. 1 Energy (TWh/year) by source, used in aluminum production in different regions of the world in 2000, 2010 and 2018. Data from Ref. [5]

G. Saevarsdottir et al.

Fig. 3. The data in Table 1 is considered reliable to draw the conclusions we have given above, but in a few cases the data seem to be questionable. For example it is not likely that there has been a three-fold increase in aluminum produced by hydro power in Europe from 2000 to 2010. Furthermore, the choice of regions by the IAI is not the best to illustrate where the action is needed to overcome the emission problem, because it sometimes gives a distorted picture. For example: the situation in Iceland and Norway is different from the rest of Europe; in North America the merging of USA and Canada distort from the shut-down of old smelters in USA; and in Oceania the New Zealand smelter has 100% green energy, while in Australia two smelters that ran on coal-fired power have been closed.

Energiewende in Germany Energiewende is the German word for energy transition and it is the planned transition in Germany to a low-carbon, environmentally sound, reliable and affordable energy supply [9]. This means that most, if not all of the existing coal-fired power generation in the country will be phased out, and the same will happen soon to the German nuclear reactors. However, experience has shown that the Energiewende is a bumpy road towards reduced emissions, as the German greenhouse gas emissions were stagnated in recent years, because its energy system relies on fossil powered capacity to compensate for the intermittence of wind and solar energy. However, the emissions fell in 2018 to their lowest levels since 2009 [10]. The initiative taken by Trimet Aluminium, which is Germany’s largest aluminum producer, demonstrates how aluminum can be a part of the solution towards renewables. This aluminum smelter has been converted into a so-called

Reducing the Carbon Footprint: Aluminium Smelting with Changing …

731

Fig. 2 The total indirect CO2e emissions (109 tonnes) in different regions due to production of electrical energy used in aluminum production in the years 2000, 2010 and 2018. (The reported energy use is scaled for actual aluminum production). Data from Ref. [3, 5, 6]

Fig. 3 The overall carbon footprint of aluminum production (kg CO2e/kg Al) based on average emission values from the processes and emissions attributed to the electrical energy used for aluminum electrolysis by region in the years 2000, 2010 and 2018 (reported data). For comparison the 2018 footprint using Best Available Technology (BAT) is included. For simplicity the direct emissions for alumina, anodes and the electrolysis have been kept constant here for all regions. Data from Ref. [3, 5, 6, 8]

“Virtual Battery”. It functions like a huge and intelligent energy storage facility and is a buffer between volatile energy generation and variable demand. The concept is based on running the potrooms at maximum capacity when renewable energy is abundant, while reducing the potline current and metal output by 25% for up to 48 h when there is insufficient energy available [11]. There are limitations in swing capacity but it can be compensated for by using variations in the side ledge thickness in the cells as the energy reservoir. This is enabled through controlled heat flow regulation from the electrolysis cells by heat exchangers, thus maintaining the protective solid ledge on the cell sidewalls at maximum current by operating with more heat transfer from the sides. It makes the energy-intensive electrolysis process more flexible by creating a large power storage facility that integrates the discontinuously produced electricity from renewable sources

into the existing power grid. This is an innovative electricity solution that the company hopes will contribute positively to the energy system transition to renewables.

Carbon Leakage Globally the lowest total greenhouse gas emissions will be achieved by maximizing aluminum production in regions that can provide clean, “green” power. All aluminum smelters in Canada, Iceland, New Zealand, Norway and Russia use renewable power, mostly hydroelectric but also geothermal in Iceland and New Zealand. These plants play a significant role in limiting the global emissions that would otherwise be produced with electrical energy from fossil fuels. However, this aluminum production has the potential to introduce very high carbon leakage. Carbon leakage

732

occurs when there is an increase in carbon dioxide emissions in one country (or region) as a result of emissions reduction by a second country with a strict climate policy. As production is initiated in the first country it replaces capacity closed down in the latter. The European Union has an ambitious system for carbon taxing, where industry must purchase quotas for their emissions through the Emission Trading System (ETS). The EU is aware of the risk of carbon leakage and has identified businesses at a particular risk of carbon leakage that get awarded free emission quotas. Industries with high international trading intensity, and where emission costs are a significant fraction of revenue, are deemed at risk of carbon leakage, and aluminum scores very high in both of those dimensions. Additionally, because the aluminum industry is very energy intensive, it is seen as particularly sensitive to the effect of the ETS system on the energy price. It has therefore wound up on a much shorter list of businesses for which countries are permitted to subsidize the companies to compensate for the increase in electricity price as a consequence of the ETS system. As a result of these actions, according to a study by Sartor [12] published in 2012, carbon leakage was not detected for aluminum production early in the period. More recent data, published by Healy et al. [13] in 2018, shows that total EU-28 imports have increased and intra EU-28 production has decreased since 2012, with the import to production ratio for unwrought unalloyed aluminum rising from 350% to 600% in the period. The authors concluded that this is an indicator of carbon leakage that warrants further investigation. This is supported by Fig. 1 in this paper, but the use of aluminum has increased in Europe since 2010. The most important threat to the competitiveness of the European aluminum industry is the energy price. Much of the industry has benefitted from long-term affordable energy contracts and that along with the free allocation of emission quotas to this production effectively has counteracted carbon leakage. As more and more of those contracts have expired in recent years, or will do so in the years to come, the industry faces the full impact of the electricity prices that are higher than in competitive markets. Some countries have chosen to activate the authorization to subsidize the indirect emission energy cost to this sector, but the risk is that aluminum smelters will close down in countries that will not subsidize, as recent smelter closures in Spain show. Norway and Iceland are a part of the ETS system, but while Norway has chosen to subsidize the indirect emission costs to the industry, Iceland has not, although the local energy price is rising towards European levels. In a wider sense the expression of carbon leakage implies greenhouse gas emissions global management and responsibility. Closing down hydro powered smelters to reduce the emissions regionally by eliminating the contribution from its

G. Saevarsdottir et al.

potlines will increase global emissions, because as the data shows, the deficit in metal supply will almost certainly be compensated by production in countries using non-renewable high emission level power sources.

Discussion The world has a growing demand for aluminum, partly because of the energy savings arising from its use. As stated above, 71% of the metal was produced from fossil fueled power plants in 2018, and while the introduction of wind and solar generation is accelerating, these have technical constraints and limitations. Thus, countries and regulators should take care not to push production from renewable power towards regions where fossil fuel is the main energy source. Globally the best result will be achieved by maximizing aluminum production in regions that can provide clean green electrical energy. In such cases, national ambition to cut emissions locally should not dominate over global responsibility. It is indeed difficult to see how the countries of the world will be able to reduce their combined emissions by 45% from 2010 levels by 2030, and reach “net zero” around 2050, unless there is a major shift in the development of energy infrastructure. Tong et al. [14] claim in a recent paper published in Nature, that if the current global energy infrastructure is allowed to operate through its planned lifetime, the 1.5 °C temperature increase is already out of reach and most of the emissions causing a 2 °C increase are already in the pipeline. Their estimate is that the most cost-effective premature infrastructure requirements will be in the electricity and industry sectors, if non-emitting alternative technologies are available and affordable. Rapidly growing countries in Asia are expanding their energy infrastructure in beat with the economy, mostly based on fossil fuel. For example, China and India have increased their primary energy consumption annually by 4.4% and 5.7%, respectively, in the period from 2006 to 2016 [15]. Modern middle-class lifestyle is very energy reliant to provide products and comforts, and renewables such as wind and solar energy are weather dependent and have, due to their intermittent nature, clear limitations in their ability to replace fossil power as baseload. Hydro power is already fully utilized in most regions, and in others development faces hurdles due to nature preservation priorities. Today, around 25% of the total global emissions come from electrical energy and heat production and 10% is associated emissions from related activities such as fuel extraction and mining. The 14% of the world emissions coming from the transport sector could be reduced significantly with electric vehicles if the electrical energy production is low-emission. Combining these, around 50% of the global greenhouse gas

Reducing the Carbon Footprint: Aluminium Smelting with Changing …

emissions are directly related to energy production and can only be reduced by decarbonizing that. Emissions are stagnating and even decreasing slightly in North America and Europe, but with improved living conditions in the fastest growing countries and the rapid growth of a middle class happily adopting western consumption habits, fossil fuel powered energy infrastructure will continue to rise with associated emissions, unless the infrastructure investment is shifted to low emission alternatives [15]. There is an environmentally clean alternative for “base-load” energy production—nuclear energy—which technically has a real potential to reduce emissions from the electrical energy production. The largest obstacle to expanding the use of that technology, however, is lack of public acceptance (because of the storage of nuclear waste and the potential for catastrophic accidents and also military implications), even though statistics show that well-managed nuclear power is by a good margin the safest electric power production technology there is [16]. That, however, is a challenging topic outside the scope of the present paper. If we then go back to the recent IPCC report [1], it was stated there that to keep the global warming less than 1.5 °C, the total global CO2e emissions must fall by 45% from 2010 levels by 2030. In comparison, the total annual anthropogenic global carbon emissions in 2018 rose by 2.0%, the fastest growth for seven years [15]. The aluminum industry is expected to make its contribution to this emission reduction. In 2010 the total global aluminum production was 42,353,000 t/year and 285,941 GWh of coal power was used. In 2018 the aluminum production had increased by 152% to 64,366,000 t/year, while 522,705 GWh of coal power was used, an increase of 183% [5]. There is no reason to expect that the amount of aluminum produced by power from natural gas will decrease in the coming years, so the main chance for the aluminum industry to reach the IPCC target is to reduce the use of coal power dramatically in the next ten years. Additionally, if carbon capture and sequestration (CCS) technology could be developed for coal-fired power plants, this would give an estimated emission reduction of 73% [17]. However, this is a moving target because the primary aluminum production will probably continue to increase, maybe to 75 or 80 million t/year in 2030. It will be extremely difficult to reduce the energy for aluminum production from coal power to about 150,000 GWh, which is less than one third of what it was in 2018.

Conclusion With growing concern about climate change, the aluminum industry faces a push to cut greenhouse gas emissions. The demand for aluminum increases steadily as the number of

733

people enjoying middle class lifestyle in the world explodes, and this easily recyclable light metal contributes to lighter and more fuel efficient transport vehicles. Therefore the task is not so much to reduce the use of aluminum but rather to reduce the emissions from its production. There are opportunities to reduce emissions from existing smelters by optimizing their operations for low CO2 emissions and minimum PFC emissions. An inert anode process and also carbon capture and sequestration (CCS) technology can reduce emissions from the present electrolysis process itself. If we assume that inert anode cell technology development will be successful sometime during the next decade, then all greenfield aluminum plants will probably be required to have this technology. But irrespectively of the development of new inert anode cells, the large majority of primary aluminum will still be produced in traditional Hall-Héroult cells with carbon anodes in 2030. Therefore CCS technology for aluminum cells needs to be developed soon. Here the international aluminum industry could cooperate in order to be able to reduce the CO2e emissions. The capture part of CCS will depend of the existing cell superstructure and may therefore be somewhat different for the various existing cell technologies, but the sequestration part could be common for most of the smelters. However, the emissions from the electrolysis process are only about 10% of the total emissions from the global aluminum production process and the dominating emission source is the electricity production. Therefore, the priority should be to power the smelters by “emission-free” or low emissions electricity. This is a topic for global energy policy, but countries with ambitions to cut emissions have a global responsibility not to cause carbon leakage by pushing aluminum production from clean energy sources towards high-emission energy sources elsewhere. The single most important opportunity would be if countries with rapidly expanding energy infrastructure would shift the expansion of their energy infrastructure to low-emission technologies, such as hydro, wind, solar or nuclear. Representatives from the aluminum industry could wield their influence and contribute to that shift in their respective countries and regions of the world.

References 1. IPCC (2018) Summary for Policymakers. In: Global Warming of 1.5°C, an IPCC special report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T.

734

2.

3.

4.

5.

6.

7.

8.

G. Saevarsdottir et al. Maycock, M. Tignor, and T. Waterfield (eds.)]. World Meteorological Organization, Geneva, Switzerland, 32 pp. Sævarsdóttir GA, Kvande H, Welch BJ (2020) Aluminum production in the times of climate change: The global challenge to reduce the carbon footprint and prevent carbon leakage. Submitted for publication in the January 2020 issue of JOM. IEA Greenhouse gas R&D programme (2000). Greenhouse gases from major industrial sources - IV The Aluminium Industry. Report number PH3/23. https://ieaghg.org/docs/General_Docs/ Reports/Aluminium%20industry.pdf. Accessed 15 September 2019. Wong DS, Welch B (2018) PFCs & anode products – myths, minimisation and IPCC method updates to quantify the environmental impact. In: Dorreen, M, Tomsett, A, Welch, B. (eds) Proceedings from the 12th Australasian Aluminium Smelting Technology Conference, Queenstown, New Zealand (paper number 4c1 Proc. 12, Nov. 2018). World Aluminium (2019). http://www.world-aluminium.org/ statistics/primary-aluminium-smelting-energy-intensity/#data. Accessed 31 August 2019. T. Bruckner, I. A. Bashmakov, Y. Mulugetta, H. Chum, A. de la Vega Navarro, J. Edmonds, A. Faaij, B. Fungtammasan, A. Garg, E. Hertwich, D. Honnery, D. Infield, M. Kainuma, S. Khennas, S. Kim, H. B. Nimir, K. Riahi, N. Strachan, R. Wiser and X. Zhang (2014) Energy Systems. In: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_ full.pdf. Accessed 4 October 2019. IKE, 2017. A life-cycle model of Chinese grid power and its application to the life cycle impact assessment of primary aluminium. Available from: http://www.world-aluminium.org/ publications/tagged/life%20cycle/ Accessed 15 June 2018. Kvande H, Welch B (2018) Light Metal Age, 76 No. 1, 28 (January/February 2018).

9. Deutschland’s Energiewende (2019). http://www.energiewendeglobal.com/de. Accessed 31 August 2019. 10. Indicator: Greenhouse gas emissions (2019). https://www. umweltbundesamt.de/en/indicator-greenhouse-gas-emissions. Accessed 4 October 2019. 11. Depree N, Düssel R, Patel PP, Reek T (2016) The “Virtual battery” - Operating an aluminium smelter with flexible energy input. In: Williams E (ed) Light Metals 2016, The Minerals, Metals & Materials Society, Pittsburgh; Springer, New York, p 571-576. doi: https://doi.org/10.1007/978-3-319-48251-4_96. 12. Sartor O (2012) Carbon Leakage in the Primary Aluminium Sector: What Evidence after 6 ½ Years of the EU ETS? USAEE Working Paper No. 13–106. https://ssrn.com/abstract=2205516. Accessed 12 September 2019. 13. Healy S, Schumacher K, Eichhammer W (2018) Analysis of Carbon Leakage under Phase III of the EU Emissions Trading System: Trading Patterns in the Cement and Aluminium Sectors, Energies MDPI, Open Access Journal, vol. 11(5):1–25, May 2018. https://doi.org/10.3390/en11051231. 14. Tong D, Zhang Q, Zheng Y, Caldeira K, Shearer C, Hong C, Qin Y, Davis SJ (2019) Committed emissions from existing energy infrastructure jeopardize 1.5 °C climate target. Nature 572 (7769):373–377. 15. BP Statistical Review of World Energy (2018) 64th edition. https://www.bp.com/en/global/corporate/energy-economics/ statistical-review-of-world-energy.html. Accessed 15 September 2019. 16. Markandya A, Wilkinson P (2007), Electricity generation and health, The Lancet, 370(9591):979–990. 17. Schlömer S., T. Bruckner, L. Fulton, E. Hertwich, A. McKinnon, D. Perczyk, J. Roy, R. Schaeffer, R. Sims, P. Smith, and R. Wiser, 2014: Annex III: Technology-specific cost and performance parameters. In: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Measurement System for Fugitive Emissions in Primary Aluminium Electrolysis Håkon Aleksander Hartvedt Olsen Myklebust, Thor A. Aarhaug, and Gabriella Tranell

Abstract

Fugitive emissions from primary aluminium production is a concern both for occupational health and the environment. Current measuring equipment for in-situ measurements of such emissions is generally large and expensive or lacks the required time and spatial resolution to provide accurate information on the source of the emissions. This research is aimed at testing and evaluating distributed micro sensors for in-situ monitoring of dust intensity in the electrolysis hall. Multiple sensors are tested simultaneously in clusters at each location to study variation between individual sensors, giving a statistical average. These clusters are spread out in the relevant areas to map how the emission varies over both time and location based on operational activities such as anode changes. The sensor system yielded results that could be correlated to the process activities, and also showed clear variation in the fractions of PM10 and PM2.5 measured for different process operations. Keywords

Microsensors • Fugitive emissions • Workers health

H. A. H. Olsen Myklebust (B) · G. Tranell NTNU, Trondheim, Norway e-mail: [email protected] G. Tranell e-mail: [email protected] T. A. Aarhaug SINTEF Industry, Trondheim, Norway e-mail: [email protected]

Introduction Dust in the Electrolysis Process The air-suspended particles produced in the aluminium production processes may be harmful if inhaled and exposure to high levels of particles has been linked to occupational asthma, with indications of increased mortality from cancer and pulmonary emphysema [1,2]. The dust produced in aluminium electrolysis often contain high levels of Flourine which may generate hydrofluoric acid if it comes into contact with water. These fumes are not only a concern in terms of workers health, but also contribute to the so-called fugitive emissions which may be harmful to the local, urban communities as well as the environment at large [3]. A schematic of the electrolysis process is shown in Fig. 1, and while most of the fumes are contained within the cells where the off-gas is filtered before its release, it is necessary to open the cells for several operations over the course of the production cycle. Examples of such operations are the anode change and cell tapping. To effectively gauge the particulate emissions from each different operation, a constant measurement system in necessary. Several previous studies provide an incomplete picture as the time-resolution is limited [3]. In the EU, regulations for fugitive emissions are tightening, and as such, measuring these categories of fumes are important [5]. Particularly fluoride emissions is considered important, and this is known to be a large component of the dust which is measured in this work [6]. Particulate emission by size fraction is also considered highly significant by the European commission, particularly in secondary aluminium production [6]. It is important to measure these emissions not just for the purpose of reporting to the authorities, but also to monitor the effects of implementations made towards reduction of fugitive emissions and improvement of working conditions.

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_99

735

736

H. A. H. Olsen Myklebust et al.

Fig. 1 Schematic of the material flow among the smelting process, gas treatment centre and emissions [4]

Current Monitoring Systems The traditional system for monitoring fugitive emissions is capturing of dust through filter systems. The simple setup consists of tubes and pumps that allow the air from the potroom to be iso-kinetically lead through a filter which collects the dust. After a set period the dust is measured and can be analysed, which can provide accurate monitoring of its content. It does however give a low time-resolution and it would be very expensive to map an entire facility to account for spatial variance. Technology for measuring dust levels through visual telemetry is also under development, with plans for constant measurement of hydrogen fluoride gas, SO2 , and CO, but is still not widely used [7].

The Use of Micro-sensors Low-cost microsensors are not widely in use neither in the aluminium industry, nor yet for air-pollution monitoring in general and industry in particular. It is however being considered by the European Commission for air pollution monitoring and personal exposure, and with the technological improvements could become a “game changer” [8]. The technology is rapidly evolving, and both the sensors themselves and the framework (such as microchips and power supplies) needed to facilitate their use, is growing smaller and cheaper. Small sensor systems, while less accurate and with higher uncertainty than reference systems, can already provide reliable coarse information after calibration and quality data assurance [9].

through the study to improve our knowledge of the dynamics in the generation and emission of pot room dust, especially with regards to which operations produce the most dust, and which size fractions these dusts fall into. The system used in this work was set up to measure PM10 and PM2.5 along with temperature and relative humidity, and each sensor system delivers a value for each of these parameters every 5 s.

Sensor Setup Figure 2 shows the sensor system used in this work. The system consists of two sensors and a microchip which collects and forwards the data to a central server, all contained in a 3Dprinted PVC box which measures around 13 * 10 * 4 cm. The Nova PM SDS011 sensor reports the concentration of PM10 and PM2.5 in µg/Nm3 , while the HTU21D reports temperature in ◦ C and relative humidity. Air from outside the box is sucked into the dust sensor through a short 2 mm diameter tube, while the temperature and humidity sensor is placed on

Project Goals The primary goal of the current study is to investigate the reliability and usefulness of a system based on microsensors in monitoring fugitive emissions from primary aluminium production. The secondary objective is to use the data generated

Fig.2 Schematic of the setup prototype. Shows the dust sensor (PM sensor), temperature and humidity sensor (T/H), the the microchip (Chip), and the sampling inlet for dust (Sampling inlet)

737

Measurement System for Fugitive Emissions in Primary …

the outside of the box where it measured the ambient air. The complete setup runs on standard 5 V 1 A current which can be supplied through power cables or batteries depending on preference. Weather data were taken from a weather station on the aluminium plant and used as background data for the measurements. The dust sensor uses the laser scattering principle to measure the concentration of fine particles [10], while the humidity is measured through change of capacitance and temperature though changing resistance. The system measures continuously and provides a snapshot of these values approximately every five seconds. The data is transferred through local WiFi, and the sensors can as such be spread across as large an area as a single network can cover. In this work, the sensors were placed in groups of four at three different positions inside a Robertson roof monitor (A natural draft roof ventilator which funnels the air out while stopping rain, marked in Fig. 3), one in the center, and one halfway to each side along the same axis as the production cells are placed. This roof monitor room is 9.75 m long and is located 12 m above the hall floor. Fumes from the processes of several cells pass through here as shown in Fig. 3. Sensor 1–4 are placed in the middle, sensor 5–8 to the left and sensor 9–12 to the right, relative to a person standing in the middle and looking towards the sensors, with a distance of 2.4 m between each group as well as the end walls as shown in Fig. 4. The end result is a file with data points for time, PM10, PM2.5, humidity, and temperature, for each sensor over the course of each day. Afterwards, the data is aggregated to an average value over each minute, allowing for standard deviations across the sensors in each group to be calculated.

Results Basis for the Data For the purpose of this work, data from two dates were chosen. On the first day, the weather was hot with temperatures reaching almost 30 ◦ C after noon, while on the second day the temperature never exceeded 20 ◦ C. Both days had periods of rain, which is shown alongside the temperatures in Fig. 5. Figure 6 shows the mean temperature and humidity values for sensor 1–4 for both days. The connection between rain, and humidity is very notable, especially around 18:00 on the first day and 11:00 on the second day. The same can be said for the temperature indoor and outdoor. No statistically significant correlation between temperature and dust nor humidity and dust was found.

Dust Load Variation, Size Fraction and Process Events Figures 7 and 8 show how the dust concentrations vary over the course of the two days as measured by the middle group of sensors. 3 periods are highlighted in Figs. 8, and 9 shows the difference in size fractions between these highlighted peaks. 18 lines labeled (a)–(r) refer to the actions listed in Table 1. From this example alone, it is clear that different distinct operations within the plant produces different size fraction of fumes. Subtracting PM2.5 from PM10 gives the concentration of the larger particles, and that is the value used in Fig. 9. For the two smaller peaks the fraction of larger particles is around than 80%, while the larger peak from before noon has more than 60% of small particles for the most part. Table 1 shows the recorded actions that were performed during these two days on the two cells just below the sensors, and each actions has a label referring to the lines shown in Figs. 7 and 8. The three peaks highlighted in Fig. 8 corresponds clearly with three events performed on cell 148: The anode changed started 10:39, the covering after the exchange at 14:54, and the covering of the measurement hole at 20:29. This tells us that the anode exchange produces far more of the finer particles compared to the two covering processes.

Deviation from Sensor Location

Fig. 3 Locations of the sensors marked with an arrow above the electrolysis cell rows, inside the Robertson roof monitor

Figure 10 shows the mean values of PM10 for each of the three groups for one hour on the second day. The values for the rightmost group (sensor 9–12) is clearly higher in the beginning of the 3 o’clock peak with the leftmost group (sensor 5–8) shows the lowest values. After 3 o’clock it is the opposite however, with the leftmost group (sensor 5–8) having the largest values. In both these peaks, the middle group

738

Fig. 4 Locations of the three sensor groups inside the Robertson roof monitor

Fig. 5 The temperature and rain rates over the course of the two days. Data taken from a weather station on site

Fig. 6 Mean values of temperature and humidity for sensors 1–4 with 95% confidence intervals for both days

H. A. H. Olsen Myklebust et al.

739

Measurement System for Fugitive Emissions in Primary …

Fig. 7 Mean values of PM10 and PM2.5 for sensors 1–4 over the course of the first day. 95% confidence intervals are shown as a shaded area above and below the mean values. The lines labeled a–i refer to the actions listed in Table 1

(sensor 1–4) measures values between the two outer groups. Just after 03:30 there is another peak where the middle group is clearly higher than the two on the side. The 95% confidence intervals between the group measuring the lowest and the highest at each peak do not overlap at all. This lets us conclude that there is a statistically significant difference in the measurements based on the location of the sensors with the groups being only meters apart.

Statistical Reliability Figure 11 shows the dust measurements for sensor 1–4 over a couple of peaks together with their mean value. There is some variance between the sensors, but by having 4 sensors together we achieve a generally small 95% confidence interval. The confidence interval ranges from close to zero to ±130 µg/Nm3 , with a mean for the period being ±18.5 µg/Nm3 . The mean 95% confidence interval for the entire day is only ±6.5 µg/Nm3 , and it is clear from the figure that the variance increases mostly where the values and the change of value over time is large. It can also be seen that it is the same sensors that measure below and above average

respectively, which points to inherent variations between the sensors. Unlike random variations, this is possible to compensate for through calibration and benchmark testing.

Discussion The results indicate the reliability of the data gathered, and the importance of having multiple sensors in each group as well as several points to measure the variance across an area, but more importantly they show how much the fugitive emissions change over the course of a day in the electrolysis hall. They also show a large difference in dust particle size fractions across different peaks, clearly displayed in Fig. 9. The different peaks can be correlated to events in the production, which allows for comparisons of the dust formation from the different operations. For example, the anode change was shown to produce a much larger fraction of fine dust compared to the covering operations afterwards. This information can be readily accessible from the affordable sensor system (99% of the total fluoride emission before the off gas is released into the environment [2]. Total fluoride evolution from an aluminium smelting cell can be broadly classified into the following two categories [3]: (1) Gaseous fluorides, where the major fluoride gas of concern is hydrogen fluoride gas (HF) (2) Particulate fluorides, made up of volatilized and condensed bath mainly in the form of sodium tetrafluoroaluminate (NaAlF4), entrained bath (liquid droplets that subsequently solidify), and entrained solids (including bath and non-bath material such as alumina/carbon particulates with adsorbed HF or solidified bath). The ratio of gaseous to particulate fluoride varies depending on sampling location and method. Primary generation of fluoride emissions occurs at the cell, and most of this is captured by the fume extraction system and sent to the gas treatment centre (GTC), while the balance is lost into the potroom as fugitive emissions. Before the captured off gas is released to the environment, the GTC is used to scrub HF gas by adsorption onto alumina, then to capture the fluoride-loaded secondary alumina and other particulate fluorides at the baghouse using filter bags. While HF gas can be captured onto alumina, it can also potentially be generated from this secondary alumina and other particulate fluorides through a hydrolysis reaction with humidity in the gas stream. It has been hypothesised that this chemical generation of HF gas at the filter bags is responsible for the sensitivity of injection type dry scrubbers to GTC inlet gas temperature and humidity, particularly in

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_101

751

752

summer months and hot/humid locations. For example, published smelter data such as Robin et al. [4] clearly shows HF gas emission to closely track GTC inlet temperature. Sorhuus and Ose [5] discussed HF emissions from two similar GTC technologies located in the Middle East and Norway. In this study, GTC stack HF emissions was found to be higher in the Middle East versus Norway, despite both operating with the same GTC inlet temperature range (100– 110 °C). This difference was attributed to the higher absolute humidity in the Middle Eastern location. In a study by Heiberg et al. [6], used filter bag samples were collected from a pilot scrubber and the effects of temperature (80–125 °C) and humidity (2–30 g H2O/kg dry air) on HF generation were studied in the laboratory. This showed that HF emission increases with increasing humidity and/or temperature, and as temperature exceeds 110 °C, a sharp increase in HF emission is observed. Through measuring HF emission at a filter compartment outlet of a GTC fitted with a heat exchanger that allows control of the GTC inlet gas temperature, Qassab et al. [7] obtained a similar curve showing in more detail the relationship in the temperature range 111–120 °C. Combining results from these two studies, Qassab et al. [7] concluded that while a moderate increase of HF emission was observed when GTC inlet gas temperatures are below 100 °C, as the temperature increases above 115 °C, HF emission is expected to increase in an exponential fashion. While the relationship between HF emission with gas temperature and humidity has been clearly established through previous studies of smelter operational data and experimental work as discussed above, these results describe the summation of possible HF generation from all particulate fluoride phases, minus any subsequent HF scrubbing by alumina particulates present in the sample. Although HF-enriched alumina (secondary alumina) is itself a potential HF generation source and a major form of particulate fluoride in the GTC system, it is also an excellent HF gas scrubbing material and consequently must be excluded to be able to accurately test the HF generation potential of other particulate fluoride phases. Therefore, the aim of this research is to first study the HF generation potential of individual particulate fluoride phases in the absence of alumina. To achieve this, various particulate fluorides (purchased or lab generated) known to be present in cell emissions were tested under controlled laboratory conditions.

J. H. Hung and J. B. Metson

and aluminium fluoride (AlF3), at a 1:1 molar ratio of NaF: AlF3 as suggested by Howard [8]. This was loaded in a carbon crucible and heated to 990 °C. A schematic drawing of the setup is shown in Fig. 1. The interior of the retort can is regarded as the ‘hot zone’ where the temperature is  800 °C. The condenser is constructed by an arrangement of 3/4” carbon steel pipes and steel elbow fittings. The condenser is naturally cooled while the lid of the retort can is water cooled. Temperature of the condenser ranges from *100 °C at the connection to the lid down to *40 °C at the elbow furthest away from the inlet; the entire condenser is therefore regarded as the ‘cold zone’. A stainless-steel gas purge rod is used to deliver nitrogen flow (>99.99% pure industrial grade N2 gas) to protect the carbon crucible from oxidation and to sweep vapours from the molten bath mixture from the hot zone to condense in the cold zone. The furnace is kept running for 1 week at a time. Each sample of condensed fume collected throughout the week is weighed, checked for phase distribution (via X-Ray Diffraction), combined when necessary to form a standard sample charge of 1 g or a larger batch of fume, and is used as the raw material for HF generation experiments the following week.

HF Generation Rig The HF generation rig consist of three main parts: a gas humidifier, fixed-bed reactor, and a Tunable Diode Laser (TDL) HF gas analyser. Nitrogen gas is humidified through a Perma Pure MH-110-SS tube-in-shell moisture exchanger made from a stainless-steel shell and a Nafion™ tube. Humidity level is adjusted by controlling the temperature of the humidifier and/or the gas flowrate through the humidifier. When carrying out HF generation experiments, a standard charge of 1 g of particulate sample is reacted with humidified nitrogen gas (500 cm3/min, 27 g H2O/kg N2) in a fixed-bed reactor (stainless steel, 35 mm ID and 15 mm tall). The particulate sample is spread on top of a generic filter bag cut-out disc (polyester needlefelt fabric) to mimic filter cake in the baghouse. The reactor unit and all associated fittings are installed inside an oven allowing control of the reaction temperature (set to 140 °C unless otherwise stated). HF concentration in the off gas is continuously measured in a gas cell (1 m path length) using a Boreal Laser GasFinder™ 2.0 HF monitor. HF exiting the gas cell is then captured in a solution of calcium hydroxide.

Methodology Phase Analysis Using XRD Condensed Fume Generation and Collection Condensed bath fume is generated in the laboratory by preparing a charge of bath—consisting of cryolite (Na3AlF6)

X-Ray Diffraction (XRD) is used for phase identification and composition analysis of the crystalline components in the laboratory generated fume samples. Scans were carried out

A Laboratory Study of the HF Generation Potential …

753

Fig. 1 Schematic drawing of the fume collection setup. Condensed fume is collected from the four locations as labelled

using a Rigaku Miniflex II diffractometer (monochromatic Cu-Ka radiation, 30 kV, 15 mA), in the 2h° range 10–80°. Phases present were identified using Bruker AXS EVA software, while phase compositions were determined with the Bruker EVA S-Q quantification method. It should be noted that compositions obtained using this method are relative and semi-quantitative in nature.

Results and Discussion Phase Composition of Generated Condensed Fume Condensed fume particulates were collected from four different locations in the fume collection set up as indicated in Fig. 1. The three main bath phases identified through XRD analysis were: NaAlF4, chiolite (Na5Al3F14), and AlF3. The distribution of bath phases in fume samples collected from these four locations is dependent largely on the location temperature and is summarised in Table 1. The main component of bath vapour is NaAlF4, which condenses into a fine, fluffy powder and is stable in normal (ambient) conditions in air [9]. When heated above 400 °C, it is expected to thermally decompose, undergoing a solid phase transformation to form chiolite and AlF3 [8, 9]. For this reason, material collected from inside the retort can (location 1, where temperature is  800 °C) has a composition of  90% chiolite with the rest being AlF3. Although the entire condenser assembly is well below 400 °C, fume collected

from the condenser inlet (location 2), which is a transition area from the ‘hot zone’ to the ‘cold zone’ consists of all three phases with greater variability between batches, typically 10–70% NaAlF4, 20–70% chiolite, and 5–20% AlF3. Fume collected from the condenser elbow after the inlet (location 3) and from the condenser pipe (location 4) also consists of the three bath phases (NaAlF4, chiolite and AlF3). In addition, two polymorphs of ferrous fluoride (FeF2) are also identified through XRD analysis. FeF2 Type 1 (JCP2.2CA:00-045-1062) is the common form of FeF2 with a tetragonal crystal structure, commercially available in high purity through a number of chemical vendors (CAS Number: 7789-28-8), while Type 2 (JCP2.2CA:00-003-0143) is a much less common form of FeF2, with undefined crystal structure. XRD patterns of a lab generated, ferrous fluoriderich fume sample (4% NaAlF4, 22% FeF2 Type 1 and 60% FeF2 Type 2), analysed before and after HF generation experiment are shown in Fig. 2. It can be observed that after HF generation experiment, the intensity of FeF2 Type 1 peaks increased while the intensity of FeF2 Type 2 peaks significantly diminished. Type 2 FeF2 was later found to be the dominant phase responsible for HF generation through hydrolysis in our laboratory experiments to date. The generation of ferrous fluoride phases occurs through reaction between fluoride in the off-gas and the iron-rich surface of carbon steel pipe and elbow. Ferrous fluorides are observed in higher percentages in the earliest samples collected after furnace heat up (an example is fume sample in Fig. 2), where the contact time between the condenser pipe and off-gas is greater due to the low N2 purge rate and

754

J. H. Hung and J. B. Metson

Table 1 Typical fluoride phase distribution in fume samples collected from the four locations of the condenser as indicated in Fig. 1 Typical fluoride phase distribution (wt%)a

Location

Sodium tetrafluoroaluminate (NaAlF4)

Aluminium fluoride (AlF3)

Ferrous fluoride (FeF2) Type 1 (common)

Type 2

(1) Retort can

–

*90%

*10%

–

–

(2) Condenser inlet

10–70%

20–70%

 20%

–

–

(3) Condenser elbow

 70%

 20%

 10%

0

8 volts)

CF4, ppm Ave (Total)

LVAE/HVAE

% LVAE

Bag 1

3

39.4

0.66

0.0025

0.010

3.00

75

Bag 2

4

1502.2

25.04

0.0255

0.036

0.41

29

Bag 3

5

161.6

2.69

0.0036

0.013

2.61

72

Bag 4

3

27.4

0.46

0.0017

0.008

3.71

79

Bag 5

9

83.8

1.40

0.0035

0.008

1.29

56

Bag 6

9

347.2

5.79

0.0093

0.018

0.94

48

Bag 7

21

577.4

9.62

0.0200

0.029

0.45

31

Total

54

Average

0.009

0.017

Average

56

Figure 2 shows the low voltage PFC emissions varies between 0.008 ppm CF4 (8 ppb) to a maximum of 0.051 ppm CF4 (51 ppb). However, there is no significant increase or decrease during the 24-hour bag #2 was collected. Most important is the presence of a pot start on April 5 at 8:14 am, which contribute to be the highest CF4 concentration of all gas bags from Plant A. The ratio of Low Voltage/High Voltage emissions (LVAE/HVAE) and % contribution of Low Voltage emissions from Total PFC emissions can be calculated using FTIR #2 results as follows: LVAE/HVAE ¼ ð0:036  0:0255Þ=0:0255 ¼ 0:41 % LVAE ¼ ð0:036  0:0255Þ=0:036  100 ¼ 29% Figure 3 shows more variability of low voltage PFC emissions with a low value of 0.003 ppm CF4 (3 ppb) to 0.041 CF4 (41 ppb) with an increase trend from 0.014 ppm CF4 (14 ppb) at 14:00 pm on April 27 to 0.041 ppm at 3:00 am on April 28 during the 48-hours bag # 2E was collected.

Note that only two high voltage anode effects were observed with a total duration of 4.02 min. The ratio of Low Voltage/High Voltage emissions (LVAE/HVAE) and % contribution of Low Voltage from Total PFC emissions can be calculated using FTIR #2 results as follows: LVAE=HVAE ¼ ð0:027  0:0038Þ=0:0038 ¼ 6:11 % LVAE ¼ ð0:027  0:0038Þ=0:027  100 ¼ 86% Similarly, as shown in Tables 5 and 6, LVAE/HVAE ratio and low voltage percentage % LVAE were calculated for all other gas bag samples. It is noticeable the high variability of low voltage PFC emissions percentages from a low value of 29% to a high value of 79% in plant A, and from a low value of 52% to a high value of 91% in plant B. Average values of 56 and 80% low voltage emissions from plants A and B, respectively, are shown in both tables and confirmed the significant contribution of low voltage emissions to total PFCs.

764

L. Espinoza-Nava et al.

Fig. 3 Continuous CF4 measurement results for gas bag # 2E at plant B (Note two HV anode effects are labeled ‘AE’)

Table 6 Anode effects during gas bags collection and Low Voltage PF C emissions calculation from plant B PlantB Bag 1 D (East)

# AE (>8 volts) 6

AED (sec) 79.4

AED (min) 1.32

CF4, ppm Ave (> 8 volts)

CF4, ppm Ave (Total)

0.0039

0.041

LV/HV 9.51

% LVAE 90

Bag 2 D (East)

8

171.8

2.86

0.0064

0.033

4.16

81

Bag 3 D (East)

16

1510.6

25.18

0.0391

0.082

1.10

52

Bag 1 E (North)

8

352.4

5.87

0.0126

0.037

1.94

66

Bag 2 E (North)

2

241.4

4.02

0.0038

0.027

6.11

86

Bag 3 E (North)

2

36.8

0.61

0.0027

0.031

10.48

91

Bag 5 E (North)

2

28.4

0.47

0.0023

0.023

9.00

90

Average

0.010

0.039

Average

80

Total

44

Conclusions Evidently, as observed in this work, there is no clear and consistent correlation between high voltage (HV) anode effects and low voltage (LV) emissions, as many factors affect the low voltage PFC emissions. An attempt was made to assess the variability in low voltage emissions, where we calculated the ratio of LV/HV emissions and total PFC emissions using gas bags over one week sampling periods. These showed a high daily variability in low voltage emissions. However, an average LV/HV emissions ratio and/or % LV PFC emissions can be used as an initial method to estimate total PFC emissions. It is our intention to extend the sampling over longer periods that include specific pot room conditions that could increase the low voltage PFC emissions. The method of using continuous FTIR to determine slope factors will continue to be used in the next few years until regulations are in effect in those regions with a cap and trade scheme but low voltage emissions must be added [20]. The industry is looking for affordable methods to calculate the total PFC emissions and the addition of gas bags and canisters with GC-MS will be the cheapest alternative. In addition, continuous Quantum Cascade Laser (QCL) technology monitors might provide an alternative measurement of total PFC emissions but these still need to be tested and

compared with other techniques to assess whether this is a cost-effective option if the plant has few stacks [21]. Nevertheless, it is imperative that the industry should join efforts to understand the limitations and current changes of the latest IPCC 2019 Refinement to the 2006 IPCC Guidelines for PFC accounting, and work together to find technologies that will provide accurate PFC inventories.

References 1. Intergovernmental Panel on Climate Change (2006), 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 3 Industrial Processes and Product Use, Chapter 4, Metal Industry Emissions, available at http://www.ipcc-nggip.iges.or.jp/public/ 2006gl/vol3.html, October 2006. 2. The Aluminum Sector Greenhouse Gas Protocol (2006). Greenhouse Gas Emissions Monitoring and Reporting by the Aluminum industry. https://ghgprotocol.org/sites/default/files/aluminium_1. pdf. 3. US EPA and IAI (2008) Protocol for Measurement of Tetrafluoromethane (CF4) and Hexafluoroethane (C2F6) Emissions from Primary Aluminum Production, available at http://www.epa.gov/ aluminum-pfc/documents/measureprotocol.pdf. 4. IPCC (2019) 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 3, Chapter 4 Metal Industry Emissions, Section 4.4: Primary Aluminium Reduction, available at https://www.ipcc-nggip.iges.or.jp/public/2019rf/index. html.

Method Development to Estimate Total Low Voltage … 5. J. Marks, P. Nunez (2018) Updated Factors for Calculating PFC Emissions from Primary Aluminum Production, Light Metals 2018, pp 1519–1525. 6. J Marks, P. Nunez (2018) New Algorithm for Calculating CF4 Emissions from High Voltage Anode Effects, Light Metals 2018, pp 1479–1485. 7. L. Dion, S. Gaboury, L. Kiss, S. Poncsak and C. Lagace, (2018) New Approach for Quantification of Perfluorocarbons Resulting from High Voltage Anode Effects, Light Metals 2018, pp 1469– 1477. 8. N. Dando, N. Menegazzo, L. Espinoza-Nava, N. Westendorf and E. Batista, (2015) Non-Anode Effect PFCs: Measurement Considerations and Potential Impacts, Light Metals 2015, pp. 551–554. 9. D. Wong, A. Tabereaux, and P. Lavoie (2014) Anode Effect Phenomena During Conventional AEs, Low Voltage Propagating AEs and Non-Propagating AEs, Light Metals 2014, pp. 529–534. 10. A. Zarouni, M. Reverdy, A. Al Zarouni and K. Venkatasubramaniam (2013) A Study of Low Voltage PFC Emissions at DUBAL, Light Metals 2013, pp. 859–863. 11. J. Thonstad and S. Rolseth, (2017) Low Voltage PFC Emissions from Aluminium Cells, Journal of Siberian Federal University. Chemistry 2017, 10(1) 30–36. 12. A. Jassim, S. Akhmetov, B. Welch, M. Skyllas-Kazacos, Jie Bao and Yuchen Yao, (2015) Studies on Background PFC Emission in Hall-Héroult Reduction Cells Using Online Anode Current Signals, Light Metals 2015, pp. 545–550. 13. W. Li, X. Chen, J. Yang, Y. Liu, D. Li and H. Guo (2012) Latest Results from PFC Investigations in China, Light Metals 2012, pp 619.

765 14. J. Marks, C. Bayliss (2012) GHG Measurement and Inventory for Aluminum Production. TMS Light Metals 2012, pp 805. 15. E. Batista, N. Dando, N. Menegazzo and L. Espinoza-Nava (2016) Sustainable Reduction of Anode Effect and Low Voltage PFC Emissions, Light Metals 2016, pp 537–540. 16. E. Batista, L. Espinoza-Nava, C. Tulga, R. Marcotte, Y. Duchemin, and P. Manolescu (2018) Low Voltage PFC Measurements and Potential Alternative to Reduce Them at Alcoa smelters, Light Metals 2018, pp 1463–1467. 17. Thermal Desorption Technical Support reference, note 77: Using Thermal Desorption for Industrial (Stack) Emission Testing, Markes International, April 2009. 18. B. Miller, R. Weiss, P. Salameh, T. Tanhua, B. Greally, J. Muhle, and P. Simmonds, “Medusa: A Sample Pre-concentration and GC-MS Detector System for in-situ Measurements of Atmospheric trace Halocarbons, Hydrocarbons, and Sulfur Compounds, Anal Chemistry 2008, 80, 1536–1545. 19. P. Fraser, P Steele and M. Cooksey (2013) PFC and Carbon Dioxide Emissions from an Australian Aluminum Smelter using time-integrated stack sampling and GC-MS, GC-FID analysis, Light Metals 2013, pp 871–876. 20. C. Dubois, L. Espinoza Nava, and E. Batista (2019) Validation of PFC slope at Alcoa Canadian smelters with anode effect assessment and future implications to add low voltage emissions into total PFC emissions, Light Metals 2019, pp 849–855. 21. L. Espinoza-Nava, N. Menegazzo, N. Dando and P. Geiser (2016) QCL-based Perfluorocarbon Emission Monitoring, Light Metals 2016, pp 541–544.

Update on SO2 Scrubbing Applied in Primary Aluminium Smelters Stephan Broek

Abstract

This paper presents an update on SO2 scrubbing in the primary aluminium industry. Discussed is how sulfur enters the electrolysis process. It starts with calcining cokes with explanations why full desulfurization during calcining is not pursued. This means the throughput of sulfur must be managed within smelter operations. To provide insight in where the sulfur goes a mass balance is presented for a generic 500 ktpa smelter. Based on this sulfur emissions can be managed with or without scrubbing. Some scenarios are discussed that don’t need scrubbing but for when scrubbing is required, an overview of the options is presented. Keywords

Primary aluminum SO2 scrubbing




Sulfur dioxide




Emissions




Introduction The main air pollution control systems in primary aluminium smelters are focused on control of particulates and fluorides. Generally, only some smelters apply additional control systems to abate the emissions of sulfur, primarily in the form of sulfur dioxide (SO2). This is driven by specific conditions, like in Norway, or by cumulative ground level concentrations where the aluminium smelter emissions do elevate the SO2 concentrations. To avoid exceedances, SO2 controls are put into place, like in Qatar and the UAE. Presently, an unprecedented wave of installation of SO2 control systems is taking place in China where the central government has taken a stance against air pollution by heavy industries including the primary aluminium industry. The S. Broek (&) Center of Excellence for Aluminium, Hatch Ltd., 2800 Speakman Drive, Mississauga, L5K 2R7, ON, Canada e-mail: [email protected]

result is that for these “26+2” municipal areas of the 28 cities, it has imposed new stack limits of 35 mg/Nm3 of SO2 from aluminium operations. The equivalent sulfur content of baked anodes would be around 0.25 wt% and it is safe to say that because of this it cannot be abated by changes in raw materials or processes so many SO2 control systems are being built in addition to the scrubbing systems for fluorides and particulates. Unlike dry scrubbing for fluorides, control systems for SO2 are primarily regarded as a pure cost to the bottom line. It means that smelter operators are trying to fend off having to install SO2 control systems if they can and with ongoing LME price levels that are too low for the true value of the metal, this is understandable. Emissions standards in jurisdictions like the US and Canada may also change with new rules leading to more SO2 control systems being implemented also in aluminium smelters. There are very few publications that have smelter SO2 emissions as the main topic. The last in-depth paper was published in 2009 [1] so it is overdue to provide an update on SO2 control in aluminium smelting. Managing SO2 emissions is mainly done by managing raw materials so there the paper begins. It finishes with a closer look at current SO2 control technologies.

Raw Materials All sulfur emissions from a smelter are linked to raw materials including fuels. If a mass balance for sulfur is drawn up, the following raw materials are considered: 1. 2. 3. 4. 5.

Calcined cokes Pitch Fresh and reacted alumina Fuel used in furnaces Fuel used in vehicles on-site.

These are discussed individually in the next sections.

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_103

766

Update on SO2 Scrubbing Applied …

Calcined Cokes The review should start at the production of calcined cokes. Often the question is asked if cokes should be calcined at higher temperature to drive off the sulfur before it arrives at the smelter. Petroleum cokes are the raw materials for the companies that produce calcined cokes. They obtain them from oil refineries where the material is left over after all usable fractions have been refined. Because the quality of the petroleum coke is highly dependent on the type of crude oil, different coke qualities are available on the market (Fig. 1). However, some important trends are that average sulfur and vanadium contents are rising year over year, and that the supply of low sulfur petroleum coke is generally expected to decline. At the same time there is an increasing demand from other applications. Petroleum cokes can technically be desulfurized using hydrogen, but this is very expensive, so the material is passed on to calciners “as is”. Calcination of petroleum coke is required for three key reasons. First, to drive of volatiles and make coke solid like rock. Second, to make the cokes conductive to pass through the electric current, and lastly, to make coke dimensionally stable with increased density. It is achieved by directly exposing the cokes to high temperatures inside a kiln. It is well known that the calcination process also drives off (besides volatiles) between 9 and 13% of the sulfur in the form of SO2. Experiments show that this is a function of the temperature and at very high temperatures additional sulfur is driven off through the process of thermal desulfurization [2]. Because the volume of combustion gases from a kiln is relatively small, the SO2 concentrations are high. This is advantageous for SO2 scrubbing because a significant portion of the cost is driven by the volume of gases passing through the scrubbing systems. Although SO2 scrubbing Fig. 1 Relationship between sulfur and vanadium in multiple sources of cokes [3]

767

always adds to the costs, it is more efficient to scrub a low volume, high concentration flue gas stream vs a high volume, low concentration stream. In coke calcining plants the technology of choice is mainly a dry SO2 scrubbing process (Fig. 2). In the US, Canada and India this is the main control technology that is used. It often includes a circulating type reactor to enhance the SO2 removal and optimization of the use of lime. For this it would be an argument to say that the calciners should maximize the desulfurization that takes place. For illustration purposes, the calcined coke target would be 0.25 wt% S to meet a stack concentration from gas treatment centres (GTCs) in the aluminium smelter of 35 mg/Nm3 with liquid pitch at 0.5 wt% S. Considering the above, there are two important reasons why this practice is not pursued. First, by driving off the sulfur the density of the calcined coke decreases (Fig. 3). The sulfur left in the coke is embedded and when released by the higher temperatures it passes through from inside to outside in gaseous form. This creates pores that ultimately lead to lower densities. And lower densities are working against the production targets to give baked anodes a high density for the best results. The value loss of not being able to reach target baked anode densities (BAD) is far greater than the benefit of driving of the sulfur during calcination. The basis for the behavior of coke as presented in Fig. 3 is a standard rotary kiln. Some improvement is possible when coke is calcined using vertical shaft calciner technology developed in China. At moderate sulfur losses of 20– 30%, a shaft calciner produces an acceptable bulk density product. At higher levels of sulfur losses, however, the calcined petroleum coke (CPC) starts to suffer a significant deterioration in bulk density and strength. Trying to achieve a target of 0.25 wt% S in the CPC product may be technically possible but would result in unacceptably poor CPC and anode qualities.

768

S. Broek

for smelter operations as it saves on the use of carbon and thus also reduces the ultimate intake of sulfur in a smelter. As a result, current calcined coke specifications commonly have both a minimum and maximum specification for the sulfur content. Most smelters prefer to take coke with a sulfur level close to the specification maximum to control/reduce anode reactivity. To manage the sulfur inside the aluminium smelting process, calcined cokes typically have sulfur contents that are in range of 1.8–3.5 wt% S.

Pitch

Fig. 2 CDS type scrubber installed by rain carbon [3]

Second, in the reduction process a small amount of sulfur is required. The sulfur in anodes reduces the loss of carbon by airburn by mitigating the catalytic effect of sodium and vanadium that is present. It also reduces the loss by CO2 burn by mitigating the catalytic effect of both calcium and sodium that is present. Reducing these losses is a great value

Fig. 3 Coke real density versus calcination temperature for cokes with different S contents [4]

Pitch is the glue that binds the calcined coke to produce anodes and is delivered either in solid or liquid form. Pitch is formed during the coking process of metallurgical coal in integrated steelworks. It is volatile and vaporizes. Because the coke ovens are indirectly fired the volatiles can be extracted and condensed into liquid pitch. The pitch is sold onto the market. This is a simple description with the purpose to state that there is nothing that can be done to influence the sulfur content. Because the sulfur content of pitch is low (0.4–0.6 wt%) and very stable, this material is not on the radar for any changes. During production of green anodes, the paste is heated and that leads to some of the pitch to volatilize. In order to capture this a conventional technology is the use of coke fines and inject these in the fumes laden with pitch fumes. The pitch fumes condense onto the coke particles or the coke

Update on SO2 Scrubbing Applied …

769

removes it from the surfaces of ducts if pitch condenses there. All in all, the fumes are taken to a baghouse where everything is filtered out and send to the bins for raw materials to prepare the recipe for green anodes. Because there is no combustion taking place, no SO2 will release from the pitch. This is different when the pitch fumes are combusted. Today, we see more and more regenerative thermal oxidizers or catalytic oxidizers being used to seek full combustion of pitch fumes. In those cases, SO2 will be formed from the sulfur that is within the pitch. The amounts are small; however, they are still independent emission points that have to be accounted for. Some of the pitch will release from green anodes during the anode baking process. When anodes are heated and go through the range of 400–550 °C a fraction of the pitch volatilizes and escapes into the flues. There it will combust and with modern combustion technology the level of combustion is almost complete. This means that the sulfur in the pitch contributes to the SO2 that is found in the fumes from the anode baking furnace.

what is generated in the pots minus what escapes into the potroom during production.

Fresh Alumina

Fuel Used in Furnaces

The alumina is a source for sulfur in the process because of the way it is calcined in the alumina refinery. It is known that alumina adsorbs SO2 and in the calcination process it is exposed to the combustion gases from the fuel that is used. Any small amounts of SO2 are caught by the alumina and carry forward to the smelter. The technical specifications typically show that 300 ppm of sulfur (as SO3) is present. One can understand that once the alumina has dissolved into the liquid bath that this sulfur is released as SO2 and becomes part of the pot exhaust gases.

Any fuel that is used in a combustion process will see the sulfur it contains form into SO2 and into small amounts of SO3 gas. Natural gas is in almost all cases pre-treated and has only 2–5 ppm H2S in the spec and is not considered a main source after the H2S burns to SO2. However, in a few cases heavy oil is used to bake anodes and then the sulfur output is considerably higher. Fuel oil may contain up to 3 wt% S. While the amount of SO3 leaving the stack of the fume treatment center in the anode baking furnace is benign (it is captured by the alumina), it is important to note its existence in the raw fumes. When an evaporative cooling tower is used, the fumes are cooled down to about 105 °C. Depending on the concentration of SO3, this temperature can be below the dew point and in that case the SO3 forms a fine mist of droplets (also identified as sulfuric acid mist). These are sticky in nature and easily can adhere to the internals of the cooling tower and ducts. Liquid SO3 is highly hydroscopic so it will draw water vapor into the droplets to form sulfuric acid (H2SO4), which is corrosive in concentrations below 70 wt%. We see the effects when the evaporative spray no longer fully vaporizes and that results in corrosion of the cooling tower. The presence of HF also does not help. The same phenomenon can occur in stand alone anode baking furnaces. These typically don’t use alumina dry scrubbers with evaporative cooling towers because they don’t have the alumina available. Instead, these use regenerative thermal oxidizers (RTO) to combust any tars and

Reacted (or Secondary) Alumina As mentioned above, alumina has the ability to adsorb SO2. Recently more insights were presented on how this takes place inside the alumina dry scrubbing process [5]. When the fresh alumina is passed through the GTC then it is exposed to a considerable amount of SO2 and the amount of SO2 captured is a function of how much HF is captured in parallel (Fig. 4). HF is a gas that reacts very strongly with the alumina thereby displacing the SO2 that is only adsorbed to the surface. As a result, the alumina can contain between 0.08 and 0.25 wt% S that is all released in the electrolysis process. It also means that a recycle takes place between pots and GTC so that the concentration in the GTC inlet gases is elevated. Net, the amount discharged from the GTC stack is

Fig. 4 Experimental data plotted against the proposed empirical model to predict adoption of SO2 on SGA [5]

770

other volatiles. In some cases, SO2 scrubbing is an additional requirement and in one case the RTO produced high SO3 amounts leading to a large concentration of SO3. The SO2 scrubber after the RTO cools the gases to well below the dew point and a large amount of SO3 is then condensed into a mist. The problem with this mist is that it is so fine (*10– 50 microns in size) that almost all of it passes through the SO2 scrubber resulting in the mist being discharged from the stack. Here a specific problem occurs when the sunlight shines through the SO3 mist. The light diffraction is such that a blue color can be seen. In other words, the stack discharges a blue haze. To eliminate this, the SO2 scrubber can be equipped with a wet electrostatic precipitator (WESP) which works well but is very expensive because it is made from special steels.

Fuel Used in Vehicles Engines in vehicles run on the combustion process so when fuel is combusted the result is that any sulfur is emitted as SO2. Most fuels, however, are very low in sulfur content so this fugitive emission is considered negligible. When permits ask to report it, it is generally not measured and reported based on fuel consumption.

Other Processes that Result in SO2 Emissions Described above are the raw materials and how the sulfur is released by the use of those raw materials. In most cases this results in SO2 emissions. However, there are some further process steps in aluminium smelting that result in the sulfur to be converted to SO2. To complete the full picture, these are discussed in the next sections.

S. Broek

in bad situations the actual anodes are exposed to the combustion gases. In that case also some coke from the anode is burned and the sulfur becomes SO2 that is the final contributor to the SO2 in the fumes. Because of the different mechanisms for SO2 to be formed in the anode baking process, variations exist but the SO2 concentrations can become relatively high. However, the biggest influence is found to be the baking temperature (Fig. 5) if natural gas is used as a fuel. There is, however, a strong difference between high sulfur (HS) coke and low (LS) sulfur coke. High sulfur coke result is a higher loss of sulfur where low sulfur coke seems to holds it sulfur content. One result of this can be that if more HS coke is used that also the stack concentrations will rise. Operational results show that if baking temperature gradually decline that SO2 concentrations in the stack gases also decline proportionally. This was reported by Alba [6]. In his lecture materials Dr. Barry Saddler [7] also points out that some sulfur is released from the furnace as elemental sulfur. This if sometimes found as a yellow substance that is deposited onto packing cokes. The yellow substance is then observed on the top of the furnace. While this sulfur eventually is recycled back into the process with the collection of the packing cokes, it is a health and safety hazard that must be accounted for. The fumes from the anode baking furnace in an aluminium smelter are mainly treated in an alumina dry scrubber. After cooling the gases pass though the reactors and enter the baghouses. Here the solids are removed, and clean gases are emitted from the stack. It is interesting to mention that the fumes have relatively low HF concentrations. This means that the alumina has a large capacity to adsorb SO2, which indeed takes place. One mitigation for SO2 concentrations that may be in excess of the permitted limit (often we see values for the limit to be 500 mg SO2/Nm3), can be to increase the throughput of alumina proportionally. More SO2 is removed but it is

Anode Baking Process As described earlier, pitch volatiles released in the anode baking process combust within the flues to add an important amount of energy to the heat balance. While the sulfur content is small, it does contribute to the total. Another part of the SO2 emission from the baking furnace is from the fuel, which is also discussed. In the baking process there are further losses that also contribute to SO2 emissions. The anodes are surrounded by packing coke to fill the gap between the anode and the flue wall. This enables the conduction of heat into the anodes. The flue walls are deteriorating over time and a part of the packing coke is exposed to the combustion gases and burns as a result of that. The sulfur that is released from the packing coke also adds to the total SO2 in the fumes. Lastly,

Fig. 5 Sulfur loss as a function of anode baking temperatures [3]

Update on SO2 Scrubbing Applied …

passed on to the electrolysis process where it eventually becomes part of the SO2 passing through the GTC. However, the dilution is very substantial so the concentrations from GTC stacks are generally not a problem. At least, it almost never was. Irrespective, from a cost point of view it is better to apply one control technology to the gases from the GTC rather than installing a dedicated SO2 scrubber in the anode baking furnace.

Electrolysis Process Ultimately, a mass balance will show that 80–85% of a smelter SO2 emissions come from the electrolysis cells (or pots). The anodes are consumed in the process and sulfur is initially released as carbonyl sulfide (COS) gas. This gas passes through the crust and gets in contact with the ventilation air. It is very unstable with oxygen present and it is reported that 95% of the COS gas react to SO2. Other sources of SO2 are the alumina itself and the SO2 adsorbed in the GTC process. This is described earlier. Some SO2 escapes from the cells and is emitted from the potroom roof ventilators. During the work on pots, covers are removed and a fraction of the electrolysis gases are released into the potroom. Over a period of 24 h, the overall gas collection efficiency of modern cells is between 98 and 99%. This means that about 1.5% of the SO2 produced in the cells is emitted through the potroom roofs. In the past it was more common also to apply wet scrubbing to the ventilation air from potrooms (Fig. 6). With today’s efficient cell technology, the emissions to the potroom are very low and this is no longer required. However, in a rare case this still is in use. For example, the Intalco smelter still operates co-current type roof wet scrubbers to capture fluoride and SO2 emissions. It uses a solution of caustic soda that is sprayed in several wet scrubbers placed

771

in the roof sections. An example from another smelter is shown in Fig. 6. It is probably not realistic to see roof wet scrubbers return to modern aluminium smelters, but Dr. Neal Dando [8] made the case that if we must go all the way and work towards emissions as low as we can, that this may be a valid tool to use again. One aspect that often is overlooked is sulfur in spent anodes. The anode is exposed to 960 °C for 28 days and while this is a relatively lower temperature compared to the temperature in anode baking (*1200 °C), one may expect that some sulfur is lost from the anode while being exposed. There are no reports available with detailed investigations so for the moment it is assumed the spent butts will have the same sulfur content as its initial value. On the total this would not make a large impact any way.

Spent Potlining One emission that is part of the mass balance is spent potlining (SPL). Over time sulfur accumulates in the lining material and where this is removed as SPL there is a source of sulfur that is emitted by a solid waste. Typically, about 0.3 wt% of the lining material represents sulfur in the form of sulfate.

Sulfur Mass Balance By means of a generic mass balance an effort is made to provide insights in where the SO2 is released within the premises of an aluminium smelter with carbon plants. In the example below a smelter is defined with a capacity of 500,000 metric tonnes per annum using cell technology that operates at 500 kA. It is found that it is common for new smelter projects under development to target this kind of capacity and line amperage. Key assumptions are: – – – – – – – – – –

Fig. 6 Example of roof wet scrubber at the now defunct ZALCO smelter in Vlissingen, Holland

No. of cells is 360 The cell efficiency is 94.8% Daily pot production is 3.8 tonne/day Net and gross carbon are 415 and 550 kg/tonne, respectively Thermal desulfurization in anode baking is 7.5% Pitch fumes from the storage are treated by a catalytic thermal oxidizer (CTO) Coke A contains 3.5 wt% S Coke B contains 2.2 wt% S Pitch contains 0.6 wt% S The FTC reacted alumina contains 0.3 wt% F.

Using these parameters, the following mass balance can be drawn up (Fig. 7):

772

S. Broek tonne/yr S

Fig. 7 Sulfur mass balance in a 500,000 tpy smelter Coke A Coke B Pitch Fuel Alumina Ext. packing coke

OUTPUT GTC stacks Potroom roofs FTC stack Other

tonne/yr SO2 9,706 148 1,765 11,619

kg/tonne Al 19.4 0.3 3.5 23.2

4,511.68 1,215.39 244.20 114.75 6,086.0

% of SO2 83.5 1.3 15.2 100.0

tonne/yr S GTC stack SO2 GTC stack COS Roof SO2 Roof COS FTC stack SO2 SPL

4,858.27 242.79 73.98 3.70 883.52 23.76 6,086.0

it was concluded that combining and heightening the stacks in one tall stack, gave the gases more time to disperse. It would lift the higher concentrations over the park and by the time the fumes would reach the ground the dilution has been large enough that the actual concentrations are now below the standard.

Fig. 8 Projected SO2 emissions from a 500,000 tpy prebake smelter

Emission Requirements

The above mass balance is presented in terms of sulfur. Because of the different molecular weights, it cannot be presented in terms of COS and SO2. To get the insight in the emissions of SO2 the next table is prepared (Fig. 8).

A key parameter in the design of an SO2 scrubber is the emission limit. Together with the inlet concentration it will lead to specific process design features to get the required performance. The target outlet concentration of SO2 depends on what the authorities decide to put in the permit. In aluminium smelting applications values seen are in range of (just under) 20–35 mg/Nm3. Inlet concentrations typically vary between 100 and 250 mg/Nm3. Also, a SO2 removal efficiency requirement of 95% has also been reported. Due to the nature of the process, a wet scrubber also removes HF gas and dust. By using a wet (or dry) scrubber those emissions are even lower than at the outlet of the GTC. There is an additional emission to consider, which is the residual droplets that carry through the mist eliminators (also called “carry over”). With two mist eliminators the outlet concentration of droplets can be kept below 50–75 mg/Nm3.

Non-scrubbing Options The first question should be if there are options available to manage SO2 emissions before scrubbing processes are considered. The most commonly used practice without scrubbing is blending of cokes. A high sulfur coke can be mixed a low sulfur coke to aim for a target sulfur content in baked anodes that then is linked to a specific emission target. In one known case, a smelter committed to have a maximum of sulfur content in the baked anodes in order to be compliant. Another principle that has been used in the past, is to buy SO2 credits. This was an accepted practice where one plant would remove a high amount of SO2 beyond the minimum requirement. The excess amount would be turned into certified credits. Another plant that needed to reduce a specific amount of SO2 could then buy a sum of credits equaling the required tonnage so that their emission would be offset. For several years it was a practice applied in the U.S., but it is not very common today for SO2 (if at all). Often the issue a smelter must deal with is an area where the ground level concentration is or has become too high when compared with a standard. In one example, a nearby natural area was the subject of increased SO2 levels. Because the GTCs had short stacks on top (it was an A398 type),

Designing for 24/7 Operation Potlines operate 24/7 and the alumina dry scrubbers are designed for this. There are many individual filter compartments and one or two can be offline while all fumes are still being scrubbed. In most cases the SO2 scrubber is a single spray tower. To create redundancy often a second tower would be installed. In the case of Massena East, normally two towers would scrub 50% of the flow each and if one was out of service then 88% of the total flow would be directed to the other tower.

Update on SO2 Scrubbing Applied …

773

GTC stack gases with the FTC stack gases for a larger impact, but this is generally not applied or required. In the next sections the most prominent SO2 scrubbing solutions are discussed [10]. Most solutions are wet processes as these are generally most cost effective. The reason is that a wet scrubber operates on 3.5 m/s superficial gas velocities while the dry scrubbers only do about 1 m/s. This means much less scrubbing volume is required in wet scrubbing, which makes the equipment often cheaper. But that is valid in western smelter applications. In China often things work different and costs of materials are not comparable. Also, if smelters don’t want to use a wet process (it means bringing water near the potrooms or having the requirement to install water treatment as well) then the preference is to use a dry process. And this is exactly what is happening in China where smelters in the “26+2” group often choose to go for a dry SO2 scrubbing process. This will be described here below.

Wet Scrubbing Processes Fig. 9 Integrated SO2 scrubber design by GE [9]

Multi compartment seawater scrubbers like in Qatalum and Al Taweelah solved this by being able to switch off one compartment much like a filter module. To take this one step further, GE provides a solution where each filter compartment within a GTC is provided with a dedicated SO2 scrubber (Fig. 9). The wet scrubber is then integrated with the filter compartment and if one is off line that SO2 scrubber is then also off line. It is an effective solution that avoids any requirements for a large investment in bypass systems. Another option is to use a bypass. In this case we take the advantage from the fact that wet scrubber has an availability of 98% or better. It has become very reliable and only needs a few days per year for maintenance and inspections. So, if the scrubber is offline for 5 days per year and the required SO2 reduction is about 8000 tonnes, then the regulator could agree to achieving those 8000 tonnes in 358 days instead of 365 days. The requirement for the removal efficiency then goes up from 83 to 85% to compensate for this and to get to the 8000 tonnes faster and compensate for the full emissions during bypass operation. But this is a small cost compared to having to install a second wet scrubber.

SO2 Scrubbing Solutions It is evident from the mass balance (Fig. 8) that the focus should be on GTC stacks if SO2 emissions need to be controlled. In a rare case it can be thought of to combine the

Scrubbing SO2 is one of the most common processes one can find. There are over 100 (!) different ways developed to scrub SO2 from an exhaust gas. Because of the large gas volume and the low SO2 concentrations only a few apply to aluminium smelting. A wet scrubbing process is very effective. SO2 is absorbed into water and a reagent is present in the water to react with the SO2 to form a product. If a sodium (Na) based reagent is used then the product is sodium sulfate, which is dissolved in water. If a calcium (Ca) based reagent is used, then the product is calcium sulfate which precipitates as gypsum. After filtration this is a solid product that is used, for instance, in the manufacturing of wall boards. This is explained because it is important to know ahead of time what the preference is to have the SO2 be converted to.

Wet Scrubbing Using Seawater Especially in western smelters, SO2 scrubbing is done in most cases using seawater. Seawater contains sodium bicarbonate (NaHCO3) that is a natural reagent for SO2. The product is sodium sulfate (Na2SO4), which is already present in seawater in large concentrations. In aluminium smelting applications the seawater enters the scrubber at pH 7.8 and is discharged at pH values of about 6.0. The seawater enters from the top of the scrubber and washes the gases in one go. It is drained from the bottom and send for treatment or directly to the outfall. The concentration of bicarbonate is small, so it is pretty much depleted in

774

S. Broek

one pass. The seawater should also not rise in temperature too much. If in circulation the temperature would be about 10 °C higher as it is at adiabatic conditions. Systems applied in the UAE and in Qatar (Fig. 10) are modeled from seawater scrubbers used in power plants. The system comprises of a long seawater intake (up to 4 km long) of almost 2 m in diameter, seawater pumps, scrubbing towers, a large basin with aeration systems and a discharge to the sea. The seawater is taken from at least 10 m deep to have consistent alkalinity. In both cases the main flow of seawater is used for cooling of the power plants so the infrastructure, including the long intake manifold, is considered part of the power plant. In Norway, however, things are simpler. Being located at a fjord has the advantage that the intake can be near the plant and so can the outfall be. It also happens to be that no corrections are needed for temperature and oxygen levels, so the seawater is discharged in the fjord as is. This makes it very cost effective. The reason to explain it in this way is to prevent the general misunderstanding that by default the seawater process is the cheapest solution. If a smelter must be retrofitted with SO2 scrubbers and the seawater intake manifold is part of the cost estimates, then one will quickly find out that the cost can be prohibitive for seawater scrubbing. There are also some learnings to consider when new SO2 scrubbers are considered using seawater. Both smelters in Qatar and the UAE see corrosion in the immediate vicinity of the scrubbers. Walkways and structural steel corrode, and it is believed this is caused by discharges of seawater from the stacks. That is because often only a single mist eliminator is used inside seawater scrubbers. It’s a design feature from power plant type seawater scrubbers where the cleaned fumes are reheated in a gas-gas type rotary heater. It eliminates the droplets; however, here such equipment is not used. For this reason, it is best if residual droplet concentrations are kept below 50 mg/Nm3 and to achieve this, not one but two mist eliminators should be used, that is, one

so-called ‘course’ type and one ‘fine’ type. This refers to the blade spacing of chevron type mist eliminators.

Fig. 10 Seawater scrubbers at Qatalum, Qatar Source Fives Solios

Fig. 11 Wet scrubbers at Alcoa Massena East Source Danieli Corus

Wet Scrubbing Using Caustic Soda or Soda Ash The second option in popularity is scrubbing with caustic soda (NaOH) or soda ash (Na2CO3) as the reagent. Both reagents are very effective and result in the same product, which is a purge stream with sodium sulfate (about 12 wt%). Other key constituents are aluminium (Al3+) and fluoride (F−). The scrubber operates with a recycle of liquor. By means of pH control a small flow of caustic soda is added to the process to compensate for the loss consumed in the reactions with SO2 and HF. There are cases where the purge stream can be directly discharged into surface waters. This is advantageous if this is indeed possible. In other cases, the water is/was treated, however, not without its problems. The purge has very high concentrations of sulfate and if calcium is added to try to capture the fluoride as calcium fluoride (CaF2), then actually calcium sulfate (gypsum) is produced and a good fraction of the fluoride remain dissolved. Gypsum is notorious for fouling up surfaces and pipes when its precipitation is not controlled. Only with the use of seed crystals this can be managed. Both water treatment systems in Hawesville and Massena East (Fig. 11) are no longer in operation. SO2 scrubbers in Norway and in Vlissingen, Holland, discharge directly in surface waters. The world largest wet scrubbing system in numbers is used in Krasnoyarsk, Russia. There are 25 potrooms and many of the GTCs have a wet scrubber attached. The liquor is taken to a pond where it cools down and precipitated. An

Update on SO2 Scrubbing Applied …

775

R&D program is in effect to recover sodium sulfate from the process in a newly configured wet scrubbing process [11].

Wet Scrubber Using the Dual Alkali Process In the dual alkali process the liquor of sodium sulfate is taken to a tank where hydrated lime (Ca(OH)2) is added. By doing so the sulfate becomes gypsum and the sodium becomes sodium hydroxide (NaOH). It requires more equipment but produces a solid byproduct in the form of gypsum. It is used in China in some smelters and Alcoa has this connected to their in-duct scrubber (IDS) technology. Hatch applies this process in the non-ferrous industry and a process team maintains the knowledge to design the process in dilute and concentrated modes.

Wet Scrubbing Using Lime Rather then using two steps, it is possible to use lime directly. Lime is made into a slurry in a slaker and added to the wet scrubbing process using pH control. The lime reacts with the SO2 to form gypsum under presence of seed crystals. The gypsum is filtered and forms a usable solid by product. While there are smelter operators in China that use limestone in their SO2 scrubbers, lime is probably preferred over limestone. In the power industry limestone is known to experience so-called limestone blinding by aluminium fluoride precipitating on the surface of the limestone particles making them inactive. With lime this is avoided and since the aluminium application sees a lot of aluminium and fluoride, it will be the safer option. Wet scrubbing with lime to produce gypsum is introduced in aluminium smelters in China following the tightening of the SO2 limit in the municipal areas of the 26+2 cities. In one case at Guangxi Baise Mining Aluminium (BSKY), the gypsum is shipped to a cement plant for processing. It was a logical step because the lime(stone) process is the world’s most used scrubbing process for SO2.

Fig. 12 GTC (left) followed by Dry FGD (right) in Yingkou Zhongwang Aluminium, China. Source Dalian Bihai

It offers high SO2 removal efficiencies but, moreover, a low calcium to sulfur stoichiometry ( < e ¼ 1E r  t
r þ r  z z x y E ð1Þ cxy ¼ G1 sxy > > > > cyz ¼ G1 syz > > : czx ¼ G1 szx

X-direction (length) deformation. However, the absolute deformation in X-direction keeps very low and such increasement of deformation in X-direction does not impact the cell’s safety. In parallel, the right-angle design eliminates ledge blocking of corner anodes. Figure 1 shows the deformation of GP500+ shell at the initial stage of start-up. Figure 2 shows the deformation after the pot reaches stable operation. The comparison of calculated and measured data is listed in Table 1. The results indicate that when pot reaches stable operation, Z-direction deformation of the shell is less than 25 mm, X-direction deformation is less than 1/600 of shell’s length and Y-direction deformation is less than 1/200 of shell’s width. Deformation of the shell is within the controllable range; the cell is safe and reliable.

The shear modulus can be calculated as: G¼

E 2ð 1 þ t Þ

ð2Þ

Since the shell is under high temperature atmosphere, it is necessary to consider the thermal expansion. Therefore, the thermal strain needs to be added in the stress-strain relationship: 8 >  eth ¼
aDT  > 1 > > e ¼ r  t ry þ rz  þ aDT x x > E > > > ey ¼ E1  ry  t
ðrz þ rxÞ  þ aDT < ez ¼ E1 rz  t rx þ ry þ aDT ð3Þ > 1 > c ¼ s xy > xy G > > > cyz ¼ G1 syz > > : czx ¼ G1 szx Actually, shell deformation, especially Z-direction (vertical) deformation is what engineers care the most. Under several years of optimization and simulation, GAMI team successfully developed a new structure: integrated welded shell structure. The structure had been used in GP500 technology and has been revised in GP500+ technology. Compared to the traditional design, this structure integrates the cradle with shell, added two connecting plates between two cradles, making the cell corner right angle and applies the boat-shape design. The new structure saves 4.3% of material, and brings 6.4% lower deformation in Y-direction (width) as well as 51.8% lower deformation in Z-direction (height), the only compromise is an increase of 9.1% in

Table 1 Deformation of GP500 + cell shell (unit: mm)

Item

Fig. 1 Deformation of GP500+ shell at initial stage of start up

Fig. 2 Deformation of GP500+ shell after the pot reaches stable operation

Max deformation during start-up

Max deformation after pot reaches stable operation

Z

X

Y

Z

Calculated

28.9

12.3

18.4

19.2

Measured

30.1

12.7

17.8

19.3

Development and Application of GP500+ Energy Saving …

829

Superstructure Design and Modeling The superstructure of cell needs to support anodes, beam busbars, breaking and feeding system, anode lifting system, pipeline, etc. Therefore, the safety of superstructure beam is essential [3]. In order to guarantee the superstructure’s safety, GAMI uses the following possible maximum load condition for the modeling of the support beam: (a) The reduction cell is under normal production case, all the anodes are covered with covering material and it is evenly distributed; (b) All the anodes attached are considered new anodes; (c) All alumina hoppers and aluminum fluoride hoppers are fully filled; (d) Anode beam rising frame is set upon the superstructure. Table 2 indicates all types of loads considered in the modeling of support beam. The calculation is based on Eq. (3). In GP500+ technology, the maximum deformation of the beam is 35.602 mm, which is less than 1/600 of its span. Also, the stress is lower than the permissible stress of the material. Figure 3 indicates the deformation of superstructure in vertical direction. In terms of duct, an uplifted design is used in GP500+ cells. Compared to the traditional “V” shape one, the new design made it flat to give more operation space to anode change and crust breaking. Seven exhaust points are designed and are divided into 2 groups. In the simulation, the outlet pressure of the duct is considered at −300 Pa, and the fume temperature is considered at 160 °C. The simulation results are given in Fig. 4 and Table 3. The results indicate that the velocity is evenly distributed in each exhaust point, and the total fume collection capacity is sufficient.

Busbar Design and Modeling As capacity (amperage) of the reduction cell increases, the geometrical size of the reduction cell correspondingly increases, which results in an enhanced impact of magnetic Table 2 Types of loads considered in the modeling of support beam

Type of load

Fig. 3 Deformation of GP500+ superstructure in vertical direction

Fig. 4 GP500+ cell duct velocity vector

field generated by pot line current, leading to an increment of ACD (anode-cathode distance) to maintain stability. Contradictorily, higher amperage result in increases of unit area heat dissipation, leading to a reduction of ACD to maintain heat balance. The above relationship is shown in Fig. 5. Therefore, the prerequisite for achieving large-scale aluminum reduction cell is to solve the problem of magnetic field stability [4]. As known, the main driving force for the molten metal and bath inside the cell is the electromagnetic force [5]: F¼JB

ð4Þ

Therefore, the horizontal current in the metal layer and vertical magnetic field creates the wave-driving force, which are mainly generated by busbar system. Hence, to increase a cell’s MHD stability, there must be an optimized busbar system which can guarantee a good magnetic field distribution in high current capacity. In GP500+ busbar system, GAMI used an isolated compensating busbar circuit to balance the magnetic field. The amperage of the compensating busbar circuit is designed

Uniform load

Concentrated load

Self-weight Alumina weight Aluminum fluoride weight Pipeline weight Alumina distribution system

Anode weight Anode clamp weight Beam busbar weight Anode lifting system weight Beam rising frame weight Anode covering material weight Crust force

830

Z. Xie et al.

Table 3 Fume flow at each exhaust point in GP500+ duct design

Exhaust point

Mass flow (kg/s)

Volume flow (m3/h)

1

0.682

2875

2

0.67

2824

2.6

3

0.652

2748

−0.1

Avg flow (m3/h)

Deviation (%)

2752

4.5

4

0.648

2732

−0.7

5

0.646

2723

−1.1

6

0.65

2740

−0.4

7

0.62

2614

−5

Total

4.57

19,265

/

/

Note Exhaust point starts from tap end

Fig. 6 The model of GP500+ magnetic field calculation Table 5 GP500+ vertical magnetic field |Bz| in four quadrants GP500+

1st quadrant

2nd quadrant

3rd quadrant

4th quadrant

Max

Fig. 5 Relationship between MHD stability and thermo equilibrium stability

|Bz| modeling (Gs)

2.45

3.63

3.98

3.78

19.13

Table 4 Busbar system of GP500 and GP500+

impact from the neighboring room. The pot line current is considered at 530 kA. The results shown that the magnetic field distribution is even, the value is low, maximum |Bz| is 19.13 Gs, the average of the absolute values of the four quadrants are very close, indicating a uniformed vertical distribution. Vertical magnetic field values and distribution are indicated in Table 5 and Fig. 7.

GP500

GP500+

No. of risers

6

7

No. of anodes

48

56

Isolated compensating busbar

No

Yes

at 32 kA with pot line current at 500 and 34 kA with pot line current at 530 kA. The isolated system also allows the compensating current to be adjusted from 30 to 40 kA to meet different pot line conditions. Table 4 indicates the comparison of busbar system between GP500 and GP500+. GAMI uses ANSYSTM software to establish a model including the busbar, internal current, cell shell and air around. The magnetic field is calculated based on steady-state Maxwell’s equations: rH ¼J

ð5Þ

B ¼ lH

ð6Þ

Figure 6 shows the model of magnetic field calculation of GP500+ cell. In this model GAMI sufficiently consider the impact from upstream and downstream cells, as well as the

Lining Design and Modeling In terms of energy saving, the lining design of a cell shall always be highlighted as thermal equilibrium is most relative to the performance. Meanwhile, lining design has a significant impact on cell life. Therefore, a new concept of regional insulation has been prompted in the development of GP500+ cell, which is targeting at effectively reduce sludge and toe ledge in the bottom as well as guarantee a good ledge profile on the side. To realize the target, two new composite materials, which can provide better insulation, were developed. The calculation of electrothermal field of aluminum reduction cell involves solution of Laplace Eqs. (7) and (8) [6].

Development and Application of GP500+ Energy Saving …

831

Fig. 7 Distribution of vertical magnetic field Bz

" #     @ 1 @V @ 1 @V @ 1 @V þ ¼0 þ @ x qx @ x @y qy @y @ z qz @ z

ð7Þ

      @ @T @ @T @ @T kx ky kz þ þ þq ¼ 0 @x @x @y @y @z @z

ð8Þ

The simulation is done by GAMI self-developed international advanced thermal field calculation software based on ANSYSTM platform. In the model, boundary conditions are given in Table 6. The temperature distribution and isotherm distribution are respectively indicated in Figs. 8 and 9. The results shown that the highest temperature of the side shell and bottom shell are respectively 278 °C and 76 °C, which can guarantee a sufficient insulation. The ledge profile is indicated in Fig. 10. Thickness of side ledge is 11.8 cm, which is sufficient to prevent the erosion of cell lining caused by bath. As shown in Table 7, the average cell voltage is calculated at 3.977 V, and the voltage drop distribution is reasonable in all parts. The actual operating average voltage is 3.98 V, indicating that the calculated value is consistent with the actual values obtained in operation. As described in Eq. (4), horizontal current reduction can also contribute to MHD stability. In GP500+ cell, GAMI made some modification on the design of collector bar. No copper was inserted in this new design. Compared to the

Fig. 8 Temperature distribution of GP500+ cell lining

Table 6 Boundary conditions of thermal calculation Item

Unit

Value

Pot line current

kA

530

Bath temperature

°C

950

Liquidus temperature

°C

942

Ambient temperature

°C

35

Metal level

cm

28

Bath level

cm

19

Anode covering height

cm

18

Cathode type

/

50% graphitic

Fig. 9 Isotherm distribution of GP500+ cell lining

traditional design (same cell capacity), the average value of horizontal current can be reduced from 1157 to 773 A/m2, while the maximum value can be reduced from 1961 to 1316 A/m2. Figure 11 illustrates the comparison.

832

Z. Xie et al.

Fig. 10 Ledge profile of GP500 + cell

Table 7 Voltage composition of GP500+ cell Item

Calculated voltage (V)

Anode

0.352

Anode–Cathode

1.341

Cathode

0.270

Back EMF

1.700

Voltage drop of busbar around

0.247

Others (pot line busbar, AE, etc.)

0.067

Avg. voltage

3.977

Cell Process Control: MPPIC System

2500 2000

Center of Cell

Jy (A/m2)

1500 1000 500 0 -500 -1000 -1500

Y (m) GP500

GP500+

Fig. 11 Result of horizontal current simulation

A reasonable design of shell, superstructure, busbar and lining guarantees a good “static equilibrium” for a reduction cell. However, only obtaining a good “static equilibrium” is far from getting an ideal performance. Alumina concentration, bath temperature, noise level, metal and bath level, etc., are dynamic parameters which will determine a cell’s “dynamic equilibrium”. Actually, it is both “static equilibrium” and “dynamic equilibrium” that jointly determine the cell’s performance. The “dynamic equilibrium” is controlled by cell control system and cell process manager. GAMI offers a proprietary software MPPIC system, which has been applied in more than 19 million mt/year capacity and over 25,000 reduction cells. The system helps the cell to obtain a good “dynamic equilibrium”. After decades of optimization, it has become the most sophisticated and trusted control system in Chinese aluminum reduction market. The latest software integrates the “cell control system”, “conveying and fume treatment control system”, “chemical components analysis system” and “remote technical support system”., All of this is integrated within a reduction cell control platform. Figure 12 shows the control model of the new generation “MPPIC” system [7].

Development and Application of GP500+ Energy Saving …

833

Fig. 12 The new generation MPPIC control model developed by GAMI

Remote Data-Diagnosis Technology Service To solve the nonstandard management issue, GAMI developed Remote Data-Diagnosis Technology Service (RDTS). It connects smelter’s operation data to GAMI’s big data system. Based on cell condition analysis system, RDTS system can automatically carry out process parameters analysis, achieving remote control on process parameters. It has the following features: • Monitoring pot data anytime and anywhere (user can have direct remote access through GAMI Internet and data security can be guaranteed). Fig. 13 RDTS connecting mode

• Rapid analysis on various problems (acquire timely guidance form GAMI experts). • Regular process diagnosis (diagnose existing problems, give feedback of abnormal data). • Technical communication among enterprises (invite enterprises to issue regular reports). The user can decide whether online data can be shared with GAMI’s big data system or not. Sharing online data will allow smelter to obtain real time support, as well as feasibility for pot manager/process engineer to remotely access smelter data. However, some smelters pursue their SCADA (Supervisory Control and Data Acquisition) system for highest security level and thus do not allow

834

Z. Xie et al.

the SCADA to directly connect to the Internet. In this case, smelter can back up the production database to a new workstation on the daily basis and use this new device to connect to the Internet. The connecting mode is indicated in Fig. 13. After successful connection, here’s how RDTS works [8]: • It makes remote monitoring on real-time and historical data, go through diagnosis reports and improves management efficiency to a large extent. • It establishes multi data-analysis models so as to make analysis on process parameters‘ stability, ordering and rationality. By doing this, it can identify the running conditions of reduction pots. • Through multi-parameter tendency control theory as well as pot condition distinction control method, the process directive system can significantly improve pots’ stability, lower consumption and raise efficiency.

Table 8 Technical indicators in smelters using GP500+ energy saving technology Smelter

DC power (kWh/t-Al)

CE

No. of cells

Start up since

Xingren

12,617

94.0%

354

2018.03

Shenhuo

/

/

330 + 328

Under construction

Fig. 14 Potroom view of Xingren smelter using GP500+ cell technology

Industrial Performance GP500+ energy saving technology has been applied to the first pot line in China in 2017. Application of all the above mentioned newly developed technology allows smelters to obtain good technical indicators. Another smelter adopted the same technology for two pot lines has started construction since October 2018. Table 8 shows the technology footprints. Figure 14 shows the photo of Xingren smelter in the potroom.

Conclusion GP500+ energy saving cell technology is successfully developed based on GP500 technology with revised design ranging from shell, superstructure, busbar, lining, cell control system and remote support service. Combination of these technologies allows smelters to operate at DC power consumption of 12,600 kWh/t-Al level. The industrial performance proved the technology successfully reaches world-advanced level.

References 1. Chen Ying. Analysis and Discussion on Structure of Aluminum Electrolysis Cell Shell [J]. Nonferrous Metals Design, 2018 (03): 99–101, 116. 2. Liu Yexiang, Li Jie. Contemporary aluminum electrolysis [M]. Beijing: Metallurgical Industry Press, 2008: 329–330. 3. Yang Zhiqiang, Liu Ying. Design and Research of Support Beam for 500kA Aluminum Cell [J]. Nonferrous Metals (Extractive Metallurgy), 2019 (03): 30–34. 4. Yang Xiaodong, Liu Wei. Discussion on Designing High Amperage Energy-Saving Aluminum Reduction Pot-Busbar, Cathode Structure and MHD Stability [J]. Light Metals, 2016 (10): 27–32. 5. Liu Wei, Yang Xiaodong. Study on Magnetic Field Modeling in Aluminum Reduction Cells with Complex Cradle and Potshell Structure [J]. Light Metals, 2018 (3): 21–25. 6. Hongmin Ao, Hailong Guo. Study on the Main Process Parameters of 530kA Aluminum Electrolysis Cell and Calculation of Electrothermal Field Simulation [J]. IBAAS-GAMI. The 8th Annual IBAAS Conference, 2019: 191–199. 7. Hong Bo, Xie Zhuojun, Li Jianping, et al. Technology Roadmap of New Generation Aluminum Reduction Cell Multivariate Process Parameters Intelligence Control System [C]. IBAAS 2016 the 5th International Bauxite, Alumina and Aluminium Symposium, 2016. 8. Hong Bo, Tian Qinghong, Yi Xiaobing, et al. The Application of the “Remote Data-Diagnosis Technology Service” (RDTS) for Aluminum Pot Line [J]. Light Metals 2019. Springer, Cham, 2019: 929–935.

Part IV Cast Shop Technology

Hands-Free Casting at AMAG Casting GmbH—It Is Possible! Bernd Prillhofer, Rudolf Dobler, and Thomas Mrnik

Abstract

The start-up of the aluminum rolling slab casting process is one of the most critical procedures in terms of casthousesafety. In many casthouses, it is common practice that the staff works directly at the launder system and on the casting table during the whole start-up, until the steady-state phase is reached. Operators are needed along the launder system (furnace spout control, opening of launder gates, CFF check etc.) and on the casting table (priming of the distribution bag, filling control etc.), but there are a lot of risks, which, upon materializing, can have a tremendous adverse impact on human health: wet starter-blocks, bleed-outs, hang-ups etc. can lead to very harmful situations and therefore it’s best for the operators to start the process from a safe place, away from the launder system and casting table. This paper deals with all needed mechanical and automation systems, as well as casting techniques, to enable the casthouse staff to control the start-up at a safe place. Keywords









Hands-free casting DC casting Casthouse-safety Automation Aluminium Aluminum




Introduction AMAG casting GmbH is producing high quality rolling slabs within all aluminum wrought alloys groups from 1xxx to 8xxx series alloys. Therefore, the casthouse operates eight casting pits covering three different casting technologies: • Conventional DC (Direct Chill) casting • LHC (Low Head Composite) casting (Wagstaff) • EMC (Electro Magnetic Casting). B. Prillhofer (&)
R. Dobler
T. Mrnik AMAG Casting GmbH, Lamprechtshausenerstraße 61, 5282 Ranshofen, Austria e-mail: [email protected]

Each casting pit can cover at least two of the mentioned casting technologies. In the last ten years, four new casting pits were installed including the new trial-casting pit, which was started up in 2018. The 3-strand-trial-casting pit can operate all three casting technologies on full scale for all slab dimensions, produced in the whole casthouse. The three new casting pits are fully automated 6-strand facilities with a minimum ingot cross section (width  thickness) of 1100  360 mm and a maximum dimension (width  thickness  length) of 2300  570  8400 mm. Figure 1 shows the two casting pits in the new casthouse, which were part of the AMAG expansion projects AMAG 2014 and AMAG 2020. Casthouse safety is the most important issue. The casting process itself has a tremendous potential for molten metal explosions (compare [1]). Therefore, the manufacturers have undertaken lots of actions to make the process as safe as possible. But at the end, the risk of injuring the casthouse workers can only be minimized and not eliminated. The start-up of the cast is one of the most critical phases for casthouse workers, because of the need to stand on the casting table interacting with the melt distribution system, molten metal etc. During the engineering process of the new casthouse, there was a special focus on keeping the workers away from the casting table. All the interactions of the workers with the casting process are analyzed and solutions are derived, to keep them away. Within the first part of the expansion project AMAG 2014, these solutions were implemented and further developed for part 2 of the project, AMAG 2020. A second advancement was applied on the trial casting pit. Out of our experiences on the topic hands-free casting, this paper focuses on following issues: • Requirements for hands-free casting • Historical development of hands-free casting at AMAG casting GmbH

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_111

837

838

Fig. 1 New casthouse at AMAG casting GmbH (expansion project AMAG 2014 and AMAG 2020)

• Solution approach • Psychological aspects.

Requirements for Hands-Free Casting The implementation of the idea of hands-free casting has several requirements: • Fully automated casting pit • Metal level control in the mould • Fully automated melt distribution system within the mould • Metal level control in the launder system • Excellent casting recipes/practices • Constant and reliable casting conditions (cooling water, melt temperatures etc.) • Well maintained moulds and starting blocks • Video System. A fully automated casting pit includes everything in terms of measurement devices, sensors, actuators like metal level measurement system in the mould, pin actuator, movable skim dams, vibrators, distribution bag wetting system, casting speed control, cooling water flow control etc. The mentioned parts are only a few ones, which are the absolute minimum effort. Depending on the casting technology, the accurate control of the metal level is highly important (for example EMC technology: ± a few millimeters) and therefore, a reliable system is a pre-condition [2]. The melt distribution system in the mould is usually unique for each casthouse and moreover for the different products. According to the ingot dimensions, microstructure

B. Prillhofer et al.

requirements, alloy etc., different distribution bags are used. During the start-up of the cast, when the first metal arrives in the bag, a wetting support of the bag is often needed, to guarantee good flow conditions. Another important item are oxide dams, which are often moveable to assist ideal mould filling during the start-up. Skim dam movement can also influence surface tension of the liquid metal in the mould and can help eliminating surface defects especially using EMC technology, where no contact between liquid metal and the mould occurs. Another tool are vibrators, which are also assisting the wetting behavior of the distribution bag (depending on the mounting position) and the surface quality. There must be a special focus on the vibrator adjustments to avoid resonance frequencies. During the start-up, while filling the launder system, certain devices like the ceramic foam filter and of course the distribution launder need metal damming with gates to ensure the right metallostatic pressure or sufficient metal flow. Gate opening must be at the right time and reproducible. Furthermore, within the steady-state phase of the casting process, the metal level in the launder system (from furnace spout to distribution launder) must be controlled (same height during the whole steady-state phase) in terms of temperature control, metal quality, efficiency of degassing systems and filtrating units (CFF) etc. This leads to the requirement of metal level measurement devices at different positions in the whole launder system connected with gate opening and furnace tilt control. Another very important issue of the automatic gate opening are safety reasons: a not well dried launder section can result in an explosion when flushing it with liquid metal—therefore the workers must be in a safe position and keep away from the launder system. An excellent casting practice regarding filling time, metal level, casting speed and cooling water flow ramp up as well as other important parameters (like CO2-amount, pulsed water control etc.) comes along with constant and reliable casting conditions (like cooling water composition and temperature, melt temperatures etc.). Without stable conditions, a successful start-up of a cast is nearly impossible to be carried out in the hands-free modus. Out of this, even how bad or good the boundary conditions are, they must be kept constant and the casting practice must be harmonized to them [3]. Well maintained moulds and starting blocks, this is a very important requirement. Some alloys allow bigger deviations and some alloys allow nearly zero deviations. The people in the mould shop have a very important role and they need excellent knowledge and training to support the casting process with well-maintained equipment and a standardized set-up. At the end, people must see what is happening along the launder system and on the casting table. A video/camera system is needed to deliver the right section at the right time

Hands-Free Casting at AMAG Casting GmbH—It Is Possible! Table 1 Solution approach for Hands-free casting

839

Staff interaction

Past time

Present time

Metal level sensors for the launder system

Unreliable/less sensitive laser systems

Reliable/stable radar system

Launder gates

Manually opened gates

Fully automated and opening according to right launder metal level

Wetting of distribution bag

Manually supported wetting of distribution bag

Supported wetting of distribution bag by automatic device

Skim dam speed

Speed of skim dam movement during filling curve manually adjusted

Speed of skim dam set with quantifiable parameters

Vibration strength

Strength of vibrator during filling curve set manually

Strength of vibrator set with quantifiable parameters

Cast control by workers

Along the launder and on the casting table

CAST-TV-System: automatic display of relevant sections on video screen

on the TV screen accompanied by relevant process data. This allows, that worker-interactions only occur, when they are necessary.

Historical Development of Hands-Free Casting at AMAG Casting GmbH In recent times many of the mentioned requirements for hands-free casting were already fulfilled. Table 1 gives a summary of the last adjustments which were carried out to realize the objective. The now automatically operating devices were also implemented into the casting practice, to allow a unique setup for each product. Furthermore, the implementation was done in a way to allow set point-changes in dependency to the casting length.

Solution Approach

steady-state phase. In recent times, the old-fashioned float switch close to the furnace spout was used for metal level control by tilting the furnace more or less strong. These devices came along with the ability to sink, which is their biggest disadvantage. This leads to the usage of laser or radar systems. Figure 2 shows different applications of these systems: (a) radar system, (b) and (c) laser system. All systems need an accompanied overfill safety, which is usually integrated in the launder refractory close to the furnace spout. At AMAG casting GmbH there was originally a change from the float switch to laser systems. Due to our existing experiences regarding the tendency to faulty measurements, always two devices were installed parallelly for mutual control (high investment costs). Long term tests originated further disadvantages: unstable operation during hot summer periods (need for additional cooling) and measurement errors in combination with very shiny high purity alloys. Radar technology offers a very easy way for fluid level measurement. Table 2 shows the aggregated pros and cons of both systems.

This section deals with practical solutions to meet the requirements for the hands-free casting modus. The focus is drawn on following solution approaches: • • • •

Metal level control in the launder system Metal level control in the mould Melt distribution system in the mould Video control system (VCS).

The given sequence doesn’t represent a special priority, because all of them are a precondition for a successful implementation. 1. Metal Level Control Launder System The importance of metal level control in the launder system is predominant during the start-up and in the

Fig. 2 Metal level measurement systems for launder applications

840 Table 2 Comparison of metal level measurement techniques for launder systems

B. Prillhofer et al. Technique

Radar system

Laser system

Advantages

– Reliable measurements – No influence of reflecting surfaces (high purity alloys) – Lower investment costs in comparison to lasers – Heat compatible – No cooling air required – Easily installed

– High measurement frequency in comparison to radar systems

Dis-advantages

– Lower measurement frequency in comparison to lasers

– Influence of reflecting surfaces by casting high purity alloys (measurement errors) – Higher investment costs in comparison to radar system – Heat sensitive (cooling air can be required) – Optical system must be cleaned periodically

The usage of radar system was already applied for metal level control in furnaces. Beside the lower measurement frequency, radar systems provide reliable measurement results. A long-term test of radar sensors resulted in no negative influence due to hot environmental conditions.

2. Metal Level Control Mould For some time, the “Gap Molten Metal Level Control” of GAP Engineering SA has been used as the standard metal level control system at AMAG casting GmbH. The system consists of an inductive metal level sensor (GLS, GAP Level Sensor, measurement range up to 240 mm) and the pin actuator GLA (GAP Level Actuator). The system allows an adaption of the molten metal level during all stages of the casting process (according to the casting recipe/practice). Figure 3 shows the arrangement of the metal level sensor. The system allows the same metal level control in several moulds simultaneously, a very high accuracy—strongly required for EMC casting—and casting with very low metal level (LHC casting).

Fig. 3 Mould—metal level control system

3. Mould Melt Distribution System The melt distribution system in the mould should consist of following elements: • • • •

Melt distribution bag Oxide dam, horizontally movable Vibrators Wetting assistance for the distribution bag

and must fit for all used casting technologies with their main difference: • EMC: constant metal level during the whole casting process • LHC: changing metal level during start-up of the cast. A changing metal level leads to the demand of floating oxide dams and of course, at the end of the cast, the complete system must be removed from molten metal. The melt distribution bag plays a major role regarding the microstructure formation inside of the ingot. Due to the wide product range of AMAG casting GmbH (covering all alloy categories from 1xxx up to 8xxx series alloys) a continuous development of different distribution bag geometries happened. Therefore, the melt distribution system must be suitable for all different types in combination with different oxide dam styles and easy mounting during cast setting-up. In recent times, separate systems were used for each casting technology, which must be exchanged by changing technology. Figure 4 shows the transformation from the old—moveable skim dam, mounted on the mould including a little pneumatic drive for the horizontal movement, equipped with a vibrator and fixing elements for the distribution bag—to the new system.

Hands-Free Casting at AMAG Casting GmbH—It Is Possible!

Fig. 4 Development of the mould metal distribution system

Fig. 5 Overview of the mould metal distribution system

841

equipment, they are prepared for interactions, if there were needed. Within the process chain, first the furnace spout is shown until a certain metal level is reached to check leak-tightness (see Fig. 6). The switch over of the camera positions occurs automatically. Depending on the length of the launder systems and the existing in-line devices, several damming sections with gates are needed. During the waiting period, to reach the required metal level, the area around the specific gate is shown on the screen. The inlet and outlet of the degassing unit is also shown to visualize the flow behavior of the melt and leakage-control (see Fig. 7). High quality products need ceramic foam filtration. By preparing the ceramic foam filter, mistakes can happen by fitting the filters in the box etc. Therefore, it is necessary to watch the filling of the filter box (see Fig. 8). The filter box lid is opened before filling the launder section in front of the unit. In the case of floating filters, the start-up of the cast can be stopped without filling the moulds. The video stream of the filter box must also be checked during the whole cast regarding floating filters.

With the new system all elements were removed from the mould and mounted on the distribution launder (see Fig. 5). It allows the assembling of fix-positioned skim dams for EMC casting and floating skim dams for LHC casting, both horizontally moveable. Further, the mounting of all different distribution bag styles with automatic centering regarding the spout position including a wetting assistance (vertical movement). The vibratos of one melt distribution system are installed in a way, not influencing each other. All movable elements (oxide dam, vibrators and wetting assistance) of the melt distribution system are integrated in the casting practice. Hence, moving duration and frequency can be set in dependency to casting length, like casting speed, cooling water flow etc. Fig. 6 VCS of the furnace spout

4. Video Control System (VCS) AMAG casting GmbH has developed its own “Casting-TV” system which is integrated in the shop floor management system and directly connected with the casting pit. It shows all camera positions in a minimized form, the actual metal flow position during the start-up on big scale and actual values of important casting parameters. After the check-in of the casting process at the casting pit control system, which is finished by start furnace tilting, the workers are watching the start-up and the cast by wearing complete safety equipment (silver jacket, silver hood etc.) in front of the TV screen. By wearing complete safety Fig. 7 VCS of the inline degasser

842

Fig. 8 VCS of the ceramic foam filter system

Fig. 9 VCS of the casting table

The last step is the flushing of the distribution launder. That is why the metal must be dammed one last time. This damming period is also shown, for the unlikely case of a leaking gate leads the workers directly to a cast abortion, because adequate mould filling cannot be guaranteed due to frozen metal in spouts etc. After reaching the right metal level, which is given by the casting practice, the last gate is opening and the filling of the moulds is shown. The resolution of the cameras must be as high as possible, to see all areas (like corner section etc.) very clearly (Fig. 9). The visualization of the moulds remains on the screen until the end of the cast, but workers have the possibility to switch within all camera position shown in a minimized manner.

Psychological Aspects At the end, having installed all the needed tools, there is one last thing—keeping the casthouse workers away from the casting table. From the early beginnings of continuous casting, casthouse workers have learned, that it is necessary to stand on the casting table, to make the cast a success. This leads us to

B. Prillhofer et al.

Fig. 10 Casthouse workers watching cast start-up in front of TV screen

the psychological side of hands-free casting and the question: “How to keep the workers away from the casting table 24 h a day, 365 days a year?” Although having prepared the casting pits and the casting practices for hands-free casting, we have observed, that people tend to stand on the casting table, especially outside the normal working time of the management. This was related to the fact, that AMAG casting GmbH cast more than 100 different products (with one individual casting practice for each product) at each casting machine and the workers where not sure, if the casting practice is already optimized to cast hands-free. Involving the workers to find a solution, they have derived a very simple way to get confident. Using a big flip-chart, containing a list with all existing casting practices, each shift has put a signature beside the product/practice, when they thought hands-free casting is possible. Otherwise, they put suggestions for further practice improvement on the flip chart. Finally, the signatures of all four shift leaders were the signal for them (all of them have approved the final casting practice including their suggestions), to cast hands-free, standing in front of the TV screen, watching the cast as it can be seen in Fig. 10.

Conclusion Hands-free casting represents a big step forward regarding casthouse safety and a standardized process. The required technology is available and must be implemented, sometimes tailored. There are a lot of requirements, like metal level control in the mould etc., which are already state of the art of available casting machines, but there are a lot of manual operations, which must be automated to fulfill the 100% hands-free casting modus. This article focuses on essential devices for automatic launder filling, a fully automatic melt distribution system in the mould and on a visualization system for the workers, to watch the cast from a safe place.

Hands-Free Casting at AMAG Casting GmbH—It Is Possible!

Beside the technological improvements, also psychological barriers of workers are put under consideration and a solution is given for better acceptance of using the hands-free casting modus. Further developments must be carried out regarding the “crack free check” after the start-up. This must also be done from the operator cabin, by using camera systems. It is easy to apply cameras for oversized casting pits and casting one single ingot—one camera box in each corner, equipped with wipers to clean off the field of view, is a sufficient solution. But common multi-strand casting pits are usually not oversized and the space between the ingots is very small. Very small cameras with a 180° angle of view are available, but it is very difficult to find a solution to wipe off waterdrops. Furthermore, depending on the installation of the water supply, the front sides of the ingots are not so easy to visualize. In a worst-case scenario, 4 cameras are needed for one single ingot, resulting in 24 cameras (including the mounting consoles, cabling etc.) for a six-strand casting pit.

843

Besides all difficulties with the hands-free casting modus, it is indispensable to reach this ambitious target for a higher safety level and improved process standardization.

References 1. Lowery, AW (2017) Has Recent Advances in Direct Chill Casting Made Us Less Safe? In: Ratvik, AP (ed) Light metals 2017. The Minerals, Metals & Materials Society, Pittsburgh; Springer, New York, pp 1089–1093. 2. Towsey, N, Scheele G, Luetzerath A, Schoell E (2019) Sheet Ingot Casting Improvements at TRIMET Essen. In: Chesonis, C (ed) Light metals 2019. The Minerals, Metals & Materials Society, Pittsburgh; Springer, New York, pp 953–959. 3. Lück, M (2018) DC-Casting Technology focusing on Water Cooling & Water Quality Demand. Presented at the NorCast® 2018—The 12th Nordic Aluminium Casthouse Conference, Arendal, Norway, 04–06 June 2018.

User-Friendly Surveillance Tools to Prevent Bleed-Out During Cast Start M. Badowski, D. Krings, G. U. Gruen, W. Droste, Ph. Meslage, and B. Jaroni




Abstract

Keywords

Cast house operation implies high risk processes related to molten metal handling like charge preparation or cast start. Hydro’s R&D center Bonn has the ambition to provide procedures and user-friendly tools helping to prevent these risks. Insufficient or deviating cooling conditions in the water curtain of the secondary cooling zone are common causes for bleed-outs, especially during cast start with the risk of water-melt explosions. They typically rely on the flow conditions in the sump, the stress-strain conditions in the solidifying shell and insufficient water supply for cooling. Hydro’s “water tester” is a robust tool to check the water flow rate and distribution in the water curtain of all types of casting molds. It is well accepted by operators due to its easy and ergonomic use. The thermopile-array based “bleed-out detector” represents an even more detailed analysis tool of the cooling features of the used molds. It is a cost-efficient tool visualizing the water and temperature distribution in the secondary cooling zone suitable to trigger alarms or even automatic cast aborts. This paper describes the technological approach and application cases for both tools.

Cast house safety Cast start Surveillance technology

M. Badowski
D. Krings (&)
G. U. Gruen
W. Droste Hydro Aluminium Rolled Products GmbH, Georg-von-Boeselager-Str. 21, 53117 Bonn, Germany e-mail: [email protected] M. Badowski e-mail: [email protected] Ph. Meslage Aluminium Norf GmbH, Koblenzer Strasse 120, 41468 Neuss, Germany e-mail: [email protected] B. Jaroni Hydro Aluminium Rolled Products GmbH, Koblenzer Strasse 122, 41468 Neuss, Germany e-mail: [email protected]




Bleed-out




Introduction Aluminium operations bear several safety hazards for equipment and personnel. The most critical risks involving fatality and life-changing injury are in focus at Hydro to develop life-saving countermeasures and include: • • • • • • •

Overhead crane safety Mobile equipment Energy isolation Fall prevention Contractor management Confined space entry Molten metal handling.

The first three mentioned topics are according to Grandfield [1] the most frequent root-causes for fatalities in Aluminium operation, while cast house explosions based on the interaction of liquid Aluminium with water is a particular risk in cast house operation and resulted according the global survey of the Aluminium Association in average in 3 fatalities per year in the Aluminium industry globally [2]. Furnace charging and remelting have been identified in this global survey as the operation giving rise to most reported incidents, especially Force 2 and Force 3 explosions with fatality potential [3] followed by the casting process itself and here especially the cast start-up [4]. Richter and Ekenes [5] assessed the AA data with special focus to DC casting and identified 78% of the incidents within the period 1980– 2002 to be related to the cast start and with Bleed-outs/ Bleed-over as the most frequent fundamental root-cause for incidents related to casting.

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_112

844

User-Friendly Surveillance Tools …

The occurrence of bleed-outs even in modern highly automized cast houses is a result of the complex interaction of physical phenomena taking place during the start-up phase of DC casting. Figure 1 shows an example of a bleed-out in the corner of 600 mm sheet ingots. The integrity of the solidifying shell is depending on its growth, mechanical properties and stress-strain conditions throughout the starting phase [6]. The local flow conditions in the sump [7, 8] as well as the general temperature development of the casting line [9] can lead to insufficient stability of the shell in the same way as insufficient or inhomogeneous heat extraction from the solidifying shell. The latter is strongly depending on the water-cooling conditions in the secondary cooling zone whereas aspects like water chemistry [10], mold maintenance [11] and casting recipe [12] getting importance. The friction towards the mold and the development of the butt curl [9, 13] give additional stress to the solidifying shell. Hydro’s R&D center Bonn has the ambition to provide procedures and user-friendly tools helping to prevent cast house risks. The current paper describes two equipment developments at R&D and application cases into Hydro’s operation: 1. Water testing bucket 2. Bleed-out detector. The water testing bucket is a simple tool to check the water flow distribution of molds during the pre-cast check.

845

The system was developed with special attention to the usability in day-to-day operation to achieve a high operator acceptance level. This includes ergonomic handling as well reliable and meaningful recordings that trigger preventive measures like mold change and maintenance before the critical situation occurs. The bleed-out detector is a more detailed analysis tool monitoring online the temperature development of the solidifying shell with the ambition to alarm the casting operator before the bleed-out occurs or reaches a critical state to apply suitable countermeasures and if necessary, to trigger automatic cast aborts resulting in a safer environment and potentially lower downtime. In today’s cast house operation, the check of the water supply is typically included in the pre-cast check procedure and includes monitoring of the global water supply to the molds or the casting table as well as visual inspection and first line maintenance (cleaning of holes or slits), which is an essential part to achieve a safe setup [4]. Systems to monitor the water flow in sections of individual molds exist [14] but are generally used to calibrate the flowrate during implementation and casting tests rather than a tool for continuous follow-up of the mold performance. This is surprising as Richter and Ekenes [5] recommended already 2005: “Water patterns should be uniform. A standard bucket test should be deployed to verify variations in flow within a mold and from mold to mold. Normally, no more than 10% variation in flow can be tolerated for a successful start-up. More critical applications require 5% or less variation in flow”. The observation of bleed-out is typically done today using a flashlight and walking around the casting pit, which brings the operator close to the risk. At more modern casting this situation is avoided by an increased automation level [12], which allows in best case a “hands-free” cast start but reduces the visibility of the incident development. Casting surveillance technologies received therefore in recent years a higher attention, starting from CCTV installations [12] observing the casting pit to thermal imaging [15] or pressure control [16] of each billet triggering alarm or even initiation automatic closing of the mold [16].

Technology Water Testing Bucket The water testing bucket aims to provide the cast house operators a simple, easy-to operate and reliable tool to check the water flow distribution of the mold sets during the pre-cast check procedure and the cast house organization useful data about a critical equipment. The tool therefore needs to combine different aspects: Fig. 1 Bleed-out in corner area of a sheet ingot

846

M. Badowski et al.

• Good ergonomics and user-friendliness • Robust for cast house application • Acceptable data accuracy and precision. Figure 2 shows a sketch of the basic setup and functionalities of the tool developed at Hydro Bonn. A metal container with a total volume of 1.5 l is equipped with two optical level switches at different heights. The container width of about 100 mm and volume is designed to ensure a representative section of the water curtain, especially for molds with hole-design, and suitable filling times for standard flow rates. The exact width of the container is adjusted to the actual mold design, especially to the water hole distance in the predefined measurement positions. Hence it is important to keep those positions the same for every measurement, to ensure equal measurement conditions. The tool is maneuvered by the operator standing upright in the targeted monitoring section and kept in position by positioning pins against front and top side of the mold. The design of the system is allowing for flexible adjustment of these positioning pins considering that the unit should be applicable to different kinds of mold technologies. In this target position the water enters the container via a deflector plate and fills the container up within 1–3 s. The optical sensors simply sending a start and stop signal for the central section of the container (10–90% of the volume) to the controller unit, where the actual local flow rate is calculated and visualized. After each measurement the water is released from the container via release plug on the bottom side by simply placing the container on the ground.

Fig. 3 Measurement accuracy assessment of “water testing bucket”

In order to utilize the water testing bucket as pre-cast check and mold performance follow-up tool the equipment must report the monitored flow rate with enough preciseness and accuracy. The actual performance of each unit was checked before on-site use in a test setup by parallel recording of the total equipment weight during the container filling between start and stop signal. Figure 3 shows the monitored data based on the weight measurements for a wide range of applied water flow rates in comparison to the actual container volume between the two optical sensors. In this test sequence as in all other tests the system showed a good preciseness of lattice diffusion > surface diffusion > lattice diffusion in anthracite cathodes.

Mechanism Understanding of Sodium Penetration …

Considering practical measured results, sodium penetration would mainly take place by vapor transport rather than through the solid diffusion under high cathode porosity condition. (4) Related to practical industry applications, it is convincing that less material structural defect, higher graphitization degree, lower electrolysis temperature, and so on would contribute to the resistance of carbon cathodes for sodium penetration.

1307

12.

13. 14.

15. Acknowledgements The authors acknowledge the financial support of the National Key R&D Program of China (2017YFC0210401), the National Natural Science Foundation of China (51674300, 51874365, 61751312, and 61533020), the Natural Science Foundation of Hunan Province, China (2018JJ2521), the Graduate Research Program of CSU (201844), and Hunan Provincial Innovation Foundation For Postgraduate (CX20190112).

References 1. Thonstad, J., Fellner, P., Haarberg, G. M., Hives, J., Kvarde, H., & Sterten, A. (2001). Aluminium Electrolysis: Fundamentals of the Hall-Herault Process. 2. Brisson, P. Y., Soucy, G., Fafard, M., & Dionne, M. (2005). The effect of sodium on the carbon lining of the aluminum electrolysis cell—a review. Canadian metallurgical quarterly, 44(2), 265– 280. 3. Dell, M. B. (2016). Reaction between carbon lining and hall bath. In Essential Readings in Light Metals (pp. 946–952). Springer, Cham. 4. Øye, H. A., Thonstad, J., Dahlqvist, K., Handa, S., & De Nora, V. (1996). Reduction of sodium induced stresses in Hall–Heroult cells. Aluminium, 72(12), 918–992 5. Li, J., Wu, Y. Y., Lai, Y. Q., Liu, W., Wang, Z. G., Liu, J., & Liu, Y. X. (2008). Simulation of thermal and sodium expansion stress in aluminum reduction cells. Journal of Central South University of Technology, 15(2), 198–203. 6. Dewing, E. W. (1963). Reaction of sodium with nongraphitic carbon-reactions occurring in linings of aluminum reduction cells. Transactions of the Metallurgical Society of AIME, 227(6), 1328. 7. Brisson, P. Y., Fafard, M., & Soucy, G. (2006). Investigation of electrolyte penetration in three carbon cathode materials for aluminum electrolysis cells. Canadian metallurgical quarterly, 45(4), 417–426. 8. Zhao, F. A. N. G., Zhang, K., LÜ, X. J., Li, L. B., Jun, Z. H. U., & Li, J. (2013). Alkali metals (K and Na) penetration and its effects on expansion of TiB2-C composite cathode during aluminum electrolysis. Transactions of Nonferrous Metals Society of China, 23(6), 1847–1853. 9. Callister Jr, W. D., & Rethwisch, D. G. (2012). Fundamentals of materials science and engineering: an integrated approach. John Wiley & Sons. 10. Gao, Y., Xue, J., Zhu, J., Jiao, K., & Jiang, G. (2011). Characterization of Sodium and Fluoride Penetration into Carbon Cathodes by Image Analysis and SEM-EDS Techniques. In Light Metals 2011 (pp. 1103–1107). Springer, Cham. 11. Li, J., Fang, Z., Lai, Y. Q., Lü, X. J., & Tian, Z. L. (2009). Electrolysis expansion performance of semigraphitic cathode in [K

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

27.

28.

29.

3 AlF 6/Na 3 AlF 6]-AlF 3-Al 2 O 3 bath system. Journal of Central South University of Technology, 16(3), 422–428. Zolochevsky, A., Hop, J. G., Servant, G., Foosnaes, T., & Øye, H. A. (2003). Rapoport–Samoilenko test for cathode carbon materials: I. Experimental results and constitutive modelling. Carbon, 41 (3), 497–505. Feynman, R. P. (1960). Soil engineering in the Arctic. Engineering and Science, 23(8), 22–36. Huang, Y., Cannon, F. S., Guo, J., Watson, J. K., & Mathews, J. P. (2016). Atomistic modelling insight into the structure of lignite-based activated carbon and benzene sorption behavior. RSC Advances, 6(61), 56623–56637. Brochard, L., Vandamme, M., Pellenq, R. J. M., & Fen-Chong, T. (2012). Adsorption-induced deformation of microporous materials: coal swelling induced by CO2–CH4 competitive adsorption. Langmuir, 28(5), 2659–2670. Sun, X., Wang, Z., & Fu, Y. Q. (2017). Adsorption and diffusion of sodium on graphene with grain boundaries. Carbon, 116, 415– 421. Liang, Z., Fan, X., Zheng, W., & Singh, D. J. (2017). Adsorption and formation of small Na clusters on pristine and double-vacancy graphene for anodes of Na-ion batteries. ACS applied materials & interfaces, 9(20), 17076–1708. Zhong, Q., Mao, Q., Zhang, L., Xiang, J., Xiao, J., & Mathews, J. P. (2018). Structural features of Qingdao petroleum coke from HRTEM lattice fringes: Distributions of length, orientation, stacking, curvature, and a large-scale image-guided 3D atomistic representation. Carbon, 129, 790–802. Pappano, P. J., Mathews, J. P., & Schobert, H. H. (1999). Structural determinations of Pennsylvania anthracites. ACS Division of Fuel Chemistry, Preprints, 44(3), 567–568. Huang, L., Ning, Z., Wang, Q., Qi, R., Zeng, Y., Qin, H., … & Zhang, W. (2018). Molecular simulation of adsorption behaviors of methane, carbon dioxide and their mixtures on kerogen: Effect of kerogen maturity and moisture content. Fuel, 211, 159–172. Sui, H., & Yao, J. (2016). Effect of surface chemistry for CH4/CO2 adsorption in kerogen: A molecular simulation study. Journal of Natural Gas Science and Engineering, 31, 738–746. Gasteiger, J., & Saller, H. (1985). Calculation of the charge distribution in conjugated systems by a quantification of the resonance concept. Angewandte Chemie International Edition in English, 24(8), 687–689. Essmann, U., Perera, L., Berkowitz, M. L., Darden, T., Lee, H., & Pedersen, L. G. (1995). A smooth particle mesh Ewald method. The Journal of chemical physics, 103(19), 8577–8593. Zhang, J., Clennell, M. B., Dewhurst, D. N., & Liu, K. (2014). Combined Monte Carlo and molecular dynamics simulation of methane adsorption on dry and moist coal. Fuel, 122, 186–197. Bussi, G., Donadio, D., & Parrinello, M. (2007). Canonical sampling through velocity rescaling. The Journal of chemical physics, 126(1), 014101. Martyna, G. J., Klein, M. L., & Tuckerman, M. (1992). Nosé– Hoover chains: The canonical ensemble via continuous dynamics. The Journal of chemical physics, 97(4), 2635–2643. Berendsen, H. J., Postma, J. V., van Gunsteren, W. F., DiNola, A. R. H. J., & Haak, J. R. (1984). Molecular dynamics with coupling to an external bath. The Journal of chemical physics, 81(8), 3684– 3690. Andersen, H. C. (1983). Rattle: A “velocity” version of the shake algorithm for molecular dynamics calculations. Journal of Computational Physics, 52(1), 24–34. Xu, Z., Lv, X., Chen, J., Jiang, L., Lai, Y., & Li, J. (2016). Dispersion-corrected DFT investigation on defect chemistry and

1308

30.

31.

32.

33.

34.

35.

potassium migration in potassium-graphite intercalation compounds for potassium ion batteries anode materials. Carbon, 107, 885–894. Perdew, J. P., Ruzsinszky, A., Csonka, G. I., Vydrov, O. A., Scuseria, G. E., Constantin, L. A., … & Burke, K. (2008). Restoring the density-gradient expansion for exchange in solids and surfaces. Physical review letters, 100(13), 136406. Perdew, J. P., Burke, K., & Ernzerhof, M. (1996). Generalized gradient approximation made simple. Physical review letters, 77 (18), 3865. Laasonen, K., Car, R., Lee, C., & Vanderbilt, D. (1991). Implementation of ultrasoft pseudopotentials in ab initio molecular dynamics. Physical Review B, 43(8), 6796. Yang, S., Li, S., Tang, S., Dong, W., Sun, W., Shen, D., & Wang, M. (2016). Sodium adsorption and intercalation in bilayer graphene from density functional theory calculations. Theoretical Chemistry Accounts, 135(7), 164. Govind, N., Petersen, M., Fitzgerald, G., King-Smith, D., & Andzelm, J. (2003). A generalized synchronous transit method for transition state location. Computational materials science, 28(2), 250–258. Joncourt, L., Mermoux, M., Touzain, P. H., Bonnetain, L., Dumas, D., & Allard, B. (1996). Sodium reactivity with carbons. Journal of Physics and Chemistry of Solids, 57(6–8), 877–882.

J. Li et al. 36. Atria, J. V., Rusinko, F., & Schobert, H. H. (2002). Structural Ordering of Pennsylvania Anthracites on Heat Treatment to 2000– 2900° C. Energy & fuels, 16(6), 1343–1347. 37. Sorlie, M., & Oye, H. A. (1994). Cathodes in Aluminium Electrolysis, 2nd Edn, p. 185. Aluminium-Verlag, Dusseldorf. 38. Jobic, H., Skoulidas, A. I., & Sholl, D. S. (2004). Determination of concentration dependent transport diffusivity of CF4 in silicalite by neutron scattering experiments and molecular dynamics. The Journal of Physical Chemistry B, 108(30), 10613–10616. 39. Zhao, Y., Feng, Y., & Zhang, X. (2016). Molecular simulation of CO2/CH4 self-and transport diffusion coefficients in coal. Fuel, 165, 19–27. 40. Skoulidas, A. I., & Sholl, D. S. (2003). Molecular dynamics simulations of self-diffusivities, corrected diffusivities, and transport diffusivities of light gases in four silica zeolites to assess influences of pore shape and connectivity. The Journal of Physical Chemistry A, 107(47), 10132–10141. 41. Ziambaras, E., Kleis, J., Schröder, E., & Hyldgaard, P. (2007). Potassium intercalation in graphite: A van der Waals density-functional study. Physical Review B, 76(15), 155425. 42. Luo, W., Wan, J., Ozdemir, B, Bao, W., Chen, Y., Dai, J., … & Hu, L. (2015). Potassium ion batteries with graphitic materials. Nano letters, 15(11), 7671–7677.

Anhydrous Carbon Pellets— An Engineered CPC Raw Material Les Edwards, Maia Hunt, and Christopher Kuhnt

Abstract

The paper reports on a new technology Rain Carbon has been developing to produce an engineered calcined petroleum coke (CPC) product. Agglomeration of green petroleum coke (GPC) fines through either granulation/ pelletizing or briquetting can be used to produce a CPC product with improved properties. Pelletizing GPC fines can produce high bulk density pellets hereafter referred to as anhydrous carbon pellets or ACP. ACP densifies when calcined to produce a high bulk density, free flowing CPC product. The spherical particle shape provides improved particle packing densities compared to irregular shaped CPC particles during anode production. The paper will summarize key results including pilot anode properties showing improvements in baked anode density, electrical resistivity and other properties when using calcined ACP. A key benefit is the ability to produce a fully engineered CPC product and Rain Carbon is currently constructing full scale, commercial plants to produce ACP. Keywords

Petroleum coke Agglomeration





Calcination ACP




Anode




Density




L. Edwards (&) VP Production Control and Technical Services, Rain Carbon Inc, Stamford, CT, USA e-mail: [email protected] M. Hunt Rain CII Carbon, Covington, LA, USA C. Kuhnt RÜTGERS Germany GmbH, Castrop Rauxel, Germany

Introduction Agglomeration of fine particle size, bulk solids is a well-established process technology used by many different industries. One of the most well-known applications is granulation or pelletizing of iron ore fines. This is done on a massive scale with some plants producing more than 9 million tons per year. At the other end of the spectrum in terms of volume and product value, is the pharmaceutical industry which typically uses high speed pellet presses to make tablets. Between these two extremes many different agglomeration technologies are used including briquetting, spray drying/granulation and pellet mills which are now routinely used to make wood or biomass pellets for heating and/or power generation [1]. In 2011, Rain Carbon started to experiment with the agglomeration of green petroleum coke (GPC) fines as a way to improve calcining economics. When a rotary kiln is used for calcining, around 10% of the finest particle size GPC becomes entrained in the counter-current flue gas stream inside the kiln. The fines are carried out the back end of the kiln and into a high temperature combustion chamber or pyroscrubber where they are combusted along with any remaining volatile matter (VM). The heat generated in this process is typically recovered and used to produce steam in a heat recovery steam generator (HRSG). Most plants with a HRSG generate electrical power via a steam turbine generator. The sale of power (or steam) is normally an important economic component of the calciner. GPC fines loss is much lower in a shaft calciner (typically < 3%) due to the absence of a counter-current flue gas stream [2] inside the calciner. As GPC prices increase, rotary kiln calciners are incentivized to reduce GPC fines carryover. Since power prices are normally fixed, it is more favorable for a calciner to convert as much GPC to calcined petroleum coke (CPC) as possible. In 2011, low sulfur GPC prices increased dramatically with US Gulf prices hitting US$400/ton in Q3 2011 [3]. The idea to separate out and agglomerate GPC fines

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_179

1309

1310

using one of the commercially available technologies was conceived during this period. It provides a way to reduce fines carryover and recover the fines as CPC product. Granulation to produce spherical shaped pellets was selected as the first technology to evaluate since there are some potential benefits in producing round particles in terms of particle packing density and powder flowability. A recent paper [4] highlights the particle packing benefits of spherical shaped CPC particles. A second benefit of agglomerating GPC fines is an environmental one. When fine particle size GPC is combusted in a pyroscrubber, any sulfur in the GPC will be fully converted to SO2 in the flue gas stream. During calcination, all cokes lose some sulfur so the sulfur level of CPC is always lower than the GPC sulfur level. For low sulfur cokes (1000 ppm) which directly impacts SO2 ground level concentrations and ambient air quality. Fines agglomeration has no impact on smelter SO2 emissions since all sulfur in petroleum coke is ultimately emitted through the bake furnace and potroom exhaust stacks.

Rationale for GPC Fines Agglomeration Although agglomeration is a well-known technology, the idea to agglomerate GPC fines was based on an understanding of what would likely happen to these agglomerates during calcination. It was expected that the agglomerated fines would densify and form a calcined product with good bulk density and strength. The agglomeration tendency of GPC has been described previously [5] in relation to its contribution to problems like coke ring formation. GPC fines typically contain a higher volatile matter (VM) content than coarser coke particles due to the heterogeneity of coke formation in the delayed coker. Well-coked material at the bottom of the coke drum has a lower VM and is harder than coke at the top of the drum. When the drum is de-coked with a high-pressure water jet, the softer, higher VM coke breaks down into fines and the coarser, lower VM coke remains in larger coke pieces.

L. Edwards et al.

If the fines are agglomerated and heated, the relatively high VM material softens and generates condensable tars which make it sticky. With further heating, these tars undergo cracking reactions which generate lighter hydrocarbon molecules like CH4 and H2 [6] which are then combusted in the kiln and pyroscrubber. With further heat treatment, the tars form solid coke which binds particles together in close proximity to each other. This phenomenon also leads to the formation of an agglomerated product from a shaft calciner [2] and is the fundamental basis for the technology development described in this paper. If GPC fines can be agglomerated successfully into a high bulk density precursor, the agglomerate should densify and develop strength during calcining. Preliminary agglomeration trials were undertaken using granulation/pelletizing equipment similar to that used by ceramic proppant manufacturers [7]. Initial results were encouraging and Rain Carbon filed two patents on the concept in 2011 which were granted in 2013 and 2014 [8, 9]. The scale of work done on the project gradually increased after that with the ultimate goal of developing a commercially viable process technology. Rain Carbon is now in the early stages of constructing a plant to make ACP.

Initial Results with Lab Scale Pelletizing Tests In the first set of experiments, GPC was screened at a particle size of 12 Tyler mesh (1.4 mm). The -1.4 mm fines were pelletized using a wide range of binders such as CTP (coal tar pitch), PVA (polyvinyl alcohol), CMC (carboxymethyl cellulose), starch, molasses and dextrin (sugar). Most of the binders worked well in terms of the ability to form pellets at an acceptable binder level (1–5%) and with sufficient green strength to allow handling after drying. CTP was the exception and the GPC had to be dried first to remove the moisture and then heated to around 150 °C prior to pelletizing. A *110 °C Mettler softening point CTP was used and added in a solid form. Once the pitch melted, the pellets formed readily but a very high binder percentage was required (25%) to achieve acceptable results. The dried pellets from the above were calcined in a static lab furnace to a temperature of 1300 °C. Pellet bulk densities were excellent after calcining with results shown in Table 1. The bulk densities were measured by Rain Carbon’s standard 8  14 Tyler mesh (1.18–2.36 mm) vibrated bulk density (VBD) method. Real densities and Lc’s were also measured to confirm that the target calcination temperature was achieved for each batch of pellets. For comparison, VBD results are included for full scale, rotary kiln calcination of the coke used for the pelletizing trials (the non-pelletized, industrially calcined form of this coke which is labeled as Regular CPC in Table 1).

Anhydrous Carbon Pellets—An Engineered CPC Raw Material Table 1 Bulk density results of initial pellet batches versus regular CPC

1311

Pellet test

Binder

8  14 VBD (g/cc)

Real density (g/cc)

Lc (A)

1

A

0.982

2.060

28.4

2

B

1.005

2.072

30.7

3

C

0.946

2.070

31.3

5

D

0.840

2.076

32.3

5

E

1.033

2.070

31.0

Regular CPC

**

0.780

2.072

31.0

Static lab calcining always gives higher bulk densities than rotary kiln calcining since it is not possible to emulate the rapid heat up rate and devolatilization that occurs in a rotary kiln. The results nonetheless, provided sufficient incentive to pursue additional development and testing of ACP. The only pellets that did not perform well during the lab calcining tests were those produced with the CTP binder. The pellets did not survive calcination due to the high volatile loss from the CTP (*45%) binder. Figure 1 shows a photograph of the starting GPC fines, the ACP product and calcined ACP. The green pellets are always dried after pelletizing to develop sufficient green strength for further mechanical handling and transfer via conveyor belts etc. A simple crush strength test was developed to test the pellet strength after drying and calcining and this was useful to check the performance of different binders and pelletizing conditions. The crush strength typically increases by a factor of 3–4 times after calcining due to pellet densification with some typical results shown in the next section.

Comparison of Pelletizing and Briquetting Rain Carbon has focused most of its agglomeration efforts on pelletizing but some work has also been done testing briquetting as an alternative. Figure 2 shows a photograph of

Fig. 1 GPC fines, ACP and calcined ACP

briquettes made with GPC screened to -2 mm and the same briquettes after calcination (in a static lab kiln). Several different binders were tested in this work and the performance varies significantly. Binders that work well in pelletizing do not necessarily work well in briquetting. Compared to APC, the briquettes were more brittle and had significantly lower calcined crush strengths. In each crush strength test, 20 pellets or briquettes were tested to determine the load in kg that the pellet or briquette could support before collapsing. Since the pellets are physically much smaller than briquettes, an equivalent load in kg represents a significantly higher pressure. Table 2 includes some comparative data for briquettes and ACP. The results for Coke B represent a direct comparison between briquetting and pelletizing for the same coke source. Since briquettes are all produced to the same final size and shape, it was not possible to measure bulk densities on naturally occurring particle size fractions. The only bulk densities measured were those on briquettes crushed after calcination. In general, the calcined ACP has significantly higher strength and 8  14 VBD compared to calcined briquettes. The 28  48 Tyler mesh (0.3–0.6 mm) VBD’s were similar since the CPC is crushed to a size comparable to the starting GPC size. It should be possible to increase the briquette strength by optimizing the binder content and additional work is planned in this area. Batches of briquettes will also be calcined in a

1312

L. Edwards et al.

Fig. 2 Green and calcined briquettes

Table 2 Crush strength and bulk density results with Briquettes and APC Sample description

Crush strength Green crush strength (kg)

CPC bulk density Calcined crush strength (kg)

0.3–0.6 mm VBD (g/cc)

1.2–2.4 mm VBD (g/cc)

Briquette batch 1 Coke A

7.7

5.0

0.893

0.752

Briquette batch 2 Coke B

7.8

7.5

0.847

0.769

Briquette batch 3 Coke C

3.5

4.2

0.909

0.752

Pellet batch 1 Coke B

11.8

24.1

0.893

0.870

Pellets batch 2 Coke D

6.4

23.1

0.943

0.893

Pellets batch 3 Coke D

13.2

24.1

0.926

0.893

pilot scale rotary kiln calciner to see how well they stand up to the faster heating and devolatilization rates and mechanical tumbling. Briquetting is a much simpler processing technology than pelletizing so it is attractive from this perspective. One significant downside however, is the non-spherical shape of briquettes. The shape selected for the Rain Carbon trials was as close to spherical as practical but did not give the same particle packing benefits as spherical pellets.

Larger Scale Pelletizing Trials In addition to a faster heat-up rate, the dynamic conditions inside a rotary kiln are very different to those in a static laboratory furnace. One early concern with ACP was that the pellets would not survive the aggressive mechanical tumbling and devolatilization in a full-scale kiln. To get more confidence on this, several batches of ACP were calcined in

a small pilot-scale rotary calciner. For these trials, a blend with 75% regular GPC and 25% ACP was used. The kiln was operated in a batch mode with a continuously rotating drum and moving coke bed. A large gas-fired burner was able to achieve similar heat-up rates to a full-scale kiln. A photograph of the equipment used is shown in Fig. 3. Previous studies with this kiln [10] had shown comparable VBD results to a full-scale kiln which gave confidence in the method. The pellets calcined in the above kiln survived well and retained their original spherical shape. The bulk density of the blend containing 25% ACP was similar to a batch of GPC calcined in the same furnace under the same conditions. The key finding from the test was that the pellets were not destroyed from the rapid VM loss and tumbling in the kiln. This provided the confidence to produce much larger batches of pellets (requiring significantly more effort) for calcination trials in a full-scale rotary kiln.

Anhydrous Carbon Pellets—An Engineered CPC Raw Material

1313

Fig. 3 Pilot scale batch rotary kiln (COREM, Quebec City, Canada)

Full Scale Rotary Kiln Trials Several 4–10 ton batches of ACP from different green cokes sized to -1.4 mm were produced and calcined in a full scale rotary kiln at the Rain Carbon Lake Charles calcining plant in Louisiana. The two kilns at this facility normally operate with a feed rate of 32–35 WMT/h (wet metric tons per hour) so a method was developed to break the GPC feed stream to add a batch of ACP for calcining. The residence time through the kiln is well known, so it was a matter of waiting for the calcined ACP to exit from the cooler for sample collection. There was co-mingling of CPC at the start and end of the trial but it was quite easy to collect a sample of 100% pellets mid-way through the run. Every batch of ACP calcined in the full-scale kiln produced good quality CPC product with no significant degradation of the pellets despite the aggressive heat-up rate and tumbling. Results for ACP produced from a low sulfur coke are shown in Table 3. Coke A was a good quality GPC with a VM level of *11%. The first row shows VBD results for the regular, non-pelletized version of Coke A. The second row shows VBD results measured on CPC pellets (ACP A) produced from Coke A. For comparative purposes, a baseline rotary kiln blend is also included. Rain Carbon has been using this blend since 2013 for pilot anode studies and it is used as a reference CPC blend for studies with different materials such as CPC, coal tar pitches, petroleum pitches.

Table 3 Bulk density results from full scale calcination trial

CPC sample

CPC sulfur (%)

Several different methods were used to measure the CPC bulk densities in Table 3. The 0.3–0.6 mm VBD results were measured via the common ASTM D4292 test on a sample crushed to 28  48 Tyler mesh (0.3–0.6 mm). The 1.2–2.4 mm VBD results were measured on samples crushed to 8  14 Tyler mesh. This method gives good information about macro-porosity in larger coke pieces and has been used by Rain Carbon for more than 40 years to monitor daily CPC bulk densities. The other four bulk density results were measured on naturally occurring fractions screened from the CPC with no crushing. A trans-axial density analyzer was used to measure the bulk densities on these fractions via the ASTM 8097-17 method [11]. The first point to note in the above, is that the 0.3– 0.6 mm VBD for Coke A was the same for regular CPC and CPC produced from ACP. It was also more or less the same as the VBD for the baseline CPC (BL). Since the pellets were produced with -1.4 mm GPC fines, much of the starting GPC already falls in the 0.3–0.6 mm size range. The fines were agglomerated to produce pellets in the size range of *2 to 10 mm. To run the VBD test, the CPC pellets are crushed to a size of 0.3–0.6 mm. This is why the VBD results from this test show no real change or improvement with pelletizing. Pelletizing GPC does not change the structural form of the starting coke and when the spherical pellets are crushed to a finer size, they produce irregular shaped particles. Any particle packing benefits associated with spherical shape pellets is therefore lost.

Vibrated bulk density (g/cc)

Naturally occuring fractions bulk density (g/cc)

0.3–0.6 mm

1.2–2.4 mm

4–8 mm

2–4 mm

1–2 mm

0.5–1 mm

Regular A

1.8

0.909

0.781

0.627

0.681

0.746

0.813

ACP A

2.0

0.909

0.833

0.868

0.853

0.806

0.829

Baseline BL

2.8

0.901

0.775

0.685

0.722

0.769

0.802

1314

The situation is quite different for all other bulk density results measured on the calcined ACP. The 8  14 VBD results are *0.05 g/cc higher which is a significant improvement. Most of this increase is due to the improved packing density with the spherical particle shape but lower open and closed porosity is also a contributor and some supporting results are provided in the next section. Not all the particles in the test were spherical since all the +8 mesh (+2.36 mm) material gets crushed to 8  14 mesh for the test. Cannova et al. [4] has discussed the potential benefits of rounding particles through selection of different crushing technologies to improve product bulk densities and these data highlights the positive impact of a spherical particle shape. The improvement in bulk density can be seen even more clearly with the bulk densities measured on the naturally occurring fractions. The biggest improvement (+0.24 g/cc or *38%) occurs with the 4–8 mm pellets vs the regular CPC screened to 4–8 mm. Coarse coke particles typically also have significant open and closed porosity and ACP eliminates some of this porosity. Figure 4 shows some low magnification, scanning electron microscopy images of calcined ACP particles compared to regular Coke A CPC. The images highlight the spherical shape of ACP versus the irregular shape of Coke A and also of the much lower open porosity in the calcined ACP particles. The 2–4 mm and 1–2 mm uncrushed particles also show a significant improvement relative to irregular shaped

L. Edwards et al.

particles from the regular CPC product but the magnitude of the improvement decreases as the average particle size decreases. The difference for the finest particle size material (0.5–1 mm) is much smaller and within the margin of error for the bulk density test. This is because most of the coke in this size range is non-pelletized given that the starting GPC was sized to 2 mm given the size of the dry flow media particles (diameter of 100–150 µm). Samples of a high volatile matter (13.5%), low sulfur GPC (Coke D) were screened into different naturally occurring particle sizes: 0–2, 2–4 and 4–8 mm. The 2 mm fines were pelletized to produce pellets with a range of particle sizes from *2 to 12 mm. The envelope densities were measured on the naturally occurring 2–4 mm and 4– 8 mm GPC particles and the 2–4 mm and 4–8 mm pellets

Fig. 4 SEM images of regular Coke A CPC (top) and Coke A calcined ACP (bottom)

Anhydrous Carbon Pellets—An Engineered CPC Raw Material Table 4 Envelope density and porosity results for regular and pelletized GPC

1315 Green coke

Calcined coke

Sample Description

Envelope density (g/cc)

Porosity (%)

Envelope density (g/cc)

Porosity (%)

Coke D: 2–4 mm non-pelletized

1.10

19.6

1.20

42.1

Coke D: 4–8 mm non-pelletized

1.15

16.2

1.29

37.5

Coke D: 2–4 mm pelletized

1.12

18.0

1.53

25.4

Coke D: 4–8 mm pelletized

1.14

16.2

1.54

25.2

produced from the fines. Both sets of samples were then calcined in a lab furnace and the envelope densities were re-measured after calcining. When coke real densities are measured, the test also calculates the average particle porosity. Results are shown in Table 4. There is little difference between the envelope densities and porosities for the naturally occurring GPC particles and the pelletized GPC fines. The calcined results are significantly different however. The envelope densities of the calcined pellets for both particle size ranges are significantly higher than the non-pelletized forms of coke D. The porosities are also significantly lower. The precision of the envelope density test is not particularly good (*0.05 g/cc) but the differences measured here clearly show that pelletizing GPC fines reduces the porosity of the calcined product relative to non-pelletized particles of the same size. This highlights the positive contribution that open and closed porosity reductions make on the bulk density improvements shown in Table 3. The improvements are due to a combination of the spherical particle shape resulting in a higher packing density and lower porosity in the calcined pellets.

In this next section, pilot anode results are presented for anodes made with formulations containing calcined ACP made from Coke A in Table 3. For reference, pilot anodes were also produced from the Baseline Coke in Table 3. The pilot anodes were produced according to Rain Carbon’s standard pilot anode production methods and aggregate

recipe [13] using a 112 M softening point pitch. Table 5 includes a summary of the cokes used to make pilot anodes in the study. No butts or baked scrap were used in the anodes to better highlight coke differences, Pilot anode results for the cokes described in Table 5 are shown in Fig. 5. The first point to note is the significantly higher baked anode density of the anodes made with calcined ACP produced from Coke A versus the anodes made with regular Coke A CPC (roughly +0.02 g/cc). The specific electrical resistivity was also significantly lower for these anodes and the flexural strength, compressive strength and modulus of elasticity were higher. The baked density of the anodes made with the baseline coke blend was slightly higher than the anodes made with the regular Coke A CPC but lower than the anodes made with 100% ACP. For the anodes labeled BL + ACP, the two coarser fractions of the baseline aggregate (1.7–4.75 mm and 4.75–8 mm) were replaced with ACP. Based on the standard Rain aggregate recipe [13], this meant that 55% of the coke in the 1.7–8 mm size range was replaced with ACP. The goal here was to replace the coarser aggregate with lower porosity and spherical ACP. These anodes had the highest baked anode density in this study confirming the particle shape and porosity benefits of using the ACP in the coarser aggregate fractions. When ACP is used in all aggregate fractions, the finer aggregate fractions have to be produced by crushing and milling the ACP. The particle shape and porosity benefits of using ACP in these fractions is therefore lost, particularly in the ball mill fines fraction and any aggregate fractions Jaw > Roll crushing irrespective of whether the material tested was coke or plant butts

the most regular shaped particles (i.e. highest convexity) with correspondingly high SSBD values. Jaw crushing gave a range of medium—high convexity and SSBD values. Overall, the coke particle shape versus bulk density, and crushing method versus shape/bulk density results for the two rotary calcined cokes and two butt samples tested aligned very well with the results from the initial study undertaken with a single coke.

Shaft Calcined Cokes Adding the shaft calcined coke results to the data set gave the results shown in Figs. 5 and 6. It can be seen (Fig. 5) that the highly calcined, relatively low VBD, higher porosity shaft calcined coke (S-LBD) fitted the SSBD—Convexity

Fig. 5 The highly calcined shaft coke S-LBD fits the rotary calcined coke/butts data set, but the more typical, lower porosity shaft coke (S-HBD) appears to give a slightly higher SSBD for a given convexity

1323

Fig. 6 Crushing technology had the same impact on convexity and hence SSBD for the shaft calcined cokes as for the rotary calcined coke and butt samples

correlation for the rotary coke/butt samples quite well. The more typical high VBD, low porosity shaft calcined coke (S-HBD), however did not fit the rotary coke/butts line, but appears to form an adjacent line that is parallel to the rotary coke/butts line. This suggests that the impact of convexity on SSBD is similar for this coke, but the significantly lower porosity of shaft coke S-HBD (Table 2) gives a higher SSBD for a given convexity. The impact of crushing technology on convexity and SSBD (Fig. 6) is the same for the shaft cokes as for the rotary cokes and butts with the technologies giving more regular shaped, higher bulk density shaft coke particles in the following order: “Puck” (impact) > Jaw > Roll crushing.

Baseline Samples The Baseline samples were Run of Kiln coke with the +4.75 mm particles jaw crushed to −4.75 mm and recombined with the bulk sample; the −0.6 + 0.3 mm material was then screen out and used for testing. These samples, therefore contained a mixture of “natural” RoK particles and some jaw crushed particles. It can be seen from Fig. 7 that the relationship between convexity and bulk density appears different for the baseline samples than for the jaw, roll, or “puck” (impact) crushed samples. These crushed samples contained no RoK particle shapes, as all of the material in the target size range had been crushed using the selected technology. Convexity appears to have less of an impact on the SSBD of the baseline samples than of the jaw, roll, or “puck” (impact) crushed samples tested as indicated by the flatter gradient of the convexity—SSBD line. While not yet confirmed, this is likely to be associated with a broader range of shapes in the baseline “RoK” samples compared to the samples fully crushed down into the target range.

1324

F. Cannova et al. Table 4 Contribution of regression components to Eq. 3

a

Fig. 7 Baseline RoK materials do not show the same gradient in the relationship between particle shape and bulk density as the samples fully crushed by the different crushers used in this study

Parameter

Relative contribution (%)

Real density at sizea

22

Sphericity

34

Open porosity

33

Note that this parameter incorporates Real Density and closed porosity

The R2 for Eq. (3) was *89% meaning 89% of the variance in SSBD was explained by the model and 11% by the error term. The contribution of each regression component is shown in Table 4. It can be seen from Table 4 that for the simple regression analysis of the materials tested, particle shape (in this case Sphericity) and open porosity have a similar contribution to explaining the variance in bulk density. Coke Real Density and closed porosity make a smaller contribution.

Table 3 Results from the testing of a range of coke types and butts used to develop Eq. 3 Coke source

Particle size (mm)

Sphericity

RD at size (g/cm3)

Open Porosity (%)

Rotary coke 1

−2.38 + 1.18

0.7984

2.0069

1.6594

Rotary coke 1

−1.18 + 0.6

0.8136

2.0078

1.6629

Rotary coke 1

−0.6 + 0.3

0.8312

2.0039

1.6491

Rotary coke 2

−2.38 + 1.18

0.7898

1.9958

1.6771

Rotary coke 2

−1.18 + 0.6

0.8106

1.9987

1.6569

Rotary coke 2

−0.6 + 0.3

0.8263

1.9964

1.6412

Hearth coke 1

−2.38 + 1.18

0.7958

1.9986

1.6986

Hearth coke 1

−1.18 + 0.6

0.8166

1.9996

1.7341

Hearth coke 1

−0.6 + 0.3

0.8335

1.9998

1.7541

Hearth coke 2

−0.6 + 0.3

0.7924

2.0032

1.7317

Hearth coke 3

−0.6 + 0.3

0.7904

2.0063

1.7235

Hearth coke 4

−0.6 + 0.3

0.7802

2.0042

1.7539

Hearth coke 5

−0.6 + 0.3

0.7815

1.9919

1.7419

Shaft coke S-HBD

−0.6 + 0.3

0.8200

2.0271

1.8375

Plant butts B-A

−0.6 + 0.3

0.8349

2.0340

1.7428

Rotary coke R-LBD

−0.6 + 0.3

0.8159

2.0291

1.8148

Discussion The experimental results presented from stage 1 are an extension of those from the initial study [1] that showed that when porosity was kept relatively constant by using a single coke, different methods of crushing could be used to modify particle shape, which in turn influenced coke bulk density. Impact type crushing produced more regular particles with higher convexity and sphericity values that packed better and gave higher bulk densities. Crushers with a greater shear breakage component such as roll crushers gave less smooth and more irregular particles with lower convexity and sphericity values resulting in lower bulk densities. The objective of the current project (stage 1) was to extend this work and determine if the initial findings held when different cokes and butts were tested, i.e. to answer the question “does the relationship established in the initial study between crushing method, average particle shape, and bulk density hold when coke porosity (a factor well known to influence coke bulk density) varies?” The results of stage 1 indicate that:

Stage 2 Results The results for the second set of samples tested are shown in Table 3. Simple regression analysis of these data gave the relationship shown in Eq. 3: SSBD ¼ 1:57 þ 1:860 Sphericity þ 0:580 Real Density at size  0:01514 Open Porosity

ð3Þ

• Different crushing methods can be used to modify the average shape and hence bulk density of rotary calcined cokes (of differing porosities) and plant butt particles, i.e. the results of the initial study on a single coke were confirmed on a range of materials. • A high bulk density shaft calcined coke was also found to have average particle shape factors that varied depending on the crushing method used, however, a higher bulk

Influence of Particle Shape and Porosity on the Bulk Density …

density was achieved for a given convexity compared to the rotary calcined cokes or plant butt particles. This was due to the significantly lower porosity of this coke. • The experimental approach used in stage 1 deliberately maximised the number of particles crushed by each of the methods used; this gave a clear relationship between average particle shape and bulk density. Not surprisingly, in baseline Run of Kiln samples that did not have all particles crushed (i.e. they contained a majority of natural or RoK shaped particles), the correlation between particle shape and bulk density was weaker. The results from the initial study suggested opportunities to improve plant aggregate and anode properties by modifying plant coke crushing principles. The current results support this and show that they may apply to a range of cokes and butts. In current plant aggregate preparation circuits, by design the amount of coke crushed is generally minimised, often with only the top size from a screen deck (commonly around +4.75 mm, but can be larger) crushed down. The results from this work suggest that an alternative approach of maximizing the number of aggregate particles subject to “impact” type crushing to achieve the target aggregate size may potentially give a better packing, higher bulk density aggregate and subsequently better quality anodes from available cokes. Current plant mass balance and aggregate size target considerations do, however need to be considered as these may limit the extent to which this can be done. Since data from the samples tested indicates that shape/ bulk density relationships also apply to crushed butts, and as all butts are fully crushed in plants, this suggests that there may be more straightforward opportunities to improve butts packing and bulk density by using more impact type crushers. While this is in contrast with the conventional wisdom of avoiding these high dust generation crushers for butt material, as these particles form the “skeleton” of the anode, getting better packing by using impact type crushers may have a disproportionately positive impact on aggregate and anode density. In stage 2 of this project a range of samples were tested for Open porosity, Real Density at size, and Sphericity; these parameters were then correlated with Small Sample Bulk Density (SSBD). The linear regression correlation had an R2 of 89%, indicating that bulk density can be predicted quite well using these three parameters according to Eq. (3). The relationship also suggested that for the samples tested, variation in coke and butts shape (Sphericity) impacted coke

1325

bulk density by about the same degree as coke open porosity. This confirms that, as has been suggested previously [1, 4], coke particle shape needs to be given much greater attention in the characterisation of cokes and butts used for anode manufacture. For example, variation in coke and butt particle shape may be contributing to unexpectedly poor plant anode properties from particular cokes.

Conclusions The studies outlined in this paper were an extension of an initial study that showed that when testing a single coke, crushing method, particle shape, and bulk density are highly correlated and that using high shear crushing methods increased coke convexity, giving better packing and higher bulk density. This initial study was extended by testing a range of coke and butts samples with varying properties including porosity. The results from the extended study: (1) Confirmed the results of the initial study, with the shape of coke and butts particles (in particular convexity) having a strong influence on how these particles pack and hence the bulk density of the materials. (2) Confirmed the impact of crushing methods on the particle shape of a range of different coke and butt samples, with impact crushing giving particles with a better packing shape (i.e. high convexity and sphericity) and roll crushers giving worse packing particles. (3) Indicated that designing and operating Carbon Plant crushing circuits to maximise “impact” crushing of coke and butt particles to achieve the target aggregate particle size could lead to better aggregate packing, higher bulk density values, and hence higher density anodes. This needs to be confirmed on a larger scale with an aggregate material. (4) The relationship between coke properties (Open porosity, Real Density at size, and Sphericity) and coke bulk density was demonstrated in the form of a regression equation with a high R2 of 89%, which suggests that, within the range of materials tested, bulk density can be predicted quite well from these three parameters. (5) The regression also showed that, within the range of materials tested, variation in shape had as big an impact on bulk density as open porosity. This indicates that particle shape warrants a lot more attention when considering the bulk density of cokes and butts and the impact of this on plant anode performance.

1326

References 1. Cannova FR, Davidson MD, Forte L, Sadler BA (2018) Influence of Crushing Technology and Particle Shape on the Bulk Density of Anode Grade Petroleum Coke. Light Metals 2018, TMS, 1169 2. Cannova FR, Davidson MD, Sadler BA, (2018) Opportunities to use particle technology to improve anode quality, Proc 12th Australasian Aluminium smelting technology conference, Queenstown, New Zealand, 7th–11th December 2018, Paper 2a3

F. Cannova et al. 3. Various authors, (2011) Papers in the session “Petroleum coke VBD”. Light Metals 2011, TMS, 925–963 4. Azari K, et al (2014) Influence of coke particle characteristics on the compaction properties of carbon paste material. Powder Technology. 257:132–140 5. QICPIC Instrument help file, Sympatec. http://www.sympatec.com/ EN/ImageAnalysis/Fundamentals.html 6. Micromeritics AutoPore IV 9500 Operator’s Manual

An EXAFS and XANES Study of V, Ni, and Fe Speciation in Cokes for Anodes Used in Aluminum Production Gøril Jahrsengene, Hannah C. Wells, Camilla Sommerseth, Arne Petter Ratvik, Lorentz Petter Lossius, Katie H. Sizeland, Peter Kappen, Ann Mari Svensson, and Richard G. Haverkamp

Abstract

The work has recently been published in Metallurgical and Materials Transactions B (https://doi.org/10.1007/ s11663-019-01676-z). Keywords

Petroleum coke speciation




EXAFS




XANES




Metal

G. Jahrsengene (&)
A. M. Svensson Department of Materials Science and Engineering, NTNU Norwegian University of Science and Technology, 7491 Trondheim, Norway e-mail: [email protected] A. M. Svensson e-mail: [email protected] H. C. Wells
R. G. Haverkamp School of Engineering and Advanced Technology, Massey University, 4222 Palmerston North, New Zealand e-mail: [email protected] R. G. Haverkamp e-mail: [email protected] C. Sommerseth
A. P. Ratvik SINTEF Industry, 7465 Trondheim, Norway e-mail: [email protected] A. P. Ratvik e-mail: [email protected] L. P. Lossius Hydro Aluminum AS, Primary Metal Technology, 6882 Årdal, Norway e-mail: [email protected] K. H. Sizeland ANSTO, 2234 Lucas Heights, NSW, Australia e-mail: [email protected] P. Kappen Australian Synchrotron, ANSTO, 3168 Clayton, VIC, Australia e-mail: [email protected]

Extended Abstract The main ingredient in pre-baked carbon anodes used in the aluminum industry, is petroleum coke. Today, the aluminum industry faces challenges regarding the availability of what is considered anode grade coke. The increasing amount of impurities (e.g. sulfur and metals) in the crude oil end up in the low-quality product, coke. Petroleum coke that can be used in the aluminum production is calcined, producing calcined petroleum coke (CPC), and coke that have previously only been used as fuel, needs to be considered for CPCs, despite the high impurity content [1]. Impurities in coke are known to affect certain reactions in the cell; sulfur is believed to reduce CO2 reactivity, while metals are suggested as catalyzers increasing the CO2 and air reactivity [2]. The exact mechanisms of these reactions are not known but can be assumed to depend on the chemical composition of the impurities. The chemical sulfur compounds in CPC are known to mainly be organically polycyclic thiophenes and thiazines, as part of the carbon sheets [3, 4]. Metals have been assumed to be present as organic complexes, similarly to the compounds found in crude oil [5], but the nature of the metals have not previously been determined. Previous investigations by the authors [6], using synchrotron radiation, identified significant quantities of an additional sulfur compound to the mentioned organic sulfur. This was identified as a compound with S-S bonds, possibly including metal sulfides, but the high amount quantified in some cokes did not correlate to the metal content in the respective cokes. Further investigations on metal speciation in cokes were therefore suggested. X-ray absorption spectroscopy (XAS) techniques were discovered to be applicable to CPCs to decide the chemical compounds of the metals V, Ni, and Fe. By comparing the recorded fluorescence spectra of cokes to those of known compounds, using the X-ray absorption near edge structure (XANES) region of the spectra, Ni and Fe were suggested to

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_181

1327

1328

be metal sulfides, and possibly some metal porphyrin. Using the extended X-ray absorption fine structure (EXAFS) region, and comparing to information on local structure, i.e. nearest atoms and bond lengths associated with variable space groups, found in large databases, all three metals were discovered to be bound as hexagonal metal sulfides (V3S4, NiS and FeS respectively). The metal sulfides were also discovered to be highly dispersed in the cokes, and not present as inclusions [7].

References 1. Edwards L (2015) The History and Future Challenges of Calcined Petroleum Coke Production and Use in Aluminum Smelting. JOM. 67(2): 308–321 2. Houston GJ, Øye HA (1985) Consumption of anode carbon during aluminium electrolysis. I-III. Aluminium. 61: 251–254, 346–349, 426–428

G. Jahrsengene et al. 3. Hay SJ, Metson J, Hyland MM (2004) Sulfur Speciation in Aluminum Smelting Anodes. Ind. Eng. Chem. Res. 43(7): 1690– 1700 4. Xiao J, Zhong Q, Li F, Huang J, Zhang Y, Wang B (2015) Modeling the Change of Green Coke to Calcined Coke using Qingdao High-Sulfur Petroleum Coke. Energy Fuels. 29(5): 3345– 3352 5. Caumette G, Lienemann CP, Merdrignac I, Bouyssiere B, Lobinski R (2009) Element Speciation Analysis of Petroleum and Related Materials. J. Anal. Atom. Spectrom. 24(3): 263–276 6. Jahrsengene G, Wells HC, Rørvik S, Ratvik AP, Haverkamp RG, Svensson AM (2018) A XANES Study of Sulfur Speciation and Reactivity in Cokes for Anodes Used in Aluminum Production. Metall. Mater. Trans. B. 49(3): 1434–1443 7. Jahrsengene G, Wells HC, Sommerseth C, Ratvik AP, Lossius LP, Sizeland KH, Kappen P, Svensson AM, Haverkamp RG (2019) An EXAFS and XANES Study of V, Ni, and Fe Speciation in Cokes for Anodes Used in Aluminum Production. Metall. Mater. Trans. B. 50(6): 2969–2981

Additive Selection for Coal Tar Pitch Modification in Aluminium Industry Julie Bureau, Armita Rastegari, Duygu Kocaefe, Yasar Kocaefe, and Hans Darmstadt

Abstract

In the aluminium industry, the quality of anodes has a direct impact on the production cost, energy consumption, and environmental emissions. Anode properties are strongly affected by the quality of binding between coke and pitch. One of the most promising avenues to enhance this binding is the modification of pitch properties using additives. They help increase the concentration of pitch surface functional groups and consequently improve coke-pitch interactions. The current work was undertaken to establish an additive selection method which would yield improved coke wettability by modified pitch. This article describes the method and presents the results for three different additives. Non-modified and modified pitches were characterized by carrying out wettability tests and FTIR analyses. Coking values (CV) of non-modified and modified pitches were also measured. The results show that it is possible to improve coke-pitch interactions via the utilization of additives. Keywords












Pitch modification Additives Interaction Coke-Pitch Wetting improvement FTIR Coking value

J. Bureau
A. Rastegari
D. Kocaefe (&)
Y. Kocaefe Research Chair on Industrial Materials (CHIMI), University Research Centre on Aluminium (CURAL), Aluminium Research Center (REGAL), University of Quebec at Chicoutimi, 555 Boulevard de L’Université, G7H 2B1 Chicoutimi, QC, Canada e-mail: [email protected] H. Darmstadt Rio Tinto, Arvida Research and Development Centre (ARDC), 1955, Boulevard Mellon, G7S 4K8 Jonquière, QC, Canada

Introduction In the aluminium industry, carbon anodes are used in the electrolytic cells for the reduction of alumina (Al2O3) to produce aluminium. Carbon anodes are made from a paste which consists of about 85% dry aggregates (calcined petroleum coke, butts, and recycled green and baked anodes) and 15% coal tar pitch used as binder [1, 2]. By penetrating the pores and covering the surface of the granular material, pitch facilitates the cohesion of the paste. The anode is formed by compacting the anode paste in a vibro-compactor or a press, followed by baking. During the anode baking process, pitch carbonization takes place which results in the formation of a solid matrix. This reduces the electrical resistivity and hence improves the electrical conductivity of the anodes produced [1–3]. Therefore, the pitch must sufficiently wet coke to manufacture high-quality paste. Wettability is defined as the degree of a liquid spreading on the surface of a solid, which depends on the surface tension of the liquid and the intermolecular forces between gas, liquid, and solid phases. Depending on the affinity of the liquid with the solid, the liquid drop adapts a characteristic shape when it is deposited on the surface of a solid. In wettability studies the contact angle, which is an indication of the degree of wetting, is measured [4]. Figure 1 shows the wetting of a solid by a liquid which is quantified by measuring the angle (h) formed between the vectors associated with the energy of the solid/liquid (cSL) and liquid/vapor (cLV) interfaces. The greater the contact angle is (90°), the lower the wettability of the solid by the liquid is; and conversely, the smaller the contact angle is (90°), the greater the wettability is. The equilibrium relation between the contact angle and the surface energy vectors cSL, cLV, and cSV is given by Young’s equation [1, 5]: cSV ¼ cSL þ cLV cos h

ð1Þ

At equilibrium, the contact angle is constant (static wetting). Due to different causes (roughness of the surface,

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_182

1329

1330

Fig. 1 Schematic representation of the wetting principle

impurities, etc.), the contact angle may change with time (dynamic wetting). In addition, if the solid is porous, the liquid penetrates into the pores of the solid. Therefore, the wettability depends on the physical and chemical properties of the coke (chemical composition, particle size, porosity, and texture) and the pitch (chemical composition, softening point, surface tension, and viscosity) [4, 5]. The wetting behavior also depends on the functional groups present on the surface of the coke and pitch, which are susceptible to induce intermolecular interactions. Several authors suggested different types of interactions (hydrogen bonds, electrostatic interactions, dispersion forces, acid-base interactions, and covalent bonds) that are responsible for the cohesion between coke and pitch [6–8]. It is well known that the nature of the interaction of coke with pitch is fundamental in order to obtain anodes with desired properties [5, 9]. The quality of anodes has a direct impact on the metal cost, energy consumption, and environmental emissions. Thus, sufficient binding between coke and pitch has a significant importance for aluminium production. Since the quality of raw material used in industry is variable, the compatibility of coke and pitch also varies. In addition, continuous improvement of the process to increase productivity and to reduce environment emissions and production cost led to the exploration of different avenues. One possible avenue to promote the coke-pitch interaction is to modify the pitch using additives. The addition of an additive to pitch could potentially help the industry achieve its objectives. Several researchers studied different methods of pitch modification using additives [5, 10–12]. However, the coke-pitch interactions were not always studied, the pitch used was rarely coal tar pitch, and there are only a few studies on the utilization of modified pitch in anode fabrication. The European Commission [11] published a report in 1999 presenting the results obtained for anodes made from a paste modified with 0.05 g/ml water of sodium carboxymethylcellulose (CMCNa), Mobilsol 40 (M40) and polystyrene granules (PS). The addition of CMCNa in paste produced poor quality anodes due to the encapsulation of coal tar pitch by CMCNa that impairs coke wetting. In

J. Bureau et al.

addition, the use of Mobilsol 40 or PS did not significantly improve the anode properties. One study showed the improvement of certain anode properties by the modification of coal tar pitch using two different promising additives (A1 and A3) [12]. The additive A1 was a surfactant which provided better wetting than additive A3. However, the results of the study indicated that the additive A1 is less efficient than the additive A3 for improving the properties of anodes probably due to micelles formation. Also, the study reported that further improvement of the anode properties might be achieved by adjusting the pitch level. A more comprehensive study is needed to understand better the coke-pitch interaction mechanism in order to choose a reliable additive for anode-making. Some researchers studied the effect of bitumen modification using biodiesel or no.6 fuel oil on the viscosity [13]. Bitumen is a mixture of different compounds such as petroleum and coal tar pitches and asphalt cements. The biodiesel to bitumen ratio was varied between 0.005 to 0.23 g/g. This mixture was characterized to obtain the functional groups on the surface with FTIR and to measure its softening point, viscosity, and coking value (CV). The results showed that the utilization of biodiesel, which reduced the viscosity of bitumen, was more effective as compared to no.6 fuel oil due to the presence of oxygenated functional groups such as esters. The softening point, viscosity, and CV decreased with increasing additive concentration. The objective was to improve the lubricity of a fuel. It was never used in anode fabrication. The objective of the present work is to establish a method to improve the wettability of coke by pitch modified using an additive. The additives selected must be inexpensive and contain functional groups that can chemically bind to pitch and coke in order to enhance their compatibility. The boiling point of the additive must be lower than the maximum paste mixing and forming temperatures so that the additive remains in the paste and contributes to pitch carbonization. The selected chemical additives and the products that form upon their decomposition must not contain any species that are detrimental to the electrolysis process. This will help prevent anode contamination and hence maintain the purity of aluminium. First, pitches and additives were characterized individually with Fourier transform infrared spectroscopy (FTIR). Then, the interaction between the pitch and the coke was studied by carrying out wettability tests using the sessile-drop method. After pitch modification, FTIR spectra of modified and non-modified pitches were compared to understand the differences in their wetting behavior based on their surface functional groups. Finally, the CVs of non-modified and modified pitches were determined to evaluate the impact of additives on the carbon loss so that the most suitable additive type and its concentration could be chosen for use in anode production.

Additive Selection for Coal Tar Pitch Modification in Aluminium Industry

Materials and Methods Materials In this project, one pitch (P1) and one coke (C1) obtained from aluminium industry were used. Pitch was modified using three different additives (Add1, Add2, and Add3) purchased from Alfa Aesar. Three different concentrations were tested: 0.005 g/g  c1 < c2 < c3  0.05 g/g (ratio of the additive mass to the total mass of the sample). The coke was crushed and sieved. The coke particle size was between +75 and −100 lm to approach a smooth coke-bed surface during the wettability tests [9]. Tables 1, 2, 3 present some of the properties of the pitch, additives, and the coke used, respectively. Table 4 shows the conditions of different pitch modifications realized.

Methodology Characterization of the pitch and the additives The chemical structures of non-modified pitch samples and pure additives were analyzed by Fourier transformation infrared spectroscopy (FTIR) at room temperature. A potassium bromide pellet (KBr, FTIR grade) containing 0.01 g/g of KBr (analytical grade) was placed in a Nicolet 6–700 FTIR spectrometer. The acquisition of the spectrum was carried out between wavenumbers 399 and 4000 cm−1 at a resolution of 4 cm−1 for a total of 26 sweeps per sample. Each test was repeated three times. In order to eliminate the effect of the environment on the test results, a blank run was done before performing a series of analysis. The IR spectra of each experiment were transformed into absorbance spectra. The Omnic32 version 7.3 software was used to correct the spectra

1331

by drawing a straight baseline starting from the lowest point at 399 cm−1 to the lowest point at 4000 cm−1. Software was developed to calculate the areas under the peaks based on MATLAB-version 2008b. This software also corrected the absorbance for each test at the concentration of 0.01 g/g of KBr. The area and the standard deviations are the averages of those obtained from three experiments. Pitch Modification Pitch was modified using different concentrations of additives. First, the selected additive was placed in a test tube. Then, the pitch was added to obtain the desired additive concentration (see Table 4). The specimen was placed in the center of an insulated enclosure under a nitrogen (N2) atmosphere to prevent its oxidation beyond the softening point. The enclosure was heated with a heat gun (Master Appliance Model VT-750C). The internal temperature of the pitch was measured using a thermocouple connected to an electronic thermometer (Fluke 52 II). The temperature was maintained around 185 °C for one minute while manually stirring the mixture. The tube was then cooled under nitrogen flow for about five minutes to lower the modified pitch temperature below the softening point. When the mixture was at room temperature, the solid pitch was recovered from the test tube. The non-modified pitch was also heated to the same temperature in order to eliminate the influence of temperature when non-modified and modified pitches were compared. Then, FTIR analyses of all the pitches (non-modified and modified with different additives at different concentrations) were carried out. Wettability A sessile-drop experimental system, developed at UQAC, was used to measure the contact angles for pitch-coke

Table 1 Properties of the Pitch Used in the Study (CV: coking value, SP: softening point, TI: toluene insolubles, QI: quinoline insoluble) Properties Pitch P1

CV

SP

(%) 59.9

Table 2 Properties of the Additives Used in the Study

Ash

S

TI

QI

(°C)

(%)

(%)

(%)

(%)

119.8

0.25

0.52

26.6

9.2

Additive

Add1

Add2

Add3

State at room temperature

Liquid

Solid

Solid

Melting point (Tmp), (°C)

7.5

77

112

Boiling point (Tbp), (°C)

248

291

248

Generic class

Phenyl-alkyl-aldehyde

Phenyl-alkyl-ketone

Phenyl-alkyl-aldehyde

Health risk

Skin irritant at high conc.; non-carcinogen*

non-carcinogen*

non-carcinogen*

*It has never been reported that this compound is a carcinogen

1332 Table 3 Properties of the Coke Used in the Study (Lc: crystalline height)

J. Bureau et al. Properties Coke C1

Table 4 Different Pitch Modifications Carried Out in the Study and the Symbols Used (Pitch: P1)

Additive

Lc

Ni

Fe

V

S

(Å)

(ppm)

(ppm)

(ppm)

[%]

24.6

271

531

499

2.73

Concentration (g/g) c1

c2

c3

Add1

Add1c1P1

Add1c2P1

Add1c3P1

Add2

Add2c1P1

Add2c2P1

Add2c3P1

Add3

Add3c1P1

Add3c2P1

Add3c3P1

systems. Details of the experimental system are given elsewhere [3]. The system is composed of a digital video camera (B/W) (APPRO, model KC), an Inconel tube with a pitch injection system, a graphite sample crucible, a secondary rotary vacuum pump (GE, Precision Vacuum Pump, Model D25), and a tube furnace (Thermolyne 21100) [8]. The graphite sample crucible was filled with the coke sample. The coke particles were compacted to a coke bed with a relatively smooth surface. The pitch injection system retained the solid pitch sample until the system reached the desired temperature. This pitch chamber has a small hole at the bottom and is placed just above the coke bed during the experiment [3]. All experiments were performed under nitrogen (N2) atmosphere to avoid any oxidation. The injection chamber was connected to a N2 line. In order to slightly pressurize the chamber, the pressure of the N2 line was higher than that of the system. The adjustment of the difference in pressure controlled the size of the drop. At the desired temperature, the injection chamber was rotated so that a molten pitch drop directly fell on the coke bed. A camera captured the images of the drop at fixed time intervals until the pitch drop totally penetrates into the coke bed. The software FTA 32 was used to measure the contact angle which is the average of the angles on two sides of the drop. Each experiment was repeated twice and the final result represents the average of these experiments [12]. The wetting behavior depends on the interaction between the pitch drop and coke. The wettability of coke increases as the contact angle decreases. An improvement in the wettability of coke by the modification of pitch indicates that the additive used enhances the coke-pitch interactions. FTIR FTIR analysis of non-modified and modified pitches were carried out. First, calculated spectra, which were the weighted average of the spectra of non-modified pitch and those of the additive, respectively, were determined as follows:

Abs calculated ¼

 100  %additive %additive Absk  þ Absk  100 100 pitch additive ð2Þ Then, the calculated and the measured spectra were compared for each additive at different concentrations. Any difference between the two shows a possible chemical modification of pitch. The change in pitch composition indicates the possible presence of new surface chemical functions that may enhance the interaction between the modified pitch and coke. To do this comparison two different ratios were determined from the spectra, namely, the aromaticity index (Ratio A) and the heteroatom index (Ratio H). The chosen bands of absorbance selected for this analysis must be present on all the spectra. Therefore, the Ratio A is the ratio of the absorbance of aromatic peaks (3050 cm−1) to the total of aromatic (3050 cm−1) and aliphatic (2800 and 2990 cm−1) peaks. The Ratio H is the ratio of the absorbance of heteroatoms to the total of aromatic (3050 cm−1) and aliphatic peaks (2800 and 2990 cm−1). The presence of heteroatoms can be observed in different bands: between 3400 and 3600 cm−1, around 1700 cm−1, and between 1000 and 1400 cm–1. Considering that the same chemical group can generate peaks in more than one of these regions, only one of its bands should be selected in the calculation of the Ratio H. Thus, the band between 1000 and 1400 cm−1 was selected based on the results of a prior work [12]. These ratios were calculated according to the following equations: Aromaticity

indexðRatioAÞ ¼ P

Absaromatic Absaromatic and aliphatic ð3Þ P

Heteroatome

indexðRatioH Þ ¼ P

Absheteroatome Absaromatic and aliphatic ð4Þ

Additive Selection for Coal Tar Pitch Modification in Aluminium Industry

Coking value (CV) The determination of CVs of the non-modified and modified pitches was performed by the industrial partner following the ASTM D 4715 method.

Results and Discussion Wettability of Coke by Pitch

Contact Angle (°)

The coke-pitch wetting behavior was investigated in order to evaluate the effect of additive utilization on pitch/coke interactions at the mixing stage. The coke-pitch wetting behavior was studied by comparing the dynamic contact angle (contact angle vs. time) measured during the wetting test for all cases studied until the total penetration of the drop as well as the contact angle at 60 s. Figure 2 compares the dynamic contact angles obtained for non-modified pitch and modified pitches at a concentration of c2. It can be observed from this figure that all modified pitches wet the coke C1 better than the non-modified pitch. These results show that the addition of all additives tested improved coke-pitch interactions. It can also be seen that Add2 and Add3 modifies the wetting behavior of pitch similarly and this behavior

120 100 80 60 40 20 0

Non-modified-P1 Add1c2P1 Add2c2P1 Add3c2P1

0

50

100 Time (s)

150

200

Fig. 2 Dynamic Contact Angles of Non-Modified Pitch and Modified Pitches with Different Additives Table 5 Contact Angles of Non-Modified Pitch and Modified Pitches with Different Additives at 60 s

1333

is slightly better compared to that of the pitch modified with Add1. The contact angles measured at 60 s for non-modified pitch and all modified pitches are presented in Table 5. The results show that, similar to the trend obtained with the measurement of dynamic contact angles, pitch modification improves the wetting behavior of pitch compared to the non-modified pitch. It can also be observed that contact angles decrease, consequently, wettability increases with increasing additive concentration. It seems that the degree of improvement is not the same at different additive concentrations. This order is Add1 ˂ Add2 ˂ Add3 at concentration c1, but it is Add1 ˂ Add3 ˂ Add2 at c2 and c3.

FTIR The examination of the surface of pitch with FTIR gives information regarding the improvement of the coke-pitch interactions. Three main types of interactions (hydrogen bonding, acid-base interaction, and electrostatic bonding) take place between coke and pitch depending on the presence of functional groups on their surface. These are shown in Fig. 3. A hydrogen bond can form between a positively-charged hydrogen atom and a strongly electronegative atom (heteroatom, usually O or N in coke and pitch). Acid-base interactions occur between an acid functional group (carboxyl or phenol) and a basic functional group (amine). Electrostatic interaction is a cation-P interaction between a negatively-charged electron cloud P with an aromatic nucleus and a positively charged center such as a quaternary ammonium ion. The chemical surface of non-modified pitch and modified pitches were characterized using FTIR in order to evaluate the effect additive on the pitch surface, and subsequently its effect on the wettability behavior of coke-pitch pair. The spectra obtained for non-modified pitch and pitches modified with additives Add1, Add2, and Add3 at concentration c2 are shown in Fig. 4.

Additive

Concentration (g/g)

Pitch Name

Contact Angle at 60 s (°)

None

None

Non-modified-P1

48.9

Add1

Add2

Add3

c1

Add1c1P1

34.7

c2

Add1c2P1

33.8

c3

Add1c3P1

7.7

c1

Add2c1P1

30.3

c2

Add2c2P1

18.7

c3

Add2c3P1

7.2

c1

Add3c1P1

25.1

c2

Add3c2P1

22.9

c3

Add3c3P1

7.6

1334

J. Bureau et al.

Pitch / Coke

Complementary functional group Basic functional group Positively charged species Hydrogen bond

Acid-Base

Electrostatic bond

Functional group

Acidic functional group

Aromatic ring

Coke / Pitch

Absorbance

Fig. 3 Possible Interactions Between Coke and Pitch

3400

2400 1400 Wavelenght (cm-1)

Non-modified-P1 Add2c2P1

400

Add1c2P1 Add3c2P1

Fig. 4 FTIR Spectra of Non-Modified Pitch and Pitches Modified with Different Additives at Concentration c2 at Room Temperature

The FTIR spectra of pitches indicated several functional groups. The bands at 3000 and 3100 cm−1 correspond to aromatic C-H stretching [14] and peaks between 2800 and 2980 cm−1 correspond to aliphatic C-H bonds [14]. The Ratio A was calculated from the areas of these peaks. An increase in this ratio indicates a possible increase of electrostatic bond which could enhance coke-pitch interaction. Peaks in the band between 1400 and 1660 cm−1 are associated with alkanes (C-C) or alkenes (C = C). More specifically, the C-C are found between 1400 and 1475 cm−1 in the form of strong peaks, the C = C shows strong peaks at 1 400 and 1455 cm−1 and relatively medium-sized peaks, if conjugated, at 1620 and 1660 cm−1, while aromatic C = C will have medium-strong peaks between 1450 and 1650 cm−1 [14]. Peaks between 1660 and 1820 cm−1 are associated with the carbonyl (C = O) functional group from the addition of additives [14]. Due to the presence of Table 6 FTIR Analysis of Non-Modified and Modified Pitches with Additive Add1 at Different Concentrations

[] (g/g)

neighboring groups, the position of C = O peak can vary. For this reason, a specific wave number for this peak was not used for the analysis. Peaks present in the 1000 and 1400 cm−1 band refer to heteroatoms: esters, ethers, alcohols, phenols, amines, etc. [14]. These peaks were used to calculate Ratio H. An increase in Ratio H can signify a possible increase of hydrogen bond or acid-base interaction, which could enhance coke/pitch interactions. Finally, the band between 700 and 900 cm−1 is associated with substitutions of the aromatic ring [14]. Ratios A and H were obtained for measured and calculated spectra in order to evaluate whether or not the additive interacted with the pitch. A difference between measured and calculated results means that an interaction took place and the pitch surface was modified due to the presence of additive. The ratios obtained for the non-modified pitch and modified pitches at different concentrations of Add1, Add2, and Add3 are presented in Tables 6, 7, 8, respectively. The additive Add1 (Table 6) chemically modified the pitch as can be seen from the difference in calculated and measured ratios. Also, the measured Ratios A and H increase with increasing additive concentration. This increase is more significant for the measured ratios. Therefore, it can be said that the change in ratios show the reason for the wettability improvement with the modification of pitch. Thus, this increase in the ratios A and H enhances the interaction of modified pitch with coke. The results for Add2 (Table 7) show similar tendency to those of additive Add1. However, the increase in Ratio A at all concentrations and Ratio H at c3 upon use of this additive is higher as compared to that of Add1. Thus, this also explains why the use of additive Add2 improves the wettability more compared to the use of additive Add1. Also, the tendency observed with additive Add3 (Table 8) is similar to those of additive Add1 and Add2. However, the increase in Ratio A with the use of additive Add3 is greater compared to that with additive Add1. This tendency for Add3 is similar to that of additive Add2. This explains why the use of additive Add3 improves the wettability more compared to the use of additive Add1. In addition, Ratio H increases less with additive Add3 than with additive Add2, explaining why additive Add2 improves slightly the wetting at c2 and c3 compared to additives Add1 and Add3 (see also Table 5).

Modified with Additive Add1 (measured)

Pitch + Pure Additive Add1 (calculated)

Ratio A (%)

Ratio H (%)

Ratio A (%)

Ratio H (%)

none

75.1

47.4

75.1

47.4

c1

83.5

54.2

74.8

48.9

c2

87.3

63.7

75.0

52.3

c3

88.3

63.3

74.5

55.5

Additive Selection for Coal Tar Pitch Modification in Aluminium Industry Table 7 FTIR Analysis of Non-Modified and Modified Pitches with Additive Add2 at Different Concentrations

Table 8 FTIR Analysis of Non-Modified and Modified Pitches with Additive Add3 at Different Concentrations

[] (g/g)

Modified with Additive Add2 (measured)

Pitch + Pure Additive Add2 (calculated)

Ratio A (%)

Ratio H (%)

Ratio A (%)

Ratio H (%)

none

75.1

47.4

75.1

47.4

c1

84.6

40.9

74.9

54.6

c2

94.2

56.7

74.6

69.2

c3

94.6

77.8

74.2

84.3

[] (g/g)

Modified with Additive Add3 (measured)

Pitch + Pure Additive Add3 (calculated)

Ratio A (%)

Ratio H (%)

Ratio A (%)

Ratio H (%)

none

75.1

47.4

75.1

47.4

c1

87.9

44.7

74.5

52.2

c2

91.8

58.2

73.3

62.0

c3

92.4

58.4

72.0

71.9

Coking Value and Selection of an Additive and Its Concentration The CVs of non-modified and modified pitches were measured in order to evaluate the potential loss in carbon during anode baking (pitch carbonization). The additives or their by-products will be evaporated with the volatiles; thus, they will not contaminate the anodes [1]. A certain loss in CV with increasing additive concentration may be acceptable as a compromise for the improvement of the coke-pitch interactions. Table 9 shows the reduction in CV obtained for biodiesel addition to bitumen found in the literature [13] and for the pitch modified with different additives in the present study. This order in loss of CV from lowest too highest is Add2 ˂ Add3 ˂ Add1 at concentration c1, but it is Add1 ˂ Add3 ˂ Add2 at c2 and c3. For each concentration, the percent decrease in CV with the additives of the present study is below those obtained for biodiesel. Biodiesel is a surfactant. Previously, Bureau et al. [12] reported that the use of surfactant may be less effective due to micelle formation. Thus, the three additives selected have the potential for improving coke-pitch interactions (wettability) and consequently anode properties. Further study is required to understand their effect on anode properties.

Table 9 Reduction in CV as a Function of Additive Concentration

1335

(g/g)

Figure 5 presents the contact angle at 60 s as a function of the percent reduction in CV for non-modified and modified pitches. It can be seen that each additive concentration forms a separate group. Based on the wettability results, at a given concentration of c2 and c3, the additive Add2 appears to be slightly more effective as compared to additives Add1 and Add 3 (lower contact angle). As explained above, wetting improves but the CV decreases with increasing additive concentration. If it is assumed that a loss up to 1 percent CV reduction is acceptable, the concentration c2 for Add2 and Add3 and the concentration c3 for Add1 represent a compromise between the decrease in CV and the improvement in wettability. However, this assumption has to be validated by producing anodes using modified and non-modified pitches and verifying their properties. Figure 6 shows Ratio A as a function of the reduction in CV for non-modified and modified pitches. The tendency observed is similar to that of Fig. 4. As it can be seen from this figure, each concentration forms a group. As presented in FTIR analysis section, Ratio A increases with increasing additive concentration, thus the wettability of coke by pitch (coke-pitch interactions) increases as the concentration increases. In addition, it can be seen that there is possibly a limit to increasing the concentration of additive. This limit

Reduction in Coking Values (%) Biodiesel [13]

Add1

Add2

Add3

0.005

0.90

–

–

–

c1

–

0.35

0.10

0.30

c2

–

0.60

0.90

0.84

c3

–

1.00

1.60

1.40

0.05

2.31

–

–

–

J. Bureau et al.

50 40 30 20 10 0

c1

c1 c1

c2 c2 c2 c3

0

80

Additive Add1 Additive Add2 Additive Add3 Non-modified-P1

none

c3

c3

0.5 1 1.5 Reduction in Coking Value (%)

c3

70 Ratio H (measured)

Contact Angle at 60 s (°)

1336

2

c2

60 50

none

40 30

0

Fig. 5 Relation between wettability results and reduction in CV for the pitch modified with three Additives at different concentrations

c3

c2

c3 Additive Add1 Additive Add2 c1 c1 Additive Add3 Non-modified-P1 0.5 1 1.5 2 Reduction in Coking Value (%) c1

c2

Fig. 7 Relation Between Heteroatom Ratios (Ratio H) and Reduction in CV for the Pitch Modified with Three Additives at Different Concentrations

Ratio A (measured)

95

c2 c2

90 85

c1

80 75

none

70 0

c1 c1

c2

c3

c3

c3 Additive Add1 Additive Add2 Additive Add3 Non-modified-P1

0.5 1 1.5 Reduction in Coking Value (%)

2

Fig. 6 Relation Between Aromatic Ratios (Ratio A) and Reduction in CV for the Pitch Modified with Three Additives at Different Concentrations

can possibly be explained by the saturation of active surface sites with the increase in additive concentration. Thus, there is not a significant difference in Ratio A when the additive concentration is increased from c2 to c3. But, a small increase in this ratio brings a significant decrease in CV. Therefore, the utilization of a concentration of c2 is a good compromise between the wettability improvement and reduction in CV. Figure 7 shows Ratio H as a function of the reduction in CV for non-modified and modified pitches. Similar to the tendency observed in Figs. 5 and 6, each concentration groups together for Ratio H. It can be seen in Fig. 7 that an increase in concentration does not significantly affect the ratio with the exception of Add2 at c3. This general tendency indicates that the active sites are possibly saturated with increasing additive concentration. Thus, these results confirm that a concentration of c2 is probably a good choice for improving coke-pitch the interactions with an acceptable CV loss.

Conclusions This study presents a method for selecting the type and the concentration of an additive in order to improve coke-pitch interactions without sacrificing pitch CV. The three additives selected showed some potential to improve the anode quality

since they improved the coke wettability by pitch. However, additives Add2 and Add3 seem to be slightly better as compared to additive Add1 at a concentration of c2. Considering the cost and the availability, it was concluded that the additive Add2 at a concentration of c2 possibly represent the best choice for pitch modification among the additives and concentrations studied. Acknowledgements The technical and financial support of Rio Tinto’s Aluminium division as well as the financial support of the Natural Sciences and Engineering Research Council of Canada (NSERC), the University of Quebec at Chicoutimi (UQAC), and the Aluminium Research Center (REGAL) is greatly appreciated.

References 1. Charette, A., Kocaefe, Y.S., and Kocaefe, D. (2012) Le carbone dans l’industrie de l’aluminium. xxi ed.,: Chicoutimi, Qc, Canada, Les presses de l’aluminium, 325. 2. Hulse, K.L. (2000) Anode manufacture: raw materials, formulation and processing parameters. xxxv ed., Sierre, Switzerland: R & D Carbon Ltd. 416. 3. Sarkar, A., Kocaefe, D., Kocaefe, Y.S., Sarkar, D., Bhattacharyay, D., Morais, B., and Chabot, J. (2014) Coke-pitch interactions during anode preparation. Fuel, 117(PART A): p. 598–607. 4. Sarkar, A., Kocaefe, D., Kocaefe, Y., Bhattacharyay, D., Sarkar, D. (2016) and Morais, B., Effect of Crystallinity on the Wettability of Petroleum Coke by Coal Tar Pitch. Energy & Fuels, 30(4): p. 3549–3558. 5. Rocha, V.G., Blanco, C., Santamaría, R., Diestre, E.I., Menéndez, R., and Granda, M. (2005) Pitch/coke wetting behaviour. Fuel, 84 (12): p. 1550–1556. 6. Kocaefe, D., Sarkar, A., Das, S., Amrani, S., Bhattacharyay, D., Sarkar, D., Kocaefe, Y.S., Morais, B., and Gagnon, M. (2013) Review of different techniques to study the interactions between coke and pitch in anode manufacturing. TMS Light Metals, p. 1045–1050. 7. Suriyapraphadilok, U. (2008) Characterization of Coal- and Petroleum-derived Binder Pitches and the Interaction of Pitch/coke Mixtures in Pre-baked Carbon Anodes, Pennsylvania State University, University Park, PA, USA. 8. Huang, X., Kocaefe, D., Kocaefe, Y., and Bhattacharyay, D. (2016) Wettability of bio-coke by coal tar pitch for its use in

Additive Selection for Coal Tar Pitch Modification in Aluminium Industry carbon anodes. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 490: p. 133–144. 9. Couderc, P., Hyvernat, P., and Lemarchand, J.L. (1986) Correlations between ability of pitch to penetrate coke and the physical characteristics of prebaked anodes for the aluminium industry. Fuel, 65(2): p. 281–287. 10. Rocha, V.G., Blanco, C., Santamaría, R., Menéndez, E.I., Granda, R., and Diestre, M. (2010) The effect of the substrate on pitch wetting behaviour. Fuel Processing Technology, 91(11): p. 1373–1377. 11. European Commission (1999) The use of coal-tar pitches of very high softening point and low carcinogen content as binders for

1337

industrial carbon. O.f.P.o.E. Communities. of work. EUR 18584 EN. 48 pages. 12. Bureau, J. (2017) Étude de l’amélioration de la qualité des anodes par la modification des propriétés du brai, Mémoire de maîtrise, Université du Québec à Chicoutimi, Chicoutimi, Qc, Canada. 13. Kiser, M.D., Sumner, M.B., Wilt, B.K., and Boyer, D.C. (2006) Viscosity Modification and Control of Pitch. Light metals 2006, p. 531–534. 14. Colthup, N.B. (1950) Spectra-Structure Correlations in the Infra-Red Region. Journal of the Optical Society of America, 40 (6): p. 397–400.

Charcoal and Use of Green Binder for Use in Carbon Anodes in the Aluminium Industry Camilla Sommerseth, Ove Darell, Bjarte Øye, Anne Støre, and Stein Rørvik

Abstract

Carbon anodes for aluminium production are produced from calcined petroleum coke (CPC), recycled anode butts and coal tar pitch (CTP). The CO2 produced during anode consumption contributes to a substantial amount of the CO2 footprint of this industrial process. Charcoal from wood has been suggested to partly replace coke in anodes but high porosity, low electrical resistivity and high ash content contributes negatively to final anode properties. In this work, charcoal from Siberian larch and spruce was produced by heat treatment to 800, 1200 and 1400 °C and acid-washed with H2SO4. Acid-washing resulted in reduced metal impurity and the porosity decreased with increasing heat treatment. Pilot anodes were made from CTP, CPC with some additions of spruce and larch charcoal. Another set of pilot anodes were produced using a green binder. Compared to reference anodes, the CO2 reactivity of anodes containing larch was less affected compared to anodes containing spruce. The green binder was found to be highly detrimental for the anodes’ CO2 reactivity properties. Electrochemical consumption increased for anodes containing both green binder, larch and spruce compared to the reference anode. Keywords







Charcoal production Spruce treatment Acid-washing




Siberian larch




Heat

by biocarbon or charcoal is one possible option. Carbon anodes for aluminium production are produced from calcined petroleum coke (CPC), coal tar pitch (CTP) and recycled anode butts. By introducing charcoal produced from wood, the global warming footprint of the aluminium industry may be reduced. Monsen et al. [1] investigated using charcoal from maple, spruce and an Indonesian source. They found that charcoal could only to be used as fines due to the high porosity of the carbon structure. The density of anodes containing charcoal was reduced and CO2 reactivity increased. The conclusion was that they did not recommend using charcoal in anodes. Recent work [2, 3] has shown that acid-washing and further heat treatment of the charcoal may reduce the undesirable effects of high porosity, high ash content as some of these elements are known to give increased air and CO2 reactivity. In this work, spruce and Siberian larch (from now on denoted as larch only) were studied. Spruce was chosen in order to investigate if it was possible to improve the negative effects observed in [1] by further heat treatment and acid-washing by H2SO4 of the charcoal and larch was chosen due to its abundance and high density. A green binder was also investigated to replace coal tar pitch and, in that way, reducing the fossil CO2 footprint of anode production.

Materials and Methods Charcoal Production

Introduction Most countries in the world agreed through the Paris agreement to take measures in order to reduce CO2 emissions. Replacing fossil fuel-based carbon in process industry C. Sommerseth (&)
O. Darell
B. Øye
A. Støre
S. Rørvik SINTEF Industry, 4760 Torgarden, 7465 Trondheim, Norway e-mail: [email protected]

Wood from spruce and larch was chopped into pieces of 7  5  5 cm3. The wood pieces were placed in a steel box, covered with packing coke and calcined to 800 °C in a chamber furnace. Some of the wood was then calcined further to 1200 or 1400 °C. The heating rate was 300 °C/h with a hold time of 5 h. The charcoal was either washed in 0.1 or 1.0 M sulfuric acid, H2SO4. H2SO4 was chosen due to the positive effect sulfur has on CO2 reactivity of anodes. A magnetic stirrer was used during the acid-washing and the

© The Minerals, Metals & Materials Society 2020 A. Tomsett (ed.), Light Metals 2020, The Minerals, Metals & Materials Series, https://doi.org/10.1007/978-3-030-36408-3_183

1338

Charcoal and Use of Green Binder for Use in Carbon Anodes …

charcoal pieces was left in the acid solution for 10–12 h at 67 °C before being washed, then rinsed in fresh water for one hour and dried at 120 °C. After the acid-washing with sulfuric acid, a white precipitate was observed on the charcoal. This was removed by soaking the charcoal in 7 % acetic acid for 10–12 h at 67 °C and then rinsed in water for 2–3 h before being dried at 120 °C. Table 1 shows a summary of the charcoal production including the abbreviated names for each charcoal type.

Anode Production Table 2 shows an overview of the aggregate composition of the produced anodes. The coke aggregate was produced with particles smaller than 2 mm to ensure homogeneous samples during small-scale characterization and electrolysis testing. The anodes contained 30 wt% fines less than 0.125 mm. Charcoal was only added to the fines. The 0.125–1 and 1–2 mm coke particles each made up 35 wt% of the coke aggregate. Pitch, coke particles and fines were dry mixed in a beaker and heated to 180 °C. The pitch, coke and fines were further mixed on a heating plate before being compressed in a mould at 180 °C. The mould was placed in the heating cabinet at 180 °C for another 30 min. The mixture was then hot-pressed at 30 kN. Anodes containing green binder was produced by placing the binder, coke particles and fines in separate containers in a heating cabinet at 50 °C before being mixed together in a beaker. The mixture was poured into a compression mould and placed in the heating cabinet at 50 °C for 30 min before being hot-pressed at 30 kN. All anodes were baked to 1260 °C with a hold time of two hours and a heating and cooling rate of 80 °C/h. The green binder used for anode making had a consistence like syrup.

Table 1 Charcoal production and acid-washing with sulfuric acid

1339

Charcoal Characterization High Resolution Inductive coupled plasma mass spectrometry (ICP-MS) was used to investigate the elemental impurities in the charcoal samples before and after acid-washing. Samples of charcoal (