Combustion Chemistry and the Carbon Neutral Future. What will the Next 25 Years of Research Require? 9780323992138

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Combustion Chemistry and the Carbon Neutral Future

Developments in Physical & Theoretical Chemistry Series Editor James E. House With the new series Developments in Physical & Theoretical Chemistry, Elsevier introduces a collection of volumes that highlight timely and important developments in this interdisciplinary field. The series aims to present useful and timely reference works dealing with significant areas of research in which there is rapid growth. Through the contributions of specialists, these volumes will provide essential background on appropriate and relevant topics and provide surveys of the literature at a level to be useful to advanced students and researchers. In this way, the volumes will address the underlying theoretical and experimental background on the topics for researchers entering the topic fields and function as useful reference works of lasting value. A primary goal for the volumes in the series is to provide a strong educational thrust for advanced study in particular fields. Each volume will have an editor who is intimately involved in work constituting the topic of the volume. Although contributions to volumes in the series will include those of established scholars, contributions from those who are rising in prominence will also be included. 2018 Physical Chemistry of Gas—Liquid Interfaces Jennifer A. Faust and James E. House, Editors 2019 Mathematical Physics in Theoretical Chemistry S.M. Blinder and J.E. House, Editors 2019 Spectroscopy and Dynamics of Single Molecules Carey K. Johnson, Editor 2020 Intra- and Intermolecular Interactions between Non-covalently Bonded Species Elliot R. Bernstein, Editor 2023 Combustion Chemistry and the Carbon Neutral Future Kenneth Brezinsky, Editor 2023 Dynamic Processes in Solids James E. House, Editor

Developments in Physical & Theoretical Chemistry

Combustion Chemistry and the Carbon Neutral Future What will the Next 25 Years of Research Require? Series Editor

James E. House Edited by

Kenneth Brezinsky Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, United States

Elsevier Radarweg 29, PO Box 211, 1000 AE Amsterdam, Netherlands The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States Copyright © 2023 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. ISBN: 978-0-323-99213-8 For information on all Elsevier publications visit our website at https://www.elsevier.com/books-and-journals

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Contents Contributors .............................................................................................................xv Introduction.............................................................................................................xxi

CHAPTER 1

Combustion emissions, internal combustion engines and greenhouse gases............................... 1 Sage L. Kokjohn and Aravindh Babu 1 Introduction ....................................................................................1 2 Transportation energy requirements ..............................................3 3 Reducing greenhouse gas emissions from internal combustion engines ........................................................................8 3.1 Approaches to reaching GHG targets .................................. 11 3.2 Challenges of using renewable fuels in mediumand heavy-duty engines ........................................................ 12 4 Conclusions and future directions ...............................................19 References.................................................................................... 20

CHAPTER 2

Soot research: Relevance and priorities by mid-century .................................................... 27 Francesco Carbone, Kevin Gleason, and Alessandro Gomez 1 2 3 4

5

6

7 8

Will soot research be relevant in the next few decades?............27 The lingering challenge of soot nucleation .................................28 Laminar flames as the preferred setting for soot studies ............29 Diagnostics ...................................................................................30 4.1 Sampling-based diagnostics ................................................. 31 4.2 Optical diagnostics ............................................................... 37 Flame selection criteria ................................................................38 5.1 Burner-stabilized flat premixed flames................................ 39 5.2 Laminar diffusion flames ..................................................... 40 Exemplars of tracking soot nucleation in flames ........................43 6.1 Counterflow diffusion flame under incipiently sooting conditions................................................................. 43 6.2 Filling the gaps in nucleation in premixed flames .............. 46 Computational modeling..............................................................50 Summary and research needs in the next few decades ...............51 Acknowledgments ....................................................................... 52 References.................................................................................... 52

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CHAPTER 3

Natural gas for combustion systems...................... 63 Jai M. Mehta and Kenneth Brezinsky 1 Introduction ..................................................................................63 2 Sources of natural gas ..................................................................64 2.1 Biogas ................................................................................... 65 2.2 Power to gas (PtG) ............................................................... 66 3 Relevant research .........................................................................68 3.1 Chemistry.............................................................................. 69 3.2 Transportation....................................................................... 79 3.3 Power generation .................................................................. 84 4 Research synopsis—What will the next 25 years of research require?......................................................................85 5 Conclusion....................................................................................87 References.................................................................................... 87

CHAPTER 4

Sustainable bio-oxygenate fuels ........................... 91 Charles K. Westbrook

1 Introduction ..................................................................................91 2 A possible solution, bio-oxygenate fuels produced from plant material.......................................................................92 3 Basics of fuel chemical kinetics ..................................................93 4 Fuels from biomass ......................................................................94 5 Early kinetic modeling.................................................................97 6 Small alcohols, methanol and ethanol .........................................98 7 Larger alcohols.............................................................................98 8 Accidental discovery of O atoms in the fuel as an inhibitor of sooting.....................................................................100 9 Introduction of methyl and ethyl esters as fuels .......................102 10 Epilog and conclusions ..............................................................107 11 What’s next?...............................................................................109 Acknowledgments ..................................................................... 110 References.................................................................................. 110

CHAPTER 5

A comprehensive perspective on a promising fuel for thermal engines: Syngas and its surrogates .................................................... 117 Annarita Viggiano and Vinicio Magi 1 Introduction ................................................................................117 2 Syngas: An alternative fuel for thermal engines .......................119 3 The performance and efficiency of syngas-fueled engines.......123

Contents

3.1 Dual-fuel (diesel-syngas) CI engines ................................. 123 3.2 HCSI engines ...................................................................... 127 3.3 DISI engines ....................................................................... 132 4 The pollutants formation and emissions of syngas fueled-engines ............................................................................133 4.1 Dual-fuel (diesel-syngas) CI engines ................................. 135 4.2 HCSI engines ...................................................................... 136 4.3 DISI engines ....................................................................... 137 5 Concluding remarks and future research ...................................138 Conflict of interest..................................................................... 140 References.................................................................................. 140

CHAPTER 6

Hydrogen, the zero carbon fuel........................... 149 Jai M. Mehta, Fokion N. Egolfopoulos, and Kenneth Brezinsky 1 Introduction ................................................................................149 2 Hydrogen internal combustion engines for road transportation..............................................................................151 3 Propagation of hydrogen flames ................................................154 4 Hydrogen-oxygen combustion mechanism overview ...............157 5 Another type of practical engine: The detonation engine.........164 6 A potential alternative to combustion engines: Hydrogen fuel cells ....................................................................165 7 A very practical consideration: Hydrogen storage ....................167 8 Conclusions and directions for research in the next 25 years (or sooner) ....................................................................168 8.1 For internal combustion engines ........................................ 168 8.2 For flames ........................................................................... 169 8.3 For chemistry ...................................................................... 169 8.4 For detonation engines ....................................................... 170 8.5 For hydrogen storage .......................................................... 170 References.................................................................................. 170

CHAPTER 7

Ammonia as an alternative ................................. 179

Jose
Antonio Mayoral Chavando, Valter Bruno Silva, Luı´s Anto´nio da Cruz Tarelho, Joa˜o Sousa Cardoso, Matthew J. Hall, and Daniela Euse
bio

1 Introduction ................................................................................179 1.1 Ammonia production.......................................................... 179 1.2 Ammonia storage................................................................ 184 1.3 Ammonia supply................................................................. 184

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2 Ammonia market........................................................................185 2.1 Key players per region ....................................................... 186 2.2 Key players per country ..................................................... 186 2.3 Key companies ................................................................... 187 3 Ammonia as an ICE fuel ...........................................................188 4 Ammonia as a power vector ......................................................193 5 Economic analysis......................................................................196 5.1 Ammonia production.......................................................... 196 5.2 Electricity production from ammonia ................................ 198 6 Environmental analysis ..............................................................199 7 Conclusions and future research ................................................200 Acknowledgments ..................................................................... 201 References.................................................................................. 201

CHAPTER 8

Small alcohols as biofuels: Status and needs for experimental data, theoretical calculations, and chemical kinetic modeling........................... 209 Chiara Saggese, Tanusree Chatterjee, and William J. Pitz 1 Introduction ................................................................................209 2 Small alcohol fuels.....................................................................211 2.1 Methanol ............................................................................. 211 2.2 Ethanol ................................................................................ 212 2.3 Propanols............................................................................. 215 2.4 Butanols .............................................................................. 218 2.5 Pentanols ............................................................................. 221 3 Recommendations for future work and future directions .........225 3.1 Methanol ............................................................................. 225 3.2 Ethanol ................................................................................ 226 3.3 Propanols............................................................................. 226 3.4 Butanols .............................................................................. 227 3.5 C5 branched alcohols ......................................................... 228 4 Summary and recommendations................................................228 Acknowledgments ..................................................................... 229 References.................................................................................. 229

CHAPTER 9

Fischer-Tropsch and other synthesized hydrocarbon fuels.............................................. 235 Mahabubul Alam, Kuen Yehliu, Chenxi Sun, and Andre
L. Boehman 1 Background ................................................................................235

Contents

2

3

4

5

1.1 History................................................................................. 235 1.2 Fuel production and characteristics.................................... 236 1.3 Fischer-Tropsch fuel properties.......................................... 240 Survey of engine performance and emissions impacts of F-T fuels.................................................................................242 2.1 Engine performance............................................................ 242 2.2 Engine emissions ................................................................ 244 Diesel combustion studies of F-T fuels and impacts on soot characteristics ................................................................248 3.1 Experimental....................................................................... 249 3.2 Case studies on the impact of fuels and operating conditions on engine performance, combustion process and emissions......................................................... 251 3.3 The impact of fuels on soot nanostructure and reactivity ...................................................................... 260 F-T fuel impacts on advanced diesel combustion processes.....................................................................................264 4.1 Heat release rate ............................................................... 266 4.2 NOx emissions.................................................................. 268 4.3 CO and UHC emissions ................................................... 270 4.4 THC-NOx trade-off .......................................................... 271 4.5 Filter smoke number......................................................... 271 4.6 PM emissions.................................................................... 272 4.7 Particle size distribution ................................................... 272 4.8 BSFC and BTE ................................................................. 273 4.9 Soot reactivity analysis..................................................... 273 4.10 Soot surface area analysis ................................................ 274 4.11 X-ray diffraction ............................................................... 276 4.12 X-ray photoelectron spectroscopy.................................... 276 4.13 Raman spectroscopy ......................................................... 277 4.14 Transmission electron microscopy................................... 277 4.15 Summary ........................................................................... 280 Concluding remarks and future directions ................................280 References.................................................................................. 282

CHAPTER 10 Low temperature combustion .............................. 291 Yiguang Ju and Ziyu Wang 1 Introduction ................................................................................292 1.1 Low temperature combustion concept in advance engines ................................................................................ 292

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1.2 Low temperature flames (cool flame and warm flame) .... 293 1.3 Low temperature combustion chemistry............................ 295 2 Dynamics of low temperature flames .......................................296 2.1 Premixed cool flame, warm flame, and double flame ...... 296 2.2 Non-premixed cool flames and warm flames.................... 300 2.3 Autoignition assisted cool flame........................................ 306 3 Low temperature combustion chemistry at high pressure ........307 4 Summary and future research....................................................311 References.................................................................................. 313

CHAPTER 11 Supercritical CO2 fluid combustion ..................... 319 Ramees K. Rahman, K.R.V. Manikantachari (Raghu), and Subith S. Vasu 1 Introduction ................................................................................319 1.1 Direct-fired supercritical CO2 power cycles...................... 320 2 Modeling consideration .............................................................323 2.1 The equation of state (EOS)............................................... 323 2.2 The compressibility factor (Z)............................................ 329 2.3 Specific heat capacities ...................................................... 330 2.4 Viscosity modeling ............................................................. 332 2.5 Thermal conductivity modeling ......................................... 333 3 Experimental validations ...........................................................334 3.1 Density of supercritical mixtures ....................................... 334 3.2 Speed of sound in supercritical mixtures........................... 338 4 Research outlook........................................................................340 References.................................................................................. 342

CHAPTER 12 Catalytic combustion for cleaner burning: Innovative catalysts for low temperature diesel soot abatement........................................ 345 Vincenzo Palma, Giuseppina Iervolino, and Eugenio Meloni 1 Introduction ................................................................................345 2 Recent advances in catalysts for soot oxidation .......................348 2.1 Ceria-based catalysts .......................................................... 349 2.2 Other transition metal oxides (TMOs) ............................... 350 2.3 Monolith based catalysts .................................................... 354 3 Reactor configurations for soot removal with catalytic “NTP”..........................................................................357 4 Catalytic species typically proposed for the abatement of soot in NTP reactors..............................................................366

Contents

5 Soot removal efficiency in the NTP catalytic reactor ..............368 6 Conclusions and future directions .............................................375 References.................................................................................. 376

CHAPTER 13 Advances in chemical looping combustion technology ........................................................ 383 Anuj Joshi, Pinak Mohapatra, Rushikesh Joshi, Sonu Kumar, Ashin Sunny, Zhuo Cheng, Lang Qin, and Liang-Shih Fan 1 Introduction ................................................................................383 2 An overview of the latest chemical looping platforms.............385 3 Material development ................................................................386 3.1 Materials for chemical looping combustion (CLC)........... 388 3.2 Materials for chemical looping hydrogen generation (CLHG)............................................................. 394 4 Process intensification ...............................................................400 4.1 Reactor design .................................................................... 400 4.2 Process optimization and operational strategies ................ 405 5 Conclusions and future research................................................406 References.................................................................................. 408

CHAPTER 14 Chemistry diagnostics for monitoring .................. 417 € Katharina Kohse-Hoinghaus, Alison M. Ferris, Johan Zetterberg, Deanna A. Lacoste, Peter Fjodorow, Steven Wagner, Liming Cai, Charlotte Rudolph, Judit Za´dor, Yuyang Li, Lena Ruwe, Nina Gaiser, Zhandong Wang, and Klaus Peter Geigle

1 Introduction: Only 25 years.......................................................419 2 Methodology: Teaming up ........................................................423 3 Results: 1+13 visions.................................................................424 3.1 Alison M. Ferris: Sensor innovations for omnivorous energy and propulsion systems ........................................ 426 3.2 Johan Zetterberg: Combinations—A seed for change? ....................................................................... 431 3.3 Deanna A. Lacoste: Diagnostics of charged and excited species in combustion................................... 433 3.4 Peter Fjodorow: Intracavity absorption spectroscopy: Combining robustness with highly-sensitive and broadband detection................................................... 437 3.5 Steven Wagner: Bringing light to complex reactive processes ............................................................. 441

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3.6 Liming Cai: Future model development driven by advanced combustion diagnostics ............................... 446 3.7 Charlotte Rudolph: Flexible polygeneration and exergy storage: A glimpse into the future from a modeling perspective..................................................... 450 3.8 Judit Za´dor: Theoretical chemistry in combustion diagnostics ........................................................................ 452 3.9 Yuyang Li: Chemistry diagnostics and control of low-carbon fuels for the upcoming carbon-neutral era ............................................................. 458 3.10 Lena Ruwe: Gaining knowledge on fuel-specific gas-phase reactions using molecular-beam mass spectrometry ............................................................ 462 3.11 Nina Gaiser: Alternative fuel combustion and prospects for PEPICO spectroscopy ................................ 465 3.12 Zhandong Wang: Detective work with advanced techniques: How to identify and measure previously elusive species .................................................................. 470 3.13 Klaus Peter Geigle: Chemistry diagnostics to resolve phenomena in soot-forming combustion processes ........................................................................... 474 4 Conclusions: The clock is ticking .............................................477 Acknowledgments ..................................................................... 479 References.................................................................................. 479

CHAPTER 15 High-pressure spectroscopy and sensors for combustion .................................................. 503 R. Mitchell Spearrin and Christopher S. Goldenstein 1 Motivation for high-pressure combustion and its role in pathway to carbon neutrality.................................................503 2 Challenges for high-pressure spectroscopy and sensing.................................................................................503 2.1 Collisional processes .......................................................... 504 2.2 Collisional broadening........................................................ 504 2.3 Line mixing......................................................................... 506 3 Laser absorption strategies for high-pressure sensing ..............508 3.1 Narrowband LAS diagnostics............................................. 508 3.2 Broadband LAS diagnostics ............................................... 511 3.3 Research needs for the next 25 years................................. 516 References.................................................................................. 517

Contents

CHAPTER 16 Bio-derived sustainable aviation fuels—On the verge of powering our future ......... 521 Mukul Tomar, Abhinav Abraham, Keunsoo Kim, Eric Mayhew, Tonghun Lee, Kenneth Brezinsky, and Patrick Lynch 1 Overview ....................................................................................521 2 Why bio-fuels?...........................................................................523 3 Overview of bio-derived jet fuels..............................................530 3.1 Overview of fuel properties requirements ......................... 530 3.2 Overview of bio-derived jet fuels production-pathways ... 532 3.3 Feedstock overview for bio-derived sustainable jet fuel production .............................................................. 544 4 Limitations and challenges for the bio-jet fuels .......................548 4.1 Commercialization challenges............................................ 548 4.2 Meeting properties requirements and certification of aviation fuels .................................................................. 550 4.3 Ignition properties-influence of combustion chemistry..... 553 4.4 Retro fits requirement for meeting bio-jet fuel properties ..................................................................... 559 5 Bio-derived sustainable aviation fuels: Current trends and future opportunities.............................................................560 5.1 Promising feedstock advances for BSAFs ......................... 560 5.2 Promising BSAF production pathway advances................ 563 5.3 Innovative policies for BSAFs and their outlook .............. 564 5.4 BSAF property and operational characteristic improvements: Fuel additives ............................................ 565 5.5 BSAF property and operational characteristic improvements: Understanding ignition properties............. 568 5.6 BSAF fuel property sensing ............................................... 575 5.7 Prospective opportunities for BSAFs in advanced propulsion ........................................................................... 578 6 Summary and concluding remarks ............................................580 Acknowledgments ..................................................................... 581 References.................................................................................. 581

CHAPTER 17 Using combustion synthesis to convert emissions into useful solid materials .................. 599 Stephen D. Tse and Hua Hong 1 Introduction ................................................................................599 2 Results and discussion ...............................................................600

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2.1 Carbon nanotube (CNT) growth [H2, CO, C2H2].............. 600 2.2 Few-layer graphene film growth [H2, CxHy, Cn, CO] ....... 605 2.3 Transition from CNT to graphene growth on metals [CO, C2H2].......................................................................... 609 2.4 Transition from CNT to graphene growth on metal oxides [H2, CO, C2H2] ....................................................... 610 2.5 Monolayer graphene (MLG) film growth [H2, CH4, CH2] ................................................................... 611 2.6 Metal-oxide nanowire growth [CO, H2O, CO2] ................ 616 2.7 Transition from metal-oxide nanocrystal growth to CNT growth [H2, CO, H2O, CO2] ................................. 620 3 Conclusions and future directions .............................................623 Acknowledgments ..................................................................... 625 References.................................................................................. 626 Index ......................................................................................................................631

Contributors Abhinav Abraham Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, United States Mahabubul Alam EMS Energy Institute, Penn State University, University Park, PA, United States Aravindh Babu University of Wisconsin—Madison, Engine Research Center, Madison, WI, United States Andr
e L. Boehman Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, United States Kenneth Brezinsky Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, United States Liming Cai School of Automotive Studies, Tongji University, Shanghai, China Francesco Carbone Department of Mechanical Engineering, University of Connecticut, Storrs, CT, United States Joa˜o Sousa Cardoso Polytechnic Institute of Portalegre, Portalegre; Instituto Superior T
ecnico, University of Lisbon, Lisbon, Portugal Tanusree Chatterjee Lawrence Livermore National Laboratory, Livermore, CA, United States Jos
e Antonio Mayoral Chavando Department of Environment and Planning & Centre for Environmental and Marine Studies (CESAM), University of Aveiro, Campus Universita´rio de Santiago, Aveiro, Portugal Zhuo Cheng William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH, United States Luı´s Anto´nio da Cruz Tarelho Department of Environment and Planning & Centre for Environmental and Marine Studies (CESAM), University of Aveiro, Campus Universita´rio de Santiago, Aveiro, Portugal Fokion N. Egolfopoulos Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA, United States

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Daniela Eus
ebio Polytechnic Institute of Portalegre, Portalegre, Portugal Liang-Shih Fan William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH, United States Alison M. Ferris Department of Mechanical Engineering, Stanford University, Stanford, CA, United States Peter Fjodorow Institute for Combustion and Gas Dynamics—Reactive Fluids, University of Duisburg Essen, Duisburg, Germany Nina Gaiser Institute of Combustion Technology, German Aerospace Center (DLR), Stuttgart, Germany Klaus Peter Geigle Institute of Combustion Technology, German Aerospace Center (DLR), Stuttgart, Germany Kevin Gleason Yale Center for Combustion Studies, Department of Mechanical Engineering and Materials Science, Yale University, New Haven, CT, United States Christopher S. Goldenstein Purdue University, West Lafayette, IN, United States Alessandro Gomez Yale Center for Combustion Studies, Department of Mechanical Engineering and Materials Science, Yale University, New Haven, CT, United States Matthew J. Hall Department of Mechanical Engineering, University of Texas at Austin, Austin, TX, United States Hua Hong SEU-FEI Nano-Pico Center, Key Lab of MEMS of Ministry of Education, Southeast University, Nanjing, China Giuseppina Iervolino Department of Industrial Engineering, University of Salerno, Fisciano, Salerno, Italy Anuj Joshi William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH, United States Rushikesh Joshi William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH, United States

Contributors

Yiguang Ju Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ, United States Keunsoo Kim Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States Katharina Kohse-H€ oinghaus Department of Chemistry, Bielefeld University, Bielefeld, Germany Sage L. Kokjohn University of Wisconsin—Madison, Engine Research Center, Madison, WI, United States Sonu Kumar William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH, United States Deanna A. Lacoste King Abdullah University of Science and Technology, Clean Combustion Research Center, Thuwal, Saudi Arabia Tonghun Lee Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States Yuyang Li School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China Patrick Lynch Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, United States Vinicio Magi School of Engineering, University of Basilicata, Potenza, Italy; Department of Mechanical Engineering, San Diego State University, San Diego, CA, United States K.R.V. Manikantachari (Raghu) Center for Advanced Turbomachinery and Energy Research (CATER), University of Central Florida, Orlando; Power Systems Mfg., LLC, Jupiter, FL, United States Eric Mayhew Weapons and Materials Research Directorate, US Army Combat Capabilities Development Command Army Research Laboratory, Adelphi, MD, United States Jai M. Mehta Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, United States

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Eugenio Meloni Department of Industrial Engineering, University of Salerno, Fisciano, Salerno, Italy Pinak Mohapatra William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH, United States Vincenzo Palma Department of Industrial Engineering, University of Salerno, Fisciano, Salerno, Italy William J. Pitz Lawrence Livermore National Laboratory, Livermore, CA, United States Lang Qin William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH, United States Ramees K. Rahman Center for Advanced Turbomachinery and Energy Research (CATER), University of Central Florida, Orlando, FL, United States Charlotte Rudolph Institute for Combustion and Gas Dynamics—Thermodynamics, University of Duisburg-Essen, Duisburg, Germany Lena Ruwe Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, Germany Chiara Saggese Lawrence Livermore National Laboratory, Livermore, CA, United States Valter Bruno Silva Department of Environment and Planning & Centre for Environmental and Marine Studies (CESAM), University of Aveiro, Campus Universita´rio de Santiago, Aveiro, Portugal R. Mitchell Spearrin University of California Los Angeles, Los Angeles, CA, United States Chenxi Sun Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, United States Ashin Sunny William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH, United States Mukul Tomar Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, United States

Contributors

Stephen D. Tse Department of Mechanical and Aerospace Engineering, Rutgers University–New Brunswick, Piscataway, NJ, United States Subith S. Vasu Center for Advanced Turbomachinery and Energy Research (CATER), University of Central Florida, Orlando, FL, United States Annarita Viggiano School of Engineering, University of Basilicata, Potenza, Italy Steven Wagner Institute for Reactive Flows and Diagnostics, Technical University of Darmstadt, Darmstadt, Germany Zhandong Wang National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, Anhui, China Ziyu Wang Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ, United States Charles K. Westbrook Lawrence Livermore National Laboratory, Livermore, CA, United States Kuen Yehliu EMS Energy Institute, Penn State University, University Park, PA, United States Judit Za´dor Combustion Research Facility, Sandia National Laboratories, Livermore, CA, United States Johan Zetterberg Combustion Physics, Department of Physics, Lund University, Lund, Sweden

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Introduction Kenneth Brezinsky Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, United States

Recent news reports have revealed that a number of automobile companies are aiming to eliminate hydrocarbon-fueled engines in their vehicles within the next 25 years or sooner [1] by switching completely to battery electric vehicles. The motivation for the switch is to eliminate carbon dioxide, the greenhouse gas produced by passenger road vehicles. Passenger road vehicles produce 45.1% of all the CO2 emissions [2] from transportation, which itself accounted for 27% of the global total CO2 emission in 2019 according to the International Energy Agency (IEA) [3]. The remaining transportation emissions come from freight vehicles (29.4%), aviation sources (11.6%), shipping (10.6%), rail (1%), and other sources (2.2%) [2]. It is important to note that CO2 emissions from passenger road vehicles and freight road vehicles together contribute about 75% of all transport carbon dioxide emissions. The elimination of carbon dioxide from transportation sources using battery electric propulsion is aimed at keeping global warming to less than 1.5°C by achieving a net zero CO2 emissions level [4]. Net zero CO2 emission is defined by the Intergovernmental Panel on Climate Change (IPCC) of the United Nations as the condition when human-produced (anthropogenic) CO2 is offset by human-developed removals [5]. Net zero CO2 emissions is used synonymously with the term carbon neutrality [5] and is the way carbon neutrality is used here and throughout the book. The implication of carbon neutrality is that it is achievable even if complete elimination of CO2 production may not be possible when mitigation strategies for all CO2 emission sources are not identifiable. Carbon neutrality could then be achieved if carbon dioxide removal can balance out its production. Nevertheless, mitigation, i.e., reduction, of CO2 emissions, is an essential component of achieving the goal of carbon neutrality [4,6]. If complete mitigation of CO2 emissions by eliminating the use of fossil fuels, decarbonization [4], is the primary goal of replacing internal combustion engines with batteries in transportation vehicles, it still remains to be determined if such an approach is technologically feasible or even advisable. Instead, a carbon-neutral scenario with reduced CO2 production might be more practical. Getting to carbon neutrality with reduced CO2 production will require many intermediate steps not only in developing the batteries required for the partial fleet conversion of passenger and freight transportation vehicles but also in developing the alternative engines needed to reduce CO2 emission and also in reducing emissions from current engines. Furthermore, although future road-based vehicles may entirely operate using electric-based engines, flying vehicles cannot and will require, for the foreseeable

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future, clean combustion engines to propel them, as will water-based shipping vehicles. These latter applications again suggest that complete transportation decarbonization may not be possible but instead an acceptable level of carbon neutrality may be a more reasonable goal. Consequently, it is imperative that current combustion researchers orient their activities to the demands of the transition period to carbon neutrality occurring over the next 25 or less years as society converts more and more to battery-powered vehicles and as more efficient fossil-fueled engines and better carbon dioxide capture and storage technologies are developed. The primary focus of the chapters in this book is on the combustion processes used in transportation and how research might improve them to mitigate greenhouse gases, mainly CO2. The focus on transportation combustion stems from two main drivers. The first is the expectation that car ownership will increase by 60% between 2019 and 2070 [4] and coupled with increases in freight transportation could lead to tripling of passenger miles traveled [4]. The implied increase in CO2 emissions follows if nothing is done to reduce the CO2 output of these car and freight sources. The second driver is that transportation combustion processes, technologies, chemistries, and amelioration strategies are often common to the other main source of global carbon dioxide, heat, and electricity generation, which together with transportation sources generated more than two-thirds of global carbon dioxide emissions in 2019 [3]. By further studying transportation combustion chemistry and its associated processes, important understanding is gained and research directions defined that would benefit the reduction of CO2 from all combustion sources. Further study of combustion could seem relatively pointless since combustion is considered a mature, well-developed field. The subfield of the chemistry of combustion is indeed mature and could be said to date from the beginning of the study of chemistry itself. Mature scientific fields often see their major advancements as having occurred in the past with only relatively small advancements seeming possible through further research. However, the demand for transitioning to carbon-neutral road vehicles and clean, efficient flying and water vehicles requires that the field of combustion stretch the boundaries of its mature past and provide solutions to many problems, as presented in each chapter of this book. Each chapter presents the research results of experienced researchers and their projections for future research directed to developing even cleaner, greener carbon-neutral combustion chemistry, and combustion processes. The primary audience for this volume will be active combustion researchers in both academia and industry who must prepare their research for changes in demand and need for knowledge as the shift to carbon neutrality takes place in the next decades. Anticipating how their expertise will be valued is tied to their understanding of the demand and need for new knowledge and this volume through its diverse authorship and broad perspective will inform those audience members. Students, especially graduate students, who are attracted to the thermal/fluid sciences and want to work in the energy, aerospace, and propulsion fields, need to know what an investment of their time and effort now can yield for them in the carbonneutral future. This volume, by giving future-oriented perspectives, will guide those

Introduction

students as well as provide them details of viable research areas that active practitioners foresee as having future importance. The reader will find in this book descriptions of active researchers’ current efforts in diverse areas of combustion chemistry and processes. An active experienced researcher has a perspective on the research field not only based on past successes but also on the prospect of future continued research. This gives the reader the opportunity to see what experienced and successful researchers are willing to invest in for future growth. The research projections by experts will point current and prospective researchers toward areas that would be more fruitful and presumably lead to sustained research. The chapter authors and coauthors have been chosen across a wide range of combustion chemistry and processes subdisciplines. Choosing researchers from diverse areas was done not only in view of the overriding perspective of preparing for a reduced carbon future, but also with the understanding that the contributions to achieving the carbon neutral goal could occur in many different ways. Having perspectives from a diverse group of researchers each of whom is focusing on a different but future-oriented research area will help other researchers define for themselves an area in which to increase their own focus.

References [1] B. Preston, J.S. Bartlett, Automakers are adding electric vehicles to their lineups. Here’s what’s coming, Consumer Reports, June 7, 2022. https://www.consumerreports.org/ hybrids-evs/why-electric-cars-may-soon-flood-the-us-market-a9006292675/. [2] H. Ritchie, Cars, Planes, Trains: Where Do CO2 Emissions From Transport Come From?, Our World in Data, October 6, 2020. https://ourworldindata.org/co2-emissions-fromtransport. [3] IEA, Greenhouse Gas Emissions From Energy: Overview, IEA, Paris, 2021. https://www. iea.org/reports/greenhouse-gas-emissions-from-energy-overview. [4] J. Rogelj, D. Shindell, K. Jiang, S. Fifita, P. Forster, V. Ginzburg, C. Handa, H. Kheshgi, S. Kobayashi, E. Kriegler, L. Mundaca, R. S
ef
erian, M.V. Vilarin˜o, Mitigation pathways compatible with 1.5°C in the context of sustainable development, in: V. Masson-Delmotte, P. Zhai, H.-O. P€ortner, D. Roberts, J. Skea, P.R. Shukla, T. Waterfield (Eds.), 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, Cambridge University Press, Cambridge, UK and New York, NY, USA, 2018, pp. 93–174, https://doi.org/10.1017/ 9781009157940.004. https://www.ipcc.ch/sr15/chapter/chapter-2/. [5] IPCC, Annex I: glossary (Matthews, J.B.R. (ed.)), in: V. Masson-Delmotte, P. Zhai, H.-O. P€ortner, D. Roberts, J. Skea, P.R. Shukla, T. Waterfield (Eds.), 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, Cambridge University Press, Cambridge, UK and New York,

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Introduction

NY, USA, 2018, pp. 541–562, https://doi.org/10.1017/9781009157940.008. https://www. ipcc.ch/sr15/chapter/glossary/. [6] P.A. Arias, N. Bellouin, E. Coppola, R.G. Jones, G. Krinner, J. Marotzke, V. Naik, M.D. Palmer, G.-K. Plattner, J. Rogelj, M. Rojas, J. Sillmann, T. Storelvmo, P.W. Thorne, B. Trewin, K. Achuta Rao, B. Adhikary, R.P. Allan, K. Armour, G. Bala, R. Barimalala, S. Berger, J.G. Canadell, C. Cassou, A. Cherchi, W. Collins, W.D. Collins, S.L. Connors, S. Corti, F. Cruz, F.J. Dentener, C. Dereczynski, A. Di Luca, A. Diongue Niang, F.J. Doblas-Reyes, A. Dosio, H. Douville, F. Engelbrecht, V. Eyring, E. Fischer, P. Forster, B. Fox-Kemper, J.S. Fuglestvedt, J.C. Fyfe, N.P. Gillett, L. Goldfarb, I. Gorodetskaya, J.M. Gutierrez, R. Hamdi, E. Hawkins, H.T. Hewitt, P. Hope, A.S. Islam, C. Jones, D.S. Kaufman, R.E. Kopp, Y. Kosaka, J. Kossin, S. Krakovska, J.-Y. Lee, J. Li, T. Mauritsen, T.K. Maycock, M. Meinshausen, S.-K. Min, P.M.S. Monteiro, T. Ngo-Duc, F. Otto, I. Pinto, A. Pirani, K. Raghavan, R. Ranasinghe, A.C. Ruane, L. Ruiz, J.-B. Sall
ee, B.H. Samset, S. Sathyendranath, S.I. Seneviratne, A.A. S€ orensson, S. Szopa, I. Takayabu, A.-M. Tr
eguier, B. van den Hurk, R. Vautard, K. von Schuckmann, S. Zaehle, X. Zhang, K. Zickfeld, Technical summary, in: V. Masson-Delmotte, P. Zhai, A. Pirani, S.L. Connors, C. P
ean, S. Berger, B. Zhou (Eds.), Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2021, pp. 33–144, https://doi.org/10.1017/9781009157896.002. https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_TS.pdf.

CHAPTER

Combustion emissions, internal combustion engines and greenhouse gases

1

Sage L. Kokjohn and Aravindh Babu University of Wisconsin—Madison, Engine Research Center, Madison, WI, United States

Acronyms AEO BEV BTE CDA CI EGR EIVC GCI GHG GIE HC IC LHV LIVC NVO SI SOC SOI US VVA WTT WTW

annual energy outlook battery electric vehicle brake thermal efficiency cylinder deactivation compression ignition exhaust gas recirculation early intake valve closure gasoline compression ignition greenhouse gas gross indicated efficiency hydrocarbon internal combustion lower heating value late intake valve closure negative valve overlap spark ignition start of combustion start of injection United States variable valve actuation well-to-tank well-to-wheels

1. Introduction Energy impacts nearly every aspect of our daily lives. Fig. 1 shows the estimated US Energy conversion in 2021. In 2021, the US converted 97.3 quadrillion BTUs of energy to deliver 31.8 quadrillion BTUs of energy services. 12.15 quads of energy Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00009-6 Copyright # 2023 Elsevier Inc. All rights reserved.

1

FIG. 1 Estimated United States energy consumption in 2021 [1].

2 Transportation energy requirements

FIG. 2 Historical and projected light-duty vehicles sales by technology and fuel type [2].

began in the form of renewables (solar, hydro, wind, geothermal, and biomass) and 8.13 quads stemmed from nuclear sources. This leaves approximately 77 quads supplied by non-renewable, carbon-containing sources. With a focus on internal combustion engines, this chapter will primarily evaluate the transportation sector. This sector converts 26.9 quads of energy with 24.3 quads coming from petroleum. Recently, substantial interest has focused on battery electric vehicles (BEV) replacing the internal combustion engine-powered vehicles. Sales of BEV’s have increased substantially in the past few years; accordingly, one is tempted to ask the question, “With the large growth in electric vehicles, why do we care about internal combustion engines?”. Fig. 2 shows projected light-duty vehicle sales by technology. In 2050 the US Energy Information Administration projects that approximately 90% of light-duty vehicles will have some form of an internal combustion (IC) engine. While this is a projection, it is certainly an indication that internal combustion engines will continue to be an important part of our future even in the light-duty sector. In other sectors, the internal combustion engine is expected to remain the dominant prime mover. For example, Fig. 3 shows the world transportation energy demand separated by energy carrier. It can be seen that oil is expected to be the dominant transportation energy carrier for the foreseeable future.

2. Transportation energy requirements The previous section suggested that internal combustion engines fueled by liquid hydrocarbons are expected to remain the dominant prime movers for transportation applications well into the future. To understand why oil and other liquid fuels are

3

4

CHAPTER 1 Internal combustion engines and greenhouse gases

FIG. 3 World transportation energy demand through 2050 [2].

expected to dominate the transportation sector for the foreseeable future, it is useful to compare the energy density of various energy carriers. Fig. 3 compares the useable energy density of liquid hydrocarbons, natural gas, and batteries on both a mass and volumetric basis. The useable energy density of the fuel accounts for losses in the energy conversion process. For an internal combustion engine, a fuels useable energy density is calculated as ρE,fuel ¼

W ¼ LHV⁎ηbrake , mfuel

(1)

where W is the work of the engine, mfuel is the mass of fuel required to perform a quantity of work, LHV is the fuels lower heating value and ηbrake is the brake thermal efficiency (BTE) of the engine. The brake thermal efficiency can be calculated as ηbrake ¼

W : mfuel ⁎LHV

(2)

The height of the bar represents an average scenario with a brake thermal efficiency of 40% and the error bars show the results with brake thermal efficiencies of 30% and 50% for the lower and upper bounds, respectively. For batteries, the usable energy density is calculated as ρE,battery,usable ¼ ρE,battery ⁎ðSOCmax  SOCmin Þ⁎ηdischarge ⁎ηmotor ⁎CEOL ,

where ρE, battery is the energy density of the battery, SOCmax is the maximum state of charge (SOC) of the battery (assumed to be 100%), SOCmin is the minimum SOC of the battery (assumed to be 20%), ηdischarge is the efficiency during discharging (assumed to be 90%), ηmotor is the efficiency of the electric motor (assumed to be 95%), and CEOL is the capacity of the battery at the end of useful life divided by

2 Transportation energy requirements

the capacity of the battery at the beginning of its useful life. Typically, end of useful life is defined as a 20% loss in capacity (i.e., CEOL ¼ 0.8). Even with a stretch goal for energy density of 500 W h/kg [3], the lithium ion-based storage technology has an order of magnitude lower energy density than current market fuels (diesel fuel and gasoline). The bound oxygen of alcohols reduces the energy content, but even for methanol, the energy density is between 5 and 8 times that of the future goal for lithium ion-based storage. Fig. 4 showed that liquid hydrocarbons have clear energy density benefits compared to electrochemical storage (represented by lithium ion batteries); however, energy density is only a portion of the picture for transportation applications. The energy must also be converted to useful work. The usable energy density provides insight into the impact of the conversion efficiency but does not consider the weight of the conversion device. The power-to-weight ratio of engines and electric motors vary widely; however, typical values are on the order of 0.5 kW/kg [4] and 3.0 kW/kg [5] for internal combustion engines and electric motors, respectively. In this case, it can be seen that the electric motor has a clear advantage. Accordingly, it is useful to combine the energy density of the storage (fuel or battery) and the mass of the energy converter (engine or electric motor) to assess the powertrain mass and identify areas where electrification is challenging. The storage plus converter mass for a fuel and internal combustion engine system can be calculated as mfuel+engine ¼ W_ b

t ρE,fuel

! W_ engine, max =W_ b + , ρengine

(3)

where W_ b is the brake power of the system, t is the operating time, ρengine is the power-to-weight ratio of the engine, and W_ engine, max is the maximum power output

FIG. 4 Useable energy density of several fuels and lithium ion batteries.

5

6

CHAPTER 1 Internal combustion engines and greenhouse gases

Table 1 Parameter values used for system-level comparison of IC engine and BEV-based powertrains. System

Parameter

Value

Fuel and internal combustion engine

Brake thermal efficiency (ηb) (%) Power-to-weight ratio (ρengine) (kW/kg) Lower heating value (LHV) (MJ/kg) Maximum power output (W_ engine, max ) (kW) Battery energy density (ρE, battery) (W h/kg) Maximum state of charge (SOCmax) Minimum state of charge (SOCmin) Discharge efficiency (ηdischarge) (%) Electric motor efficiency (ηmotor) (%) Power-to-weight ratio (ρmotor) (kW/kg) Maximum power output (W_ motor, max ) (kW) Battery capacity at the end of useful life Percent of brake power recovered during regenerative braking (ηregen) (%)

35.0 0.5 42.8 5W_ b 250 1 0.2 90 95 3.0 5W_ b

Battery and electric motor

0.8 10.0

of the engine. Similarly, the storage plus converter mass for a battery and electric motor system can be calculated as 0

mbattery+motor ¼ W_ b @

 1  ηregen ⁎t

ρE,battery,usable

1 W_ motor, max =W_ b A + , ρmotor

(4)

where ηregen is the fraction of brake power that is recovered during regenerative braking, ρmotor is the power density of the motor, W_ motor, max is the maximum power output of the motor. With these parameters, the mass of an electrified powertrain can be compared to an engine powertrain for a given duty cycle (i.e., required operating time and power). Table 1 shows the parameters used for this analysis. Operating time is varied from 0 to 24 h and operating power is varied from 0 to 250 kW. These ranges were selected to encompass a range of light through heavy-duty applications. Fig. 5 shows the mass of the battery and electric motor system minus the mass of the fuel and engine system. Several representative duty cycles for medium- and heavy-duty applications are also shown in Fig. 4. The details of these cycles are shown in Table 2 and discussed below. For operating times below 1 h, the mass of the battery and electric motor system is similar to or less than the mass of the fuel and engine system. This is because the storage plays a minimal role in this region due to the short operating time. When the operating time increases beyond 1 h, the mass of the battery and electric motor system begins to significantly exceed that of the fuel and engine system. For example, at an average power of 100 kW and operation for 4 h, the mass of the BEV system is approximately 1700 kg higher than the mass of the ICE-based system. Note that this is approximately the mass of a medium-sized sport utility vehicle. Increasing the required operating time further results in additional

2 Transportation energy requirements

FIG. 5 Increase in mass of a BEV-based powertrain compared to a conventional IC engine-based powertrain. Symbols show the average power and operating time for several representative medium- and heavy-duty on-highway cycles.

Table 2 Representative duty cycles for medium- and heavy-duty applications [6,7]. Cycle

Time (h)

Average power (kW)

Drayage Local delivery Long haul Regional haul Transit bus

8.6 5.0 19.7 9.9 16.1

42.1 57.0 107.6 91.8 29.9

increases in system mass. For example, at 107 kW (near the average power required for a long haul transport cycle) and 11 h of operation (long haul limit for a single driver in the United States), the mass of the BEV powertrain is 7000 kg greater than that of the internal combustion engine powertrain. Fig. 5 showed that the mass of an BEV architecture is substantially greater than that of a conventional engine architecture for duty cycles above 1 h. In the United States, the average daily driving time is 59 min [8]. Accordingly, this suggests that light-duty vehicles are well-suited for electrification with minimal increases in required weight. Conversely, heavy-duty vehicles operate over much longer duty cycles. For example, the National Renewable Energy Laboratory [6,7] evaluated 137 medium and heavy-duty vehicles and identified representative drive cycles

7

8

CHAPTER 1 Internal combustion engines and greenhouse gases

for drayage, long haul, regional haul, local delivery, and transit bus. The typical times for all of these cycles are greater than 5 h, suggesting that these sectors would have substantial penalties in mass if a battery is sized to perform the full duty cycle. In the above analysis, it is assumed that both the battery and fuel tank are sized to enable operation over the full duty cycle without recharging or refueling. Accordingly, it is useful to evaluate the need for this assumption by evaluating the required charging time. For a battery, the required charging time can be calculated as tcharge ¼

W_ b ⁎ð1ηregen Þ ηdischarge ηmotor ⁎t

V charge I charge ηcharge

,

(5)

where Vcharge is the charger voltage and Icharge is the charger current. Two options for charging will be considered: (1) a dedicated home charging station at 240 V, 48 A (max) and (2) a dedicated fast charge station (e.g., tesla supercharger) at 480 V and 300 A. Fig. 6 shows the charging time and average power and operating time for representative medium and heavy-duty applications [7]. At 240 V and 48 A, all of the medium and heavy-duty cycles charging times are greater than 1 day. It is worthwhile to note that this power level is 25% of a typical new construction home in the United States (typical homes have 240 V and 200 A service) and 50% of most homes built more than 30 years ago (prior to 1990 most homes in the United States were built with 240 V, 100 A service). Even with 480 V and 300 A, typical charging times for medium and heavy-duty vehicles are substantial. The shortest charging time is 2 h for the transit bus and local delivery applications. However, even for these applications, the charging times can become unacceptably long depending on the duty cycle. For example, although the shortest duty cycle for the local delivery cycle allows a recharge in 2 h, the most energy-intensive cycle operates for over 12 h and requires more than 12 h of charging, making it unsuitable for daily use. The transit bus application appears most suitable for full electrification, but even in this application, the longest cycle can exceed 19 h and require greater than 6 h of charging. Long-haul appears to be least suited for electrification as 4 out of 5 representative cycles operate at over 20 h and would require nearly a day of charging time after completing the cycle. Drayage and regional haul also appear to be challenging to electrify due to excessively long charging times.

3. Reducing greenhouse gas emissions from internal combustion engines The discussion in the previous section shows that even with the penetration of battery electric vehicles, many markets and sectors will continue to rely on internal combustion engines. Accordingly, continued research and development efforts are needed to reduce greenhouse gas (GHG) emissions and meet future GHG regulations. The regulatory landscape is rapidly changing. Fig. 7 shows the US light-duty CO2 regulations from 2022 to 2026. The regulations require a greater than 25%

FIG. 6 Charging time for a BEV over a range of average power and operating time. Symbols show the average power and operating time for several representative medium- and heavy-duty on-highway cycles.

10

CHAPTER 1 Internal combustion engines and greenhouse gases

FIG. 7 US light-duty CO2 regulations [9].

by 2026. Other countries have similar mandates in place. The European Union is proposing a 55% reduction by 2030, China is proposing a 20% reduction by 2025, and Japan is proposing a 24% reduction by 2030 [10]. Heavy-duty vehicles are facing similar requirements for reductions in CO2 at both the engine and vehicle level. For example, Fig. 8 shows CO2 regulations for a range of medium- and heavy-duty vehicles in the United States. Regulations require a 5% to 10% reduction in CO2 from 2020 to 2027.

FIG. 8 US medium- and heavy-duty emissions regulations [11].

3 Reducing greenhouse gas emissions from internal combustion engines

3.1 Approaches to reaching GHG targets To reach future GHG target approaches must consider a combination of the fuel (well-to-tank (WTT)) and powertrain (well-to-wheels (WTW)) CO2 emissions. The combination can be considered through the following expression 

BSCO2WTW,engine ¼

CO2welltotank +

 nc ⁎MW CO2 1 , LHV⁎MW f ηbrake

(6)

where CO2well to tank is the mass of CO2 produced or consumed during production of the fuel, nc is the number of carbon atoms in the fuel, MWCO2 is the molecular weight of CO2, and MWf is the molecular weight of the fuel. It is useful to compare the fuel and engine well-to-wheels CO2 with an equivalent value from an electric vehicle charged using the grid. The US average CO2 from a power plant is 425 g/kW h [12]. This can be converted into a well-to-wheels value using BSCO2WTW,BEV ¼

BSCO2grid , ηtranmission ⁎ηcharge ⁎ηdischarge ⁎ηmotor

(7)

where ηtransmission is the electric power transmission efficiency (i.e., considering any losses in the electric lines). Typical values for transmission losses are 5%. Fig. 9 shows the well-to-wheels (or well-to-shaft) CO2 emissions as a function of brake thermal efficiency for several fuels and the equivalent WTW CO2 for a BEV with 95% transmission efficiency, 85% charging efficiency, 90% discharging efficiency, and 95% electric motor efficiency. Beginning with a baseline case at 40% brake thermal efficiency, CO2 emissions can be reduced from 776 to 621 g/kW h by increasing the brake thermal efficiency to 50% using diesel fuel with a well-to-tank CO2 of 44.5 g/kW h. 50% brake thermal efficiency has been demonstrated by a variety of heavy-duty engine original equipment manufacturers (OEMS) through the United States Department of Energy SuperTruck Program [13]. It is interesting to note that this results in an equivalent CO2 of a gridcharged BEV without considering CO2 from battery production. Further improving brake thermal efficiency to 55% would allow BSCO2 reductions to 564 g/kW h, approximately 9% lower than a BEV charged from the current (average) grid. These results show promising, near-term potential to achieve over a 25% reduction in brake specific CO2 emissions. Utilizing ethanol or renewable diesel fuel enables step changes in WTW CO2 emissions. For example, at 40% BTE, an ethanol-fueled engine would have WTW CO2 emissions of 387 g/kW h, 63% lower than a diesel-fueled engine with equivalent BTE and 37% lower than a BEV. The reductions in WTW CO2 are even greater using soybean-based renewable diesel fuel. A soybean-based renewable diesel-fueled engine at 40% BTE has WTW CO2 of 142 g/kW h, 103% reduction compared to a petroleum diesel-fueled engine and 77% lower than a BEV. Further reductions are possible if the engine efficiency is improved along with utilization of renewable fuels.

11

12

CHAPTER 1 Internal combustion engines and greenhouse gases

FIG. 9 Well-to-wheels CO2 emissions for several fuels as a function of the engine’s brake thermal efficiency. The horizontal dashed line shows the CO2 emissions of a battery electric vehicle charged with the average United States electric grid.

3.2 Challenges of using renewable fuels in medium- and heavy-duty engines The analysis above showed that the use of ethanol, renewable gasoline, and renewable diesel fuel are promising pathways to substantially reduce CO2 emissions. These approaches have the potential to achieve CO2 emissions substantially below that of a comparable battery electric vehicle. These fuels each have benefits and challenges. Renewable diesel fuel meets ASTM D975 [14] and is, therefore, a direct drop-in for existing engines. If renewable diesel fuel can be produced in a volume suitable for replacement of diesel fuel, this is an extremely promising approach; however, renewable diesel fuel capacity is currently 600 million gallons per year with a near-term goal to grow to 2 billion gallons per year [14]. US diesel fuel consumption is 45 billion gallons per year, highlighting a substantial shortfall; accordingly, other renewable fuels will be needed to enable substantial CO2 reductions. Ethanol and renewable gasoline have the potential to provide a portion of this energy. For example, ethanol is a well-established fuel with a current production

3 Reducing greenhouse gas emissions from internal combustion engines

capacity of 17 billion gallons per year in the United States [2]. The light-duty sector is the dominant end-use for ethanol. Fig. 5 showed that the light-duty sector is suitable for electrification; accordingly, it is expected that demand for ethanol from the light-duty market may decrease in the medium/long term. This suggests that finding approaches to utilize ethanol and renewable gasoline in medium- and heavy-duty engines is needed. The simplest approach to use ethanol and renewable gasoline in medium- and heavy-duty engines would be to use a spark-ignited (SI) combustion mode. However, SI combustion typically has lower efficiency than a comparable compression ignition engine due to a knock-limited compression ratio and the requirement for stoichiometric operation. Furthermore, the medium- and heavy-duty engine markets are dominated by diesel engines due to their superior performance characteristics, including snap torque response, higher torque capability that is not limited by knock, higher efficiency over a wide operating space, and combustion robustness under widely varying operating conditions. Diesel engines operate in a compressionignited (CI) combustion mode, in which fuel is injected directly into the combustion chamber, entrains air and subsequently auto-ignites when the chamber reaches a high enough temperature due to compression. This mode of combustion is well-suited for fuels that are easily ignited (often referred to as high-cetane), such as diesel. However, fuels such as ethanol and gasoline are much less reactive, which makes them unsuitable for use in certain portions of the CI combustion operating space. Accordingly, there is a need to study the challenges of using low-cetane fuels such as ethanol and gasoline-like fuels in CI combustion modes. Gasoline is the most widely studied low cetane fuel for compression ignition applications (e.g., [15–18]). Accordingly, much of the discussion will focus on gasoline compression ignition (GCI) combustion; however, it is expected that approaches for gasoline compression ignition combustion will be applicable to ethanol and other low cetane liquid fuels. At high-load operating conditions, utilization of these fuels is straightforward. For example, Paz et al. [19] compared gasoline and diesel fuel at full load conditions in a heavy-duty engine and showed that their combustion characteristics are nearly identical. However, at low-load conditions, fuel injection becomes shorter, incylinder pressures and temperatures decrease and the mixtures become leaner, considerably decreasing the reactivity of the fuel-air mixture. This decreased reactivity substantially impacts combustion and operability [20]. Accordingly, this section will focus on discussion of approaches to enable low-to-mid load operation using lowcetane fuels. Table 3 summarizes low-load GCI strategies and focuses on the fundamental impact of each strategy.

3.2.1 Intake charge preparation The use of intake charge preparation to stabilize compression ignition operation of low cetane fuels typically relies on intake heating or intake pressurization. The role of intake pressure on GCI combustion has been well-studied by several authors [21–23]. Hanson et al. [22] found that, on a heavy-duty engine, ignition delay shortened as intake pressure was increased, which they hypothesized as being due to

13

Table 3 Summary of GCI stabilization methods in current literature. Strategy Intake charge preparation

Increasing intake pressure

Intake charge heating Intake charge heating (exhaust regen) Un-cooled EGR VVA strategies

Injection parameters

Negative valve overlap (NVO) Rebreathing

Spray targeting

Rail Pressure

Primary effect

Efficiency

Implementation

Effectiveness

Hardware cost

Secondary effect

Drawback(s)

References

Increases reactivity and enhances lowtemperature heat release Increases reactivity

Reduces over mixing through increased charge density and decreased ignition delay

Energy requirements

[21–26]

Decreases ignition delay

[24,27–29]

Increases reactivity

Decreases ignition delay

Energy requirements; cold starts Energy requirements; cold starts

Increases charge temperature Increases charge temperature

None

Reduced O2

[30–34]

Fuel injection and reforming during NVO

Reduced O2, efficiency losses

[35–37]

Increases charge temperature Reduces over mixing (retains fuel in piston bowl) Reduces over mixing

None

Reduced O2

[36,38,39]

None

Geometry not optimized high load

[40,41]

Reduces atomization

Emissions increase

[42,43]

[24,27–29]

Fuel reactivity

Cetane improvers Fuel blending In-cylinder fuel blending Intake seeding

RON

Low fuel sensitivity

Aromatic fraction

Increases fuel reactivity Increases fuel reactivity Increases fuel reactivity

Decreases ignition delay LTHR may be enhanced Reduction in second fuel to additive levels

Emissions increase Blending fuels

[41]

Fueling hardware

[50–52]

Increases reactivity and enhances LTHR Increases ignition delay

Improves performance of multiple injection GCI

New concept

[53,54]

None

[46,55]

Low sensitivity fuels tend to be more reactive at low temp High aromatic fuels tend to resist autoignition at low temperatures

NTC behavior may be favorable at high load

Tradeoffs between stability and emissions None

Exhibits behavior opposite of the ideal GCI fuel

[55–57]

The interaction between aromatics and cycloalkanes my decrease ignition delay at high temperatures

[43–49]

[55,56]

16

CHAPTER 1 Internal combustion engines and greenhouse gases

increased charge reactivity; this hypothesis was also proposed by Ra et al. [24]. Studying the demands placed on the air handling system during GCI operation, Kumar et al. [58] showed that although capable of handling the demands, the stock turbocharger on diesel engines is often not efficient during GCI operation. They showed that off-the-shelf turbocharging options were much more efficient, suggesting that new air-handling technology is not necessarily required for GCI operation so much as altered matching procedures with the specific boost and EGR constraints better taken into account. Ra et al. [24] found that increasing intake temperatures improved the stability of combustion by increasing charge reactivity when operating under GCI conditions. However, they also found that increasing the intake temperatures caused excessive pressure-rise rates and thus recommended using low intake temperatures with high exhaust gas recirculation (EGR) rates to keep the operating window wider. An et al. [59] studied the role of intake temperature in an optical engine by varying the intake temperature from 50 °C up to 120 °C. To make their study representative of incylinder conditions, they used a re-entrant piston geometry identical to that of a production diesel engine and continuously fired the injector for 150 cycles, as opposed to the skip-fire approach typically adopted in optical studies, both of which makes their study particularly unique. They showed that 70 °C was the lowest intake temperature at which stable combustion was possible when a 150 kPa intake pressure was used and that this temperature is also optimal for gross indicated efficiency (GIE) and NOx emissions, although not for soot emissions, which correspondingly increase. Analyzing the combustion stratification data, they found that as the intake temperature is decreased, the in-cylinder stratification decreases, resulting in less stable combustion. Similar results were reported by Jiang et al. [60], who studied the role of intake temperature on HFS-GCI and found that at low loads, intake heating enhances both stability and efficiency.

3.2.2 Variable valve actuation Several variable valve actuation (VVA) strategies have been attempted to extend the operating range of GCI. These include cylinder deactivation (CDA), negative valve overlap (NVO) and exhaust rebreathing for stabilization at low-load as well as early intake valve close (EIVC) and late intake valve close (LIVC) to improve premixing and reduce soot emissions. NVO is the effect achieved when the exhaust valve is closed early, leading to more exhaust gas remaining trapped in the cylinder as residuals. Borgqvist and coworkers investigated the effect of negative valve overlap on ignition delay on a light-duty CI engine [37,39,61] and found that while the increased trapped residuals helped stabilize combustion, they also reported decreased pumping efficiency, concluding that the minimum level of NVO needed to stabilize combustion under any set of operating conditions is the level that should be utilized. Further, they observed that the inclusion of a fuel injection event during the NVO period resulted in more efficient and stable combustion, which was corroborated by Urushihara et al. [36].

3 Reducing greenhouse gas emissions from internal combustion engines

Exhaust re-breathing is similar to NVO in that the goal is to introduce exhaust gases into the combustion chamber directly, but the method adopted is different: rebreathing is achieved by opening the exhaust valve during the intake stroke, typically through the modification of the exhaust cam. Borgqvist et al. [39] investigated rebreathing and found that it offers similar combustion stability characteristics to NVO (without the aforementioned fuel injection event during NVO), but with superior efficiency. This difference in efficiency was explained to occur due to a decrease in pumping efficiency seen with the use of NVO, that was not observed when rebreathing was used. Studying CDA and cylinder cutout on a single-cylinder GCI engine, Babu and Kokjohn [62] reported that stable GCI operation was achievable down to a no-load condition, with simultaneous improvements in fuel consumption and aftertreatment temperature. The improvement in stability was shown to primarily be due to a lengthening of the fuel injection while the fuel efficiency benefit was shown to arise from the reduction in pumping and heat transfer losses. Zhang et al. [63] studied EIVC on a heavy-duty GCI engine and found that, in conjunction with a tailored fuel injection strategy, fuel consumption and soot were lowered while NOx emissions remained constant and stability was maintained throughout. They concluded that careful variation of the effective compression ratio (ECR) through EIVC could maintain stability while yielding fuel consumption and emissions benefits. Kumar et al. [64] studied both LIVC and EIVC and found that although EIVC is superior from the standpoint of reducing the ECR, it also results in greater pumping losses. They also pointed out that a coupled adjustment to the air handling system would be needed if VVA strategies were to be implemented, to avoid offsetting deterioration in the turbocharger performance. Pursuant to this, Kumar et al. [65] worked with BorgWarner Inc. to study an off-the-shelf 2-stage turbocharger as well as a prototype single-stage turbocharger matched with the explicit goal of meeting boost and EGR targets during VVA-GCI operation. They concluded that the 2-stage turbocharger offered significantly reduced pumping losses when compared to the stock turbocharger, while the single-stage prototype offered a significant improvement in combined turbocharger efficiency alongside an improvement in the engine BTE.

3.2.3 Fuel injection effects Ciatti and coworkers [30,46] have investigated the effect of the injector nozzle included angle, start of injection (SOI) timing and injection pressure on low-load GCI combustion in a light-duty engine using 87 AKI gasoline. They concluded that a lower included angle caused a narrower spray cone, which kept combustion confined to the bowl; the resultant combustion is locally richer, causing an increase in stability. However, this effect is typically undesirable at higher loads, where locally rich combustion could result in increased PM emissions. They also concluded that GCI stability improves as injection pressures are lowered, which they conclude to be because of overmixing at high injection pressures; this finding was subsequently confirmed by Roberts [66].

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Kalghatgi et al. [67] studied the role of pilot injections in GCI and found that the pilot injection considerably delayed the combustion phasing, with low cyclic variation compared to a single injection strategy, indicating a stability improvement. In another study, Kalghatgi et al. [68] also reported the potential of shaping the HRR profile by using multiple injections: they showed that the low reactivity of gasoline allowed for injections quite early in the cycle with additional injections near TDC to initiate autoignition. The fundamental reason for improved combustion stability when using multiple injections was shown by Goyal et al. [69], by conducting line-of-sight studies in an optical engine. When comparing single and pilot-main injection strategies, they found that pilot-main injection strategies cause a more rapid transition from low- to high-temperature combustion. They quantified this transition by using HCHO and OH radical concentrations while theorizing that the speed of this transition directly dictated the combustion stability. This assertion was supported by Tang et al. [70], who showed that misfire due to combustion instability was well-correlated to the persistence of HCHO in the combustion chamber. An et al. [71] studied the role of injection schedule on GCI stability by comparing single, pilot-main and pilot-main-post injection strategies in an optical engine. They showed that lower intake temperatures were needed to stabilize GCI when multiple injections were used, compared to the reference single injection strategy, concluding an increase in combustion stability from the use of multiple injections. They showed that an increase in injection pressure when using multiple injections led to increased efficiency and stability due to the formation of pool fires; unfortunately, these pool fires also contribute to increased HC and CO emissions, especially at late stages of the combustion. They also concluded that when multiple injections are used, the authority of SOI timing over combustion phasing is transferred to the main injection of fuel, as opposed to the pilot injection. The latter finding was echoed by Lundgren et al. [72], who also compared single injection and pilot-main injection schedules; they concluded that the ignition is delayed by the main injection, which tends to cool the bulk gas, but that the spacing between the two injections offers additional control over the combustion phasing. Studying triple injection strategies, Liu et al. [73] found that decreasing the post-injection ratio (increasing the proportion of fuel injection during the main injection event) led to increased premixing as well as increased wall-wetting, which leads to lower soot emissions and lower efficiencies respectively. Cung et al. [74] showed that the third (post) injection has the effect of reducing CO and HC emissions by promoting oxidation. Other injection schedule optimization efforts [75–79] concurred with the previous findings and further concluded that pilot-main injection schedules with 5– 10 degrees of dwell between the pilot and main injections are advantageous because they simultaneously reduce combustion noise while improving control both at medium- and high-load strategies. Zhang and coworkers [77,80] also found that the reduced heat loss due to the split injection strategy increased efficiency and that split injections were highly effective at improving combustion stability while reducing excessive combustion noise regardless of the reactivity of the gasoline.

4 Conclusions and future directions

3.2.4 Fuel reactivity effects on GCI Wang et al. [43] investigated the effects of fuel reactivity on low-load GCI combustion through pre-blending of gasoline and diesel. The increased reactivity of the blends caused significant improvement in the minimum load achievable; a blend of 80% gasoline and resulted in a substantial reduction in ignition delay and decreased the minimum achievable load from 2.5 bar to 1.8 bar. Roberts et al. [66] investigated pre-blended mixtures of diesel and gasoline and found that judicious use of EGR combined with the use of diesel as an additive allowed NOx levels to be reduced to near-zero values with the minimum intake pressurization required. A detailed investigation into the effects of EGR showed that, for a given fuel, there is a maximum EGR rate that allows for stable operation, which sets the minimum engine-out NOx emissions. In another study, Roberts et al. [81] investigated a novel fuel injector that could blend gasoline and diesel on the fly and found that stable GCI operation could be achieved down to no-load conditions with no more than 20% diesel. Simulating a full drive cycle, they showed that at most conditions, no diesel would be needed for stable operation, bringing overall diesel usage over the drive cycle below DEF usage for trucks on the road today.

4. Conclusions and future directions The discussion in the preceding sections has shown that internal combustion engines are likely to make up a large portion of the transportation industry for the foreseeable future. The energy density differences between liquid hydrocarbons and electrochemical storage (i.e., batteries) makes replacing engine-based powertrains with fully electric powertrains challenging for applications where duty cycles exceed 1 h. Furthermore, the analysis suggests that an engine-based system fueled by renewably sourced fuels has the potential to achieve CO2 emissions substantially below that of a battery electric vehicle. The discussion suggests that fuel flexibility will be very important in the future and it is likely that large-bore engines suitable for operation on low cetane fuels are needed. Discussion in the final section focused on gasoline compression ignition as an example of approaches to achieve stable combustion of a low cetane fuel. The analysis showed several pathways to achieve stable compression ignition operation of low cetane fuels; however, it can be seen that this is an area where additional research and development efforts are needed. The following areas are suggestions for areas where future efforts are needed. •

Fuel agnostic combustion systems suitable for use with a range of future, low carbon fuels. Effort is needed to identify robust ignition strategies that are insensitive to the fuels cetane number to enable fuel flexible combustion systems that can be used with no or minimal modifications as new low carbon fuels come to market. These efforts may require development of new approaches to simulate reacting systems and improvements in fuel chemical kinetics models for new and future fuels.

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•

•

•

Hybrid powertrains for off-highway vehicles. Off-highway vehicles have duty cycles that require substantial operating time and are often operated in remote environments with limited electric power infrastructure; accordingly, it is expected that these applications will continue to be powered by internal combustion engines well into the future. However, increasing electrification of implements for improved control and precision (e.g., placement of seed) makes electric systems available for use. Additional research is needed into engine and powertrain systems that can take advantage of the increased level of electrification in an internal combustion engine dominated powertrain. Full level analysis of the GHG intensity of various powertrain architectures. The discussion in this chapter showed that in many scenarios an internal combustion engine can have equivalent or lower CO2 than a battery electric vehicle. However, more detailed analysis is required to consider spatial (e.g., different regions have vastly different grid-level CO2) and temporal dependence of the electric grid (e.g., charging at night uses primarily fossil fuels while charging during the day can take advantage of intermittent renewables). Furthermore, it is expected that future fuels and increasing penetration of renewable energy will change the CO2 outlook of various energy carriers. Continued refinement of conventional powertrains. Continued effort focused on conventional powertrains fueled by today’s energy carriers is needed to ensure that progress can be made to improve efficiency and reduce criteria pollutants. This requires training and education to ensure a robust workforce that can address near and mid-term solutions that will likely be primarily powered by internal combustion engines.

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comparison with a diesel fuel, SAE Technical Paper Series, no. 2007-01-0006, 2007, https://doi.org/10.4271/2007-01-0006. G. Kalghatgi, L. Hildingsson, B. Johansson, Low NOx and low smoke operation of a diesel engine using gasolinelike fuels, J. Eng. Gas Turbines Power 132 (9) (2010), https://doi.org/10.1115/1.4000602. H. Goyal, Y. Zhang, S. Kook, K.S. Kim, C.-B. Kweon, Low- to high-temperature reaction transition in a small-bore optical gasoline compression ignition (GCI) engine, SAE Int. J. Engines 12 (5) (2019), https://doi.org/10.4271/03-12-05-0031. Q. Tang, H. Liu, M. Li, M. Yao, Optical study of spray-wall impingement impact on early-injection gasoline partially premixed combustion at low engine load, Appl. Energy 185 (2017) 708–719, https://doi.org/10.1016/j.apenergy.2016.10.108. Y. An, et al., Combustion stability study of partially premixed combustion by highpressure multiple injections with low-octane fuel, Appl. Energy 248 (2019) 626–639,https://doi.org/10.1016/j.apenergy.2019.04.048. M. Lundgren, et al., Optical study on combustion transition from HCCI to PPC with gasoline compression ignition in a HD engine, SAE Technical Paper Series, 2016, https:// doi.org/10.4271/2016-01-0768. X. Liu, H. Goyal, S. Kook, Y. Ikeda, Triple injection strategies for gasoline compression ignition (GCI) combustion in a single-cylinder small-bore common-rail diesel engine, SAE Technical Paper Series, 2019, https://doi.org/10.4271/2019-01-1148. K. Cung, et al., Investigation of gasoline compression ignition (GCI) combustion in a high compression-ratio heavy-duty single-cylinder diesel engine, SAE Technical Paper Series no. 2021-01-0495, 2021, https://doi.org/10.4271/2021-01-0495. H. Liu, B. Mao, J. Liu, Z. Zheng, M. Yao, Pilot injection strategy management of gasoline compression ignition (GCI) combustion in a multi-cylinder diesel engine, Fuel 221 (2018) 116–127, https://doi.org/10.1016/j.fuel.2018.01.073. B. Mao, P. Chen, H. Liu, Z. Zheng, M. Yao, Gasoline compression ignition operation on a multi-cylinder heavy duty diesel engine, Fuel 215 (2018) 339–351, https://doi.org/ 10.1016/j.fuel.2017.09.020. Y. Zhang, et al., Mixing-controlled combustion of conventional and higher reactivity gasolines in a multi-cylinder heavy-duty compression ignition engine, SAE Technical Paper Series, 2017, https://doi.org/10.4271/2017-01-0696. M.R. Herfatmanesh, P. Lu, H. Zhao, In-cylinder studies of high injection pressure gasoline partially premixed combustion in a single cylinder optical engine, SAE Technical Paper Series, no. 2015-01-1819, 2015, https://doi.org/10.4271/2015-01-1819. Y. Han, D. Yoo, W.G. Lee, J. Sim, J. Chang, A demonstration of high efficiency, high reactivity gasoline compression ignition fuel in an on & off road diesel engine application, SAE Technical Paper Series, no. 2020-01-1311, 2020, https://doi.org/10.4271/ 2020-01-1311. Y. Zhang, P. Kumar, Y. Pei, M. Traver, D. Cleary, An experimental and computational investigation of gasoline compression ignition using conventional and higher reactivity gasolines in a multi-cylinder heavy-duty diesel engine, SAE Technical Paper Series, 2018, https://doi.org/10.4271/2018-01-0226. J. Roberts, S. Kokjohn, D. Hou, Y. Huang, Performance of gasoline compression ignition (GCI) with on demand reactivity enhancement, SAE Technical Paper Series, no. 201801-0255, 2018, https://doi.org/10.4271/2018-01-0255.

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2

Francesco Carbonea, Kevin Gleasonb, and Alessandro Gomezb Department of Mechanical Engineering, University of Connecticut, Storrs, CT, United States, b Yale Center for Combustion Studies, Department of Mechanical Engineering and Materials Science, Yale University, New Haven, CT, United States

a

1. Will soot research be relevant in the next few decades? The emission of carbonaceous particles (i.e., soot) is a problem that has been plaguing humans for centuries, with repercussions on health [1–3] and climate [4,5] that have become clear only in recent decades. Soot is an inevitable byproduct of wildfires and most combustion technologies responsible for more than 80% of the total energy conversion worldwide. Soot optical properties make it a good absorber in a broad range of solar wavelengths and soot deposition on snow-covered surfaces or ice decreases the albedo contributing to global warming [6]. The impact on global warming is evidenced by the fact that soot is considered the second most significant contributor to radiative forcing in climate change [4,5]. Even if stringent regulations have curtailed the emissions of large soot particles in combustion technologies, the health impact remains unabated because of the reported increased toxicity of nanosized materials [7–9] with sorbed toxic semi-volatile compounds. To address the universally recognized existential threat from climate change, most industrialized countries, including the United States, pledged to be carbonneutral by the year 2050, with China following suit by 2060 [10]. However, the experience of the past few decades shows that pledges are all too often unfulfilled even by countries that are environment-friendly and have a relatively harmonious political system. The problem is compounded in the United States because the alternation of administrations results in inconsistent policies, as shown by the flip-flop in climate and energy policies in the past two decades. With this premise, it is tempting to conclude that, to some extent, it will be business as usual for combustion engineering and the attending soot challenges in the next 25 years. Projections from multiple sources, including the US Energy Information Administration, still list fossil fuels as the dominant source of energy even in 2050, although in a diminished capacity compared to today’s energy landscape, with renewable energy projected to satisfy only 25% of the ever growing world energy consumption [11,12]. This somewhat pessimistic stance Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00007-2 Copyright # 2023 Elsevier Inc. All rights reserved.

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is partially counteracted by recent declarations from some industry leaders who, under public opinion pressure, are acting even without a government mandate. For example, General Motors has declared that will sell only zero-emission vehicles by the year 2035 [13], although other automakers have been reluctant to sign any pledge the fulfillment of which depends on an infrastructure (e.g., electric grid, charging stations, etc.) that governments would have to build [14]. In conclusion, the primary reason why soot research will remain relevant in the next 25 years is that we will not be able to wean ourselves off fossil fuels in such a time. This statement holds on an even longer time horizon for certain sectors like power production in aerospace and maritime applications, in which petroleum-based liquid fuels such as diesel and jet fuel are likely to remain dominant players because of their high energy density [12]. On the other hand, certain combustion engineering applications such as internal combustion engines in passenger cars may be progressively phased out in favor of the electrification of the fleet. The substitution of conventional fossil fuels with alternative fuels is no panacea. Potentially viable alternatives compatible with a Carbon-neutral economy are hydrogen and biofuels. Of course, hydrogen combustion does not produce soot, but applications of green hydrogen will become viable only when its production and storage become economically competitive, which is unlikely to happen in the short term. This is the case despite the recent sharp decrease in the cost of renewable energy, especially solar, that would be used in the electrolysis route to green hydrogen. As to biofuels, except for currently marginal production from organic scraps (e.g., food waste and industrial waste), they are derived from energy crops and include ethanol and, to a much lesser extent and mostly in Europe, biodiesels. From a soot emissions perspective, the control of soot emissions remains a challenge primarily for biodiesels, even though they are partially mitigated by the presence of oxygen in the fuel which lowers the soot yield in comparison to conventional diesel fuels [15–18]. From a broader perspective, there are two reasons to have reservations about the carbon neutrality of crop fuels, which tempers any enthusiasm for biofuels: it should be analyzed on a life cycle basis, including changes in land use whose assessment is very uncertain, and it should account for the use of fertilizers and the consequent increase in emission of NOx, a much more potent global warmer than CO2. Furthermore, from a net energy balance (energy from biofuel divided by fossil fuel energy to produce it) some biofuels like ethanol from sugar cane make sense both energetically and economically, while others like corn ethanol are marginal, with biodiesels falling somewhere in between.

2. The lingering challenge of soot nucleation This chapter focuses on our perspective on the major challenge in soot research: soot nucleation, that is, the transition from the gas phase to the particle phase. A critical gap remains between soot gaseous molecular precursors, including Polycyclic

3 Laminar flames as the preferred setting for soot studies

Aromatic Hydrocarbons (PAHs), molecular clusters, and incipient soot particles, mostly because of the lack of a concurrent chemical and physical characterization encompassing the relevant dimensional range due to diagnostic limitations. Additionally, as emissions are reduced in terms of mass, nucleation becomes increasingly more relevant in determining the release of the smallest and most toxic particles. On the other hand, once soot particles are formed, the growth mechanisms by coagulation, agglomeration, and concurrent surface growth are reasonably well understood and tackled with well-established methods. This is the reason why most soot studies to date concerned themselves with these late steps of particle evolution. This review chapter has a relatively narrow scope in covering the experimental work relevant to soot nucleation. The discussion points out areas that are ripe for further development and considers the most convenient setting for soot nucleation studies, namely laminar flames. We focus on the arsenal of diagnostic techniques to employ in these “battlefields,” which bears on the flame configurations that are compatible with them and discuss some of the limitations of the diagnostics as well as approaches for further improvements. Next, we cover methods to stabilize flames with the desired characteristics to guarantee a high level of control of key variables and allow us to infer cause-effect relationships. We conclude by presenting two exemplars of comprehensive studies in laminar flames. For a broader overview of a field that has been the focus of research for more than half a century the reader is referred to several review articles [19–23].

3. Laminar flames as the preferred setting for soot studies Fundamental kinetic studies may be performed in shock tubes and other types of pseudo-homogeneous reactors (e.g., flow reactors, perfectly stirred reactors, rapid compression machines, etc.) [24–30]. To the extent possible, such reactors aim at reducing the complexity of the reactive environment from a fluid mechanics standpoint, thereby simplifying the interpretation of chemical kinetic pathways in the formulation of chemistry mechanisms for subsequent integration in computational models. However, they do not capture the coupling between chemistry and transport phenomena (i.e., diffusive processes) which is critical in all flames and may have consequences on the sequence and relative importance of reactions occurring in practical devices. Indeed, soot formation in shock tubes is not the same as in flames [31] and one should be cautious when generalizing conclusions to different environments. As macroscopic evidence of this distinction, one should consider that shock tubes have characteristically short time scales during which the fuel pyrolysis, aromatic growth, and soot nucleation occur at a constant temperature so that soot formation is affected prevalently by the thermodynamic stability of soot precursors [19,32]. The thermodynamic stability decreases with increasing temperature, counteracting an increase in the Arrhenius-based reaction rates, such that soot formation exhibits a non-monotonic temperature trend and soot ceases to exist at sufficiently high

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temperatures [26,33]. In contrast, early studies on soot production in diffusion flames revealed a monotonic trend with temperature [34,35]. The spatial temperature gradients and mass transport intrinsic to all practical flames allow soot precursors and particle nuclei to be formed in regions at different temperatures and affect the relevant kinetics via transport. Since flames maintain the coupling between chemistry and transport, we consider them better suited to investigate the formation of soot at a fundamental level. The understanding of soot nucleation requires the quantification of the evolution of the parent fuel molecule into soot precursors and eventually particulate so that well-controlled laminar environments with simple fluid mechanics but inevitably complex kinetics are favored for fundamental investigations. As a result, the majority of soot studies are performed on laminar flames of either diffusion or premixed type to assess the effect of the key variables associated with combustion, such as temperature, pressure, local equivalence ratio, stoichiometric mixture fraction, reactant composition, etc. [19–21,31,32,36,37]. Turbulent flames, on the other hand, to the extent that the application of intrusive/sampling diagnostics is indispensable to a detailed understanding of soot inception, as discussed in the following section, are not a good choice for the study of soot nucleation since they would provide at best average quantities of limited usefulness and the intrusiveness of the diagnostic technique would be difficult to quantify. If the ultimate goal remains the understanding of what occurs in engines and other practical combustion devices, it is tempting to consider studying soot directly in such environments. However, the complexity associated with turbulence and the timedependence associated, for example, with the cylinder compression/expansion cycle, makes the task very difficult, if not impossible. Even the application of laser diagnostics would have severe restrictions in terms of a complete and quantitative characterization, in addition to physical restrictions to access the combustion environment within the engine. Moreover, the control and abatement of soot formation in engines are generally engine-specific, with dependencies on geometry, injection timing, intake temperature, etc. [38]. We conclude that it is preferable to capture critical aspects of soot nucleation in steady laminar flames. This approach should not diminish the importance of practical engine experiments because qualitative measurements can help define the direction of fundamental studies [38–41]. For example, experiments in Compression Ignition (CI) engines [39,40] revealed that soot appears to form and grow in a rich premixed-flame environment and is eventually oxidized in a nonpremixed (diffusion) regime. Such a process can be captured fundamentally in a partially premixed laminar flame using a counterflow configuration [42–46].

4. Diagnostics The understanding of soot formation and validation of soot models in the context of nucleation requires the use of complementary experimental approaches because the process involves materials with disparate sizes (masses) ranging from

4 Diagnostics

sub-nanometric (1 Da) to tens of nanometers (several thousand Daltons), which cannot be all characterized by a single diagnostic technique. In principle, one should quantify all gaseous species, including the largest ones that can be considered either soot precursors or nuclei, and characterize soot particles in terms of their distribution of sizes, elemental composition, charge, optical properties, and morphology, including the smallest ones that may be viewed as large molecules or molecular clusters. Additionally, all measurements should be performed with the necessary spatial resolution. One can rely on two classes of techniques to gather the desired information: the first includes diagnostics that are based on intrusive sampling, and the second encompasses optical methods that are relatively unintrusive. Sampling followed by chemical analysis is indispensable for chemical speciation since laser diagnostics are very limited in terms of the species they can probe and quantitate accurately. Optical techniques, on the other hand, are often best suited for the particle phase, although sampling methods have been recently extended to characterize incipient particles. We now consider typical diagnostic techniques for the study of soot nucleation in flames and highlight their limitations.

4.1 Sampling-based diagnostics 4.1.1 Molecular Beam (MB) sampling coupled with Mass Spectrometry (MS) One of the first sampling-based diagnostics is the MB-MS analysis of flame products. It was introduced in the 1960s in the study of the chemistry of premixed flames at sub-atmospheric pressures [47]. MB sampling relies on the ability to quench collisions among the sample components via a supersonic expansion which, ideally, freezes the chemistry enabling the quantitation of even short-lived radical and charged species [48–52]. The transport time of the analyte from the flame to the ionization site and subsequent analysis zone of the instrument is also minimized so that MB-MS became the standard technique for the measurement of the gaseous products in premixed flames, including radical species. MB-MS studies began with the pioneering work of Homann and Wagner [47] and included notable entries from Howard’s group at MIT [49] for the detection of molecules ionized via electron impaction, ions, and naturally charged particles. Most recently MB-MS benefited from the introduction of photoionization with tunable photon energy (larger than 1 eV) that enabled the distinction of isomeric species with the same mass [50–52]. The advantages of MB-MS come at the cost of significant perturbation of the flame through the unavoidable use of bulky skimmers and very high (i.e., sonic) sampling velocities, causing severe distortions of the temperature, flow, and composition fields of the flame [48,50–55]. To date, there is no reliable approach to account for the biases introduced by such a perturbation and questions remain about the relation between the results of the measurements and the real composition of the material in the unperturbed flame. Other limitations of the ionization methods appear when one wants to quantitate the large species and/or molecular clusters that are involved in

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soot nucleation and are present in the flame in relatively low concentrations: the (temperature-dependent) values of ionization efficiencies are unknown for large aromatic species and always very small under the deep MB vacuum, posing severe limitations in the accurate quantitation and often even detectability of the mechanistically most interesting large analytes. The problems become insurmountable if one wants to quantify weakly bonded molecular clusters formed in flames at temperatures lower than 2200 K. Indeed, even for the mildest photoionization, the energy of photons is larger than the average kinetic energy of gas molecules at 7000 K. Consequently, and unavoidably, photoionization causes the fragmentation of weakly bonded clusters [56,57]. Furthermore, a study with MB-MS in a premixed flame [58] demonstrated that a large fraction of OH radicals sampled from the flame is photo-ionized after impacting the wall of the vacuum chamber rather than within the MB. Such a finding not only poses questions on the quantitative accuracy of the results based on estimates of the MB temperature and velocity (among other parameters influencing the ionization efficiency), but also raises concerns about possible modifications of the population being ionized and analyzed only after it interacted with the wall.

4.1.2 Capillary sampling followed by chemical analyses of stable species The challenge of intrusiveness is often mitigated by investigating laminar flames with mild gradients (e.g., premixed) in which spatial resolution is not a limiting factor and the residence time of the reactant flow in the perturbed region of the flame can be made small compared to that in the unperturbed zone of the flame [59,60]. Perturbations of the flame affecting the temperature and flow fields (i.e., the temperature-time history) in the proximity of the sampling position cause the sampled population to differ from that of the gaseous mixture present in the unperturbed flame. Sampling may result even in the chemical modification of the sampled gas. The problem is exacerbated at high pressures because an increase in pressure reduces the diffusivity of gases and decreases the flame thickness, which makes spatially resolved measurements more challenging. The insertion of the probe often “drags” the flame, introducing uncertainty in the sampling location, and distortion from its originally planar geometry. This dragging was quantified by laser-induced fluorescence in diffusion flames visualizing the shift in OH concentration due to the presence of the probe [61], and the magnitude of the dragging is dependent on the probe position relative to the stagnation plane of the counterflow flame. The effect can be corrected by measuring optically the distance between the probe tip and the distorted flame blue chemiluminescence, whose position corresponds to the maximum concentration of CH*. This approach allows one to overlap the experimental data with the model predictions and enables spatially-resolving flames with very steep concentration gradients [43,62–64]. The use of extremely thin capillary probes minimizes the thermal perturbation of the flame and the remaining issue is associated only with the steady-state energy balance of the radiative losses at the surface of the probe which can exceed 100 K at most for the probe surface [62–66] but is negligible in the upstream sampled region of the flame.

4 Diagnostics

Probe-induced sampling artifacts, that is, the change in concentration of stable species due to reactions occurring within the probe, can be verified to be relatively modest by repeating the measurements with probes of decreasing sizes [62]. Additionally, the effective quenching of the reactions occurring within the probe can be assessed by modeling: the most severe temperature and pressure conditions within the sampling probe result in changes in composition much smaller than the overall experimental uncertainty [62]. Although capillary sampling was proven to be the least intrusive flame sampling technique enabling the characterization of very thin flames at high pressure, detailed modeling of the effects of capillary probe effects would be still desirable.

Gas Chromatographic (GC) analyses Capillary sampling has been proven to be robust under a wide range of flame conditions [59,62,66–68] when the probe inserted into the flame is under choked flow conditions. Most commonly, the extracted gaseous samples are injected into a Gas Chromatograph Mass Spectrometer (GC-MS) system to separate and quantify the species composed of up to three-ring aromatics via quantitative calibrations based on the use of internal standards. As mentioned above, this analysis method is limited only to stable molecules since radical species recombine during sampling and analysis. However, radicals are present in flames at concentrations at least two orders of magnitude smaller than their respective stable counterparts so that their recombination does not introduce a significant bias in the quantitation of stable molecules. The major limitation of using capillary probes is their tendency to clog in the presence of soot, which restricts their use to incipiently and moderately sooting conditions (i.e., volume fractions smaller than 10
7). The limit in detecting species with more than three-ring aromatics via capillary sampling followed by GC analyses is dictated by condensation losses in the sampling system and the vanishingly small concentrations of the heaviest species of interest in addition to the sensitivity of the used GC sensors and selectivity of the GC columns. An appropriate choice of the temperature and volume of the sampling system, the GC capillary column, and the flame under investigation can extend the detection to larger PAHs but, in some cases, it may hinder the detection of equally important aliphatic species [66]. A promising application of the capillary sampling technique recently introduced for flame studies [69] consists of the use of a low-volume polyurethane foam (PUF) filter inserted into the sampling line to trap non-volatile compounds from the sampled gas before they are lost to the wall of the sampling system. After the sampling, the PUF is processed using an accelerated solvent extractor to disperse/ solubilize the captured materials in a solvent (e.g., dichloromethane). The solution can then be concentrated by rotary evaporation and injected into a GC/MS system for quantitative analysis. By collecting samples over times of the order of 1 h, one can quantify species at concentrations of the order of 1 ppb [69], with the necessary spatial resolution as long as flame stability and probe clogging are not problematic. Because of the concentration via rotary evaporation, this method is only able to

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quantify non-volatile compounds with boiling temperatures larger than 410 K, in other words, aromatic species composed of at least two rings.

4.1.3 Dilution sampling and collision charging followed by high-resolution “aerosol” analyses Many challenges arise in the analysis of the smallest soot particles and their gaseous precursors by chemical analytic techniques. For example, the volatility and solubility of the gaseous species of interest decrease quickly with increasing molecular mass, so much that conventional analyses by gas and liquid chromatography may be precluded for masses above 300 Da, even without considering the problems associated unavoidably with the flame sampling and the manipulations of the sample necessary to inject the analytes in the analytical instrument [69,70]. A reasonable option to circumvent these problems is to keep the analytes in the gas/aerosol phase and apply a gentle ionization, as achieved with the diffusion charging methods routinely used for Scanning Mobility Particles Spectrometry (SMPS) or, more properly, Differential Mobility Analysis (DMA) measurements. Then, one can perform mobility and mass spectrometric analyses of aerosolized samples directly with the highest achievable instrumental sensitivity and resolution. After an exploratory application of DMA to perform extra-situ measurements of nascent soot samples collected in water [71], SMPS became the preferential tool for online measurements of the soot Size Distribution Functions (SDFs), thanks to the pioneering work of Wang [72,73] and Maricq [74,75] who adapted a dilutionsampling method [76] to slightly sooting conditions. The large number of studies that followed [77–82] provided some systematic but perhaps counterintuitive evidence of the size bimodality of incipient soot. Some DMA studies evidenced qualitatively also the existence of soot particles with sizes smaller than 3 nm [71,80,81], even though the data analyis did not account for artifacts resulting from questionable instrumental assumptions on the diffusion charging efficiency of the sample and the limited resolution of the used DMAs for sizes smaller than three nanometers [83,84]. Thanks to these studies, the rapid dilution probing coupled to SMPS/ DMA became the standard method for the determination of incipient soot particles’ SDFs. The probe is steadily crossed by dilution nitrogen while the flame products are sampled through a tiny orifice drilled through its wall and oriented to face the flow. Nitrogen flow rate and orifice diameter determine the applied dilution ratio which is kept constant during the measurements by controlling a slight and constant underpressure in the probe. Although smaller underpressures increase the dilution ratio, computational modeling revealed that the biases introduced by the probe intrusiveness in the flame and the diffusion losses of particles in the probe are amplified when lowering the sampling velocity [60]. An underpressure of approximately 600 Pa is recommended to minimize probe intrusiveness effects on the results while enabling the achievement of dilution ratios of several thousand with appropriately small probe orifice and large nitrogen flows. Finally, recent work of our group introduced an extremely soft-ionization method based on ion seeding in the dilution flow. The quantitation of the ionization efficiency of this method needs ad-hoc modeling of

4 Diagnostics

ion collision charging [56,83]. As a benefit, the method enables the detection of weakly bonded molecular clusters that would not survive traditional ionization methods. Consequently, it enables the size, mass, and compositional characterization of soot nuclei smaller than 2 nm while minimizing potential changes in the population to be analyzed [56,57,60,83].

High-Resolution Differential Mobility Analysis (HR-DMA) DMAs rely on a control voltage applied between two electrodes separated by a laminar sheath flow. The generated electric field separates materials charged in one polarity with a specific value (within the instrumental resolution) of the mobility diameter (i.e., a size relevant for the diffusive transport [85]) from the entire population of analytes in the sample flow entering the classfication section from the inlet slit in one of the electrodes. The resulting unipolar charged and almost mono-mobile analytes exit another slit on the opposite electrode and can be counted by a Faraday Cup (FC) electrometer [86] and/or Condensation Particle Counters [84,87]. The Size Distribution Function (SDF) of charged materials at the DMA inlet is determined upon scanning the control voltages and implementing appropriate signal inversion algorithms [83,84,88,89]. The maximum achievable instrumental resolution is limited by the laminar sheath-to-sample flow ratios achievable in the used DMA [88]. Commercial DMAs rely on resolutions much smaller than 10 [86,90] for particles smaller than 3 nm, whereas the careful aerodynamic design of dedicated researchgrade instruments enables resolutions well above 20 even for sizes as small as 1.47 nm [83]. Tandem DMA configurations consisting of two DMAs connected in series would enable the investigation of size-resolved collision growth and charging kinetics. These types of studies are relatively common in the aerosol and ion spectrometry communities but have not been implemented yet in sooting flames studies [91–93].

Atmospheric pressure intake mass spectrometry Measuring sizes, charge states, and concentrations of flame-generated molecular clusters is important but should be complemented with information about the chemical nature of the materials. A viable option to gather this information is to perform mass spectrometric analyses of the diluted and softly ionized flame samples directly with the highest achievable sensitivity and resolution. The ideal instrument to perform these types of measurements is the Atmospheric Pressure intake-Time of Flight Mass Spectrometer (APi-TOF MS) which is equipped with a system of aerodynamic and electromagnetic lenses [56,57,94] to transfer efficiently the charged sample from the atmospheric pressure in the probe to the deep vacuum necessary for MS analyses. High sensitivity is necessary because the number concentrations of the analytes should be kept low to minimize their dynamics in the probe (e.g., coagulation), whereas high resolution enables the determination of the elemental composition of increasingly heavier compounds. Ideally, the high resolution and mass accuracy of the measurements allow for the chemical characterization of the analyzed material once one assumes it contains carbon, hydrogen, oxygen, and nitrogen which are the

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only elements that are fed to the flame and, consequently, to the dilution system. The identification of the exact composition of a peak in the measured mass spectra is possible because the molecular weight of an element is not an exact integer but differs from its nominal value by a fractional mass defect that is element-specific [56,57,95]. C has exactly zero mass defect (nominal mass of 12 Da), H and N (1 and 14 Da) have positive mass defects of +0.007825 and +0.003074, respectively, whereas O and Ar (16 and 40 Da) have negative mass defects of
0.005085 and
0.037617, respectively.

4.1.4 Thermophoretic sampling Thermophoretic sampling, first introduced in the classic study of Dobbins and Megaridis in diffusion flames [96], has been applied also to incipiently sooting premixed flames to image the smallest nanoparticles by Transmission Electron Microscopy (TEM) [21,60], Atomic Force Microscopy (AFM) [20,21,97] and, more recently, the “gentler” Helium Ion Microscopy (HIM) [60,97,98]. These studies confirmed that nanoparticles smaller than 2–3 nm are involved in the early stages of soot inception [20,71,78,99]. In addition to ex-situ microscopy, mass spectrometric analysis of desorbed compounds is another diagnostic option that reveals which large aromatics are embedded in the structure of the sampled soot particles [100]. Thermophoretic sampling is routinely performed under the assumption that the population of particles and sorbed species collected on the substrate is representative of the aerosolized materials present in the flame. This hypothesis is questioned rarely, even though conditions for sampling-independent results are difficult to achieve [60]. Indeed two conflicting requirements should be satisfied. On the one hand, the collecting substrate should stay sufficiently cold during sampling to maximize the thermophoretic velocity driving the particle deposition and allowing for short sampling times and the minimization of the surface rearrangement growth of soot particles. In this case, physical condensation of heavier species such as aromatics may play a role in biasing the process, which depends not only on the concentration of these condensable species that is typically quite low, especially under incipient sooting conditions, but also on the kinetically favored heterogeneous condensation on either the substrate itself or soot nanoparticles acting as condensation nuclei. On the other hand, the substrate should be sufficiently small and hot (i.e., as close as possible to the local temperature) to minimize the perturbation to the flame and allow for the necessary spatial resolution. In such a case, though, one should guard against chemical kinetics affecting the adsorption and rearrangements of deposited atoms/molecules on the surface. There may be also a modifications of the sample population during the unavoidable transit time of the sample across the perturbed thermal boundary layer surrounding the substrate. Using different sampling times, substrate sizes, orientations, and/or shapes may help identify substrate sampling biases before unleashing any in-depth analysis of the collected material. In our experience, thermophoretic sampling techniques are among the most challenging to be implemented when one wants to achieve sampling-independent and spatially resolved measurements of incipient soot.

4 Diagnostics

4.2 Optical diagnostics 4.2.1 Multiwavelength pyrometry Pyrometry is completely non-intrusive, even by comparison with widely used laser diagnostics, and can provide spatially resolved measurements in either onedimensional or axisymmetric geometries. The traditional application of pyrometry is to measure emission through narrow-band interference filters and determine iteratively an object temperature [101], but it can also be used to measure the soot concentration (volume fraction) in a flame [102]. Kuhn et al. [103] demonstrated that consumer-grade digital cameras with a color filter array are capable of being used as a cost-effective detector even though each color filter is relatively broad. A single image of a sooting flame provides simultaneous measurements of the soot luminosity with three detectors (the red, green, and blue color channels). If the emissivity of the object is known, the three measured light color intensities can provide the value and the uncertainty of the soot temperature through their ratios and of the soot volume fraction through their absolute values. The emissivity of soot, ε(λ) is expected to follow a power-law dependence on wavelength, ε(λ)  λ
α, where α is the dispersion exponent or Angstrom coefficient. The dispersion exponent is far from constant in flames, especially under incipiently sooting conditions [59,104,105] and this variability can induce large uncertainties in pyrometric temperature measurements. An alternative approach is to use an independently validated temperature measurement to infer the dispersion exponent in the investigated flames under the assumption of particle thermal equilibrium with the gas phase [59]. The dispersion exponent is not only an important optical parameter but also provides a measure of the soot H/C and, consequently, age [106] so that α can be used to track changes in the composition of soot. The direct measurement of α can improve the accuracy of laser diagnostics such as Laser-Induced Incandescence (LII), whose results are interpreted based on estimates of the soot absorption and emissivity at the relevant excitation and detection wavelengths [107,108]. While pyrometry assumes that the flames are optically thin, which is valid only for lightly or moderately sooting flames, heavy sooting flames can still be investigated after accounting for self-absorption iteratively [109,110]. As a result, this relatively simple non-intrusive optical technique can provide simultaneous measurements of soot volume fraction and dispersion exponent and can be used in a wide range of axisymmetric flame conditions, complementing laser-based measurements.

4.2.2 Laser Light Scattering (LLS) and Light Extinction (LE) Laser Light Scattering (LLS) is a classic optical diagnostic technique that can provide information on the average nascent soot particle sizes when it is coupled to an independent measurement of their volume fraction [111–114]. These types of measurements were pioneered in the 1970s’ by D’Alessio [112] by combining LLS and broadband LE. The Rayleigh regime applies certainly to soot nucleation when particles no larger than a few tens of nanometers are present. However, no information

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on the particle size distribution function can be extracted from elastic static light scattering measurement and one has typically to assume monodispersity in size in the interpretation of the results. The monodispersity assumption is reasonable in the early stage of soot nucleation before substantial coagulation/agglomeration occurs. One challenge in applying LLS, especially in high-pressure environments, is presented by the intrinsically steep temperature and density gradients of the flame causing steering of the laser beam which is difficult to account for in the result analysis, unless one investigates highly-controlled self-similar flames of the types discussed in Section 5. Broadband/multiwavelength light extinction measurements in either onedimensional or axisymmetric geometries not only allow the determination of the soot volume fraction with an estimate of the particle refractive index but also a direct measurement of α [104] or the nanoparticle optical band gap. The concurrent application of different optical diagnostics enables the estimate of the particle optical properties at different wavelengths (e.g., Ref. [115]) whose values are relevant not only to track soot evolution with laser diagnostics but also because they affect radiative heat transfer in practical devices.

4.2.3 Laser-Induced Incandescence (LII) Laser-Induced Incandescence (LII) uses a pulsed laser to heat the absorbing nanoparticles and relies on the detection of the resulting thermal radiation emission. The detected LII signal can be correlated to particle volume fraction via LE calibration [37,116–118]. Temporal tracking of the particle transient cooling provides information on the primary particle size in agglomerates via modeling. Schulz et al. studied the factors that influence LII signals by comparing 9 models in 12 case studies, including 2 excitation wavelengths and 2 laser fluences [119]. The review of Michelsen et al. discusses fundamentals and numerous applications in various fields [120]. However, the application of LII to soot nucleation is very limited, with the singular exception of [121] which leverages a calibration performed by cavity ringdown extinction under conditions of very low soot volume fractions. Indeed the smallest nascent soot particles are vaporized easily under laser irradiation that would bring them to the high temperatures necessary to measure appreciable LII signal. On the contrary, LII is the optical diagnostic of choice for tracking the later stages of soot evolution and in turbulent flames because of its ability to perform two-dimensional instantaneous measurements. We will not discuss LII in further details since it has been a diagnostic of limited applicability to the scope of the present review.

5. Flame selection criteria Soot formation is a highly temperature-sensitive process since it is initiated by the high activation energy chemistry of its precursors. Thus, good control of the temperature field is desirable, as recognized in several earlier studies [122,123]. The tuning

5 Flame selection criteria

of the maximum flame temperature can be implemented by changing the dilution level of the fuel and/or using different inert gases as diluents [122–125]. These traditional approaches modify not only the maximum temperature but also the local stoichiometry. Residence time is just as important as temperature and a proper comparison among different flame conditions should be performed under wellcharacterized and approximately constant normalized temperature-time histories [43,62]. Therefore, one must consider not only changes in peak flame temperature but also the spatial temperature profile when investigating the effect of temperature on soot nucleation and growth. Pressure is another variable that plays a significant role in the formation of soot: most practical combustion applications occur at high pressures with soot formation being exacerbated under these conditions. Experiments at high pressures tend to require complex apparatuses and pose major challenges in terms of flame stability, accessibility and spatial resolution. As a result, most traditional studies on soot nucleation have been performed at atmospheric pressure, or at sub-atmospheric pressure to achieve acceptable spatial resolution [50,126].

5.1 Burner-stabilized flat premixed flames Although soot emissions are a challenge mostly in non-premixed combustion systems, local fuel-rich (partially) premixed conditions are common under turbulent conditions in many combustion systems and contribute significantly to soot formation (e.g., Ref. [39]). Additionally, diffusion flame configurations investigated routinely in research laboratories (i.e., co-flow and counterflow) limit the maximum reactant residence times and the use of relatively intrusive sampling methods, both of which are necessary if one is interested in unraveling the mechanisms of particle nucleation in incipiently sooting conditions. Fuel-rich (atmospheric pressure) premixed flames offer the most convenient conditions to perform detailed mechanistic studies on soot inception because of the easy access to the soot-laden post-flame region with mild spatial gradients. To date, the necessary spatial resolution to follow the evolution of the size distribution of incipient soot in a flame environment was achieved only in premixed flames [59,77,83]. The simplest burner to stabilize such flames consists of a honeycomb or porous medium which uniformizes the velocity profile in the feed stream and acts as a flame arrestor. The resulting flame is flat, stable, and essentially one-dimensional with all variables changing in the streamwise direction, normal to the reaction zone. The soot load can be dialed by adjusting the stoichiometry (i.e., the C/O ratio) and/or dilution of the reactants which affects the flame maximum temperature through diffusive heat and radical mass losses to the burner surface. The effect of cooling of the flame products on soot formation, causing secondary particle nucleation, can also be investigated by impinging the flow of the premixed flame products against either a cold stabilization plate [59,60,77] or a counterflowing stream of inert gas.

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CHAPTER 2 Soot research: Relevance and priorities by mid-century

5.2 Laminar diffusion flames Experimental work on soot inception in diffusion flames is far less comprehensive compared to that in premixed flames. A study dating back to the 1980s was performed using a slot burner by Smyth et al. [127]: taking advantage of the ease of access of the two-dimensional flame configuration, the authors simultaneously probed the gas phase using mass spectrometry and the particle phase using optical diagnostics but presented no measurements of either PAHs or incipient soot nanoparticles. Building on the introduction of the thermophoretic sampling technique, Dobbins’s group provided the first chemical characterization of soot nanoparticles extracted from an axisymmetric coflowing diffusion flame and also made a distinction between two classes of particles (incipient and mature soot) based on their degree of transparency under the TEM electron beam [128]. Unfortunately, the results did not have good spatial resolution and did not include data on the complex flame structure in terms of gaseous species to follow the conversion from gas to particles. From a chemical characterization perspective, the review of McEnally et al. [15] provides a useful entry to the speciation of soot precursors in the gas phase in coannular diffusion flames. More recently, attempts to adapt traditional dilution sampling approaches to perform size (DMA) and speciation (MS) measurements of nascent soot along the axis of co-annular diffusion flames have been reported in the literature [74,75,129], but the studies not only did not have the necessary spatial resolution to resolve the structure of the flame but also faced all the problems of traditional DMA techniques mentioned in the previous section. D’Anna and coworkers examined counterflow diffusion flames with the necessary spatial resolution using UV-visible spectroscopy. They managed to distinguish between mature soot particles that emit broadband light from nanometric organic carbon (incipient soot) that is transparent to visible light and selectively detected in the UV [130]. Unfortunately, their results are only qualitative. Measurements of both gas phase and soot in a single diffusion flame remain relatively rare [59,69,131] and the current databases are often limited to species composed of two-ring aromatics or smaller. This deficiency is largely motivated by the incompatibility of diagnostics since the application of analytical chemistry tools for a proper chemical characterization requires gas sampling from flames using microprobes that invariably tend to clog in the presence of soot. There have been ingenious approaches to prevent it [131], but usually at the cost of using bulky probes and losing spatial resolution. Despite some recent progress in elucidating the soot inception process, as reviewed in Refs. [21,31], there is still a substantial gap in its understanding. Addressing such a gap requires quantitative diagnostics, adequate spatial resolution, and, inevitably, a light sooting load in highly controlled environments [44,62,63,132]. With respect to the effect of pressure, co-flow diffusion flames have been stabilized up to 100 atm [36], with flame height relatively independent of pressure at fixed volumetric fuel flow rates. This observation implies that pressure effects on soot

5 Flame selection criteria

formation can be investigated by comparing soot measurements at the same height above the nozzle at an approximately fixed residence time in the flame, independently of pressure. However, a strong role of buoyancy in co-flow flames induces instabilities when the flames are sufficiently tall [133]. As a result, short flames are required, which leads to additional challenges in maintaining well-defined boundary conditions with no heat nor species losses to the burner [134,135]. For such a reason, experiments on high-pressure flames are becoming increasingly more common using a counterflow configuration [62,64,136–138], even though it remains a challenge to isolate the effect of pressure and preserve incipiently sooting conditions at the same time.

5.2.1 The self-similar counterflow diffusion flames An exceptional control can be achieved in counterflow diffusion flames if one keeps constant their stoichiometric mixture fraction Zst ¼ (1 + sYFF/YOO)
1 and global strain rate, a ¼ (VF + VO)/L, where L is the separation between fuel and oxidizer nozzles, s the mass-based stoichiometric coefficient, and YOO and YFF, are the mass fraction of oxygen in the oxidizer stream and fuel in the fuel stream whose average velocities are VO and VF, respectively. The approach enables comparisons well beyond those of similar studies on either temperature [122,123] or pressure effects on soot [133,139,140] because it freezes the normalized temperature and composition time history experienced by the flame products, as highlighted in Fig. 1. The figure presents experimental and computed profiles of temperature and two critical soot precursors, C2H2 and C6H6, all normalized by their peak values, for three flames at pressures of 1, 4, and 8 atm. The left panel shows these normalized variable as a function of a scaled coordinate: to account for changes in diffusivity and, in turn, in the diffusive layer thickness, δ, as the pressure, P, is increased, the axial position is rescaled in the bottom abscissa as z δ0/δ, with δ0 being a reference value, at atmospheric pressure. The thicknesses ratio is determined from simple scaling considerations by neglecting small (less than 20%) changes in diffusivity, D, due to pffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffi temperature changes, as δ=δ0 ¼ D=a= D0 =a0  P0  a0 = P  a with a0 being the reference strain rate at P0 [63]. Fig. 1 shows that all flames are remarkably self-similar with respect to temperature and gaseous species, once the peak values are chosen for normalization, regardless of the considered large range of conditions. As a result, the interpretation of the pressure effects on soot formation and its precursors is significantly simplified. The advantage of the self-similarity is that the flame temperature and pressure can be adjusted as independent parameters to control the soot chemistry and load. A consequence of maintaining constant the normalized temperature- and concentration-time history as pressure is raised is an increase in mass flow rate, which, in turn, increases the total carbon available for conversion to soot. However, by approximating the diffusive flux into the reaction zone as pffiffiffiffiffiffiffiffiffi j00F ¼
ρDrY F 
ρD YδF ∝ P  a , one can estimate easily the changes in the amount of carbon available for conversion to soot at different pressures [64,141].

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CHAPTER 2 Soot research: Relevance and priorities by mid-century

FIG. 1 (Left) Comparison of computed (lines) and experimental (symbols) profiles of C2H2, C6H6, and temperature normalized with their peak values for three flames at pressures of 1, 4, and 8 atm versus a rescaled axial coordinate that accounts for changes in diffusivity with pressure (see text). (Right) Same normalized variables as in the left panel versus the convective residence time computed from the first location where the temperature rises on either side of the flame; the break in the abscissa is due to the divergence of residence time at the GSP. The orange bands in the two panels show the region where soot forms. Adapted from K. Gleason, F. Carbone, A. Gomez, Pressure and temperature dependence of soot in highly controlled counterflow ethylene diffusion flames, Proc. Combust. Inst. 37 (2) (2019) 2057–2064 with permission of Elsevier.

When interpreting results, one should bear in mind how the selected value of the mixture fraction Zst dictates where the flame is positioned relative to the gas stagnation plane. The flame is positioned on the oxidizer side of the stagnation plane, as shown in Fig. 1, when Zst is chosen to be 0.5. In either case, soot is formed in the fuelrich zone before being convected away radially at the stagnation plane, but it undergoes oxidation at the flame front when Zst > 0.5 whereas it can only pyrolyze in absence of oxygen when Zst < 0.5. The constancy of Zst when comparing flames ensures that the relative position of flame and stagnation plane is unchanged in the non-dimensional space of Fig. 1. Perturbing Tmax with this restriction via the adjustment of the dilution of the fuel and oxidizer streams, is very useful to isolate the pressure and temperature effects on the slow chemistry of soot inception [35,141,142]. Indeed, the normalized temperature-convective time history remains also nearly constant, as also shown in Fig. 1 using the right ordinate and the top abscissa, and further discussed in Refs. [35,43]. Therefore, in addition to pressure, Tmax is isolated as the other key controlling parameter, as desirable in the kinetically limited processes leading to soot.

6 Exemplars of tracking soot nucleation in flames

The conclusion is that, by operating at a constant stoichiometric mixture fraction and nominal strain rate through a careful selection of the feed stream composition and flow rates, one can achieve an unprecedented level of control over the flames with constant normalized temperature- and composition-diffusive and convective times history. Thus, the task of deconvolving temperature and pressure effects on soot formation is significantly simplified.

6. Exemplars of tracking soot nucleation in flames

6.1 Counterflow diffusion flame under incipiently sooting conditions Fig. 2A shows a picture of a typical incipiently sooting counterflow diffusion flame rotated 90 degrees to match the abscissa of the other panels. Panels B and C show profiles of a subset of species and temperature with symbols and continuous lines representing experimental data and the results of a model described in Ref. [143], respectively, with calculations performed using the OPPDIF code in CHEMKIN [144]. The capillary sampling technique can resolve steep gradients and provides a resolution on the order of 100 μm or finer, depending on the choice of capillary probe diameter [62]. Resolving the steep concentration gradients p atffiffiffiffiffiffiffiffi high ffi pressures requires scaling the probe diameter with the diffusive length δ∝ 1= P  a, with inner diameters on the order of 10 μm for flames above 25 atm [62,64]. Panel D results from a combination of pyrometry and LLS yielding soot particles volume fraction, fv, dispersion exponent, and the average particle diameter, d, which determines the reported number density with the monodisperse approximation as N s ¼ π6fdv3 . The data in Fig. 2 can be further manipulated to yield the soot production rate and dimerization rate of various PAHs to follow the molecular growth process in unprecedented detail. To determine the first, we followed a hybrid approach relying partly on experimental data, partly on computational results from a model that had been well-validated using our experimental species and temperature data. Specifically, the soot production rate is recovered from the governing equation for the number concentration Ns of soot particles along the axis, z, of the axis-symmetric flow field through ∂N S  ∂N S  d d Vr d d + ðN s  V th Þ + ðN s  V P Þ: ¼ ðN s  V z Þ + N s  
 ∂t nucl ∂t coag dz dr dz dz

(1)

The first term on the LHS of Eq. (1) is the number concentration production rate from the gas phase (i.e., nucleation rate) and the second term is the destruction rate due to coagulation of particles, ∂N∂tS jcoag ¼ γ coag 12 K coll N 2s , with Kcoll as collision kernel and γ coag as coagulation efficiency (the probability that two particles stick together during their collision) [20,145]. The four terms on the RHS are the two convective terms, the thermophoretic contribution due to particle drift down a temperature gradient and the diffusive term due to the particle Brownian motion, respectively [146,147]. Vz, Vr, Vth and VP are the axial velocity component, the radial velocity component, the thermophoretic velocity, and the particle Brownian velocity, respectively. In this equation Ns is experimentally determined under the assumption of particle

43

B) 1E19

2100

D) 1E14

O2

1200

CO2

900 1E17 600

CO

C2H2

1E13

1E12

1E11

300

GSP

1E16

0 -3

-2

-1

0

1

2

axial position (mm)

3

1E-8 1E13

1E-9 1E12

3

9

2

1E10 -3

-2

-1

0

1

2

axial position (mm)

3

6 1 3 0 -0.5

0.0

0.5

diameter (nm)

Temperature (K)

1E18

1E14

disperion exponent

Temperature

1500

number concentration (cm-3)

1800

1E-7

Flame

soot volume fraction

C2H4

C) 1E15

number concentration (cm-3)

A)

0 1.0

axial position (mm)

FIG. 2 (A) Photograph of the counterflow diffusion flame after 90 degree clokwise rotation. Also marked is the gas stagnation plane at the interface of the two streams. (B) Spatial profiles of temperature and major species. (C) Spatial profiles of select aromatic soot precursors. (D) Soot characterization in terms of volume fraction, number concentration, particle size, and dispersion exponent. Adapted from K. Gleason, F. Carbone, A.J. Sumner, B.D. Drollette, D.L. Plata, A. Gomez, Small aromatic hydrocarbons control the onset of soot nucleation, Combust. Flame 223 (2021) 398–406 with permission of Elsevier.

6 Exemplars of tracking soot nucleation in flames

monodispersity, whereas the velocity terms are extracted from the computational model, along with kinematic gas viscosity, ν, density, ρ, and temperature, T, in view of the excellent agreement between experiments and computed variables (see Fig. 2B). To estimate the aromatics dimerization rate, we considered the self-collision rate from the gas kinetic theory according to ω_ DIM ¼ η

rffiffiffiffiffiffiffiffiffiffiffiffiffi 4πkB T 2 ∗  ∗  2 σ Ω T N a ½PAH2 , MPAH

(2)

where η, kB, Na, MPAH, σ, Ω∗(T∗) are the dimerization efficiency, Boltzmann constant, the Avogadro number, the mass, the collision diameter, and the reduced collision integral [148] of the PAH in question. ω_ DIM represents the number of dimers generated per unit volume and time from the self-collisions of the considered PAH at concentration [PAH]. The self-collision production rate is estimated by interpolating the experimental measurements of [PAH] and assumes a high probability of dimerization with η ¼ 0.01. Of course, Eq. (2) can be generalized beyond self-collision to the collision of any two aromatics. As shown in Fig. 3, only aromatics containing one or two rings exhibit dimerization rates comparable to the nucleation rate of soot inferred from the experimental results, whereas the dimerization rates of large 4–6-ring PAHs are too low to account for the formation of the detected soot particles. Moreover, the dimerization of larger PAHs would have had to be irreversible for the rates to be adequately high [149–151]. It appears that the rate-limiting step in the sequence that ultimately controls the nucleation rate is the formation of either single-ring aromatic compounds or at most two-ring aromatic molecules. The main findings associated with Fig. 3 are valid also in diffusion flames at moderate pressures, as detailed in Ref. [142]. The results of Fig. 3 pose a major question: if small aromatic compounds control the soot nucleation rate, how can one reconcile the presence of PAHs of several hundred Da in the ordered stacks and disordered clusters that constitute soot nanoparticles, as revealed by several studies [19,21,100,152,153]? A plausible explanation is that large PAHs are short-lived intermediates that do not affect the onset of nucleation but are rapidly adsorbed on the metastable dimers of smaller aromatics, promoting their stabilization and growth. Under this hypothesis, the concentration of large PAHs is small as a consequence of a steady-state condition between their formation from smaller species in the gas phase and their consumption due to adsorption on existing dimers of smaller aromatics. Mechanistically, the absorption of large peri-condensed PAHs may provide the necessary resonance stabilization that prevents the fragmentation of the dimers and may explain the presence of large PAHs observed in some analyses of soot nanoparticles. Since this hypothesis cannot be further tested with optical diagnostics, the detailed kinetics of these mechanisms remain unclear. Considering the long-standing hypothesis that chemical bond-building and clustering of relatively large aromatic systems such as pyrene trigger incipient soot [20,21,32,154,155], the finding that only small aromatic structures could support early soot formation rates from non-aromatic fuels is noteworthy.

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CHAPTER 2 Soot research: Relevance and priorities by mid-century

1E+18 1E+17

production rate (cm-3s-1)

46

1E+16

Soot 1E+15 1E+14 1E+13 1E+12 1E+11 1E+10 -1.0

Flame -0.5

0.0

0.5

1.0

axial position (mm) FIG. 3 Profiles of soot nucleation rate calculated under the hypothesis of monodisperse size in an atmospheric pressure counterflow diffusion flame: the shaded area is bracketed by assuming a coagulation efficiency of either 2% for the lower bound or 100% for the upper bound. The profiles of dimerization rate (colored lines) of several PAHs via kinetic theory of self-collisions and a representative benzene-toluene clustering (turquoise line) are calculated by assuming 1% collision efficiency. Adapted from K. Gleason, F. Carbone, A.J. Sumner, B.D. Drollette, D.L. Plata, A. Gomez, Small aromatic hydrocarbons control the onset of soot nucleation, Combust. Flame 223 (2021) 398–406 with permission of Elsevier.

The corollary of this finding is that good predictions of the chemical pathway from parent fuel to the formation of single- and double-ringed aromatic structures, as well as acetylene, may be sufficient to enable the modeling of soot inception rates in flames fueled by aliphatic fuels.

6.2 Filling the gaps in nucleation in premixed flames The same techniques that were applied to counterflow diffusion flames are applicable to a premixed flame. However, measuring quantitatively only stable hydrocarbon species composed of up to six aromatic rings (i.e., lighter than 300 Da) and particle average diameters no smaller than two nanometers provides only a partial picture. Making further progress requires the comprehensive characterizations of the distributions of masses, size, elementary charge state, and chemical (including radical) functionalities of the products of slightly sooting flames with the spatial resolution

6 Exemplars of tracking soot nucleation in flames

necessary to track the evolution of these distributions. This, in turn, requires the use of relatively intrusive sampling methods to keep the flame products in the gas/aerosol phase and transport them to the analysis device, while minimizing sample manipulations and interactions among different components of the analyte population and/ or with the wall of the sampling system. A premixed flame with a mild gradient is ideal for these types of studies. A photograph of a well-characterized atmospheric pressure premixed flame of ethylene and air with a C/O ¼ 0.69 is shown in Fig. 4, rotated 90 degrees clockwise to match the abscissa of the other panels. The flat premixed flame is stabilized on a honeycomb burner with soot luminosity detected in the hot flame products at Heights Above the Burner (HAB) larger than approximately 5 mm. The luminous zone also highlights the flame necking caused by buoyancy. Panel B of Fig. 4 includes the axial profiles of temperature and selected species. The premixed flame has a maximum temperature of 1680 K that is nearly constant up to 20 mm HAB; also the concentrations of major combustion products (i.e., CO, CO2, and C2H2) vary mildly in that region, whereas the flame reactants (C2H4 and O2) are consumed in the first 5 mm above the burner. Panel C shows the axial profiles of the number concentration of aromatic species from capillary sampling followed by GC/MS analysis, and of soot particles from a combination of results using DMA and optical diagnostics. Most aromatics increase in concentration up to HAB  7.5 mm, eventually plateauing much like the major combustion products in Panel B. Particles and/or molecular clusters larger than 1 nm are present early in the flame (at HAB between 2.5 and 7.5 mm) at a number concentration of 1012 cm
3 which is comparable in the soot inception region of the flame (i.e., HAB < 7.5 mm) to that of aromatics composed of two-ring aromatics and larger than that of three-ring compounds, with larger aromatics expected to be at even smaller concentrations. Panel D of Fig. 4 compares the soot volume fraction, particle diameter, number concentration, and dispersion index (α), inferred from a combination of optical techniques (i.e., pyrometry [59] and LLS) and dilution sampling-based High-Resolution DMA (HR-DMA) [60] and APi-TOF measurements [56,57]. Below HAB ¼ 10 mm, the light scattered by particles is indistinguishable from that due to the gases so that only the dispersion exponent and soot volume fraction are accessible via optical diagnostics. The comparison includes the H/C ratio inferred from APi-TOF measurements [56] which correlates with α (i.e., α  6H/C). Dilution sampling and optical diagnostics provide results that agree very well within the result uncertainty. Furthermore, the dilution sampling techniques provide a detailed characterization of the soot nuclei population, including their size distribution functions and their elemental composition, which may shed some light on the nucleation step, as further discussed below. The comparison also highlights that nucleation occurs at HAB below 7.5 mm above which the number concentration of the measured particles decreases substantially because of the expected prevalence of particle growth via coagulation. Notice that materials detected at HAB between 5 mm and 7.5 mm are not gaseous compounds since the flame has the characteristic broadband visible thermal luminosity of particles measured via pyrometry. To shed further light on the smallest

47

B u r ne r

Temperature (K)

1500 1E18

CO 1200

CO2

900

C2H2

600

1E17

number concentration (cm-3)

Temperature

number concentration (cm-3)

1800

D)

1E15

1E19

1E14

1E13

C2H4

1E12

1E-8

1E11

1E-9

20

Optical Diagnostics Sampling Diagnostics

1E10

15 10

0.5 5

Soot

O2 0

1E16 5

1E-7

1.0

1E12

300

0

1E13

10

15

height above burner (mm)

0.0

1E11 0

5

10

15

height above burner (mm)

soot volume fraction

C)

2100

diameter (nm)

B)

H/C, α/6

A)

0 0

5

10

15

height above burner (mm)

FIG. 4 (A) Photograph of the ethylene-air atmospheric pressure burner stabilized premixed flame with C/O ¼ 0.69 after 90 degree clockwise rotation. (B) Spatial profiles of temperature and major species. (C) Spatial profiles of select aromatic soot precursors and soot number density estimated in the monodisperse size approximation. (D) Soot characterization in terms of volume fraction, number concentration, particle size, and dispersion exponent overlapping the results of optical techniques and DMA via dilution sampling. Data reprocessed from F. Carbone, M.R. Canagaratna, A.T. Lambe, J.T. Jayne, D.R. Worsnop, A. Gomez, Detection of weakly bound clusters in incipiently sooting flames via ion seeded dilution and collision charging for (APi-TOF) mass spectrometry analysis, Fuel 289 (2021) 119820; F. Carbone, M.R. Canagaratna, A.T. Lambe, J.T. Jayne, D.R. Worsnop, A. Gomez, Exploratory analysis of a sooting premixed flame via on-line high resolution (APi-TOF) mass spectrometry, Proc. Combust. Inst. 37 (1) (2019) 919–926; F. Carbone, K. Gleason, A. Gomez, Probing gas-to-particle transition in a moderately sooting atmospheric pressure ethylene/air laminar premixed flame. Part I: gas phase and soot ensemble characterization, Combust. Flame 181 (2017) 315–328; F. Carbone, S. Moslih, A. Gomez, Probing gas-to-particle transition in a moderately sooting atmospheric pressure ethylene/air laminar premixed flame. Part II: molecular clusters and nascent soot particle size distributions, Combust. Flame 181 (2017) 329–341.

6 Exemplars of tracking soot nucleation in flames

Natural Positive Charge

Mass defect

0.8

C/

H

=1

6.5

HAB=2.5mm

0.6

C/ = 2 H

0.4 H

=3 4.5 4 3.5

0

100

200

300

400

500

600

700

800

900

1000

Natural Positive Charge

0.8

1100 C/

H

1200

1300

1500 6.5

HAB=5.0mm

0.6

1400

=1 C/ = 2 H

0.4

6 5.5 5

C/

0.2

H

=3 4.5

0 -0.2

4 3.5 0

100

200

300

400

500

600

700

800

900

1000

Natural Positive Charge

0.8

1100 C/

H

1200

1300

1500 6.5

HAB=7.5mm

0.6

1400

=1 C/ = 2 H

Log10{d(N)/d[ln(m/z)]}, cm–3

-0.2

Mass defect

5.5 5

C/

0.2 0

Mass defect

6

6 5.5

0.4 5 C/

0.2

H

=3 4.5

0

4 3.5

-0.2 0

100

200

300

400

D≈1.0nm

500

600

700

800

900

mass/charge, Th

1000

1100

1200

1300

1400

1500

D≈1.5nm

FIG. 5 Mass defect plots visualizing the overall chemical composition of flame products naturally charged in positive polarity at HAB of 2.5, 5.0, and 7.5 mm (top to bottom). Lines depict singly charged hydrocarbons with increasing C/H ratio and oxygenated carbon with a C/O ratio of three. Adapted from F. Carbone, M.R. Canagaratna, A.T. Lambe, J.T. Jayne, D.R. Worsnop, A. Gomez, Exploratory analysis of a sooting premixed flame via on-line high resolution (APi-TOF) mass spectrometry, Proc. Combust. Inst. 37 (1) (2019) 919–926 with permission of Elsevier.

“particles” detected by HR-DMA at HAB between 2.5 and 7.5 mm, Fig. 5 summarizes the results of APi-TOF analyses of flame products naturally charged in positive polarity. Similar results can be shown for the flame neutral products which have been characterized with APi-TOF after implementing a soft ion collision ionization [56]. Results at HAB ¼ 2.5, 5, and 7.5 mm are presented from top to bottom in terms of mass defect plots. The latter sorts the results in two dimensions not only as a function of the mass/charge of the analytes but also of their mass defect (difference from integer value) in the y-axis, while their concentrations are identified by a color scale. In a mass defect plot, materials with constant C/H/O ratios but with increasing total mass/ charge (e.g., homomolecular clusters) lie on straight lines whose slope is determined by the elemental composition. Three lines representative of hydrocarbons with C/H equal to 1, 2, and 3 are shown in the figure to provide visual identification of the overall composition of detected materials. At HAB ¼ 2.5 mm, “particles” are first detected with mass up to 300 Da and high hydrogen content.

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Many of the high peaks (dark red spots) are localized in the proximity of the line representative of C/H ¼ 1 which is typical of the one- and two-ring aromatics identified via GC but whose mass is at most 152 Da (i.e., Acenaphthylene). One could speculate that such small PAHs coalesce into relatively heavier dimers that act as “particle growth nuclei.” Such nuclei appear to grow to masses up to 550 Da and average C/H  1.4 while being convected from HAB ¼ 2.5 mm to HAB ¼ 5 mm. The growth seems to occur by uptaking/condensation of the available larger PAHs since most of the detected peaks are still characterized by C/H < 2 but the ones at masses smaller than 300 Da are still characterized by C/H  1. Data analysis does not allow yet to estimate to what extent surface reactions (e.g., via the HACA mechanism) contribute to the “molecular” growth and stabilization of “particle growth nuclei.” One would expect the dimers to evaporate at the flame temperatures but, instead, they grow and are converted to “particle growth nuclei” which emit visible broadband thermal luminosity at HAB  5 mm. At HAB ¼ 7.5 mm the mass spectra become multimodal with the three equispaced “modes” roughly lining up along the C/H ¼ 2 line. The lining up of the modes indicates that physical clustering (i.e., coagulation) of “particle growth nuclei” becomes active at this position in the flame consistently with the results in Fig. 4.

7. Computational modeling The emphasis up to this point was strictly on experimental approaches with demonstrative results. To appreciate the role that computational modeling plays and its synergy with experimental work, we devote this short section to the topic. Modeling of one-dimensional laminar flames is seemingly trivial from a fluid dynamic viewpoint precisely because such flames are laminar and one-dimensional. Commercial and open-source software such as CHEMKIN Pro is ideal for the purpose [156], combined with various detailed chemical kinetic mechanisms of the reactants-to-products conversion. For simple fuels, these kinetic models are well established and have been extensively validated for different stoichiometries and compositions of the feed streams. Only some subsets of the literature mechanisms have as an additional focus molecular growth eventually leading to soot [143,157–160], which is very relevant to the scope of this chapter. The extensive database developed with the diagnostic tools discussed in Section 4 can help refine key aspects of this growth chemistry for subsequent incorporation in more complex (e.g., multidimensional and eventually turbulent) computational models. But the coupling of experiments and models goes beyond the goal of model validation and we would be remiss not to acknowledge that modeling lends credibility to key aspects of the experimental approach. For example, without the progress in computational work in the past several decades, there would have been considerable doubt that the perturbation of capillary sampling in counterflow flames could be accounted for to retain accuracy and spatial resolution, especially so at high pressures when the entire flame structure width is less than 0.5 mm and flame dragging due to

8 Summary and research needs in the next few decades

probe intrusiveness can be significant [62,64]. In another example, the use of computational modeling was critical to demonstrate and take advantage of the selfsimilar flame structure as illustrated in Fig. 1. If partial validation of a chemistry model with respect to temperature, major species, and some critical soot intermediates such as benzene and pyrene is offered by the type of data shown in Fig. 2, any modest departures from the validated boundary conditions, such as changes in dilution to control the maximum flame temperature, would only marginally affect the accuracy of the model with respect to chemical speciation and one can broaden the experimental testing conditions to explore flames with a moderate soot loading while relying on partially validated model predictions of gaseous precursors, as implemented in recent work [35,141]. Yet another example of the coupling and complementary use of experiments and modeling is the determination of the soot production rate in Fig. 3. As a result, there is a real synergy between experiment and model. Importantly, with a variety of software packages that are easily accessible to the experimentalist, modeling of simple flames, as those discussed in this review, has become a commodity and a careful experimentalist can iterate between the experiments and modeling singlehandedly without a specialized computational background.

8. Summary and research needs in the next few decades The need for sustained soot research in the next few decades is self-evident since (a) fossil fuels will remain the dominant source of energy for decades, (b) soot is not only a byproduct of combustion in power generation but is produced naturally in forest fires, whose frequency and intensity is increasing as a result of global warming, (c) health effects of soot inhalation remain severe, with the reported increased toxicity of nanosized materials and sorbed toxic compounds, and (d) there is a need to synthesize new carbon-containing nanostructured materials for all sort of energy related and unrelated applications. Nucleation, that is the transition from the gas phase to the particle phase, remains the most challenging aspect of soot research for a fundamental understanding of the physicochemical processes underlying the formation of soot. Decoupling these complex processes from fluid dynamic complications requires persisting in the study of laminar flames that retain the coupling of chemistry and transport but sidestep the complications of turbulence. Progress in the study of nucleation will require a synergistic approach, with the complementary use of multiple diagnostics and computational modeling for the comprehensive characterizations of the distributions of mass, size, morphology, elementary charge state, and chemical (including radical) functionalities of precursors and soot from incipiently sooting flames, with the necessary spatial resolution to track the evolution of these distributions within the flame. The desired type of information requires the use of relatively intrusive sampling methods to keep the flame products in the gas/aerosol phase and transport them to the analysis device. Flame sampling in

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the gas/aerosol phase is affected by three problems: (i) perturbation of the flame with hard-to-quantify effects on the flame products; (ii) modifications of the sample introduced during its transfer from the flame to the analyzer; (iii) bias in the analysis because of the need to ionize/charge the analyte in a predictable, non-destructive, and non-perturbative manner. Mitigation and, quantification of these problems need more research, especially since the minimization of any of these problems results in conflicting requirements for the others. Additional goals regard the adaptation of intrusive diagnostic methods to flames with sharp gradients while retaining adequate spatial resolution and applying them to multidimensional laminar flames. Unless new nonintrusive but quantitative and detailed diagnostics are developed, efforts should be invested in minimizing and quantifying perturbations that are introduced by the insertion of even miniaturized probes into flames. The quantification of the effects requires (multidimensional) models of the coupled flame, probe, and ionization systems which consider the flow from an unperturbed location in the flame to the detector, to quantify the effects of both flame perturbations and sample transport, manipulation, and/or storage before analysis.

Acknowledgments F.C. acknowledges the support of the National Science Foundation (Grant #CBET-2013382, Prof. John Daily, Program Manager). K.G. and A.G. acknowledge the support of the National Science Foundation (CBET-1853150, Prof. John Daily, Program Manager).

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of the size of the incandescent incipient soot particles in premixed sooting and nucleation flames of n-butane using LII, HIM, and 1 nm-SMPS, Aerosol Sci. Technol. 51 (8) (2017) 916–935. A. D’Alessio, A.C. Barone, R. Cau, A. D’Anna, P. Minutolo, Surface deposition and coagulation efficiency of combustion generated nanoparticles in the size range from 1 to 10 nm, Proc. Combust. Inst. 30 (2) (2005) 2595–2603. R.S. Jacobson, A.R. Korte, A. Vertes, J.H. Miller, The molecular composition of soot, Angew. Chem. Int. Ed. 132 (11) (2020) 4514–4520. Y.A. Levendis, K.R. Estrada, H.C. Hottel, Development of multicolor pyrometers to monitor the transient response of burning carbonaceous particles, Rev. Sci. Instrum. 63 (7) (1992) 3608–3622. F. Cignoli, S. De Iuliis, V. Manta, G. Zizak, Two-dimensional two-wavelength emission technique for soot diagnostics, Appl. Opt. 40 (2001) 5370–5378. P.B. Kuhn, B. Ma, B.C. Connelly, M.D. Smooke, M.B. Long, Soot and thin-filament pyrometry using a color digital camera, Proc. Combust. Inst. 33 (1) (2011) 743–750. J. Simonsson, N.E. Olofsson, T. Sandra, P.E. Bengtsson, H. Bladh, Wavelength dependence of extinction in sooting flat premixed flames in the visible and near-infrared regimes, Appl. Phys. B Lasers Opt. 119 (4) (2015) 657–667. N.J. Kempema, B. Ma, M.B. Long, Investigation of in-flame soot optical properties in laminar coflow diffusion flames using thermophoretic particle sampling and spectral light extinction, Appl. Phys. B Lasers Opt. 122 (9) (2016) 232. R.C. Millikan, Optical properties of soot, J. Opt. Soc. Am. 51 (1961) 698–699. H.A. Michelsen, F. Liu, B.F. Kock, H. Bladh, A. Boiarciuc, M. Charwath, T. Dreier, R. Hadef, M. Hofmann, J. Reimann, S. Will, P.E. Bengtsson, H. Bockhorn, F. Foucher, K.P. Geigle, C. Mounaim-Rousselle, C. Schulz, R. Stirn, B. Tribalet, R. Suntz, Modeling laser-induced incandescence of soot: a summary and comparison of LII models, Appl. Phys. B Lasers Opt. 87 (3) (2007) 503–521. H.A. Michelsen, Effects of maturity and temperature on soot density and specific heat, Proc. Combust. Inst. 38 (2021) 1197–1205. D.R. Snelling, K.A. Thomson, G.J. Smallwood, O.L. Gulder, E.J. Weckman, R.A. Fraser, Spectrally resolved measurement of flame radiation to determine soot temperature and concentration, AIAA J. 40 (9) (2002) 1789–1795. N.J. Kempema, M.B. Long, Effect of soot self-absorption on color-ratio pyrometry in laminar coflow diffusion flames, Opt. Lett. 43 (5) (2018) 1103. C.F. Bohren, D.R. Huffman, Absorption and Scattering of Light by Small Particles, John Wiley & Sons, 2008. A. D’Alessio, A. Di Lorenzo, A.F. Sarofim, F. Beretta, S. Masi, C. Venitozzi, Soot formation in methane-oxygen flames, Proc. Combust. Inst. 15 (1) (1975) 1427–1438. A. D’Alessio, A. D’Anna, A. D’Orsi, P. Minutolo, R. Barbella, A. Ciajolo, Precursor formation and soot inception in premixed ethylene flames, Symp. Combust. 24 (1) (1992) 973–980. P. Minutolo, G. Gambi, A. D’Alessio, Properties of carbonaceous nanoparticles in flat premixed C2H4/air flames with C/O ranging from 0.4 to soot appearance limit, Proc. Combust. Inst. 27 (1) (1998) 1461–1469. D. Cecere, L.A. Sgro, G. Basile, A. D’Alessio, A. D’Anna, P. Minutolo, Evidence and characterization of nanoparticles produced in nonsooting premixed flames, Combust. Sci. Technol. 174 (11–12) (2002) 377–398.

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[133] K.A. Thomson, O.L. Gulder, E.J. Weckman, R.A. Fraser, G.J. Smallwood, D.R. Snelling, Soot concentration and temperature measurements in co-annular, nonpremixed CH4/air laminar flames at pressures up to 4 MPa, Combust. Flame 140 (3) (2005) 222–232. € G€ [134] M.R.J.J. Charest, H.I. Joo, O.L. ulder, C.P.T.T. Groth, O.L. Gulder, C.P.T.T. Groth, Experimental and numerical study of soot formation in laminar ethylene diffusion flames at elevated pressures from 10 to 35 atm, Proc. Combust. Inst. 33 (1) (2011) 549–557. [135] N.A. Eaves, M.J. Thomson, S.B. Dworkin, The effect of conjugate heat transfer on soot formation modeling at elevated pressures, Combust. Sci. Technol. 185 (12) (2013) 1799–1819. [136] H.M.F. Amin, A. Bennett, W.L. Roberts, Determining fractal properties of soot aggregates and primary particle size distribution in counterflow flames up to 10 atm, Proc. Combust. Inst. 37 (1) (2019) 1161–1168. [137] B.G. Sarnacki, H.K. Chelliah, Sooting limits of non-premixed counterflow ethylene/ oxygen/inert flames using LII: effects of flow strain rate and pressure (up to 30 atm), Combust. Flame 195 (2018) 267–281. [138] X. Xue, P. Singh, C.J. Sung, Soot formation in counterflow non-premixed ethylene flames at elevated pressures, Combust. Flame 195 (2018) 253–266. [139] W.L. Flower, C.T. Bowman, Soot production in axisymmetric laminar diffusion flames at pressures from one to ten atmospheres, Proc. Combust. Inst. 21 (1) (1988) 1115– 1124. [140] H.M.F. Amin, W.L. Roberts, Soot measurements by two angle scattering and extinction in an N2-diluted ethylene/air counterflow diffusion flame from 2 to 5atm, Proc. Combust. Inst. 36 (1) (2017) 861–869. [141] K. Gleason, F. Carbone, A. Gomez, Pressure and temperature dependence of soot in highly controlled counterflow ethylene diffusion flames, Proc. Combust. Inst. 37 (2) (2019) 2057–2064. [142] K. Gleason, F. Carbone, A. Gomez, PAHs controlling soot nucleation in 0.101— 0.811MPa ethylene counterflow diffusion flames, Combust. Flame 227 (2021) 384– 395. [143] Y. Wang, A. Raj, S.H. Chung, A PAH growth mechanism and synergistic effect on PAH formation in counterflow diffusion flames, Combust. Flame 160 (9) (2013) 1667–1676. [144] A.E. Lutz, R.J. Kee, J.F. Grcar, F.M. Rupley, OPPDIF: A Fortran program for computing opposed-flow diffusion flames, Report No. SAND96-8243, Sandia National Laboratories, 1997. [145] D. Hou, D. Zong, C.S. Lindberg, M. Kraft, X. You, On the coagulation efficiency of carbonaceous nanoparticles, J. Aerosol Sci. 140 (2020), 105478. [146] S.K. Friedlander, Smoke, Dust and Haze: Fundamentals of Aerosol Behavior, John Wiley & Sons Inc, 1977. [147] Z. Li, H. Wang, Thermophoretic force and velocity of nanoparticles in the free molecule regime, Phys. Rev. E 70 (2) (2004) 11. [148] P.D. Neufeld, A.R. Janzen, R.A. Aziz, Empirical equations to calculate 16 of the transport collision integrals Ω(l,s)* for the Lennard-Jones (12–6) potential, J. Chem. Phys. 57 (3) (1972) 1100–1102. [149] M. Frenklach, A.M. Mebel, On the mechanism of soot nucleation, Phys. Chem. Chem. Phys. 22 (2020) 5314–5331.

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[150] H. Miller, K.C. Smyth, W.G. Mallard, J. Houston Miller, K.C. Smyth, W.G. Mallard, Calculations of the dimerization of aromatic hydrocarbons: implications for soot formation, Proc. Combust. Inst. 20 (1) (1984) 1139–1147. [151] N.A. Eaves, S.B. Dworkin, M.J. Thomson, The importance of reversibility in modeling soot nucleation and condensation processes, Proc. Combust. Inst. 35 (2) (2015) 1787– 1794. [152] K. Yehliu, R.L. Vander Wal, A.L. Boehman, Development of an HRTEM image analysis method to quantify carbon nanostructure, Combust. Flame 158 (9) (2011) 1837– 1851. [153] M.L. Botero, Y. Sheng, J. Akroyd, J. Martin, J.A.H. Dreyer, W. Yang, M. Kraft, Internal structure of soot particles in a diffusion flame, Carbon 141 (2019) 635–642. [154] M. Frenklach, H. Wang, Detailed modeling of soot particle nucleation and growth, Proc. Combust. Inst. 23 (1) (1991) 1559–1566. [155] A. D’Anna, A. Violi, A kinetic model for the formation of aromatic hydrocarbons in premixed laminar flames, Proc. Combust. Inst. 27 (1) (1998) 425–433. [156] I. Reaction Design, CHEMKIN Theory Manual, (July), 2013, pp. 1–402. [157] H. Wang, X. You, A.V. Joshi, S.G. Davis, A. Laskin, F.N. Egolfopoulos, C.K. Law, USC Mech Version II. High-Temperature Combustion Reaction Model of H2/CO/ C1-C4 Compounds, 2007. http://ignis.usc.edu/USC_Mech_II.htm. [158] G. Blanquart, P. Pepiot-Desjardins, H. Pitsch, Chemical mechanism for high temperature combustion of engine relevant fuels with emphasis on soot precursors, Combust. Flame 156 (3) (2009) 588–607. [159] J. Appel, H. Bockhorn, M. Frenklach, Kinetic modeling of soot formation with detailed chemistry and physics: laminar premixed flames of C2 hydrocarbons, Combust. Flame 121 (1–2) (2000) 122–136. [160] C. Saggese, S. Ferrario, J. Camacho, A. Cuoci, A. Frassoldati, E. Ranzi, H. Wang, T. Faravelli, Kinetic modeling of particle size distribution of soot in a premixed burner-stabilized stagnation ethylene flame, Combust. Flame 162 (9) (2015) 3356– 3369.

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CHAPTER

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3

Jai M. Mehta and Kenneth Brezinsky Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, United States

1. Introduction The challenge facing the world’s transportation systems is how to ensure a clean and sustainable environment for the future. The increasing global climate crisis and decreasing fossil fuel reserves are jeopardizing the future of the planet. There is an urgent need to find alternative sources of energy (fuels) which can replace the dominant fossil fuels of conventional petroleum based liquid hydrocarbons and solids, i.e., coal, and reduce the generation of greenhouse gases (GHG). The Intergovernmental Panel on Climate Change (IPCC) has highlighted the need to maintain the global temperature rise to 1.5 °C until 2100 [1], which can be achieved by reduction of carbon dioxide (CO2) emissions since it is one of the largest contributors to greenhouse gases at 37 Gt [2]. About 23% of this total carbon dioxide is generated from combustion of conventional fossil fuels as of 2014, and the contribution to carbon dioxide generation from fossil fuels is expected to rise to about 30% in the next decade [3]. Significant steps need to be taken to curb the formation of greenhouse gases and at least a carbon neutral future is necessary to ensure successfully achieving the goal of reducing temperature rise over the next century. Petroleum based and solid fossil fuels are currently the dominant source of energy for the world, with little to no direct competition in the transportation sector. All modes of transportation—land, sea and air rely on petroleum based fuels and actively generate greenhouse gases and harmful pollutants. In recent years to remedy this, new technologies in the form of battery powered and hydrogen fuel cell powered vehicles have been introduced into the transportation sector. While these technologies promise a cleaner and sustainable source of energy for transportation, they come with several limitations like short operating ranges, special infrastructure requirements for recharging and high sensitivity to ambient conditions that cannot be ignored when considered for total replacement of combustion based systems. While this technology develops means of overcoming its limitations, there is a current need Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00004-7 Copyright # 2023 Elsevier Inc. All rights reserved.

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for optimization of combustion systems and seeking an alternative fuel which can fulfill the energy needs while moving toward a sustainable future. Natural gas is one such contender capable of meeting energy needs while significantly reducing the carbon footprint and helping move to a sustainable future. Natural gas has been used as a fuel source for domestic applications such as cooking and heating as well as industrial applications for centuries. Over the last few decades, natural gas fueled systems have found their way into electricity generation, replacing coal powered systems to realize economical as well as environmental benefits. Natural gas use has also penetrated land transportation processes, particularly in heavy vehicles during the last decade of the 20th century. This increasing penetration of natural gas into various industries displacing petroleum based fuels makes it a promising replacement fuel. While natural gas applications have significantly widened, research into expanding its applications and optimizing its combustion process have not received commensurate attention. The relatively simple composition of natural gas has resulted in overlooking the need for detailed research into its combustion behavior because of the assumption that its combustion behavior can be easily predicted from that of methane. Natural gas has methane (CH4) as the primary component, usually upwards of 87% with hydrocarbon species from C1-C4 making up the rest of the natural gas. The high quantity of methane in natural gas has led to assumptions that the behavior of natural gas is like that of pure methane and can be accurately predicted by assumption that natural gas is all methane. However, several recent research studies [4–13] carried out to investigate the use of natural gas for high power and performance sensitive applications like rocket engines and detonation engines has shown that the behavior of natural gas is far from simple and cannot be accurately predicted from methane chemistry. The immense variability in the composition of natural gas from region to region as well as from time to time also adds to the difficulty in prediction of natural gas combustion behavior. Unlike gasoline, diesel, jet fuels and kerosene based propellants which have several standards that specify their fitness for use, natural gas lacks any such standards resulting in large compositional variation of supplied natural gas which consequently results in unpredictable combustion behavior. This variation in composition has motivated a need to understand the chemistry of natural gas in detail to successfully predict its behavior in critical applications and to develop specifications to gauge the fitness of a sample of natural gas for use in different applications. To successfully develop the standard and understand the implications of the compositional variations on its behavior detailed scientific studies have been carried out like those by Mehta and Brezinsky [7], Shao et al. [5] and Crane et al. [8].

2. Sources of natural gas Natural gas is usually obtained from under the surface of the earth where it has been formed by decomposition of organic matter under immense heat and pressure. As a result, it is considered a fossil fuel but because it is a gas with relatively simple

2 Sources of natural gas

chemical composition it is distinctly different from liquid fossil fuels derived from petroleum or solid fossil fuels such as coal and has compensatory benefits not present for liquid and solid fossil fuels. The compositional variation of the decomposing matter that generates natural gas along with the environmental conditions of decomposition play a role in determining the chemical constituents of the natural gas that is formed. The subsurface natural gas is usually extracted from the ground along with crude oil extraction or by deliberate extraction through hydraulic fracking. While these conventional methods are successful and widely used, they have long lasting and detrimental ecological and environmental effects. The net gains of using natural gas as a fuel are significantly lower when obtained from underground sources because of the environmental impact and should be avoided where possible. Fortunately, natural gas can be obtained from other sources that aid in reducing greenhouse gas emissions and waste management.

2.1 Biogas Biogas is a byproduct obtained by anaerobic decomposition of organic waste. Biogas mainly consists of methane along with small amounts of carbon dioxide, hydrogen and hydrogen disulfide. Since the dominant component of biogas is the same as natural gas—methane, it has a high potential to be interchangeable with natural gas after removal of carbon dioxide [14]. For practical operations the compositional difference between natural gas and biogas should not affect the overall performance significantly but detailed chemical kinetic studies will help ensure the most optimum design of equipment to handle both these sources of methane rich fuels. Since small scale biogas plants are also effective, several biogas plants can be setup in major cities to generate natural gas at a local level which can be supplied to the city to fulfill its domestic needs. Any excess natural gas from biogas can be supplied to domestic power plants or added to the natural gas grid to support electricity generation to serve the cities and localities directly. This would make the cities self-sustaining by generating their own power from their generated waste. This arrangement would further reduce the contribution of greenhouse gases from transportation and treatment of organic waste. The waste byproduct of the biogas plants is a natural fertilizer which can be supplied to local farms so that it returns to the locality in the form of crops that would continue the cycle. There will be a onetime cost and resource consumption involved with setting up the biogas plants as well as arranging for separation and supply of organic wastes to the plants but when strategically placed across the cities the cost benefit can be realized. As illustrated by the lifecycle of biogas in Fig. 1, the system is self-sufficient with minimal maintenance cost suggesting that the initial cost can be justified. The net utility cost to the citizens will also be reduced. The natural gas generated from bio sources can not only be added to the natural gas grid but also can be directly utilized by local natural gas powered hybrid vehicles to generate electricity for their electric powered components.

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FIG. 1 Lifecycle of biogas highlighting its sustainability [14].

2.2 Power to gas (PtG) One of the novel methods used for generation of synthetic natural gas (SNG) is the power-to-generation (PtG) method in which a methanation reaction [15] is utilized to form methane by reaction between hydrogen and carbon dioxide. This reaction is widely used in methanizers for gas chromatography to allow detection using flame

2 Sources of natural gas

Solar

Electric Grid Power Plants

Power to Gas

Wind O2

H2O Other Renewables E.g.. Biogas upgrading

CO2

Electrolysis, H2 Storage

CO2 Storage

Liquefaction Unit

Heat Market Methanation CO2 +4H2 ↔CH4 +2H2O Mobility

Gas Storage Industry

Natural Gas Grid

FIG. 2 Block diagram illustrating power to gas generation system [16].

ionization detectors of the non-hydrocarbon species carbon monoxide and carbon dioxide by converting them to methane equivalents. Fig. 2 illustrates a block diagram of power to gas generation method [16]. This method of methane generation can be considered a renewable and sustainable method since the hydrogen required is generated from electrolysis of alkaline water using power from renewable sources such as wind or solar energy [1,16,17]. The hydrogen is made to react with carbon dioxide sourced from biogas and industrial flue gases to generate the SNG. The SNG is considered a sustainable source of fuel since the combustion of natural gas in appropriate conditions would generate water and carbon dioxide which will in turn feedback into the generation of SNG. Studies [1,15] regarding the technological capability of utilizing this process for SNG generation have been carried out and have shown promising results. This method helps reduce fluctuating energy generation from renewable sources by allowing energy to be stored in the form of chemical energy. The use of the PtG method for generation of SNG can be carried out locally at power plants operating on natural gas which would further reduce the net carbon emissions from the power plant. The carbon dioxide generated from the power plants would be used to regenerate the carbon dioxide being used to make the methane. In the absence of a renewable energy source, a part of the electricity generated from combustion of natural gas can be utilized to assist the methanation process and any carbon dioxide deficit can be fulfilled by stored carbon dioxide or by that extracted from atmospheric carbon dioxide. A completely sustainable self-sufficient natural gas power plant can be developed with very low net carbon emissions, within thermodynamic constraints. The SNG system would provide greatest environmental benefits when utilized with renewable energy generation. However, the fluctuating supply of renewable

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energy sources makes the energy generation potential of these power plants unpredictable. With the proper design of PtG with renewable energy sources, the renewable energy can be chemically stored in the form of natural gas when there is excess availability and low demand. In situations with high demands and low renewable energy availability, like at nighttime in case of solar energy or on still days with wind energy, the stored natural gas can be used to generate electricity to make up for the deficit in energy directly from the renewable sources. A combination power plant will be able to provide reliable electricity with minimum greenhouse gas contribution to atmosphere. Clearly, a highly reliable source of clean electricity will be key to uninterrupted operation of an electrified transport system in the future.

3. Relevant research Natural gas has been used for domestic applications for over a century as previously mentioned and the previous research has largely been limited to thermodynamic conditions and timescales relevant to domestic stationary power plant applications such as furnaces, burners, and cooking tops. These devices are simple and “burn” the fuel to generate heat unlike engines which “combust” fuel to produce energy (mechanical or electrical). Extensive penetration of natural gas into automotive markets and growing interest in utilization of natural gas as a fuel for high performance military applications and space crafts have driven natural gas research to new levels in the last 5 years. To develop engines for these devices, precise design decisions need to be carried out using accurate and detailed analysis of the combustion of the fuel. Rocket and propulsion engines are ever developing engines, with significant ongoing innovations to improve their performance and range. The fuel for space exploration rocket engines is dominated by specialized propellants like liquid hydrogen, hydrazine, dinitrogen tetroxide, and the military propulsion engines are largely fueled by complex hydrocarbon fuels like JP-10, RP-1, RP-2 and JP-8 which are petroleum based fossil fuels and have significant contributions to greenhouse gases when combusted. The rocket engines often burn fuel with little to no emission mitigation and each launch can significantly increase the atmospheric greenhouse gas content if spacecraft launches are to become regular events in the future and accessible to the public. The global climate crisis has prompted the need to find alternative fuels for such applications, especially if the goal of inhabiting Mars is achieved and space travel will become frequent. Methane was seen as a potential replacement propellant for liquid hydrocarbons because it generates lower carbon dioxide for the same power when compared to other hydrocarbon propellants as the result of having the lowest carbon to hydrogen ratio of any hydrocarbon fuel. The simplicity of the molecule makes its combustion chemistry highly predictable over a wide range of operating conditions resulting in simpler and more cost efficient designs. The combustion of methane does not generate any significant soot making the rocket highly reusable without major refurbishments. A further advantage of using methane include maintaining methane

3 Relevant research

in liquid form consumes less energy and requires simpler systems when compared to other clean propellants like liquid hydrogen which requires significantly lower temperatures to stay in liquid state. Several spacecraft manufacturers have embraced these benefits and have already started developing rocket engines operating on pure methane [18]. However, obtaining pure methane requires significant refining processes, which adds to cost; natural gas has a potential to reduce this cost with minimum compromises. Natural gas is predominantly methane, as previously discussed, with small amounts of other hydrocarbons and impurities which makes its carbon to hydrogen ratio nearly that of pure methane and still significantly better than conventional liquid or large molecule hydrocarbon based propellants. The cost benefit of obtaining natural gas is significant along with its ease of availability across the world. There are several pipelines across all continents supplying natural gas and can directly supply launch locations. The composition of natural gas makes it easier than methane to keep under cryogenic conditions since components other than methane raise the boiling point of natural gas above that of pure methane and it is also easier to ignite than pure methane [5]. These advantages make natural gas an almost obvious choice as a replacement alternative fuel to liquid hydrocarbons for rocket and propulsion engines. However, there is one natural gas feature that has been widely overlooked and has turned out to be a significant factor from recent research studies [5– 7,9,11,13,19,20]—the compositional variability of natural gas. The effect of compositional variation has been observed in practice prompting extensive research studies on combustion characteristics and physical effects of natural gas as a function of its composition. Successful implementation of natural gas in propulsion engines requires a detailed understanding of the effects of compositional variation at elevated pressures and temperatures relevant to these systems and knowledge of the steps necessary to ensure that the combustion behavior is within tolerable limits. This knowledge could allow implementing sensors on the propulsion systems that detect combustion irregularities and in real time adjust the operating parameters to maintain performance.

3.1 Chemistry Recent research studies by Mehta and Brezinsky [7] and Shao et al. [5] have highlighted the need for optimizing well established chemical kinetic models currently in use by demonstrating the mismatch between experimental observations and predictions from the chemical kinetic models. To address the mismatch, Wang et al. [8,21] have envisioned building a chemical kinetic mechanism focusing on the detailed chemistry of small hydrocarbons that make up the natural gas. Similarly, Curran et al. [9,11] have investigated mixtures of small hydrocarbons at conditions relevant to piston engines as well as turbine engines to study the ignition delay time and intermolecular interactions in these mixtures to develop new chemical kinetic mechanisms.

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Mehta and Brezinsky [7] carried out shock tube studies of different natural gas samples under oxidation to obtain speciation data as a function of temperature at nominal pressure of
60 atm. A reference natural gas sample whose composition was tailored to mimic the average natural gas composition of the United States was used to study the effect of equivalence ratio (φ) on the oxidation of natural gas. Six other real natural gas samples were also studied at near stoichiometric conditions. The results show the significant effect that natural gas composition can have on oxidation at high pressures and temperatures. This study was carried out over temperature range of 1150–1750 K and provides species yields of eight different species for every experiment as a function of temperature. The study by Mehta and Brezinsky [7] shows the significant effect of sample composition on oxidation behavior of the natural gas samples. The start temperature of fuel decomposition and formation of carbon dioxide increases with increase in methane concentration of the fuel sample, suggesting higher operating temperatures as well as longer ignition delay times. The speciation data when compared to prediction by well known chemical kinetic models—CRECK [22–25], Aramco Mechanism 3.0 [26], USC Mechanism II [27] and San Diego Mechanism [28] show a less than acceptable match with most mechanisms not predicting the experimental results within the error limits of the experiments. The comparison made it clear that in most cases these well-established chemical kinetic models could not predict speciation accurately. However, the Aramco Mechanism 3.0 and the USC Mechanism II had the best overall match with experimental data from the set of mechanisms tested. Despite the limited success of these two models, they, as well as the others, could benefit from additional optimizations of rate constants for key reactions. Fig. 3 shows predictions using the Aramco Mechanism 3.0 for two of the natural gas samples having minimum and maximum methane concentration—Kentucky (KY) and South Carolina (SC) respectively, studied by Mehta and Brezinsky [7]. The species yields predictions for pure methane and pure ethane using Aramco Mechanism 3.0 at conditions matching the natural gas samples are also illustrated in Fig. 3. The simulations were carried out at near stoichiometric conditions for all fuels and the difference in species yield is clear particularly between the natural gas samples. The NG-SC sample with a methane concentration of 96.3% by mole fraction (2.7% ethane) shows fuel decay like that of methane, although the ethylene formation is significantly different. The formation of ethylene with respect to temperature is much more gradual and starts as soon as 1200 K, unlike that for pure methane which starts at about 1400 K. However, the formation of carbon dioxide closely matches with pure methane. The NG-KY samples of natural gas with 91.2% of methane by mole fraction (7.6% ethane) behaves significantly different from pure methane. The NG-KY natural gas fuel decay starts more gradually at about 200 K before the end of reaction, whereas for pure methane decay starts at about 100 K before the end and at a higher temperature. The ethylene formation is even more dramatically different. Ethylene formation starts at least 300 K before for NG-KY and peaks at about 1400 K which is nearly 200 K before that of pure methane. This observation is in line with the difference between predictions for pure methane and ethane. As

Prediction of Key Species - Aramco 3.0 Ethylene

Normalized Mole Fraction

Fuel

Carbon dioxide

1.0

1.0

1.0

0.8

0.8

0.8

0.6

0.6

0.6

0.4

0.4

0.4

0.2

0.2

0.2

0.0

0.0

0.0

1000

1200

1400

1600

Temperature (K)

1800

1000

1200

1400

1600

Temperature (K)

1800

NG - KY NG - SC Ethane Methane

1000

1200

1400

1600

1800

Temperature (K)

FIG. 3 Prediction of species yield as a function of temperature for real Natural Gas Samples (KY and SC) [5,7], pure methane and pure ethane using Aramco Mechanism 3.0 [26].

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CHAPTER 3 Natural gas for combustion systems

evident in Fig. 3 ethane reacts much sooner with respect to temperature than methane, by over 300 K, and the assumption that the chemistry of their binary mixtures should be easily interpolable is not apparent as evidenced by the ethylene predictions illustrated in Fig. 3. The behavior of their mixtures is not linearly related to their individual chemistry and detailed chemical kinetic analysis is necessary to understand the effect of mixing under oxidation conditions. Shao et al. [5] carried out a shock tube ignition delay study using similar real natural gas samples and compared them to pure methane over a temperature range of 1450–1850 K. The differences in ignition delay time for all samples at a given temperature vary by about 60 μs between the samples with minimum (K fuel) and maximum (S fuel) methane composition. The difference between the natural gas sample with maximum methane concentration and pure methane is around 100 μs suggesting a significantly different chemical kinetic behavior of natural gas compared to methane, in line with observations from Mehta and Brezinsky [7]. Fig. 4 from Shao et al. [5] illustrates the variation in ignition delay times (IDT) for various natural gas samples. The natural gas samples in this study match those used by Mehta and Brezinsky [7]—NG-KY sample is represented as K fuel and NG-SC sample is represented as S fuel. The ignition delay time of S fuel is unsurprisingly close to that of methane owing to the high methane concentration in that sample of

FIG. 4 Ignition delay time measurements by Shao et al. [5] for different natural gas samples and pure methane under oxidation, compared to predictions from Aramco Mechanism 3.0 [26] and USC Mech II [27].

3 Relevant research

FIG. 5 Time resolved measurements of ethylene at 1460 and 1630 K by Shao et al. [5], compared to predictions from two mechanisms, Aramco Mechanism 3.0 and USC Mechanism II.

natural gas and in-line with observations of Fig. 3. The converse is true for the K fuel sample with the lowest methane concentration of all samples and has an ignition delay time difference of about 170 μs from pure methane at any given temperature. The same ignition delay time for the two extreme fuel samples is observed at a temperature difference of about 80 K which can result in significant deviation in performance of an engine when the fuel samples are interchanged, unless the engine is carefully designed to handle the variation in combustion resulting from varying fuel composition. In the same study Shao et al. [5] carried out time-resolved species measurement at nominal pressures of 10 atm. Fig. 5 shows the ethylene yield at two temperatures 1460 and 1630 K for all the five natural gas samples tested. The formation of ethylene in 400 μs at 1460 K for the K-fuel is nearly five times more than that of the S fuel. This result complements the results in Fig. 3 where the concentration of ethylene at around 1400 K for the NG-KY sample is nearly four times that for the NG-SC sample at the end of 2.5 ms (reaction time). The ethylene yields at a given time and temperature increase with the decrease in methane (increase in ethane) composition in the fuel tested, which is further supported by the observations of Mehta and Brezinsky [7] making it clear that extensive research is necessary to understand the behavior of natural gas with varying composition. To further investigate the chemical kinetic implications of the significant variation in behavior of different natural gas samples and the seeming inability of chemical kinetic models to capture it, sensitivity analysis of the chemical kinetic system needs to be carried out so that rate constants for key reactions needing refinement can be identified. Then new measurements for rate constants of important reactions could be carried out and models re-optimized to predict the behavior of natural gas samples accounting for compositional variation. Several groups [4,29–33] have already started identifying key reactions of small hydrocarbon (C1-C4) and have made attempts to experimentally measure rate constants and validate them with theory.

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FIG. 6 Rate of progress for KY and SC natural gas samples at 1449 and 1492 K, respectively, corresponding to 50% fuel decomposition at the end of 2.5 ms and at a nominal pressure of 60 atm using Aramco Mechanism 3.0.

As a guide to what research needs to be conducted, a net rate of progress analysis was conducted using the Aramco Mechanism 3.0 for the natural gas samples described previously. The analysis points to the key reactions responsible for the behavior of natural gas. Fig. 6 shows the net rate of progress of top 10 reactions at end of reaction (2.5 ms) and at temperatures corresponding to 50% fuel decomposition—NG-KY sample at 1449 K; NG-SC sample at 1492 K. Fig. 6 shows the top 10 reactions involved in oxidation of these natural gas samples. While the key reactions remain the same, the reaction rates significantly vary between both samples. The dominant reaction for the SC sample is the formation of HO2 from H and O2, which is the same for the KY natural gas sample although the net rate is one third at about 6 mol/m3/s. The reaction responsible for reformation of methane (CH4) from methyl (CH3) and formaldehyde (CH2O) has a higher progress rate for the SC sample when compared to KY although it is the lowest compared to the remaining top 10 reactions for SC-NG. Formaldehyde is considered a critical species in oxidation, but the highly elusive nature of formaldehyde makes experimental measurements challenging. Since formaldehyde is one of the species rarely studied in any of the recent natural gas related research efforts, there is a need to study formaldehyde chemistry as a part of the oxidation of natural gas and mixtures of small hydrocarbons. Rate of progress analysis on various natural gas samples should be carried out to find the most common dominant reactions across various samples and attempts should be made at optimizing them. New measurements of these rate constants should be carried out and used in models, replacing the more commonly used best fit estimates that result from optimization to meet a limited specific target such as ignition delay times.

3 Relevant research

Sahu et al. [9] and El-Sabor Mohamed et al. [11] in two related studies have recently made attempts to study the effect of natural gas composition on oxidation at thermodynamic conditions relevant to gas turbine engines and develop chemical kinetic models capable of modeling the effect of composition variation. Unlike previously discussed studies by Mehta and Brezinsky [7] and Shao et al. [5,32] these studies were carried out at in the relatively lower temperature range of 650– 1050 K using a rapid compression machine (RCM) for measuring ignition delay times. Ten different fuel samples with methane as the primary component blended with C2-C7 alkanes in varying composition to mimic real natural gas composition variation were studied. A chemical kinetic model capable of capturing the combustion behavior of natural gas with varying composition was developed using ignition delay data, illustrated in Fig. 7. Since the natural gas blends from this study have varying composition across seven different alkanes, the mixtures do not follow a systematic order with respect to methane concentration which varies from 35.6% to 98.125% by volume in these blends. It is evident from Fig. 7 that ignition delay time can vary by as much as 67 ms (between NG10 and NG2 at
800 K). NG10 and NG2 which are the two extremes in the ignition delay data shown in Fig. 7 have significantly different methane compositions of 35.6% and 81.25% by volume respectively. The comparison of experimental measurements with predictions from several models further highlights the need for optimization of chemical kinetic models for natural gas use. Comprehensive studies like these provide much needed information to understand the combustion characteristics of natural gas, although more validation targets are necessary for development of a successful comprehensive chemical kinetic model. More speciation data from the oxidation of such natural gas blends would provide the much needed additional information necessary to improve the chemical kinetic models.

FIG. 7 Comparison of ignition delay time for six different natural gas blends measured using RCM by El-Sabor Mohamed et al. [11] showing the ignition delay time variation between natural gas blends with different compositions over a temperature range of 650–950 K and pressures of 20 and 30 atm.

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With optimized and validated comprehensive chemical kinetic models it would be possible to accurately predict other combustion characteristics of practical importance such as flame speed, heat release, and species emissions. While the previously mentioned studies analyze different natural gas samples and the effect of stoichiometric conditions, they have limited the thermodynamic parameters to conditions relevant to deflagration engines. There is a growing interest in replacing methane and hydrogen as fuel in detonation engines. The most common and heavily developed engine, the rotating detonation engine (RDE) [33], utilizes synchronized detonations waves moving in a circular chamber which when they exit the chamber, expand to generate thrust. The fuel and oxidizer are injected into the annular chamber and after the startup of the engine, the detonation is self-sustaining allowing continuous thrust generation. The operating conditions are not well established since the engines are still under full scale development. However, they are generally operated using ethylene-oxygen or hydrogen-oxygen mixtures [34] and detonation waves generate large amounts of pressure which is not ordinarily seen in deflagration engines. The high operating pressures in the presence of detonation waves require a detailed chemical kinetic analysis of potential fuels at matching pressure and temperature conditions. However, most chemical kinetic models are developed using data at relatively low pressures (2000 K). Carbene mediated unimolecular decomposition reactions dominate, initiated by 2–3 and 3–2 hydrogen shift reactions, as these have much lower barriers to reaction compared to CdH fission reactions. These carbenes can rapidly decompose, thus breaking the furan ring, with the subsequent

5 Early kinetic modeling

acyclic species capable of decomposing via simple fission and/or by concerted elimination reactions [22]. The presence of chemical bonds and molecular structures not previously seen have required extensive new kinetic studies. In addition to these new details, previously existing research tools required many changes, in particular those affecting the theoretical chemistry models that are widely used. Existing tools are now good enough to make realistic preliminary estimates of bond energies and thermochemistry parameters, even for such a complex fuel as 2-butyl tetrahydrofuran [59]. The rate of progress in developing technical understanding of the subdiscipline for oxygenated hydrocarbon fuels to the degree reflected in the detailed review of Leitner et al. published in 2017, became active only about 10–12 years earlier. The number of teams and individuals contributing to this noteworthy productivity in this most recent research activity is larger than those contributing to past disciplinary efforts, but their rate of progress is impressive. Theory grew at the same time, theory was developed gradually, and GAUSSIAN, and THERM, and CHEMKIN and H2 explosion limits, and Benson thermochemical kinetics, countless other tools.

5. Early kinetic modeling The capabilities of computer simulations of the detailed chemical kinetics of pyrolysis, ignition, and combustion of fuels have evolved historically at very much the same rates as the evolution and development of computer size and speed. The earliest fuel kinetic models were developed for H2 oxidation [62], followed by models for the smallest hydrocarbon fuel, methane (CH4) [63–65]. Computational mechanisms for larger, more complex hydrocarbon fuels followed steadily to include propane [66], the primary reference fuels for gasoline octane ratings [60,61], structural isomers of heptane [67] and further detailed kinetic reaction mechanisms containing as many as 20 carbon atoms [68–71]. Overall, fuel mechanisms for methane to isooctane took place from about 1983 to 1988. By the end of that time period, reaction rate rules and tables had become capable of dealing with any alkane hydrocarbon fuel of any structural complexity or overall size. Details for unsaturated fuels were not as well developed, but that lack was due to a lack of interest or usage for such fuels, which was in turn caused by a lack of practical combustion devices that used unsaturated fuels. Development of mechanisms was quite slow for aromatic fuels, but there was limited concern since emissions were not particularly stringent for soot emissions, which was the only place where aromatic species were important. Standards or limitations on soot and smoke emissions were slow in appearing or enforced by legislation. A small number of researchers were making significant but not rapid advances in kinetics of aromatic species kinetics, while the overall development of kinetic models for alkane fuels had been accomplished over an time period of approximately 5–6 years.

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6. Small alcohols, methanol and ethanol Methanol has been proposed as an attractive fuel for many years as a fuel with considerable advantages over more traditional fuels. There are many ways to produce methanol from fossil fuels as well as biomass and other sources, it has good ignition properties, blends well with other fuels, avoids soot production due to its lack of CdC bonds, and has a high Octane Rating and avoids engine knock. Over time, interest in methanol combustion has varied from great enthusiasm to nearly complete disinterest. Chemical kinetic studies of methanol began in 1975 with a high temperature mechanism developed by Bowman [72] that simulated the shock tube ignition of methanol, assuming that H atom abstraction from the fuel was accomplished by radicals OH, O, and CH3, breaking one of the CdH bonds and producing the •CH2OH radical. Methanol combustion was visualized as similar to methane, with one of the H atoms replaced by a hydroxyl OH group. The “interior” O atom was puzzling, and it was unclear how to deal with the H atom in the OH radical in methanol. Another puzzle in methanol kinetics was determination of the distinction, if any, between the CH2OH and CH3O radicals from decomposition of methanol or as products when H atoms are abstracted from CH3OH. This distinction was a very early illustration of the need for techniques to deal with reactions with multiple possible product distributions, an unusual (at that time) complication resulting from inclusion of an O atom into a previously uncomplicated combustion reaction, and how subsequent theoretical and computational studies made considerable improvements in the mechanisms [73,74]. Kinetic modeling applications of ethanol combustion have progressed much more rapidly and with much more success than for methanol. This might be viewed as puzzling, since the ethanol molecule is more complex than methanol, but the most significant factor has been that ethanol has found a much more vital place in current technical life than methanol, so there is considerable motivation for finding uses for it. Those uses include extensive use of ethanol as an antiknock additive in SparkIgnition (SI) engines in the United States, currently specified to be at a level of 10% of the fuel. Ethanol is also valuable in compression-ignition (CI) or Diesel engines, where it has become well established that adding O atoms to Diesel fuel reduces the amount of smoke or soot produced in the engine. This will be described more thoroughly below as a powerful demonstration of the value of kinetic modeling of combustion in particular reaction environments.

7. Larger alcohols There are four distinct isomers of butyl alcohol (C4H9OH); the details of their structures demonstrate how the location of the O atom can affect the reactivities and respective bond strengths of the four Carbon atoms and 10 Hydrogen atoms. These structural effects also influence their respective Research Octane Numbers

7 Larger alcohols

(RON) and Motor Octane Numbers (MON). Using values from Sarathy [74] for n-butyl alcohol: H H - C H 1

H - C H 2

H H - C - C - O - H H H 3 4

The bond energies for each of the three CdH bonds for C atoms at location #1 are 101.9 kcal/mol, the bond energies for the two CdH bonds for the C atoms at location #2 are 98.8 kcal/mol, the bond energies for the two CdH bonds for the C atoms at location #3 are 100.6 kcal/mol, and the bond energies for the two CdH bonds for the C atoms at location #4 are 95.5 kcal/mol. Without the O atom in the above n-butanol, the chemical species would be the much more symmetric n-butane, and the CdH(2) and the CdH(3) bond energies would be identical secondary CdH bonds, as would be the equal primary CdH(1) and CdH(4) bond energies. The presence of the oxygen atom distorts its “electron neighborhood,” attracting nearby electron density from and weakening the adjacent bonds, as seen as the bond energy of only 95.5 kcal/mol for the two CdH bonds at location “4” above, from which the nearby O atom has taken electron density. The distortion of electron density from that O atom has a smaller but non-negligible effect, actually increasing the bond energy for the CdH bonds at the “3” site. As we will demonstrate below, the same pattern can be seen not only in other alcohol fuels, but also in alkyl ester, aldehydes, furans and other molecules with similar O atoms. An excellent example is a process for conversion of biomass developed at the RWTH Aachen University [75] into a long-chain n-octanol fuel, n-C8H17OH, in which the three CH2 groups adjacent to the terminal OH group have CdH bond energies with the smallest bond energy at site 1 being the smallest, those at site 2 the highest bond energies, and those at site 3 and farther down the chain having bond energies between those at sites 1 and 2. This results in preferential H atom abstraction at the weakest site 1, followed in most cases by addition of molecular O2 at this “1” site, and reactions to produce a C8 stable aldehyde species, which thus delays the fuel ignition kinetics and an increased Octane rating. An understanding of the detailed structure of such oxygenated fuels from biomass provides a procedure to build a realistic reaction pathway. H H H H H 3 2 1 H - C - C - C - C - C - C - C - C - O - H H H H H H 3 2 1

n-octanol

Abstraction of the H atom in the hydroxyl group is very slow, while the CdH bond energies of the “1” sites are weaker than in the corresponding sites in a conventional alkane fuel, making the abstraction of the “1” H atoms favored. The other CdH bonds are similar to those in an analogous n-C8H18 alkane molecule, but the weaker “1” CdH bonds are a result of electron delocalization due to the presence of the

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strong CdO bond nearby in the fuel. The principle of electron delocalization has become an important part of understanding many modern fuels, and the term and manifestations of it will appear frequently in the following discussions. Following H atom abstraction from n-octanol, addition of the resulting radical to molecular oxygen O2 occurs just as in alkane and other fuels. However, when an H atom is abstracted from the preferred 1-site in the alcohol fuel, O2 addition at that site occurs rapidly, followed almost instantaneously by internal H atom transfer from the OH group to the OO• and then decomposition to produce an aldehyde and the rel˙ 2 radical, as described by Za´dor et al. [76] and da Silva atively unreactive HO et al. [77]. Thus, in contrast to the chain branching features of conventional ˙ 2 radical isomerization reaction sequences in alkanes, O2 addition at the 1-site RO in alcohols produces chain termination due to production of two stable products. This ˙ 2 reaction path, following the preferred 1-site H-atom abstraction, aldehyde + HO effectively quenches low-temperature reactivity. As a result, alcohol fuels, including the linear n-alcohols methanol, ethanol, n-propanol, and n-butanol, have high values of Octane Sensitivity (OS) [78,79] and improve anti-knock properties of SI engines [80].

8. Accidental discovery of O atoms in the fuel as an inhibitor of sooting Combustion of Diesel fuels with oxygenated fuel molecules as major components of the fuel was studied by Miyamoto et al. [81], noting that O atoms in the fuel reduced soot production and emissions of soot dramatically, increased engine thermal efficiency, reduced engine noise, and provided other significantly improved engine performance, when compared with the soot production with non-oxygenated diesel fuel molecules. Their study included oxygenated fuels di-n-butyl ether (DBM), 2ethylhexyl acetate (EHN), diethylene glycol dimethyl ether, and ethylene glycol mono-n-butyl ether (TPGME), with oxygen content ranging from 12.3% to 35.8% by weight. Some of these oxygenated fuel additives are illustrated in Fig. 2. All of the effects of oxygen content in the fuels improved as the amounts of oxygen in the fuel increased, including a total elimination of soot/smoke emissions when the oxygen content exceeded 25%. Miyamoto also studied the effects of adding variable amounts of oxygenated fuels to conventional Diesel fuel, finding that the amounts of soot and smoke emissions precursors were reduced at a rate proportional to the total amount of oxygen in the overall fuel mixture, independent of the initial fuel mixture. They also reported that the location of the oxygen in the fuel mixture had no influence on its soot reduction effects, even when the oxygen was provided in the completely unreacted form of molecular O2. Westbrook et al. [82] subsequently used detailed chemical kinetic modeling with n-heptane as a surrogate diesel fuel and oxygenated fuel additives of methyl butanoate, di-methoxy methane, ethanol, methanol, and tripropylene glycol methyl ether(TPGME) as oxygenated fuel additives. The kinetic modeling focused on initial

8 Accidental discovery of O atoms in the fuel as an inhibitor of sooting

FIG. 2 Saturated diesel fuels and oxygenated species as soot-reducing additives.

ignition of very fuel-rich mixtures, consistent with the extensive diesel combustion studied by Dec [83]. This premixed, fuel-rich (i.e., ϕ  2–4) calculated ignition reproduced the experimental rates of soot exhaust levels reported by Miyamoto et al. very well, as shown in Fig. 3, including the complete elimination of soot emissions when the oxygen content of the fuel exceeded 25–30% oxygen mass fraction. Several observations from this experimental/kinetic modeling study can be made that have broad applications. Since the kinetic effect does not seem to depend on the sources of the O atoms, the effect of oxygenation can be provided also by reducing the overall fuel/oxidizer equivalence ratio, which is consistent with the common feeling that fuel-rich mixtures are more likely to emit soot than fuel-lean mixtures. Similarly, the now-common use of ethanol as a fuel additive acts simultaneously as a knock suppressor in spark-ignition (SI) engines and as a soot suppressor in Diesel compression-ignition (CI) engines. Perhaps most important, bio-oxygenate fuels possess both benefits. The kinetic analysis provided in an earlier study [84] was based on a computation of the homogeneous autoignition of a fuel-rich (ϕ ¼ 3.0) reactant mixture, which followed the evolution of the species not consumed during the rich ignition, reinforcing the observation that Diesel ignition occurs under very

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MB DMM TPGME

DBM

Ethanol Methanol DME Dibutylmaleate

TPGME

0

0.1

0.2

0.3

0.4

Fracon of oxygen in fuel by mass FIG. 3 Variation in computed levels of soot precursors with different oxygenated species in n-heptane.

fuel-rich conditions, and then leaving behind unreacted hydrocarbon pieces that subsequently combine in an oxygen-free environment to build soot particles. This conclusion, about a reaction environment that leads naturally to such an important conclusion, is a rather startling result from a rather simple, uncomplicated homogeneous calculation of autoignition that consumed a few seconds of computer time on a laptop computer. The Platform Chemicals (HMF, Furfural, Succinic Acid, Levulinic Acid, and Itaconic Acid) identified by Leitner et al. [1] as keys to conversion of Ligno-Cellulose to Biofuel Candidates contain 3, 2, 4, 3, and 4 oxygen atoms, respectively, making them attractive as non-sooting bio-diesel fuels, as suggested from the fundamental experimental studies of Miyamoto et al. followed by simple kinetic modeling calculations.

9. Introduction of methyl and ethyl esters as fuels For many years, the only realistic biodiesel fuel in common use was the oil that your “odd” neighbor received when he went to the local hamburger vendor with some bottles and asked them for some used cooking oil. He could drive his truck, with its Diesel engine, for a week with the exhaust smelling like French-fried potatoes. As we now realize, that diesel fuel consisted of vegetable-based oils, like the cooking oil you use in your own home. If analyzed, the cooking oils contained long chains of carbon atoms with some single and an occasional C]C double bond, with as many

9 Introduction of methyl and ethyl esters as fuels

as 15 to 20 carbon atoms in the chains. That description is interesting because that is also the nature of many molecules in conventional Diesel fuels delivered from petroleum refineries (e.g., n-hexadecane [71], isocetane [85,86]), so the commercial cooking oil is very similar to Diesel fuel that can be sold at your neighborhood gas station. Serious program development began about 2000 to determine what the optimal components for a commercial biodiesel fuel might be and then to begin producing and marketing those fuels. Corresponding modeling studies also began to understand and simulate the combustion chemistry of biodiesel fuels. A review by Graboski and McCormick [87] provided a great deal of information, showing that biodiesel fuels consisted primarily of large (15–20) carbon atom chains with a methyl ester group at one end of the long chain, with a small number of 0, 1, 2, or 3C]C double bonds in the carbon chain. These molecules were considerably longer than the largest molecules currently in the kinetic models then in common use, and the methyl ester group at the end of the long carbon chain provided additional challenges to modeling efforts. Combinations of the same 5 specific components were dominant in biofuels made from oils of many plant seeds and berries, as well as soy and rapeseed, and animal fats such as beef tallow. The methyl esters from most familiar biodiesel fuels consist primarily (i.e.,  99%) of only 5 distinct species, whose molecular structures are shown in Fig. 4 where the names show the number of carbon atoms in the long chain, and the number following the colon “:” shows the number of C]C double bonds at the specific locations shown in the figure. Different vegetable oils reflect differences in the plant or other source of the vegetable oil, and those differences from one plant to another are responsible for the cetane number CN of each biodiesel fuel mixture. The relative compositions of 12 biodiesel fuels into the five primary methyl ester components are shown in Table 1, together with the experimental Cetane number rating of each type of biodiesel fuel. Cetane number provides a way to compare relative ignition properties of each fuel under Diesel engine operating conditions. A kinetic model must accurately reproduce the ignition distinctions between these biodiesel fuels, which is a very challenging test of the diesel fuel oxidation kinetics model, which was successfully accomplished. Developing kinetics of these oxygenated, biodiesel fuel components can be divided into three efforts, the first focusing on methods to deal with the methyl ester group, the second to deal with sequences of repeated C]C double bonds separated by individual CH2 groups, and the third seeking methods to simulate long chains of C atoms for groups. Fisher et al. [88] provided a very early (in 2000) methyl ester kinetic model, using methyl butanoate as the fuel. Methyl butanoate is a methyl ester at the end of a short, saturated, linear C4 chain and is the smallest methyl ester to display a limited amount of Negative Temperature Coefficient (NTC) behavior. Fisher et al. used the similarity of the H atom abstraction rates from acetaldehyde to empirically assign a reduced CdH bond energy for the α-site bond energy in their selected methyl ester fuel. Numerous similar kinetic models of small methyl and ethyl ester fuels soon

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FIG. 4 Structural diagram for the 5 primary components in almost every biodiesel fuel.

followed [89–96]. We observe that, while the initial alkyl ester molecule kinetic mechanism was published in 2000 using methyl butanoate as the fuel, subsequent activity on the topic of chemical kinetic modeling of small methyl or ethyl esters did not begin to appear until 6–8 years later with the studies of Gaı¨l et al. [89], Sarathy et al. [91], and Dooley et al. [90], all simulating combustion of methyl esters and based on the earlier model of Fisher et al. A much greater variety of experiments and kinetic studies followed this re-awakening of interest in chemistry of alkly esters in 2007–08 and has continued since then, extending attention to both smaller [92] and larger alkyl ester fuels [96], and finally with a full surrogate model for methyl decanoate by Herbinet et al. [97,98]. The chemical kinetics community at that time had little or no significant experience in simulating kinetics of long carbon chains with more than 6–8C atoms or with fuels containing oxygenated groups such as methyl esters or alcohols. Fortunately, however, based on experience described above for alcohol and 1-olefin fuels, a very limited type of electron delocalization was observed at the end of methyl butanoate ester molecules due to the oxygen atoms in the methyl and ethyl ester groups in biodiesel components. The ester structure produces similarly weak CdH bonds at the α-site in Fig. 4 of each of the five fuel components, making that

Table 1 Percent of each of the 5 C18 and C16 methyl esters in each class of oils. Palmitate Stearate Oleate Linoleate Linolenate CN

Sunflower

Safflower

Linseed

Jatropha

Cottonseed

Corn

Olive

Tallow

Palm

Peanut

Soy

Rapeseed

7 5 19 68 1 49

7 2 13 78 0 50

7 1 19 19 54 39

4 8 49 38 1 58

23 3 20 53 1 51

10 4 38 48 0 49

13 4 72 10 1 55

28 22 46 3 1 58

46 4 40 10 0 62

11 8 49 32 0 54

8 4 25 55 8 47

4 1 60 21 14 54

Oils are from sunflower, safflower, linseed, jatropha, cottonseed, corn, olive, beef tallow, palm, peanut, soy, and rapeseed. Cetane number of the diesel oil fuels from each plant shown as “CN.”

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site preferred for initial H atom abstraction from all of these fuels. Subsequent reactions displaying abstraction at the α-site H atom depend on the temperature; at lower temperatures, addition of molecular O2 at the alpha site is most important, while at higher temperatures β-scission of the α-site radical produces a new, much shorter methyl propenoate species, with the same short species produced, regardless of the size of the original alkyl species. Key features of larger methyl ester models are the decomposition reactions of the radical species produced from an original alkyl ester fuel. RðC〓OÞOR0

where R0 is a methyl radical in methyl ester fuels and an ethyl radical in ethyl ester fuels. It is important to be able to predict the overall reactivity of the products of alkyl ester fuels, as well as the ratio of CO to CO2 produced from alkyl ester consumption. Alkyl ester fuel products with long dCH2d chains will often decompose to smaller species by a series of β-scission reactions which proceed down the carbon atom chain, stopping near the alkyl ester group. Following H atom abstraction from an alkyl ester fuel, the resulting radical species often still retain the ester structure with a radical located at any of at least three forms, where the • indicates the radical site in the radicals A •C - C (C=O) – O – C

B or

C

- C - •C (C=O) – O – C

or

C - C (C=O) – O – •C

Significant contributions to these problems were made by fundamental theoretical chemistry [90,94]. Some of the biodiesel fuel components contain one or more C]C double bonds. The process of simulating kinetics of reactions with an “isolated” C]C group is quite familiar to the kinetic simulations community, but the methyl linoleate and methyl linolenate species place multiple such structures in close proximity to each other, yielding structures, first for a single C]C double bond, which introduces allylic CdH bonds (a) which are adjacent to the double bond, reflecting the electron delocalization due to the C]C double bond, and the vinylic CdH bond. In the example shown here, the common secondary CdH bond strength is approximately 98 kcal/mol, the weaker allylic CdH bond strength is 85.5 kcal/mol, and the stronger vinylic CdH bond strength is 107 kcal/mol. s

s

a

v

v

a

s

s

- C - C - C - C = C - C - C - C s

s

a

a

s

s

Extension of this approach to methyl linoleate and methyl linolenate, with three C]C double bonds, each separated by a conventional dCH2d unit, requires the structure

10 Epilog and conclusions

s

a

v

v

a’

v

v

a’ v

v

a

s

- C - C - C = C - C - C = C - C - C = C - C -C - C s

a

a’

a’

a

s

in which the CdH bonds marked as a0 are even “more allylic” since they have more electron delocalization than those above because two pairs of C]C double bonds are together taking away electron density from the Cda0 bonds in two directions, reducing the bond strength to 76.0 kcal/mol. A similar analysis of bond strengths of CdO2 bond strengths show that the lifetime of molecular oxygen at such a “bisallylic” site is very short, relative to the lifetime of O2 at conventional RO2 sites, which can dramatically reduce the overall reactivity of such a fuel component. However, once a bis-allylic H atom is abstracted (which is energetically very easy), the remaining bis-allyl RO2• radical is very stable and non-reactive, so the overall effect of the repeated C]C structures in these biodiesel fuels is ultimately inhibiting on its ignition. All of these factors were collected into an ambitious kinetic mechanism [99–102] for practical biodiesel fuel that included all of the mechanistic complications noted above. The five fuel molecules shown in Fig. 4 are all included, and each fuel component included high- and low-temperature kinetics with thorough RO2 low-temperature kinetic pathways. The challenges of accounting for details in the structure and sizes of the molecules of these new, large oxygenated fuels also require a combination of thermochemistry and molecular geography, since variables such as “ring strain energy, multiplicity, and degeneracy” are key parameters that are equal in importance with bond energies and heats of reaction. Computed histories for ignition and combustion of each fuel component were carried out and were successfully compared with available experimental results for each component individually and for mixtures of all of the components as components of a fuel mixture. The number of distinct chemical species in this mechanism is nearly 5000 and the number of individual chemical reactions is more than 20,000; these parameters are steadily growing.

10. Epilog and conclusions Kinetic modeling of combustion chemistry has had a meteoric history, beginning slowly with hydrogen kinetics before 1950. Those very early models were developed with pencil and paper, slide rules and mechanical adding machines. Everything changed with the appearance of computers, which catalyzed far-reaching changes. Those changes began slowly at first, with developments on hydrogen kinetics that required more than a decade.

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Further advances toward hydrocarbon fuel mechanisms were made at an evolutionary time scale, beginning with the “simplest” such fuel, methane (CH4), which we now understand to not be all that simple as a challenging, complicated fuel that eventually required more than a decade to understand. Ultimately, the decade spent learning about methane was time well spent, since many kinetic advances were made that have since become powerful tools, including stiff-equation solvers and pressuredependent reaction rates. Once methane was “solved,” progress through the entire field of saturated hydrocarbons reached linear and branched octane and then hexadecane, relatively quickly. Other tools were added, including GAUSSIAN in the area of theory as well as new methods of automatic generation of quite useful reaction mechanisms. Development of the large biodiesel methyl ester fuels has been accomplished rapidly and delivered excellent predictive powers for fuels that are rather complicated structurally. The most challenging task was expected to be understanding the bio-oxygenate fuels, which consisted of fuels with completely new parameters, including the novel presence of oxygen atoms embedded in furanic rings never encountered previously in kinetic models. The capability of having advance knowledge of the energy balances of possible reactions was very important, and the field was well prepared for the tasks of modeling the furanic fuels and their development into kinetic models was overall not as difficult as expected. In retrospect, the most challenging chemical kinetic modeling topics at any time continue to grow steadily in complexity, but the kinetic modeling community has been able to respond even more rapidly. In many ways, the reason is that the computer science and computational sciences needed to provide accurate and efficient models have also grown dramatically, so the capabilities needed to respond to new fuels and new classes of fuels are making our kinetic modeling capabilities continually better. An additional factor with a very strong, beneficial influence on this family of fuels is the dominant presence of some unusually impactful, large research groups who have are focusing their collective expertise on “fuels from biomass.” Several of the most active such groups include the Joint BioEnergy Institute (JBEI) at the Lawrence Berkeley National Laboratory (LBNL), founded by Jay Keasling, the Fuels and Combustion Science group at the National Renewable Energy Laboratory (NREL) led by Robert McCormick, and the Fuel Science Center-Adaptive Conversion Systems for Renewable Energy and Carbon Sources at the RWTH-Aachen University, whose members Alex Heufer and Alina Wildenberg collaborated with the present author on Ref. [5] of this chapter. The impacts of these group research teams has significantly accelerated the development of models for oxygenated fuels from biomass, and such performance has great implications for more ambitious kinetic modeling in the future. The final message for the Combustion Chemistry of “Sustainable bio-oxygenate fuels” is that current mechanisms appear to be reliable and are quite well understood and predictable, but the rapid development of detailed kinetic models has benefited from the long period over which we have learned the essentials of that chemistry that are important.

11 What’s next?

11. What’s next? The term “fuels from biomass” is very new and is still an exciting and productive title for a chapter in a survey of combustion, but any attempt to predict the future of the subject is likely to be very speculative. Fuels from biomass are only beginning to make impacts on society today, but there are many fledgling ideas that are likely to grow into important subjects. Today, virtually all fuels from biomass are based on products derived from ligno-cellulosic waste materials that are extensively processed into new liquids and gases that are combustible themselves or can be processed further into even more convenient forms for combustion. This process, which is the basis of the outstanding review from Leitner et al. [1], has great promise, but it has not yet made significant inroads into the current world or national economic or energy budgets. The dominant application to date is production of ethanol, derived mainly from corn. The initial appeal of biofuels from ligno-cellulosic materials is that, by using otherwise waste materials, fuel development should not compete with biomass associated with food production. While this source is potentially very large, there is still a need to match the lignocellulosic waste materials with the types of oxygenated hydrocarbons that can be produced from it, to obtain optimal results. This process will require two types of improvements, one to broaden the variety of the lignocellulosic materials that can be treated in existing catalytic routes to provide future fuels, and second, development of new catalytic processing pathways to treat source materials. Current attention is being given only to lignocellulosic products as sources for biofuels. This particular limitation of source materials is a result of restriction of source material that will lead only to hydrocarbon or oxygenated hydrocarbon molecules. For example, all of the “target molecules” being treated today lead to platform chemicals or other molecular targets that are furans or furanic acids and to C5 and C6 sugars. The next level of materials are large hydrocarbon acids and other very familiar organic molecules that we already know how to use as primary hydrocarbon fuels. The use of such conventional molecules as source fuels is attractive because we already know how to use them, but it makes it nearly impossible to expand the list of possible, likely not simple hydrocarbon, molecules that could perform the same tasks as familiar hydrocarbons. In a long view, processes for biofuels have thus far been restricted to those that can be easily be related to familiar combustion fuels. Biological systems might contribute products to alternative reaction cycles that might participate in more complex reaction processes; that is, the overall reaction cycles could be more complex that the simple, 2-step cycles that are familiar but could be more productive over longer reaction cycles. Finally, reaction cycles involving microscopic life, either in the oceans or on land, can participate in larger biological and chemical cycles that are rarely characterized or quantified.

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Acknowledgments The author thanks Alex Heufer and Alina Wildenberg of RWTH Aachen for their significant contributions to our discussions of combustion of furanic fuels from biomass. This work was supported by the US Department of Energy, Office of Basic Energy Sciences and the Vehicle Technologies Office, program managers Wade Sisk, Gurpreet Singh, and Kevin Stork, and was performed under the auspices of the US Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344.

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[85] M.A. Oehlschlaeger, J. Steinberg, C.K. Westbrook, W.J. Pitz, The autoignition of isocetane at high to moderate temperatures and elevated pressures: shock tube experiments and kinetic modeling, Combust. Flame 156 (2009) 2165–2172. [86] P. Dagaut, K. Hadj-Ali, Chemical kinetic study of the oxidation of isocetane (2,2,4,4,6,8,8-heptamethylnonane) in a jet-stirred reactor, Exp. Mol. 23 (2009) 2389–2395. [87] M.S. Graboski, R.L. McCormick, Combustion of fat and vegetable oil derived fuels in diesel engines, Prog. Energy Combust. Sci. 24 (1998) 125–164. [88] E.M. Fisher, W.J. Pitz, H.J. Curran, C.K. Westbrook, Detailed chemical kinetic mechanisms for combustion of oxygenated fuels, Proc. Combust. Inst. 28 (2000) 1579–1586. [89] S. Gaı¨l, M.J. Thomson, S.M. Sarathy, S.A. Syed, P. Dagaut, P. Dievart, A.J. Marchese, F.L. Dryer, A wide-ranging kinetic modeling study of methyl butanoate combustion, Proc. Combust. Inst. 31 (1) (2007) 305–3011. [90] S. Dooley, H.J. Curran, J.M. Simmie, Autoignition measurements and a validated kinetic model for the biodiesel surrogate, methyl butanoate, Combust. Flame 153 (2008) 2–32. [91] S.M. Sarathy, S. Gail, M.J. Thomson, P. Dagaut, A comparison of saturated and unsaturated C4 fatty acid methyl esters in an opposed flow diffusion flame and a jet stirred reactor, Proc. Combust. Inst. 31 (2007) 1015–1022. [92] C.K. Westbrook, W.J. Pitz, P.R. Westmoreland, F.L. Dryer, M. Chaos, P. Oßwald, K. Kohse-H€oinghaus, T.A. Cool, J. Wang, B. Yang, N. Hansen, T. Kasper, A detailed chemical kinetic reaction mechanism for oxidation of four small alkyl esters in laminar premixed flames, Proc. Combust. Inst. 32 (2009) 221–228. [93] Y.L. Wang, D.J. Lee, C.K. Westbrook, F.N. Egolfopoulos, T.T. Tsotsis, Oxidation of small alkyl esters in flames, Combust. Flame 161 (2014) 810–817. [94] A. Farooq, D.F. Davidson, R.K. Hanson, C.K. Westbrook, A comparative study of the chemical kinetics of methyl and ethyl propanoate, Fuel 134 (2014) 26–38. [95] B. Yang, C.K. Westbrook, T.A. Cool, N. Hansen, K. Kohse-H€ oinghaus, The effect of carbon-carbon double bonds on the combustion chemistry of small fatty acid esters, Z. Phys. Chem. 225 (2011) 1293–1314. [96] M.F. Campbell, D.F. Davidson, R.K. Hanson, C.K. Westbrook, Ignition delay times of methyl oleate and methyl linoleate behind reflected shock waves, Proc. Combust. Inst. 34 (2013) 419–425. [97] O. Herbinet, W.J. Pitz, C.K. Westbrook, Detailed chemical kinetic oxidation mechanism for a biodiesel surrogate, Combust. Flame 154 (2008) 507–528. [98] O. Herbinet, W.J. Pitz, C.K. Westbrook, Detailed chemical kinetic mechanism for the oxidation of biodiesel fuels blend surrogate, Combust. Flame 157 (2010) 893–908. [99] C.K. Westbrook, Combustion of biodiesel fuel made from soybean oil, in: A. Ahmad (Ed.), Soy: Nutrition, Consumption and Health, Nova Science Publishers, New York, 2013 (Chapter 16). [100] C.K. Westbrook, C.V. Naik, O. Herbinet, W.J. Pitz, M. Mehl, S.M. Sarathy, H.J. Curran, Detailed chemical kinetic reaction mechanisms for soy and rapeseed biodiesel fuels, Combust. Flame 158 (2011) 742–755. [101] C.K. Westbrook, Biofuels combustion, Annu. Rev. Phys. Chem. 64 (2013) 201–219. [102] C.K. Westbrook, W.J. Pitz, S.M. Sarathy, M. Mehl, Detailed chemical kinetic modeling of the effects of C¼C double bonds on the ignition of biodiesel fuels, Proc. Combust. Inst. 34 (2013) 3049–3056.

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CHAPTER

A comprehensive perspective on a promising fuel for thermal engines: Syngas and its surrogates

5

Annarita Viggianoa and Vinicio Magia,b School of Engineering, University of Basilicata, Potenza, Italy, bDepartment of Mechanical Engineering, San Diego State University, San Diego, CA, United States

a

1. Introduction Solving the countless problems that have arisen in the energy sector is among the most important challenges humanity is currently involved in. The reasons are different and depend on variously connected factors. Such factors include the growing danger posed by climate change, decarbonization, the need to significantly increase the share of energy from renewable energy sources, the increase in global energy demand, security risks, the need for inclusive and integrated market policies, etc. The energy policy of the various countries aims to meet the growing demand for energy, the sustainability of the energy sector and the need to resort to eco-friendly and cleaner energies. Therefore, in this global energy framework, it is a question of addressing forms of energy that guarantee sustainability as well as the continuity of energy supply without any risk. To this end, it is necessary to promote scientific research toward clean and low-carbon energy technologies. The energy sources defined as renewable are different and include solar energy, wind energy, hydroelectric energy, biomass and biofuels. Specifically, syngas is a fuel derived mainly from the gasification of biomass and can be considered as a recovery gas of the energy content of waste products of various human activities, from industry to agri-food. Among the various uses of syngas, there are not only the production of heat obtained through its combustion but also the production of mechanical and/or electrical energy through the use of gas turbines or internal combustion engines (ICEs) [1]. As regards ICEs, the interest in the use of syngas in internal combustion engines originated in India [2–5], thanks to the large availability in that country of bioresources and the lack of fossil fuels. Furthermore, producer gas had already been employed during the World War II to yield electrical power and heat [6]. The use of waste from agri-food industry and forest activities to produce syngas is a very Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00001-1 Copyright # 2023 Elsevier Inc. All rights reserved.

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interesting process, directed to feed stationary engines for power and heat generation in peripheral areas, with a relatively small amount of pollutant emissions. It is well known that engines are an extremely valid device for mechanical power production. On the other hand, challenging environmental issues require the use of new engine power strategies. Syngas very often represents the output of the disposal of plastic waste and scraps, or derives from waste from the agri-food industry. In this context, syngas engines can be considered sustainable power units, which are independent of fossil fuels. A comprehensive review of the methods to satisfy the energy demand would be necessary in the event that such hydrogen-based renewable fuels are to be used. Indeed, decentralization should be carried out toward rural areas or small communities that are able to supply feedstocks to energy generation systems, thus without affecting transport costs. This energy decentralization policy obviously has important social and economic implications. To date, the use of syngas power generation systems is mainly addressed to small plants for recovery purposes. However, companies today show a strong interest in developing in-house energy recovery solutions to meet environmental sustainability and the requirements of the so-called circular economy. As an example, companies could dispose of their industrial waste through a highly efficient gasification system in order to produce syngas for their direct use, thus reducing the external demand for energy. Not only, syngas in engines may also reduce greenhouse gases and hydrocarbons emissions if a specific gas composition is carefully selected. It is important to underline that the energy recovery strategies described above are more efficient and economically viable if they refer to plants with increasing power production. To this end, it is interesting to observe how the cost of producing syngas decreases more than linearly with the increase in the power of the plant [7]. Unfortunately, even today the economic analysis is limited to small-scale plants [7–9], since large plants are not yet considered in this context. However, these studies have shown that the use of syngas can be economically competitive. This competitiveness may be further accentuated due to the likely future increases in the cost of petroleum-derived fuels. In light of all these considerations, this work represents an effort to briefly outline the current state of the research aimed at analyzing the combustion strategies of engines powered by syngas and the chemical-physical characteristics of syngas so that it can efficiently power internal combustion engines. In Section 2, the most important physical and chemical properties of syngas are given with emphasis on the species composition of syngas required to increase engine power output and efficiency. Section 3 is focused on the performance and efficiency of engines powered by syngas and a variety of combustion strategies are described in detail. Then, Section 4 refers to the very important aspect of pollutants and emissions of engines powered by syngas. Finally, concluding remarks are given on the use of syngas as an increasingly promising and efficient fuel for the power generation sector.

2 Syngas: An alternative fuel for thermal engines

2. Syngas: An alternative fuel for thermal engines Syngas consists of a gas mixture of hydrogen (H2), carbon monoxide (CO) and methane (CH4) as main chemical species, with a small amount of heavy hydrocarbons. Other species are hydrogen sulfide (H2S), carbonyl sulfide (COS), ammonia (NH3), hydrogen cyanide (HCN), hydrogen chloride (HCl) and traces of mercury, arsenic and other heavy metals. The gas is diluted with about 50% of inert gases, such as N2, H2O and CO2, whose fractions depend on the gasifying agent. Syngas obtained with addition of steam or oxygen has a medium heating value of about 10–28 MJ/Nm3 (syngas or powergas), while syngas obtained with addition of air has a lower heating value of about 4–7 MJ/Nm3 (producer gas). Syngas is obtained through the gasification of biomass, coal, or wastes inside a gasifier at high temperature. In the gasifier, a partial oxidation of the feedstock occurs under controlled thermodynamic conditions and in the presence of oxygen deficiency. Gasification consists of a sequence of several stages that provide at the end of the entire process the so-called syngas. The processes are: drying, pyrolysis, combustion, cracking and final reduction. Among those processes, cracking follows the carbonaceous particles combustion and is needed to turn tar compounds into elemental molecules by heat. Such a molecular breakdown is essential to get a gaseous fuel to be compatible with internal combustion engines. This is because tars could condense at relatively low temperatures and this may damage the engine valves. Finally, reduction is the process that ensures the formation of hydrogen and carbon monoxide starting from water and carbon dioxide, that are the products of the combustion process. Based on the specific syngas application, the gasification process may be addressed to optimize either the hydrogen content [3] or the lower heating value, with a good carbon conversion and thermal efficiency of the process. It has been found that the maximum H2/CO ratios occur at intermediate temperatures. At such temperatures, the water-gas-shift reaction is the most important reaction of the gasification process in the presence of a proper amount of steam. Several authors [5,6,10] used different procedures with ad-hoc compounds to achieve high H2/CO ratios and good thermal and carbon conversion efficiencies at the same time. In parallel, predictive models [11–19] based on equilibrium thermodynamic models have been employed to get the optimum syngas composition, in terms of hydrogen, carbon monoxide, methane, water and carbon dioxide mass fractions for a specific application. More complex CFD approaches have also been used by some authors [20–22]. Such models are in principle able to provide more accurate results based on the level of complexity of the implemented sub-models. Recently, machine learning techniques have also been employed with a certain level of reliability. Specifically, Dong et al. [23] and Xiao et al. [24] developed an artificial neural network to study a fluidized bed with various feedstocks. However, a large amount of experimental data to perform a good network training is required for such approaches.

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CHAPTER 5 A comprehensive perspective on a promising fuel

Syngas can be considered a promising fuel for internal combustion engines applications due to its chemical-physical properties and energy content [1]. In what follows an overview of the most important properties of syngas is given. Syngas has a low calorific value and a reduction of syngas combustion performance compared to conventional fossil fuels can be expected. As a matter of fact, the energy density of the fuel-air mixture near stoichiometric conditions is almost the same for syngas and for common fossil fuels. This is due to the low air-to-fuel ratio of the syngas-air mixture under stoichiometric conditions. Indeed, the engine power derating is attributed only in part to the lower heating value of the fuel, but it comes from the decrease of the engine volumetric efficiency [25] because of the low density of syngas. Another very interesting property of syngas is its relatively high laminar flame speed. This is a fundamental parameter for engine combustion and pollutant formation, and it is mostly influenced by mixture composition, i.e., mainly H2/CO ratio, pressure and temperature. A large number of works are available in the literature to evaluate such a flame speed [26–33]. For example, Fig. 1 shows the laminar flame speed by Kishore [26], in absence of methane, as a function of the equivalence ratio at 1 bar and 300 K for different chemical compositions. As expected, the laminar flame speed increases with H2 content and the maximum flame speed is reached for rich mixtures (equivalence ratios between 1.4 and 1.6). With CH4 in the syngas composition, i.e., 12% of methane replaces the same fraction of CO, the increase of the laminar flame speed with the hydrogen content is less effective (Fig. 2). 140

Burning velocity (cm/s)

120

120 100 80 60 40 20 0

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

Equivalence ratio (f) H2 48%, CO 0% H2 36%, CO 12%

H2 24%, CO 24% H2 12%, CO 36%

FIG. 1 Burning velocity as a function of the equivalence ratio for different syngas chemical compositions (0% CH4). Reprinted from V.R. Kishore, M.R. Ravi, A. Ray, Effect of hydrogen content and dilution on laminar burning velocity and stability characteristics of producer gas-air mixtures, Int. J. React. Syst. 2008 (2008) 310740.

2 Syngas: An alternative fuel for thermal engines

Burning velocity (cm/s)

45 40 35 30 25 20 15 10 5 0

0.6

0.8

1

1.2

1.4

1.6

1.8

Equivalence ratio (f) H2 0%, CO 36% H2 12%, CO 24% H2 24%, CO 12%

FIG. 2 Burning velocity as a function of the equivalence ratio for different syngas chemical compositions (12% CH4). Reprinted from V.R. Kishore, M.R. Ravi, A. Ray, Effect of hydrogen content and dilution on laminar burning velocity and stability characteristics of producer gas-air mixtures, Int. J. React. Syst. 2008 (2008) 310740.

Unfortunately, beside methane, the presence of inert content tends to reduce the laminar flame speed of syngas-air mixtures. Furthermore, flame instabilities [26] have also been observed due to the high diffusion of hydrogen and non-unitary Lewis number effects. Another important property of syngas is its wide range of flammability. This has a positive consequence for internal combustion engines as they can be operated with very lean fuel-air mixtures. Kutcha [34] and Fossum and Bayer [29] found an operating range of 20–60% fuel in air and compared the wider range of flammability of syngas to natural gas and gasoline. In another study [16], the authors found that the lean flammability limit of syngas is more affected by the inert content than by the unburnt gas temperature. Li et al. [35] measured the lean flammability limits of syngas-air mixtures with different levels of inert dilution and unburnt gas preheating temperatures. Such limits seemed to be unaffected by the inert content (N2 and CO2) up to a certain level of dilution. Sensitivity analysis [36] of kinetic mechanisms for syngas, given in Table 1, shows that hydrogen plays the main role to control the reactivity of the mixture, while CO has an inhibiting effect on chemistry. Indeed, mixture reactivity is highly influenced by the rates of production and destruction of OH radicals. As syngas contains other species beside H2 and CO, efforts were made to broaden the range of applicability of the mechanisms to more reactants and diluents, such as methane, carbon dioxide and water vapor [44].

121

Table 1 Chemical kinetics mechanisms for syngas combustion. Range Ref.

Number of species

Number of reactions

p (atm)

T (K)

Equivalence ratio

Validation data

s et al. [36] Keromne

14

41

914–2220

0.1–4.0

[37–39]

32 5 30

0.987– 69.085 0.039–450 1–20 0.047–64

Frassoldati et al. [40] Nikolaou et al. [44] Davis et al. [48]

12 8 14

0.0005–11.6 0.4–5.0 0.84–3.0

[41–43] [45–47] [49–51]

38

190

40–260

0.2–6.0

[52,53]

13

30

1

298–2850 298–700 298.2– 2625 1040– 1500 298

Petersen et al. [52] Saxena and Williams [54] Sun et al. [58] Li et al. [61] Starik et al. [63] Yetter et al. [41] GRI mech.3.0 [70]

0.6–4.5

[55–57]

15 20 15 13 53

33 84 44 28 327

1–40 0.03–9.6 0.01–60 0.3–2.2 0.033–19.7

298 300–2850 850–2900 823–2870 300– 2800

0.3–5.0 0.005–6.1 0.3–5.0 0.0005–6.0 0.0005–6.0

[59–61] [38,57,62] [48,64–67] [38,68,69] [38,68,69]

Reprinted from M. Fiore, V. Magi, A. Viggiano, Internal combustion engines powered by syngas: a review, Appl. Energy 276 (2020) 115415 with permission of Elsevier.

3 The performance and efficiency of syngas-fueled engines

3. The performance and efficiency of syngas-fueled engines The use of syngas in internal combustion engines may lead to improvements in terms of performance and efficiency under specific conditions [1]. In literature, several applications are given on the use of syngas in Compression Ignition (CI) engines, in Homogeneous Charge Spark-Ignition (HCSI) engines, and in Direct Injection (DI) for Spark Ignition (SI) engines. As regards CI engines, such engines operate with high compression ratios, usually higher than 14:1, and, as syngas autoignition is not easy to be achieved, a pilot fuel, i.e., diesel fuel, is used to ignite the mixture. As regards HCSI engines, syngas replaces gasoline or natural gas, and the compression ratio of such engines is increased to reach engine performance comparable to that obtained with conventional fossil fuels. Such an increase is possible due to the reduced knocking tendency of syngas with respect to gasoline. Nevertheless, the volumetric efficiency of such engines reduces due to the low density of syngas [71,72] and this is the reason for the relatively low output power of those engines. Such a limitation can be overcome by employing the direct injection of syngas in the combustion chamber with a specific arrangement of the injection system, as most of the DI engines were originally designed to operate with gasoline, diesel fuel or natural gas.

3.1 Dual-fuel (diesel-syngas) CI engines In dual-fuel CI engines, the combustion process takes place in part from a diesel fuel, and in part from an alternative fuel, e.g., syngas. The amount of diesel fuel to be employed must be carefully selected in order to minimize the fuel consumption and obtain the best engine performance for the entire range of engine loads. Diesel fuel replacement with syngas cannot overcome a certain diesel/syngas ratio because the engine efficiency decreases with such a ratio. During diesel fuel injection, a certain number of ignition spots take place, leading to an uncontrolled energy release rate during premixed combustion. Hence, difficulties arise to simultaneously control engine efficiency and diesel fuel consumptions. Table 2 shows the maximum diesel saving obtained by several researchers. A diesel saving up to 50% was achieved by Mahgoub et al. [77] with composition B of Table 3 at 1200 rpm. The maximum diesel replacement of 74.2% at 1200 rpm was obtained with Syngas C of Table 3, with the highest increase in terms of efficiency (37.5%) and power output. An analogous diesel fuel saving of around 75% was obtained by Dasappa and Sridhar [80]. However, the efficiency of the engine decreased from 28% to 22% in dual-fuel mode. Uma et al. [78] obtained diesel savings ranging from 67% to 86% with a significant increase of the specific fuel consumptions. Singh and Mohapatra [46] measured the maximum diesel fuel reduction of 45.7% at low loads. Finally, Malik [2], employed a CI engine optimized to achieve the maximum replacement of diesel fuel, which was about 50%. In dual-fuel engines, combustion mainly consists of different stages [79]. The first stage occurs after diesel injection and concerns with the ignition delay of the

123

Table 2 Maximum diesel saving with dual fuel engines. Ref. Parikh et al. [73] Sombatwong et al. [74] Mahgoub et al. [75] Dasappa and Shridar [76] Uma et al. [77] Singh and Mohapatra [78] Malik [79]

Engine speed (rpm)

Cylinders

Volume displacement (cc)

Max load (kW)

Compression ratio

Maximum diesel saving

649.8 1500

1 1

1428 411

4.4 5.884

22:1 18:1

90% 64.21%

1200 1800

1 6

319 6494

4.0 68.4

17.6:1 17.5:1

74.2% 75%

1500 1500

6 1

6614 553

77 3.5

15:1 18:1

86% 45.7%

1500

1

553

5.0

18:1

50%

Reprinted from M. Fiore, V. Magi, A. Viggiano, Internal combustion engines powered by syngas: a review, Appl. Energy 276 (2020) 115415 with permission of Elsevier.

3 The performance and efficiency of syngas-fueled engines

Table 3 Composition of syngas used in Ref. [77]. Syngas

LHV (kJ/kg)

CO (%)

H2 (%)

CO2 (%)

CH4 (%)

N2 (%)

A B C

4726.19 5418.4 7444.13

25 22 29

10 18 19

12 6 8

4 3 6

49 51 38

Reprinted from M. Fiore, V. Magi, A. Viggiano, Internal combustion engines powered by syngas: a review, Appl. Energy 276 (2020) 115415 with permission of Elsevier.

pilot fuel. The ignition delay time is generally longer in dual fuel combustion, due to the lower oxygen concentrations within the spray region based on the presence of gaseous fuel fraction [76]. At the end of this stage, several ignition kernels occur in the chamber. Hence, a premixed combustion takes place with a visible pressure rise. As the premixed flame moves away from the injection region, combustion is controlled by the fuel mixing rather than chemical kinetics. The following stage is related to the primary fuel delay period and a noticeable pressure decrease is observed during this stage. Then, a fast combustion of the primary fuel occurs, which leads to a significant pressure rise. Finally, turbulent flame propagation of both fuels follows. Therefore, the combustion process in dual-fuel engines shows features of both compression-ignition engines and spark-ignition engines [81]. In the literature, a decrease of power output in dual-fuel mode has been observed for all the engines. This decay is mainly due to both the lower gas heating value of the producer gas and to the reduction of the volumetric efficiency. Strategies have been employed to overcome such limitations and to improve the engine performance. One of them is the use of the so-called PREmixed Mixture Ignition in End-gas Region (PREMIER) combustion, which involves a two-stage combustion. Another interesting strategy is the use of Reactivity Controlled Compression Ignition (RCCI) engines, with an early injection of a pilot fuel during the compression stroke. Azimov et al. [82], proposed the so-called PREMIER combustion, which is, under specific operating conditions, a two-stage heat release combustion. Such a strategy has been investigated in [82–85]. At the first stage, the pilot diesel fuel is injected and auto-ignites before TDC. A turbulent flame propagation occurs in the combustion chamber. Then, a second stage of combustion takes place with a very high heat release rate as the end-gas region reaches the autoignition temperature. The second stage occurs away from the first ignition kernels to allow a controlled combustion and to avoid the onset of pressure oscillations. PREMIER combustion presents two peaks of heat release, the highest occurring several crank-angles after TDC. This combustion strategy leads to an increase in engine performance. Fig. 3 shows a comparison in terms of IMEP and thermal efficiency of a syngas dual fuel engine with and without the occurrence of PREMIER combustion. One of the most important controlling parameters in the PREMIER combustion is the SOI (Start of Injection) of the pilot fuel. The SOI timing has been studied by Roy et al. [85], by

125

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CHAPTER 5 A comprehensive perspective on a promising fuel

FIG. 3 Engine performance (mean combustion temperature, IMEP and indicated thermal efficiency) and NOx emissions as a function of H2 content in syngas for conventional and PREMIER combustion with the same input energy (Qin) and injection timing, corresponding to the minimum advance for the best torque (MBT). Reprinted from U. Azimov, E. Tomita, N. Kawahara, Y. Harada, Effect of syngas composition on combustion and exhaust emission characteristics in a pilot-ignited dual-fuel engine operated in premier combustion mode, Int. J. Hydrog. Energy 36(18) (2011) 11985–96 with permission of Elsevier.

varying the injection timing from 23° BTDC to 5° ATDC. They found that a twostage combustion occurred with both lean mixtures with an ignition timing between 23° BTDC and 4° BTDC and near stoichiometric mixtures with ignition timing between 7° BTDC and 3° ATDC. An improved control of combustion can be obtained with the use of RCCI engines [86,87], where an early injection of the pilot fuel occurs during the compression stroke. However, this strategy is still under investigation to identify the optimum operating parameters. Specifically, recent analyses [86] focused on the selection of both optimum dual-fuel ratio and the injection timings for both pilot and primary injections. As previously stated, the decrease of the engine volumetric efficiency due to the low mass density of syngas compared to air density, also underlined by Sahoo et al. [88] and Maghoub et al. [77], requires a special care. In Refs. [82,88,89] the authors

3 The performance and efficiency of syngas-fueled engines

considered a syngas, as a blend of gases mainly composed of hydrogen and carbon monoxide. Specifically, Sahoo et al. [88] measured a volumetric efficiency of 73.7%, 69.5% and 66.2% at high load, with hydrogen volume fractions of 100%, 75% and 50% in syngas, respectively. Mahgoub et al. [77] showed how the volumetric efficiency decreases as a function of the diesel replacement ratio for different engine speeds. A strategy to improve both volumetric and thermal efficiencies is the use of a supercharger or turbocharged engine as suggested by Singh and Mohapatra [90] and Hassan et al. [91]. They were able to obtain a noticeable increase in terms of combustion efficiency with respect to naturally aspirated premixed dual fuel engines. From the numerical point of view, dual fuel combustion has been analyzed by several researchers. Caligiuri and Renzi [92] implemented a simple model based on three Wiebe functions for the premixed combustion of diesel fuel, the premixed combustion of syngas and the diffusive combustion. The model was able to simulate the two pressure peaks at the maximum heat release crank angles. They estimated the heat losses through the cylinder walls (Woschini [93]) and the ignition delay (Prakash and Ramesh [94]). More complex models were employed by Feng et al. [95], which employed a reduced kinetic mechanism to account for syngas addition, and by Stylianidis et al. [96], which developed a new syngas mechanism that was validated in terms of in-cylinder pressure trace. The kinetic mechanisms were then introduced in a multi-dimensional engine model, with the addition of many other sub-models for the liquid atomization process, for the coalescence and evaporation of droplets, for the gas turbulence and for the chemistry. Even with accurate simulation models, the selection of the optimum engine operating conditions is not an easy task, due to the large number of parameters that influence the performance and efficiency of such engines. For example, Rinaldini et al. [97] tried to provide a correlation for the optimum injection timing vs diesel replacement rate and Chuahy et al. [87] tried to reduce the computational cost through a recursive use of Design of Experiments (DOE) and a Genetic Algorithm (GA). A multi-objective optimization of the engine parameters was also carried out in [86], with a large number of details provided by the authors. An efficient coupling of CFD, genetic optimization and feedback control techniques is required to achieve good results with reasonable computational costs.

3.2 HCSI engines It is well known that in homogeneous charge spark-ignited engines the mixing of air and fuel takes place before the intake valve. Indeed, this strategy typically provides a good mixing of the charge. On the other hand, with syngas, such a strategy generally limits the engine volumetric efficiency, since the gaseous fuel is characterized by a low density and, at the same time, reduces the indicated work due to pumping losses. Such a reduction is also accentuated by the relatively low heating value of syngas.

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A strategy to limit such negative effects is the increase of the compression ratio of the engine unless knock conditions are detected. Nevertheless, the power output is still lower than that obtained with gasoline engines, and the trade-off between emissions and the low volumetric efficiency is still an unresolved issue. Several researchers addressed their works to identify the engine operating conditions that avoid knocking. Sridhar [98] varied the compression ratio from 11.5 to 17 and found the absence of knock by using producer gas as fuel, even at the highest compression ratio. The absence of knock was mainly due to the fast H2 burning rate and to the specific engine chamber geometry. The engine efficiency increased with the compression ratio, although such an increase flattened out beyond a certain point, at which friction losses become predominant. Indeed, the upper limit of the compression ratio is mainly related to friction losses rather than knocking. The same low knocking attitude of syngas combustion was also assessed by Ahrenfeldt [99]. Rakopulos and Michos [100] employed a knock sub-model and found a risk of knocking under full load operation at the maximum pressure peak. Some authors tried to reduce engine knocking by increasing the air excess-ratio. The work of Marculescu et al. [101] shows that with an increase of the air excessratio to 2.2–2.8, knocking was avoided mainly due to the high H2 reactivity. Bika et al. [102] showed that the maximum compression ratio to avoid knocking decreases as the equivalence ratio increases (Fig. 4). Syngas composition influences the ignition delay and the premixed flame propagation, which in turn influence engine performances in terms of power output and efficiency. Specifically, hydrogen content plays a major role in such a propagation due to its high reactivity. Indeed, Arroyo et al. [103] show that syngas provided the fastest flame propagation with respect to gasoline, natural gas and biogas. Cribick et al. [104] replaced natural gas with syngas and found an increase of the brake torque. Due to H2 reactivity, ignition advance has been investigated by several authors. Mustafi et al. [72], Shridar and Yarasu [98] and Arroyo et al. [103] adjusted the spark timing to maximize the performance of an engine fueled with syngas. Ji et al. [105] measured a reduction of the ignition lag and rapid burn angle in an engine with the addition of syngas to gasoline. Such reductions are also found by Ran et al. [106], whose results are shown in Fig. 5 for different fuels. Another feature of syngas combustion relates to low cycle-to-cycle variations (COV), as shown in Fig. 6 by Arroyo et al. [103]. Such a stable combustion mode makes syngas particularly advantageous under lean conditions. For example, Dai et al. [107] evaluated an increase of the engine efficiency from 36% to 40% with a syngas addition of 2.5% under lean conditions as shown in Fig. 7. In the figure, the thermal efficiencies measured by Ahrenfeldt [99] and Ran et al. [106] are also given with air-to-fuel ratios ranging from 1.2 to 2.5. The results show a fairly constant thermal efficiency, which confirms that producer gas is a good choice for lean burning combustion. Nevertheless, the engine power output is generally lower compared to that of engines powered with conventional fossil fuels. This is related to the lower energy content of syngas. As an example, Sridhar and Yarasu [98] measured a reduction of

3 The performance and efficiency of syngas-fueled engines

Compression Ratio

100%H2

75/25H2/CO

50/50H2/CO

13 12 11 10 9 8 7 6 5 0.5

0.6

0.7

0.8

0.9

1

1.1

1.2

Equivalence Ratio FIG. 4 Maximum compression ratio as a function of equivalence ratio for different syngas compositions. Reprinted from A.S. Bika, L. Franklin, D.B. Kittelson, Engine knock and combustion characteristics of a spark ignition engine operating with varying hydrogen and carbon monoxide proportions, Int. J. Hydrog. Energy 36(8) (2011) 5143–52 with permission of Elsevier.

the engine power output from 17% to 26% with respect to diesel fuel for stoichiometric and slightly rich mixtures, respectively. Mustafi et al. [72] measured a decrease of the brake torque ranging from 23% to 30% with respect to natural gas, as shown in Fig. 8. As regards wall heat losses, Ji et al. [105] measured an increase of the engine thermal efficiency related to a reduction of the heat transfer due to the faster combustion of syngas compared to gasoline. An opposite trend was found by Sridhar Yarasu [98] and Shivapuji and Dasappa [108], which showed that the H2 content in syngas enhances the engine cooling. They claim that, even if the first stage of combustion is faster due to the higher mixture reactivity, the second stage is slower due an increased cooling of the unburnt mixture near the engine walls. From the numerical point of view, simple zero-dimensional models of HCSI engines have been employed by several researchers with some successful comparisons with measurements. Among those works, the work of Sridhar and Yarasu [98] can be mentioned, who applied a filling and emptying technique with a single-zone burning model to an engine with different compression ratios and equivalence ratios. Papagiannakis et al. [109] applied a two-zone model. Their results suffered from a lack of spatial and temporal resolution and this brought to some discrepancies with measurements. A step ahead was done by Rakopulos and Michos [100], who developed a multi-zone model with several zones for the burning gas region, to simulate the effect of temperature stratification. The validation of the model was done by considering an engine running at full load. Mustafi et al. [72] also employed a multi-zone model, named ISIS (Integrated Spark Ignition engine Simulation), which is based on a model proposed by Ferguson [110]. Numerical

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35 E10-Gasoline

30

Natural Gas Ethanol Syngas

CA 0-10 (deg)

25

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FIG. 5 Ignition delay time and rapid burn angle as a function of equivalence ratio for E10-gasoline, natural gas, ethanol and syngas. Reprinted from Z. Ran, D. Hariharan, B. Lawler, S. Mamalis, Experimental study of lean spark ignition combustion using gasoline, ethanol, natural gas, and syngas, Fuel 235 (2019) 530–7 with permission of Elsevier.

FIG. 6 Coefficients of variation (COV) of the indicated mean effective pressure (IMEP) computed for different fuels and conditions. Reprinted from M. Fiore, V. Magi, A. Viggiano, Internal combustion engines powered by syngas: a review, Appl. Energy 276 (2020) 115415 and from J. Arroyo, F. Moreno, M. Mun˜oz, C. Monne, N. Bernal, Combustion behavior of a spark ignition engine fueled with synthetic gases derived from biogas, Fuel 117 (2014) 50–8 with permission of Elsevier.

FIG. 7 Engine efficiency as a function of air-to-fuel ratio obtained by various authors for pure syngas (Ran et al. [106], Ahrenfeldt [99]) and for a blend of gasoline and syngas (2.5%) (Dai et al. [107]). Reprinted from M. Fiore, V. Magi, A. Viggiano, Internal combustion engines powered by syngas: a review, Appl. Energy 276 (2020) 115415 with permission of Elsevier.

40.0

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Brake torque (Nm)

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FIG. 8 Brake torque and specific fuel consumption as a function of engine speed measured by Mustafi et al. [72] for syngas and natural gas. Reprinted from N.N. Mustafi, Y.C. Miraglia, R.R. Raine, P.K. Bansal, S.T. Elder, Spark-ignition engine performance with ‘powergas’ fuel (mixture of CO/H2): a comparison with gasoline and natural gas, Fuel 85(12– 13) (2006) 1605–12 with permission of Elsevier.

and experimental results show a good agreement in terms of brake torque. Kitanovic et al. [111] employed the AVL BOOST IC software package to perform a parametric study with several engine displacements and excess-air-ratios. The limitations of zero dimensional models can be overcome by the use of more accurate multi-dimensional approaches. Gamino and Aguillon [112] employed a two dimensional model based on the solution of RANS equations with a relatively coarse numerical grid and validated their results with those obtained by Shridar [113] and Peters [114]. Fanelli et al. [115] solved the RANS equations on a much more refined grid, i.e., 570,000 grid points at TDC, and the numerical results were in very good agreement with measurements of Bika et al. [102]. More recently, STAR-CD v4.30 [116] has been employed for three-dimensional CFD simulations of an engine fueled with syngas. A good comparison with experiments was carried out although some improvements are still required as regards the blow-by and the ignition model. Further 3-D simulations were carried out by Kan et al. [117], who employed KIVA-4 code. The results show some discrepancies with measurements in terms of a fluctuating heat release rate and a wider combustion interval.

3.3 DISI engines Direct injection of syngas in a spark ignition engine can be an effective strategy to overcome all the above limitations. Indeed, the volumetric efficiency would improve if syngas was directly injected into the chamber, as an increased amount of air would be introduced into the engine during the intake process. Furthermore, the direct injection of fuel is able to extend the operating range of the engine to much leaner

4 The pollutants formation and emissions of syngas fueled-engines

operating conditions. Hence, a stratified charge is needed to guarantee the ignition of the mixture, i.e., a region with an approximately stoichiometric mixture where the spark ignition takes place. Finally, such stratification reduces strong temperature gradients along the cylinder walls, thus reducing the heat losses. Despite the advantages that can be achieved with such SI engines, a relatively few works are available in the literature as regards DI of syngas. An interesting work has been proposed by Hagos et al. [118]. They considered the direct injection of syngas in an engine and compared the results with those obtained by injecting natural gas. A syngas with 50% of hydrogen and 50% of carbon monoxide, in terms of volume fractions, was used and injected under lean conditions. A large amount of syngas was injected into the chamber to provide similar engine performances with respect to natural gas. Thus, most of the syngas injection took place during intake valve opening. As a result, a significant amount of air left the cylinder during the injection process, as it was replaced by the injected low-density gas. This problem had important consequences on the overall efficiency of the engine. A subsequent work of Hagos et al. [119] focused on the SOI timing effect on the engine performances. The start of injection was varied from 180° to 120° and 90° BTDC. Syngas composition was enriched by a volume fraction of 20% of methane to increase the heating value of the fuel. An increase of the volumetric efficiency occurred with a delayed injection. An increase of IMEP was obtained with the engine speed and with SOI equal to 180°. On the contrary, at high engine speeds, less fuel-air mixing was observed with SOI of 120° and 90° with a noticeable reduction of the engine performances. In Ref. [120], an interesting comparison has been carried out by employing different fuels: syngas enriched with methane (MES), pure syngas and natural gas (CNG). Fig. 9 shows that MES was able to provide the maximum torque and thermal efficiency of the engine. On the other hand, the same figure shows that the brake specific consumption was maximum by injecting syngas and minimum under CNG operating conditions, whereas was in between under MES operating conditions. Finally, Fiore et al. [121] analyzed the influence of the piston shape and injection specifics on the performance of a DISI engine fueled by syngas. Three different piston cup geometries and several included half-angles of injection were used. The SOI timing was also changed from 90° BTDC to 130° BTDC. The results show that the piston shape considerably influenced the stratification and, as a consequence, the outcome in terms of power output and thermal efficiency of the engine. However, this study was preliminary and a number of new configurations need to be investigated before drawing final conclusions. Further optimization studies are needed due to the high dependence on operating and geometrical parameters.

4. The pollutants formation and emissions of syngas fueledengines In order to reduce GreenHouse Gas (GHG) emissions, governments legislation is encouraging the use of low-carbon and zero-carbon fuels. Syngas is mainly composed of hydrogen and CO, so its combustion could lead to a reduction in GHG

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30 28 Maximum torque,Nm

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3 3.5 2.5 BMEP, bar MES Syngas

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FIG. 9 Maximum brake torque as a function of engine speed, thermal efficiency and brake specific fuel consumption (BSFC) as a function of brake mean effective pressure (BMEP) measured by Hagos et al. [120] with natural gas, syngas and methane-enriched syngas (MES). Reprinted from F.Y. Hagos, A.R.A. Aziz, S.A. Sulaiman, Methane enrichment of syngas (H2/CO) in a sparkignition direct-injection engine: combustion, performance and emissions comparison with syngas and compressed natural gas, Energy 90 (2015) 2006–15 with permission of Elsevier.

4 The pollutants formation and emissions of syngas fueled-engines

emissions compared to fossil fuels. For this reason, researchers are investigating the emissions of engines fueled with syngas and are comparing the results with those obtained by using conventional fuels, thus assessing if syngas could be a valuable choice in the transition toward a transport system consisting of electric vehicles and H2-based fuels. Syngas combustion in reciprocating engines leads to different types of emissions, which depend on the initial composition of the fuel mixture, on the design of the engine and on the operating conditions. If intensive syngas cleaning systems are used prior to fuel firing, emissions of sulfur gases, halogens, trace metals and fly ashes can be avoided [122]. In this case, NOx, CO and CO2 are the main pollutants to be monitored. A careful design of engine geometry and optimization of operating conditions should allow these emissions to be controlled, although CO and CO2 emissions are closely related to CO and CO2 syngas content. CO in the exhaust gas could result from unburnt syngas, incomplete oxidation of hydrocarbons in the syngas, and decomposition of lubricating oils. NOx emissions are generally enhanced by the high combustion temperature of synthesis gas. However, low-NOx combustion techniques could be effectively adopted to control NOx. Among these techniques, Exhaust Gas Recirculation (EGR) is an efficient strategy, which consists of recirculating a partial amount of exhaust gas, i.e., a mixture of N2, CO2 and H2O, into the engine chamber, thereby reducing the combustion temperature. Emissions from different types of syngas-fueled engines are examined in the following subsections.

4.1 Dual-fuel (diesel-syngas) CI engines In dual-fuel CI engines, the use of syngas as a partial substitute of diesel fuel results in a net reduction in CO and unburned hydrocarbons emissions under medium load conditions. As a matter of fact, as diesel is replaced with syngas, H2 content in fuel is increased, thus reducing CO and HC emissions [82,85,123]. Under high load conditions, several researchers [75,76,78,124] found an increase in CO emissions compared to standard diesel combustion, which is due to incomplete combustion. Some researchers [77,89,124] stated that the partial fuel oxidation is mainly due to the lack of oxygen. Specifically, in Ref. [124] the low density of the charge during intake led to a decrease in the oxygen content in the chamber during combustion. Optimization of engine geometry and of injector specifications could be helpful to achieve a more efficient combustion process. As regards NOx emissions, they are higher under PREMIER combustion mode, due to high temperatures. This is not the case when a one-stage combustion regime occurs [2,88,90,124] and the temperature in the chamber is lower, with a relevant reduction of NOx production with respect to conventional diesel engines. Since PREMIER mode is clearly favorable in terms of engine performance, specific strategies, as EGR and catalyst reduction, must be implemented to control NOx emissions. The optimization of injection could also help to reduce the temperature in the chamber.

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To this end, different strategies could be used and combined: early pilot fuel injection, injection of steam or water after the injection of pilot fuel, multiple injections in time and in space.

4.2 HCSI engines HCSI engines exploit their advantages under lean conditions. In these cases, lowtemperature combustion leads to low NOx and high CO emissions, so researchers are investigating new solutions to achieve a compromise between NOx and CO at the exhaust. In the scientific literature many works are devoted to compare the emissions of HCSI engines when they are fueled with syngas or with fossil hydrocarbons, such as gasoline, methane or natural gas. Emissions are strictly related to the composition of the fresh mixture and to the operating conditions used for carrying out the comparison, so different researchers provide different results [1]. Shah et al. [125] compared the emissions of an SI engine, which drove a generator, powered by syngas with those obtained by fueling the engine with gasoline at the same electrical power outputs. The composition by volume of syngas was 16.2– 24.2% CO, 13–19.4% H2, 1.2–6.4% CH4, 9.3–13.8% CO2 and the remaining was N2. Four values of the generator’s electrical power output were considered, which corresponded to four different syngas flow rates. In each case, emissions of CO and NOx were significantly lower for syngas than for gasoline, whereas CO2 emissions were 33–167% higher for syngas. These results are closely related to both syngas composition and engine operations. The carbon content of syngas is more than five times lower than that of gasoline, thus justifying the lower CO emissions. On the other hand, the overall efficiency of the engine under syngas operations is higher, thus explaining the more complete conversion of CO to CO2 than under gasoline operations. Finally, the differences in NOx emissions are probably due to the lower combustion temperature in the case of syngas. A different approach was employed by Dai et al. [107]. They produced syngas in a fuel reforming reactor by recovering the engine exhaust heat. Syngas composition (mainly H2 and CO) depended on the excess air ratio used for engine operations: H2/CO concentration increased/decreased when the excess air ratio increased from 1.01 to 1.36. The engine ran at 1800 rpm by employing gasoline or a mixture of gasoline and syngas, with a syngas volume fraction equal to 2.5%. Syngas blending improved the indicated thermal efficiency of the engine for all values of excess air ratio considered, but slightly increased both CO and NOx emissions. The differences with respect to gasoline operations were more pronounced at near stoichiometric conditions in terms of CO, for two motivations: on one hand, under this condition syngas was mainly composed by CO, on the other hand the oxidation of CO was less complete because the fast combustion of H2 consumed more oxygen than gasoline. Conversely, at very lean conditions syngas addition increased the combustion temperature, thus increasing NOx emissions with respect to gasoline. The same authors in Ref. [105] obtained a reduction of NOx emissions by blending gasoline with

4 The pollutants formation and emissions of syngas fueled-engines

syngas up to 1.84% by volume with a global excess air ratio equal to 1.2. In this case syngas was produced by using an onboard system for ethanol catalytic decomposition and contained a certain amount of ethanol, which led to a reduction of the combustion temperature, i.e., of NOx emissions. Besides, the reduction of oxygen concentration in the intake flow, when syngas flow rate was increased, further contributed to reduce NOx at the exhaust. Emissions obtained by using different fuels, i.e., E10-gasoline, natural gas, ethanol and syngas, under lean conditions were compared in Ref. [106], thus showing lower NOx emissions for syngas compared to E10-gasoline and higher compared to natural gas and ethanol. On the other hand, CO emissions were slightly higher for syngas when the equivalence ratio ranged from 0.7 to 0.8. Arroyo et al. [103] used catalytic decomposition of biogas (60% CH4 and 40% CO2 by volume) to produce two synthetic gases, composed by H2, CO, CH4 and CO2, which were then used in a SI engine. Syngas LHV was lower, but comparable, with that of biogas and was more than three times lower than that of methane. Engine operations, when it was fueled with syngas, gasoline, methane and the biogas from which syngas was obtained, were compared by considering different engine speeds and three values of equivalence ratio, corresponding to stoichiometric and lean mixtures. Under stoichiometric conditions, CO emissions obtained with syngas were comparable to those of gasoline fueled engine and were higher with respect to the case with methane and biogas. Under lean conditions gasoline was not examined, however for all the other fuels CO emissions considerably decreased with respect to the stoichiometric case. CO2 emissions were high especially for syngas, but also for biogas. Both CO and CO2 emissions could be explained by considering the initial composition of syngas and biogas. On the other hand, hydrogen content in syngas was crucial for NOx emissions: the syngas with 40% by volume of hydrogen led to more NOx than all the other fuels, whereas the syngas with 23% by volume of hydrogen led to less/more NOx than methane/biogas. As regards unburned HC emissions, several researchers agree on the benefit of using syngas. As expected, HC emissions are generally negligible in the case of pure syngas combustion [103,125], since syngas contains a very low amount of complex hydrocarbons. On the other hand, if syngas is blended with fossil fuels, incomplete hydrocarbons combustion could occur. Indeed, Dai et al. [107] found higher HC emissions by adding 2.5% of syngas to gasoline for λ higher than 1.21.

4.3 DISI engines In recent decades, direct fuel injection has been adopted in SI engines as it allows to increase the engine volumetric efficiency and to extend the operating range toward leaner conditions. Regarding emissions, lean conditions lead to a lower in-cylinder temperature, thus reducing NOx emissions. Hagos et al. [120] compared the emissions obtained by using syngas (50% H2 and 50% CO by volume), methane enriched syngas (MES), and natural gas in a direct injection spark ignition engine. At intermediate loads, the emissions obtained with

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the three fuels were comparable, although syngas and MES gave lower NOx emissions and higher CO emissions. At high loads NOx emissions increased for syngas and MES. Besides, syngas and MES allowed stable combustion even at low loads, although in this case CO emissions increased significantly. The same authors in Ref. [119] showed the effect of injection timings on emissions: CO, NOx and unburned HC emissions worsened by delaying the injection timing, especially at high engine speeds. A numerical analysis was performed by Fiore et al. [121] to study the effects of injection characteristics and piston geometry in a syngas-fueled DISI engine. In all cases, a decrease in CO corresponded to an increase in NOx. Specifically, the omega cup in the piston minimized CO and maximized NOx. New configurations and solutions should be explored to solve the trade-off between NOx and CO emissions.

5. Concluding remarks and future research This work provides an overview on the use of syngas for internal combustion engines over the last few decades. It is well known that internal combustion engines are considered valid devices for the production of mechanical and electrical energy. These engines require the use of increasingly green fuels to meet the countless environmental problems of our century. An interesting strategy concerns the use of syngas, which is often obtained from the disposal of plastic waste and scraps, or derives from waste from the agri-food industry. In this context, syngas-powered engines can be considered ecological and sustainable engines. The use of this fuel requires a differentiated energy vision, which looks at a reduction in energy transport costs. In fact, energy could be produced locally in rural areas or small communities that offer an adequate supply of raw materials to energy generation systems. This new energy policy can have important social and economic implications. The use of syngas in electricity production plants is currently substantially limited to energy recovery purposes. New plant strategies, linked to what is now called circular economy, provide for on-site energy recovery from waste materials. In other words, industries could use a waste disposal gasification system to produce synthetic gas, thus reducing external energy demand. On the other hand, by selecting a specific syngas composition, it could also significantly reduce emissions of harmful gases into the environment, with particular attention to greenhouse gases and unburned hydrocarbons. In internal combustion engines, all this is achieved through an appropriate tuning of the engine operating parameters. In light of these advantages, the use of syngas in internal combustion engines has been extensively studied in the literature. Among the different types of engines, dualfuel engines have interesting applications thanks to their lower power derating compared to spark ignition engines with syngas. These engines allow a high diesel fuel

5 Concluding remarks and future research

saving. To further improve their efficiency and reduce emissions, appropriate strategies can be used, such as exhaust gas recirculation, reactivity control based on multiple injections, premixed combustion of the end-gas region. However, the presence of two distinct fuel supply lines poses problems related to the storage and transport of fuels. Furthermore, it is necessary to pay attention to transient and fault situations, as well as to anomalous conditions relating to one of the fuel supply lines, also considering the variability of the syngas composition. Recently, several works are aimed at analyzing and optimizing these engines with numerical techniques and advanced modeling. Unlike dual-fuel engines, homogeneous charge spark ignition engines suffer, when fueled with syngas, from a more marked reduction in power than when they use gasoline or natural gas. This power derating is a consequence of the low heating value and of the reduced volumetric efficiency of syngas, which can only be partially counter-balanced by the increase in the compression ratio. It is however interesting to observe that, with syngas, extremely lean conditions become feasible and this contributes to the reduction of nitrogen oxide emissions. One strategy to improve the performance of these engines is to use turbocharged and supercharged SI engines, which have been considered in a limited number of works. In particular, the use of supercharging involves new studies to avoid engine knocking with a careful selection of compression ratios and equivalence ratios to be used to avoid detonation. A promising alternative to overcome the problem of low volumetric efficiency is the use of direct injection of syngas into the combustion chamber. This strategy also allows to reduce heat losses and improve the combustion process. However, studies are needed to select the optimal injection and ignition timings. Furthermore, very long injection durations represent a limit to the actual use of syngas. A possible solution is the use of injectors specifically designed for syngas injection, which include multi-holes injectors with large injection sections. Another possibility is the increase of the injection pressure. To this end, new experimental and numerical analyses are needed to study the charge stratification and the consequent combustion process depending on the composition of the syngas under examination. An economic analysis will also be required to compare the direct injection of syngas into the combustion chamber with the injection of other fuels. It can be observed that, for all types of engines, most of the studies are limited to syngas compositions with a relatively small number of chemical species. More detailed studies are therefore required to obtain accurate results, by means of the use of optimization methods with a larger number of species. Finally, it can be concluded that syngas technology seems to have reached an important level of technical development. The final purpose of syngas powered engines is to optimize their operating conditions and to get, in the near future, accurate experimental and numerical tools for research and development work on syngas in the automotive industry.

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Conflict of interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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CHAPTER

Hydrogen, the zero carbon fuel

6

Jai M. Mehtaa, Fokion N. Egolfopoulosb, and Kenneth Brezinskya Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, United States, bDepartment of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA, United States

a

1. Introduction With the increase in global climate change, moving to clean and sustainable sources of energy has never been more needed. Among several factors, greenhouse gases that control the earth’s temperature are the primary sources for the rise in global temperatures. Methane (CH4) and anthropogenic carbon dioxide (CO2) from the burning of fossil fuels are the largest contributors to the greenhouse effect. Decarbonizing energy sources is required to reduce or eliminate the carbon-based emissions and ensure that the average global temperature rise is limited to 2 °C until the year 2050 [1]. An alternative carbon free source of energy which will not degrade the environment is needed, particularly for transportation systems because they are currently highly dependent on carbon-based fossils [2]. Hydrogen (H2), a carbon-free fuel based on its molecular structure, has a very high potential to be a replacement fuel owing to its high energy content by mass compared to any other fuel [2]. Also, H2 is widely available on earth as a part of water and can be separated using several methods, some of which can be considered sustainable. H2 combustion produces water that while it is a greenhouse gas it does not contribute to climate change since water in the atmosphere is generated in notably larger quantities via nonanthropogenic evaporation from oceans, lakes, and rivers [3]. This is not the case for carbon dioxide. The positive incentives for moving to a carbon free fuel source have motivated new interest in H2-powered internal combustion engines for road transportation. Interest in H2 for aviation also has increased and investigations of its viability for powering aviation gas turbines have grown in number (Ref. [4] and references therein). Nevertheless, aviation gas turbine uses of H2 are still in the exploratory stages and less developed than for road transportation. Although using H2 in reciprocating internal combustion engines for road transportation was studied and implemented on a small scale as early as the 1930s [5], Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00011-4 Copyright # 2023 Elsevier Inc. All rights reserved.

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more recent studies and implementations were driven by the aftermath of the oil crisis and eventually lost momentum as the global oil market recovered over the end of the 20th century. Using H2 as an internal combustion engine fuel also posed technical problems such as increased chances of knock and backfire when compared to gasoline and diesel engines. Pre-ignition related problems have been also observed for compression ignition (CI) engines and the diminishing need to transition to H2 as a fuel source slowed down the investigation of these problems [6]. The “Hydrogen Economy” is a system where H2 assumes the role of the primary source of energy and along with electricity helps move toward zero-carbon emissions to mitigate the global climate crisis [7]. Several attempts have focused on the transition to a hydrogen economy worldwide. Ajanovic and Haas [8] have studied the prospects of moving to H2-powered vehicles and examined impediments to this transition in detail. Sehgal et al. [9] investigated performance improvements of natural gas (NG) engines by H2 addition and Manoharan et al. [2] studied the prospects of fuel cell vehicles (FCV) as a replacement for conventional combustion powered engines. Candelaresi et al. [10] have provided a detailed comparison between various technologies available to introduce H2 into the transportation industry. While substitution of H2 as a fuel for combustion engines is a practical solution since it would lead to zero “well-to-wheel” emissions unlike electricity powered vehicles which can only ensure zero “tank-to-wheel” emissions, it comes with combustion challenges. As an alternative to combustion, H2 fuel cells can provide the simplicity of use with H2 as a day-to-day transportation fuel, but large-scale adoption of fuel cells is impeded by slow technological advancements. However, in recent years research progress in H2 fuel cells (FC) has dramatically increased. H2 fuel powered vehicles running on fuel cells are capable of zero carbon-based harmful tailpipe emissions. While these vehicles are currently not accessible to most people, it has been estimated that by 2030 the cost of these vehicles will be at par with internal combustion engine based vehicles [2]. These fuel cell vehicles actively compete with battery electric vehicles [BEV] in the research community as well as for widespread consumer adoption. While BEVs also promise zero tailpipe emissions, one needs to be mindful of the source of electricity generation since currently over 60% of electricity generation in the world is dominated by fossil fuel based powerplants [11]. The unambiguity in the net zero emissions certainly makes H2 a more reliable zero emission fuel source for the future transportation systems. In exactly what type of propulsion device it will be used, however, remains to be seen. The use of H2 has not been limited to ground transportation applications but also has been widely studied and used as a propellant for space missions. In cryogenic states, liquid H2 can form energetic mixtures with certain other gases [2]. H2 when oxidized only generates water and the energy release from this reaction is extremely large. However, kerosene-based propellants have replaced H2 in recent decades because they are more economical and easier to handle and store even though they contribute significantly to emissions of pollutants and greenhouse gases because of their high carbon content. The concern about carbon-based emissions from spacecrafts is often disregarded owing to the rarity of space flights. However,

2 Hydrogen internal combustion engines for road transportation

if space travel is to become a day-to-day event in the future, then considerations need to be made for controlling emissions from space missions as well. The benefits of moving to a hydrogen economy make it a promising prospective for a cleaner and greener future. There are, nevertheless, several consequences, technical and political, that need to be overcome for universal adoption of H2 as a source of energy. Some of them are described in the following sections.

2. Hydrogen internal combustion engines for road transportation Making a shift to engines powered by H2, particularly from renewable sources such as steam regeneration or electrolysis using renewable electricity [8,12,13] is a more realistic path to a zero-carbon future in the short term when compared to the global electrification of transportation. The shift to electrification of the transportation sector would require significant investment in infrastructure development such as charging stations, new power lines, and battery availability. The successful transition to an electrified transport system is only possible if the infrastructure developments and technology can keep up with the growing demand. These infrastructure development costs, both economic and environmental, are significant and in the short term, will reduce the net benefits of the transition. The transition to H2 as a combustion fuel will not significantly burden infrastructure development and modification, unlike for electrification. The greatly reduced infrastructure burden should allow for a swift, economic, and environment friendly transition to H2 fuel. Unlike charging stations needed for electrification, fuel pumps needed for H2 are a well-established technology. Benefits like infrastructure availability can be realized when moving to H2-powered reciprocating internal combustion engines because modification of engines currently on road is a relatively simple and swift procedure. Utilization of H2 in combustion-based powertrains eliminates the primary fuel generated emissions of particulate matter, unburnt hydrocarbons (HC), carbon monoxide, and carbon dioxide [6], which are regulated by the EPA and are major greenhouse gasses (GHG). In addition to emission benefits, H2-powered vehicles provide very high efficiencies when compared to gasoline powered engines and have driving cycle efficiencies of up to 35% when combined with hybrid power trains [6]. There are several ongoing studies [2,9,13–20] focusing on the introduction of H2 as a chief fuel source for land transportation, and they range from modification of available engine technologies to adapt to H2 to the development of new novel systems like H2 fuel cells and solid state storage of H2. The vast knowledge developed over the last few decades for using natural gas and petroleum gas (mainly propane, butane and propylene) as fuels for transportation applications can be very well extended to H2-fueled engines. Modern designs of these engines can allow for bi-fuel operation between H2 and NG—which is another promising fuel achieving notably reduced carbon emissions.

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The significant improvements the bi-fuel operation of internal combustion engines has resulted in an interest in hythane [21] which is a mixture of 10–30% H2 and 70–90% NG. Hythane can be prepared by mixing H2 generated using electrochemical processes, ideally powered by renewable energy sources and biogas from organic waste, making hythane a sustainable and clean source of fuel. The addition of H2 improves the operation of the NG/CH4 engine significantly and reduces emissions. Sehgal et al. [9] carried out experimental studies on engines operating on such blends of H2 and NG and they observed up to an 18% increase in engine power and up to 20% reduction in hydrocarbon emissions. Hythane has the added benefit of being able to be transported using the existing NG infrastructure. While hythane does not promise zero emissions, it certainly demonstrates the significant advantage of using H2 even in small quantities to achieve a greener, possibly carbon-neutral future. Interest in purely H2-fueled engines was at the peak in the first decade of 21st century. One of the most notable examples was the BMW Hydrogen 7 [6,22] engine which was produced for vehicles but only in a limited run. The engine was used in road cars built by BMW and was a dual fuel engine using both H2 and gasoline. It had a 6 L V-12 engine with liquid H2 injected into the cylinder that was ignited using both spark and compression ignition processes. A growing interest in H2-fueled IC engines extended to compression ignition (CI) engines in which H2 was introduced as the fuel for heavy duty applications [23]. While it was claimed that the engine had zero emissions, it was not accepted by the EPA since emission measurements often resulted in appreciable amounts of regulated emissions from the exhaust [22]. These emissions were a result of the burning of lubrication oil that was introduced into the combustion chamber through clearances in moving parts of the engines as well as through direct decomposition of the lubricants by large amounts of heat that was generated by the hydrogen combustion in the cylinder. The observation of these emissions slowed the development of H2-fueled engines since the primary goal of no emissions was not met, and the cost of further development could not be justified. Verhelst et al. [5] undertook a relatively recent review study to understand the problems faced by H2-fueled spark ignition (SI) engines and possible solutions to them. They claim that there is a possibility of achieving indicated efficiency of a H2-powered SI engines of up to 52% which is significantly higher than conventionally fueled internal combustion engines. In addition to added efficiency by using H2, there is the fact that the emissions from these engines are limited to NOx with zero carbon emission. However, in one study it was observed that up to a 20% increase in NOx emissions was observed with just 18% H2 added to NG-powered engines [9]. The generation of NOx in purely H2-fueled engines at stoichiometric conditions is significantly higher compared to gasoline engines [17]. However, with H2 as the fuel, NOx emissions under 10 ppm can be achieved while maintaining indicated efficiency up to 50% with a planned load control strategy [5]. The Verhelst et al. study [5] also pointed out several common problems faced in H2 engines like knock—auto-ignition of the charge following compression, pre-ignition—uncontrolled premature ignition of the charge usually resulting from

2 Hydrogen internal combustion engines for road transportation

hot spots and backfire—ignition during the intake stroke resulting in flashback [5]. H2 requires significantly lower ignition energy [5] than hydrocarbon fuels, which makes it more susceptible to pre-ignition from hot spots and residual combusted gases. Additionally, the low concentration of ions in H2-air flames results in residual energy in the charge which can ignite later such as during the intake stroke causing backfire [5]. The backfire problem can be mitigated by reducing the compression ratio to reduce the combustion chamber temperature which would avoid occurrence of hot spots in the system. The converse is also true to mitigate backfire—increasing the compression ratio leads to higher temperatures resulting in more efficient heat transfer to the cooling system which would quench the charge and prevent uncontrolled ignition. The higher compression ratio also improves the efficiency of the engine. It is suggested that the knock phenomenon in hydrogen engines is a result of the high flame speeds of H2 and not end gas reactions, hence reducing the rate of pressure rise in the cylinder would help mitigate the knocking phenomena [5]. Sehgal et al. [9] on the other hand praise hydrogen for a high auto-ignition temperature, since it allows for operating these engines at high compression ratios, which improves efficiency. Despite the high self-ignition temperature of H2, it requires significantly lower ignition energy of about 0.02 mJ [9] which makes it suitable for compression ignition engines. Introduction of H2 into the engines can be done using various methods like carburetion, port injection, and direct injection very effectively. Boretti [6] undertook a detailed review of various H2 engine configurations—dual fuel, bi-fuel, and H2 only internal combustion engines. H2-fueled engines operating with a port fuel injection set-up and turbo charger were capable of efficiencies above 40% even when operating under fuel lean condition (λ
2 to 4) [6]. The peak efficiencies can be further improved using direct injection strategies to above 45% along with improved efficiencies at part loads. Each of these engine types provide a promising benefit toward reducing emissions and improving performance and facilitates moving to a zero carbon emission transportation system. There are several research directions being pursued which can help bring hydrogen fueled engines to a more practically useable state. For example, advances in tribology over the last decade can help solve the problem of lubricant contamination in the combustion chamber and make H2-fueled engines truly zero emitting, but further work is necessary. Further research on heat transfer in H2-fueled engines is needed because there is a larger amount of heat generation resulting from H2 combustion when compared to conventional fuels. The larger amount of heat generation results in greater heat loss in cooling and exhaust gases and additional techniques need to be employed to minimize these loses and maximize the overall efficiency of the engine. Exhaust Gas Recirculation (EGR) and turbocharging can help utilize the heat lost in exhaust gases. Additionally, H2-fueled engines operating at higher compression ratios [9], as previously mentioned, can realize larger benefits of recuperating heat energy from exhaust gases. While these aforementioned studies, and many others available in the literature, have concentrated on the practical problems of using H2 as a fuel and have proposed some solutions, relatively little has been done focusing on the fundamentals of H2 combustion in the engines. In one relevant example,

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Verhelst and Wallner [24] carried out a scientific analysis of H2 fuel engines indicating the effect of critical physicochemical properties on H2 combustion. It is largely assumed that laminar flames exist in the combustion chamber, however several mechanisms can introduce flame instabilities under engine-relevant conditions. The understanding of H2 combustion, particularly laminar flame speeds, at the scientific level is necessary for the successful implementation of H2-fueled engines.

3. Propagation of hydrogen flames The utilization of H2 or its blends with NG is expected to play a major role in reducing CO2 emissions from industrial gas turbines used in power generation and from land transportation engines. Currently, the optimum and efficient utilization of these fuels, H2 and NG, is hampered by an insufficient understanding of the combustion fundamentals, especially given their rather different combustion characteristics. Autoignition, flashback, flame stability, and emissions are among the key operating considerations that need to be addressed. To this end, fundamental flame property experiments and reaction kinetic mechanism (model) development and uncertainty minimization are critical to developing rational strategies for their utilization. Additionally, for such data to be useful they need to be determined at engine-relevant conditions, that is at pressures up to 30–50 atm and temperatures up to 700–800 K. At such conditions, reliable fundamental combustion properties of H2, NG, and their blends range from being scarce to non-existing. As a consequence, the capabilities of existing combustion models have limited predictability and notable extrapolations may be needed for computational fluid dynamics (CFD) under engine conditions. Additionally, no length, time, and velocity flame scales are available that could be used in modeling of turbulent combustion at realistic conditions. Chemical kinetic mechanisms are developed based on kinetic experiments, such as shock tubes, flow reactors, and rapid compression machines (RCM), supplemented by a range of theoretical methods from ab initio electronic structure calculations to reaction rate theory calculations as mentioned in the next section. Historically, the validity of these mechanisms is tested against fundamental combustion properties such as ignition delay time (IDT) and species time histories. Importantly, for mechanisms to be used in the CFD of combustors, they must be tested also against fundamental flame data, including flame structures, laminar flame speeds (Sou), and extinction strain rates (Kext) so that transport effects are account for. Sou relates directly to the heat release rate, while Kext is a measure of the extinction propensity that affects combustor stability. In addition to its heightened sensitivity to reaction kinetics, Kext is also sensitive to the mass and heat diffusivities as manifested classically by the Lewis number (Le). Measuring fundamental laminar flame properties at engine-relevant conditions is associated with a number of challenges especially under premixed conditions. Historically, flame structures and Kext can only be measured in steady, continuous flow burner configurations such as burner-stabilized and counterflow flames (CF). The limitation of these configurations is that the measurement can be conducted for

3 Propagation of hydrogen flames

low Reynolds numbers only, and flame structures cannot be resolved for pressures significantly larger than 1 atm because the flame thickness is well below 100 μm. Currently, Kext measurements are limited to pressures below 10 atm due to the Reynolds number limitation—the flow transition to turbulence initiates above that pressure for typical burner setups. Sou can be measured similarly to Kext in the CF configuration up to 10 atm. The spherically expanding flame (SEF) method, on the other hand, elevates the accessible pressure range to well above 10 atm [25]. Measurements of Sou using the SEF method can be carried out in either the constant pressure (SEF-CONP) or constant volume (SEF-CONV) condition. During an SEF experiment, the thermodynamic pressure remains nearly constant for flame radii up to about 70–80% of the (spherical) chamber radius. It increases thereafter due to isentropic compression that also results in the preheating of the unburned end gas. Both the SEF-CONP and SEF-CONV methods can be implemented to measure Sou for engine-relevant conditions, and details can be found in, e.g., Refs. [26–29]. Kext and Sou data in general and especially at high pressures and temperatures are not only necessary for testing and validating kinetic models, but they also serve as the key optimization targets during kinetic model development: • •

• •

Model tests against Kext and Sou data offer a key platform for testing model assumptions and model parameter choices. The Kext and Sou data have been historically used as the optimization targets or the training set for reaction model optimization (e.g., the GRI Mech [30,31]) and uncertainty minimization [32]. The Kext and Sou values exhibit heightened sensitivities to reaction kinetics as pressure increases. In turbulent flames the sensitivity to reaction kinetics can be greatly amplified due to local flame extinction and re-ignition processes [33].

For these reasons, the availability of accurate flame data is critical to reaction mechanism optimization, uncertainty minimization and reliable application in CFD simulations of practical combustors operating at elevated pressures. As mentioned earlier, high-pressure flame data are scarce. Among the 46 experimental studies of Sou for H2 flames [34–77], only 5 investigations were made for P > 10 atm [28,38,58,69,73]. The lack of high-pressure flame data poses a significant challenge to kinetic model development. The rate parameter uncertainties and especially those of pressure dependent reactions remain to be too large to make accurate flame predictions a priori [78]. In a recent study [79], it was shown that kinetic models that were capable of predicting Sou up to P ¼ 15 atm failed to reproduce the data above 20 atm by a significant margin. Clearly, while low-pressure data are abundant, models exhibit only a modest sensitivity to the flame properties at low pressures. The sensitivity increases nearly linearly with pressure (for example, for the laminar flame speed of a stoichiometric H2-air flame, the logarithmic sensitivity coefficient to the H + O2 ¼ O + OH reaction rate coefficient is calculated to be around 0.1 at 1 atm, and 0.9 at 80 atm). H2-rich mixtures also exhibit complex, multiple explosion-limit behaviors, resulting in non-monotonic response of the mass burning

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rate m_ ou ≡ρu Sou (where ρu is the density of the unburned mixture) to pressure and possibly negative overall reaction orders [55]. If during the transition period H2 had to be used along with NG, the current knowledge of the flame response of H2/CH4 blends to pressure is rather limited. In summary, it is apparent that the scarcity of highpressure data and the historical low-to-high pressure extrapolation approach fundamentally hinders model development [54]. Regarding Sou data accuracy, H2 flames are associated with a number of challenges stemming from the particularly large diffusivity of H2 relatively to any other species due to its very low molecular weight. When air is the oxidizer, fuel-lean H2 flames are highly unstable due to the development of thermal-diffusional instabilities caused by the very low Le values of such mixtures (e.g., Ref. [54]). For mixtures that are near-stoichiometric or fuel-rich the notable differential diffusion between H2 and O2 will lead to flame structure modification under the influence of stretch that is unavoidable in most experiments (e.g., Ref. [80]). A literature search of Sou data for H2/air flames at atmospheric conditions has revealed a notable scatter that cannot be attributed to simply experimental errors but rather to the interpretation of the directly measured quantities [81]. The data scatter is shown in Figs. 1 and 2 along with 1σ (68.3%) and 2σ (95.5%) confidence interval bands. In Fig. 1, the data are shown as a function of the equivalence ratio, ϕ, and H2/air, Tu = 298 K, p = 1 atm

300

250

Flame Speed, su cm s

156

200 Burke et al 2012 Hu et al. 2009

150

Tang et al. 2008 Huang et al. 2006 Lamoureux et al. 2003

100

Kwon and Faeth, 2001 Tse, Zhu and Law 2000 Aung, Hassan ane Faeth

50

Vagelopoulos et al. 1994 Taylor 1991 0

0

1

2

3

4

5

Equivalence Ratio, FIG. 1 Experimentally determined (symbols) and computationally predicted (solid line) for hydrogen/ air mixtures at 1 atm pressure and 298 K unburned temperature as a function of the equivalence ratio, φ. The dotted and dashed lines represent the 1σ (68.3%) and 2s (95.5%) confidence interval bands, respectively [81].

4 Hydrogen-oxygen combustion mechanism overview

Flame Speed, su cm s

300

H2/air, Tu = 298 K, p = 1 atm

250

200

150

100

50

0 0.2

0.3

0.4

0.5

0.6

Normalized Equivalence Ratio,

0.7

0.8

0.9

1

FIG. 2 Variation of experimental (symbols) and computed (solid line) Su with the normalized equivalence ratio, φ. The legend is the same as that of Fig. 1. The dotted and dashed lines represent the 1σ (68.3%) and 2σ (95.5%) confidence intervals of the data, respectively [81].

this representation enhances the scatter on the fuel-rich side. In Fig. 2, the data are shown instead as a function of a normalized equivalence ratio ϕ defined as ϕ≡ϕ=ð1+ ϕÞ that enhances the scatter on the fuel-lean side. The results shown in Figs. 1 and 2 illustrate the challenges associated with the measurement of Sou for H2 flames even under atmospheric conditions that present notably less experimental challenges compared to engine-relevant ones.

4. Hydrogen-oxygen combustion mechanism overview

The discussion in the preceding section highlighted the challenges in obtaining Sou, which are necessary for modeling combustion systems containing H2. The modeling of the combustion of H2 is, of course, dependent on the chemical kinetic H2/O2 mechanism. In fact, the mechanisms are critical to not only the H2/O2 reacting system but also to all combustion systems that involve H2, most of the time as atoms contained in molecules of the fuel. The importance of the H2/O2 mechanism has led to an extremely large number of studies of it, which have included not only developments of the mechanism but, necessarily, experimental validation as well. In 2014, Olm et al. [82] published a comprehensive review of nineteen relatively recent mechanisms in comparison to their predictions of data from ignition measurements in both shock tubes and RCMs, and data

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300

1 2 3 4 5 6 7 8 9 14 10 11 12 13 14 15 16 17 18

200

Overall average error function value

100

60 50 40 30 20 10

Kéromnès-2013 NUIG-NGM-2010 ÓConaire-2004 Konnov-2008 Li-2007 Hong-2011 Burke-2012 SaxenaWilliams-2006 Davis-2005 Starik-2009 USC-II-2007 CRECK-2012 SanDiego-2011 GRI3.0-1999 Sun-2007 Rasmussen-2008 Ahmed-2007 Zsély-2005

18

no He 17

all data: 1535 data points 145 datasets

16

selected data: 1215 data points 115 datasets

15

13

11

9

12

10

8 5

3

4

6

7

2 1

3s limit

20 13

20 11

20 09

20 07

20 05

20 03

20 01

0 19 99

158

Year

FIG. 3 Overall performance of the mechanism taking into account all experimental data (black full square) and only those that were reproduced by at least one mechanism with Ei  9 (green open square) vs, year of publication. All diluents except He [82].

about species concentration profiles from flow reactors, jet-stirred reactors and lastly from Sou measurements (note the relevance to the preceding section on Sou). The conclusions from their exhaustive studies are essentially summarized in Fig. 3 for eighteen mechanisms [31,83–99], after one mechanism had been excluded because of diluent considerations. Fig. 3 illustrates that based on all the data points, five mechanisms (1–5 in the legend and shown as black squares) yielded the lowest error function value, where the error function is a measure of the difference between the model simulated data value and the experimental value. Once the data were further curated to exclude data measurements that could not be simulated by any mechanism within an uncertainty of three standard deviations, only two mechanisms, numbers 1 and 2 in the legend, yielded an average agreement with the data of less than or equal to two standard deviations, the figure of merit used in this study. These two mechanisms denoted as Keromnes 2013 [83] and NUIG-NGM-2010 [84] would seem to be the definitive mechanisms of choice for use in H2/O2 studies, especially Keromnes et al. 2013 [83] because of its application specific success such as for IDT and Sou. Keromnes et al. [83] developed their H2/O2 mechanism as part of a larger study of the oxidation of H2 and syngas (H2 + CO) mixtures involving extensive RCM, shock tube and Sou data. In the course of their study, they optimized the H2/O2 mechanism in

4 Hydrogen-oxygen combustion mechanism overview

τign= t([OH(A)]max) / ms

2000 K 100

1667 K

1429 K

1250 K

1111 K

1000 K

909 K

H + O2 (+M) = HO2 (+M)

10

RCM 1

H + O2 (+M) = HO2 (+M) H2 + HO2 = H + H2O2

Shock Tube

0,1

H + O2 = O + OH

0,01

1E-3 5

6

7

8

9

10

11

10000 K / T FIG. 4 Main reactions as functions of temperature regime for a mixture of 0.7 H2 + O2 + 3.76 Ar tested with the present mechanism at 8 bar (black dashed line), 16 bar (red solid line) and 32 bar (blue dot dashed line) [83].

part by studying pure H2/O2 in argon and/or nitrogen. Fig. 4 illustrates the dominant H2/O2 chemical reactions that control ignition at the conditions of the study. Fig. 4 along with the Fig. 5, the sensitivity analysis of the mechanism as a function of pressure, clearly indicate important reactions in the mechanism and serve as the basis for the close examination of their rate parameters as discussed in the paper [83]. It would seem clear from the analyses of Keromnes et al. and the success of their updated model as verified by the study of Olm et al. [82] that a definitive mechanism for the H2/O2 reacting system had been finally arrived at by 2014. Nevertheless, as documented in Jin et al. [100], as of mid-2021, at least 10 additional new or updated H2/O2 mechanisms [93,101–109] have been offered since 2014. In some cases, these were further revised versions of mechanisms and in others more involved optimization techniques were used. One reported revision by Konnov entitled “Yet another kinetic mechanism for hydrogen combustion” [107] appears to say it all, at least as of 2019. An intriguing aspect of the Konnov work is that it attempts to add, in a sense, new science to H2/O2 mechanism development. The newly recognized potential importance of termolecular reactions [107] at high radical concentrations was addressed by Konnov through the inclusion of four reactions identified by Burke and Klippenstein [99] to be significant. The four reactions are: H + O2 + H $ H2 + O2

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4 3 Sensitivity coefficient

160

2 1 0 -1 -2

(R1) H + O2 = O + OH (R2) O + H2 = H + OH (R9) H + O2 (+M) = HO2 (+M)

-3

(R11) HO2 + H = OH + OH (R14) HO2 + HO2 = H2O2 + O2 (R15) H2O2 (+M) =OH + OH (+M)

-4

(R17) H2O2 + H = H2 + HO2

1

10 Pressure / atm

100

FIG. 5 Sensitivity analysis of ignition time delays as a function of pressure at 1000 K for the present mechanism (mixture: H2/O2/N2/Ar ¼ 1/1/1.88/1.88). Only seven most sensitive reactions are included [83].

H + O2 + H $ OH + OH H + O2 + O $ OH + O2 H + O2 + OH $ H2 O + O2

When Konnov added these four reactions along with their rate parameters as calculated by Burke and Klippenstein to his mechanism developed in 2015 [106], comparison with Sous for H2/air mixtures showed no improvement due to the addition of the reactions. This observation led Konnov to “revisit other parameters of the kinetic mechanism for H2 combustion in an attempt of improving its accuracy while including chemically termolecular reactions.” The result of revisiting the other parameters was yet another mechanism, as the article title promised, along with a highlighting of the importance of transport parameters when simulating Sou. Konnov identified a set of transport parameters developed by Jasper et al. [110] as critical to successful modeling of Sou. The combination of updated rate parameters and transport parameters instituted by Konnov led to results of improved predictions of Sous for a variety of data sets. These results further led Konnov to conclude that for flame modeling the incorporation of termolecular reactions along with updated rate parameters and updated transport parameters were important. His conclusion has special significance for the condition for which

4 Hydrogen-oxygen combustion mechanism overview

chemical kinetic models are developed because he also showed that just the inclusion of termolecular reactions and updated rate parameters did not significantly improve the prediction of ignition in flow reactors. Furthermore, Konnov’s updated H2/ O2 model’s predictions when compared to those of the model of Keromnes et al. [83] and Konnov’s own model from 2015 [106] demonstrated about the same level of prediction of IDTs from RCM data. It would seem, based on the Konnov work, that a definitive, more comprehensive mechanism for H2/O2 combustion had been arrived at and which did not significantly differ from the previously recommended mechanism of Keromnes et al. [83]. Perhaps then, it might be surprising that Jin et al. [100] in 2021 found different mechanisms, albeit related to previous ones, to be most predictive of their RCM results. The Jin et al. [100] RCM experiments were a little bit different than other RCM ones in that they focused on varying argon/nitrogen diluent ratios in an attempt to investigate the argon power cycle (APC). The argon power cycle is one in which the working fluid is primarily argon leading to improved thermal efficiency and reduced emitted NOx. They obtained extensive ignition delay data. With the extensive IDT data from the RCM, comparisons with predictions from H2/O2 chemical kinetic mechanisms were made. The mechanisms used for comparison with data were the top 7 from the Olm et al. study [83–87,98,99] which included the Keromnes et al. mechanism [83], and also the 10 mechanisms published since 2014 [93,101–109] which included among them the 2019 Konnov mechanism [107] with termolecular reactions. The authors concluded that the best mechanisms for predicting their results did not include the previously recommended Keromnes et al. [83] mechanism but instead a 2015 update of it, designated Vargas et al. [105] and did not include the Konnov mechanism but instead a mechanism from Li et al. [87] also from 2015. Perhaps it is encouraging that at least one of the recommended mechanisms, Varga et al. [105], had a connection to the previously highly recommended Keromnes et al. [83] mechanism. The authors also concluded that depending on the temperatures and pressures the following reactions, consistent with the original Keromnes et al. [83] sensitivity analysis, were indeed the most sensitive for their RCM data. H + O2 ð + MÞ $ HO2 ð + MÞ H + O2 $ O + OH 2OH ð + MÞ $ H2 O2 ð + MÞ H + H2 O2 $ H2 + HO2

The implication of these reactions being the ones to which the predictions are most sensitive for RCM data but also for a wide range of other data as described in Keromnes et al. [83] is that definitive determination of their rate parameters is probably necessary to be able to converge on a final H2/O2 mechanism. An attempt at a definitive determination of rate parameters was undertaken by Yang et al. [111] in

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late 2021. The authors contended as a basis for their analysis that all the major mechanisms for H2/O2 reactions contain the same 9 species and 21 reactions. If the species include H, H2, O, O2, H2O, OH, H2O2 and HO2, which all the models contain, there would be eight. Some models include ozone, O3, making the total nine. Additional species, which enter in evaluations of third body (M) efficiencies, include for most experimental validation data, Ar, He and N2. Models containing these species typically do have approximately 21 reactions depending on whether or not the developers include reactions deemed irrelevant [106]. The original Keromnes et al. [83] model has 19 listed reactions and the Yang et al. [111] set of reactions consists of 20 listed ones. Some H2 combustion mechanisms include excited species reactions and ozone reactions [106] but for thermal systems with no added excited species these additional reactions contribute negligibly to the predictions. Therefore, the evaluation of the set reactions selected by Yang et al. [111] appears to be a reasonable step in arriving at “yet another” H2/O2 mechanism. Yang et al. [111] applied uncertainty weighted statistical analysis of the elementary reactions in the H2/O2 mechanism to account for the data sources, thermodynamic and mixture composition experimental conditions, biased data due to sampling techniques, and lack of data at critical conditions. The authors also point out that since some experimental data for rate parameter evaluation comes from IDTs, Sous, RCMs, and jet stirred reactors, there could be systematic errors associated with the indirectly derived data from these experiments. The authors instead use more directly derived data from shock tubes, flow reactors, and high-level theoretical calculations. The result is a set of evaluated rate coefficients for the twenty reactions in the H2/O2 mechanism to be used for modeling. When data from flow reactor experiments is indeed modeled with the statistically evaluated rate parameters, excellent agreement is obtained as is evident in Fig. 6. Note however that the sensitivities shown in Fig. 6B do not contain two of the reactions found by Jin et al. [100] to be important in their RCM work and three of the reactions showing sensitivity in Fig. 6B did not show sensitivity in the Jin et al. [100] work indicating, as discussed in many articles, the importance of experimental conditions on the relative role of different reactions in the H2/O2 chemistry. The comparison with flow reactor species data provided by Yang et al. [111] and the sensitivity of the predictions to different reactions as a function of experimental conditions are suggestive of the ultimate test of a mechanism—can it simulate the data from high quality experiments at conditions of interest. Of relevance to H2 as a carbon neutral fuel, the experiments of importance to test a mechanism would not only be the ones used to probe H2 combustion chemistry such as shock tubes and flow reactors, but also ones that couple in transport and fluid mechanics such as RCM IDT measurements and Sous. Which of the recent mechanisms mentioned in this brief overview of hydrogen combustion chemistry, the Varga et al. [105] update of the Keromnes et al. [83] model, Konnov’s “Yet another mechanism…” [107], the Yang et al. [111] mechanism or the others developed since 2014 [93,101–109] will be the definitive one still remains to be determined and depends on the conditions of interest. Varga et al. [105] even point out that although their mechanism was the best

4 Hydrogen-oxygen combustion mechanism overview

FIG. 6 (A) Comparison with flow reactor experiment, Aramco Mech 3.0, FFCM-1 using mechanism with current evaluated rates. (B) Effect of key reactions related to H2 destruction at 6 atm and 934 K [111].

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overall for simulating experimental data it was not the best for the individual categories of data from Sou measurements, flow reactors and jet stirred reactor outlet species concentrations. It is clear that having high quality experimental data is essential not only for developing H2/O2 mechanisms but also, and probably more importantly, for validating the mechanisms over a wide range of conditions of practical interest. In particular, the design of combustion devices that use H2 as a fuel require predictive chemical kinetic mechanisms based definitively on very high-quality data. These combustion devices, engines especially, involve H2 flames suggesting the critical importance of having H2 Sou and related data. The challenges presented in obtaining these data were discussed in the preceding section.

5. Another type of practical engine: The detonation engine Detonation engines are modern propulsion devices that have gained prominence over the last couple of decades. Detonation engines utilize energy generated by the detonation of a fuel and oxidizer mixture to obtain propulsive power instead of by a deflagration as in conventional propulsion engines (ramjets, scramjets, etc.) and turbine engines. There are several types of detonation engines [112] that have been developed at the prototype level, one of the types—Rotating Detonation Engines (RDE) is illustrated in Fig. 7. However, large scale adoption of detonation engines still faces challenges. Different configurations of engines that utilize detonation to generate energy are described by Wolanski [112]. The use of detonation instead of deflagration provides several advantages in efficiencies and performance.

FIG. 7 Schematics of a rotating detonation engine [112].

6 A potential alternative to combustion engines: Hydrogen fuel cells

Deflagration engines usually have high burning velocities resulting in high temperatures which unfortunately can result in the formation of NOx when used in a fuel-air configuration. Utilization of H2 as a fuel can at least curb all carbon-based emissions but NOx emissions are usually magnified, as mentioned in previous sections. Nevertheless, detonation engines are advantageous because the thermodynamic and volumetric efficiencies are higher than that of deflagration engines [113] since there is high heat produced by the detonation event and a small specific volume of the combusted mixture. An additional benefit of detonation engines is that they are easy to scale to different sizes making the transition from a research sized benchtop detonation engine to a large-scale practical engine realistic. However, there is much research needed for successful adoption. Since detonation systems have only recently been considered for clean power generation, there is a lack of information on the detailed behavior of various fuels, including H2, under detonation conditions. Crane et al. [114] have shown the significant variation in detonation behavior of various fuels and the need for a chemical kinetic mechanism capable of predicting this behavior for the simple fuels (C0–C4) that are being considered as a potential fuel for detonation engines. While Crane et al. [114] have demonstrated the detonation behaviors of CH4 and NG, Xia et al. [20] have carried out a detailed analysis to study the instabilities in a detonation engine using a H2/air mixture and operating in various modes. It was observed that detonation engines are susceptible to low-frequency oscillations with pressure peaks greater than 10%. The change in fuel injection conditions showed significant variation in operating modes some of which were stable whereas others were unstable. The modes of operation have critical bounds, which also vary with injection conditions. Tang et al. [115] carried out numerical analysis of a rotating detonation engine operating on H2/air mixtures. However, those results need to be considered in view of the uncertainties associated with the kinetic model that was used. Several recent studies [116–119] have shown the limitation of several well established kinetic models at predicting combustion characteristics accurately even for relatively simple fuels. For successful adoption of detonation engines, accurate simulations need to guide design decisions and selection of appropriate operating conditions. Additional research for understanding and predicting the detonation behavior of H2 would greatly benefit the development of detonation engines since H2 has been the primary fuel choice for these engines since their inception because of the high detonation velocity of H2/air mixtures, particularly under fuel rich conditions.

6. A potential alternative to combustion engines: Hydrogen fuel cells It is worth mentioning fuel cells in the context of a zero carbon or carbon neutral future, even though they are not H2 combustion devices. Nevertheless, they offer a complementary H2-based energy source to H2-fueled engines and they benefit from the same infrastructure that H2-fueled internal combustion engines can benefit from,

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i.e., minimal modifications of current fueling infrastructure. Furthermore, H2 storage and safety developments can be shared with H2-fueled internal combustion engines. For these reasons, a brief description of H2 fuel cells is given. H2 fuel cells, albeit in their technological infancy, have shown significant potential for using H2 as a fuel for transportation. The principle of operation of H2 fuel cell vehicles (FCV) is analogous to that of battery electric powered vehicles (BEV). In a fuel cell, H2 is fed to the anode while air or oxygen is taken up at the cathode and the transfer of electrons occurs between the electrodes resulting in formation of water and heat as a byproduct. This reaction generates electricity which can then be stored or directly used to power the motors responsible for providing power to the vehicle [2,120]. Fig. 8 illustrates the schematic of a typical fuel cell. There are several types of fuel cell technologies available, and they are usually classified based on the membrane used for separation of H2 ions and electrons and allowing selective transmission across them. H2 fuel cell vehicles are already capable of having a range up to 600 miles [2] on a full tank which is a significantly longer range than for battery electric vehicles. Since the H2 fuel cell operates on a fuel source that can be refilled quickly, unlike charging batteries, in the presence of appropriate infrastructure can operate with infinite range like current fossil fuel powered transportation sources. Additionally, there are Unitized Reversible Fuel Cells (URFC) under development, which can operate in reverse mode when heated to the appropriate temperature to convert the water generated during fuel cell operation to regenerate H2 and allow for real time mode switching to recuperate lost energy under low loads making the system self-sufficient. 2e–

Fuel in

Load

Oxidant in

H2

½O2 Positive ion

H2O

Negative ion H2O

Depleted Oxidant and Product gases out

Depleted Oxidant and Product gases out Cathode

Anode Electrolyte (ion conductor)

FIG. 8 Schematics of a hydrogen fuel cell [2].

7 A very practical consideration: Hydrogen storage

Fuel cell technology has the potential for decarbonization of the environment and moving toward a sustainable transport system, but only after significant technological developments and research attention. The current projection anticipates that FCVs will take over about 17% market share of all vehicles by 2050 [2]. A carbon-neutral transition period is needed before fuel cells can become dominant.

7. A very practical consideration: Hydrogen storage One of the greatest challenges of using H2 as an alternative fuel source is the safety concern related to the storage and handling of H2 during mobile vehicle operation. H2 is stored in the form of compressed gas or in liquid state under cryogenic conditions. H2 has a very wide flammability range at atmospheric conditions, which is extended at high pressures adding further safety concerns to the use of H2 in compressed form. The burning of H2 results in flames that are not visible under normal conditions since the emissions are in the infrared region beyond human visibility range. This invisibility, along with odorless burning, make H2 flames difficult to detect by humans. Also, H2 has a very low density of 70 g/L which results in a large storage volume for an equivalent mass of hydrocarbon fuels. In addition to its low density, it has a very low boiling point of 20.28 K (253 °C) which results in difficulty storing it in the liquid state. To maintain stored H2 in the liquid state, the tank needs to be heavily insulated to prevent vaporization that can result in excessive pressurization of the tank and leakage. Additionally, significant energy is required to liquify H2, which can further reduce the net gains of moving to H2 [2,6,121]. Fischer et al. [17] have estimated that 7.1 kg of compressed H2 gas is required for about a 300-mile range. The maximum storage density obtained by some modern tanks is 40 kg/m3 at a pressure of 700 atm [17]. Given these values, a 41% increase in tank capacity is necessary to obtain a range comparable to current transport systems [122]. Significant advancements and research investments need to be made into the development of compressed H2 gas storage systems for successfully achieving the H2 economy. Research focusing on new tank designs is needed to maximize safety and minimize the loss of space in the vehicles. New methods of effectively compressing H2 to high pressures efficiently need to be investigated so that they can be implemented at small scale in fuel pumps across the transport network and can be handled by the public. The cryogenic storage of H2 in the liquid phase is another option, which reduces the risk of carrying highly pressurized flammable gas between transportation destinations. However, significant design investment needs to be made into insulating the tank to ensure that H2 remains in liquid state throughout the operation, and any vaporization of liquid H2 needs to be safely handled without compromising the integrity of the tank. The refueling of liquid H2 requires sophisticated equipment and care needs to be taken to ensure the tank or the refueling system is not contaminated since H2 when mixed with certain gases in the cryogenic state can form an explosive mixture [2,121]. Improved system design and additional research is necessary to develop

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state-of-the art H2 storage and delivery systems in the cryogenic state with high safety and efficiency. While the storage of H2 in liquid (cryogenic) and gas (pressurized) form is commonly considered, H2 has the added advantage of possibly being stored in the solid state. Solid state H2 storage is usually carried out by hydration of metals from which H2 can be released at a high temperature of about 200 °C. This storage can be done at near or below atmospheric pressure eliminating pressure related safety concerns. Furthermore, no sophisticated temperature maintaining systems or insulations are necessary since heating to 200 °C is not particularly complex. Lithium nitrite has shown a potential for storing H2 with the capability of releasing up to 66% of H2 readily at 200 °C [2]. The search for a more suitable material capable of storing H2 in solid state is ongoing. NaAlH4 is one of the promising possibilities from recent research, however large-scale applications have not been demonstrated because of its low overall storage capacity [121]. Several more potential candidates for solid state H2 storage have been investigated, but none has been implemented at large scale due to cost and scarcity. One drawback of solid state storage systems is the added weight and increased cost resulting from using metals. A significant investment in the research and development of solid state H2 storage systems will further the case for moving to a H2 fueled transportation system and bring us closer to a zero carbon/carbon neutral future.

8. Conclusions and directions for research in the next 25 years (or sooner) It appears that hydrogen combustion is a viable route to a carbon-neutral future. If it is combined with natural gas combustion, hydrogen may play an even more important role in the transition from the current high levels of carbon dioxide producing liquid fossil fuel use to a more environmentally advantageous use of fossil fuel based natural gas. As described in this article, there are a number of technologies available to use hydrogen as a fuel, but additional research is necessary on many levels to implement them. The following is a brief list of some of what is needed.

8.1 For internal combustion engines • •

• •

Research in tribology can help solve the problem of lubricant contamination in the combustion chamber and make hydrogen fueled engines truly zero emission. Further research on heat transfer in hydrogen fueled engines because there is a larger amount of heat generation resulting from hydrogen combustion when compared to conventional fuels. Research into EGR and turbocharging that can help hydrogen powered engines utilize the heat lost in exhaust gases. Although it is assumed that laminar flames exist in the H2 combustion chamber, several processes can introduce flame instabilities under engine-relevant conditions. Research into flame speeds and related flame characteristics, as

8 Conclusions and directions for research in the next 25 years (or sooner)

•

described below, is necessary for the successful implementation of hydrogenfueled engines. Since hydrogen fueled engines operate at higher temperatures and lead to more NOx production, research into operating conditions that reduce NOx is necessary, especially because hydrogen can in principle sustain flame propagation and thus heat release at notably lower temperatures compared to hydrocarbons.

8.2 For flames •

•

•

Autoignition, flashback, flame stability, and emissions are among the key operating considerations that need to be addressed. To this end, fundamental flame property experiments as well as reaction kinetic model development and uncertainty minimization are critical to developing rational strategies for H2 utilization. Additionally, such data need to be measured at engine-relevant conditions, that is at pressures up to 30–50 atm and temperatures up to 700–800 K. Extrapolations to such conditions from near-atmospheric ones is not a good practice for hydrogen whose oxidation kinetics can exhibit quite non-linear behavior with density. Additionally, no length, time, and velocity flame scales are available that could be used in modeling of turbulent combustion at realistic conditions and therefore require further research. Importantly, for models to be used in CFD of combustors, they must be tested also against fundamental flame data, including flame structures, laminar flame speeds, and extinction strain rates so that transport effects are accounted for. The laminar flame speed relates directly to the heat release rate, while the extinction strain rate is a measure of the extinction propensity that affects combustor stability. In addition to its heightened sensitivity to reaction kinetics, the extinction strain rate is also sensitive to the mass and heat diffusivities as manifested classically by the Lewis number.

8.3 For chemistry •

•

Research is needed to obtain a definitive H2/O2 chemical kinetic mechanism that is comprehensively derived from and universally predictive of ignition delays measured in shock tubes and rapid compression machines, output species in jet stirred reactors, flow reactor species profiles, shock tube species, laminar flame speed and related flame characteristics over wide temperature and pressure ranges but especially high pressures relevant to engines. The validated and predictive temperature range should bridge lower to higher temperatures at higher pressures since the relative importance of reactions appears to change dramatically with these conditions. It may be necessary, in the absence of establishing a universally predictive chemistry mechanism, to research and establish application specific mechanisms especially ones for H2 combustion in engines. Despite the type of mechanism developed, it should be consistent with direct experimental and theoretical rate parameter evaluations.

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•

•

In view of the variability of uncertainty in validation experimental data, it might be necessary to revisit and further determine specific direct, experimental and theoretical, and indirect mechanism evaluation data with a focus on reducing uncertainties in the effort to arrive at a comprehensive, universally validated H2/O2 mechanism. Research emphasizing diluents and diluent ratios may help refine the H2/ O2 chemical kinetic mechanism since the reaction chemistry can be especially sensitive to diluent ratios.

8.4 For detonation engines •

•

•

Research into scaling different engine sizes from research laboratory sized benchtop detonation engines to large scale practical engines is necessary if these engines will become realistic power sources. Similarly, since detonation systems have only recently been considered for clean power generation, there is a lack of information on the detailed behavior of various fuels, which might include hydrogen mixed with natural gas, under detonation conditions. This lack of information needs to be remedied with research focusing specifically on fuel effects. For successful adoption of H2 detonation engines, accurate simulations need to guide design decisions and selection of appropriate operating conditions. These simulations will be contingent on the development of an appropriate H2/O2 reaction mechanism as described above. Additionally, mechanistic information about NOx formation at detonation engine conditions needs to be researched.

8.5 For hydrogen storage • •

• •

Research focusing on new tank designs is needed to maximize safety and minimize the loss of space in the vehicles if compressed H2 gas is to be used. Research into new methods of effectively compressing hydrogen to high pressures efficiently needs to be conducted so that the methods can be implemented at small scale in fuel pumps across the transport network and can be handled by the public. Research and development are needed into solid state hydrogen storage systems as an alternative to compressed gas storage. If hydrogen is to be used in combination with natural gas, embrittlement of natural gas pipelines must be researched further.

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CHAPTER

Ammonia as an alternative

7

Jos
e Antonio Mayoral Chavandoa, Valter Bruno Silvaa, Luı´s Anto´nio da Cruz Tarelhoa, Joa˜o Sousa Cardosob,c, Matthew J. Halld, and Daniela Eus
ebiob Department of Environment and Planning & Centre for Environmental and Marine Studies (CESAM), University of Aveiro, Campus Universita´rio de Santiago, Aveiro, Portugal, bPolytechnic ecnico, University of Lisbon, Institute of Portalegre, Portalegre, Portugal, cInstituto Superior T
Lisbon, Portugal, dDepartment of Mechanical Engineering, University of Texas at Austin, Austin, TX, United States a

1. Introduction Ammonia production ranks second among synthetic chemicals produced globally [1]. The production of ammonia in 2016 was around 200 million tons [2]. It is mainly utilized for fertilizer production, which accounts for
85% of total output, while the remaining
15% is primarily used to make explosives, polymers, and refrigeration fluids [3]. The ammonia era began in Germany shortly after 1900, when Fritz Haber devised the process idea that still serves as the foundation for today’s ammonia production processes [4]. Haber obtained two renowned patents for his work: the “circulation patent” [5] and the “high-pressure patent” [6]. The circulation patent is characterized by constant pressure and heat transfer from the reaction gases to the feedstock gases. In contrast, the high-pressure process uses a pressure of 100 atm or more. Consequently, the synthesis of ammonia is highly dependent on the generation of hydrogen and nitrogen. Although hydrogen may be obtained in various ways, nitrogen is mainly obtained from the air. The following equation represents the thermocatalytic ammonia synthesis. N2 + 3H2 $ 2NH3

(1)

1.1 Ammonia production Nitrogen is typically introduced into the ammonia production process through the air, while hydrogen is obtained directly or as a by-product from various feedstocks. The feedstocks utilized globally are natural gas, accounting for 67%; coal share is 27%; fuel oil is 2%, NAFTA 2%, and others 1% [7]. Fig. 1 summarizes the different ways of producing ammonia. Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00008-4 Copyright # 2023 Elsevier Inc. All rights reserved.

179

(1) Raw Syngas Production

Heavy oil

Natural Gas +H2O

+O2 Partial Oxidation (POX) CH4 + 0.5O2 → CO + 2H2 ΔH < 0 kJmol–1

Steam Reforming (SRM) CH4 + H2O → CO + 4H2 ΔH = 206 kJmol–1

+CO2

+O2 +H2O

Dry Reforming (DRM) CH4 + CO2 → 2CO + 2H2 ΔH = 260.5 kJmol–1

Autothermal Reforming POX + SRM

Purification Adjustment

H2 Production

Coal

Biomass

+O2

H2O

Partial Oxidation (POX)

Pulverization

Biomass Preparation

Gasification

Gasification

Sulfur Removal

Sulfur Removal

Sulfur Removal

Purification Adjustment

Purification Adjustment

Purification Adjustment

H2,N2,CH4Co,CO2,H2 O

CO + H2O → CO2 + H2

ΔH < –41 kJmol–1

(3) Gas cleaning

(4) N2 Production

N2 (5) Ammonia Synthesis N2 + 3H2 ↔ 2NH3

FIG. 1 Ammonia production ways.

Electrolysis Reactor

+Air,O2,H2O

+Air,O2,H2O Carbon Removal

(2) Water Shift Conversion

H2

Electrolysis

ΔH < –92 kJmol–1

H2

1 Introduction

As can be observed, whether fossil fuels or biomass are used, the process is primarily concerned with producing syngas (CO + H2). The production of syngas is divided into three main stages: (1) Production of raw syngas, (2) water shift conversion, and (3) CO2 removal. The first stage depends on the feedstock utilized, commonly natural gas or heavy oil. It may, however, be produced by the gasification of coal and biomass. Syngas is typically produced from CH4 in one of four ways: partial oxidation (POX), steam reforming (SRM), dry reforming (DRM), or autothermal reforming (a combination of POX and SRM). The following reactions describe each way [8–10]. CH4 + 0:5O2 ! CO + H2 ðpartial oxidationÞ

(2)

Biomass ! H2 + CO + CO2 + CH4 + C2 H4 + H2 O + char ðpartial oxidationÞ

(3)

xCH4 + yH2 OðsteamÞ ! zCO + ðx  zÞCO2 + yH2 ðsteam reformingÞ

(4)

xCH4 + CO2 ! 2CO + 2H2 ðdry reformingÞ

(5)

On the other hand, heavy oil is converted via POX like coal and biomass. However, coal and biomass are solids processed via gasification at 800 °C to 900 °C using mixtures of air, oxygen, carbon dioxide, or steam [11,12]. The second stage water-gas shift reaction occurs in two adiabatic steps: (1) at high and (2) at low temperatures. The water-gas shift reaction, at higher temperatures, occurs in a fixed bed reactor over 350 °C and employs iron-based catalysts. The water-gas shift reaction at lower temperatures, on the other hand, runs at temperatures ranging from 200 °C to 250 °C in a fixed bed reactor with Cu-based catalysts, favoring H2 generation [9]. The third stage is a gas cleaning, for example, an adsorption reactor to remove CO2 from the gas stream and obtain an H2-rich gas stream, which generally runs at a higher feed pressure of 20–60 bar and contains silica gel activated carbon, zeolite, and alumina [9]. The fourth stage is the supply or production of a nitrogen source. Finally, the fifth stage is ammonia synthesis, typically using the Haber-Bosch process. Currently, ammonia production is also classified according to the process’s carbon capture and storage (CCS) [13]. This classification is shown in Fig. 2, where brown ammonia, also called gray ammonia, is synthesized utilizing carbon-based feedstock such as methane, naphtha, and coal [14]. When methane is used, a reforming reaction is used (see reaction 4), and when coal or biomass is used, partial oxidation is used (see reaction 3). Unfortunately, brown ammonia is energy expensive, accounting for 1% of worldwide energy output, and ecologically unfriendly since it contributes 1.8% of global GHG emissions due to the use of fossil fuels to provide hydrogen. Furthermore, brown ammonia has no environmental advantage if utilized as a transportation fuel [15]. Blue ammonia production is similar to brown

181

FIG. 2 Ammonia process classification.

1 Introduction

ammonia, but its production procedures use CCS [16]. For example, urea production from CO2 [17], CO2 absorption [18], scrubbing with amines, and carbonate looping [19]. Finally, green ammonia is produced using zero-carbon power, such as solar energy, water, and air. The ammonia generated is the same as the brown or blue ammonia. However, the process emissions are different. A new method to supply pure ammonia is the production of turquoise or green-blue ammonia. This type of ammonia is characterized by methane pyrolysis, which directly breaks methane into hydrogen and solid carbon. Instead, this eliminates the reforming reaction, that produces CO2, which must otherwise be removed from the gas [20]. Regardless of whether we have brown, blue, turquoise, or green ammonia, the manufacturing of ammonia is generally carried out by the Haber-Bosh process, which combines hydrogen with nitrogen [21]. This process highly depends on the temperatures and pressures, so when they change, so does the conversion of ammonia. Le Chatelier’s principle states that equilibrium compensates for the disruption (quantities, pressure, temperature, etc.). Therefore, as seen in the accompanying table (Table 1), increasing pressure and reducing temperature in this system will favor ammonia concentration equilibrium. The Haber-Bosch process uses hydrogen as a reagent, which can be used independently as a fuel. However, using hydrogen alone has several disadvantages, due to as its physical qualities; it is the lightest element and has exceptionally low volumetric energy density, and has safety concerns (flammability and formation of explosive mixtures with air). Furthermore, the hydrogen logistics are expensive, and there are just a few hydrogen fueling stations. Therefore, the only viable solution is to store compressed gas hydrogen (CGH2) in pressurized tanks (at 350 or 700 bar for trunk tanks and 120 bar for stationary tanks) [23]. Although CGH2 has a modest energy density, tremendous pressure, and excellent flammability, it poses safety risks. Therefore, hydrogen may be kept in liquid form (LH2). However, hydrogen liquefaction consumes a significant amount of energy (up to 30% of the lower heating value) and results in boil-off losses [24]. That is why ammonia is an excellent hydrogen carrier. It offers the same clean energy advantages as hydrogen but with the added benefit of a well-developed infrastructure for production, storage, and delivery [25]. For example, the Haber-Bosch process’s technology readiness levels (TRL) are 9, and Electric Haber-Bosch with Table 1 Ammonia conversion at different operational conditions (%) [22]. T (°C)/P (atm)

1

10

50

100

300

600

1000

200 300 400 500 600 700

15.3 2.2 0.4 – – –

50.7 14.7 3.9 1.2 0.5 –

74.4 39.4 15.3 5.6 2.3 1.1

81.5 52 25.1 10.6 4.5 2.2

89.9 71 47 26.4 13.8 7.3

95.4 84.2 65.2 42.2 23.1 11.5

98.3 92.6 79.8 57.5 31.4 12.9

183

184

CHAPTER 7 Ammonia as an alternative

alkaline electrolysis is 8–9 [26]. So, it’s unsurprising that ammonia output continues to grow year after year.

1.2 Ammonia storage Ammonia is liquid at 33.6 °C and 1 bar or 8.6 bar and 20 °C. Industrial-scale storage demands low temperatures, which are energy-intensive to maintain [27]. Due to the lower storage design pressures, this approach may have a cheaper capital cost than pressurization in certain circumstances. However, re-liquefaction storage in Type C tanks (about 18 bar) may be a more practical naval alternative since it would avoid the requirement for extra onboard re-liquefaction equipment. Ammonia needs about 2.4 times the tank capacity as Heavy Fuel Oil (HFO) to provide the same amount of energy [27]. Ammonia tanks must follow the IGC and IGF Codes’ standards for minimum distances from the hull’s shell, accommodation space, design, and safety rules [27]. In addition, the IGC Code sets particular material specifications for ammonia fuel containment in IGC Code 17.12, which should be applied to marine fuel storage tanks [27].

1.3 Ammonia supply The fuel supply system (FSS) is responsible for delivering gasoline to the engine at the proper temperature and pressure. The use of low flashpoint fuels and gases complicates the fuel supply and consumer systems and increases the dependency of essential techniques compared to traditional fuel systems. For fuels such as ammonia that need cryogenic/pressurized liquefied storage, the fuel may be pumped, or pressure fed directly in liquid form. The FSS may be a more sophisticated and costly system for gas-fueled applications. The FSS must ramp up, or down fuel delivery rates to meet engine fuel demand. This transitory fuel demand may be challenging, especially when maintaining fuel supply readiness during high demand or low demand without shutting down the FSS. Additionally, it may not be supplied by the engine’s Original Equipment Manufacturer (OEM) but is specifically built to meet the engine OEM’s criteria [27]. Ammonia’s worldwide adoption is assisted by the vast infrastructure already to store and deliver the chemical. This mature distribution is a consequence of ammonia’s widespread usage in the fertilizer industry, which has resulted in establishing a well-established international marine trade network with an extended chain of ports capable of handling ammonia on a massive scale. Additionally, some of the most extensive ammonia storage facilities are near port hubs, facilitating international transportation [16]. Apart from cargo ships, ammonia is transported worldwide by pipelines, railway links, and road trailers. Conveniently, the vast majority of the existing natural gas pipeline network can be adapted to transport liquid ammonia with minimal modifications, as ammonia requires significantly lower pressures than natural gas and is compatible with the iron and steel materials used to construct the

2 Ammonia market

existing infrastructures [28]. The fact that ammonia’s distribution network is wellestablished and can be used with most existing structural components strengthens its position as a superior energy carrier.

2. Ammonia market Ammonia has a bright future since its production, consumption, and capacity have increased [29]. Indeed, the ammonia industry’s compound annual growth rate (CAGR) is 5.3%. Furthermore, in 2016, the worldwide ammonia market was worth USD 48.65 billion, and it is predicted to grow to USD 76.64 billion by 2025 [30]. According to Fig. 3A, consumption and ammonia production is increasing, having

(a)

190

Million tons per year

183.83

182.72

180.32

180

182.04

181.50

170 160 150 144.11

152.39

149.85

147.07

144.27

140 130 120 2016

2017 Capacity

2018 Production

55

(b)

2019

(c)

8.14%

2020

Consumption

108.9 13.28%

162.6

274.7

24.05%

107.3 198.6

33.49%

13.08%

29.38%

107.2 13.07%

259.8 38.43%

222.2 27.09%

Million tons per year Coal Refinery-sourced Oliofins & Aromatics Natural Gas & NGLs Liquid Oil Products

Million tons per year N-fertilizers Thermosets, fibre & elastomers Solvents, additives & explosives Other Thermoplastics

FIG. 3 Global ammonia overview (A) global ammonia trends, (B) ammonia feedstock share, (C) ammonia products share [31].

185

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CHAPTER 7 Ammonia as an alternative

the same trend (The green line is superimposed on the red line); between 2017 and 2020, annual ammonia output climbed by 1.84%. On the other side, capacity is exhibiting a little downward trend. However, large expenditures are planned to expand hydrogen and ammonia capacity and production. For example., Woodside Petroleum (WPL.AX) will spend over A$1 billion ($746 million) in Western Australia to construct a carbon-neutral hydrogen and ammonia production plant. The project will generate up to 1500 tons of hydrogen per day, or 547,500 tons per year, in ammonia and liquid hydrogen for export. Construction is scheduled to start in 2024, pending commercial and regulatory permissions [32]. The Danish Energy Technology Development and Demonstration Program (EUDP) has awarded around 11 billion Euros to the green ammonia project. The project aims to construct a 10-MW green ammonia plant directly tied to on-site wind and solar energy [33]. Similarly, Austria, Netherlands, Norway, and Portugal announced hydrogen plans [34]. Global ammonia production now stands at around 176 million tons per year. It is mainly produced by steam reforming methane to provide hydrogen for use in ammonia synthesis through the Haber Bosch process [16]. Other sources, however, say that ammonia output is around 144 [35], 152 [31], and 200 [2] million tons per year. The fact is that ammonia output is increasing. Fig. 3B shows the consumption of fuels used to produce ammonia in 2013 (Secondary reagents such as H2O, O2, CO2, and N2 are not considered). Fig. 3C shows the products made with ammonia.

2.1 Key players per region Fig. 4A shows the global ammonia capacity, production, exports and imports, where East Asia holds the leading role, accounting for 35.97%, Eastern Europe and Central Asia occupy second place with 14.38%, South Asia’s share is 10.31% and the North America share is 10.19%. Fig. 4B shows ammonia production and behaves very similarly to Fig. 4A. Fig. 4C shows the exports of ammonia, where the largest exporter of ammonia is Eastern Europe & Central Asia with 23.75%, followed by Latin America with 21.71% and West Asia with 17.72%. Note that the quantity exported and imported is the same (15.10 million tons per year). However, Fig. 4D shows that the largest ammonia importer is Western Europe with 22.13%, followed by East Asia with 18.18%.

2.2 Key players per country The information previously described provides a general scenario of ammonia’s leading producers, consumers, exporters, and importers. However, Fig. 5 provides detailed information on the top ammonia producers by country (Total ammonia production 144.2 million tons in 2020). China’s leading ammonia producer is producing 38 million tons per year, followed by Russia with 15, the United States with 14, and India with 13. Together, the participation of these four countries is 55.47% in total, more than half of the global production of ammonia, with China at 26.35%, undoubtedly the leading ammonia player.

2 Ammonia market

FIG. 4 Global ammonia trade (A) global ammonia capacity, (B) global ammonia production, (C) global ammonia exports, and (D) global ammonia imports (2020 in a million tons per year) [36].

2.3 Key companies Although the literature classifies ammonia production by geographic region or nation, the reality is that companies dominate ammonia production. Table 2 illustrates the key actors in ammonia production [55]. The preceding numbers suggest that the primary player in the manufacture of ammonia is China, which generates the chemical primarily from coal (80–82%) [2,56]. However, it is also recognized that the principal application of ammonia is the production of fertilizers, which are critical for the growth of crops. Therefore, its demand will be determined by the rise in population. In addition, ammonia is a fuel par excellence. It has a strong LHV and does not generate CO2; therefore, environmental regulations might further stimulate this chemical manufacturing to utilize it as a transportation fuel and an energy generator. Similarly, ammonia’s price may

187

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CHAPTER 7 Ammonia as an alternative

Vietnam Uzbekistan Australia Ukraine Oman Poland Netherlands Algeria Germany

1.1 1.1 1.3 1.5 1.7 2.2 2.2 2.2 2.4 3.1 3.2 3.5 3.9 4.0

Pakistan Qatar Iran Canada Saudi Arabia Trinidad and Tobago Egypt

4.3 4.5 5.0

Indonesia India United States Russia Other countries China

13.0 14.0 15.0 17.0 38.0 0.0

10.0

20.0

30.0

40.0

Million tons per year FIG. 5 Ammonia production by country (2020, million tons) [35].

grow if its demand increases. The price of ammonia in 2019 fluctuated from $235 to $250 per ton [57]. Demand for ammonia will expand as it is employed as a fuel source in internal combustion engines (ICE) and energy generation, which has garnered considerable interest since NH3 is an excellent carrier of hydrogen that emits no CO2 when burnt [58].

3. Ammonia as an ICE fuel Internal combustion engines (ICE) are categorized in the literature according to their ignition type. Primarily, two engines have been developed to burn ammonia blends: spark ignition (SI) and compression ignition (CI). In a SI engine (often gasoline engines), combustion happens when the air-fuel combination is ignited with the help of a spark plug. On the other hand, in a CI engine (typically diesel), a high temperature is created inside the cylinder by mechanical compression, igniting the injected

3 Ammonia as an ICE fuel

Table 2 Major ammonia companies. Company

Country

Gross production (million tons per year)

Reference

CF Industries Holdings Inc YARA Nutrien Basf Koch Industries Inc. Qatar Fertiliser Company SABIC EuroChem Jinmei Group Yihua Group PetroChina Group Yangmei Group Jinkai Group Sonopec Group Yancon Group Luxi Group CNOOC Henan Xinlianxin Matix Fertilisersa Indian Farmers Fertilisers Coop Ltd.b National Fertilizers LTDc Krishak Bharati Co-operative Ltd., Environment statementd Chambal Fertilisers and Chemicals Ltd Rashtriya Chemicals and Fertilizerse Togliattiazot (ТольяттиАзот) Company KuibyshevAzot Novatek

US NO CA DE US QA SA CH CN CN CN CN CN CN CN CN CN CN IN IN

10.25 8.48 7.00 1.70 0.08 3.77 3.40 1.00 4.98 4.13 3.89 2.99 2.08 1.79 1.24 1.15 1.05 1.04 0.79 1.06

[37] [38] [39] [40] [41] [42] [43] [44] [45] [45] [45] [45] [45] [45] [45] [45] [45] [45] [46] [47]

IN IN

1.09 1.44

[48] [49]

IN

1.42

[50]

IN

0.79

[51]

RU

3.00

[52]

RU RU

1.10 1.20

[53] [54]

a

2200 Metric Tonnes Per Day (MTPD) 2955 MTPD c 3040 MTPD d 4000 e 2200 MTPD (Assuming 360 days per year). b

fuel [59]. SI engines prefer high octane fuels, but CI engines benefit from fuels with a high cetane number for enhanced ignition [60]. Because ammonia has no cetane number, it requires exceptionally high compression ratios ranging from 35:1 to 100:1 in CI engines [61]. On the other hand, SI engines can run on neat ammonia since a spark plug begins the ignition process and ammonia’s high-octane rating

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CHAPTER 7 Ammonia as an alternative

prevents knocking [60]. However, due to ammonia’s poor reactivity and combustion unpredictability, most current engines need the addition of a combustion promoter fuel to operate safely under these conditions [62]. Ammonia can be an excellent transportation fuel because (1) it has a more significant volumetric energy density than hydrogen (up to three times) and (2) it can be held at a low pressure (0.8 MPa, against 17–69 MPa for hydrogen) at room temperature, which is comparable to propane [62]. Furthermore, (3) the hazard of ammonia is reasonable and comparable to that of existing fuels [63]. The first paper (2005), authored by Risø Denmark’s National Laboratory, assesses the dangers of utilizing ammonia as a fuel for internal combustion engines and fuel cells [64]. They said that the risks of using ammonia as a fuel must be addressed by technical and regulatory means. The basic needs are advanced vehicle safety systems, additional technological safeguards and regulations to prevent leaks in repair workshops and unauthorized fuel system maintenance, and safeguards for road transfer of chilled ammonia to fueling stations. When these precautions are taken, ammonia as a transport fuel poses no more danger than commonly utilized fuels (in current practice) [64]. The second paper that talks about ammonia risks as a fuel was prepared by Iowa State University in 2009 [65]. They concluded that public risk levels associated with using anhydrous ammonia as an automotive fuel are similar to those associated with LPG and gasoline [65]. The following equation describes the complete combustion of ammonia. 3NH3 + 0:75ðO2 + 3:75N2 Þ ! 1:5H2 O + 3:32N2 + heat

(6)

Ammonia is developing as a potential marine fuel option among several potential future fuel choices that might help decarbonize shipping. J
er^ome Leprince-Ringuet (Vice President, Marine Fuels, TotalEnergies) has discussed the potential for ammonia to considerably cut greenhouse gas emissions in the marine sector and contribute to climate change mitigation [66]. Table 3 shows the leading players in ammonia as a fuel demonstration for marine engines. Most companies demonstrating ammonia usage for ICEs are focused on marine engines. For example, W€artsil€a aims to have a marine engine operating on an ammonia mix this year. Additionally, they anticipate developing an engine design that runs on pure ammonia fuel around 2023 [80]. These efforts will also result in a refined hydrogen engine and plant design for the energy industry by 2025. As a result, W€artsil€a forecasts that green hydrogen will meet 7% of world energy consumption by 2050 in the energy industry [80]. Although the initiatives of these companies are highly commendable, the technology necessary to drive and power ships using ammonia as a fuel is still in its infancy. Significant research and legislative initiatives will be required to make it economically feasible. The introduction of ammonia as a fuel presents new issues in bunkering, storage, supply, and ammonia fuel composition for various ship types. As a fuel source aboard ships, practical safety requirements for ammonia do not exist and must be implemented. Ammonia is a hazardous chemical, and the extra safety concerns must be carefully addressed before ammonia is considered a maritime fuel.

3 Ammonia as an ICE fuel

Table 3 Ammonia as fuel, demonstrations. Country

Company

Application

Fuel

Reference

FI

€rtsila €, with Knutsen Wa OAS Shipping AS

Marine engines

70% ammonia blend

[67]

Marine engines

–

[68]

Two-stroke ammonia engine Marine engines

–

[69]

–

[70] [71]

Marine engines

–

[72]

NO DE

CN

US CH JP KR

Repsol Sustainable Energy Catapult Centre MAN Energy solutions

Shanghai Merchant Ship Design and Research Institute (SDARI) American Bureau of Shipping (ABS) WinGD Sumitomo Institute for Energy Research (KIER)

Marine engines Marine engines Car

US

University of Minnesota

Truck

FR


d’Orle
ans Universite

PT US

University of Lisbon, MIT, and the Polytechnic Institute of Portalegre

Ammonia fuel spray engine They are working on a 100% ammoniafueled ICE

– 30% ammonia blend 30% ammonia and 70% diesel – 100%

[73] [74] [75,76]

[77]

[78] [79]

Ammonia is less explosive than methane and poses a decreased danger of explosion, although not negligible. However, it is still necessary to handle all leakage possibilities while designing and operating a ship due to the toxicity. As a result, the safety principles created for LNG fuel will serve as an appropriate guideline for formulating the safety criteria for ammonia-fueled ships. In addition to these difficulties, engines have concerns with flame speed and other aspects of material ignition. That is why several research institutions and colleges conduct simulations and experiments to help address these issues. Table 4 illustrates some of these centers, where the majority have utilized ammonia and other fuel blends. For example, blending ammonia with a common hydrocarbon boosts its flame speed while lowering CO2 emissions relative to burning pure hydrocarbons [94].

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CHAPTER 7 Ammonia as an alternative

Table 4 Ammonia as fuel, simulations, and experimentation. Simulation or experiments

Country

Institution

PL

Warsaw University of Technology,

Simulation

UK

Cardiff University

Simulation

CN

Tsinghua University

Simulation

CN CN

Jiangsu University Xi’an Jiaotong University

Simulation Simulation

CN

Beijing University of Technology

Experiments

CA

Experiments

CA

Energy, Mining and Environment Research Center University of Ontario

Experiments

US

University of Michigan

Experiments

FR

PRISME laboratory

Experiments

FR


ans University Orle

Experiments

JP

Toyota Central R&D

Experiments

UK

University College London

Experiments

Fuel

Reference

Dieselammonia blends Ammoniahydrogen blends Ammoniahydrogen Ammonia Ammoniamethane blends Ammoniahydrogen blends Ammoniadiesel

[81]

Ammoniahydrogen blends Ammoniagasoline blends Ammoniahydrogen blends Ammoniamethane blends Ammoniahydrogen blends Ammoniadiesel blends

[82]

[83] [84] [85]

[86]

[87]

[88]

[89]

[90]

[91]

[92]

[93]

Ammonia offers significant issues when used in CI and SI engines; for example, ammonia burns slowly due to its “zero” cetane number, demanding precise temperature and pressure adjustments in a CI [95]. Furthermore, the poor reactivity and combustion unpredictability necessitated a combustion promoter fuel to ensure steady functioning. Ammonia also can be blended with other hydrocarbons to

4 Ammonia as a power vector

overcome these constraints. This has led to the development of novel solutions to improve ammonia combustion with promising results [62]. For instance, A study by Niki et al. [96] found that the ignition time, cylinder compression, and maximum pressure decreased when ammonia in the diesel fuel was increased. On the other hand, fuel mixtures containing ammonia were more ammoniasoluble when methanol and ethanol were added [97]. Furthermore, fuel substitution with kerosene increased ignition performance [98]. These experiments demonstrate unequivocally that ammonia’s advantages may be reaped when combined with fossil fuels. However, there is still more work to be done.

4. Ammonia as a power vector Ammonia may be used as a renewable energy source. For example, Japan is exploring alternatives to fossil fuels. A 22-member consortium headed by Tokyo Gas has been formed to curate Japan’s Cross-Ministerial Strategic Innovation Program (SIP)sponsored “Green Ammonia” initiative. Hydrogen has been promoted as a viable option for meeting their energy needs while lowering greenhouse gas emissions. However, ammonia s more cost-effective and less polluting [75]. On the other hand, In the United States, the Advanced Research Project AgencyEnergy (ARPA-E), a subsidiary of the Department of Energy, has recently launched its Renewable Energy to Fuels through Utilization of Energy-Dense Liquids (REFUEL) program. The aim is to develop scalable technologies for converting electrical energy from renewable sources into energy-dense carbon-neutral liquid fuels [99]. Japan might be considered the market leader in ammonia-based energy generation. The Japanese government will spend $242 million subsidizing two demonstration projects that seek to replace coal in power plants with at least 50% ammonia (made from hydrogen) by 2029. In addition, JERA, Japan’s biggest power company, will spend an additional $150 million in emissions-reduction programs. According to the International Energy Agency, yearly ammonia production of around 176 million tons results in approximately 420 million tons of direct CO2 emissions for its production and 170 million tons of indirect CO2 emission for electricity and chemical processing when pesticides are considered. Thus, ammonia production releases around 2.4 tons of CO2 per ton of ammonia [100]. Each ton of green ammonia would need 8.85 MWh of renewable energy to generate the required green hydrogen and an additional 5.53 MWh to operate the Haber Bosch process solely on electricity. Japan is interested in importing vast volumes of hydrogen and ammonia to achieve net-zero emissions by 2050 due to a lack of sufficient land for wind and solar energy generation [101]. TNB Genco, a wholly-owned subsidiary of Tenaga Nasional Berhad (TNB), announced the signing of a tripartite Memorandum of Understanding (MoU) with IHI Corporation and PETRONAS Gas + New Energy. The study’s scope includes investigating the technology of co-firing ammonia in Malaysian coal power stations

193

194

CHAPTER 7 Ammonia as an alternative

Table 5 Ammonia as a power vector. Country

Company

Description

JP

Mitsubishi

JP

Japan Science and Technology Agency (JST) IHI

Ammonia-fired in a Gas Turbine System Ammonia and CH4 fired in a Gas Turbine System Ammonia-fired in a Gas Turbine System Plan to use cofiring ammonia rate of 20% at Unit 4 of JERA’s Hekinan Thermal Power Station in 2024

JP

JP

JERA IHI

Power (MW)

Fuel

Reference

40

100% NH3

[103]

2

20% NH3 80% CH4

[104]

2

70% NH3

[105]

1000

20% NH3

[106]

and assessing the technology and economics of the complete ammonia supply chain [102]. Table 5 summarizes some current research on ammonia-fuel gas blends for power generation. The first example is a Mitsubishi’s turbine test with output of 40 MW, the turbine runs at 100% Ammonia. After other tests, Mitsubishi Power intends to commercialize the technology in or around 2025. Without a doubt, it will require significant efforts since pure NH3 brings new challenges. For example, ammonia/air mixtures have a narrower range of flammability limits than typical hydrocarbon fuels, particularly on the rich side. At standard temperature and pressure, the lean flammability limit (LFL) is approximately 15%, while the rich flammability limit (RFL) is about 28%, corresponding to an equivalence ratio range ϕ of 0.63–1.39 [107]. The maximum adiabatic flame temperature is close to that typical of hydrocarbon fuels, about 2100 K [108]. However, the unstretched laminar flame speed is considerably lower than for most hydrocarbon fuels, with a laminar flame speed of about 7 cm/s, peaking at an equivalence ratio of about ϕ ¼ 1.1 [109]. In addition, unlike a premixed hydrocarbon flame that appears blue, an ammonia flame burns with a characteristic orange glow due to chemiluminescence associated with the NH2 band [108]. According to Ho Kyung Lee et al. [110], there are important issues to address to use ammonia as a power vector. For example, the low reactivity results from the fuel’s low laminar flame burning velocity, temperature, and flammability limit compared to typical hydrocarbon fuels. Another aspect is the increased NOx generation due to the fuel-NOx mechanism, which produces NOx faster and at a lower

4 Ammonia as a power vector

temperature than thermal-NOx. Thus, these two limitations must be addressed to fully use ammonia’s benefit as a carbon-free fuel. While the fundamental research on ammonia combustion that has been done complements one another, they may be generically classified into laminar and turbulent flame investigations [108,110]. While laminar flame research focuses on combustion rate, ignition energy, flammability limits, and ignition delay time, turbulent flame research focuses on the features of flame stability in turbulent fields. Additionally, based on the results of combustion experiments with ammonia-air and mixed fuels such as ammonia-hydrogen-methane in laminar and turbulent flow conditions, the existing reaction mechanisms can be modified or improved to increase the accuracy of the ignition delay and NOx composition in a high-pressure environment. Due to the early stage of research into the mechanisms of ammonia combustion, it is required to compare and validate these mechanisms according to the respective combustion circumstances before use [110]. On the other hand, recent studies focus on solid fuels blends with ammonia. For example, Yu Xia et al. [111] studied the influence of the ammonia/oxygen/nitrogen equivalence ratio on the flame propagation characteristics of pulverized coal/ammonia co-combustion at different turbulence intensities. They concluded that (1) in lean ammonia conditions, the flame propagation velocity of pulverized coal/ammonia co-combustion is greater than that of pure ammonia combustion. (2) In the ammonia-rich state, the flame propagation velocity of pulverized coal/ammonia co-combustion is lower than that of pure ammonia combustion. (3) In the stoichiometric condition, the flame propagation velocities of co-combustion and pure ammonia combustion are almost identical. A mechanism accounting for three effects was proposed to address the findings above. First, the favorable benefits of the intense radiation from the brilliant flame and the increase in local equivalence ratio caused by the addition of volatile matter outweigh the negative impact of heat absorption by coal particles in the preheat zone under the lean ammonia condition. Increasing the local equivalence ratio by adding volatile materials negatively affects the ammoniarich situation. Consequently, the negative impacts on the ammonia-rich condition outweigh the benefits, resulting in a decreased flame propagation velocity for pulverized coal/ammonia co-combustion compared to pure ammonia combustion. Finally, the positive and negative impacts are equal in the ammonia stoichiometric state, resulting in a flame propagation velocity that is almost the same between cocombustion and pure ammonia combustion. Similarly, KhalidHadi et al. [112] studied the effect of the coal fuel fraction on the turbulent flame speed of ammonia/coal mixtures. They concluded that the local equivalence ratio increased due to the addition of volatile matter from coal particles and to increased radiation heat flux from the luminous flame to the volatizing coal particles in the preheat zone. One disadvantage is the heat sink effect, which occurs due to the high heat capacity of coal particles in the preheat zone. Without a doubt, using ammonia as a potential fuel in internal combustion engines and as an energy vector through the burning of ammonia mixes with fuel gases and ammonia mixtures with solid fuels such as carbon is a feasible way to reduce carbon emissions. However, this technology is still being continuously

195

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CHAPTER 7 Ammonia as an alternative

FIG. 6 Ammonia as an ICE Fuel SWOT [34].

examined, tested, and improved. To describe the pros and downsides of this technology, a SWOT analysis is shown in Fig. 6.

5. Economic analysis

5.1 Ammonia production At the present time, no facility has been able to synthesize ammonia using renewable energy sources at an industrial scale. Only a few studies have examined the technology required to manufacture renewable ammonia in its entirety and the economics of such operations [62]. A recent survey by Joao Cardoso et al. [62] mentions some attempts in this field. For example, Oxford and Siemens collaborated to create a model for determining the optimal scale of a green ammonia production facility, considering the needed renewable energy supply and the levelized cost of ammonia [113]. According to Argus, the cost of green ammonia production today would exceed $650 per ton (using Australia as an example and “assuming 2020 prices, technology, energy mix, and an average electricity cost of $50/MWh”) [114]. This cost is nearly double that of regular ammonia on the market [114,115]. However, assuming an electricity cost of $50/MWh could be very optimistic for the present and near future, where war between Ukraine and Russia is increasing the cost of fossil fuels and electricity. For example, the price of a MWh in Spain (Mar. 08, 2022) is 492.47 €/MWh [116],

5 Economic analysis

FIG. 7 Green ammonia cost estimate and global ammonia cost curve. Mn t (million tons) [114,115].

which makes the production of ammonia and hydrogen very expensive. Fig. 7 depicts the Argus forecast. On the other hand, another research study examined the cost of brown ammonia as a function of plant size. As shown in Fig. 8, the plant size substantially affects the ammonia production costs, which rise considerably below a plant capacity of 100 tons/day [117]. Calculating the cost of ammonia is not straightforward since there are several variables to consider. For instance, the raw material to be utilized, the technique to be employed, the presence or absence of CO2 capture, the location in which ammonia is generated, the energy cost, etc. CarlosArnaiz del Pozo et al. [118] assessed the potential for blue and green ammonia as future energy carriers, considering the gas switching reforming method for co-production of H2 and N2 from natural gas with inherent CO2 capture (blue ammonia) and H2 generation via an optimized value chain from wind and solar energy, electrolyzer, cryogenic N2 supply, and various energy storage

FIG. 8 Ammonia cost based on plant size.

197

198

CHAPTER 7 Ammonia as an alternative

Table 6 Ammonia production cost.

Energy consumption Technology (GJ/ton)

CO2 capture rate (%)

Specific emissions (ton of Cost with CO2 per ton of NH3) CO2 capture

Cost without CO2 capturea

KelloggBraun and Root Linde ammonia concept Gas switching reforming

28.5

82.8

0.28

385.9 €/ton

479.0 €/ton

27.7

76.3

0.36

385.1 €/ton

–

26.2

94.4

0.07

Green ammonia

31

0

0

– 332.1 €/ton 192.7 €/ton (Saudy Arabia) 772.1 €/ton (Germany) 569.3 €/ton (Spain) 484.7 €/ton (Saudi Arabia)

CO2 tax of 100 €/ton.

a

options (green ammonia). These long-term approaches were compared to two existing CO2 capture technologies: the Kellogg Braun & Root and Linde ammonia concept. They also considered European energy prices (6.5 €/GJ natural gas and 60 €/MWh electricity) and Saudi Arabian energy prices (2 €/GJ natural gas and 40 €/MWh electricity). Table 6 summarizes the ammonia cost based on the region and technology [118]. Gas Switching Reforming shows that producing ammonia in Saudi Arabia is cheaper than in Europe. This situation exists as a result of the disparity in energy prices. As a result, the cost of ammonia may be expected to be exactly proportional to the cost of energy and the quantity of energy spent in the form of green ammonia is shown. Naturally, these rates may fluctuate throughout the conflict between Ukraine and Russia since the cost per MWh in Europe has risen significantly.

5.2 Electricity production from ammonia Green ammonia is a technically possible and economically competitive fuel for the decarbonization of the electrical sector through high-efficiency gas turbine power plants by 2040. The levelized cost of energy from green ammonia is expected to be 167–197 USD/MWh at a 25% power plant capacity factor in 2040, assuming a widely accessible green ammonia fuel price of 380 USD/t. However, there are significant uncertainties in the production cost of green ammonia, principally owing to a broad range of estimates and a lack of solid experience regarding data for electrolyzer capital cost. The levelized cost of energy is a good measure of economic

6 Environmental analysis

competitiveness, but only when it is incorporated into a national grid can the actual economic competitiveness of green ammonia be recognized. Specific networks will have varied capacity utilization rates of dispatchable energy sources and have different accessible fuel costs, including local and imported green ammonia. Further study will be required to comprehend the ramifications of such concerns at a grid or regional size [119].

6. Environmental analysis Climate change mitigation requires decarbonizing energy output. However, how can communities continue to supply global electrical demand without increasing CO2 emissions? According to scientists, one answer may lie in an unusual source: ammonia since it burns without releasing carbon [120]. Ammonia is also attractive to transport energy from the point of manufacture to the end of use. Furthermore, some experts believe ammonia might be utilized to encapsulate and store hydrogen, easily broken from liquid or gas and used in fuel cells [121]. Nonetheless, significant obstacles remain if ammonia is to contribute to resolving the world’s significant carbon emissions issue. Currently, typical electricity production methods include the combustion of hydrocarbon fossil fuels, most often methane, contributing CO2 to the environment. Furthermore, the Haber-Bosch process consumes significant energy, whose production also realizes CO2. According to some estimates, ammonia production accounts for around 2% of global fossil fuel use. As a result, it emits more than 500 million tons of CO2, accounting for more than 1.8% of global greenhouse gas emissions [16]. The Haber-Bosch technique is mainly used in commercial ammonia production at elevated temperatures and pressures. Brown ammonia manufacturing is, on average, an energy-intensive process, using 8 MWh of energy per ton of ammonia. However, hydrogen generation accounts for most energy usage and around 90% of carbon emissions [16]. Steam reformation of fossil fuels is nearly the sole method for hydrogen production. The majority of ammonia plants generate hydrogen and carbon dioxide via the steam reformation of natural gas. Carbon dioxide emissions from its production from coal, heavy fuel oil, and naphtha is even more significant (between 2.5 and 3.8 tons of CO2 per ton ammonia, compared to 1.6 tons of CO2 per ton ammonia for natural gas). Compressed air or an air separation device is used to acquire nitrogen [16]. Biomass gasification can reduce GHG emissions by 65% during ammonia synthesis, making it a potential contributor to decarbonizing ammonia (and hydrogen) production [122]. Despite significant reductions in CO2 emissions, green ammonia production lags behind conventional techniques, mainly owing to cost restrictions that are impeding its widespread adoption. Under present market circumstances, green ammonia manufacturing costs more than steam reforming with fossil fuels [26]. Fig. 9 compares the CO2 emissions associated with the manufacture of ammonia using fossil fuels and biomass.

199

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CHAPTER 7 Ammonia as an alternative

0

0.5

1

1.5

2

2.5

3

3.5

4

Tons of CO2 per ton of NH3 Biomass (Gasificaon)

Natural Gas (Steam Reforming)

Coal and Heavy oil (Steam Reforming)

FIG. 9 Ammonia production emissions based on feedstock.

Today, green ammonia remains much more expensive than fossil fuels steam reforming. Therefore, renewable energy prices must fall to achieve cost parity, so electrolysis costs must decrease, electrolysis efficiency must increase, and the Haber-Bosch cycle must be further optimized for more small-scale operations [123]. Starfire Energy has created a revolutionary solution for the production of ammonia that utilizes a method that has been modified for variable power operation [124]. Additional electrolysis solutions are now being explored. For instance, Haldor Topsoe, a technological developer, is investigating high-temperature electrolysis [125]. This appealing choice can separate oxygen from the air and waste heat to save energy, resulting in lower investment and higher efficiency. The business launched a demonstration project in the Netherlands in March 2019.

7. Conclusions and future research Ammonia is a desirable commodity; its demand increases as the world’s population rises since its principal usage is in the manufacturing of fertilizers. The global production of ammonia is around 176 million tons per year and has risen 1.84% annually. However, numerous initiatives have been launched globally to increase ammonia production. The primary producers are China, Russia, the United States, and India, and in terms of corporations, the key producers are CF Industries Holdings Inc., YARA, and Nutrien. On the other hand, the increasing concern about climate change due to uncontrolled emissions has prompted the industry to consider alternative production methods, and

References

ammonia production is no exception. As a result, modern technologies can make ammonia production cleaner (Green ammonia). However, green ammonia synthesis is still more costly than conventional fossil fuel steam reforming. Thus, continuous development of cost-effective renewable energy resources, additional research efforts on process implementation obstacles and inefficiencies, and the elimination of capital costs associated with green ammonia production solutions are critical steps toward cost parity and widespread green ammonia production. Nonetheless, the future appears bright for green ammonia and green hydrogen ventures, owing to broad geopolitical interests that have led countries and international agencies to commit significant investments and subsidies to these mutual energy enablers as they work to build a low-carbon society. However, the use of NH3 for power generation still presents some limitations. Research gaps need to be filled, for example, its low burning velocities compared with conventional fuels, its higher energy demand for ignition, a superficial knowledge about NH3 blends flame structure and characteristics, and the prevalence of high nitrogen oxides emissions from the combustion process as well as slipped unburnt NH3. Using combustion promoter fuels can be addressed the low burning velocities and poor reactivity—in other words, cofiring of ammonia blends with fossil fuels. However, more research is also needed on this topic, but it could be the preliminary step for engines that use only ammonia.

Acknowledgments The authors would like to thank to the Portuguese Foundation for Science and Technology (FCT) for the grant SFRH/BD/146155/2019, contract CEECIND/00641/2018 and the projects SAICT ALT/39486/2018 and PTDC/EME-REN/4124/2021. Thanks are also due to the FCT/ Ministry of Science, Technology and Higher Education (MCTES)UIDP/50017/2020+UIDB/ 50017/2020+LA/P/0094/2020, through national funds. This book is also a result of the project Norte-06-3559-FSE-000045 supported by NORTE 2020, under PORTUGAL 2020 Partnership agreement.

References [1] P. Venkat, R. Jim, Introduction to Ammonia Production, AIChE, 2016. [2] V. Litvinenko, B. Meyer, Syngas utilization technologies, in: Syngas Production: Status and Potential for Implementation in Russian Industry, 2018, pp. 23–46, https://doi.org/ 10.1007/978-3-319-70963-5_5.

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[3] J. Brightling, Ammonia and the fertiliser industry: the development of ammonia at Billingham, Johnson Matthey Technol. Rev. 62 (1) (2018) 32–47, https://doi.org/10.1595/ 205651318X696341. [4] I. Dybkjaer, Ammonia production processes, Ammonia (1995) 199–327, https://doi. org/10.1007/978-3-642-79197-0_6. [5] L.B. Anilin, Soda-Fabrik, GER 235421, CA (1911) 5: No. 3137, 1908. [6] F. Haber, GER 238450, CA (1912) 6: No. 1663, 1909. [7] J.A. Moya, A. Boulamanti, European Commission, Joint Research Centre, Production Costs From Energy-Intensive Industries in the EU and Third Countries, 2016, p. 163. [8] K.T. de Campos Roseno, R.M. de B. Alves, R. Giudici, M. Schmal, Syngas production using natural gas from the environmental point of view, in: Biofuels—State of Development, InTech, 2018. [9] G. Voitic, et al., Hydrogen production, in: Fuel Cells and Hydrogen: From Fundamentals to Applied Research, Elsevier, 2018, pp. 215–241. [10] A.C. Lausche, J.A. Schaidle, N. Schweitzer, L.T. Thompson, Nanoscale carbide and nitride catalysts, in: Comprehensive Inorganic Chemistry II (Second Edition) From Elements to Applications, vol. 7, 2013, pp. 371–404, https://doi.org/10.1016/B978-0-08097774-4.00730-0. [11] Y.A. Situmorang, Z. Zhao, A. Yoshida, A. Abudula, G. Guan, Small-scale biomass gasification systems for power generation ( tert-butanol, while n-propanol is always more reactive than isopropanol. The reactivity of propanol isomers is similar to that of iso- and 2-butanol. Recently, Saggese et al. [36] refined the kinetic model for C3–C4 linear and isoalcohols from Sarathy et al. [61]. They updated the rate coefficients of H-atom abstraction reactions by OH and HO2 from [33,62], which play a major role in the ignition chemistry in the low-to-intermediate temperature range. This mechanism was proved to satisfactorily predict the IDTs of neat n-, iso-butanol and n-, iso-propanol in engine-relevant conditions. The model by Saggese et al. [36] was tested against both sets of data at lowtemperature and diluted conditions for propanol isomers, as shown in Fig. 4. The agreement is satisfactory across the whole range of temperatures, pressures and stoichiometries. Similarly to ethanol, the combustion of FACE F/isoalcohol blends was also studied in a RCM at oxygenate blend levels of 0% to 30% (vol/vol), at pressures of 20 and 40 bar, temperatures from 700 to 1000 K, and at dilute, stoichiometric fuel loading conditions (15% O2, ϕ ¼ 1) [63]. At lower temperature conditions (700–860 K), the isoalcohols are found to suppress first-stage reactivity and associated heat release with main ignition times extended. Reactivity suppression can be ranked as ethanol > isopropanol > isobutanol. At higher temperatures (860–1000 K) changes to fuel reactivity are less significant, where isopropanol slightly suppresses reactivity, while isobutanol promotes it. The detailed kinetic model developed by Saggese et al. [36] captures reasonably well the overall trends in the blending behavior and the effect of isopropanol addition on IDTs, as shown in Fig. 5 for 20 and 40 bar.

2 Small alcohol fuels

(A)

(B) FIG. 4 Measured and simulated ignition delay times for propanol isomers; panel A: diluted condition with 11% O2 [35], and panel B: under 90% dilution [60]. Symbols indicate experiments and lines indicate model results. Reprinted from S. Cheng, D. Kang, S.S. Goldsborough, C. Saggese, S.W. Wagnon, W.J. Pitz, Proc. Combust. Inst. 38 (1) (2021) 709–717 and X. He, Q. Wang, R. Fernandes, B. Shu, Combust. Flame 237 (2022) 111818 with permission from Elsevier.

Sensitivity analyses indicate that at Tc ¼ 760 K, H-atom abstraction by OH from the gasoline surrogate fuel molecules (e.g., cyclopentane, isooctane, n-heptane) are seen to be sensitive pathways controlling the main ignition time, while H-atom abstractions from isopropanol and isobutanol lead to alpha radicals, respectively,

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FIG. 5 Experimental and modeled ignition delay times for FACE-F/isopropanol blends at Pc ¼ 20 bar and Pc ¼ 40 bar, presented as functions of inverse temperature [63]. Mixtures are stoichiometric and dilute (15% O2). Symbols indicate experiments, lines are model results.

which act as scavengers in the system, and thus suppress reactivity. At the Tc ¼ 900 K, similar chemistries are dominant, but there is an increasing importance of HO2 as the H-atom abstractor.

2.4 Butanols In comparison to propanol isomers, butanol isomers were studied more widely and prior studies have been well reviewed by Sarathy et al. [61]. For experimental work, both shock tube and RCM measurements of IDT’s are available. For shock tube IDTs, they are available for neat n-butanol and other isomers [64–66] and neat isobutanol [35,67]. Moss et al. [64] studied the autoignition of four butanol isomers between 1200 and 1800 K in a shock tube and developed a detailed kinetic mechanism validated with their measurements. They found that the more reactive n-butanol and isobutanol were consumed mainly through H-abstraction, while the less reactive 2-butanol and tert-butanol were consumed primarily via dehydration. For RCM IDTs, experiments for all the neat butanols were carried out by Weber et al. [68] for air-like mixtures at ϕ ¼ 0.5, 1 and 2. n-Butanol was found to be more reactive compared to the other three isomers. Also, experiments on all the isomers were recently published by He et al. [60] for 90% dilution over a range of stoichiometries from 0.25 to 0.9. Neither a NTC phenomenon nor a multi-stage ignition has been observed from their measurements. At a temperature range lower than 850 K, the reactivity of n-butanol was found to be much higher than the other fuels. In comparison, at temperatures higher than 900 K, the reactivity of tert-butanol was much lower than that of the other fuels. Additionally, n-butanol [69] and 2-butanol IDTs

2 Small alcohol fuels

are available from [35]. For isobutanol, RCM data experimental sets are available on IDTs [35] and on intermediate temperature heat release (ITHR) [70]. Pelucchi et al. [71] measured IDTs of stoichiometric linear C3–C6 alcohols between 704 and 935 K in an RCM at 10 and 30 bar. There was no NTC behavior observed for ethanol, propanol and butanol. However, an apparent NTC behavior was found for n-pentanol. JSR experimental speciation data on butanol isomers are also available from [72– 75]. Dagaut et al. [72] found out that H-abstraction was the main pathway of n-butanol consumption in the JSR at 10 atm, while unimolecular decomposition was relatively negligible. Togbe et al. [73] carried out speciation measurements for 2- and iso-butanol at 10 atm in a JSR. They concluded that the oxidation rates of n-, 2-, and iso-butanol are similar but have different intermediate stable products. Lefkowitz et al. [74] observed large quantities of acetone and methane in the oxidation of tert-butanol at 780 K and 12.5 atm in the Princeton Variable Pressure Flow Reactor (VPFR). They observed that a lack of isobutene production indicates that in these conditions tert-butanol is consumed by a bimolecular radical-oriented reaction rather than by molecular elimination to form water and isobutene. Jin et al. [75] studied the combustion of tert-butanol experimentally in a flow reactor in pyrolysis conditions at 30–760 Torr, in a premixed laminar flat flame at 30 Torr and in a coflow methane/tert-butanol diffusion flame at atmospheric pressure. They found under pyrolysis and flame conditions, the unimolecular decomposition reaction is the dominant reaction among the fuel consumption pathways, in which the four-center ring water elimination reaction has an extremely high contribution. Isobutene and acetone were found to be the main primary products. Various studies on laminar flame speeds on butanol isomers are present in literature [76–78]. Different groups found that the molecular structures of the butanol isomers have a significant influence on laminar flame speed (LFS). Gu et al. [76] investigated the LFS of butanol isomers and found that n-butanol/air mixtures had the highest LFS due to the highest number of inner CdH bonds, followed by 2butanol, isobutanol as well as tert-butanol, which was consistent with the results from Veloo et al. [77]. Wu and Law [78] concluded that the primary reason for the lowered flame speed of 2-butanol, isobutanol and tert-butanol compared to n-butanol is that they crack into more branched intermediate species which are relatively stable, such as isobutene, isopropanol and acetone. There have been many efforts to develop detailed kinetic models for butanol isomers [79–82] and these have been reviewed by Sarathy et al. [61] and He et al. [60]. One recent study on n-butanol and isobutanol is from Saggese et al. [36]. As found in case of methanol, they found occasional difficulty in reconciling the simulation of multiple experimental data sets. As seen in Fig. 6, the simulated behavior for isobutanol is slower compared to measured IDTs from one RCM [70] at 10 and 20 atm. However for another RCM [68], the simulations agree with experiments at 10 bar and are too fast at 30 bar. These differences occur even though experiments were at the same equivalence ratio and dilution. Numerical simulation approaches are needed that can account for these discrepancies in the mechanism validation process.

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FIG. 6 Measured (symbols) and simulated (solid lines) ignition delay times for: (A) isobutanol at φ ¼ 1 with 21% O2 in Ar and N2 from an RCM [35]; (B) isobutanol at φ ¼ 1 in air from an RCM [68]. Predictions are carried out using the model from Saggese et al. [36].

Other discrepancies were found by He et al. [60] who used the Sarathy et al. [79] kinetic model to simulate their RCM experiments for all four butanol isomers under dilute conditions over a wide range of stoichiometries. They found that the kinetic model did not sometimes reproduce the temperature dependence (i.e., activation energy) of the IDTs and this is another area for kinetic model improvements. In a fuel blending study, the IDTs of blends of isobutanol with a research gasoline (FACE F) were examined in an RCM for dilute (15% O2), stoichiometric mixtures [63]. When the kinetic model of Saggese et al. [36] was used to simulate the results, the simulated IDTs at the higher blend level (20–30%) were too fast compared to experiments (Fig. 7). Similar discrepancies were found in the case of methanol and ethanol. Further work is needed to improve the accuracy of kinetic models in simulating fuelcomponent interactions for these alcohol blends with gasoline. This effort may also warrant acquiring more experimental data on the interaction of butanol isomers with gasoline-type fuels. Some recent efforts on fuel blending of butanols are the works of Michebalch et al. [83] for isobutanol and Kalvakala et al. [84] for n-butanol. The blending of isobutanol with a 5-component gasoline surrogate was carried out by Michelbach et al. [83] at conditions of 675–870 K, 20 bar, and Ф ¼ 1 within a RCM. The authors found that isobutanol addition to gasoline produces interesting non-linear responses in terms of measured IDTs at low isobutanol concentrations, similar to those previously observed for n-butanol blending [85]. Instead, Kalvakala et al. [84] performed computational fluid dynamics (CFD) simulations of a single-cylinder gasoline compression ignition (GCI) engine to investigate the impact of blending two biofuels, namely ethanol and n-butanol, with gasoline. The CFD model was employed to simulate the combustion of a gasoline-ethanol blend with 45% ethanol (E45) and a gasolinebutanol blend with 45% n-butanol (B45) under the same operating conditions to study the effects of fuel composition and start-of-injection (SOI) timing on

2 Small alcohol fuels

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FIG. 7 Experimental and modeled ignition delay times for FACE-F/isobutanol blends at Pc ¼ 20 bar and Pc ¼ 40 bar, presented as functions of inverse temperature [63]. Mixtures are stoichiometric and dilute (15% O2). Symbols indicate experiments, lines are model results.

combustion phasing and soot emissions. The sooting propensity followed the trend: B45 > E20 > E45 at all SOI timing conditions. Overall, it was observed that the autoignition phenomena was primarily related to fuel chemistry. On the other hand, the sooting propensity showed strong coupling with both fuel chemistry and physical properties, with greater impact of fuel physical properties at advanced SOI conditions.

2.5 Pentanols Several chemical kinetic models of 1-pentanol oxidation have been developed based on analogies to smaller alcohols of similar structures using established reaction rate rules developed for alkanes and alcohols [61,71]. The kinetic models have been validated using fundamental experiments on 1-pentanol combustion. The first kinetic model for 1-pentanol was proposed by Togb
e et al. [86] for its high temperature (T > 1000 K) oxidation. Heufer et al. [87] were the first to extend the 1-pentanol kinetic model to include both low- and high-temperature reaction classes. The authors observed that model predictions are highly sensitive to the rate constants in low temperature reaction classes such as R + O2 (first O2 addition) and QOOH + O2 (second O2 addition). To improve model predictions, Heufer et al. [87] altered the rate constant of reactions involving first and second O2 addition by a factor of 2–3, which lies within the uncertainty involved in the mechanism due to the lack of available theoretical calculations for reaction rates for low temperature reactions. Recently, Pelucchi et al. [71] developed an updated, comprehensive lumped kinetic model for n-C3–C6 alcohols pyrolysis and oxidation, and validated it against new ignition and speciation experiments.

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To reduce uncertainty in the rate constants for reactions related to 1-pentanol, several theoretical studies using ab-initio methods have been undertaken. Zhao et al. [88] theoretically studied the unimolecular decomposition reactions of 1pentanol at the CBS-QB3 level of theory. For H-atom abstraction reactions from 1-pentanol, Rawadieh et al. [89] recently calculated the rate expression for abstrac˙ 2, based on the CBS-QB3 method with transition state thetion from the α-site by HO ory. For the 1-pentanol radical consumption, Van de Vijver et al. [90] explored their decomposition and isomerization reactions on potential energy surfaces (PESs) at the UCCSD(T)-F12a/cc-pVTZ-F12//M06-2X/6-311++G(d,p) level of theory and calculated the pressure-temperature dependence of the rate constants by solving the master equation. For low temperature reactions for 1-pentanol, a theoretical investigation has been conducted by Bu et al. [91] by employing the G4 compound method. They calculated the pressure-dependent rate constants for the reaction classes of R + O2 ¼ RO2, RO2 ¼ QOOH, RO2 ¼ olefin + HO2, and QOOH ¼ cyclic ether + OH. Very recently, Duan et al. [92] performed ab-initio calculations at the CCSD(T)/ aug-cc-pVTZ//M06-2X/cc-pVTZ level on the fate of the 1-hydroxy-1-peroxypentyl radical. Duan et al. [92] and others [91,93,94] identified HO2 elimination from α-alcohol peroxy radical forming aldehyde and HO2 as the most important alcohol-specific reaction that competes with the low-temperature chain-branching channels and inhibits the fuel reactivity at low temperatures. The incorporation of these theoretically derived rate constants into the 1-pentanol chemical mechanisms has been shown to improve the model performance [90,92]. Recently, based on abinitio calculations, Lockwood et al. [95] calculated the rate constants for important low temperature reaction classes such as R + O2 ¼ RO2 and RO2 ¼ QOOH at the CCSD(T)/cc-pV∞Z level of theory. Using newly calculated pressure-temperature dependent rate constants for 1-pentanol, a new kinetic model for low temperature oxidation of 1-pentanol has been developed by Chatterjee et al. [96]. Unlike previous models which were based on analogy to ethanol oxidation, the newly developed kinetic model for 1-pentanol by Chatterjee et al. [96] shows that at engine-relevant pressure conditions (30 bar), the major intermediate species 1-pentanal formed during 1-pentanol oxidation primarily forms via a stabilized adduct pathway ˙ 2,aldehyde + HO2), rather than the chemically activated pathway (R + O2,RO (R +O2,aldehyde + HO2). The newly proposed model is in good agreement with the experiments across a wide range of temperature and pressure. Fig. 8 shows the comparison of Chatterjee et al.’s [96] kinetic model to experimental data for 1-pentanol obtained from using both the high-pressure shock tube (HPST) and RCM facilities at NUI Galway (NUIG) [96]. Regarding other straight-chain pentanol isomers, secondary C5 alcohols such as 2- and 3-pentanols have been identified as potential alternative fuels or blending components for modern engines. The first high-temperature kinetic model for all three straight-chain pentanol isomers was developed by K€ohler et al. [97]. For 3-pentanol, Carbonnier et al. [98] developed a high-temperature kinetic model oxidation and validated it using speciation data from a jet-stirred reactor (JSR) and IDTs from a shock tube (ST). For theoretical studies, Feng et al. [99] recently calculated

2 Small alcohol fuels

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FIG. 8 Comparison of simulated (solid lines) and measured (symbols) IDTs [96] for 1-pentanol at P ¼ 15 and 30 bar, φ ¼ 0.5, 1 and 2, 21% O2 in N2/Ar. The closed symbols are from the HPST, and the open and half-filled symbols from the RCM.

˙ 2, ˙ H3, HO the rate constants for H-atom abstraction reactions from 3-pentanol by Ḣ, C ˙ and OH radicals and updated the Carbonnier et al. [98] model. Regarding 2-pentanol, Bai et al. [100] theoretically studied the radical decomposition kinetics in detail. Dayma et al. [101] used the newly calculated rate constants by Bai et al. [100] involving 2-pentanol radical decomposition kinetics to construct and validate a new hightemperature kinetic model using high-pressure JSR and ST experimental data. Recently, a low temperature kinetic model for 2- and 3-pentanol has been developed by Chatterjee et al. [96] for the first time. In these kinetic models, rate constants for important low temperature reaction classes initiated by R + O2 reactions are based on theoretical calculations for 1-pentanol by Lockwood et al. [95]. The proposed kinetic model for 2- and 3-pentanol by Chatterjee et al. [96], including both high temperature and low temperature reaction classes, has been validated against HPST & RCM data obtained using experimental facilities at NUI Galway (NUIG) [96] as well as

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FIG. 9 Comparison of NUIG’s experimental data (symbols) and simulation predicted IDTs (solid lines) for 2- and 3-pentanol at P ¼ 15 and 30 bar, φ ¼ 1, 21% O2 in N2/Ar. The open symbols are for the Shock Tube (ST) and the closed symbols are for the RCM [96]. Simulations use the Chatterjee et al. kinetic model [96].

experimental data available in the literature [98–101]. Fig. 9 shows the comparison of simulations using the Chatterjee et al. kinetic model [96] to IDT experimental data for 2- and 3-pentanol in a HPST and RCM [96]. For branched pentanols, Tsujimura et al. [102,103] developed a detailed chemical kinetic model for isopentanol (3-methyl-1-butanol) and used it to simulate homogeneous-charge compression-ignition (HCCI) combustion. Dayma et al. [104] measured species concentrations in a JSR (jet stirred reactor) over a range of equivalence ratios and temperatures at 10 atm and proposed a detailed chemical kinetic model of isopentanol. A detailed reaction mechanism of isopentanol including a wide range of temperature, pressure and equivalence ratio was developed by Sarathy et al. [61], and validated against previous and new experimental data. Their results show that isopentanol is less reactive than 1-pentanol. Recently, Cao et al. [105] revisited the pyrolysis of isopentanol with flow reactor experiments at 30 and 760 Torr and they developed a pyrolysis kinetic model. Comparing their results with similar data of 1-pentanol and 2-methyl-1-butanol pyrolysis, they found that the initial decomposition temperatures of the two branched pentanol isomers are slightly lower than that of 1-pentanol at both pressures and that the concentrations of benzene and fulvene in the pyrolysis of the two branched pentanol isomers are significantly higher than those in the pyrolysis of n-pentanol. Tang et al. [106] measured the high temperature ignition behavior of C5 alcohols (1-pentanol, isopentanol, and 2-methyl-1-butanol) in the temperature ranging from 1100 to 1500 K and pressures of 1.0 and 2.6 atm. A high temperature chemical kinetic model for 2-methyl-1-butanol was proposed and compared against their ignition data. Serinyel et al. [107] measured the species concentrations at 10 atm, from lean

3 Recommendations for future work and future directions

to rich conditions in a jet-stirred reactor (JSR) and simulated their measurements using a detailed chemical kinetic mechanism. Later, Zhang et al. [108] measured pyrolysis products of 2-methyl-1-butanol in a flow reactor at low and atmospheric pressures and tested a kinetic model against their measurements. The results indicate that the decomposition of 2-methyl-1-butanol is similar to isobutanol rather than to n-butanol. Park [109] et al. were the first to study the low-temperature chemistry of 2-methyl-1-butanol with a high-pressure shock tube experiments at temperatures from 750 to 1250 K and pressures at 20 and 40 bar and with detailed kinetic modeling. The ignition delay times of 2-methyl-1-butanol/air mixtures at intermediate temperatures are similar to those of isopentanol, while the reactivity of 2-methyl-1-butanol is higher than isopentanol in the high temperature region. Up to now, no ignition experiments of 2-methyl-1-butanol ignition were carried out at lower temperatures (e.g., 650 K) using a rapid compression machine. However, new ignition delay time data of 2-methyl-1-butanol combustion at lean and high-pressure conditions have recently been acquired and a new kinetic model has been developed, which will be included in a forthcoming paper that is currently under preparation. Laminar flames speeds of these pentanol isomers were measured and compared first by Li et al. [110] and recently by Nativel [111] et al. who found 1-pentanol flame speeds being higher than those from Li et al. Laminar flame speeds of pentanol isomer-air mixtures were found to decrease in the order of 1-pentanol > 2-methyl1-butanol > isopentanol.

3. Recommendations for future work and future directions 3.1 Methanol

Given the large amount of experimental data on methanol (for example, see the supplementary data of Dong et al. [20]), it is difficult to identify conditions where further progress in accuracy can be made for methanol. This is also true for other alcohols that have large amounts of experimental data like ethanol. Some simulations show good agreement and others do not when compared to experiments at similar conditions of temperature, pressure, and equivalence ratio. Numerical tools are needed to identify specific regions of temperature, pressure, equivalence ratio and dilution where discrepancies between predictions and experimental measurements exist so that these conditions can be studied in experiments and kinetically analyzed. Then further progress in kinetic-model accuracy can be made. Also, because of advancements in the accuracy of theoretically-based rate constants and thermodynamic properties, it is important to use theoretically-based methods to increase the accuracy the rate constants and thermodynamic properties and potentially improve the accuracy of kinetic model predictions of methanol and other alcohols.

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3.2 Ethanol Despite several studies on H-abstraction by OH from ethanol [37–39], discrepancies remain. Hashemi et al. [40] noted that despite the consistency among the literature on the total rate coefficient for OH + ethanol ! R + H2O, branching fraction predictions are in substantial disagreement. Similar to OH, Hashemi et al. [40] also noted discrepancies among chemical kinetics mechanisms for abstraction reactions of ethanol with HO2. A more accurate determination of the rate coefficients for these abstraction reactions is important to improve the reliability of modeling predictions. There are needs for the understanding of ethanol oxidation in the presence of NO. When ethanol is oxidized with NO in a flow reactor at high-pressure, the kinetic model modified by Glarborg et al. [50] could not capture the measured NO concentration profile for high pressure conditions. Also, it should be noted that combined studies of methanol and ethanol fuel interaction with NOx have not been published so far, neither from an experimental nor from a modeling point of view. Therefore, more experimental work focusing on NOx/fuel interaction is required for arriving at an improved mechanistic understanding for methanol and ethanol, being the basis for future studies on NOx formation and fuel interaction during the combustion of larger alcohols. In the rapid compression machine experiments, discrepancies were noted when ethanol was mixed with a research gasoline and its surrogates at higher levels of ethanol blending [46,47]. This is primarily caused by the inadequately characterized interactions between the ethanol and surrogate sub-chemistries, highlighting the need to quantify the complex, non-fuel-specific intermolecular reactions between ethanol and each surrogate constitute. Moreover, differences in ethanol blending effects between the surrogates and FACE-F indicate the need to formulate more robust surrogates that better account for ethanol-blending effects. This could be achieved by including experiments on gasoline/ethanol blends, in addition to those of “neat” gasolines, as targets to be matched by kinetic models.

3.3 Propanols The kinetics of propanol isomers is not studied as much as the other alcohols and requires more experimental and theoretical investigation. For isopropanol, there are inconsistencies of a factor of four between the rate of its dehydration reaction (iC3H7OH ! C3H6 + H2O) from theoretical calculations and from fundamental experiments. For all alcohols, experimental measurements of rate coefficients for H-abstraction are absent in the 400–900 K range [112]. No detailed theoretical studies on the reactions between propanol isomers and CH3 at the molecular level have been reported in literature until two recent studies appeared. Nguyen et al. [113] investigated the mechanisms and kinetics of the reactions of methyl radical with n/i-propanol (n/i-C3H7OH) in detail using density functional theory and coupled cluster theory with rate constant prediction. Their analysis suggests that the H-cleavage from CdH bonding of C-atom bonded to dOH group

3 Recommendations for future work and future directions

plays a significant role in the H-abstraction reactions and, at the same conditions, the reaction of methyl radical with isopropanol takes place faster than with n-propanol. Similarly, Shi and Song [114] studied H-abstraction reaction by H and CH3 at the M06-2X level of theory. They found that for n-propanol the H-abstraction channels from the α-CH2 group are kinetically more favorable. For the isopropanol + R (R ¼ H, CH3•) reactions, the H-abstraction channels from the dCH group are predominant at low-temperature. Moreover, the study on H-atom abstraction reactions from propanol isomers by HO2 is very scarce. Rawadieh et al. [89] recently carried out a theoretical study on the H-atom abstraction reactions from C1–C5 alcohols by HO2, but only the rate constants of the H-atom abstraction reactions from the weakest carbon sites were reported. A more comprehensive investigation was recently reported by Duan et al. [115] who calculated the rate constants of all the possible H-atom abstraction reaction channels from propanol isomers by HO2 using the multistructural variational transition state theory (MS-VTST). These rate constants calculated for propanol isomers are lower than the recent calculations reported by Rawadieh et al. [89] by several orders of magnitude. This significant discrepancy highlights the importance of accurate theoretical efforts. Moreover, the rates from Duan et al. [115] for propanol isomers were directly tested in the model of Saggese et al. [36], showing suppression of fuel oxidation reactivity, leading to longer ignition delay times and retarded fuel consumption, in particular at low temperatures and high pressures. In the Saggese et al. kinetic modeling study [36], the rate of abstraction by OH from propanol isomers was taken from the McGillen et al. [62] study on butanol isomers. While this was a successful approach for the Saggese et al. study, more theoretical or experimental studies on OH abstraction rates are needed for the pentanol isomers to verify this approach. He et al. [60] studied both propanol isomers under dilute conditions over a range of lean stoichiometries in an RCM. They tested many kinetic models and found that the Saggese et al. [36] model most accurately simulated their experimental results. However, they found that the kinetic model was inconsistent in simulating the measured activation energies of IDTs on Arrhenius plots. They stated that further work on the propanol kinetic models is needed to resolve these discrepancies.

3.4 Butanols As in case of methanol, occasional difficulty is found in reconciling the simulation of multiple experimental data sets for isobutanol at similar experimental conditions [36]. Strategies are needed in mechanism validation workflows to deal with this issue. Also, in the case for methanol and ethanol, a recent butanol model showed difficulty in simulating isobutanol blends at high levels in gasoline [70]. More experimental studies of butanol isomers blended with full-boiling gasoline fuels are needed to help resolve these difficulties. Additionally, although Sarathy et al. [79] kinetic model was identified as the best literature model for simulating the He et al. [60] butanol isomer IDTs at diluted/lean conditions, this model sometimes

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had difficulty in reproducing the experimental temperature dependence of the IDTs. Finally, theoretical calculations of R + O2 for butanol isomer radicals and the successive low-temperature chemistry classes are still very few, with the newest effort being from Labbe et al. [95]. More such theoretical studies are needed.

3.5 C5 branched alcohols Despite progress, further fundamental chemical kinetic studies are needed for larger alcohols. Specifically, a comprehensive theoretical study for various channels on R + O2 potential energy surfaces is needed to determine low temperature reaction rate rules for branched C5 alcohols. A first attempt to calculate kinetic constants for 1pentanol oxidation chemistry has been carried out in the work of Chatterjee et al. [96]. Such studies will improve the model’s predictive capabilities at high-pressure and lean conditions, which are typical of new, high-efficiency, low-emission engines.

4. Summary and recommendations Small alcohol fuels can be made from low carbon feedstocks through biochemical processes that meet technical requirements and economic goals for biofuels. Methanol, ethanol, and isomers of propanol, butanol and pentanol have been found to be suitable for use in internal combustion engines and have been identified by the CoOptima project as having low barriers for market adoption. Detailed chemical kinetic models are needed to assess the impact of small alcohol fuel properties on engine combustion. In this chapter, the state of development of chemical kinetic models for small alcohols is assessed and future needs for the advancement of such models are identified. Methanol and ethanol have been studied widely experimentally and many chemical kinetic models have been developed and reported in the literature. For methanol with its large set of experimental validation data, there are instances when experiments at similar conditions in the shock tube and/or RCM show agreement and disagreement with the kinetic model. Further work is needed to resolve these differences and to identify the causes of agreement and disagreement. With ethanol, some disagreement is seen when blending at higher levels of ethanol in a research gasoline when computed IDTs are compared to the experimental data in the RCM. Also, significant discrepancies remain the literature about what abstraction rate by OH to use for ethanol. For isopropanol, there are inconsistencies of a factor of four between the rate of its dehydration reaction (iC3H7OH ! C3H6 + H2O) based on theoretical calculations and from fundamental experiments. For C5 alcohols, more theoretical calculations are needed on their low temperature reaction channels on the R + O2 potential energy surface to potentially help increase the accuracy of the associated chemical kinetic models.

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Acknowledgments This work was performed under the auspices of the US Department of Energy (DOE) by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was conducted as part of the Co-Optimization of Fuels & Engines (Co-Optima) initiative sponsored by the DOE Office of Energy Efficiency and Renewable Energy (EERE), Bioenergy Technologies and Vehicle Technologies Offices. The authors thank Dr. Shijun Dong for producing Fig. 1.

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CHAPTER

Fischer-Tropsch and other synthesized hydrocarbon fuels

9

Mahabubul Alama, Kuen Yehliua, Chenxi Sunb, and Andr
e L. Boehmanb EMS Energy Institute, Penn State University, University Park, PA, United States, bDepartment of Mechanical Engineering, University of Michigan, Ann Arbor, MI, United States

a

1. Background 1.1 History

Fischer-Tropsch fuels are produced in the Fischer-Tropsch process which relies on coupling of carbon atoms and hydrogen molecules via a “synthesis reaction,” where a carbon chain building process occurs in which methylene groups are attached to the carbon chain [1]: ð2n + 1ÞH2 + nCO ! Cn Hð2n+2Þ + nH2 O

(1)

ð2nÞH2 + nCO ! Cn H2n + nH2 O

(2)

ð2nÞH2 + nCO ! Cn Hð2n+1Þ OH + ðn  1ÞH2 O

(3)

Alkanes Alkenes Alcohols

Thus, the Fischer-Tropsch process is a catalyzed chemical reaction in which carbon monoxide and hydrogen are converted into liquid hydrocarbons of various forms. Typically the catalysts used in the F-T process are based on iron and cobalt. The principal purpose of this process has been to produce a synthetic petroleum substitute, by hydroprocessing the paraffinic wax product from the F-T synthesis reaction into synthetic fuels and synthetic lubricants. In 1902, Sabatier and Senderens first demonstrated the hydrogenation of carbon oxides by using a nickel catalyst [2]. They hydrogenated carbon monoxide to methane and carbon dioxide to methane. The development of pressurized Fischer-Tropsch synthesis started in about 1925 in Germany when Prof. Franz Fischer and Dr. Hans Tropsch applied for a patent describing a process to produce liquid hydrocarbons from carbon monoxide gas and hydrogen using metal catalysts. Their US patent was awarded in 1930 [3].

Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00006-0 Copyright # 2023 Elsevier Inc. All rights reserved.

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1.2 Fuel production and characteristics Gasification of renewable feedstocks and the recycling of captured CO2 via solar and e-fuels routes rely on providing the fuel conversion process a form of “synthesis gas” (syngas), generally a mixture of CO and H2. A thorough treatment of the process of gasification is found in Higman and van der Burgt [4]. In contrast to biodiesel and renewable diesel fuel, for example, which are produced from lipids, fuels produced via the Fischer-Tropsch process can produced from an enormous variety of feedstocks, since the F-T process takes as input CO and H2. Once you have syngas from biomass or other feedstocks, the traditional routes are to Fischer-Tropsch (F-T) fuel [5] and methanol, and via methanol to dimethyl ether (DME) [6]. From methanol and DME, one could also pursue the “methanol to gasoline” (MTG) process [7]. Here we will focus on the F-T process, the fuels that process produces and the application of F-T diesel fuels. There is an array of renewable fuels production processes that includes biochemical and thermochemical pathways. The thermochemical pathways include pyrolysis to biocrude and fuels, and gasification to syngas followed by syngas conversion via the synthetic fuel processes [5]. Fig. 1 shows various pathways that can be pursued with syngas as the intermediate step in the process. So, the F-T process can be considered a thermochemical pathway when starting from a feedstock that is gasified. When recycling CO2 to fuel, the F-T process is one of several synthetic fuel routes that can be pursued.

Diesel Alkanes ch ps ro -r T Fe he or sc Co Fi s esi nth osy Ox Fer mentation

Syngas

Isosyn thesis Wa ter g a Fe and s shif Cu t Cu /Z nO

Gasoline Olefins Alcohols Aldehydes Ethanol Isobutane Hydrogen Reforming Pd

236

Methanol

e en tyl bu esin o s r + I cid A lites o Ze Deh yd

ratio n AI O 2 3

MTBE Olefins Gasoline M100 M85 DME

FIG. 1 Primary syngas conversion pathways. From R.M. Swanson, J.A. Satrio, R.C. Brown, A. Platon, D.D. Hsu., Techno-Economic Analysis of Biofuels Production Based on Gasification, National Renewable Energy Laboratory, Golden, CO, 2010 (Report No.: NREL/ TP-6A20-46587).

1 Background

The typical F-T process requires three steps to convert raw material into fuels (as an aside, there are some that claim today that they can merge the second and third steps into one although that remains to be proven commercially or even on a significant pilot scale basis). The first step is the generation of synthesis gas. In the second step, synthesis gas is then converted in the F-T reactor to mainly straight-chain hydrocarbons and water. At room temperature the hydrocarbons separate into liquid and solid phases. In the final stage, the process is completed by hydrocracking of the solid wax into the F-T liquid phase, hydrotreating the F-T liquid and distilling into diesel, kerosene and naphtha. The refining of the F-T wax into fuel can readily produce diesel range compounds (see Fig. 1) with very desirable properties, as shown in Table 1. F-T diesel is typically rich with long chain saturated n-alkanes, leading to high cetane number but poor low temperature properties. F-T liquids are generally used as a blendstock to upgrade diesel fuel properties, since they provide high cetane number and have no aromatics [18]. Diesel fuel properties are discussed in more detail below. A variety of F-T processes have been developed using several different types of catalysts and reactor technologies. Similarly, the properties of F-T fuels also vary considerably depending upon the process and reactor technology. In general, F-T diesel fuels possess characteristics that make them desirable for use in diesel engines because they provide lower exhaust emissions compared to conventional diesel fuels. The F-T process can occur at low temperature (below 300 °C) over a cobalt or an iron catalyst (LTFT, low temperature Fischer-Tropsch) or at high temperature (above 320 °C) over an iron catalyst catalyst (HTFT) [18]. There is also a “Synthol” process that can produce an aromatic rich product and light alkenes [4,18]. Most commonly, F-T diesel fuels are comprised of long n-alkanes, and generally possess very high cetane number (>70 is typical) but have high cloud point because these long straight chains make precipitation of waxes very likely [19]. So, typical refining of the F-T wax includes some amount of isomerization to lower the cloud point, at the cost of cetane number. Because they are similar in cetane number and chemical composition, F-T diesel and renewable diesel (from hydrodeoxygenation of lipids from animal fats and vegetable oils) may function similarly as blending agents to upgrade the quality of diesel fuel, or with proper formulation, serve as neat fuels. F-T fuels can also fit within a scheme to produce what are being referred to as “solar fuels,” “electro-fuels” and “power-to-liquids” [18]. The Fischer-Tropsch route can be very expensive, with the minimum selling price for F-T fuel estimated at $7.60 to $8.10 on a gasoline gallon equivalent basis [5]. Both the capital expense and the operating expense for conversion to methanol and DME is far lower than for F-T fuels [6]. There is a growing interest in blending DME from low greenhouse gas (GHG) pathways into propane to produce a low GHG autogas [20]. Gasoline blendstocks can be produced from the F-T fuel process, by cracking the longer chain hydrocarbons and by using the naphtha fraction from the F-T process.

237

Table 1 Selected properties of Fischer-Tropsch diesel fuel. Sasol fuels

Properties Density at 15 °C, kg/L API Gravity @ 15.6 °C Flash point, °C Cloud point, °C Pour point, °C Freezing point, °C Kinematic viscosity @ 40 °C, mm2/ s Distillation, °C IBP 10% 50% 90% FBP

ASTM method

EPA 2-D certification diesel fuel requirement [8]

CARB diesel fuel [9,10]

SPD F-T diesel fuel [8– 10]

SPD F-T diesel fuel [8,15]

Syntroleum fuels C9-C22 F-T diesel [8,16]

F-T CI fuel distillate [8,16]

ExxonMobil Shell F-T diesel [8,11–13]

Mossgas F-T diesel [12,14]

F-T diesel [17]

F-T naphtha [17]

D 4052/ D 1298 D 287

0.865–0.839

0.838

0.7769

0.7698

0.7845

0.8007

0.774

0.731

32.0–37.0

38.7

50.6

52.3

54

45.22

51.32

62.07

D 93

54.4, min

54, min

67

59

72

100

60

74

>74

34.99 MJ/L

35.7 MJ/L

27.0, min

10, max

36.6 MJ/L Gross 2.7 (D 5186) 2700

46.6 MJ/L Gross 0.7 (D 5186)

D 6078

4300

D 6079

270

567 (60 °C) (460. max)

>67

None

>64

None

74

34.4 MJ/L

34.2 MJ/L

0.1

10.1

0.26

0.01

1700

1950

420/540/ 570

600

240

CHAPTER 9 Fischer-Tropsch fuels

1.3 Fischer-Tropsch fuel properties The most straightforward approach to displacing petroleum-derived diesel fuel with a renewable fuel is for the renewable fuel to be comprised of the same types of compounds as found in diesel fuel. Renewable diesel and Fischer-Tropsch diesel fuel both approach this “drop-in” replacement capability, since they are primarily comprised of normal and branched alkanes. Table 1 shows some properties of F-T diesel from different manufacturers and of commercially available petroleum diesel fuels [8–17,21]. Pyrolysis oil-derived fuels may require more processing to serve as “dropin” blendstocks, due to the presence of organic acids and other compounds that may not be suitable for finished diesel fuels [22,23]. Renewable diesel and FischerTropsch fuels with their high alkane content display a high cetane number, provide a short ignition delay, high EGR tolerance and low sooting tendency. The high cetane number arises from the abundance of longer chain alkanes, but will be tempered by isomerization to form branched alkanes which may be necessary to achieve acceptable low temperature behavior. The low sooting tendency arises from a combination of high H/C ratio, lack of aromatics and lack of CdC double bonds [24]. The reduced sooting tendency results in low particulate matter emissions and less nucleation mode particles (< 50 nm particle diameter) by as much as 80% fewer particles, although some observations of reductions in the concentration of small particles may have been due to the sulfur content of the diesel fuel to which the Fischer-Tropsch fuel is compared [25]. In a common-rail diesel engine, comparing F-T fuel with an ultra low sulfur diesel fuel (ULSD) does not result in a substantial reduction in total particle number emissions, although PM mass emissions are reduced substantially relative to ULSD [26]. Another general observation is that CO and unburned hydrocarbons are reduced with F-T fuel, and this may be a consequence of the high cetane number and overall autoignition tendency, which leads to a low critical equivalence ratio [27,28]. The critical equivalence ratio is a measure of how readily a fuel will still ignite and burn, even under very lean local conditions. If fuel over-mixes, this can lead to incomplete combustion and unburned CO and hydrocarbons [29]. Fuels with higher ignition quality can also tolerate higher levels of EGR without having degraded combustion and lengthened combustion duration [30]. The low temperature operability limits indicated by the cloud point and the pour point are defined as the lowest temperatures at which acceptable engine performance is possible. Good cold flow properties are necessary for fuel to flow through the fuel filter without plugging and reach the injector in sufficient quantity to support combustion and match the demand for power during cold weather engine operation. The low temperature properties of F-T diesel fuels depend on the manufacturer, type of processing plant, process design and the combination of the alkane molecules in the products. Reports have shown that the Sasol SPD F-T diesel fuel utilized hydrocracking and hydroisomerising of the F-T syncrude to overcome low temperature problems providing very good low temperature properties [9,10,15,21]. Syntroleum C9-C22 F-T diesel fuel requires further refining to provide a F-T CI fuel distillate with very good low temperature properties [16,21]. Mossgas also hydrotreated their final

1 Background

product and the cold flow properties of their F-T diesel fuel were excellent with pour point and cloud point below 60 °C [12,14]. Cold flow properties of diesel fuel are often improved by blending with additives (pour point suppressants), however, hydrocracking and hydroisomerization to produce F-T diesel products can also provide good cold flow properties. From the product utilization point of view, it is desirable to include as wide a fraction as possible of F-T diesel fuel for use as an alternative fuel for CI engines. Unfortunately, inclusion of too many heavy alkanes leads to cold flow problems. A greater fraction of lighter paraffins can reduce cold flow problems, but too much light paraffin content can lead to an F-T diesel having an ignition temperature that is too low. The inclusion of naphtha both increases the volume of the fuel produced and reduces potential problems with low temperature properties [31]. The density of the fuel has a great influence on engine performance and emission characteristics, and is directly related to the heating value of the fuel. Specific gravity is used to express the relative density of petroleum products. A common descriptor is the API gravity, where a higher API gravity translates to a lower density material. All the F-T diesel fuels from different manufacturers presented in Table 1 have lower density than petroleum diesel fuel. Several reports also indicated that the power output with F-T diesel was lower than with petroleum diesel due to the reduced density and lower heating value of the F-T diesel fuel [16,32,33]. Heating value is an important fuel property for achieving acceptable engine power output and acceptable fuel consumption on a volumetric basis. It indicates the energy available from a fuel when it is burned and it is directly related to calculation of the efficiency of the engine. Fuel injection equipment delivers fuel on a volumetric basis and power output from the engine decreases as the net heat of combustion decreases. Table 1 shows that the net heat of combustion for F-T diesel is lower than for diesel fuel. Similarly, power output from the F-T powered diesel engine was lower due to the combined effects of lower heating value and density [16,32,33]. Viscosity is an important physical property for a fuel because of its relevance to the performance of the fuel injection equipment. As shown in Table 1, for almost all F-T fuels the viscosity is lower than for 2-D diesel fuel, and all F-T diesel fuels possess low lubricity. The lubricity of these F-T fuels were increased or improved by adding commercially available lubricating additives [10,11,14,34]. Norton et al. reported that the high frequency reciprocating rig test (HFRR, ASTM D 6079) showed the lubricity of neat F-T diesel fuel was unacceptable because the wear scar exceeded the 380 μm limit specified by an engine manufacturer [11]. However, addition of 200 ppm of Paradyne 655 (or similar lubricity additive) to F-T diesel fuel might be suitable to prevent fuel system wear. In the market, F-T fuels are highly desirable because their properties are readily tailored in the hydrorefining process [18,35]. However, since the dominant pathway for production of F-T fuels today is from natural gas (“gas to liquids,” or GTL), the traditional F-T process may not be economically viable in the coming decades without carbon sequestration or renewable feedstocks, such as renewable natural gas

241

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CHAPTER 9 Fischer-Tropsch fuels

(RNG), as the feedstock. While a broad range of feedstocks can serve as inputs to the F-T process (referred to as “XTL”), including captured CO2 and green H2, the economics and challenges of scaling up such facilities which are expensive to build, may limit how much of F-T and other so called “e-fuels” pathways will be implemented in time to meet GHG emissions targets [36]. Nonetheless, F-T fuels have been in the market for decades, and have been studied extensively as the survey in the next section shows.

2. Survey of engine performance and emissions impacts of F-T fuels Below is a survey of engine performance and emissions studies performed with F-T fuels, organized in terms of early work before the roll out of ultra low sulfur diesel fuels and before the implementation of the US EPA 2010 diesel emissions standards. The earlier studies were performed in a mixture of engines, some that used mechanical fuel injection systems and some that used early versions of common rail fuel injection systems. The historic survey is followed by later work from the authors in common rail engines, using conventional combustion strategies. Section 3 considers the combustion of F-T fuels and impacts on soot characteristics in a modern common rail diesel engines. Then, Section 4 considers the use of F-T fuels in advanced combustion strategies.

2.1 Engine performance Synthetic F-T diesel fuels have higher cetane number, lower aromatic content and almost no sulfur making them ideal for ultra clean diesel engine combustion. However, their lower density and lower energy content compared to conventional diesel fuel may limit the maximum power output from engines operating with F-T diesel fuel. Given the variety of F-T diesel production processes and the range of F-T diesel composition, it is very important to know the in-cylinder combustion behavior when these fuels are burned in a diesel engine. In an abundance of earlier studies, reports compared F-T diesel with conventional fuel, and almost all the reports compared the emissions characteristics of F-T diesel with 2-D diesel fuel or California Air Resources Board (CARB) diesel fuel (both of which were fuels that preceded the current “ultra low sulfur” diesel fuels, which entered the market in 2006) [9–17,21]. However, only a few reports from that wave of studies in the late 1990s and early 2000s presented in-cylinder combustion behavior such as cylinder pressure, combustion duration, and ignition delay [24,32,33]. First, Payri et al. theoretically showed that the decrease in density (8%) of F-T diesel fuel results in a decreased mass injection rate of 4% and an increased jet velocity of about 4% [33]. Spray penetration and spray angle depend on the momentum flux of the fuel. The change of the mass and velocity with F-T diesel fuel injection had no influence on fuel jet momentum. Therefore, one would expect that the fuel

2 Survey of engine performance and emissions impacts of F-T fuels

jets of F-T diesel and reference fuel would have the same spray tip penetration and spray angle. Payri et al. confirmed their analysis by injecting F-T and reference fuel into a high-density injection spray chamber. Results showed that the spray tip penetration and spray angle of the two fuels were not significantly different. Their results also showed that the SMD (Sauter Mean Diameter) was well correlated to local velocity and nearly identical for both F-T diesel and reference diesel fuel. Since the spray tip penetration and spray angle are not significantly different compared with petroleum diesel fuel, the effects of F-T diesel on the combustion process probably arise from physical and chemical properties of the F-T diesel fuel other than the fuel density. In general, lower density F-T fuel will produce lower power, increase fuel consumption, increase the fuel injection period, lower the heat release rate, and decrease soot emissions. Several reports also indicated that the power output with F-T diesel was lower than with petroleum diesel due to the reduced density and lower heating value of the F-T diesel fuel [16,32,33]. It is necessary to account for the density of F-T diesel fuel and its lower power output. Injector modifications might improve power output, however they might affect some other engine-out exhaust emissions. Therefore, careful examination is necessary to find out the optimum solution. Atkinson et al. [32] reported in-cylinder combustion characteristics with cylinder pressure, ignition delay, maximum burn rate and total combustion duration of the F-T fuel compared to petroleum diesel fuel. The high cetane number of F-T fuel provided a shorter ignition delay than that of diesel fuel. The F-T diesel fuel showed a delay period of about one tenth of a millisecond less than the petroleum diesel fuel and provided a means to reduce fuel evaporation and premixed combustion. As a result, a lower initial combustion temperature can pave the way to lower NOX emission with F-T diesel. Fischer-Tropsch diesel fuel had a slightly longer burn duration than diesel fuel. The total period for ignition delay and combustion was higher for F-T diesel than for the petroleum diesel fuel. The time taken to burn 50% of the fuel was higher for the F-T fuel than for the diesel. The peak cylinder pressure with F-T fuel was lower compared to the diesel fuel since the diesel fuel has a strong premixed combustion phase, whereas the F-T burns more evenly over the burn duration [32]. A possible reason for the longer burn duration is that the cetane number of F-T diesel fuel is much higher than reference diesel fuel. Kidoguchi et al. conducted an experiment with diesel fuel by varying the cetane number and indicated that combustion duration increased with an increase in cetane number and BSEC increased along with PM emissions [37]. Another cause for the higher burn duration might be the lower density of F-T diesel fuel compared to the petroleum diesel fuel [38,39]. Schaberg et al. showed that the brake specific fuel consumption (BSFC) over a transient test cycle with F-T diesel fuel was lower than with 2-D (No. 2 diesel fuel) and CARB diesel fuels [9]. Their results showed that lower aromatic content fuels tended to lower the BSFC. BSFC depends on LHV of the fuel and the thermal efficiency of the engine, which is influenced by the combustion efficiency. The engine operating condition, and the physical and chemical properties of the fuel influence

243

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CHAPTER 9 Fischer-Tropsch fuels

combustion efficiency. The LHV of the aromatic hydrocarbons is lower than for the equivalent carbon number alkane. Therefore, aromatic content reduces the LHV of the fuel and leads to increased BSFC.

2.2 Engine emissions Fischer-Tropsch diesel is liquid at normal atmospheric pressure and temperature and it has good autoignition characteristics due to its high cetane number. Fischer-Tropsch diesel fuel provides some specific properties compared to conventional diesel fuel that lead to lower exhaust emissions. Schaberg et al. showed the emissions reduction potential of F-T diesel fuel over 2-D and CARB diesel fuels [9]. In their test, a 1988 model, 12.7 L, DDC series 60 engine rebuilt to 1991 emission standards was used for hot-start transient emissions tests conducted in accordance with the federal test protocol (FTP) test procedure. Table 2 shows that the higher cetane number and lower aromatic content are the major differences between CARB and 2-D diesel fuel. Also CARB diesel fuel has lower density than the 2-D diesel fuel. Table 2 shows the emission reduction behavior with F-T diesel fuel compared to 2-D and CARB diesel. The CARB diesel fuel showed HC, CO and NOX emissions reduced by 40%, 13% and 15% respectively, when compared to 2-D diesel fuel. No significant PM reduction was observed with CARB versus the 2-D diesel fuel. The HC, CO, NOX and PM emissions with F-T diesel fuel were reduced by 49%, 33%, 27% and 21% respectively, compared to 2-D diesel fuel. The volatile organic fraction (VOF) of PM was reduced by 34%, with respect to 2-D diesel fuel. Similarly, F-T showed 15%, 23%, 15% and 21% reduction of HC, CO, NOX and PM emissions respectively, over CARB diesel fuel. Also, 29% of VOF was reduced with F-T diesel fuel compared to CARB diesel fuel. Their report also presented some emissions characteristics when F-T diesel fuel was blended with 2-D diesel fuel. By blending the F-T with 2-D, cetane number, aromatic content, sulfur content and density were changed proportionally. These blends also showed emissions reductions, which were proportional to the amount of F-T diesel fuel in the blend. Fig. 2 represents emissions with the blended fuel compared to Table 2 Emissions reduction potentials of F-T diesel fuel. Emissions reduction potential in % Exhaust emissions

CARB over 2-D

F-T diesel over 2-D

F-T diesel over CARB

HC CO NOX PM

40 13 15 0

49 33 27 21 (VOF 34)

15 23 15 21 (VOF 29)

Adapted from P.W. Schaberg, I.S. Myburgh, J.J. Botha, P.N. Roets, C.L. Viljoen, Diesel exhaust emissions using Sasol slurry phase distillate process fuels, SAE Tech. Pap. 972898, 1997.

2 Survey of engine performance and emissions impacts of F-T fuels

Emissions (% relative to CARB Fuel)

100

80

60

40

20

1991 Model Year 1999 Model Year

0 HC

CO NOx Emission

PM

FIG. 2 Comparison of exhausts emissions during a hot-start test from 1991 (1988 engine rebuilt to meet 1991 emissions levels) and 1999 DDC series 60, 12.7 L, heavy-duty diesel engines [15]. Republished with permission of Society of Automotive Engineers, from I.A. Khalek, P.W. Schaberg, I.S. Myburgh, J.J. Botha, Comparative emissions performance of Sasol Fischer-Tropsch diesel fuel in current and older technology heavy-duty engines, SAE Tech. Pap. 2000-01-1912, 2000, permission conveyed through Copyright Clearance Center, Inc.

CARB diesel fuel. Fig. 2 shows that a blend of approximately 40% F-T diesel fuel in 2-D diesel fuel appears to be suitable to meet the CARB fuel emissions standard. It is well known that the sulfate portion of PM emissions decreases with the reduction of fuel borne sulfur. Fig. 3 presents sulfate emission versus fuel sulfur consumption rate during hot-start transient operation. The linear trend demonstrates that sulfate emissions vary proportionally with fuel sulfur content. Therefore, reducing the fuel sulfur content can directly lead to reductions in PM emissions [9]. The cetane number of F-T diesel fuel is higher than that of 2-D and CARB diesel fuels. Retarding injection timing is a technique to reduce NOX for a high cetane number fuel, but retarded timing results in a penalty on PM and BSFC. Experimental results showed that the NOX emission was decreased to 15% by retarding the injection timing by 3 °C A, with PM and BSFC penalties in the region of 2% to 3%. The unburned engine oil contribution to PM emission during retarded injection timing was found to be constant. The increase in VOF due to the unburned portion of the fuel, and insoluble portion of the PM contributes to the increased PM emissions at retarded injection timing. Schaberg et al. published another report comparing emissions performance of F-T diesel fuel in current and older technology heavy-duty diesel engines [15]. One of their objectives was to determine whether the high cetane F-T fuel would provide any additional advantage on engine-out exhaust emissions. The respective CARB and F-T diesel fuels used in these studies with 1999 model year engine

245

CHAPTER 9 Fischer-Tropsch fuels

100 % relative to CARB Fuel Total PM

246

1991

1999

80

60

40

20

Sulphate + Bound Water Unburned Fuel Unburned Oil Carbon

0 CARB

SPD CARB Test Fuel

SPD

FIG. 3 Breakdown of relative hot-start PM emissions from 1991 (1988 engine rebuilt to meet 1991 emissions levels) and 1999 DDC series 60, 12.7 L, heavy-duty diesel engines [15]. Republished with permission of Society of Automotive Engineers, from I.A. Khalek, P.W. Schaberg, I.S. Myburgh, J.J. Botha, Comparative emissions performance of Sasol Fischer-Tropsch diesel fuel in current and older technology heavy-duty engines, SAE Tech. Pap. 2000-01-1912, 2000, permission conveyed through Copyright Clearance Center, Inc.

[15] were not identical of their previous studies with 1991 model year engine [9], however differences were relatively small. Fig. 2 shows the relative emissions of the two different model year engines. F-T diesel fuel showed a smaller reduction of HC and larger reduction in CO, when compared in the 1991 engine. The reduction of NOX emission was 4% smaller with the 1999 engine, while PM emission was 11% greater. These results may be attributed to differences in the amounts of diffusion controlled combustion, which will be more pronounced in the later model engine. Under diffusion burning conditions and in the absence of significant difference in ignition delay, both NOX and PM have been found to be primarily dependent on H/C ratio of the fuel [40,41]. Therefore, the influence of fuel cetane number on NOX emissions becomes smaller and the H/C ratio becomes a more important factor. Fig. 3 compares the breakdown of sulfates, unburned fuel, unburned oil and carbon relative to the total PM emission from the two model year engines. The difference between the PM emissions from the two engines is primarily observed in the VOF and carbon content. The older model engine with F-T diesel fuel showed approximately the same amount of VOF and carbon reduction relative to CARB diesel fuel. In the late model engine VOF was unchanged with the two fuels, and the PM reduction was mainly due to the carbon (soot) portion.

2 Survey of engine performance and emissions impacts of F-T fuels

FIG. 4 Boiling point effect of F-T fuels on exhaust emissions from a Peugeot 405 indirect injection (IDI) light duty diesel vehicle measured using the combined Urban Drive Cycle and ExtraUrban Drive Cycle (ECE-EUDC) hot and cold test protocols [17]. The term LSADO means low sulfur automotive diesel oil, meaning No. 2 diesel fuel. Samples representing a UK diesel fuel and a US diesel fuel were used in these comparisons. Republished with permission of Society of Automotive Engineers, from J.W. Johnson, P.J. Berlowitz, D.F. Ryan, R.J. Wittenbrink, W.B. Genetti, L.L. Ansell, et al., Emissions from Fischer-Tropsch diesel fuels, SAE Tech. Pap. 2001-01-3518, 2001, permission conveyed through Copyright Clearance Center, Inc.

Fig. 4 shows the effect of boiling point temperature of F-T diesel fuel on engineout exhaust emissions [17]. The cetane numbers of the F-T diesel fuels are more than 70 and densities are lower than the reference diesel fuel. Cold flow properties are well below the allowable level, even when the T95 (temperature to boil 95% of the fuel) extended beyond the reference fuel. The negative sign in the figure indicates reduction of emissions compared to conventional diesel fuel. By increasing T95 of the F-T diesel fuels from 330 to 390 °C, no significant increase in PM emission was observed. However, PM emission increases with increase in back-end temperature in the case of conventional diesel fuel. It seems that the heavy component of the F-T fuel does not behave in the same way as the heavy back-end of the conventional diesel fuel. When operated on F-T diesel fuel, a diesel engine with a modified piston bowl showed an improvement in NOX emissions with a penalty in PM emissions [34]. With this modified piston combined with EGR, a large amount of NOX reduction was achieved in both light-duty and heavy-duty modal tests. Further reduction was also possible, however PM and fuel consumption increased rapidly. The study included use of a “De-NOx” catalyst, although very little detail is provided on the catalyst type and NOx reduction mechanism. Nonetheless, overall DeNOX efficiency increased with F-T diesel fuel compared to 2-D diesel fuel [34]. A higher NOX emission reduction was demonstrated with a combination of a De-NOX catalyst and F-T fuel. The overall De-NOX efficiency was 68% with

247

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CHAPTER 9 Fischer-Tropsch fuels

F-T diesel fuel and 55% with 2-D diesel fuel. However, a fuel consumption penalty of several percent accompanied this improved NOX reduction. Fischer-Tropsch naphtha can be used as a fuel for diesel engines due to its straight chain paraffin content and higher cetane number compared with petroleum naphtha, which has lower cetane number. The initial boiling point of F-T naphtha is much lower than that of conventional diesel fuel. This may lead to a flash point for the F-T naphtha that is below the minimum limit required for a standard diesel fuel. The fuel system may need some modification to avoid vapor lock when F-T naphtha is used in a conventional diesel engine. A typical F-T naphtha with boiling point between 71 and 253 °C showed almost 50% PM reduction compared to diesel fuel [31]. Reduction of PM was higher and NOX was lower with F-T naphtha when compared with F-T diesel fuel.

3. Diesel combustion studies of F-T fuels and impacts on soot characteristics In this section, work by the authors is surveyed in which a fuel produced in a gas-toliquid Fischer-Tropsch (FT) process is compared with two other types of fuels: an ultra low sulfur diesel fuel (BP15), and a pure soybean methyl-ester biodiesel (B100) [26,42,43]. Tables 3 and 4 show fuel composition and property information. The standards by which the fuel properties in Table 4 were measured were also included. The fuel temperature was controlled through a water cooling system and it was monitored during all tests. The mean fuel temperature of all test conditions (combination of different test fuels, operating conditions, injection strategies) is 25.3 °C, 1.0 °C at 95% confidence [44]. The PM and gaseous emissions, PM size distribution, and combustion process are analyzed under baseline, advanced and retarded injection timings. The operating condition (2400 rpm, 64 Nm) was selected Table 3 Composition of test fuels (% wt). Hydrocarbons

BP15

FT

Soybean methyl ester

B100

Paraffins Olefins Aromatics

76.17 1.71 22.12

100 0 0

Palmitic acid Palmitoleic acid Stearic acid Oleic acid Linoleic acid Linolenic acid Araquidic acid Gadoleic acid Behenic acid Erucic acid Linoceric acid Nervonic acid

8.80 0.09 4.55 24.16 52.67 7.74 0.39 0.23 0.41 0.01 0.13 0.01

3 Diesel combustion studies of F-T fuels and impacts

Table 4 Fuel properties. BP15

B100

FT

Standard

Density (g/cm3)a Kinematic viscosity (cSt)b Gross heating value (MJ/kg) Low heating value (MJ/kg)c Acid number (mg KOH/g) % C (wt)d % H (wt)d % O (wt)d ppm S (wt)e Molecular weightf Stoichiometric air-fuel ratiof

0.837 2.53 45.77 42.87 0.04 86.26 13.60 0 15 232.3 14.63

0.8843 4.06 39.84 37.26 0.27 77.09 12.03 10.79 2–5 286.8 12.57

< 0.8 1.87 47.11 43.83 0.04 84.52 15.35 0 BP15 (0.79 nm) > B100 (0.72 nm). The uncertainty is 0.03 nm [43]. The fringe tortuosity histograms were obtained from the extracted fringes of FT, BP15 and B100 soot. As expected from a visual comparison, B100 soot contains a high degree of tortuosity among the lamella. Relative to the distribution for the FT and BP15 soot with 1.7% and 3.2% of the lamella greater than 1.5 in tortuosity ratio, more than 14% of the B100 soot fringe tortuosity histogram is greater than 1.5. In contrast, the BP15 and FT soot contain fringes that have a lower level of tortuosity, with 91% and 85% of the measured fringes having a tortuosity ratio of less than 1.2. As a comparison, B100 soot only contains 58% of fringes with a fringe tortuosity ratio of less than 1.2. The mean of the tortuosity ratio for B100 soot is 1.37, greater than the mean values, 1.14 and 1.17, for the FT and BP15 soot. The uncertainty is 0.021 [43].

3 Diesel combustion studies of F-T fuels and impacts

The HRTEM images of soot generated with the split injection strategy were analyzed in the same methods. Unlike the case of single injection, for split injection, the differences in fringe length and tortuosity are not so apparent using visual comparison of the fringe extraction images. However, the fringe length and tortuosity analysis shows the similar trend as the result obtained from the soot from three different test fuels with the single injection. Visual comparison of the shapes of the fringe length histograms does not indicate any trend. However, the fringe length histogram for the B100 soot has 64% of the lamella smaller than 1 nm in length, while 55% of the fringe length histogram of FT soot is less than 1 nm. Alternatively 7.6% of the B100 soot fringe length histogram is greater than 2 nm while 12% of the lamella in the FT soot are greater than 2 nm. The median of the fringe length histograms shows an order of FT (1.01 nm) > BP15 (0.96 nm) > B100 (0.92 nm). The uncertainty is 0.03 nm [43]. While the trend is the same, the differences in the median fringe length in the case of split injection are not as significant as seen in the case of single injection. Visual comparison of the tortuosity histograms indicates that B100 soot has fringes that contain a wide range of tortuosity, implying high degree of curvature among the lamella of the soot [74]. Relative to the distribution of the FT and BP15 soot with 94% and 83% of the lamella smaller than 1.2 in tortuosity ratio, only 78% of the fringe tortuosity of B100 soot fringe tortuosity histogram is smaller than 1.2. The mean tortuosity ratio of B100 is 1.31, greater than the mean values 1.12 and 1.18, of the FT and BP15 soot, respectively. The uncertainty of tortuosity ratio reported in Ref. [43], 0.021, indicates that the difference in the mean tortuosity ratios between B100 and the other two soot samples is statistically significant. Both the XRD and HRTEM analysis results indicate a relation between soot reactivity and nanostructure. The La derived from XRD patterns and the median fringe lengths derived from HRTEM images were compared directly. It is found that, La, median fringe length versus apparent rate constant for soot oxidation of BP15, FT and B100 soot samples generated with single injection strategies at matched combustion phasing. The result also indicates a qualitative agreement between the results from XRD and HRTEM analysis. The numerical discrepancy between the La obtained by XRD pattern analysis and the median fringe length obtained from the HRTEM image analysis method has been observed by Sharma et al. [75]. The crystallite dimension derived from XRD pattern tends to shift toward larger values, because a small quantity of these will increase the peak height [76]. Using Diamond’s empirical formula may reduce the discrepancy [75,76]. The XRD and HRTEM analysis results of the soot samples generated by the three test fuels using the split injection strategy at matched combustion phasing were also compared. The median fringe lengths qualitatively agree with the trend of the La. The differences in crystalline parameter values (La and median fringe length) and soot reactivity for the soot samples generated by the split injection strategy are not as significant as those for the soot samples generated by the single injection strategy. The results show that La obtained from XRD patterns and median fringe length obtained from TEM images are both indicators of the ratio of edge (active) carbon atoms to basal (inactive) carbon atoms. The ratio directly affects the soot reactivity and notably is more difficult to evaluate by measuring active surface area [77,78].

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The high tortuosity of B100 soot generated by single and split injection is consistent with the smallest crystallite height (Lc) and average number of layers per crystallite (N) derived from XRD pattern. Tortuosity measures the undulation of carbon fringes, which arises from 5- and 7-membered ring structures within the aromatic framework. Therein, high tortuosity in soot nanostructure prevents development of stacked layers [74]. Although the variations in Lc and N are small, B100 soot shows a consistent trend of having smaller valves of Lc and N, indicating smaller crystallites with fewer stacked layers [68]. These observations are confirmed by the fringe tortuosity derived from the TEM images. The relationship between soot nanostructure and soot reactivity is thus confirmed by two independent techniques of XRD (La, N) and HRTEM (fringe length and fringe tortuosity). Tortuosity may affect the fringe separation distance [79], however, the d002 from XRD patterns and fringe separation distances from HRTEM image analysis do not show a relation with the soot reactivity. Both the XRD and HRTEM image analyses yields separation distances between 0.36–0.38 nm. This suggests that the differences in soot reactivity are not dominated by the initial separation between fringes. As Sections 2 and 3 have shown, there are a number of beneficial impacts and features of F-T diesel fuel under conventional diesel combustion processes. As the next section discusses, there are also benefits from F-T fuels under advanced combustion strategies that rely on “low temperature combustion,” where in high levels of exhaust gas recirculation (EGR) are used to dilute the fuel-air charge.

4. F-T fuel impacts on advanced diesel combustion processes Advanced combustion modes combine the advantages of traditional spark-ignition (SI) and compression-ignition (CI) engines, and which can decrease engine-out emissions while maintaining fuel conversion efficiency. Homogenous charge compression ignition (HCCI) combustion has offered the promise of achieving high thermal efficiency while significantly reducing NOx and PM emissions [80]. However, HCCI combustion is limited to low loads, since it is very difficult to control the ignition timing and combustion rate. Several other combustion modes are derived from the HCCI combustion concept: low-temperature combustion (LTC), partially-premixed charge compression ignition (PCCI), and reactivity controlled compression ignition (RCCI) combustion modes. Partially premixed charge compression ignition combustion (PCCI) processes offer a practical means of achieving HCCI-like combustion in a diesel engine [81]. PCCI combustion applies very early or late injection timing, low compression ratio and high EGR level to achieve a separation between the end of injection and the start of combustion, which can give enough time to create a premixed charge inside the cylinder. PCCI combustion can also use port injection and direct injection together [82]. Low cetane number fuel also provides an effective way to achieve

4 F-T fuel impacts on advanced diesel combustion processes

ignition delay for PCCI combustion [83]. Soot and NOx emissions are much reduced compared to traditional CI engines. PCCI provides an effective way to reduce the soot and NOx emissions over a greater range of engine load than HCCI combustion can permit. However, PCCI combustion poses several challenges. It is still limited to light to medium loads and can lead to high levels of THC and CO emission [84,85]. Early injection PCCI combustion mode can utilize multiple early injections [86] or port injection to achieve a partially premixed mixture, while an additional direct injection near TDC can be used to control ignition timing and extend engine operation to higher load. Early single direct injection can help vaporize fuel and promote mixing, although very early injection can cause wall wetting which consequently reduces thermal efficiency and increases THC emissions. Late injection PCCI can also be used to achieve sufficient ignition delay for good mixing, with the advantage of providing better control over the combustion phasing [87]. Higher injection pressure during PCCI combustion helps to achieve a more premixed mixture, which can reduce PM emissions but may cause slightly higher NOx emissions [88]. With regard to fuel, cetane number, aromatic content and distillation temperature are the three primary factors that affect PCCI combustion [89]. Other parameters such as oxygen content, viscosity and density can also impact PCCI combustion. Generally, low cetane number, low distillation temperature and low viscosity fuels are preferred to lengthen the ignition delay and reach a more homogenous mixture inside the cylinder before ignition occurs, which can effectively reduce soot emissions. Cetane number is considered to be the most significant factor. Low cetane number (CN) fuel is applied to lengthen the ignition delay and provide more time for premixing, as well as to extend the load range [90–92]. However, low CN fuels still have problems at low load and high EGR conditions because of ignition difficulty, and result in higher fuel consumption. Higher pressure oscillation, ringing and enhanced heat transfer after combustion are also problems for low CN fuels [93]. With the increasing of fuel aromatic content, the density and viscosity of the fuel would increase while the CN would decrease. Neill et al. [94] showed that higher PM and NOx emissions will result from high aromatic content fuel. The high PM emissions for high aromatic content fuel is due to the high carbon content, and the ring structure of aromatics can strongly assist soot precursor formation. The higher adiabatic flame temperature can effectively advance the combustion phasing for high aromatic fuel, which can increase NOx emissions. Paraffinic fuels have shorter ignition delay compared to aromatic fuels, because the chain structure is much easier to decompose than aromatic rings. As a result, paraffinic fuel can keep the combustion efficiency high even with very late injection timings. The shorter ignition delay for paraffinic fuel can effectively increase the combustion duration and decrease the maximum rate of heat release, which can reduce the NOx emissions. CO and UHC emissions are also reduced by paraffinic fuels because aromatic fuels achieve a leaner mixture before ignition occurs.

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Low distillation temperature fuel can improve the homogeneity of the mixture before ignition occurs. The reduced local equivalence ratio can highly suppress the PM formation, which could improve the soot-NOx trade-off [95]. In addition, thermal efficiency can also be improved by low distillation temperature fuel. Oxygenated fuels are used to reduce soot emissions. High oxygen content fuels can reduce local fuel/air ratio and reduce soot emissions as a consequence. Biodiesel is also known to reduce CO, UHC and soot emissions simultaneously. However, NOx emissions can increase with some oxygenated fuels [96–98]. Lilik and Boehman [30] found that during PCCI combustion, high ignition quality fuel can reduce incomplete combustion products arising from an over-lean charge. They showed that LTFT fuel can reduce PM, NOx, CO and THC simultaneously with a slight increase in brake thermal efficiency (BTE). As a high CN fuel, LTFT will have a lower lean limit of combustion than a low CN fuel. With a short ignition delay, incomplete combustion products, CO and THC, are reduced because over-lean charge is avoided. Reduced bulk cylinder temperature reduces NOx emissions. PM emissions are also reduced due to the low aromatic content of LTFT fuel and the premixed combustion. However, cetane number alone does not provide this effect. A means of reducing unburned CO and THC from PCCI combustion, in addition to PM and NOx, is to utilize a fuel with high n-alkane content and high cetane number. The key to this effect is to use a fuel with a low critical equivalence ratio [28]. In other words, one needs a fuel that burns to completion under lean, dilute, low temperature conditions. LTFT fuel has very high n-alkane content, which has higher reactivity compared to fuels with high aromatic content. As a result, LTFT fuel will auto-ignite at a lower equivalence ratio, which means it has a low “critical equivalence ratio” (a concept introduced by Musculus et al. to describe localized regions in the engine cylinder that be potential sources of incomplete combustion [99]). This section summarizes recent past work by the authors comparing an ultra low sulfur diesel fuel, a low temperature Fischer-Tropsch fuel and a renewable diesel fuel (hydrodeoxygenated camellina oil) under conventional and low temperature combustion conditions. The low temperature combustion mode used in this work is partially-premixed charge compression ignition, which employs a single main injection and high levels of EGR. Properties of the test fuels are included in Table 5. The engine operating conditions in these experiments are listed in Table 6. The test engine is a 1.9 L GM light duty turbodiesel engine, described in detail in previous publications.

4.1 Heat release rate LTFT fuel has higher peak ROHR during PCCI combustion. ULSD fuel has longer ignition delays compared to LTFT fuel due to its low cetane number and high aromatic content, while LTFT fuel have similar ignition delays for both conventional and PCCI combustion modes. Here ignition delay is defined as the time interval

4 F-T fuel impacts on advanced diesel combustion processes

Table 5 Test fuel properties.

Cetane number C (wt%) H (wt%) Molar H/C (A/F)s, dry Density (kg/m3) Lower heating value (MJ/kg) Aromatics (wt%) Polycyclic aromatics (wt%) Saturates (wt%) n-Alkanes (wt%) T50 (°C) T90 (°C) Kinematic viscosity @40 °C (mm2/s) Sulfur (ppm wt)

ULSD

LTFT

Renewable diesel

45.1 87.32 13.34 1.820 14.47 831.8 42.6 31.5 8.3 – 32.3 256 312 2.40

81 84.3 15.2 2.183 14.98 760 43.8 0 0 99 72 236 308 1.87

89.2 84.86 15.09 2.119 14.89 784.4 43.9 0.7 0.1 94 32.2 300 315 3.61

10

2

4.0

Table 6 Engine test conditions for low temperature combustion study. Conventional Speed (rpm) BMEP Boost (bar) Swirl Injection pressure (bar) EGR rate (%) Pilot injection (obTDC) Main injection timing (obTDC)

ULSD LTFT

1500 2.6 bar 1.06 93% 394 25 19.9 5.5 5.5

RD

5.5

PCCI

600 40 N/A 10.5, 8.5, 6.5, 4.5, 2.5 8.5, 6.5, 4.5, 2.5, 0.5, 1.5, 3.5 8.5, 6.5, 4.5, 2.5, 0.5, 1.5, 3.5

between start of injection and start of combustion, and start of combustion means the crank angle where the apparent ROHR becomes positive. During conventional combustion, ULSD has a higher maximum ROHR due to its lower cetane number and longer ignition delay, which tends to increase the fraction of premixed burn. LTFT fuel have higher cetane numbers and shorter ignition delays during conventional combustion. The reduced fraction of premixed burn reduces the

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maximum ROHR compared to ULSD. For PCCI combustion, high paraffin content LTFT fuel have higher maximum ROHR compared to high aromatic content fuel ULSD. This is because increased injection pressure and higher EGR rate already made the charge well premixed before ignition occurs. So the composition of the fuel dominates the speed of combustion. Because alkane rich fuels have greater autoignition tendency than aromatic fuels, LTFT fuel has faster reaction speed and higher maximum ROHR during PCCI combustion modes. For ULSD, ROHR decreases with retarded injection timing under PCCI combustion. This is because during late injection timings, cylinder expansion can reduce cylinder temperature, which increases the ignition delay and reduces the rate of combustion. As a consequence, with the retarded injection timing, peak ROHR decreases and combustion duration increases. However, with the retarded injection timing, LTFT has increased peak heat release rate and less diffusion combustion, which is closer to the definition of PCCI combustion. This is because retarded injection timing can increase the ignition delay and create a better premixed charge for high ignition quality fuels, which promotes PCCI combustion (Fig. 8).

4.2 NOx emissions There are three important NOx formation processes [100]: (1) Thermal NOx, which is formed via the Zeldovich mechanism and occurs at temperatures above 1800 K. The increase of temperature and reaction time can increase the formation of thermal NOx [101]; (2) Prompt NOx, which involves hydrocarbon fragments as intermediates in the formation of NOx; (3) Fuel NOx, which is generated from nitrogencontaining fuels. Thermal NOx is considered to be the dominant origin for NOx emissions from IC engines. As a consequence, the formation of NOx depends highly on temperature [102]. PCCI combustion can greatly reduce NOx emissions due to the reduced combustion temperature and reduced oxygen concentration. The higher heat capacity of CO2 in the EGR gas can act as a thermal sink. Increased rates of EGR can effectively increase the heat capacity of exhaust gas, and reduce oxygen content and combustion temperature, which can suppress NOx formation. With retarded injection timing, the piston is moving away from TDC when combustion occurs, and cylinder temperature is reduced during the expansion stroke. Cylinder volume expansion can reduce cylinder temperature and combustion speed. More importantly, with the delay of combustion phasing, the time allowed for NOx formation under high temperature is also reduced. As a result, NOx emissions are further decreased with late injection timing under PCCI combustion. With retarded injection timing, the piston is moving away from TDC when combustion occurs, and cylinder temperature is reduced during the expansion stroke. Cylinder volume expansion can reduce cylinder temperature and combustion speed. More importantly, with the delay of combustion phasing, the time allowed for NOx formation under high temperature is also reduced. As a result, NOx emissions are further decreased with late injection timing under PCCI combustion.

4 F-T fuel impacts on advanced diesel combustion processes

FIG. 8 Heat release rate for conventional and PCCI combustion modes for (A) ULSD, (B) LTFT and (C) RD fuels.

Fuel with higher aromatic content like ULSD generally has higher NOx emissions [103], due to the higher adiabatic flame temperature for aromatic fuels. Although the maximum heat release rate of ULSD fuel is the lower with similar CA50 (timing of the mid-point of fuel mass burn), according to Szybist et al. [39], timing for maximum cylinder temperature has the most significant correlation to NOx emissions as compared to maximum cylinder temperature, maximum heat release rate, and timing of maximum heat release. ULSD reaches maximum cylinder temperature earlier compared to LTFT. This could be caused by the relatively earlier low temperature heat release. Cylinder temperature increases to a maximum quickly and then reduces slowly. As a result, longer time is provided for NOx formation if cylinder temperature reaches a maximum earlier. ULSD has a low cetane number, so

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it has a longer ignition delay, which can provide longer time for the charge to premix with air before combustion occurs. Higher combustion temperature and higher local oxygen concentration can both promote NOx formation. Northrop et al. [104] showed that NOx emissions are primarily a factor of combustion phasing under PCCI combustion, regardless of the type of fuel, injection timing or pressure. They found similar NOx emissions among fuels for a given CA50, whether combustion phasing was adjusted by injection timing or pressure. ULSD has slightly higher NOx emissions compared to the other two fuels under early PCCI combustion, due to the higher adiabatic flame temperature caused by the high aromatic content. Conventional combustion still has significantly higher NOx emissions with similar CA50 compared to PCCI combustion.

4.3 CO and UHC emissions Hydrocarbon emissions from PCCI combustion are generated from several sources [105], (1) over lean mixture from the clearance volume, crevice and squish volume; (2) over rich mixtures near the injector; (3) piston-top and ring crevice films; (4) liquid fuel dribble from the injector or late cycle vaporization from the injector sac. Increased CO emissions from PCCI combustion are mainly caused by the low combustion temperature, which lowers the concentration of OH radicals and results in reduced CO to CO2 conversion rate [106]. CO mass typically originates from the crevice and boundary layer when the peak cylinder temperature is between 1000 and 1400 K [107]. The incomplete combustion of over-lean mixtures is considered to be the major source of CO and THC emissions, especially from the region near the injector where the last fuel to be injected has very low momentum [99]. As a consequence, PCCI combustion generally has higher CO and THC emissions as compared to conventional combustion due to the increased ignition delay which can promote over-lean mixing and reduced combustion temperature. Han et al. [108] demonstrated that methods that extend PCCI ignition delay, such as increased EGR, increased gasoline portion in a diesel-gasoline fuel blend, or reduced intake pressure, tend to increase THC emissions. In contrast, CO emissions from PCCI combustion tend to be dominated by global equivalence ratio. In the case of ULSD, early PCCI combustion produces lower CO and THC emissions than conventional combustion. Late PCCI combustion produces higher CO and THC than conventional combustion. This is because the low cetane number ULSD results in longer ignition delay even during conventional combustion. As a result, THC and CO emissions are high for ULSD under conventional combustion due to the lean mixture formed prior to ignition. LTFT fuel has very short ignition delay during conventional combustion. For LTFT fuel, all PCCI combustion conditions produce both higher THC and CO emissions compared to conventional combustion. CO and THC emissions further increase with retarded injection timing under PCCI combustion, because combustion temperature reduces with late injection

4 F-T fuel impacts on advanced diesel combustion processes

timing. With retarded injection timing, the prolonged ignition delay can also cause over mixing of fuel and air as well as fuel impingement, which can result in higher CO and THC emissions. In addition, the lack of time for combustion with delayed injection timing can also cause more incomplete combustion. The high cetane number LTFT fuel has shorter ignition delay compared to low cetane number fuel ULSD. The reduced ignition delay can reduce the portion of over lean charge and fuel impingement on the cylinder wall, which can effectively reduce THC and CO emissions. Less premixed charge can also increase local combustion temperature and improve the concentration of the radical pool, thus reducing incomplete combustion products CO and THC. In addition, aromatic hydrocarbons have higher ignition temperatures than alkanes. The high alkane content of LTFT also contributes to the reduction of CO and THC emissions because alkane content has higher reactivity and lower ignition temperature [109]. A high saturate content can serve similarly to a high n-alkane content to suppress CO and THC emissions, for mildly branched isoalkanes [110].

4.4 THC-NOx trade-off Although PCCI combustion provides an efficient way to reduce NOx and soot emissions simultaneously, THC and CO emissions increase due to reduced combustion temperatures and increased mixing and dilution. High cetane number and high alkane content fuel LTFT fuel produces less THC and CO emissions compared to higher aromatic ULSD fuel under PCCI combustion. However, NOx emissions depend more on the EGR ratio or in-cylinder O2 concentration than the difference of fuel properties [111]. In addition, the high cetane number of LTFT fuel reduces ignition delay and further reduces the amount of over-mixing and overly lean combustion. For this reason, the high cetane number, low aromatic LTFT fuel can significantly improve the NOx-THC trade-off curve.

4.5 Filter smoke number LTFT fuel has higher filter smoke number (FSN) compared to ULSD fuel, under both conventional and PCCI combustion. Low cetane number fuels yield reduced soot emissions during PCCI combustion [112]. Low CN fuels have longer ignition delay leading to better fuel/air mixing, which could reduce local equivalence ratio and suppress soot emission. Aromatic content has the secondary effect on soot emissions. High aromatic fuel has the tendency to increase soot emissions [111]. The ignition dwell could be negative for high CN fuels like LTFT fuel, which generates some diffusion burning and results in higher FSNs. These trends in FSN as well as PM emissions suggested that for the LTFT fuel, some amount of diffusion burning is occurring, since the short ignition delay with the high cetane number LTFT fuel leads to overlap of the fuel injection duration and the combustion process.

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Under PCCI combustion, higher injection pressure and better premixing can reduce local equivalence ratio. Increased EGR ratio and modified combustion phasing can reduce combustion temperature. As a consequence, soot emissions are greatly reduced due to the reduced local equivalence ratio and combustion temperature, which avoids the in-cylinder conditions that promote soot formation. As injection timing is retarded during PCCI combustion, FSN first increases and then decreases. Soot production from an IC engine is a competition between soot formation and soot oxidation [113]. The combustion phasing is not optimized with very early injection timing, which reduces the peak cylinder temperature and suppresses the soot formation. With late injection timing, ignition delay is also prolonged due to reduced temperature. Combustion occurs during the expansion stroke which reduces the combustion temperature and avoids soot formation. As a result, soot emissions are reduced with both early and late injection timing.

4.6 PM emissions LTFT reduces total PM emissions despite the increased FSN. The nature of PM from PCCI combustion is quite different from PM of conventional combustion. The SOF of PM from PCCI combustion is much higher [114]. Conventional combustion produces much higher soot emissions according to the smoke number. However, ULSD yields much higher PM emissions for PCCI combustion than conventional combustion due to the high SOF content under PCCI combustion. For LTFT fuel, which yields relatively low SOF within its PM emissions, PCCI combustion produces lower PM emissions than the conventional combustion mode. Compared to LTFT, ULSD produces higher total PM emissions but lower soot emissions. This means there is a higher SOF of the PM produced by ULSD. This is also suggested by the higher THC emissions from ULSD fuel. An increase in cetane number [115] and reduction in aromatic content [116] can both reduce the SOF within PM emissions. As a low viscosity, high cetane number and n-alkane content fuel, LTFT fuel yields lower SOF content compared to ULSD under PCCI combustion. With the retarding of injection timing, PM emissions for LTFT fuel followed the same trend as FSN. However, PM emissions for ULSD increase greatly with retarding of the injection timing, despite its very low FSN under late PCCI combustion mode. This indicates that ULSD soot has very high SOF content under late injection PCCI condition, which is caused by the lack of time and temperature for complete combustion and increased unburned hydrocarbon emissions.

4.7 Particle size distribution PCCI combustion generally shifts particles to smaller aggregation size compared to conventional combustion [117,118]. LTFT fuel can effectively reduce total particle emissions under late injection PCCI combustion mode. Total particle number

4 F-T fuel impacts on advanced diesel combustion processes

follows a similar trend as total PM mass. For ULSD fuel, total particle number is increased by PCCI combustion mode, especially with the latest injection timing condition due to the increased SOF content. For LTFT, conventional and PCCI combustion modes have comparable particle number and size distributions. Total particle number increases and the size distribution moves to larger particle sizes as injection timing is retarded. Total PM and the SOF content increase with retarded injection timing, due to the lack of time for complete combustion. Compared to the FSN results, with similar soot emissions, high SOF content can increase PM aggregate size. However, for the latest injection timing PCCI condition, both particle size and number are reduced, which indicates that the nature of the particles produced under this condition may be different from other conditions.

4.8 BSFC and BTE LTFT has lower BSFC due to its higher lower heating value. PCCI combustion results in slightly higher BSFC compared to conventional combustion, which results from the incomplete combustion and the non-optimized spontaneous ignition of the premixed charge [119]. BSFC is increased with early injection PCCI combustion because combustion occurs before the piston reaches TDC, and the enhanced heat transfer to the cylinder walls. BSFC also increases with late injection timing, because of reduced effective expansion ratio and fuel energy loss due to incomplete combustion. LTFT fuel has slightly higher lower heating values (LHV) than ULSD, which results in slightly lower BSFC. In addition, LTFT fuel has higher BTE than ULSD fuel because LTFT fuel has better optimized heat release rate. PCCI combustion with optimized injection timing has similar or slightly higher BTE compared to conventional combustion. However, PCCI combustion with retarded injection timing has reduced BTE because combustion occurs during the expansion stroke which reduces the thermal efficiency.

4.9 Soot reactivity analysis PM from PCCI combustion has higher VOF content compared to PM generated from conventional combustion, which is in agreement with several other PCCI studies [114,120]. This is because the reduced combustion temperature leads to an increased level of unburned hydrocarbons condensed onto the surface of the soot aggregates. In addition, PM produced from LTFT fuel has less VOF compared to PM produced from ULSD under conventional combustion condition. As fuels with high cetane number, high alkane content and low viscosity, PM from LTFT fuel yields lower VOF content than PM from ULSD. Late injection PCCI combustion produces soot with significantly higher reactivity compared to conventional combustion. As fuels with high cetane number and high paraffinic content, LTFT fuel produces soot with lower reactivity compared

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to ULSD. Song et al. [45] and Yehliu et al. [68] also found that LTFT fuel produces soot with lower reactivity compared to ULSD, and biodiesel (an oxygenated fuel) produces soot with the highest reactivity. There are several factors which could explain why PM produced from PCCI combustion shows higher reactivity. To achieve PCCI combustion, higher EGR ratio and late injection timing are applied. Increased level of EGR could result in soot with higher reactivity. The reason could be explained as follows [121,122]: (1) Increased level of EGR could reduce the combustion temperature due to the thermal effect of CO2, which could result in a less severe carbonization process. As a consequence, less mature soot is produced. (2) Reduced temperature could reduce the concentration of reactive radical H, and decrease the production rate of PAH. This dilution effect of EGR can inhibit soot formation and result in soot with less developed nanostructure. (3) CO2 could react with H radical and produce CO and OH radicals, or decompose into CO and O radicals. The OH and O radicals could react with soot precursors and suppress soot formation, which is considered as the chemical effect of EGR. With retarded injection timing under PCCI combustion, combustion temperature is lowered due to the delayed combustion phasing, and local equivalence ratio is reduced because of longer ignition delay. The two factors could result in PM with higher reactivity as explained previously. In addition, soot formation and oxidation history could be altered due to the change of combustion phasing. Soot produced from late injection timings experiences a shorter period under high temperatures, which could reduce the carbonization process, and result in soot with increased reactivity [123]. Fuel formulation also has a strong impact on the reactivity of soot. ULSD produces PM with higher reactivity in this study, which is in agreement with the work of Song et al. [45–47] and Yehliu et al. [68]. The reduced reactivity of PM from LTFT fuel could be caused by the high CN of the two fuels. The shortened ignition delay could increase the local equivalence ratio and combustion temperature, which enhance soot formation and carbonization. The reaction rate constant increases during the oxidation process. Firstly, the opened pore area during oxidation can increase the quantity of active sites. Secondly, graphene layers shrink during oxidation, which also increases the density of active sites. The two factors can increase the oxidation reactivity of soot during the oxidation process. Many factors could impact soot reactivity, such as surface area, surface functional groups, chemical composition and nanostructure. Soot produced from different fuels or engine operating conditions could go through different oxidation processes (Fig. 9).

4.10 Soot surface area analysis Surface area of soot shows no direct relationship with the rate of oxidation. It is considered that, instead of total surface area (TSA), active surface area (ASA) has a closer relationship with soot reactivity [124]. The total number of active sites

4 F-T fuel impacts on advanced diesel combustion processes

FIG. 9 Thermogravimetric analyses for soot generated from conventional and late injection PCCI combustion modes with (A) ULSD, (B) LTFT and (C) RD fuel under isothermal oxidation at 525 °C.

Nt could be described as: Nt ¼ λ*Sa, where λ is the concentration of active sites on the surface, and Sa is the total surface area. Although TSA is found not to be directly related to soot reactivity, ASA is often found to increase with the increase of TSA [125]. In addition, total and active surface areas could change by different magnitude for different soots during the oxidation process, due to the removal of VOF, opened pore area and different oxidation processes. This change in TSA and ASA area during oxidation can also affect soot reactivity. Initial soot BET surface area is generally increased by PCCI combustion mode. Soot produced from LTFT has very similar rate of oxidation and surface areas under both late injection PCCI

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and conventional combustion mode. Under late injection PCCI combustion conditions, ULSD produces soot with lower surface area compared to soot from LTFT, however, with much higher reactivity. This may be caused by the relatively higher VOF content which blocks the pore areas. In addition, surface area increases with retarded injection timing under PCCI combustion for LTFT fuel. However, ULSD shows the reverse effect, even though the particle aggregates are very small and the structure is amorphous under this particular condition. This indicates soot produced from ULSD late PCCI condition has dramatically different properties compared to the other soots.

4.11 X-ray diffraction Soot generated from PCCI conditions show a slightly smaller number of layers per crystallite. In addition, LTFT fuel at late injection PCCI condition produce soot with smaller stacking height. No clear trend is shown for basal plane diameter of soot generated from the different fuels and conditions. This is because soot produced here is highly disordered and contains a significant amount of amorphous carbon. The uncertainty of the instrument is higher than the variation between samples. In addition, there are also limitations for using Scherrer’s equation for amorphous materials [126].

4.12 X-ray photoelectron spectroscopy Combustion mode has a major impact on soot composition, more so than fuel type. Soot produced from late injection PCCI combustion conditions contains much higher concentrations of oxygen compared to conventional combustion conditions, indicating higher concentrations of surface oxygen functional groups within late injection PCCI soot. Although surface oxygen content correlates well with oxidative reactivity, previous research has found that surface functional groups do not necessarily affect the reactivity of soot [69]. Defect/graphitic carbon ratio correlates well with the rate constant of soot oxidation. Here the defect carbon means amorphous carbon with sp3 bonding and fullerene carbon. The graphitic carbon means graphite carbon with sp2 bonding. Soot from conventional combustion has lower defect/graphitic ratio and lower oxidation rate constant compared to soot from PCCI combustion. ULSD has lower CN than LTFT fuel. As a result, longer time is provided for charge mixing and the local equivalence ratio is reduced. ULSD has higher defect carbon ratio and higher oxidation rate constant compared to LTFT fuel. The bonding of amorphous carbon and fullerene carbon is weaker than the bonding of graphite carbon. So those “defect” carbons are more reactive and requires less activation energy during oxidation. Fitting of the XPS C 1 s peak can provide an effective way to predict and explain the oxidative reactivity of soot. Oxidation rate constant generally increase with surface oxygen functional groups. Some researches show that soot reactivity relates with surface

4 F-T fuel impacts on advanced diesel combustion processes

oxygen content [68], while some show that surface oxygen content does not affect soot reactivity [127]. Carbon atoms bonded with oxygen functional groups should require less activation energy during the oxidation process. However, to prevent carbon nanostructure changes under high temperatures, the initial soot is examined without pretreatment, so the oxygen functional groups could also result from VOF coated on the surface of the soot particles.

4.13 Raman spectroscopy The degree of structural disorder could be interpreted by analyzing the spectra. The curve fitting of spectra can follow the method developed by Seong et al. [128], which is a 3L1G method. The three Lorentizan bands are at 1200 cm1 (D4), 1350 cm1 (D1), and 1590 cm1 (G); the Gaussian band is at 1500 cm1 (D3). Both G and D1 peaks represent the features of sp2 bonding. The G mode has E2g symmetry, which involves the in-plane bond-stretching motion of sp2 carbon atoms. The D1 peak comes from the breathing mode of A1g symmetry, which is only present in disordered carbons such as carbon atoms on graphene edges [129]. The D3 peak represents the stretching of sp3 bonding of amorphous carbon. The intensity ratio or area ratio of D1 and G band, and the FWHM of D1 and G band are usually used as indicators of carbon material disorder [130]. The ID1/IG or AD1/AG ratios can be used to represent the density of edge sites [131]. The FWHM of D1 peak can provide information about the distribution of crystallite sizes, and relative abundance of structural disorder [132]. In addition, the G peak broadens as the graphite structure becomes disordered within the carbon layers [133] The intensity or area of the D3 peak could be used to represent amorphous carbon [134]. A linear relationship can be observed between the D1 band FWHM and the oxidation rate constant of soot produced from the three fuels under both conventional and PCCI conditions. A broadened D1 band means a higher density of graphene edge sites. The relationship between G band FWHM and oxidation rate constant has similar trend. The increased G band FWHM also indicates higher degree of disorder for soot particles. PCCI combustion results in soot with larger D1 and G band FWHM for all three fuels, which also have higher oxidation rate constant. So it can be indicated that, the reduced combustion temperature and local equivalence ratio of PCCI combustion can not only increase the density of amorphous carbon, but also can result in particles with smaller graphene layers, higher density of edge sites and more disordered nanostructure. In addition, ULSD produces soot with larger D1 and G band FWHM and higher rate constant compared to LTFT soot. Low CN ULSD also produces soot with smaller graphene size and higher reactivity.

4.14 Transmission electron microscopy Soot usually has a core/shell nanostructure. The core is mainly composed of amorphous carbon, while the shell has small graphene layers which are parallel to the

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particle surface. High resolution TEM images show that soot produced from conventional combustion mode displays a relatively distinct core/shell structure. However, soot produced from late injection PCCI combustion conditions displays a more disordered nanostructure. There are multiple cores within each particle and the graphene layers do not show parallel orientation with some stacking order between adjacent crystallites due to the low combustion temperature [133]. Soot produced from ULSD for the late injection PCCI combustion condition even shows completely amorphous nanostructure. Soot structure rearrangement cannot take place under the relative low temperatures of PCCI combustion. The observations from HRTEM images are in accordance with bulk testing results from XPS and Raman spectroscopy: soot produced from PCCI combustion shows higher amorphous content, and shorter graphene layers with higher concentrations of defects. According to Vander Wal and Mueller [63], soot with smaller graphene layers has a higher concentration of edge sites, which is more reactive compared to carbon atoms in the basal plane. In addition, curvature of the graphene layers can cause bond strain and result in weakened CdC bonds, which can also increase the reactivity of soot particles. As a consequence, the less ordered soot produced from PCCI combustion mode has higher reactivity. Fig. 10 shows high resolution transmission microscope images of soot samples under conventional and two fuel injection timings under PCCI combustion. Soot aggregates show a coagulation effect and much larger aggregation is found during the oxidation process, especially for soot produced under PCCI conditions. In addition, partially oxidized soot aggregates are more compact and show higher fractal dimensions. Soot produced from LTFT fuel under conventional combustion mode show internal oxidation. This is because the inner core of the soot particles is composed of amorphous carbon which is more reactive. For 40% mass burned soot, pore area development [135] with some extent of surface burning is still dominant. The pore areas cannot be observed from HRTEM images at this stage of oxidation. At 75% mass burned, soot became hollow inside after the micropores are fully opened so that the amorphous carbon from the inner core is oxidized. Soot produced from ULSD and PCCI conditions shows a shrinking-core type of oxidation. The primary particle size decreases during oxidation. No layer rearrangement is observed here. Soot particles also become more disordered during oxidation, which agrees with the Raman spectroscopy result. From XPS and Raman Spectroscopy analysis, it could be anticipated that, amorphous carbon oxidizes with graphene layers shrinking. This is because certain crystallite directions are unfavorable for thermal annealing, such as cross-linking. The joining of graphene layers is prevented when the orientation of the graphene layers is not parallel or in stacking order [136]. In addition, no curvature flattening effect was observed, which would allow better ordering and reduces reactivity [137]. For soot produced from PCCI conditions, both primary soot particles and soot aggregates merge together and show blurred boundaries instead of layer rearrangement. This confirms the overall amorphous nanostructure of PCCI soot.

(a)

(b)

(c)

FIG. 10 Transmission electron microscope images at 400,000 magnification for soot produced with LTFT fuel under conventional combustion mode (A) and PCCI combustion mode at injection timings of (B) 1.5°bTDC and (C) 3.5°bTDC. Note the “fullerenic” structures in the PCCI soot images.

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4.15 Summary LTFT fuel can significantly reduce PM emissions due to reduced SOF, and has reduced CO, THC and NOx emissions compared to ULSD. High cetane number and low aromatic content LTFT fuel can effectively reduce PM and NOx emissions simultaneously. Fuels with high n-alkane content can effectively reduce incomplete combustion emissions CO and THC. In addition, low viscosity and low distillation temperature are shown in this work to be important factors for the reduction of emissions. PCCI combustion can be achieved with increased EGR and injection pressure. It provides an effective way to reduce NOx and soot emissions, however, with increased CO and THC emissions. With retarded injection timing in PCCI combustion, combustion phasing is retarded and combustion temperature is reduced. As a result, NOx emissions decrease, CO and THC emissions increase due to over lean combustion. Soot emissions first increase then decrease and PM emissions increase with as injection timing is retarded due to increased SOF content. Soot produced form late injection PCCI combustion conditions shows higher reactivity than soot from conventional combustion conditions. LTFT fuel produces soot with lower reactivity compared to ULSD under both conventional and PCCI combustion modes. Soot produced under PCCI combustion has higher BET surface areas, surface oxygen content and amorphous carbon content. Amorphous carbon content and surface oxygen content correlate well with the oxidation rate constant. In addition, Raman spectroscopy shows that soot from PCCI combustion has smaller graphene layers. As a result, soot from PCCI combustion has higher reactivity than soot from conventional combustion. TEM images also show that soot from PCCI combustion has less ordered nanostructure. PCCI combustion has lower cylinder temperature and local equivalence ratio resulting from higher EGR ratio and longer ignition delay. Those factors caused the soots formed under PCCI combustion conditions to have less mature nanostructure and higher reactivity. Soot from LTFT fuel under conventional combustion shows internal burning during the oxidation process. However, soot with higher reactivity which are produced from PCCI combustion and ULSD show shrinking core oxidation. This can be caused by the overall amorphous nanostructure of PCCI soot. No layer rearrangement is observed during the oxidation process for both conventional and PCCI soot. Amorphous carbon content and graphene layer size both decrease during oxidation.

5. Concluding remarks and future directions Fischer-Tropsch fuels are high value fuels that can be made from any source of H2 and CO mixtures (“syngas”) provided that the necessary ratio of H2/CO is available. Thus F-T fuels represent a perpetual source of highly desirable hydrocarbons to serve as a replacement for petroleum diesel fuel. Challenges include the cost of construction and operation of F-T liquids plants, the low temperature behavior of F-T

5 Concluding remarks and future directions

diesel fuels, and the treatment of engine exhaust pollutants in a world with ever tightening tailpipe emissions standards. The life cycle carbon intensity of F-T fuels can be quite low, and using recycled CO2 and green H2 can potentially approach net zero GHG emissions. Thus, this century old technology has great promise but may be challenged in the century ahead to compete with fuel production routes with lower costs. Some analysts are not optimistic that F-T, as an example of GTL or XTL, will be competitive with other technologies without a carbon cap to make the technology profitable [35]. Ramberg et al. note that of the synthetic fuel pathways, those that produce a diesel fuel or a petrochemical feedstock, have been proven economic, when operated on a large scale. Others argue that the combination of cost and scale-up challenges will limit the impact of all forms of “e-fuels” [36]. Nonetheless, in 2021 and 2022, ExxonMobil and Porsche have announced a series of test programs involving the use of e-fuels as racing fuels, based on recycling of captured CO2 and combining with hydrogen via the MTG technology [138]. Considering the research directions and needs for F-T fuel and XTL overall, there is clear guidance on topics of interest. Van Steen et al. have recommended process improvements through catalyst design that will give better economics for XTL for F-T fuels, which as pointed out earlier in this chapter, is a capital intensive process [139]. They suggest that cobalt-based catalysts may be preferred over iron-based catalysts due to their higher selectivity to C5+ hydrocarbons. Suppiah et al. recommend advancements in catalyst design to permit enhancements in CO2 recycling to valuable fuels and chemicals, an essential component of arresting the growth of the CO2 inventory in the atmosphere [140]. They suggest that for CO2 conversion, the adsorption energy of CO2 on the catalyst surface is a limiting factor, so metalsupport interaction is a key aspect of designing catalysts for superior performance. Fischer and Claeys suggest the complexity of the F-T process and the need for advanced catalyst characterization techniques motivates development and application of in situ catalyst characterization [141]. Their recent review of the application of in situ characterization of F-T catalysts addresses the capabilities of such techniques for catalyst and process improvements. They suggest that in situ characterization can overcome challenges such as highly dynamic behavior and that catalyst oxidation, poisoning, sintering, attrition and phase separation can be better interpreted than when relying on conventional characterization techniques. Karre and Dadburjor have reviewed iron-based catalysts for F-T synthesis with catalyst promotors that enable water-gas-shift (WGS) reaction [142]. They also the reviewed the potential benefits of using zeolite materials as supports for iron-based F-T synthesis catalysts. Kargbo et al. have performed an extensive review comparing the F-T process with other competing routes (pyrolysis, hydrothermal liquefaction and biochemical routes to “drop-in” fuels) for biomass to liquids (“BTL”), including review of techno-economic analysis (TEA) studies [143]. They suggest that F-T synthesis is the most competitive route to drop-in BTL fuels because of the flexibility of F-T synthesis and its commercial experience, whereas other routes need more development and pilot-scale demonstration.

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What we have covered in this chapter are combustion studies that demonstrate the significant benefits of F-T fuels in past and current engine technologies, as well as describing the benefits F-T fuels can have for low temperature combustion processes. It remains to further explore how F-T fuels, including not only F-T diesel but also F-T naphtha, can be designed to support advanced combustion processes. It also remains to explore how F-T fuels can benefit synergistically the next generation of high efficiency diesel engines that may incorporate Miller cycle operation with high compression ratio pistons, such as those being demonstrated in the US Department of Energy Supertruck II program [144].

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CHAPTER

Low temperature combustion

10 Yiguang Ju and Ziyu Wang

Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ, United States

Nomenclature ACI CFE Da DME FLEX HCCI HFE HRR HTC IPCC ISS ITC LTC NASA NTC O2QOOH OQ0 O OQ0 OOH PCCI PLIF QOOH R R0 R0 CO R0 O RCCI RH RI RO2

advanced compression ignition cool flame extinction Damk€ohler number dimethyl ether flame extinguishment homogenous charge compression ignition hot flame extinction heat release rate high temperature combustion Intergovernmental Panel on Climate Change International Space Station intermediate temperature combustion low temperature combustion National Aeronautics and Space Administration negative temperature coefficient peroxy hydroperoxyl alkyl radical ketoalkyloxy radical ketohydroperoxide molecule premixed charge compression ignition planar laser-induced fluorescence hydroperoxyl alkyl radical fuel radical small alkyl radical aldehyde radical alkoxy radical reactivity controlled compression ignition fuel molecule radical index alkylperoxy radical

Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00012-6 Copyright # 2023 Elsevier Inc. All rights reserved.

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SACI SL SP-JSR τ Φ a ω

spark-assisted compression ignition laminar flame speed supercritical jet-stirred reactor low temperature chemical time scale equivalence ratio strain rate low temperature branching rate

1. Introduction The recent IPCC report [1] calls for an immediate action to reduce 45% greenhouse gas emissions by 2030 from the 2010 level and to limit the global temperature rise within 1.5 °C. The improvement of engine efficiency and the utilization of low carbon fuels are the feasible solutions to lower greenhouse gas emissions. To increase the efficiency of internal combustion engines from today’s approximately 38% to 60% for carbon reduction [2], it is critical to develop lean burn and low temperature combustion technologies to reduce heat losses. As such, low temperature combustion (LTC) has attracted renewed attention in research due to its strong relevance to lean burn, ignition and emission control, engine knock, low speed pre-ignition, near-limit flame stabilization and blow-off, and low carbon alternative fuel development [3–8].

1.1 Low temperature combustion concept in advance engines Currently, most of the commercial vehicles on the road has net thermal efficiency below 40% [9]. Fig. 1 illustrates a schematic of the energy input, output, and losses of an advanced diesel engine [10]. It can be noted that the net output thermal efficiency is only 42.3% with 100% fuel energy input. The energy loss in cooling alone accounts for 28.9%. If one assumes the engine peak flame temperature is 2400 K and the engine compression ratio is 16, the Carnot and Otto cycle efficiencies are 87% and 70%, respectively. Therefore, the engine thermal efficiency is limited neither by the Carnot cycle efficiency nor the Otto cycle efficiency, rather by the heat losses from the high temperature combustion to engine walls. To improve engine efficiency and drastically reduce the thermal losses, different LTC technologies such as advanced lean burn gasoline engines [9–11], advanced compression ignition (ACI) and spark-assisted compression ignition (SACI) [12], homogenous charge compression ignition (HCCI) engines [13–15], premixed-charge compression ignition (PCCI) engines [16–19], partially premixed compression ignition (PPCI) engines [8,20,21], and reactivity controlled compression ignition (RCCI) engines [2,12] have received great interest. Furthermore, the LTC strategies have been developed to reduce the harmful emissions from diesel engines. These LTC strategies, such as HCCI, PCCI, and RCCI, reduce engine-out nitrogen oxides (NOx) and soot emissions simultaneously. Hence, an accelerated optimization of internal

1 Introduction

FIG. 1 Schematic of heat balance for an automotive diesel engine. Courtesy by Shuji Kimura;this figure was first published by Y. Ju, Understanding cool flames and warm flames, Proc. Combust. Inst. 38 (2021) 83–119.

combustion engines through newer and more efficient combustion concepts with alternative fuel utilization are vital for reducing emissions in the foreseeable future [22].

1.2 Low temperature flames (cool flame and warm flame) Cool flames and warm flames are the typical phenomena of LTC. Cool flame was first observed by Davy in 1810 [23]. Phenomenologically, a cool flame is a faint blue luminescent reaction front which partially oxidizes fuel into aldehydes, alkenes, and other intermediate small hydrocarbons at a low flame temperature (typically below 800 K) via the alkylperoxy chemistry [4]. Warm flame typically has two luminescent flame fronts, a leading faint blue cool flame front and a trailing brighter blue reaction front, which further converts some of the partially oxidized intermediate species from the cool flame such as aldehydes into CO and H2O with a moderate flame temperature (typically between 800 and 1100 K). The use of fire is a history of mankind civilization. Fig. 2 shows schematically the milestone of the cool flame and warm flame studies. Mankind discovered the use of fire (hot flame) millions of years ago and mastered it for lighting, cooking, agriculture, and machining tools. About 200 years ago, Davy [23] and Perkin [24,25] discovered that a very faintly luminous bluish cool flame played round a heated metal surface when a rich ether and hexane/air mixture was impinged on. Around 2000, Pearlman et al. [26–29] conducted microgravity experiments of premixed cool flames aboard NASA’s KC-135 aircraft. The experiment successfully captured the unsteady outwardly propagating spherical cool flames of fuel rich propane/butane blends after auto-ignition at elevated temperatures.

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FIG. 2 Schematic of the history for observing low temperature flames [4].

Recently, Ju et al. modeled the existence of a propagating cool flame coupled with a hot flame (double flame) for lean n-heptane mixtures at high pressure [30]. Maruta et al. [31] observed a three-stage flame structure for a stoichiometric dimethyl ether (DME)/air mixture in a preheated micro-channel. In 2012, Nayagam [32] and the NASA microgravity team observed that a diffusion cool flame might be formed after the hot flame radiation extinction with a large n-heptane droplet in Flame Extinguishment Experiments (FLEXs) on board the International Space Station (ISS). In 2013, Ju and co-workers succeeded in the establishment of self-sustaining diffusion cool flames in a counterflow setup by plasma and ozone sensitization [33,34]. At the same time, Law and co-workers [35] also observed the negative temperature coefficient (NTC) affected weakly burning diffusion flame with heated air in a counterflow system. In 2015, Reuter et al. [36–38] observed premixed cool flames with sub-limit fuel lean mixtures. Furthermore, similar to the prediction in Ref. [30], a premixed double flame structure with a leading cool flame and a trailing hot flame was successfully observed experimentally at conditions slightly above the fuel lean burn limit of the hot flame. In a shock tube experiment, Hanson and co-workers [39] also observed the spherically expanding transient double flames at near stoichiometric conditions at elevated temperature. More recently, Yehia et al. [40,41] experimentally observed stable diffusion warm flames for both ether and alkane fuels in a counterflow flame with ozone sensitization. At the same time, NASA microgravity experiments also revealed the existence of a warm flame in droplet combustion [42]. In 2022, by using a high pressure counterflow burner, Wang et al. [43] observed the stable cool flame and warm flame of DME up to 5 atm for the first time. In the same year, Kim et al. [44] experimentally observed the spherical cool diffusion flames in the microgravity environment of the ISS. Because of the interest in the development of advanced engines and alternative fuels, low temperature flame research has received renewed interest. Details of these studied can be found in recent review articles [3,4].

1 Introduction

1.3 Low temperature combustion chemistry Low temperature combustion chemistry has been comprehensive reviewed by Battin-Leclerc [45], Za´dor et al. [46], and Wang et al. [47]. Previous studies have shown that the low temperature fuel oxidations are highly dependent on temperature and the radical-branching processes. Fig. 3 shows the schematic of three temperature dependent chain-branching reaction pathways at low (typically below 800 K), intermediate (typically between 800 and 1100 K), and high temperatures (typically above 1100 K). For cool flames, the major low temperature chain-branching reaction pathway is: R ! RO2 ! QOOH ! O2QOOH ! OQ0 O + 2OH. For warm flames, the intermediate temperature chain-branching pathway is: R + HO2 ! RO + OH and R0 CO + O2 ! aldehyde + CO + OH followed by the aldehyde oxidation and hydrogen peroxy chemistry: CH2O ! HCO ! HO2 ! H2O2 ! 2OH. For a hot flame, the high temperature chain-branching pathway is: H + O2 ¼ OH + O [3]. Understanding of these three sets of chain-branching reactions is critical to understand different flame regimes and their temperature, pressure, and oxygen dependence. Nowadays, high pressure and supercritical combustion applications have enormous potential for gas turbines and advanced engines as well as the supercritical CO2 power cycle [48–50]. Under ultra-high pressure conditions, multiple-body collisions and collisional stabilization of radicals begin to cause significant deviations in the rate constants developed at a normal pressure. For example, the reaction rates, even for some well-studied reactions such as CO + OH ¼ CO2 + H, H + O2 (+ M) ¼ HO2 (+ M), and H + O2 ¼ OH + O, might have significant discrepancies between supercritical and normal pressure conditions. Furthermore, thermodynamic properties, such as entropy and enthalpy, also deviate significantly from the ideal gas

Plasma O(1D), O, R, O3 O2(1Δ), N2(v), …

RO2

+O2 alkene

QOOH +O2

Fuel (RH) +(OH, HO2) aldehyde R +O2 +O2 + HO2 +O2+(M) H2O2 R’

O2QOOH

nOH

+O2

+HO2 OQ’O

OQ’OOH

O2Q’(OOH)2

C2H3/CH2O H/HCO +M CO +OH CO2

FIG. 3 A schematic of key reaction pathways at high, intermediate, and low temperatures (blue arrow: below 800 K; yellow arrow: 800–1100 K; red arrow: above 1100 K), respectively [3].

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law at high pressures. Therefore, the understanding of low temperature chemistry at ultra-high pressure is necessary. To explore low temperature and high pressure combustion chemistry, Shao et al. [51] measured the ignition delay times of methane and hydrogen with highly diluted CO2 at 300 bar to investigate the effect of supercritical CO2 on flame ignition. Kogekar et al. [52] studied the real-gas effects on ignition delay time of n-dodecane in a high-pressure shock tube. Liang et al. [50] evaluated the effects of thermodynamic and transport properties on hydrogen and methane flame speed measurements at supercritical conditions. They reported that laminar flame speeds at high pressures increase due to the non-ideal equation of state. Aranda et al. [53] and Hashemi et al. [54–57] used a high pressure laminar flow reactor to study the supercritical oxidation chemistries of methanol, methane, ethane, and propane at 100 bar. Fernandes et al. [57] used a high-pressure flow reactor to perform elementary reaction rate measurements up to 1000 bar. Recently, Zhao et al. [58] and Yan et al. [59] recently studied the low temperature chemistries of n-butane and DME at 100 atm in a supercritical pressure jet-stirred reactor (SP-JSR).

2. Dynamics of low temperature flames

2.1 Premixed cool flame, warm flame, and double flame To understand the dynamics of self-sustaining, planar, and unstretched premixed cool flame, Ju et al. [60,61] simulated one-dimensional freely propagating DME/oxygen flames. Fig. 4A shows the schematic of computed flame temperature

FIG. 4 (A) Schematic of computed flame temperatures and flammability limits of planar freely propagating hot flame, cool flame, and warm flame of DME/O2 mixtures at 1 and 20 atm. (B) A flammability limit diagram for cool, warm, and hot flames at elevated pressure. Region I: hot flame; Region II: either a hot flame, a double flame, or a cool flame, Region III: cool flame, and Region IV: warm flame. Reprinted by permission of Elsevier Science from (A) Y. Ju, C.B. Reuter, S.H. Won, Numerical simulations of premixed cool flames of dimethyl ether/oxygen mixtures, Combust. Flame 162 (2015) 3580–3588 by the Combustion Institute and (B) Y. Ju, On the propagation limits and speeds of premixed cool flames at elevated pressures, Combust. Flame 178 (2017) 61–69 by the Combustion Institute.

2 Dynamics of low temperature flames

as a function of equivalence ratio at 1 and 20 atm. It can be noted that the numerical modeling well-captured the existence of multi-staged warm flame and double flame as well as cool flame on fuel rich mixtures beyond the rich flammability limit of the hot flame. Moreover, it is also predicted the existence of cool flame beyond the lean flammability limit of the hot flame. Furthermore, it was shown that on the fuel rich side at low pressure (1–4 atm), the transition from a hot flame to low temperature flame is smooth without a hot flame extinction. However, the transition from a hot flame to a cool flame shows an extinction-ignition S-curve on the fuel lean side. Therefore, three different flame regimes, cool flame, double flame, and hot flame, can all exist in a broad equivalence ratio range on the fuel lean side. Note that at a planar unstretch condition, the double flame on the S-curve shown in Fig. 4A is not on the stable flame branch. A small perturbation will trigger the double flame to transfer to either a cool flame or a hot flame. However, with either radical loss, heat loss, or flame stretch in a counterflow flame [36,38] or in an unsteady spherical flame propagation [30,39,62], a stable or quasi-steady double flame propagation can be observed. With the increase of pressure (above 5 atm), it is interesting to note that the transition between hot flame and cool flame on the fuel lean side also becomes monotonic due to the appearance of a warm flame. The smooth transition from hot flame to warm flame for fuel lean mixtures remains to be experimentally validated at elevated pressure. Fig. 4B shows the predicted flame regime boundaries and burning limits of lean premixed cool, warm, and hot flames as well as the double flames [61]. Line BAB0 is the lean burn limit of hot flame. Therefore, hot flame only exists on the right-hand side of line BAB0 (regions I and II). Line DE is the fuel lean limit of cool flame and line A0 AC is the upper limit or the reignition limit of cool flame. On the reignition limit (A0 AC), the cool flame will reignite and become a hot flame (see Fig. 4A). As such, cool flame only exists between lines DE and A0 AC in the regions of II and III. Therefore, depending on the initial conditions, one can observe either a hot flame, a cool flame, or even a double flame in region II, where the hot flame and cool flame flammable regions overlap. At high pressure (above point A), the warm flame starts to appear in region IV in the region between lines AA0 and AB0 . With a further increase of pressure, the transition from cool flame to warm flame (line A0 A) occurs at a lower equivalence ratio (higher O2 concentration) due to the enhancement of HO2 chemistry. However, the transition from a warm flame to a hot flame is much less sensitive to pressure because hot flame has a stronger temperature dependency of the chain-branching reactions. The transition between the cool flame and warm flame as well as the hot flame at high pressure is also a smooth transition for fuel lean mixtures. Therefore, understanding the burning limits of different flame regimes and the transitions will help to understand the dynamics of cool flame, warm flame, and hot flame to develop advanced engines and fuels. Fig. 5 shows the pressure dependence of normalized flame temperatures and flame speeds by their values at 1 atm for the hot flames as well as the lean and rich cool flames [61]. It is seen that the flame temperatures of hot flame and rich cool flame only have negligible dependence on pressure. However, the lean cool flame

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FIG. 5 The pressure dependence of flame temperatures and speeds normalized by that at 1 atm, respectively, for hot flame and cool flames on the fuel lean and fuel rich sides for DME/air. Reprinted by permission of Elsevier Science from Y. Ju, On the propagation limits and speeds of premixed cool flames at elevated pressures, Combust. Flame 178 (2017) 61–69 by the Combustion Institute.

temperature increases considerably with pressure due to the strong oxygen dependence of low temperature chemistry. The normalized flame speeds of hot flame and lean cool flame both decrease with pressure despite of their significant difference in pressure dependences of high temperature chemistry and low temperature chemistry. For a hot flame, the dependence of flame speed on pressure is often given by n P21, where n is the overall global reaction order. However, the cool flame chemistry has a stronger pressure and oxygen dependence due to the unimolecular reactions such as RO2 chemistry. On one hand, an increase of pressure enhances the low temperature reactivity and increases the cool flame speed. On the other hand, the increase of temperature via the increased low temperature reactivity by pressure will slowdown the reactivity due to the NTC effect. This is why an increase of pressure slows down the fuel lean cool flame speed dramatically. Therefore, in considering the strong pressure and oxygen concentration dependence of low temperature chemistry as well as the NTC effect, the cool flame speed as a function of pressure can be modified as: n

SL  P21+α

(1)

where α < 0 for fuel lean mixture, 0 < α < 1 for fuel rich mixture. To observe the self-stabilized lean premixed cool flames, Reuter et al. [36] and Zhao et al. [63] conducted the counterflow experiments for DME/oxygen mixtures with and without ozone addition. Ozone plays an important role to sensitize the LTC of DME to enable cool flame stabilization at low preheating temperature although an auto-ignition assisted premixed cool flame can be sustained without ozone at high inert N2 temperature [63]. Fig. 6 shows the schematic of the counterflow setup [36]. The upper burner nozzle ejects nitrogen preheated up to 600 K. The lower oxidizer stream consists of pure oxygen, which passes through a non-equilibrium plasma ozone generator to produce ozone, and DME at 300 K. The axial velocity

2 Dynamics of low temperature flames

FIG. 6 (Left) Schematic of the ozone-assisted counterflow burner. (Right) (a) Direct image of cool flame and (b) a hot flame image at Φ ¼ 0.114 and a strain rate of a ¼ 89 s1. (c) A double flame image at a ¼ 59 s1 and Φ ¼ 0.087 [38]. Reprinted by permission of Elsevier Science from C.B. Reuter, S.H. Won, Y. Ju, Experimental study of the dynamics and structure of self-sustaining premixed cool flames using a counterflow burner, Combust. Flame 166 (2016) 125–132 by the Combustion Institute.

gradient at the oxidizer side is defined as a global strain rate, a ¼ 

  1=2 2Uo =L 1+ UUof ρρf , where Uo and Uf are the flow velocities of oxidizer and o

fuel side streams, ρo and ρf are the densities of those two streams, and L is the separation distance between two nozzles. Fig. 6a and b shows the direct images of DME/ O2/O3 premixed cool flame and hot flame at the same conditions of Φ ¼ 0.114 and a ¼ 89 s1. The CH2O PLIF images showed that cool flame had a very high concentration of CH2O formed through low temperature chemistry [36]. However, CH2O in the hot flame was low and only existed in front of the high temperature reaction zone. Fig. 6c shows a double flame image at a ¼ 59 s1 and Φ ¼ 0.087 [38], where the lower dimmer zone is a premixed cool flame and upper brighter zone is a hot flame. Reuter et al. [38] further measured the cool flame extinction (CFE) limit, the hot flame extinction (HFE) limit, and the structure of near-limit hot flames. With the decrease of equivalence ratio, the extinction limit of hot flame became lower than the cool flame. This result indicates that a cool flame can burn at the sub-limit condition of a hot flame, which supports the schematics in Fig. 4. Note that when the equivalence ratio is slightly above the hot flame flammability limit, a stable nearlimit double flame appears. As shown in Fig. 4A, an unstretched planar double flame is not stable. However, the heat and radical losses due to the finite flow residence time could stabilize a double flame in a counterflow setup. Note that a double flame is different from a warm flame. The former is a two-stage flame governed by low temperature chemistry and high temperature chemistry and can exist only above the hot flame lean flammability limit (Region II in Fig. 4B). The latter is a two-stage flame governed by low temperature chemistry and intermediate temperature chemistry chain-branching reaction pathways and can exist only below the lean hot flame flammability limit (Region IV in Fig. 4B) or above the rich hot flame burning limit.

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Therefore, by using an atmospheric counterflow flame with ozone sensitization, one can observe all three low temperature premixed flame regimes: cool flame, hot flame, and double flame shown in Fig. 4. If one raises the pressure, as the low temperature chain-branching reaction pathway becomes faster, a stable warm flame could be observed as well.

2.2 Non-premixed cool flames and warm flames 2.2.1 Droplet cool flames and warm flames The first observation of a diffusion cool flame was made in microgravity droplet combustion conducted in the FLEX program on board the ISS [32]. The results showed that a large n-heptane droplet exhibited dual modes of combustion, the high temperature hot flame and the low temperature cool flame. Fig. 7 shows the dependence of the flame size and the square of the droplet diameter on the time after

FIG. 7 Three representative examples of radiative extinction and subsequent second-stage combustion of n-heptane droplets with different droplet diameters, showing the flame diameter (df) and the square of the droplet radius (d2) as a function of time. Vertical solid lines denote the end of OH* emissions, and vertical dotted lines denote the second-stage extinction. The insets are a representative UV camera flame image taken during the hot-flame stage (top), a backlit droplet image during the second stage (middle), and a fuel vapor cloud image after the second extinction (bottom) at the transition point. Reprinted by permission of Elsevier Science from V. Nayagam, D.L. Dietrich, P.V. Ferkul, M.C. Hicks, F.A. Williams, Can cool flames support quasi-steady alkane droplet burning?, Combust. Flame 159 (2012) 3583–3588 by the Combustion Institute.

2 Dynamics of low temperature flames

ignition at three free-floating droplet burning conditions. It can be noted that the typical quasi-linear relation between the square of the droplet diameter and time of the high temperature droplet combustion was observed right after the hot flame ignition at t ¼ 0 s. However, after the hot flame extinction with a rapid drop of flame luminescence, the decreasing rate of droplet size was unchanged until 35, 26, or 13 s, respectively, depending on the initial droplet size. To explain the abnormal phenomenon, it was suggested that the continued droplet burning after the radiative extinction of the hot flame was a cool flame [32]. Recently, microgravity cool flame experiments were further extended to bicomponent droplets of n-decane/hexanol blends (50/50 by volume) at higher pressures [64]. The results revealed that the transition from radiative extinction of hot flame to cool flame has oscillatory multicycle reignition where the flame undergoes multiple hot-cool flame transitions [65]. The results also showed that, depending on the ignition energy, there exists a direct ignition to cool flame transition without radiative extinction of a hot flame when the ignition source is carefully controlled [66]. The bi-component n-decane/hexanol experiments [64] showed even more intriguing cool flame extinction and reignition phenomena at elevated pressure. At 2 atm, the results showed that the large fiber-supported hot flame radiatively extinguished and then became a cool flame for a period before the cool flame re-ignited to a hot flame. At 3 atm, the hot flame again radiatively extinguished and burned with a cool flame without the cool flame reignition to a hot flame phenomenon. The droplet burned to completion with a cool flame. More recently, FLEX 1268 experiment [42] of n-dodecane droplet burning at elevated pressure (2.7 atm) in air diluted with helium revealed that there was a transient three-stage (hot flame, warm flame, and cool flame) burning behavior. The numerical and experimental results showed that the diffusion heat transfer, enhanced by helium substitution, extended the second-stage warm flame burning mode until the heat loss became too large. Therefore, both chemistry and transport process affect the dynamics of cool flame and warm flame.

2.2.2 Counterflow cool flames and warm flames Since 2013, self-sustaining non-premixed cool flames have been successfully established in the counterflow configuration at Princeton with and without plasma and ozone sensitization [33,34]. Early studies on non-premixed counterflow cool flames began with numerical modeling of the NTC effect on ignition limit [67]. Law and Zhao [67,68] studied the NTC effect on the ignition and extinction of n-heptane/ air in the non-premixed counterflow configuration numerically. Won et al. [33] and Sun et al. [34] successfully stabilized a self-sustaining n-heptane and DME/ O2 non-premixed cool flame in a counterflow burner with plasma and ozone sensitization. Deng et al. [35,69] studied the hysteretic ignition and extinction behavior of non-premixed DME/air cool flame at 1–3 atm. They reported that significant discrepancies existed for the extinction temperatures even with the well-developed reaction model. Possible reason for the discrepancy is the uncertainty of the branching ratio of QOOH decomposition and oxygen addition.

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More recently, Yehia et al. [40] conducted atmospheric non-premixed warm flame experiments using dibutyl ether/oxygen/ozone in a counterflow burner. They observed a self-sustaining low temperature non-premixed warm flame, existing between the cool flame and hot flame. Fig. 8 (left) shows a direct image of a two-stage dibutyl ether warm flame. The warm flame has two reaction zones, a leading cool flame on the fuel side (top burner) and an intermediate temperature flame on the oxidizer side (bottom burner). Fig. 8 (right) shows the computed species mole fractions and heat release rate distribution. It is clearly seen that there are two heat release zones. The heat release rate and OH concentration in the ITC reaction zone is higher than that in the LTC reaction zone. The cool flame on the fuel side was formed by the oxygen leakage from the ITC reaction zone. The ITC reaction zone for intermediate temperature on the right is formed via the fuel fragments from the cool flame at a higher oxygen concentration on the oxygen side. Numerical analysis showed that different from the cool flames, the most important elementary reactions for the warm flames are the HO2 chemistry and the intermediate temperature chain-branching reactions. Yehia et al. [41] later observed the two-stage non-premixed warm flame formation for n-alkanes in the same setup. However, the prediction and experiment have large discrepancy in the transition limits between cool flame and warm flame. The uncertainty of HO2 chemistry for warm flame needs to be addressed in the future. To understand the flame dynamics of non-premixed cool flame and warm flame and their relationship with hot flame burning limits. Lin et al. [70] simulated near-limit DME/O2 diffusion flames at different pressures, temperatures, and oxygen and fuel concentrations with and without radiation heat loss. There are three different branches (hot flame, warm flame, cool flame) for the adiabatic flame at high pressure. When radiative heat loss is considered, the hot flame branch and the low temperature flame branch are separated.

FIG. 8 Left: Direct image of multi-stage non-premixed warm flame of dibutyl ether/oxygen/ozone in a counterflow configuration. Right: Simulated species mole fraction and chemical heat release rate distributions. Reprinted by permission of Elsevier Science from O.R. Yehia, C.B. Reuter, Y. Ju, Low-temperature multistage warm diffusion flames, Combust. Flame 195 (2018) 63–74 by the Combustion Institute.

2 Dynamics of low temperature flames

To utilize cool flame extinction limit for ranking the low temperature fuel reactivity, Zhou et al. [71] studied the cool flame radical index and the effect of oxygen concentration [O2] on non-premixed cool flame extinction of large n-alkanes. It was shown that oxygen concentration has significant effects on the global low temperature chain-branching reactions. The multiple oxygen addition reactions R + O2 ¼ RO2 and QOOH + O2 ¼ O2QOOH are two major steps in low temperature reaction pathways. The global low temperature chain-branching reaction rate (ω) is inversely proportional to low temperature chemical time scale (τ), which can be estimated by the cool flame residence time at extinction (1/aE). Fig. 9A shows the experimentally measured cool flame residence time at extinction limit versus oxygen concentration for large n-alkanes, with the corresponding fitting curve. Fig. 9A shows the slopes of oxygen dependence for different fuels are proportional to [O2]n with n (1.61–1.89). Three key reactions (R + O2 ¼ RO2, RO2 ¼ QOOH, and QOOH + O2 ¼ O2QOOH) are considered to understand the nonlinear oxygen dependence of cool flame extinction. A further assumption is that RO2 and QOOH are quasi-steady state species. It can be simply deduced that ω  1τ  aE  ½O2 2. Hence, the slope of [O2] and 1/aE in the logarithmic plot should be 2. However, because the reactions occur both forward and backwards, the concentration of the O2 involved in the reactions is strictly lower than the one in n ¼ 2, especially for the cool flame near extinction. In addition, the NTC effect via these backward reactions and decomposition of QOOH further slows down the low temperature reactivity. This explains why the present measured slopes are between 1.61 and  1.89. Note that the oxygen concentration dependence of the cool flame is different from that of hot flame, where is mainly governed by one chain-branching reaction (H + O2 ¼ OH + O). The extinction limits of diffusion cool flames are governed by the combination of chemical kinetics, thermal transport, and mass transport. Zhou et al. [71] developed a simple scaling to describe the contributions of transport and reactivity to cool flame extinction. A transport-weighted enthalpy concept was first proposed by Won et al. [72] to separate the effect of chemical kinetics on the hot flame extinction from the thermal and mass transport term. The thermal and transport effects on the cool flame extinction limit might be scaled by the product of fuel concentration, [Fuel], oxygen concentration, [O2], the ratio of fuel to nitrogen density, ρfuel/ρn2, and the heat release of low temperature combustion, ΔHLow,ig. The transport-weighted enthalpy can be written by [Fuel]  [O2]  ΔHLow_ig  ρfuel/ρn2 [71]. The radical index (RI) concept (based on the OH formation rate) was proposed to represent the chemical kinetics contribution to diffusion hot flame extinction limits [72]. However, the measurement of OH radical concentrations in cool flames is very difficult using traditional optical diagnostics (e.g., OH laser-induced fluorescence) due to the very low signal-to-noise ratio. Therefore, the cool flame radical index is obtained by fitting the extinction strain rates onto a reference curve. Fig. 9B shows the cool flame radical indexes of n-heptane, n-octane, n-decane, and n-dodecane respectively, where n-dodecane is the reference fuel with a unity cool flame radical index. With the decreasing of the chain length, the low-temperature reactivity decreases. Therefore, using the measurements of counterflow cool flame extinction limits, one can rank the fuel low

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FIG. 9 (A) Cool flame residence time at extinction as a function of oxygen concentration for large n-alkane diffusion flames at initial oxidizer temperature of 550 and 300 K. (B) Rescaled cool flame extinction strain rate of all tested fuels in terms of RI  [Fuel]  [O2]  ΔHLow_ig  ρfuel/ρn2; Line: linear fit of all experimental measurements. Reprinted by permission of Elsevier Science from M. Zhou, O.R. Yehia, W. Xu, C.B. Reuter, Z. Wang, C. Yan, B. Jiang, Y. Ju, The radical index and the effect of oxygen concentration on non-premixed cool flame extinction of large n-alkanes, Combust. Flame 231 (2021) 111471 by the Combustion Institute.

temperature reactivity quantitatively and conveniently by using the cool flame radical index, which can rapidly accelerate surrogate component formulation and fuel screening. More recently, Wang et al. [43] developed a high pressure counterflow burner to study the cool flame and warm flame at elevated pressure. They investigated the pressure effects on the oxygen concentration dependence. Fig. 10 (left) shows the

2 Dynamics of low temperature flames

FIG. 10 Left: Measured non-premixed DME cool flame residence time at extinction versus oxygen concentration. Right: Cool and warm flame images with DME mole fraction of 0.3 [43].

experimental cool flame residence time at extinction versus oxygen concentration for DME at different pressure, with the corresponding fitting curve. It is seen in Fig. 10 (left) that the oxygen concentration dependences (n) are 1.45, 1.57, and 1.64, for pressures of 1, 3, and 5 atm, respectively. The oxygen addition reactions are enhanced by increasing pressure; thus, the cool flame extinction has stronger oxygen concentration dependence at higher pressure. They also observed the warm flame for DME at elevated pressure. Fig. 10 (right) shows the DME cool flame and warm flame images without/with ozone addition at 1 and 3 atm. The cool flame cannot be observed without ozone addition for strain rate of 100 s1 and fuel mole fraction of 0.3 at 1 atm (case a), while it can exist with ozone addition at the same condition (case b). As pressure increases to 3 atm, the cool flame can exist without ozone addition (case c) and the warm flame can be observed with ozone addition at the same condition (case d). The O3 addition promotes the cool flame and warm flame mainly through the reaction of O3 (+ M) ¼ O2 + O (+ M). The increasing pressure promotes the warm flame mainly through O2 additions and H2O2 (+ M) ¼ 2OH (+ M) reactions.

2.2.3 Spherical cool flames Kim et al. [44] investigated the diffusion cool flame using a spherical porous burner with gaseous fuels in the microgravity environment of the ISS. Spherical cool diffusion flames with gaseous fuel were observed for the first time. Fig. 11 (left) shows a 6.4 mm diameter spherical porous burner, which was located near the center of the pressure vessel. The burner temperature was measured using an embedded type K thermocouple. Tests were terminated whenever the burner temperature reached 723 K to prevent the burner or its support tube from overheating. The flames were ignited by a retractable hot wire ignitor. Fig. 11 (right) shows the hot flame

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FIG. 11 Left: The spherical porous burner. Right: Intensified camera images for (a) the hot flame and (b) the cool flame. The times after ignition, t, are shown. The dashed circles indicate the burner location. False colors were obtained by matching the colors of microgravity hot flames and normal gravity cool flames (b) is an average of images from the times shown and whose intensity was increased by a factor of 50 [44].

(a) and cool flames (b) captured by the intensified camera. The cool flame appeared at 3 s before the hot flame extinguished radiatively. Compared to the cool flame, the hot flame was larger, brighter, and more spherical and it had a thinner reaction zone. The hot flame had a larger quenched region near the burner tube.

2.3 Autoignition assisted cool flame Because of the short low temperature ignition delay time at engine conditions at which the mixture is close to auto-igniting and have a very ignition Damk€ohler numbers (Daig), the combustion in practical engines can be affected by autoignition assisted flame propagation. To understand the dynamics of autoignition assisted cool flame and warm flame, Zhang et al. [73] simulated the propagation speeds of n-heptane/air cool flame and warm flame at elevated temperatures and pressures and at large ignition Damk€ ohler numbers (Daig). They reported that the cool flame speed had a strong non-linear dependence on initial temperature due to the NTC effect. In addition, at a certain temperature range, the cool flame speed can be faster than the hot flame speed. This explains the mechanism of the double flame structure formation shown in Fig. 5. However, in the NTC region, the cool flame speed decreases rapidly. With a further increase of the initial temperature, the cool flame reignition occurs and transits to the hot flame. The study shows that low temperature ignition Damk€ohler number (Daig,L) has strong effects on the propagation speeds of cool flame and warm flame. With the increase of Daig,L, the cool flame and warm flame speeds increase exponentially. This rapid flame speed increases with ignition Damk€ohler number suggests that the autoignition assisted cool flame and warm flame regimes need to be appropriately considered in compression ignition engines, knock, and flame lean-blow off in a flow recirculation zone. By using a three-zone flame structure: autoignition,

3 Low temperature combustion chemistry at high pressure

convection-diffusion, and reaction zones with a one-step global reaction model, the laminar flame speed at a large ignition Damk€ohler number was given as [73], h i  T p ¼ T a = ln 1  Daig eT a =T 0 + Daig eT a =T f sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Tf  T0 SL  SL,Daig ¼0 Tf  Tp

(2)

(3)

where Tp is the temperature after the first-stage autoignition at Daig, Ta and Tf are the reduced activation energy and flame temperature, and SL,Daig¼0 is the laminar flame speed at Daig ¼ 0.

3. Low temperature combustion chemistry at high pressure The fuel oxidation with low temperature chemistry is highly dependent on temperature and pressure. At low temperatures (below 800 K), the major fuel (e.g. alkanes) oxidation pathways are shown in Fig. 3 and listed in Table 1. The fuel oxidation process starts with an H-abstraction of the fuel molecule (RH) by a radical such as OH, O, or HO2 (via reaction R1) and forms a fuel radical (R). The fuel radical (R) then forms an adduct with an O2 molecule to produce RO2 (via reaction R2). The internal isomerization of RO2 will lead to the production of QOOH (via reaction R3a). QOOH will either decompose to form one OH (via reaction R4a) or one HO2 radical (via reaction R4b) or will undergo a second O2 addition to form a peroxy hydroperoxyl alkyl radical (O2QOOH) (via reaction R5). The subsequent decomposition of O2QOOH produces ketohydroperoxide (OQ0 OOH) and an OH radical. Finally, OQ0 OOH decomposes to form a ketoalkyloxy radical (OQ0 O) and another OH radical. Therefore, the low-temperature reaction pathway from Table 1 Key chain initiation, propagation, and branching reactions at low temperature. RH + X ¼ R + XH, X ¼ OH, O, HO2, CH3… R + O2 $ RO2 RO2 $ QOOH RO2 ! alkene + HO2 QOOH ¼ cyclic ether + OH QOOH ¼ alkene + HO2 QOOH ¼ alkene + ketene + OH QOOH + O2 $ O2QOOH O2QOOH ¼ OQ0 OOH + OH OQ0 OOH ¼ OQ0 O + OH O2QOOH + O2 ¼ O2Q0 (OOH)2

(R1) (R2) (R3a) (R3b) (R4a) (R4b) (R4c) (R5) (R6a) (R6b) (R7)

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R ! RO2 ! QOOH ! O2QOOH ! OQ0 O + 2OH via reactions R2, R3a, R5, R6a, and R6b produces multiple radicals and is the low temperature chain-branching pathway governing low temperature combustion. Note that at very low temperatures and high pressures, it is possible that a 3rd (reaction R7) and 4th oxygen molecule can be added to O2QOOH [74,75] to form a large oxygenated complex that can lead to additional chain branching reactions. However, as the temperature becomes higher, the chain-propagating pathway of R ! RO2 ! QOOH ! OH + cyclic ether (R4a) become so fast that the low temperature R ! RO2 ! QOOH ! O2QOOH ! OQ0 O + 2OH chain-branching pathway is suppressed. Moreover, the reverse reactions of R2 and R5 as well as the decomposition of RO2 to olefin and HO2 (R3b) further reduce the formation of RO2. As such, the slowdown of radical production results in the so-called NTC behavior. At intermediate temperatures (between 800 K and 1100 K), fuel oxidation is governed by a chain-branching process involving HO2, as shown in Fig. 3 and listed in Table 2. At these temperatures, HO2 can be directly produced via RO2 and QOOH (reactions R3b and R4b, respectively). A small alkyl radical (R0 ) formed via RO2 or QOOH decomposition can also react with HO2 in R9b to form an active OH radical and an alkoxy radical (R0 O). In addition, the reaction between an aldehyde radical (R0 CO, e.g., CH2CHO) and O2 via R9a also produces an active OH radical and a smaller aldehyde (e.g., CH2O). Furthermore, the reaction between R0 O with O2 via reaction R10b leads to an (excited) aldehyde molecule and HO2. The subsequent CH2O ! HCO ! HO2 ! H2O2 ! 2OH reaction pathway via reactions R11-R15 then converts HO2 into a second OH radical. Therefore, the chain-branching reaction pathway at intermediate temperatures appears to be the production of multiple OH radicals via the smaller radicals (e.g., R0 and R0 CO) Table 2 Schematic of key chain-branching reaction pathways at intermediate temperatures. RO2 ! alkene + HO2 QOOH ! cyclic ether + OH QOOH ! alkene + HO2 R0 CO + O2 ¼ aldehyde + CO + OH R0 + HO2 ¼ R0 O + OH, R0 ¼ C2H5, C3H7, C4H9… Aldehyde + HO2 ¼ H2O2 + R0 CO R0 + O2 ¼ alkene + HO2 R0 O + O2 ¼ aldehyde +HO2 CH2O + X ¼ HCO + XH, X ¼ H, OH, O, HO2… HCO + O2 ¼ HO2 + CO HCO + (M) ¼ H + CO + (M) H + O2 + (M) ¼ HO2 + (M) HO2 + HO2 ¼ H2O2 + O2 H2O2 ¼ OH + OH + (M)

(R3b) (R4a) (R4b) (R9a) (R9b) (R9c) (R10a) (R10b) (R11) (R12a) (R12b) (R13) (R14) (R15)

3 Low temperature combustion chemistry at high pressure

formed from the low temperature sequence and via H2O2 decomposition. It can also be noted that this chain-branching process is relatively slow and is sensitive to heat loss and oxygen concentration. As such, at an intermediate temperature, the HO2 chemistry is the major chain-branching pathway for the second-stage ignition and warm flame formation. At high pressure, HO2 chemistry plays a greater role, which weakens the NTC behavior and shifts it to higher temperature. In summary, there are different sets of chain-branching reaction pathways that exist at low temperature (R ! RO2 ! QOOH ! O2QOOH ! OQ0 O + 2OH), intermediate temperature (R0 + HO2 ! R0 O + OH and R0 CO + O2 ! aldehyde + CO + OH followed by CH2O ! HCO ! HO2 ! H2O2 ! 2OH), and high temperature (H + O2 ¼ OH + O) in combustion chemistry, respectively. Therefore, these three chain-branching pathways determine that there are three different flame regimes, cool flame, warm flame, and hot flame. Although low temperature combustion chemistries have been widely studied [45–47], the low temperature chemical kinetics at an extremely high pressure and supercritical condition have not been well-studied. A supercritical pressure jet-stirred reactor (SP-JSR) [58] recently developed at Princeton provides a new platform for conducting kinetic studies at low temperatures and extremely high pressures with a uniform temperature distribution and a short flow residence time. The novelty of the SP-JSR lies in its eight perpendicular nozzles with 0.2 mm inner diameter on four jet fingers at the center of the sphere, which generate intense turbulence and homogenous mixing. Zhao et al. [58] recently studied the low temperature chemistry of n-butane (n-C4H10) with CO2 diluent between 10 and 100 atm in SP-JSR. Fig. 12A shows the

FIG. 12 (A) Temperature evolution of the fuel mole fraction, n-C4H10 (Φ ¼ 0.1), from 500 to 900 K with and without CO2 additions, at 10 and 100 atm [58]. (B) Temperature evolution of the fuel mole fraction, DME (Φ ¼ 0.175), from 500 to 900 K, at 100 atm. Reprinted by permission of Elsevier Science from C. Yan, H. Zhao, Z. Wang, et al., Low- and intermediatetemperature oxidation of dimethyl ether up to 100 atm in a supercritical pressure jet-stirred reactor, Combust. Flame (2022) 112059 by the Combustion Institute.

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mole fraction of n-C4H10 as a function of temperature with and without 20% CO2 additions at 10 and 100 atm. Experimental data shows a typical low temperature window from 650 to 750 K and a clear NTC behavior at 10 atm without CO2 addition. However, a much weaker NTC behavior is observed at 100 atm, and the intermediate temperature oxidation region is shifted to lower temperatures. It can be also noted that supercritical CO2 has limited effect on the low temperature oxidation of n-C4H10, while slows down the intermediate temperature oxidation. Healy’s model [76] can well predict the onset of the low temperature oxidation of n-C4H10. However, it underpredicts the NTC behavior and the intermediate temperature oxidation, and the discrepancy becomes larger at 100 atm. The kinetic analyses showed that the two important radicals of s-C4H9 and p-C4H9 (R) are formed from H abstraction reactions of n-C4H10 by OH and HO2 radicals and further produces RO2 through the first O2 addition. As pressure increases, the H abstraction reaction by HO2 becomes more important. The reaction of RO2 ¼ QOOH (R3a in Table 1) is the main reaction to form QOOH. The QOOH competing reactions of QOOH + O2 ¼ O2QOOH (R5 in Table 1) and QOOH ¼ QO + OH (R4a in Table 1) control the NTC behavior. However, at pressure up to 100 atm, R5 becomes much more important than R4a due to the intense molecular collision between QOOH and O2 and thermalizing and stabilizing of excited O2QOOH. As a result, R5 dominates the n-C4H10 oxidation at a broader temperature range and the NTC behavior is inhibited at 100 atm. On the other hand, the reaction RO2 ¼ HO2 + C4H8, which is the main reaction channel at intermediate temperature, appears in low temperature region. It indicates that the intermediate temperature chemistry is shifted to lower temperature and overlaps with the NTC region at 100 atm. This is why the NTC effect at 100 atm becomes much weaker and indistinct. An updated Healy’s model [76] with modifying reaction rates of QOOH + O2, CH3CO + O2, and H2O2 (+ M) within uncertainties of calculations or measurements shows better agreement with the experimental data, especially in the NTC and intermediate temperature region. However, the model still slightly underpredicts the n-C4H10 oxidation and cannot well-capture the effects of supercritical CO2 addition. Yan et al. [59] recently studied the low temperature chemistry of DME at 10 and 100 atm in SP-JSR. Fig. 12B shows the mole fraction of DME as a function of temperature at 100 atm. Similar to n-C4H10, the experimental data exhibit a typical window of NTC behavior from 650 to 750 K. The NTC behavior at normal pressure is due to a competition between two channels (R5 in Table 1 and R4a in Table 1), as discussed before. However, at high pressure, they also reported the radical production via H2O2 (+M) ¼ 2OH (+M) and 2HO2 ¼ 2OH + O2 reactions is dramatically increased and shifted to lower temperature. Therefore, with increasing pressure, the HO2 chemistry suppresses the NTC effect via QOOH and O2QOOH decomposition. Moreover, the initiation temperature of low temperature DME oxidation is around 550 K, which is unusual for such a small fuel molecule (e.g., n-alkanes). This can be explained by the presence of an O-atom that weakens the neighboring CdH bond, favoring the H-abstractions compared with similar n-alkanes. The Habstraction reaction from DME by HO2 has a significant impact on the oxidation

4 Summary and future research

at high pressures and high temperatures (above 800 K), while its importance is minor compared to DME + OH at low pressures and low temperatures (below 800 K). This change in importance is because HO2 production at high pressure increases dramatically, and reactions involving HO2 then have a higher impact on the fuel oxidation. One of the major uncertainties in the variation in the model simulations with pressures comes from the DME + HO2 reaction, which could benefit from a high-level ab initio kinetics analysis. A varying role for non-thermal reactions, as discussed in diethyl ether oxidation [77], may also play a key role in interpreting the dependence on pressure. To further investigate the low temperature oxidation chemistry of DME, Fig. 13 shows a sensitivity analysis for DME concentrations at 100 atm. The oxidation onset region (550–600 K) is primarily sensitive to the competition for RO2 radicals between R3a and R3b in Table 1. As the temperature increases into the NTC region, the opposing sensitivities to R5 and R4a in Table 1 become large as these reactions compete for QOOH. With the temperature increasing further beyond the NTC region, thermal dissociation of R becomes increasingly rapid and the reverse reaction RO2 ¼ R + O2 increases in importance; both effects inhibit the low-temperature chainbranching mechanism. Concurrently, the importance of the HO2 radical grows, with the sensitivity to DME + HO2 growing near the peak of the NTC region along with sensitivity to H2O2 ¼ 2OH (H2O2 is mainly formed via HO2 + HO2 ¼ H2O2 + O2). The chain-propagating reaction DME + OH ¼ R + H2O has one of the largest sensitivity coefficients. The significant dip in sensitivity to this reaction across the NTC region occurs partly due to the increased formation of CH2O via QOOH decomposition; the CH2O competes with DME for consumption of OH radicals. With increasing equivalence ratio, the sensitivities to QOOH + O2 ¼ O2QOOH and QOOH ¼ 2CH2O + OH become negligible at lower temperatures. Lower O2 concentration inhibits both the first and second O2 additions. Another subtle change due to equivalence ratio is the importance of R decomposition, R ¼ CH2O + CH3. The peak sensitivity to this reaction shifts to lower temperatures as the equivalence ratio is increased due to less consumption of R via R + O2 ¼ RO2 with decreasing O2 concentration. It can be also noted that the NTC behavior is weaker for lean case than rich case at 100 atm. This is because the lean case has higher O2 concentration, which leads to more HO2 formations. The enhanced HO2 branching channel suppresses the NTC effect via reactions H2O2 (+ M) ¼ 2OH (+ M) and 2HO2 ¼ 2OH + O2 with the increase of temperature.

4. Summary and future research This chapter summarizes the recent progress in the experimental and numerical studies of low temperature flames and chemical kinetics as well as their impacts on low temperature advance engines and alternative fuels design. The experimental observation and numerical modeling showed a clear picture of the dynamics and regimes of different low temperature flames such as cool flame, warm flame and double

311

FIG. 13 DME sensitivity coefficients (top panels) and predicted mole fractions (bottom panels) versus temperature for (A) lean, (B) stoichiometric, and (C) rich conditions at 100 atm. Reprinted by permission of Elsevier Science from C. Yan, H. Zhao, Z. Wang, et al., Low- and intermediate-temperature oxidation of dimethyl ether up to 100 atm in a supercritical pressure jet-stirred reactor, Combust. Flame (2022) 112059 by the Combustion Institute.

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flame and their relationship with hot flame. For near-limit premixed flames, it is shown that a hot flame above its flammability limit can potentially transition into a double flame at near limit condition or a cool flame. A cool flame and warm flame can exist below the burning limit of a hot flame, leading to a monotonic and non-monotonic ignition-extinction curve. In addition, low temperature flame speeds have different pressure dependence from that of hot flames because of its strong pressure and oxygen dependence and the NTC effect. In addition, low temperature ignition and auto-ignition assisted flame propagation can significantly enhance the flame speeds and ignition to detonation transition under engine condition. Droplet combustion and spherical flame experiments in microgravity onboard the ISS provided an ideal platform to observe transition from hot flame to cool flame and warm flame after radiative extinction. The experiments show that both pressure and fuel molecular structures can affect hot flame to cool flame transitions. Moreover, it was shown that the cool flame properties and chemistry can be controlled by using chemical sensitization such as plasma, ozone and NOx addition. Moreover, it was demonstrated that low temperature flames can serve as new platforms not only for understanding low temperature flame dynamics, low temperature chemical kinetics, and kinetic model validation, but also for screening and ranking low temperature fuel reactivities for advanced engine design and fuel development. The cool flame radical index via the cool flame extinction limit measurements provides a sensitive measure the low temperature fuel reactivity and its dependence on oxygen, pressure, additives, and diluents. There are three different temperature dependent chain-branching reaction pathways that govern, respectively, the low temperature, intermediate temperature, and high temperature flames. Although these chain-branching and chain-propagation reaction pathways have been widely studied for different fuels, the low temperature chemistry at high pressure, especially at extreme pressure and for oxygenated fuels, needs to be further explored. The SP-JSR and the high pressure flow reactor operating above 100 atm provide new platforms for investigating low temperature and high pressure combustion chemistry under extreme pressure at advanced engine conditions. It was shown that small molecular fuels such as methane and methanol show strong low temperature oxidation behaviors at 100 atm. Moreover, the NTC behavior is largely suppressed at extreme pressure due to the competition between the NTC effect and the HO2 chemistry. At extreme pressure and low temperature, there are large discrepancies between the experiments and model predictions. Moreover, at supercritical pressure, the real gas effects, thermodynamic properties, non-equilibrium kinetics, and termolecular reactions also need further considerations for advanced engine and fuel development. Low temperature combustion is a new endless frontier of combustion research.

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CHAPTER

Supercritical CO2 fluid combustion

11

Ramees K. Rahmana, K.R.V. Manikantachari (Raghu)a,b, and Subith S. Vasua a

Center for Advanced Turbomachinery and Energy Research (CATER), University of Central Florida, Orlando, FL, United States, bPower Systems Mfg., LLC, Jupiter, FL, United States

1. Introduction Energy consumption across the globe is growing swiftly. Global energy needs are forecasted to increase by over 25% by 2040. Along with energy consumption, greenhouse gas emissions are also expected to increase at alarming rates. Burning fossil fuels for electricity is the second largest (Fig. 1) human contributor to greenhouse gases in the United States [1]. Sadly, the current annual CO2 levels are one of the highest in history [2]. New technologies and efficient strategies are required to reduce greenhouse gas emissions and simultaneously cater to the increasing energy demands. Government agencies and industries worldwide are exploring various technologies that could address increasing energy demands and lower greenhouse gas emissions. Conventionally, power generation uses fossil fuels and operates according to the Rankine cycle. In this regard, the supercritical carbon dioxide power cycles (sCO2) are gaining attention from policymakers in the government, industries, and researchers in academic institutions. The remarkable theoretical efficiency, smaller size, and ecofriendliness are a few prime reasons for this. The efficiency that can be acquired by sCO2 cycles is higher than conventional Rankine cycles primarily due to the properties of CO2 beyond the critical point [3,4]. In a supercritical state, CO2 has a higher density and specific heat while viscosity is lower, as shown in Figs. 2–4 [5]. The high density allows for compact machinery due to reduced volumetric air flow rate and reduces required compressor power, while low viscosity reduces transmission losses. The high specific heat prevents significant changes in temperature due to energy release, which helps reduce the number of intercoolers and reheating stages [3].

Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00014-X Copyright # 2023 Elsevier Inc. All rights reserved.

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FIG. 1 CO2 emission by various sources in the United States in 2017 [1].

FIG. 2 Variation of CO2 density near the critical point [5].

1.1 Direct-fired supercritical CO2 power cycles Direct-fired supercritical CO2 power cycle operates by Allam-Fetvedt cycle also known as Allam cycle. Fig. 5 shows the layout of the Allam cycle [6]. Since the Allam cycle uses nearly pure oxygen, the first unit operation is the separation of oxygen from the air in an Air Separation Unit (ASU). The pure oxygen supplied by ASU is mixed with natural gas/syn gas and diluted with a sCO2 bypass stream. The mixture then undergoes combustion inside the combustion chamber and is expanded through a turbine for power generation. The exit stream from the turbine is fed into

1 Introduction

10

CO2

8 8.0 MPa

6 Ratio of Specific Heats

12 MPa

4 4.0 MPa

16 MPa 20 MPa

2

0 200

Critical temperature

300

400

500

600

Temperature [K]

FIG. 3 Variation of the ratio of specific heats of CO2 near critical point [5].

FIG. 4 Variation of the viscosity of CO2 near critical point [5].

a heat exchanger and condensed. A liquid-gas separator downstream separates water (liquid) from the remaining exit stream, mainly CO2 (gas). A part of the exit stream is recirculated to dilute the air stream. At the same time, the remaining high-pressure CO2 can be used for commercial purposes or carbon capture, utilization, and storage (CCUS).

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FIG. 5 The layout of the Allam cycle [6].

It should be noted that the operation of a direct-fired sCO2 cycle poses several challenges, including, but not limited to, the requirement of pure oxygen, materials, and equipment required to sustain operation at extreme pressures and high temperatures, combustion at high pressures, etc. Several studies have analyzed the feasibility of oxygen separation for demanding oxy-fuel combustion systems [7–9]. The typical combustion conditions inside the sCO2 combustor are shown in Table 1 and are unconventional and challenging. The operating pressures are close to 300 bar (for comparison, heavy-duty engines operate at pressures
100 bar), and operating temperatures are close to
1000 °C. Designing any equipment to withstand these pressures and temperature is challenging and expensive. However, the remarkably high efficiency, close to the efficiency of combined power cycles (
60%), and the reduced environmental impact makes sCO2 combustion worth pursuing. Another critical challenge in developing sCO2 combustion is the combustion chemistry under these conditions. Any experimentation on the combustion Table 1 Operating conditions of the direct-fired sCO2 combustor. Parameter

Operating conditions

Fuel Oxidizer Operating temperature Operating pressure Percentage of sCO2 dilution

Natural gas/syngas Oxygen 760–1150 °C 300 bar > 95% by mass

2 Modeling consideration

phenomenon at
300 bar pressure and 95% CO2 dilution is expensive, timeconsuming, and even dangerous. Hence, accurate modeling of the sCO2 combustion phenomenon would significantly help developers in all phases of the design and development process. This chapter will discuss the design considerations in developing sCO2 combustors mainly from a combustion chemistry modeling perspective.

2. Modeling consideration

2.1 The equation of state (EOS) Combustion is a complex physical phenomenon that involves fluid flow, chemical kinetics, and heat transfer. The interactions between these three phenomena are of particular importance. Due to the complexity and limitation of the computational power, most of the theories and models in combustion are built based on certain underlying assumptions. Conventionally, combustion modeling relies on the assumption that gas-phase combustion is ideal (the “ideal gas” assumption, abbreviated as IGA hereafter). IGA assumes that the mean free path between the molecules is large; hence, there are no intermolecular forces. However, under supercritical conditions, the molecules are closer than usual. Hence these assumptions are not valid. The molecules being closer exerts attractive/repulsive forces based on their electron cloud distribution. This may result in a significant deviation from IGA in their kinetic, thermal, and transport properties. For modeling purposes, it is accepted to simplify problems as long as the simplification does not compromise the characteristics of the problem studied. Experiments must be conducted to validate the simplification assumption when this is not known. For example, it is well known that no gas is ideal, but IGA helps simplify the problem and get reliable results for low-pressure applications using many gases. The density of the mixture for the sCO2 system deviates significantly from IGA prediction due to high pressure and the gas’s supercritical state. In a reacting flow simulation, as is the case with combustion, a change in density affects the mass flow rate and hence affects the predictions of heat release rates, reaction rates, etc. Using IGA may underestimate these critical properties; therefore, a reliable equation of state (EOS) needs to be used to estimate the density of the mixture at supercritical conditions. EOS is one of the most important models for simulating a combustion system’s thermal, transport, and kinetic properties. Hence, it is imperative to choose an appropriate EOS. At the supercritical operating pressures, the mean free path between the molecules reaches a distance where the intermolecular forces become prominent [10]. Hence, a new constant, “Z” appears in the thermodynamic state equation as shown in Eq. (1). P ¼ ρZRmix T

(1)

323

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CHAPTER 11 Supercritical CO2 fluid combustion

Here, P is the pressure (Pa), ρ is the density of the mixture (kg/m3), Rmix is the gas constant of that mixture (kJ/kg K), T is the temperature (K), and Z is the compression (or compressibility) factor. The value of Z is unity for ideal gases and either higher or less than unity for real gases. A Z value less than unity represents the effect of attractive forces, and higher than unity represents the effect of repulsive forces between the molecules. All the real gas properties can be written as a function of Z [11]. Hence, all the EOS models determine its value. Here, it is important to note that the variation of compressibility factor Z can contribute to the pressure change in a combustor. Generally, there is a pressure loss across any gas turbine combustion chamber. The energy associated with this pressure loss will be wasted without producing useful work. In the sCO2 combustor, we can anticipate additional pressure loss just because of the strange Z variation in the reacting fluid. The works of Ref. [12] report the loss in the pressure due to significant variation of Z with respect to the reaction progress. The direct numerical simulation (DNS) work of Ref. [13] also confirms such crucial variation. The addition of more sCO2 to post combustion products could help in regaining the lost pressure loss due to variation of Z [12,13]. Thus, accurate modeling of EOS is vital. There are several EOS available in the literature, and a brief discussion of EOS for sCO2 application is provided in this chapter. For more details, interested readers are referred to the works in literature [14–16]. Boyle was the first to demonstrate the P-T-relation for an ideal gas, but Van der Waals’ extensive work in the late eighteenth century [14] defined the first approximation of EOS for real gases. The EOS can be broadly classified into three types: virial-type, molecular-based, and van der Wall type [15,16]. The formulations of the virial and molecular-based EOS are highly accurate and complex. As a result, using such EOS types in CFD combustion applications is challenging because the EOS must consider all of the species in the mixture and solve for each cell in the computational domain at each time step. The NIST-REFPROP [17] is one such program where complex EOS of such type are used to calculate the thermal properties of the fluids and fluid mixtures. The computational expensiveness of using the NIST for CFD is reported in Ref. [18]. However, it must be noted that the NIST is considered to be the most accurate EOS available. Therefore, it is usual in the literature to see the usage of NIST as a reference for EOS validations where experimental data is unavailable. The third category of EOS, i.e., the van der Waals type of EOS are empirical in nature and they are the main type used in combustion simulations. Following proposals have largely modified the basic van der Waal correlation for greater accuracy. Because of their simple formulation and low computational cost, improved van der Waals class equations such as Redlich-Kwong (RK) [19], SoaveRedlich-Kwong (SRK) [20], and Peng-Robinson EOS (PRS) [21] are the most popular EOS for supercritical CFD simulations of Rocket combustion systems [22,23]. Patel’s [24] work proposed a common cubic equation form for RK, SRK, and PRS EOS, as shown in Eq. (2).

2 Modeling consideration

P¼

RT aðT Þ  ðV  bÞ V ðV + bÞ + cðV  bÞ

(2)

R is the universal gas constant, a is a temperature function, and b and c are temperature corrections. The term a represents the temperature correction factor, and the terms b and c represent the volume correction factors in the equation. Eq. (2) reduces to the Peng-Robinson equation when c 5 b, and to the Redlich-Kwong or Soave-Redlich-Kwong equation when c ¼0. In addition, Eq. (2) can be represented in a cubic form of Z, as shown in Eq. (3). The important equations listed below are taken from the CHEMKIN-RG manual [11].

 Z 3  1 + B∗  uB∗ Z2 + A∗ + wB∗2  uB∗  uB∗2 Z  A∗ B∗  wB∗2  wB∗3 ¼ 0

(3)

Because of its cubic order, the Z in Eq. (3) can be solved analytically and has three solutions. Only when the mixture of interest is subcritical in pressure and temperature does this equation have three real roots. As a result, the correct real Z must be identified at subcritical conditions using the phase equilibrium procedure, whereas, at supercritical conditions, the largest real root can be used to calculate the compressibility factor. The term, A∗. in Eq. (3) is a non-dimensional attraction term equal to Ra2mTP2 , B∗ is a mP non-dimensional repulsive term equal to bRT : The mixing rules in Eqs. (4), (5) are used to calculate am and bm. am ¼

KK XKK X i¼1


1=2
 Xi Xj ai aj  1  kij

(4)

j¼1

and bm ¼

XKK

Xb i¼1 i i

(5)

The subscript i refers to a species index, Xi. represents mole fractions, ai and bi are pure species properties, and, kij are empirically determined binary-interaction coefficients. In practice, this interaction coefficient is a measure of deviations from ideal solution behavior for interactions between the ith and jth. components [25]. Thus, it is 1.0 when i equals j, i.e., for pure fluid interaction, and it is close to 1.0 for component pairs that form nearly ideal solutions. When the component pair produces highly non-ideal solutions, its value deviates significantly from 1.0. When i or j is a light hydrocarbon or a non-hydrocarbon, precise values of kij are required (for example, methane with hydrocarbons heavier than n-butane, CO2hydrocarbon, H2S-hydrocarbon, and N2-hydrocarbon mixtures). More information about kij can be found in Refs. [19,20,26,27]. Table 2 also includes the coefficients u, w, a and b for Eq. (3). The coefficients chosen change Eq. (3) to the EOS of interest. The CHEMKIN-RG has the capabilities to model the EOS by van der Waals (vdW), Redlich-Kwong (RK), Soave-Redlich-Kwong (SRK), Peng-Robinson (PRS), Becker-Kistiakowsky-Wilson (BKW) and Nobel-Abel (NA) EOS. In the

325

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CHAPTER 11 Supercritical CO2 fluid combustion

Table 2 The coefficients for cubic eq. of state. EOS

u

w

b

a

vdW

0

0

RK

1

0

RT c 8Pc 0:08664RT c 8Pc

SRK

1

0

0:08664RT c 8Pc

PRS

2

1

0:07780RT c 8Pc

27 R2 T 2c 64 Pc 0:42748 R2 T 2:5 c 64 Pc T 0:5 0:42748 R2 T 2:5 c l 64 Pc T 0:5 0:42748 R2 T 2:5 c l 64 Pc T 0:5

current work, only the RK, SRK, and PRS EOS are used for comparison because these are the most popular EOS used in rocket combustion simulations. Here, Tc—Critical Temperature of the species Pc—Critical pressure of the species ω—acentric factor of the species 2 l ¼ [1 + fω(1  T0.5 r )] For SRK EOS, fω ¼ 0.48 + 1.574ω  0.176ω2 For PRS EOS, fω ¼ 0.37464 + 1.54226ω  0.26992ω2 It should be noted that critical properties such as Tc , Pc, and ω are not available in the literature for all species and radicals in a combustion phenomenon. As a result, it is common practice to apply the critical properties of the largest diluent in the simulation to species or radicals whose critical properties are unknown. Because these cubic-EOS are empirical, applying them to a specific application necessitates data validation. Some studies, for example, recommend SRK EOS for CH4/LOx and kerosene/LOx mixtures [21,22]. Poschner and Pfitzner [28] advocate PRS for H2/O2 mixtures. Nonetheless, the SRK and PRS are the most commonly used EOS. Compared to NIST, PRS EOS has a higher accuracy for sCO2 than SRK and RK EOS, which increases as the temperature rises. Surprisingly, the accuracy of the SRK EOS increases with temperature, and beyond 1200 K, the SRK and PRS cannot be distinguished [12]. Small-scale turbulence (turbulent dissipation rates, N) has been found to alter chemical pathways [23]. The turbulent dissipation rate characterizes the degree of molecular mixing (small-scale turbulence) in a combustion process, where pockets of high strain change in the local chemical processes, influencing chemical kinetic pathways [24]. As a result, the amounts of mixture ingredients differ between turbulent regimes with differing dissipation rates [29]. As a result, this EOS validation is performed between two turbulent dissipation levels, such as N ¼ 10,000 and N ¼ 1. Most EOS validation in previous research is only available for pure species.

2 Modeling consideration

However, in the current study, EOS validation is performed for combustion mixtures by varying reaction progress variable (RPV). The reference inlet mixtures are chosen as shown in Table 3, and Fig. 6 shows a schematic of the mixture compositions considered for EOS comparison. To compare EOSs, mass fractions at various RPVs were determined using the PCMC code as mentioned above, and CHEMKIN-RG was used for thermal state prediction. The RPV is calculated by subtracting the quantity of enthalpy released from the total accessible enthalpy of the mixture. When RPV equals zero, the mixture is still unburned; when RPV equals one, the mixture has released its whole enthalpy content, or the combustion is complete. The Premixed Conditional Moment Closure (PCMC) [23] calculates the equilibrium solution of this inlet condition first. It then solves the PCMC equation between these inlet and equilibrium solutions for different turbulent dissipation values (N). As a result, the proportion of mixture ingredients varies between RPV ¼0 and 1. Using a constant enthalpy and constant pressure process, the PCMC can determine the mass fraction of all the species involved in the chemical mechanism, i.e., Aramco 2.0. However, NIST can only calculate the parameters of a mixture including seven species (CO2, CH4, O2, H2, H2O, CO, and C2H6). Despite the limited number of species, the NIST can still be utilized Table 3 Operating conditions considered for investigating the behavior of Z. Operating condition OP1 OP2 OP3 OP4

What it explains? Reference mixture When the inlet [CO2] increases When the inlet [CH4 + O2] increases When the inlet temperature decreases

Inlet unburnt mixture Inlet moles nCH4=1 nO2=2 nCO2=24 T=1000 K P=300 bar

Initial molar mixture (CH4/O2/CO2)

Initial temperature (K)/pressure (bar)

1/2/24 1/2/40

1000/300 1000/300

2/4/24

1000/300

1/2/24

800/300

At mid of the combustion

CH4+O2+CO+C2H6 +CO2 + H2O+H2

After complete combustion

CO2 + H2O + Other equilibrium products; T=1500 K P=300 bar

FIG. 6 Schematic diagram to illustrate the mixture conditions considered for comparing the EOS.

327

CHAPTER 11 Supercritical CO2 fluid combustion

for sCO2 combustion EOS validation because the sum of all these mole fractions is greater than 99.99% at any given RPV. The operating condition one (OP1), as shown in Table 3, is used for the EOS comparison. This operating condition considers the approximate boundary conditions for sCO2 combustors, namely the inlet temperature of 1000 K, the exit temperature of 1500 K, and the inlet CH4-O2 ratio in stoichiometric proportions. The difference in mass fractions of the PCMC solution by SRK and PRS is reported to be minimal (less than 0.001%) for the species such as H2O, CO2, and O2. However, for CH4 this difference is up to 2.1% and the temperatures differ by 0.12%. As a result, the average mass fractions and temperatures of both SRK and PRS solutions were used to get the relevant thermal characteristics from the NIST. The RK EOS is not included in this comparison owing to its greater variance from NIST. Fig. 7 compares the thermal state predictions of PRS and SRK EOS with NIST at 300 atm pressure and two different turbulent dissipation rates. A density difference of 2.5% is seen due to species diversity between the unburned and entirely burnt mixtures at these turbulent dissipation levels. The mixture density is shown by the primary vertical axis, while the secondary vertical axis represents the difference between EOS and NIST. The results demonstrate that the SRK EOS has greater density prediction accuracy at both turbulent dissipation levels. When N ¼ 1, the average deviation of SRK EOS is 0.71%, whereas PRS has 1.78%. When N ¼ 10,000, the SRK EOS has 0.70%, and PRS has 1.71%. These small SRK EOS deviations from NIST demonstrate that SRK EOS is one of the most accurate EOS employed for sCO2 combustors. Also, the calculation time for these EOS is almost the same because they are derived from the same cubic equation of state.

N=10000

N=1

150 2.0

1.5

120 1.0

110 100

% deviation from NIST

130

Mixture Density [kg/m3]

2.0 140

140 130

1.5

120 1.0

110

% deviation from NIST

150

2.5

160

2.5

160

Mixture Density [kg/m3]

328

100 0.5

0.5 90

90 0.0

80 0.0

0.2

0.6

0.4

0.8

1.0

0.0

80 0.0

0.2

0.4

IG NIST

0.8

1.0

RPV

RPV PRS SRK

0.6

% differ., PRS % differ., SRK

PRS

IG

% differ., PRS

SRK

NIST

% differ., SRK

FIG. 7 Comparison of PRS and SRK EOS with NIST for the turbulent dissipation rates N ¼ 1 and N ¼ 10,000.

2 Modeling consideration

2.2 The compressibility factor (Z) When a flow is incompressible, the thermodynamics can be separated from the fluid kinematics (flow movement) and fluid dynamics (flow forces) [30]. This is a simplified assumption for many non-reacting flows where the system density is nearly constant, and the incompressible assumption makes the flow much easier to analyze. Pressure gradients, temperature gradients, and Mach number fluctuations, on the other hand, can make the flow compressible. However, it also arises in supercritical flows due to molecule attraction and repulsive forces, which Z represents. As a result, it is critical to comprehend Z’s behavior in sCO2 combustion. The density variation in the working fluids transfers energy from the fluid to the surroundings in compressible flows. In other words, mechanical energy converts into thermal energy (increases the temperature and hence changes in density), or thermal energy in the system converts into mechanical energy (changes in velocity and momentum). Fig. 8 depicts the fluctuation of the compressibility factor as a function of the operating parameters stated in Table 3. The operating conditions here indicate multiple sCO2 combustor operation options. OP1 is the reference case considered in the current study, which addresses the intake and outlet boundary conditions for a sCO2 combustor, as discussed in earlier sections. This literature’s measurement of fundamental thermal characteristics is based on the case OP1. The OP2 depicts what could happen to the Z if the CO2 mole fraction in the reference mixture rises, the OP3 depicts what might happen if the CH4 and O2 mole fractions in the reference mixture

1.10

Compression Factor ‘Z’

1.09

1.08

1.07 OP1 OP2 OP3 OP4

1.06

1.05

1.04 0.0

0.2

0.4

0.6

0.8

1.0

RPV

FIG. 8 Variation of Z with respect to RPV for various SCO2 operating conditions.

329

330

CHAPTER 11 Supercritical CO2 fluid combustion

rise, and the OP4 depicts what might happen if the inlet temperature in the reference combination falls. In addition, Fig. 8 resolves the issue posed in the preceding section: whether sCO2 operating conditions are in a zone where molecules repel or attract one other. The solution is that the sCO2 combustor operates in a zone where repulsive interactions exist between the molecules. In Fig. 8, the steady reduction of Z with regard to the progress variable reveals an essential design issue for sCO2 combustor designers. Because, according to Eq. (1), Z is proportional to pressure, the static pressure may decrease as the reaction advances (the temperature of the mixture rises). It’s possible that the turbine’s efficiency will suffer as a result. The loss of static pressure in a typical gas turbine combustor can be caused by flow barriers or turbulent mixing, but with sCO2 combustors, the designers must account for the depreciation of Z in the combustor owing to the supercritical nature of the flow. It’s also worth noting that, above the critical point, the Z value increases with temperature up to a certain pressure and reverses after a certain supercritical pressure. The working parameters of the sCO2 combustor are in a zone where the Z decreases with temperature. Fig. 8 also shows that the slope of Z for OP3 is greater, indicating that raising the inflow of CH4 and O2 will increase the static pressure loss, owing to the increase in temperature (the Z loss is 5% in this case). OP2 and OP4 both have a minimal slope, indicating that the static pressure loss may be reduced by increasing the CO2 level in the initial mixture or lowering the input temperature. Because CO2 absorbs the temperature emitted due to its high specific heat, the inlet temperature drops, resulting in a lower end temperature. After burning, dilution of the combustion mixture with more CO2 would aid in restoring the Z and hence the static pressure. The rate of change of momentum exchange per unit area of the combustor walls is the pressure in ideal gases. The repulsive interactions between molecules are added to the total momentum and hence pressure in supercritical circumstances. As a result, the pressure correction equation is changed for the Pressure Implicit Split Operation method (PISO), and Park and Kim [31] provide a suitable solution sequence. In the PISO algorithm, the Z factor is taken into account from the real-gas EOS rather than the ideal gas EOS.

2.3 Specific heat capacities The resistance of a system to alter temperature when heat is applied is measured by its specific heat. Because CO2 has a higher heat capacity than other species in a combustion mixture, it carries a significant amount of enthalpy with it rather than boosting the temperature in a sCO2 combustor. The Z factor, on the other hand, affects the specific temperatures in supercritical combustion. In this section, an attempt is made to assess its impact on sCO2 combustors. Fig. 9 depicts the fluctuation of cp, cv, and γ (ratio of specific heats) for real and ideal gas combustion mixtures. Because the Z value is always more than unity, specific heat capacities determined for sCO2 combustion mixtures are always bigger than those derived using the ideal gas assumption. The equation is the general formula for specific heat.

2 Modeling consideration

1.21

1.40 1.35 1.30

1.19

1.25 1.20

γ (Cp/Cv)

Specific Heats [kJ/kg-K]

1.20

1.18

1.15 1.17 1.10 1.05 0.0

1.16 0.2

0.4

0.6

0.8

1.0

RPV Cp - SRK Cp - IG

Cv - SRK Cv - IG

γ - SRK γ - IG

FIG. 9 Specific heats for SCO2 combustor.

 c¼

)c¼

de dT

 p or v


E  d m dT p or v

0  1 d ρEi V )c¼@ Z A dT

(6) p or v

According to Eq. (6), the specific heats in the sCO2 combustion system are always larger than the ideal gas case for the same energy content (E) of the system. It should be noted that, as previously indicated, there exist some operating situations beyond the critical point where the Z is less than unity, and the specific heats are lower than the ideal gas assumption. In other words, because of repulsive interactions between the molecules, the specific energy of a sCO2 combustion mixture is larger. When these repulsive forces are considered, they raise all of the particular qualities like entropy, Gibbs energy, and so on. The enthalpy-entropy relationship for ideal and actual gas assumptions is shown in Fig. 10. The enthalpy and entropy are normalized in this case with regard to their

331

CHAPTER 11 Supercritical CO2 fluid combustion

2.0 RG-SRK IG

1.8

1.6 h/ho

332

1.4

1.2

1.0 1.00

1.02

1.04

1.06

1.08

1.10

1.12

s/so

FIG. 10 Enthalpy-entropy diagram for SCO2 combustor.

starting values at RPV ¼ 0. As combustion progresses, these two curves diverge. It states that due to the impact of Z, there is a larger irreversibility connected with the combustion process, and that this irreversibility rises with higher temperatures. At the end of the combustion, the enthalpy released is roughly 1.6% more and the entropy increased by 0.03% higher than in the ideal situation. The mixture’s cp begins at 1.331 and rises to 1.381 kJ/kgK by the conclusion of combustion, whereas the cv begins at 1.111 and rises to 1.187 kJ/kgK. It should be emphasized, however, that the cp and cv values are functions of Z, and they vary as the operating circumstances alter Z. In addition, the value γ of is around 1.2 for the inflow mixture and 1.164 for totally burned products. Another intriguing pattern noted in Fig. 7 is that the cp and cv of ideal and real gases converge as the reaction advances due to the decrease in repulsive forces as temperature rises.

2.4 Viscosity modeling Shear stresses may be substantial in a simulation with the fluid flow at high pressure. In such instances, the viscosity must be calculated with great precision. Even though viscosity varies dramatically while approaching the critical point, viscosity and temperature are linearly related in the operational range of the sCO2-combustor. As a result, modeling viscosity is not as difficult as other factors. There are a few different ways to calculate viscosity. The individual species’ viscosity under the appropriate circumstances may be used to estimate viscosity using the mixing rule [32].

2 Modeling consideration

1000 K 1250 K 1500 K

10 % deviation lines

Mixing Rule

Chung ct al. ( Kij=1) Chung ct al. Lucas ct al. Wilkes Mixing Rule Weighted average

0.00

0.01

0.02

0.03

0.04

0.05

0.06

Viscosity (cP)

FIG. 11 Viscosity of sCO2 combustion mixture using various models [12].

Individual species viscosities can be estimated using methods such as Lucas’s [33] or Chung’s [34]. The Wilkes mixing technique, a subset of Wassiljewa-Mason-Saxena (WMS) [32] method, is another way. For supercritical applications, the Chung and Lucas techniques are two prominent fluid mixture viscosity approaches [35]. According to Ref. [12], the calculated viscosities of sCO2 combustion mixtures are shown in Fig. 11. The differences between the models are minor, and computing costs determine model selection. According to Manikantachari et al. [12], the Lucas technique provides good predictions at a cheap computational cost, making it one of the preferred methods in sCO2 combustion modeling.

2.5 Thermal conductivity modeling The ease with which a species distributes heat across it is determined by its thermal conductivity. In general, the increase in density enhances thermal conductivity at high pressures. Contrary to common belief, thermal conductivity rises with the temperature at low pressures. The thermal conductivity declines with temperatures above critical pressure up to particular pressure limits [35]. Beyond this pressure barrier, temperature increases cause a rise in thermal conductivity. Thermal conductivity is calculated using a variety of models. This comprises the Chung model, Stiel and Thodos approach [35,36], and Amooey et al. [37] model. The empirical Amooey et al. [12] model only applies to sCO2 at temperatures up to 900 K. Fig. 12 compares the calculated thermal conductivity of each species with NIST data for each individual species. Amooey et al. [37] model predictions for CO2 at 300 bar beyond 900 K

333

334

CHAPTER 11 Supercritical CO2 fluid combustion

FIG. 12 Thermal conductivity of various species at 300 bar predicted by different methods compared with NIST values.

show significant deviance. For CO2, CH4, and O2, both the Chung and Stiel and Thodos methods give reasonable predictions. While the prediction by the Chung method for CO is closer to NIST values, the prediction by the Stiel and Thodos method is closer to NIST values for H2O.

3. Experimental validations

3.1 Density of supercritical mixtures Since the density determined by EOS is purely based on empirical relations, experiments are necessary to validate the parameters obtained from these. Under various pressure and temperature conditions, the density of various mixtures, including CO2, O2, CH4, and H2O, was experimentally measured by Park et al. [38]. A brief description of their experimental methodology is provided here. Table 4 displays the target compositions of three chosen mixtures. These requirements were taken from the model combustor system that was put forth in an earlier study [12]. Table 4 Target mixture compositions in mole fraction ratios [38]. Reaction progress

O2

H2O

CO2

CH4

RPV ¼ 0, inlet RPV ¼ 0.5, mid-combustion RPV ¼ 1, exit

2 2 0

0 3.29 1

24 56.8 12.5

1 0.55 0

3 Experimental validations

FIG. 13 Experimental setup for sCO2 mixture property measurements. Reproduced from S. Park, J. Urso, K.R.V. Manikantachari, A. Hosangadi, A. Zambon, S.S. Vasu, Measurements of density and sound speed in mixtures relevant to supercritical CO2 cycles, J. Energy Resour. Technol. 142 (2020).

Density measurements were performed using a portable, temperature-controlled high-pressure cell. The experimental setup’s schematic is shown in Fig. 13. The cell has a maximum pressure tolerance of 4000 psi (276 bar). The manifold connection can be removed after filling mixtures for precise weight measurement. The weight of the gas mixtures in the test cell was determined using a precision weight scale. A high-pressure gauge and type-T thermocouple probes fastened to the test cell’s outer wall were used to measure pressure and temperature. The cell’s internal volume was roughly 80 mL. After each modification to the test cell, the volume was measured by adding liquid water or pure CO2 to the cell. In the previous numerical simulation work, mixture compositions were chosen to be reasonably close to frozen mixtures at the inlet, mid-combustion, and exhaust conditions of a model sCO2 combustor. The experiments’ temperature and pressure range from 310 to 450 K and 0 to 150 bar, respectively. The density of pure CO2 was measured to demonstrate the measurement system’s viability. The test cell was initially pressurized with CO2 to a maximum of 150 bar. After the mixture in the test cell reached thermal equilibrium, measurements were made. The cell pressure was reduced for the subsequent pressure condition, and weight measurement was carried out once more. Pure CO2 density measurements are shown in Fig. 14 at four different temperatures. Isothermal density curves from the NIST REFPROP database are displayed as solid lines. High-temperature mixtures’ densities behaved like ideal gases, whereas low-temperature mixtures strongly exhibit compressibility’s non-unity effect. CO2 is clearly more compressed (showing a reduced dp/dρ) in the low-pressure cases when the pressure is close to the critical condition. At five different temperatures, the isothermal density of the inlet ternary mixture (CH4:O2:CO2 ¼ 1:2:24) was determined. The inlet mixtures’ densities are shown in

335

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CHAPTER 11 Supercritical CO2 fluid combustion

FIG. 14 The measured density of pure CO2. Markers: measurements and solid line: REFPROP data. Reproduced from S. Park, J. Urso, K.R.V. Manikantachari, A. Hosangadi, A. Zambon, S.S. Vasu, Measurements of density and sound speed in mixtures relevant to supercritical CO2 cycles, J. Energy Resour. Technol. 142 (2020).

FIG. 15 The measured density of the inlet mixture in comparison with REFPROP (RPV ¼ 0). Reproduced from S. Park, J. Urso, K.R.V. Manikantachari, A. Hosangadi, A. Zambon, S.S. Vasu, Measurements of density and sound speed in mixtures relevant to supercritical CO2 cycles, J. Energy Resour. Technol. 142 (2020).

Fig. 15. Near CO2’s critical point, the gas is most compressible. The disparity in density between measurement and REFPROP was less than 10%. At pressures under 100 bar, measurements and REFPROP agree well within the estimated measurement uncertainty. At high pressures, a greater departure from REFPROP was observed. The highest difference found, for instance, was 10.3% between 137 bar measurements at 450 K. Regarding the non-uniformity of the temperature distribution across the test cell, a temperature difference of 2 K is estimated to be the maximum. The highest temperature case at 450 K shows a larger difference when compared to low-temperature cases (310–390 K). Due to greater heat loss, the test cell’s non-

3 Experimental validations

uniformity of temperature may be greater than predicted, but it is difficult to compensate for such effects. Given that temperature is the main source of uncertainty, it is necessary to ensure a more consistent temperature in order to get around the current experimental setup’s limitations in future studies. As a simplified exit condition frozen mixture, a binary mixture of CO2 and H2O was used. Although adding water was the most difficult step in preparing the mixture, the actual amount of water added to the cell was precisely measured by observing the water’s vapor pressure with the pressure gauge. CO2 was filled to the manifold as buffer gas during the water vapor pressure measurement to minimize pressure fluctuation due to water condensation at the manifold. Density measurements for the binary mixtures are shown in Fig. 16 and Table 5. H2O compositions for the Table 5 Measured density of exit mixtures [38]. P (bar)

Measured

T ¼ 420 K

Density (kg/m )

147.1 132.1 100.6 69.3

247.7 217 155.9 102.1

T ¼ 450 K

Density (kg/m3)

146.2 131.8 101.1 69.4

208 187.6 135.9 89.8

REFPROP

Difference

231.7 203.8 148 97

6.89% 6.47% 5.37% 5.30%

199.7 178.6 132.3 87.1

4.12% 5.04% 2.74% 3.07%

3

FIG. 16 The measured density of the exit mixture in comparison with REFPROP (RPV ¼ 1). Reproduced from S. Park, J. Urso, K.R.V. Manikantachari, A. Hosangadi, A. Zambon, S.S. Vasu, Measurements of density and sound speed in mixtures relevant to supercritical CO2 cycles, J. Energy Resour. Technol. 142 (2020).

337

338

CHAPTER 11 Supercritical CO2 fluid combustion

FIG. 17 The measured density of the mid-combustion mixture with H2O, CH4, O2, and CO2 (RPV ¼ 0.5). Reproduced from S. Park, J. Urso, K.R.V. Manikantachari, A. Hosangadi, A. Zambon, S.S. Vasu, Measurements of density and sound speed in mixtures relevant to supercritical CO2 cycles, J. Energy Resour. Technol. 142 (2020).

420 K data were 0.70% and for the 450 K data were 1.47%. Fig. 10 compares the midcombustion mixture’s measured density at 450 K to REFPROP. Temperatures significantly higher than 373 K were needed because the final mixture contained water vapor. The upper range was restricted to 450 K due to the piezoelectric sensor’s limitations. For consistency with the inlet mixture conditions, the mid-combustion and exit mixture test conditions of 420 and 450 K were chosen. Measurement and REFPROP exhibit good agreement, as shown in Fig. 16. The measurement and REFPROP data discrepancy falls within the estimated measurement uncertainty range. With the midcombustion mixture depicted in Fig. 17, a difference of less than 5.5% was also noted.

3.2 Speed of sound in supercritical mixtures A pressure transducer was used to track the resonant frequencies of the pressure chamber containing the pre-combustion mixture to measure the speed of sound. The method is based on earlier research using an ultrasonic cell and acoustic resonators to measure time of flight [39–41]. Due to modifications required for the current system, frequency shift tracking was employed rather than direct time of flight measurement. Fig. 18 depicts the sound generation, pressure data acquisition, and signal processing systems. A sine wave signal was produced using a function generator and an audio power amplifier to drive a speaker. A high-power tweeter with a 4-Ω input impedance was used to excite the pressurized cylindrical test cell

3 Experimental validations

FIG. 18 Speed of the sound measurement process [38].

externally. A Kistler pressure transducer (603B) was installed on the pressurized cell to receive resonance signals from inside the cell. The Kistler system had a sensitivity of 0.2 mV/Pa. The signal needed to be bandpass filtered with a sharp and narrow pass window because the piezo transducer’s signal level was significantly lower than that of conventional microphones. The system was excited by the tweeter speaker’s sweeping frequencies between 5 and 10 kHz. Assuming a closed-end cylinder, the speaker produces standing waves that are influenced by the mixture’s speed of sound: c¼nf λ c¼f

nL 2

(7)

(8)

where L is the dominant length of the cylinder, n is the nth resonance of the fundamental frequency, c is the speed of sound, f is the fundamental frequency of excitation, and λ is the fundamental wavelength of the acoustic wave. Given the same harmonic and chamber length, the percent difference in speed of sound, c, is equivalent to the percent difference in frequency, Δf, while maintaining a constant temperature: Δc Δf ¼ c f

(9)

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The frequency sweep was repeated at each pressure step as the mixture’s pressure was changed along an isotherm. The speed of sound models for REFPROP and the tracked resonant peak shifts were identically normalized to the low-pressure speed of sound for that isotherm and compared. Since near-ideal behavior can be assumed, the low-pressure speed of sound was chosen as the normalization factor, resulting in a “known” speed of sound well within the confirmed, validated range of REFPROP. Using pure CO2 and comparing to trends with REFPROP, the experimental procedure was validated for the tested pressure and temperature range. Six isotherms of the inlet mixture condition’s peak frequency and density are shown in the normalized form in Fig. 19 for comparison. Particularly at higher temperatures, the measured trends closely match REFPROP’s models. Near the critical point, where the transition to the supercritical region causes significant variation of physical properties across small pressure and temperature differences, is where there is a significant departure from REFPROP’s model. Similar to this, any temperature variation within the cell at lower temperatures can lead to the formation of liquid CO2, which significantly impacts the mixture’s sound speed. This high sensitivity of properties close to the critical point can be used to explain the largest difference seen in 310 K near 74 bar.

4. Research outlook The research in sCO2 combustion is progressing rapidly. Some research outcomes are already used in the field to design sCO2 combustors. However, our understanding of supercritical combustion needs to progress much further. For example, there is a need to understand the fundamental properties of supercritical fluids in a better way. These are driven by empirical EOS and need to be validated by experiments. The properties like specific heat, viscosity, thermal conductivity, density, and speed of sound at sCO2 combustor conditions need to be validated at high temperatures and supercritical pressures. More experimental studies are needed on the kinetics of sCO2 combustion mixtures relevant to practical combustions. With a clear understanding of the fundamental properties and kinetics of sCO2 combustion, efficient sCO2 combustors can be designed and thus help in our quest for a carbon-neutral future.

FIG. 19 Measured speeds of sound of the inlet condition by temperature [38].

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References [1] USEP Agency. https://www.epa.gov/ghgemissions/overview-greenhouse-gases. (Accessed 20 December 2022). [2] R. Lindsey. https://www.climate.gov/news-features/understanding-climate/climatechange-atmospheric-carbon-dioxide. (Accessed 20 December 2022). [3] K. Brun, P. Friedman, R. Dennis, Fundamentals and Applications of Supercritical Carbon Dioxide (sCO2) Based Power Cycles, Woodhead Publishing, 2017. [4] V. Dostal, M.J. Driscoll, P. Hejzlar, A Supercritical Carbon Dioxide Cycle for Next Generation Nuclear Reactors, Massachusetts Institute of Technology, Department of Nuclear Engineering, 2004. [5] D.S.G.O. Musgrove, S. Sullivan, L. Chordia, M. Portnoff, tutorial: heat exchangers for supercritical CO2 power cycle applications, in: sCO2 Symposium, 2016. [6] NetPower, Natural Gas, Syngas, or Oil Allam Cycle CCS Power Plant, 2018. [7] A. Darde, R. Prabhakar, J.-P. Tranier, N. Perrin, Air separation and flue gas compression and purification units for oxy-coal combustion systems, Energy Procedia 1 (2009) 527–534. [8] J.-P. Tranier, R. Dubettier, A. Darde, N. Perrin, Air separation, flue gas compression and purification units for oxy-coal combustion systems, Energy Procedia 4 (2011) 966–971. [9] F. Wu, M.D. Argyle, P.A. Dellenback, M. Fan, Progress in O2 separation for oxy-fuel combustion–a promising way for cost-effective CO2 capture: a review, Prog. Energy Combust. Sci. 67 (2018) 188–205. [10] E. Schmidt, Thermodynamics—Principles and Applications to Engineers, New York, 2009. [11] R.G. Schmitt, P.B. Butler, N.B. French, Chemkin Real Gas: A Fortran Package for Analysis of Thermodynamic Properties and Chemical Kinetics in Nonideal Systems, University of Iowa, Iowa City, 1994. [12] K.R.V. Manikantachari, S. Martin, J.O. Bobren-Diaz, S. Vasu, Thermal and transport properties for the simulation of direct-fired sCO2 combustor, J. Eng. Gas Turbines Power 139 (2017) 121505. [13] S.M. Ovais, K.A. Kemenov, R.S. Miller, Direct numerical simulation of supercritical oxy-methane mixing layers with CO2 substituted counterparts, Phys. Fluids 33 (2021) 035115. [14] J.D. van der Waals, On the Continuity of the Gaseous and Liquid States, Universiteit Leiden, Leiden, 1873. [15] J.V. Sengers, R. Kayser, C. Peters, H. White, Equations of State for Fluids and Fluid Mixtures, Elsevier, 2000. [16] J.O. Valderrama, The state of the cubic equations of state, Ind. Eng. Chem. Res. 42 (2003) 1603–1618. [17] M. McLinden, S. Klein, E. Lemmon, NIST REFPROP V7. 0, 2006. [18] M. Anderson, NEUP Project 12-3318: Advanced Supercritical Carbon Dioxide Brayton Cycle Development, Report No. NU-12-WI-UWM_-3030-02, Univesity of Wisconsin, Madison, 2015. [19] D.S.H. Wong, S.I. Sandler, A theoretically correct mixing rule for cubic equations of state, AICHE J. 38 (1992) 671–680. [20] P. Ghosh, Prediction of vapor-liquid equilibria using Peng-Robinson and SoaveRedlich-Kwong equations of state, Chem. Eng. Technol. 22 (1999) 379–399. [21] M. De Giorgi, A. Sciolti, A. Ficarella, Application and comparison of different combustion models of high pressure LOX/CH4 jet flames, Energies 7 (2014) 477–497.

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[22] S.-K. Kim, H.-S. Choi, Y. Kim, Thermodynamic modeling based on a generalized cubic equation of state for kerosene/LOx rocket combustion, Combust. Flame 159 (2012) 1351–1365. [23] S.M. Martin, The Conditional Moment Closure Method for Modeling Lean Premixed Turbulent Combustion, University of Washington, 2003. [24] R.S. Cant, E. Mastorakos, An Introduction to Turbulent Reacting Flows, Imperial College Press, London, 2008. [25] P. Chueh, J. Prausnitz, Calculation of high-pressure vapor-liquid equilibria, Ind. Eng. Chem. Res. 60 (1968) 34–52. [26] G. Soave, S. Gamba, L.A. Pellegrini, SRK equation of state: predicting binary interaction parameters of hydrocarbons and related compounds, Fluid Phase Equilib. 299 (2010) 285–293. [27] B. Balaji, V. Raghavan, K. Ramamurthi, A parametric study of the choice of binary interaction parameter and equation of state for high pressure vapor-liquid equilibrium of nitrogen–n-Dodecane binary system, Int. J. Thermodyn. 14 (2011) 79–86. [28] M.M. Poschner, M. Pfitzner, CFD-Simulation of the Injection and Combustion of LOX and H2 at Supercritical Pressures, AIAA Paper No. 2010-1144, 2010. [29] S.M. Martin, J.C. Kramlich, G. Kosa´ly, J.J. Riley, The premixed conditional moment closure method applied to idealized lean premixed gas turbine combustors, J. Eng. Gas Turbines Power 125 (2003) 895. [30] F.M. White, Fluid Mechanics, McGraw Hill, 2011. [31] T.S. Park, S.-K. Kim, A pressure-based algorithm for gaseous hydrogen/liquid oxygen jet flame at supercritical pressure, Numer. Heat Transf. A Appl. 67 (2015) 547–570. [32] E. Masi, J. Bellan, K.G. Harstad, N.A. Okong’o, Multi-species turbulent mixing under supercritical-pressure conditions: modelling, direct numerical simulation and analysis revealing species spinodal decomposition, J. Fluid Mech. 721 (2013) 578–626. [33] K. Lucas, Pressure-Dependence of the Viscosity of Liquids—A Simple Estimate, VCH Publishers, Deerfield Beach, FL, 1981, pp. 959–960. [34] T.H. Chung, M. Ajlan, L.L. Lee, K.E. Starling, Generalized multiparameter correlation for nonpolar and polar fluid transport properties, Ind. Eng. Chem. Res. 27 (1988) 671–679. [35] B.E. Poling, J.M. Prausnitz, J.P. O’Connell, The Properties of Gases and Liquids, McGraw-Hill, New York, 2001. [36] L.I. Stiel, G. Thodos, The thermal conductivity of nonpolar substances in the dense gaseous and liquid regions, AICHE J. 10 (1964) 26–30. [37] A.A. Amooey, A simple correlation to predict thermal conductivity of supercritical carbon dioxide, J. Supercrit. Fluids 86 (2014) 1–3. [38] S. Park, J. Urso, K.R.V. Manikantachari, A. Hosangadi, A. Zambon, S.S. Vasu, Measurements of density and sound speed in mixtures relevant to supercritical CO2 cycles, J. Energy Resour. Technol. 142 (2020). [39] P. Ahmadi, A. Chapoy, B. Tohidi, Density, speed of sound and derived thermodynamic properties of a synthetic natural gas, J. Nat. Gas Sci. Eng. 40 (2017) 249–266. [40] I. Velasco, C. Rivas, J.F. Martı´nez-Lo´pez, S.T. Blanco, S. Otı´n, M. Artal, Accurate values of some thermodynamic properties for carbon dioxide, ethane, propane, and some binary mixtures, J. Phys. Chem. B 115 (2011) 8216–8230. [41] J. Trusler, M. Zarari, The speed of sound and derived thermodynamic properties of methane at temperatures between 275 K and 375 K and pressures up to 10 MPa, J. Chem. Thermodyn. 24 (1992) 973–991.

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CHAPTER

Catalytic combustion for cleaner burning: Innovative catalysts for low temperature diesel soot abatement

12

Vincenzo Palma, Giuseppina Iervolino, and Eugenio Meloni Department of Industrial Engineering, University of Salerno, Fisciano, Salerno, Italy

1. Introduction In various combustion reaction systems, undesired by-products may form, including soot [1]. Among the internal combustion engines, Diesel and gasoline direct injection (GDI) ones are widely diffused due to their high efficiency, durability, and low concentration of CO and hydrocarbon (HC) emissions. But their main drawback is the higher emission of soot or particulate matter (PM), responsible of severe environmental and health issues. In fact, PM presents a significant health hazard as it causes respiratory, cardiovascular and mutagenic diseases (such as lung and bladder cancer) and skin cell modifications [2]. Moreover, HC can react with nitrogen monoxide in the presence of sunlight to form ozone which irritates the lung [3,4]. According to Johnson et al. [5] and Kittelson [6], PM (often called soot) consists of a carbonaceous core with an agglomerated structure that forms in the combustion chamber by incomplete combustion, with size in the range 5–500 nm [7]. According to Klingenberg the core has a graphite-like structure [8]. There is an agreement that the most common reaction pathway to soot, considering that PAHs are thought to be the precursors of soot particles, involves the steps of (i) formation of PAHs, (ii) nucleation of particles from PAHs, (iii) surface growth of particles, and (iv) particle coagulation [2] (Fig. 1). The harmful effect of Diesel engines emissions made mandatory the adoption of increasingly stringent regulations in particular for soot and NOx, whose fulfillment may be reached only by using abatement systems. The former may be limited by using a diesel particulate filter (DPFs) or gasoline particulate filter (GPF), with or without catalysts, aiming at filtering it by the exhaust [9]. The most performant DPFs are commonly ceramic devices, whose high filtration efficiency (> 95%) unavoidable results in the increase of the pressure drop due to the soot accumulation; so, a compromise is mandatory in order to keep high both engine power and performance Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00002-3 Copyright # 2023 Elsevier Inc. All rights reserved.

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FIG. 1 Steps involved in the formation of particulate matter (PM). Reproduced from E. Meloni, V. Palma, Most recent advances in diesel engine catalytic soot abatement: structured catalysts and alternative approaches, Catalysts 10 (2020) 745.

[10]. In fact, DPFs operate in the wall flow mode (inlet and outlet channels alternatively plugged) including the deposition of soot onto the porous filter walls, while the exhaust flows through them. Therefore, the periodical burning of the entrapped soot (phase named “regeneration of the filter”) up to its combustion temperature is mandatory for keeping the soot level/backpressure not so high, and in this way, the ideal flow conditions are re-established [11]. Some different configurations of the soot abatement device have been proposed in the past, aiming at reducing the pressure drop increase during the filtration step. For example, Palma et al. proposed radial flow ceramic foam traps (both non-catalytic and catalytic) for the removal of soot from the exhausts of combustion systems, studying two different trap volumes (0.5 and 1.5 L) to evaluate the effect of the gas velocity on the filtering performance of the trap. They find that at high velocity of the gas through the trap critical conditions can be reached which lead to the discharge of soot depending on the speed and temperature of the gas, the soot load on the trap and the operating conditions of the burner (quantity and quality of the particulate). The catalytic trap has shown good performance being able to remove soot from the burner exhaust gases with an efficiency of 70% and allowing simultaneous filtration and combustion of the captured soot [12]. Since Diesel exhaust temperature is typically in the range 200–500 °C, and the oxidation temperature of soot is in the range 550–600 °C [7], oxidation catalysts are needed for allowing the reactions to occur at lower temperatures. In the development of catalysts in this field, many issues must be considered: (i) in addition to being active for soot oxidation, a catalyst must be also resilient in the exhaust environment or practical conditions, and (ii) the viability of soot oxidation is very much dependent on the degree of interaction between soot/catalyst, so it becomes very important to maintain the contact conditions as such the maximum utilization of contact points between soot/catalyst can be achieved, both of which are in solid-state [13]. Regarding the first aspect, the causes for the deactivation of diesel catalysts are thermal degradation and chemical poisoning [14]. The thermal degradation can be more detrimental as the temperature inside a filter can elevate up to 1000– 1100 °C and even higher in certain hot spots during the regeneration process (due to the exothermicity of the reaction). The chemical deactivation due to fuel derived sulfur and lubricant-derived phosphorus may cause serious poisoning influence on the catalysts and will completely diminish the activity of the catalyst in the long

1 Introduction

run. Regarding the soot/catalyst contact issue, there are different types of contact conditions, in particular: loose contact (mixing soot and catalyst with just a spatula), mixing in a mechanical mill (close contact) and passing of the diesel exhaust gas containing soot on a catalyst bed (in situ contact). Sometimes, it has been found that although free contact conditions are much closer to realistic due to the better reproducibility of results, close contact is commonly employed to test soot activity under laboratory conditions [1]. It has been reported that although some catalysts are very active in close contacts, they do not retain their activity in loose contact [15]. As previously mentioned, the aim of the catalyst is to be able to burn the soot particles at lower temperatures [1]. The catalysts with the best performance for these purposes are noble metals [16], transition metal oxides [17], alkali metal oxides [18], perovskite-like oxides [19], and copper ferrite [20]. Transition metal oxides such as MnOx [21], FeOx [22], CoOx [23] and CuOx [24] have been used as main catalysts for soot oxidation due to their redox catalytic cycles. It is possible to act with the catalysts in two different ways: it is possible to add the catalyst to the fuel in the form of organic derivatives of active metals or to provide for the deposition of a catalytic coating on the surface of the filter. In this last case, a catalytic DPF (CDPF) may be obtained, allowing simultaneous soot filtration and combustion [25,26]. This system assures that the pressure drop through the filter never reaches high values, resulting in further fuel consumption, as well as the filter thermal stresses, occurring during regeneration of catalytic trap loaded with large soot amount, are minimized [12]. It should be emphasized that most metal oxide-based catalysts allow optimal oxidation of soot only at temperatures above 400 °C. However, in recent years, some researchers have focused on developing catalysts to lower the catalytic oxidation temperature of diesel soot below 300 °C [27]. Considering the possibility of removing the soot through catalytic oxidation, the importance of transition metals was found as they are essential for the transfer of oxygen from the catalytic surface itself to the soot [7]. Moreover, catalysts may be coupled to innovative heating systems, such as microwaves [28], and non-thermal plasma [7], for example, for reaching the soot oxidation temperatures. With non-thermal plasma it is possible to supply the electrons with an energy that allows them to accelerate and have very high temperatures (over 20,000 K) but at the same time the temperature of the gas that surrounds them remains much lower (generally not over 400 K). The electrons collide with the molecules present in the gas (N2, O2 and H2O) and produce secondary electrons, photons, ions and radicals that accelerate the oxidation reaction of the soot [7]. In this way it is possible to work in the presence of low temperatures but at the same time exploiting the strongly oxidizing species generated by the plasma. Non-thermal plasma finds applications in various fields thanks to its extraordinary potential. It is possible to predict the application of NTP in the electronics industry to doping semiconductors and in the manufacture of microcircuits to engrave and deposit thin films [4]. Or another interesting application concerns the removal of contaminants in the gas or liquid phase through the strongly oxidizing species generated by NTP [29–34]. For the NTP it is possible to apply different reactor configurations: corona discharge, DBD, pulsed corona. The efficiency of NTP depends on several

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parameters, including the potential used to obtain the complete degradation of contaminants or the high selectivity to CO2. However, the process is limited in this sense, and it is for this reason that it was decided to couple the catalysts to the NTP process. Indeed, previous work indicates that the coupling of NTP with a catalyst often causes a synergistic effect on the oxidation efficiency of soot [7]. This synergistic effect can be explained by the short-lived reactive species formed in the discharge that promotes the reoxidation of metal oxide vacancies generated in oxidation reaction. In fact, the coupling between the NTP technology and the adoption of catalysts is an interesting issue in the PM removal; indeed, as also reported by Ranji-Burachaloo et al. [7]. They suggested that the short-living reactive species formed in the discharge could play an important role in promoting the re-oxidation of metal oxide vacancies generated during the oxidation reactions in the discharge and, moreover, the catalytic decomposition of the ozone could also result in an increase of the energy efficiency and allow the removal of this harmful component from the outlet gas stream [35]. The presence of ozone should not be underestimated, an important oxidant species generated in the plasma which has the characteristic of being thermally stable up to 200 °C. Considering the exhaust gases of diesel engines, which are at higher temperatures, you will notice the thermal and catalytic decomposition of ozone which certainly involves greater energy efficiency, and also allows the removal of O3 (harmful to the atmosphere) directly. Considering these premises, in this chapter the most recent advances in soot catalytic oxidation will be given, and the potential of NTP coupling with catalyst for soot abatement will be highlighted. Some of the main results reported in the literature will be exposed and compared with each other. In particular, the most commonly used reactor configurations for the plasma generation coupled to the catalyst, the catalysts typically adopted, and the definition of soot removal efficiency are among the main topics covered in this chapter.

2. Recent advances in catalysts for soot oxidation The research for the development of catalysts for soot combustion began since the early 1980s. Excellent catalytic performance coupled to optimal stability are the main features of the platinum group metal based (PGM) catalysts in the automotive exhaust treatment. Anyway, their limited resource availability and costly nature led to the need for exploration of alternative catalysts. Aiming at this, many non-noble metal-based catalysts characterized by different compositions and structural characteristics have been investigated and employed for soot removal. In this section, the recent advances in the development of various types of non-noble metal-based catalysts will be presented. Moreover, the monolithic catalysts will also be analyzed. Therefore, three different sub-sections are shown: (1) Ceria based catalysts, (2) Transition metal oxides, in which catalysts based on Spinel/Perovskite/hydrotalcite/delafossite, other metal oxides/mixed metal oxides will be reported, and (3) monolithic catalysts.

2 Recent advances in catalysts for soot oxidation

2.1 Ceria-based catalysts The oxygen storage and release capacity of CeO2 is an important feature which allows its effective use in soot oxidation reaction. This property is due to the ability of cerium to switch between the Ce4+ and Ce3+ oxidation states and to incorporate more or less oxygen into the crystal structure depending on various parameters, such as the gas composition, temperature, and pressure. In the years, several research groups have investigated the role of each of these parameters. For example, Bueno Lopez et al. [22] have demonstrated that the rate of gas-phase oxygen exchange by the CeO2 labile lattice oxygen with soot are much faster than the reaction rate of O2 reacting with soot directly. Besides the above discussed beneficial role of oxygen storage capacity (OSC) of CeO2, in several research paper the role of defects in CeO2-based catalyst has also pointed out. Among the others, the addition of Cu and Mn as dopants allowed the creation of both intrinsic and extrinsic defects in the CeO2 lattice, so enhancing the catalytic performance in the case of Ce95Cu2.5 Mn2.5 catalysts [19]. The authors demonstrated how the creation of O2-deficient sites is facilitated during oxidation over defective catalysts presenting an abundance of O2 vacancies on their surface, thus, benefitting the soot oxidation. Moreover, the almost reversible behavior of pure and Mn-doped CeO2 even after total soot oxidation revealed the exceptional ability of these catalysts to regenerate the most active defect sites. Anyway, CeO2 suffers from deactivation if it is calcined at high temperature (
1000 °C), with consequent very low surface area (2 m2 g1), large crystal size (110 nm) and lack of surface redox properties [21]. In order to overcome this deactivation, two approaches have been suggested. The first one is to dope CeO2 with other rare earth elements such as La3+ [22], Pr, Sm, and Tb, coupled to transition metals (Zr and Fe) [23]. In particular, the research has demonstrated that La-doped CeO2 increased both the specific surface area and the redox properties so resulting in an enhanced catalytic activity for soot oxidation by O2. The second approach is related to the improvement of the morphology of CeO2 through properly designed innovative preparation techniques aiming at forming stable frameworks and high surface area catalysts. Piumetti et al. studied the structure sensitivity of the nanostructured ceria-based catalysts and reported that the nanocubes of CeO2 are very active for soot oxidation owing to enormous contribution from highly reactive (100) and (110) planes [24], and, when well-exposed, these surfaces are generally more active than conventional polycrystalline ceria NPs with (111) exposed surfaces [36]. The order/sequence of catalytic activity reported for ceria-nanostructures based on several catalytic reaction is nanocubes > nanofibers > conventional CeO2 nanoparticles [24], which reflects the reverse order of the surface stability of ceria: [100] and [110] < [111] crystal facets. The maximization of the exposition of more active surfaces of CeO2 may be obtained by depositing ceria directly on the surface of the filter wall [37]. In this sense, the use of ceria nanofibers may be useful due to their ability to form randomly arranged networks [38], which may improve the soot oxidation activity under poor condition of contact. In fact, they retain their morphology in the coating process, so having high open porosity which led to an increased soot

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trapping, as well as to low associated backpressure in the fibers [37]. GuillenHurtado et al. have synthesized a novel Ce0.5Pr0.5O2 catalyst having beneficial morphological properties, which resulted in better catalytic performance in soot oxidation (in NOx-containing atmospheres) than a commercial Pt-based catalyst [39]. In general, different studies have demonstrated that nanostructured materials are remarkable due to their small-featured size, that gives them two fundamental characteristics: (i) high surface-to-volume ratio, resulting in the abundance of coordinatively unsaturated metal centers, and (ii) distinctive electronic properties, resulting in the so called quantum confinement effects [1]. The effectiveness of ceria based nanostructured material has also been confirmed in various reactions, such as carbon dioxide oxidation [40], carbon dioxide reforming of methane [41], steam reforming of methanol and ethanol [42], low-temperature water-gas shift (WGS) reaction [43] and, more notably, soot combustion [44].

2.2 Other transition metal oxides (TMOs) Among various transition metal oxides, spinel/perovskite/delafossite/hydrotalcite catalysts have received great focus as they are quite promising catalysts having good mobility of active species and facilitate NO decomposition [45]. Therefore, the key findings of the work done over such type of catalysts are summarized below.

2.2.1 Spinel based catalysts Spinels form an important class of TMOs with appealing catalytic activity for soot oxidation reactions owing to their desirable activity, widespread availability, low cost, easy synthesis, thermodynamic stability, and environmental friendliness. In the spinel structure, the coexistence of tetrahedral and octahedral sites provides multiple sites to accommodate different transition-metal cations with a wide range of valence states to form a large number of oxides. Given its promising features, various studies have been reported over spinel-based catalysts for soot removal. In particular, the Co-based ones have been extensively studied. CoAl2O4 catalyst exhibited a remarkable activity for soot oxidation comparable to that of the commercial Pt/Al2O3 catalyst [46]. Co3O4 catalyst exhibited a soot oxidation temperature of 683 K (lower than non-catalytic one) under tight contact [46]. Lin et al. have revealed unexpectedly high performance of BaAl2O4 spinel catalyst for the simultaneous abatement of soot-NOx, even under very loose conditions of catalyst/soot contact [47]. Other investigated Co-based spinel catalysts with high soot oxidation activity reported in literature include CuCo2O4 [48], CoFe2O4 [49], CoMn2O4 [50]. In general, the addition of a dopant to pure spinel-based catalysts may enhance the soot oxidation activity. The dopant may be added by either (i) dispersing on the surface or (ii) intercalating into the structure alkali cations. The former way leads to (a) the modification of the electro donor properties of the surface (so resulting in the formation of active forms of oxygen by means of the electron transfer), and (b) the formation of low melting point compounds, which result in improved soot-catalyst contact. The latter way very often may result in the formation of layered or tunneled

2 Recent advances in catalysts for soot oxidation

structures (nanostructuration) enabling very high cation mobility, but in some cases the catalytic activity may enhance also without changes in the structure [51]. Legutko and coworkers studied the effect of K on the soot oxidation activity of transition metal (Mn, Fe, Co) spinels [52]. The results of their studies evidenced that the K addition could effectively enhance the spinel soot oxidation activity, even if, both the dopant concentration and its location (bulk or surface) influence this promoting activity. In particular, K located in bulk has been more active than K located on the surface. In fact, the formation of layered structures of KCo4O8 and KMn4O8 in bulk location revealed a Tonset of the soot oxidation of 250 °C. Moreover, it was observed that the difference in activity between intimate and poor conditions could be reduced in the presence of NO because of its conversion into NO2 that acts as the O2 carrier from the catalyst surface into carbon particles, bridging the differences due to the soot-catalyst contact conditions. One important drawback of the spinel-based catalyst is their tendence to sintering, for example in the case of typical spinel NPs such as Co3O4. In this case, the catalyst exposed very low surface areas to soot particulates, thereby decreasing their catalytic activities. So, well-defined and hierarchical structures to prevent aggregation of NPs have been designed for spinel-based catalysts, such as spinel oxide fibers, 3DOM spinel structures [53] etc. Anyway, these approaches, effective in preventing aggregation of NPs, require sophisticated and multiple-step fabrications, making them less practical for large-scale production. Hence, further research is required to develop more economical and environmentally benign routes for the synthesis of structurally stable spinel-based catalysts.

2.2.2 Hydrotalcite based catalysts Another class of TMOs, layered double hydroxides (LDHs) also known like hydrotalcites, are also found to be promising supports and catalyst precursors for heterogeneous catalysis owing to their wide variety of features, such as a large number of hydroxyl groups, tunable surface basicity and acidity as well as high adsorption capacity for the immobilization of active species. Under soot combustion work over hydrotalcites, Ura and co-workers [54], Li et al. [55] have reported that K-doped hydrotalcite-derived CoMgAlO catalysts showed promising activity for soot oxidation and simultaneous soot-NOx abatement under conditions comparable to that observed in CDPF. Recently, Zhao et al. studied the influence of Pd, K co-doping on the morphology and soot oxidation activity of the Mg-Al hydrotalcite catalyst in an SO2-containing atmosphere. An interaction between Pd and K, forming a species of Pd-O-K, which enhanced the K dispersion, and the K, Pd co-doping significantly decreases the activation energy of CO2 and N2, meanwhile reduces the soot ignition temperature and enhances the NOx conversion [56]. Despite its promising activity, one severe disadvantage concerning hydrotalcite based catalysts is the requirement of very strict experimental conditions during its synthesis to avoid chemical segregations and improve homogeneities is very demanding. Thus, the existence of some technological-economic problems in hydrotalcite preparation limits its wide applicability.

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2.2.3 Perovskite based catalysts The perovskite-type oxide with an atomic ratio of ABO3 has excellent redox property, low cost, thermal stability, and structural stability and it is very suitable as a catalyst for catalytic oxidation of diesel soot [57]. In research supported by General Motors (GM) company, strontium-doped perovskite catalyst have been successful in replacing existing commercial Pt-based after control devices (such as Diesel Oxidation Catalyst), thus showing a potential for low-cost diesel exhaust treatment system [58]. Additionally, several perovskites (LaCoO3 [59]; SrCoO3, CeCoO3 [60]; LaFeO3 [61]; LaCrO3 [62]) or perovskite-related oxides such as double perovskites (LaSrFeCoO6 [63]); metal substituted perovskite (La-SrFeO3; Ba doped LaMnO3 catalysts [64]) have shown promising soot oxidation activity. As discussed in the above paragraphs, the contact conditions between soot and catalyst have a strong effect on the efficiency of soot oxidation catalysts. However, the pore size of these powdered form catalysts is much smaller than the size of soot particles (> 25 nm), which results in the less contact on the internal surface of the catalyst. The soot particles on the external surface of catalyst take part in the soot combustion, which limits the catalytic activity [65]. To tackle this issue, many efforts have been taken into the fabrication of hierarchical porous structure in order to improve the contact conditions of catalyst-O2 and catalyst-soot in soot oxidation. In a recent work done by Sun et al. synthesized microporous La1–xCexCoO3 perovskite oxide catalysts by complexcombustion method [66]. The introduction of ethylene glycol complexing agent and relatively low calcination temperature in preparation led to the formation of hierarchical macroporous-mesoporous composite structures. The obtained specific surface areas were reported to be higher than the same type of materials reported in the literature (below 10 m2 g1) which helps in improving contact conditions of catalystO2 and catalyst-soot in soot oxidation. In case of three-dimensional ordered microporous (3DOM) materials (3DOM LaFeO3), the macropores are larger than 50 nm which can permit the soot particles to enter their inner space, promoting the reaction of soot catalytic combustion. Moreover, the interconnected macroporous tunnels facilitate the soot particle to transfer and reach active sites easily with less diffusion resistance. Hence, the contact frequency between soot and catalyst increases considerably and contribute to the improvement of soot oxidation activity of catalysts. Further in case of nanofibers, the high efficiency of nanofibrous oxide in trapping as well as oxidizing soot makes than promising catalysts for the designing of novel catalytic systems. A coating of 6-μm-thick layer of nanofibrous lanthanum manganite perovskite was done on silica fiber, and the final rods of about 20 μm in diameter were obtained [67]. The obtained nanofibrous LaMnO3 catalyst exhibited similar soot oxidation activity as that of powder LaMnO3 catalyst, but the trapping efficiency of soot by fibrous oxide was higher than the trapping efficiency of soot by powder oxide. Lee and co-workers obtained La1xSrxCo0.2Fe0.8O3δ perovskite oxide fibrous webs having 3D porous framework via electrospinning method for soot oxidation [68]. The characterization results revealed that the enhanced catalytic activity is possibly due to enhancement of contact chances between the reactant (soot) and the surface of the catalyst, resulting from the 3D large-pore structure which can hold the soot

2 Recent advances in catalysts for soot oxidation

particles. This unique feature provides a high contact area, thus, able to increase soot oxidation activity with very low activation energy. One more recent example of 3DOM perovskitic catalysts has been proposed by Li et al., who prepared and tested La1xKxMnO3 catalysts with high activity for the simultaneous elimination of soot and NOx [69]. All these studies evidenced that the 3DOM structure not only increases the contact efficiency between soot and catalyst but also provides more reaction places which is beneficial to mass transfer. Thus, perovskite oxides with fiber web structures are found to be promising catalysts for soot oxidation.

2.2.4 Delafossite based catalysts The delafossite-type compounds with general formula A + B3 + O2 have been known and studied for a long time, but not much work is reported over such catalysts as soot oxidation catalysts. Their structure can be viewed as the stacking of [B3+O2 2 ]∞  layers made of two closed packed oxygen planes having all octahedral sites occupied by B3+ cations, which are connected by planes of A+ cations arranged according to a triangular network. Each A+ cation is coordinated linearly to two oxygen anions from the oxygen planes above and below. Depending on the mutual orientations of successive layers, various delafossite structures can exist. Bensaid et al. prepared several Li-Cr delafossite catalysts in various stoichiometric and sub-formulations via solution combustion synthesis (SCS). All the obtained formulations were examined in laboratory-scale studies as well as in wall-flow ceramic filter in which the catalyst having LiCr0.9O2 composition exhibited the best activity [70]. The so-catalyzed trap achieved a significant decrease in time needed for the regeneration of filter and performed much more complete regeneration in comparison/with respect to a un-catalyzed trap. Similarly, in recently published research, Wang et al. studied several Li-Co delafossite catalyst synthesized via SCS can efficiently decrease the soot ignition temperature, and reduce NOx up to certain degree, thus, can effectively abate NOx and soot simultaneously [71]. Varying the Li or Co cations stoichiometry can increase the soot oxidation performance of the catalyst, where the optimized catalyst (LiCo0.9O2) lowered the soot ignition temperature to 289 °C and achieved the NOx conversion rate of 13.2%.

2.2.5 Other single metal oxides or mixed metal oxides Sa´nchez et al. have examined the activity of noble metal (Rh and Pt here) promoted K-La2O3 catalysts and showed that this doping favors the simultaneous abatement of NOx-soot, under intimate contact mode [72]. Castoldi et al. investigated the role/ reactivity of some alkaline (Na, K, Cs) and alkaline-earth (Mg, Ca and Ba) metal oxides for the soot combustion and found that their doping is beneficial for the soot oxidation [73]. The doping with Cs and Mg gives the highest and the lowest activity, respectively. The reactivity in the soot oxidation of the selected species observed to be a function of electronegativity of the constituent cations. Olong et al. applied combinatorial method for the exploration of multi-component oxides and screened out 50 metal oxides for doping of La5Co95 binary catalyst [74]. The unusually exceptional activity is obtained with Pb-doped La5Co95 (Pb10La5Co85Ox) catalyst, though the

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presence of Pb in catalyst raised doubts regarding its possible applications in real diesel exhaust system. Moreover, Cs3Co97 oxides are potential catalysts for soot oxidation, exhibiting better stability as compared to K-doped CeO2 catalysts. A CuMnHBeta catalyst with hierarchical mesopore micro-microporosity framework has been prepared using zeolite beta as a catalyst carrier, followed by an alkali etching and a co-impregnation process of co-loading of active Cu and Mn species. The resultant CuMn-HBeta catalyst shows an outstanding and extremely stable catalytic performance with low light-off temperatures of T50 (260 °C) and T90 (300 °C), owing to the formation of 3D hierarchically porous framework, the efficient dispersion of Cu and Mn species and the synergism between valence-changeable Cun+ and Mnn+, that facilitate the creation of active O2 species (O/O2) and active intermediate (NO2), together accelerating the soot oxidation [75].

2.3 Monolith based catalysts As the problem of NPs aggregation is commonly encountered in TMOs on their high temperature calcination. The sintered NPs show very low surface areas leading to their poor contact with soot. Besides doing morphological changes in the structure of the catalysts, researchers usually put the active components on the monolithic support to act as a particulate filter [76,77]. The monolithic support is consisting of a single block of small parallel channel has a cross-section like a honeycomb structure. One of the main advantages of monoliths in comparison with conventional powder catalysts is the low resistance, and they expose to the gas flow due to a high open frontal area which could be higher than 70%. The generally preferred support material is cordierite with the following composition:2MgO:5SiO2:2Al2O3, and a softening point above 1300 °C. Honeycomb cordierite is commonly used due to its high mechanical strength, stability at high temperature, temperature shocks and low thermal expansion coefficient. Banus and co-workers deposited Co, Ba, K/ZrO2 catalyst on a cordierite monolith and investigated them for soot combustion [78]. It was reported that the morphology of wall-flow type soot filters (cordierite monoliths) provides an optimum substrate for the anchoring of a thin catalytic coating, thus achieving an excellent mechanical stability. Moreover, the catalytic layer also covers internal pores of the channel walls, where some of the soot particles are trapped, enhancing the catalytic activity and preserving most of the original cordierite monolith macroporosity. Thus, coating cordierite walls with a Co, Ba, K/ZrO2 catalyst reported to be an effective catalytic filter for soot removal. One disadvantage concerned with the use of cordierite is its low specific surface area (0.7 m2 g1). Consequently, a bare cordierite monolith is not an adequate carrier for the incorporation of the active metals. The method of depositing a porous material (e.g. alumina, 200 m2 g1) found to solve the problem over the monolithic substrate. The methods such as dip-coating, direct synthesis, chemical vapor deposition, have been used to deposit catalytic coatings on cordierite substrate. ɤ-Al2O3 is the most prevalent secondary support materials due to its advantages in porosity and large specific surface area (150–300 m2 g1). The use of ɤ-Al2O3 further solves the problem of coating

2 Recent advances in catalysts for soot oxidation

adhesion. The difference in thermal expansion coefficients of metallic support and ceramic washcoat have led to the weak adhesion force problem between them. The active components on the filter are easy to fall off due to the weak adhesion force between the monolithic support and the coating layer, leading to the need for extra binders. The extra binders are not needed in case of ɤ-Al2O3 dip-coating process because of its outstanding adhesiveness. Recently, Tang et al. studied the role of ɤ-Al2O3 in which they successfully prepared LaCoO3/ɤ-Al2O3/cordierite monolithic catalysts and LaCoO3/cordierite monolithic without alumina sol coating [76]. The stability and catalytic performances of the LaCoO3/ɤ-Al2O3/cordierite monolithic catalysts were reported to be much better than LaCoO3/cordierite monolithic catalyst. The reason revealed behind this is that the introduction of Al2O3 washcoat can greatly enhance the surface area of monolithic cordierite, and it further increase the loading amount and dispersion of active components of the catalysts on the surface of monolithic cordierite. The higher the contents of active components the monolith catalysts have, the greater numbers of active sites of the catalysts have for soot oxidation. The higher the surface area of the catalysts and the larger contents of active components the monolith catalysts have the higher contact efficiency of the catalysts and soot particle will possess [76]. Besides the use of ɤ-Al2O3, the approach used to solve the adhesion problem is the application of some pre-treatments. Ferrandon et al. developed a technique to grow a number of textured alumina whiskers on the surface of the metal support before dip coating, which greatly improved the combination ability between the alumina washcoat and the support [79]. Shen and co-workers studied the influence of Ce0.68Zr0.32O2 solid solution on depositing ɤAl2O3 washcoat on FeCrAl foils [80]. The results reported that the addition of Ce0.68Zr0.3O2 solid solution into slurries could improve ɤ-Al2O3-based washcoat adhesion on FeCrAl foils as the Ce-Zr solid solution can inhibit the transformation of ɤ-Al2O3 crystal into others at 1050 °C for 20 h. In addition to weak adhesion force problem, the preparation process of catalytic filter using monolithic support is also very complicated. In recent years, dedicated investigations were performed by the research group of the University of Salerno in the development of an effective and resistant soot oxidation catalyst. The investigated catalyst was the copper ferrite (CuFe2O4) deposited on a silicon carbide (SiC) DPF by means of an optimized deposition procedure [81]. The deposition of a high catalyst load (30 wt%), without affecting the pressure drop, was possible due to specifically developed pretreatment of the bare monolith based on a controlled chemical erosion structure with an HF:HNO3 acid solution with the aim to increase the average pore diameter [82]. The tests performed at the exhaust of a 500 cm3 diesel engine have shown that the catalytic DPF (0.35 L) was able not only to oxidize the soot starting from 350 °C but was also able to reduce the duration of the regeneration step. The K addition to the catalyst formulation (Cu0.95K0.05Fe2O4) had the effect to further decrease the duration of the regeneration procedure, allowing a further energy saving [83]. Then, well established experimental tests aimed at evaluating the feasibility of this developed catalytic DPF in real conditions were performed at the exhaust of a EURO V light-duty diesel engine (2.3 L), operating at

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different speed/load conditions, by using a 30 wt% CuFe2O4 loaded DPF (3.5 L); a no catalytic DPF was used as comparison [84]. The preliminary tests have shown that the two DPFs had similar filtration efficiency, demonstrating that the catalysts’ deposition did not affect the filtration performance. A step-by-step increase of injected fuel during the post injection phase was used, in order to identify the starting temperature of the DPF regeneration. The experimental results have shown that the catalytic filter exhibits a threshold temperature of 150 °C lower than the bare one. Moreover, the results also evidenced that the amount of injected fuel for the catalytic DPF regeneration was significantly smaller than standard DPF, with considerable benefits on fuel economy and CO2 saving. Further investigations were subsequently performed to verify the possibility to have a passive regeneration of the DPF, and the results highlighted a constant value of pressure drop (meaning that the soot oxidation rate equals its deposition rate) at the temperature of 320 °C. A further increase of the temperature up to 340 °C, achievable by a small adjustment of engine load, resulted in the decrease of the pressure drop, thus evidencing the occurrence of passive regeneration [85]. To overcome the issues of complicated process and weak adhesion force, advance supports are being studied. Differing from then traditional monolithic catalysts, the SBA-15 monolith (SM) supported catalysts are reported to be prepared more easily. In addition, the high specific surface area of SM enables the high dispersion of active component on it for generation of more active sites, while the macropores derived from the 3D network in SM provide high accessibility of the soot reactants to the active sites. Working in this direction, Yang et al. synthesized a cobalt and cerium composite oxide functionalized SBA-15 monolith (SM) with an inner three-dimensional (3D) network structure (CoCe/SM) by isovolumetric impregnation and evaluated for its soot combustion activity [77]. It was reported that compared with unsupported Co3O4-CeO2 particles, the CoCe/SM catalysts with optimized Co3O4-CeO2 loading showed much higher catalytic ability, achieving a complete oxidation of the soot to CO2 below 400 °C in the presence of NOx, which is attributed to the high dispersion of Co3O4-CeO2 on SM and the cross-linked macroporous structure of SM that can house the soot particulates, thus providing closer contact between the soot and catalytically active sites. Based on the above discussions, it can be concluded that in order to fulfill the future prospects favoring diesel-fuelled engines, it is essential to design novel catalysts possessing high activity and robust framework but economically priced. Hence, focus should be made toward the synthesis of powder catalysts that reduce, or discard, the use of noble metal-based catalysts. In particular, nanostructured ceria-based catalyst (Ce-NC/ ZMS-5) have shown a good thermal stability when evaluated under three successive catalytic cycles (TPO tests) (e.g., as a function of temperature, on each heating run and then kept at 750 °C for 1 h in dry conditions) for soot oxidation. As a whole, comparable performances have been attained during multiple TPO cycles, and no significant deactivation was seen in terms of total soot conversion [24]. However, a slight decrease in soot conversion at low temperature is observed due to a lower amount of surface-adsorbed oxygen species, which play a significant role in oxidation catalysis (via spillover phenomena or “remote control effect”). However, accelerated

3 Reactor configurations for soot removal with catalytic “NTP”

deactivation experiments (e.g., stream on run at 850 °C in 10 vol% water vapor) are necessary to assess the potential of catalysts for its application in DPFs in realistic diesel exhaust conditions.

3. Reactor configurations for soot removal with catalytic “NTP” In order to understand the efficiency of the non-thermal catalytic plasma in the soot removal, it is necessary to first consider the NTP-catalyst coupling, regarding the reactor configuration used and the arrangement of the catalyst in the plasma reactor. This combination (NTP-CATALYST) is proposed in the literature for different applications: from water treatment to the removal of VOCs, to methanation, and therefore, as we will see later, for the soot removal. From the literature, it is possible to observe that the most used system to create a catalytic NTP is the dielectric barrier discharge (DBD) reactor where the heterogeneous catalyst, for example in the pellets form, were packed into the discharge zone (between the ground electrode and the reactor body) [86,87]. But, where is placed the catalyst? It is legitimate to ask this question. Is the catalyst inside the reactor, in contact with the discharge? Or downstream? According to the catalyst position in reactors, NTP coupled with catalyst was divided into two configurations: in-plasma (IPC) and post-plasma (PPC) catalysis. Fig. 2 provides the basic structures of IPC and PPC. In particular, it has been seen that the IPC configuration ensures excellent exposure of the catalytic surface with the ionized gas and therefore an intimate contact between the active sites and the reactive species generated by the plasma. Furthermore, it has been reported that the presence of a heterogeneous catalyst is able to intensify the electric field generated at the angles and curves of the catalytic surface, thus ensuring an effective treatment even in the presence of “lower” voltage values compared to the typical values used for NTP but without catalyst [31,32,87,88]. When a catalyst is filled in a plasma discharge region, micro-discharges are formed in the pores of the porous catalyst, electric field distribution changes, local electric field strength rapidly increases, and energy density can be increased. After the filling of catalyst ferroelectric particles, the specific energy input was higher (6–10 times that at a high voltage) than that in the plasma reactor alone [89]. Plasma discharges can improve catalyst performance. NTP can directly act on the active centers of catalysts and reduce the activation energy of reactions; alternatively, it can expand the distribution of active components and thereby promote the formation of more active centers and enhance catalytic performance [90]. Moreover, the presence of heterogeneous catalyst in the plasma can increase the production of active substances in the discharge process. In an IPC type configuration it is possible to provide three different ways by which catalysts are usually placed in DBD reactor. It is possible to create a catalyst coating directly on the surface of the electrodes or it is possible to provide for the filling of the reactor in the discharge section and finally, it is possible to create a catalytic layer in correspondence with the grounder electrode, leaving the surface

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plasma IN GAS

PACKED BED catalyst OUT GAS

plasma IN GAS

a)

Catalyst COATING

OUT GAS

plasma IN GAS

Catalyst LAYER

OUT GAS

b) Plasma REACTOR

Catalyst REACTOR

IN GAS

OUT GAS

FIG. 2 Schematic representation of IPC (A) and PPC (B) reactor.

of the catalyst free which will thus be exposed to the discharge and to the ionized gas. So, it is possible to find in the literature a large number of scientific papers dealing with the application of catalysts in NTP reactors. For example, Chen et al. have proposed a catalytic study on NTP-assisted CO2 methanation using Ni catalysts supported on BETA zeolites [86]. In their work they propose the use of a DBD reactor filled with catalyst pellets (IPC configuration). In this case, the applied peak voltage was varied from 5.5 to 7.5 kV. Regarding water treatment, e.g. for drug removal, it was reported by Shi Gong et al. the degradation of Levofloxacin (LFX) by non-thermal plasma (DBD) combined with Ag3PO4/activated carbon fibers [91]. They reported that the degradation efficiency of LFX increases with the increase of discharge voltage, liquid circulation velocity, catalyst dosage and, moreover, low value of pH favors LFX degradation. However, the best energy yield

3 Reactor configurations for soot removal with catalytic “NTP”

was obtained by applying a voltage equal to 8 kV [91]. DBD coupled with Fe2O3 immobilized on glass spheres for Acid Orange 7 dye degradation has been reported [92]. The experimental tests were conducted in a falling film DBD reactor with a cylindrical configuration and with a voltage value equal to 12 kV. The temperature inside the reactor (with liquid phase) didn’t exceed 30 °C. Therefore, it is possible to understand, just from these few examples (but there would be many in the literature) that the development of NTP technology, in particular based on DBD reactors, coupled with the use of heterogeneous catalysts, is widely used in different fields, ranging from the treatment of the gas phase with VOC removal to the degradation of organic contaminants of various kinds (drugs, dyes, pesticides). Let’s now move on to the case of interest, which is the NTP application coupled to catalysts, for the abatement of the soot. Let’s see in particular what are the reactor configurations and the relative operating parameters most used for this purpose. A DBD is usually always used. In particular, one proposal is a DBD made with two alumina plates, two stainless steel plates and two alumina spacers, all assembled and installed in a stainless-steel case [93]. A schematic representation is shown below (Fig. 3): The ionized gas can be a mixture of water and nitrogen to which it is possible to add saturated water at 25 °C in the case of tests in the presence of humidity. With this reactor configuration, the applied voltage did not go beyond 8 kV (so these are always lower voltages than those generally used for systems without catalyst, which are around 20–30 kV). Under these conditions the system temperature varied between 100 and 250 °C (range of a typical exhaust gas temperature for a light-duty

STAINLESS STEEL PLATE ELECTRODE

ALUMINA PLATE (1)

ALUMINA PLATE (2) DPM PRECIPITATE LAYER

STAINLESS STEEL PLATE ELECTRODE

FIG. 3 DBD alumina plate reactor. Reproduced form S. Yao, X. Shen, H. Lu, D. Ni, X. Tang, Z. Wu, J. Han, X. Zhang, Metal sulfates enhanced plasma oxidization of diesel particulate matter, IEEE Trans. Plasma Sci. 45 (2017a) 2984–2987.

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diesel engine). Diesel particulate matter (DPM) was loaded on the alumina plates and, after DBD application (with these operating parameters Pdis ¼ 4.5 W, t ¼ 1 h, and T ¼ 200°C) 10.8 mg of DPM was removed from the alumina plate and converted in CO and CO2. Moreover, the effect of only heat on the DPM removal was investigated and it was observed that the reduction in DPM weight due to a sole heating effect (for 1 h) is less than 2 mg. So, this result indicate that the DPM removal from the alumina plate was dominantly due to the DBD, due to the effect of oxidizing species produced with non-thermal plasma [93]. Furthermore, in order to get as close as possible to the real combustion conditions of diesel, it is possible to carry out experiments for the abatement of DPM with NTP in the presence of water vapor. In fact, the combustion of diesel fuel produces water. The presence of water in the system allows for an increase in energy yield of about 11%. This is due to the fact that the presence of water vapor promotes the formation of oxidizing species such as hydroxyl radicals. OH radicals are mainly produced by the reaction of O (1D) and H2O, as shown in Eq. (1). Since an O atom produces two OH radicals, the energy yield of the DPM oxidation could be improved in the case of discharge in humid air:
H 2 O + O 1 D ¼ 2OH

(1)

In this regard, how is it possible to calculate the energy yield in a process like this? It is observed that generally the energy yield of a cold plasma process for the removal of DPM is expressed in terms of mass of oxidized DPM after a certain reaction time, in the presence of a certain power value applied to the system (W). So the unit of measurement will be [g/kWh]. This is a simple and fairly explicit way to evaluate the functionality of the system, used not only for the abatement of low temperature DPM with NTP, but also for other contexts of cold plasma application. However, there are also other analytical methods proposed to define the efficiency of the catalytic NTP in the removal of the soot but which will be described in detail below, together with the catalytic species used. Another possible reactor configuration is always a DBD in which the power electrode is placed inside an alumina tube (it could be defined as a cylindrical coaxial configuration, not with parallel plates like the previous one). The second electrode is instead a copper foil wrapped around the alumina tube [17] The catalyst is then positioned inside the reactor, between the two electrodes using a packing length. The position of the power electrode, as well as of the catalyst, can be fixed by two porous ceramic rings. In this configuration it is possible to apply a voltage of 7–11 kV, in order to obtain a temperature range in the reactor that varies between 150 and 350 °C. To evaluate the performance of this system, it is possible to study the abatement of soot using a soot simulant (naphthalene), as reported in some scientific papers [17]. Below is a schematic of the proposed reactor configuration (Fig. 4). The application of non-thermal plasma allows not only to obtain excellent performance in terms of removal of particulate matter from the exhaust gas, but also an excellent conversion of the particulate into CO2. NTP certainly has the advantage of guaranteeing a sort of electrostatic precipitation of particulate matter, offering the

3 Reactor configurations for soot removal with catalytic “NTP”

TRASFORMER

OSCILLOSCOPE

GAS OUT GAS IN PACKED BED CATALYST IN DISCHARGE ZONE

TUBE FURNACE

FIG. 4 Schematic representation of IPC DBD reactor. Reproduced from V.T. Nguyen, D.B. Nguyen, I. Heo, Y.S. Mok, Plasma-assisted selective catalytic reduction for low-temperature removal of NOx and soot simulant, Catalysts 9 (2019) 853.

following advantages over a filter-based technique (DPF): moderate energy consumption, low maintenance costs and no interference in engine operation diesel. However, it should be considered that with electrostatic precipitation it is possible to have a dirtying of the electrodes due to the precipitated DPM (Diesel particulate matter (DPM)) [9]. Consequently, washing with water is necessary to continuously clean the electrodes. However, the water washing process requires a water supply system, which is very complicated for the development of a compact system for vehicle applications. The literature proposes the pulsed dielectric discharge reactor (DBD) which fully exploits NTP using ions produced by plasma and oxidative radicals in a single treatment process [9]. The removal of DPM can be described by considering the two phases: (1) the electrostatic precipitation of the charged DPM (through ion attack) and (2) the oxidation of the precipitated DPM into CO and CO2 [9]. By optimizing the reactor configuration, relatively high DPM removal (
80%) and CO2 selectivity (
60%) were achieved for light diesel vehicles with a very competitive fuel penalty (3%) [94]. Further optimization of DPM removal and CO2 selectivity requires the combination of heterogeneous catalysts with the pulsed DBD reactor. For this purpose, excellent results can be obtained by combining a pulsed DBD reactor combined with Au/CaSO4/γ-Al2O3 catalyst balls. γ-Al2O3 balls were used because of their large surface area, good mechanical and chemical stability, and excellent nanoparticle trap ability. 30 CaSO4 and Au were used as catalysts because CaSO4 has a good ability for the plasma-catalytic oxidation of DPM, 25 while Au has a high activity for the simultaneous removal of NOx, HCs, and CO at low temperatures [9]. As very often happens, the application of nonthermal plasma not only guarantees the removal of the soot but also the abatement of other polluting compounds present in the exhaust gas of diesel engines, therefore: CO, HCs, and NOx [9], In this case the reactor configuration includes two alumina

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plates, two stainless steel plates, and two alumina spacers. The discharge gap was filled with ca. 8 g of catalyst balls having a diameter between 1.0 and 1.5 mm. In order to maintain the constant temperature inside the reactor, a feedback-controlled electrical furnace can be used. The temperatures involved are always in the 150– 250 °C range. A nitrogen-oxygen mixture can be introduced as process gas (to be ionized), which allows to perform different tests by varying the O2%, in particular in the presence of about 10% or 15% of oxygen, very similar to the conditions present in exhaust gas from a higher load diesel engine. However, it has been noted that with a lower oxygen concentration the DPM removal efficiency as well as the CO2/CO ratio decreases as compared to a higher oxygen concentration (20%) plasma processing. in fact, in the NTP process it is precisely the presence of oxidizing species such as the O atom and O3 that guarantees the oxidation of the particulate at relatively low temperatures, as described by the following equations: DPM + O ! CO, CO2

(2)

DPM + O3 ! CO, CO2

(3)

CO + O ! CO2

(4)

Where an O atom is produced by the electronic dissociation of O2 (O2 + e ! O + O + e) and O3 is produced by the combination of an O and O2 atom (O + O2 ! O3). It was noted that the direct contribution of O3 to the DPM oxidation could be insignificant and that the reaction rate of the DPM reaction with an O atom (DPM-O) is about 10 times higher than that of the DPM-O3 reaction in the temperature range between 100 and 320 °C. In this regard, the role of the catalyst comes into play. In fact, it is precisely the presence of a catalytic species that affects the use of the O atom rather than the use of O3 in the oxidation process of the DPM model. In the literature it is reported that, in presence of catalyst, the concentration of O3 remains constant. In fact, the catalyst could promote the oxidation of DPM through Eq. (5) and increase the CO2/CO ratio through the following equations: DPM + CAT ðOÞ ! CO, CO2 + CAT

(5)

CO + CAT ðOÞ ! CO2 + CAT

(6)

Where CAT (O) denotes the active catalyst, which acts as a source of activated oxygen and CAT denotes the reduced catalyst. The reduced catalysts could be regenerated by oxygen-filling reactions using an atom of O and O3 through Eqs. (7), (8), which is considered the main reason for the synergistic response of the plasma and the catalyst [9,95]: CAT + O ! CAT ðOÞ

(7)

CAT + O3 ! CAT ðOÞ + O2

(8)

3 Reactor configurations for soot removal with catalytic “NTP”

Multi-cell DBD reactor

Diesel engine

To vent

Pulsed power source

Current sensor

FIG. 5 Schematic of a multi-cell DBD reactor. Reproduced from S. Yao, H. Zhang, X. Shen, J. Han, Z. Wu, X. Tang, H. Lu, B. Jiang, T. Nozaki, X. Zhang, A novel four-way plasma-catalytic approach for the after-treatment of diesel engine exhausts, Ind. Eng. Chem. Res. 57 (2018) 1159–1168.

As for the voltage applied to the electrodes, it is 5–7 kV. Such reactor thus realized can be considered a SINGLE-CELL DBD. If more cells are connected in parallel, what is called a MULTI-CELL DBD (MCDBD) reactor is obtained. A multi-cell reactor can be built with 20 discharge cells connected in parallel. The number of discharge cells was optimized on the basis of a trade-off between energy efficiency and reactor cost. The choice of creating two types of DBD gives the possibility to test the catalytic activity combined with the plasma on the single cell reactor and to carry out the diesel engine test on the multicell. Below is a diagram of a multi-cell DBD (Fig. 5). Also for this configuration, considering the variable operating parameters such as the catalytic species, temperature, and oxygen amount, it is possible to define DPM oxidation efficiency in terms of [g/kWh]. Often the DBD reactor is the most proposed configuration since DBD can produce high concentrations of reactive oxygen species which could oxidize the carbon PM to CO2 efficiently at lower temperature. Another simplest types of DBD, involves the use of a quartz tube used as the reactor as well as the dielectric barrier, and also a stainless steel rod applied as the highvoltage electrode. The catalyst (e.g. pellets (20–40 mesh, 0.5 g)) was filled in the discharge zone. The stainless steel net wrapped on the outer surface of the quartz tube was employed as the grounding electrode [96]. A possible schematic of this system is shown in Fig. 6. In a DBD configuration it is possible to test the performance of the system in removing PM with and without catalyst in a wide temperature range (from 20 to 200 °C). However, it has been shown that in this temperature range, without the application of NTP, the catalyst would not be able to carry out the PM abatement, thus demonstrating that it is difficult to oxide carbon PM only by the catalytic combustion since oxidation of PM requires a high temperature [96]. However, with the presence of non-thermal plasma (NTP) technologies and heterogeneous catalyst applied in the discharge zone, a significant PM removal efficiency can be observed.

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Mix O2, N2

catalysts High voltage electrode

Grounding electrode

Gas out

FIG. 6 DBD reactor with packed bed catalyst [96].

In particular, literature study reported that, in presence of catalyst it is possible to reach a removal efficiency equal to 85.2% at 20 °C and 94.3% at 200 °C [97]. This result indicates that by using NTP, the reactant molecules can be easily activated and dissociated at ambient temperature. Similarly, over other catalysts, effective carbon PM removal efficiency is obtained as well during combined plasma-catalytic process. The nature of the catalyst plays an important role in the reaction mechanism and in the responsibility of the oxidizing species. This combined plasma-catalytic process is possible due to the fact that various oxygen atoms generated by plasma discharges play an important function in breaking CdC bonds, which results in the oxidation of graphite. These oxygen atoms are the main reactants that can react with carbon PM to convert them into CO and CO2 [97]. In the reaction process, the O2 is converted to O that reacts with O2 to generate O3. The observed synergistic catalytic effect is particularly relevant in the presence of catalysts such as manganese oxide supported on CeO2, because more oxygen can be joined in the redox cycle [98]. The presence of the catalyst in the discharge zone means that the active species generated by the NTP are easily adsorbed and dissociated on the surface of the catalyst. Consequently, it is possible that the radical species reach the surface of the catalyst by actively participating in the reaction [96]. As a DBD configuration, not only tubular, but also batch-type DBD plate reactor is proposed in the literature [95]. Specifically, it is possible to create a DBD reactor as follows: one aluminum plate and two alumina plates. The aluminum plate was inserted between the two alumina plates as one set. Three sets were arranged in parallel with two discharge gaps of 0.5 mm by inserting four alumina spacers. The two alumina plate surfaces at the middle of the three sets were supported with the catalyst powder. The pulsed power supply connected to the system provides a pulsed voltage of a peak value of 12 kV. The schematic configuration it is similar to that described in the Fig. 5. However, in this case it is specified that the PM removal mechanism can consist of two phases: the first phase is the deposition (precipitation) of PM on the electrodes due to plasma discharges (functioning as an electrofilter) and the second phase is oxidation of PM by oxygen atoms (O) generated by plasma discharges [95] PM deposition in the DBD reactor is a key factor in improving PM removal by oxidation, but also the cause of the increased pressure loss due to excess PM deposition. To remove excessively deposited PM, catalysts, particularly transition metal

3 Reactor configurations for soot removal with catalytic “NTP”

oxides, are considerable for promoting oxidation of PM [95,99]. By correlating the rate of catalytic oxidation with the enthalpies of formation per oxygen atom of the catalysts, it was found that the redox catalytic cycles act practically as catalytic mechanisms of the transition metal oxides. The O atoms generated by plasma discharges can play an important role in promoting re-oxidation of the metal under plasma discharge conditions. It has been suggested that the high catalytic activity for the oxidation of PM is due to the balance between the reduction rate and the re-oxidation rate within the redox catalytic cycles [95]. Although the DBD configuration is the one most proposed for soot abatement with catalytic NTP, the Corona Discharge reactor is also used for this application. When we talk about corona discharge we mean a partial breakdown of a gas with a relatively strong electric field that is established between two inhomogeneous electrodes at or near atmospheric pressure. In particular, in this configuration we find the discharge stressed electrode (SE) (coronating), which has a small radius of curvature (e.g. a sharp point or a thin wire), and it is held at a high voltage. The passive electrode (also called noncoronating), present a much larger radius of curvature, (e.g., a flat plate or a cylinder) and it is electrically grounded [100]. The effectiveness of using electrode electric discharges to initiate ignition and stabilize the combustion process of corona discharges at or near atmospheric pressure has been demonstrated in numerous theoretical and experimental studies [101–103]. The configurations commonly adopted to obtain a corona discharge are: (1) pin-to-plate discharge [104], (2) wire-to-plate discharge [104] and (3) carbon-fiber brush discharge [105]. In particular, for soot oxidation the synergetic effects of a pin-to-plate corona plasma and metal oxide catalysts were investigated under diesel exhaust gas conditions of 10% oxygen and temperature in the range 180–350 °C [7]. This reactor configuration comprised of a plate electrode, generally made of stainless-steel mesh and one platinum pin electrode (Fig. 7). The cylindrical Pyrex reactor, which reduces, was used for the catalytic soot oxidation under plasma discharge conditions. The pin and plate electrodes presented a discharge gap of about 15 mm (this value may undergo variations) and they were connected to the negative and positive electrodes of a DC high voltage power supply, respectively. The electrical discharge was ignited by applying a DC high voltage (in the range 0–20 kV) between the positive and negative electrodes of the reactor. Below is a schematic of a “pin to plate” reactor for catalytic non-thermal plasma applied to the soot abatement. With this configuration, literature studies demonstrate that the soot can be removed completely by corona plasma at 250 °C. However, the soot combustion ignition temperature in the absence of plasma is about 600 °C. Combustion at low temperatures is the main reason why plasma is used to remove diesel engine soot. The plasma discharge produces active oxygen species, and it dramatically lowers the soot oxidation temperature in the range of the diesel exhaust gas temperatures of 180–350 °C [7]. In this case, the soot removal efficiency is a function of both temperature and Energy injection (EI). Specifically, it was noted that in the pin to plate configuration it is possible to accelerate the oxidation of the soot by increasing the number of oxidizing species through an increase in energy injection. The higher energy injection [from 3.9 to 7.4 W] produces more reactive species, accelerates the soot oxidation, and depletes the soot more rapidly [106].

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NEGATIVE ELECTRODE

PIN ELECTRODE

366

GAS OUT

MESH ELECTRODE WITH SOOT AND/OR CATALYST

QUARTZ CHIPS

Temperature controller Thermocouple

GAS IN

POSITIVE ELECTRODE

FIG. 7 “Pin to plate” reactor schematic representation for catalytic non-thermal plasma [7].

4. Catalytic species typically proposed for the abatement of soot in NTP reactors From the previous paragraph it emerged that typically, the reactor configuration used for soot abatement with catalytic NTP is DBD, in various forms (cylindrical or plate). The geometry of the reactor is certainly important as it allows to enhance the synergistic effect established between the plasma and the catalyst, but it is also important to identify which are the most efficient catalytic species for this purpose. These are obviously heterogeneous catalysts, sometimes deposited directly on the surfaces of the electrodes (typical case of a DBD plate reactor) or used as a filling material placed inside the DBD at the discharge area. From the analysis of the scientific literature it emerges that it is possible to apply different types of catalytic species, from metal sulfates [93], metal oxides to noble metals sometimes dispersed on alumina. In

4 Abatement of soot in NTP reactors

any case, the role of the catalyst was fundamental in increasing the soot removal efficiency and obtaining optimal CO2 selectivity. For example, the influence of metal sulfate on plasma oxidation of DPM using dielectric barrier discharge (DBD) was investigated [93]. In particular, several metal sulfates were evaluated in terms of DPM oxidation deposited on an alumina plate inserted in the DBD plate configuration (as described in Fig. 3). The DPM (10 mg) was dispersed in an aqueous ethanol, mixed with an aqueous solution of a metal sulfate. The aqueous ethanol containing DPM mixed with the metal sulfate is then uniformly loaded onto the alumina plate within a designated area where the discharge [93] took place. Metal sulfates such as MgSO4, K2SO4, ZnSO4 or CaSO4• resulted in an enhanced energy yield of DPM oxidation. Among these, K2SO4 seems to be the one that guarantees a more effective improvement in the oxidation of DPM with NTP. Very often, once the catalytic species has been identified, experiments are carried out by varying some operating conditions, for example by changing the temperature (which in any case remains in the 150–250 °C range) or by inserting water since during the combustion of diesel it is possible to form water. In the presence of a metal sulfate, the increase in temperature (250 °C) causes beneficial effects on the oxidation of the DPM. This positive effect could be attributed to the enriched oxidative active species at the elevated temperature as might be caused by two reasons: (1) increased electron energy due to the enhanced reduced field intensity (E/n, electric field/gas number density) [107] and (2) ozone decomposition due to activated thermo-chemistry reactions. When steam is presented in the discharge space, OH radicals may contribute to DPM oxidation where OH radicals are mainly produced from the reaction of O (1D) and H2O. According to the literature, a mechanism that leads to the oxidation of DPM in a plasma catalysis system in the presence of metal sulfates could be the following: 1. formation of O from O2 decomposition in an O2 enriched plasma 2. is bulk O diffusion onto a vacancy of sulfate surface 3. migration of the surface oxygen to a place where the oxidation of DPM and surface oxygen reaction occurs 4. is the release of oxidation products, CO and CO2 The role of the catalyst in the NTP reactor is essential if good soot removal is to be achieved. In fact, in the absence of catalyst, the presence of DPM is noted which precipitates on the walls of the electrodes, drastically reducing the efficiency of the process. The presence of the catalyst avoids this phenomenon, thus improving the performance in terms of soot removal. In this regard, one type of catalyst that showed excellent performance was the Au. In particular, it is possible to study the effect of this species by depositing it on alumina pellets placed inside the DBD reactor as in the configuration described above (Fig. 4). With a voltage applied to the system of approximately 5 kV, Au is considered as a suitable catalyst because it has great DPM oxidation ability with both low-temperature (100 °C) and high-temperature plasma processing (250 °C). In particular, the performances obtained in the presence of Au were compared with those of Pt, Ag and Pd. The observed difference between the activity in the presence of Au and those of the other catalysts could be due to the different method of use of the O atom rather than the use of ozone in the oxidation

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process of the DPM. To confirm this hypothesis, it is necessary to measure the concentration of ozone in the system and it was observed that, in the presence of different catalysts, the concentration of ozone at the temperatures tested was almost the same for the different catalysts [108]. Interesting results for the removal efficiency of carbon PM were found in the presence of on MnOx/CeO2 catalysts (Mn loading 5.0 wt%). This catalyst allows to obtain a removal efficiency of 85.2% and 94.3% at 20 °C and 200 °C respectively, at the discharge power of 18.0 W. The removal efficiency of carbon PM increases with Mn loaded, but it reaches a highest value on 5.0% MnOx/CeO2 catalyst. This trend may be attributed to the formation of bulk manganese particles which will decrease catalytic activity when the MnOx content is over 7.5% [108]. Reaction temperature and time greatly affect on plasma removal of PM over 5% MnOx/CeO2 catalyst (better at higher temperatures). This result suggests that manganese oxide supported on CeO2 can enter the ceria lattice and improve the oxygen storage capacity of ceria as well as the mobility of oxygen on the surface of mixed oxides [109]. Interesting is the use of Transition Metal Oxide Catalysts as heterogeneous powder catalysts based on TiO2, ZnO, V2O5, Fe2O3, Co3O4, MnO2 and CuO, deposited on alumina plates used as electrodes in the DBD configuration [95]. In particular, TiO2, ZnO, V2O5, Fe2O3, are catalytically active for the oxidation of the soot and to promote oxidation compared to the use of plasma alone. Thanks to this study it was understood that the catalytic mechanism acts like a redox cycle [95]. The inactivity of Co3O4, MnO2, CuO was understood by evaluating the relationship between the catalytic oxidation rate and the enthalpy of oxide formation. In general, high values of formation enthalpy denote a good oxidative capacity by the oxide but for values that are too high probably the species that have been reduced during the oxidation of the soot are unable to re-oxidize and therefore to support the redox cycle. The best catalytic species is Fe2O3 in which the oxidation and reduction rates are perfectly balanced [95].

5. Soot removal efficiency in the NTP catalytic reactor Once the possible reactor configurations and catalytic species have been defined, an evaluation of the efficiency of the non-thermal catalytic plasma in the removal of the soot is necessary. Defining the efficiency of this process means evaluating not only the% of oxidized DPM, but establishing how long, and above all, with what energy requirement this objective is met. For this reason, generally the efficiency of this process is defined dimensionally as [g/kWh], also considered “energy yield,” or it is possible to calculate the PM conversion [%]. For example, it is possible to define the energy efficiency g/kWh as follows [93]: E¼

m1  m2 Pt

where m1 and m2 in grams are the weights of DPM before and after DBD, respectively. t is the DBD processing time in hours, and P is the power injection in W.

5 Soot removal efficiency in the NTP catalytic reactor

This parameter can be compared both with the temperature of the process or with the% of active catalytic phase used in the reactor. In this way it is possible to define the best performance of the reactor, of the catalyst, but always in relation to the energy required. In other cases, it may be useful to associate the evaluation of selectivity to CO2 with energy efficiency (or also defined oxidation efficiency), which in this case can be defined as [108]: CO2 selctivity ð%Þ ¼

moles of CO2 produced  100 moles of ðCO2 + COÞ produced

Like energy efficiency, CO2 selectivity can also be related to the amount of catalytic species used in the process. In particular, it was observed that, unlike the energy efficiency which is greatly influenced by the amount of catalyst, the CO2 selectivity may not be affected by the amount of active species. This result has been interpreted considering that the CO oxidation process takes place mainly in the gas phase (CO + O ! CO2). However, it has always been verified that most of the CO produced by the oxidation of DPM has been oxidized into CO2 [108]. It has been observed that the soot removal efficiency (SRE) (as below specified), evaluated in a pin to plate reactor (corona discharge) and expressed in [g/kWh], increase with the increase of energy injection (EI ¼ VI) at various gas temperatures in the range of 180–350 °C. This range corresponds to the diesel exhaust gas temperatures. SRE ¼

m  100 EI  t

But why does the SRE improve with increasing temperature? The answer lies in the interaction between the oxygen atoms and the soot. The oxygen atoms are generated by the decomposition of ozone. In fact, ozone formed in the plasma reactor is thermally decomposed to O2 and O radicals at temperatures higher than 200 °C. The O radicals play important roles in the oxidation reaction. The increase in the ozone decomposition rate with temperature as well as interactions between reactive oxygen atoms and soot particles are the reasons why SRE increases with temperature [110,111]. In order to evaluate the catalytic effect of each catalyst on PM oxidation, the PM oxidation rates calculated using the following equation is another method proposed in literature: r¼

MðcÞ r CO + CO2 RT

PM oxidation rate “r” [mgC min1] was defined as oxidized PM weight per minute which was calculated from the generation rate rCO + CO2. where M(C) is molecular weight of carbon [g mol1], R is the gas constant [L atm K1 mol1], T is the temperature in FTIR analysis cell [K]. On these considerations it is useful to make a comparison in terms of types of catalyst, reactor and soot removal efficiency for the different solutions proposed by the literature (Table 1).

369

Table 1 Comparison between the different soot abatement systems with catalytic NTP proposed, by the recent scientific literature.

Bibliographic ref. [93]

NTP technology/ operating conditions DBD Gas: mix of O2, N2 and H2O N2 ¼ 800 mL/min O2 ¼ 200 mL/min Voltage:
7 kV Tgas: 100– 250 °C

Catalyst formulation Metal sulfates Na2SO4 Fe(SO4)3 Al2(SO4)3H2O MgSO4 K2SO4 CaSO42H2O

Experimental setup

Parameters analyzed

Observation

Two soot-coated alumina plates Two stainless steel plates and two alumina spacers

Soot removal efficiency SRE [g/kWh] Emax ¼ 3.8 g*kWh1 with K2SO4 (T ¼ 200 °C, time ¼ 1 h, P* ¼ 4.5 W) *Power injection

– The increase in gas T improves the oxidation of the soot due to the greater presence of active oxidizing species. – The addition of water vapor increases the energy yield of the system thanks to the formation of other oxidizing species (OH). – The catalytic performance of metal sulfides depend on the metal present. – Of those examined only MgSO4, K2SO4, CaSO4 2H2O increase the oxidation of the particles. – The most effective was K2SO4 with a load of 5 wt%

[7]

Corona plasma reactor Voltage: 0–20 kV Power: 4–7.5 W Gas composition: [O2] ¼ 10% in N2 Tgas: 180– 350 °C

Fe2O3 MnOx Co3O4

Pin to plate corona discharge

7.0 g/kWh With MnOx (T ¼ 350 °C EI ¼ 7.4 W) CO2 selectivity ¼68%

[108]

DBD (dielectric barrier discharge) Voltage: 5–6 kV Power: 4.5 W Tgas: 100– 250 °C

Au, Pt, Pd and Ag

DBD configuration in which catalyst coated alumina plates act as electrodes

E ¼ 6.1 g/kWh with Au (P ¼ 4.5 W, time ¼ 1 h, T ¼ 200 °C [O2] ¼ 20%) CO2 selectivity ¼65%

The SRE increases with increasing gas temperature and injection energy (EI ¼ V * I), and there have also been improvements with the addition of NOx and water vapor to the gas feed. SRE and selectivity increase when the catalyst is mixed with the feed gas, favoring the interaction between the soot and the catalytic sites. The best catalysts are MnOx and Fe2O3 at high and low temperature respectively. Oxygen is provided both by the reactive species generated by the plasma and by the catalyst The active phase that has shown the best catalytic performance at both low and high temperatures is Au. It has been observed that the selectivity to CO2 is not influenced by the choice of the noble metal since the oxidation reaction takes place mainly in the gas phase. The Au Continued

Table 1 Comparison between the different soot abatement systems with catalytic NTP proposed, by the recent scientific literature—cont’d

Bibliographic ref.

[112]

NTP technology/ operating conditions

DBD Insulated gate bipolar transistor (IGBT) Gas: [O2] ¼ 0– 5% in Nitrogen feed Power: 9.4 W Voltage: 27 kV

Catalyst formulation

Ag/γAl2O3

Experimental setup

The system consists of a discharge electrode placed in the center of a quartz tube. The second grounding electrode is of the aluminum strip type that wraps the external surface of the pipe

Parameters analyzed

Emax (PM) ¼ 0.92 g/kWh (P ¼ 9.4 W time ¼ 1 h)

Observation is also the best choice because it avoids the accumulation of particulate matter in the plasma reactor. In fact, in the presence of the catalyst, the soot is oxidized with a speed comparable to that of the electrostatic fall of the particles In this study, a catalytic system capable of simultaneously removing NOx and particulate matter was examined. In general, the addition of the catalyst to the plasma reactor made it possible to improve the energy efficiency of removal for both the soot and NOx

[96]

DBD Gas composition [O2] ¼ 21% [N2] ¼ 79% Tgas: 20–200 °C Power: 10–18 W

Al2O3 CeO2 MnOx/ Al2O3 MnOx/CeO2

The reactor consists of a quartz tube and a dielectric barrier. The high voltage electrode is a stainless steel rod placed inside the tube while the grounding electrode is a stainless steel mesh wrapped on the surface external

PM conversion ¼ 85.2% (at T ¼ 20 °C) PM conversion ¼ 94.3% (at T ¼ 200 °C)

[95]

DBD Batch-type Gas composition: [O2] ¼ 10% in N2 Tgas: 200 °C

TiO2 ZnO V2O5 Fe2O3 Co3O4 MnO2 CuO Powder catalysts with which alumina plates have been coated

The reactor consists of an aluminum plate, which acts as an electrode connected to the electrical power generator, interposed between two plates of alumina coated with catalyst

PM oxidation rate r [mg-C min1] in presence of Fe2O3 has been improved approximately 34% in comparison with that without catalyst

In the temperature range examined it was observed that using only the catalyst in the absence of NTP there is no removal of the soot therefore it is necessary to integrate the plasma in a catalytic reactor to operate at such low T. Among the various catalysts examined in this study, the one that showed the greatest removal of PM is MnOx/CeO2 as thanks to this system many more oxygen atoms enter the redox catalytic cycle. This type of system is therefore capable of operating even at ambient temperatures. Out of the 7 metal oxides examined, only 4, in particular TiO2, ZnO, V2O5, Fe2O3, are catalytically active for the oxidation of the soot and promote oxidation compared to the use of plasma alone. Thanks to this study it was understood that the catalytic mechanism acts like a redox cycle. The Continued

Table 1 Comparison between the different soot abatement systems with catalytic NTP proposed, by the recent scientific literature—cont’d

Bibliographic ref.

NTP technology/ operating conditions

Catalyst formulation

Experimental setup

Parameters analyzed

Observation inactivity of Co3O4, MnO2, CuO was understood by evaluating the relationship between the catalytic oxidation rate and the enthalpy of oxide formation. In general, high values of formation enthalpy denotes a good oxidative capacity from part of the oxide but for values that are too high, the species that have been reduced during the oxidation of the soot are probably unable to re-oxidize and therefore to support the redox cycle. The most active species is Fe2O3 in which the oxidation and reduction rates are perfectly balanced

6 Conclusions and future directions

6. Conclusions and future directions In recent years, many soot oxidation catalysts have been investigated, and the most promising catalytic technologies aims at developing stable catalysts that exhibit high mobility of the oxidizing species. The studies have demonstrated that the mobile nature of active sites at solid surfaces allows them to interact with each other through transport phenomena and surface flexibility. Nevertheless, the stability of soot combustion catalysts is fundamental for the application of catalytic materials in DPFs. Important progress has been reached in the development of soot oxidation catalysts, anyway there are still some challenges to develop highly effective soot oxidation catalysts, such as (1) a deep exploration of catalyst deactivation by other components in exhaust (Sulfur, Phosphorous, water vapors) and their possible regeneration during application. In addition, more and more tests of the CDPFs downstream of actual diesel engines are needed. Focusing research in these areas will contribute to the application of highly active soot oxidation catalysts in real conditions. On the catalytic material side, new challenges would be addressed toward the (1) synthesis of multi-component catalysts based on a combinatorial approach, (2) controlled catalyst morphology using novel synthesis techniques for desirable physio-chemical characteristics. All these efforts will lead to the development of advanced soot oxidation catalysts with both high activity and high stability. The coupling of NTP with heterogeneous catalysts has proved to be an interesting solution for the abatement of soot in diesel exhaust gases at low temperatures. From an overview of the latest NTP applications in this field, it has emerged that the most commonly used reactor configuration is the dielectric barrier discharge (DBD), probably because it lends itself better to coupling with the catalyst. In particular, there are several catalytic species that can be used but one of the most interesting aspects is that these species do not necessarily contemplate the use of noble metals alone. For example, the use of transition metal oxides or metal sulfides has made it possible to obtain excellent results in terms of both soot oxidation and CO2 selectivity. In particular the metal oxides act as regenerative sources of activated oxygen and this is correlated with the oxide’s oxygen storage capacities, reducibility and particle sizes. Moreover, the metal oxides oxygen vacancies generated by oxidation of soot are refilled more easily with the reactive species than with molecular oxygen. The presence of the catalyst is essential in order to allow oxidation at low temperatures (100–200 °C) but also to avoid the deposition of the DPM on the walls of the electrodes present in the DBD reactor configurations. Therefore, the coupling of the NTP with the catalyst allows to have a soot removal process with a reaction temperature lower than that of the traditional catalytic combustion method.

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CHAPTER

Advances in chemical looping combustion technology

13

Anuj Joshi⁎, Pinak Mohapatra⁎, Rushikesh Joshi, Sonu Kumar, Ashin Sunny, Zhuo Cheng, Lang Qin, and Liang-Shih Fan William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH, United States

1. Introduction The world demand for energy and commodities is increasing at an unprecedented rate due to plethora of factors such as urbanization and better quality of life aspirations. However, this demand has increased utilization of fossil fuels which in turn has led to increased CO2 emissions [1,2]. Renewable energy sources are emerging and gradually replacing fossil fuel usage. However, the high initial cost of installation, the availability and stability of power supplies hurdle the scale-up utilization of renewable energy [3,4]. Moreover, treaties such as the Paris Agreement have put limitations on total CO2 emissions, restricting fossil fuel deployment [1,5]. Thus, there is a need for a technology and/or a process that can effectively use/replace fossil fuels while reducing CO2 emissions until renewable energy sources completely replace fossil fuels. Chemical looping is one such technology that has the potential to replace the current fossil fuel processing technologies as it achieves de-carbonization through an effective CO2 mitigation strategy. The technology directly tackles the CO2 emission problem in power generation by providing a high-purity sequestration ready CO2 stream. Its versatile nature enables conversion of hydrocarbon feedstock into electricity and CO2 through chemical looping combustion (CLC) scheme, and/or value-added chemicals through chemical looping reforming scheme [6,7]. Moreover, its modular nature allows it to be retrofitted to renewable energy-based structure, thus allowing production of chemicals through hydrocarbon feedstock in an economic and sustainable manner. The chemical looping technology was conceptualized almost 120 years ago and has been demonstrated at commercial, pilot, and sub-pilot plant scale depending on ⁎

These authors contributed equally to this work.

Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00003-5 Copyright # 2023 Elsevier Inc. All rights reserved.

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the application until recently [8]. The reaction scheme involves breaking the reaction into supplementary reactions facilitated by solid intermediates that oscillate between their reacted and regenerated state [6]. These solid intermediates are termed as “chemical looping carriers” and can be metal oxides, metal nitrides, metal sulfides, etc. depending on the reaction involved [9]. This technology can be used for many applications including but not limited to electricity production through fuel combustion, H2 production, H2S splitting, NH3 production and alkane dehydrogenation [9,10]. As the reaction is split into multiple sub-reactions, inherent product separation is achieved, and each sub-reaction can be optimized to achieve the maximum possible thermodynamic yield. Chemical looping combustion is an innovative fuel conversion technology for electricity generation and is illustrated in Fig. 1. As mentioned earlier, CLC inherently solves the CO2 capture issue since a pure CO2 stream is obtained as a byproduct after the water condensation step. In CLC, the hydrocarbon fuel reacts with a metal oxide (MOx) based oxygen carrier in the reducer reactor to form CO2 and H2O (Eq. 1). In this reactor denoted as reducer, the metal oxide donates its lattice oxygen to form partially reduced metal oxide (MOy), after which it is transferred to the combustor wherein it reacts with oxygen present in air to regenerate back to MOx (Eq. 2) thereby completing the solid loop Reducer reaction : Cm Hn + MOx ! CO2 + H2 O + MOy

(1)

Combustor reaction : MOy + O2 ! MOx

(2)

Overall reaction : Cm Hn + O2 ! CO2 + H2 O

(3)

The overall reaction remains identical to hydrocarbon combustion (Eq. 3) however herein a pure CO2 stream is obtained from reducer after the water condensation step that can be directly sent for sequestration Thus, chemical looping combustion eliminates typical challenges of conventional hydrocarbon combustion technologies such as post combustion CO2 capture and requirement of air separation unit (ASU). This chapter will discuss chemical looping combustion applications— specifically, electricity generation and H2 production. Moreover, this chapter delves

FIG. 1 Schematic of two reactor chemical looping combustion.

2 An overview of the latest chemical looping platforms

into the three fundamental facets of chemical looping, namely oxygen carrier development, reactor design, and process simulation and analysis. The aim is to provide the reader an overview of current progress in chemical looping combustion based on recent development and literature reviews [11–14]. Moreover, an effort has been made to provide useful insights into what research is required in the three fundamental facets in order to further develop this technology. Specifically, distinction between modes of chemical looping operation based on product requirement are analyzed followed by a brief discussion on chemical looping carriers utilized by each mode along with their underlying principles. The role of reactor design and process simulations in improving product yields and economic gains is also discussed.

2. An overview of the latest chemical looping platforms The current industry demands an efficient process along with flexibility in terms of operation depending on the product demand and supply of the raw materials. Chemical looping through its oxygen transfer mechanism offers a high degree of flexibility in terms of the operation, product requirement, and raw material availability. The CLC operation involves the use of two reactors, i.e., reducer and combustor as shown earlier in Fig. 1. The metal oxide reduction is generally endothermic depending on the fuel while the regeneration by air oxidation is exothermic. However, the net reaction of the system is exothermic on account of it being identical to single step combustion. Thus, heat released in the combustor can be utilized for electricity generation, which is the principal product of any CLC system. Moreover, the reducer reactor offers a great deal of versatility in terms of the fuels it can handle as it can process not only gaseous fuels, but also solid fuels such as coal, biomass, petcoke, etc. [15,16]. Employing a chemical looping scheme for combustion and subsequent electricity generation has numerous advantages over conventional technologies. However, the oxygen mediation occurring in chemical looping system can be explored to produce valuable products such as hydrogen and syngas by adding another reactor to the tworeactor scheme as shown in Fig. 2. The three-reactor system consists of another reactor called oxidizer, which is placed between the reducer and combustor. After the fuel combustion in the reducer, instead of sending the fully reduced carrier to the combustor, it can be partially oxidized using steam and/or CO2 in the oxidizer. This allows for combustion chemistry to be used for production of chemicals, a feature absent in conventional combustion technologies. If steam is used in the oxidizer, a high purity hydrogen stream is obtained, and the overall scheme is termed as chemical looping hydrogen generation (CLHG). Moreover, the amount of oxidizing gas going into the oxidizer can be optimized such that co-production of both chemicals and electricity can be achieved. Thus, chemical looping provides a unique benefit of utilizing fuel combustion to produce electricity, H2, syngas or carbon monoxide based on the demand. This chapter focuses specifically on CLHG as part of three

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FIG. 2 Schematic of three reactor chemical looping.

reactor scheme, but the concepts discussed can be applied to syngas or carbon monoxide production as well.

3. Material development Carrier development for chemical looping processes follows an iterative approach involving theoretical studies, small lab scale, bench scale, sub pilot and pilot scale experiments to assess the performance. Since the reaction conditions involve high temperatures in the range of 800 °C to 1000 °C and high pressures, appropriate formulation of carrier is crucial for it to endure significant physical and chemical stresses. Moreover, for CLHG applications an additional criterial of steam oxidation kinetics also needs to be considered during development of carrier. The final selection of carrier can be realized after assessment of design attributes such as oxygen carrying capacity (OCC), reactivity, selectivity, mechanical strength, attrition resistance, environmental impact, and cost. The first step in development of carrier is analyzing the redox thermodynamics in conjunction with the raw material and synthesis cost. The thermodynamic study is critical as it evaluates the oxidation and reduction feasibility in the temperature range of operation. This determines the carrier’s suitability for the desired reaction, its reactivity with fuel, and its regenerability. In

3 Material development

addition, at this stage the economic analysis is also necessary to justify the overall capital and operating cost of the process. Based on the availability, oxygen carriers are broadly divided into two groups, i.e., synthetic carriers and nature-based carriers. Nature based carriers are naturally occurring ores with minor modifications and are usually inexpensive. Besides, there is a significant cost savings as the ores require minimal pretreatment to be employed as oxygen carriers. In contrast, synthetic carriers require extensive treatment and formulation steps, resulting in higher cost though offer excellent reactivity and recyclability. Second step of development is to investigate the activity and selectivity of the carrier toward the desired products. This can be achieved by atomistic level Density Functional Theory (DFT) simulations. DFT helps investigate the crystal structure and oxygen vacancies of oxygen carrier materials and reveals the underlying reaction mechanism. Further, it also aids in dopant screening to enhance the reactivity of carriers for any chemical looping system [17–21]. In combustion processes, during reduction of carriers, the oxygen ion diffuses toward surface to react with the fuel thereby creating an oxygen vacancy. The formation of vacancy affects electronic properties of carrier and has an impact on the reaction behavior. Therefore, it is crucial to probe the energetics of reaction, ionic diffusion, and crystal structure of carrier due to vacancy formation. Once the carrier’s thermodynamic, economic, and kinetic restraints are overcome, the next step is conducting long-term redox testing while ensuring the carrier maintain its high mechanical strength and attrition resistance. This is important as mentioned earlier, the carrier has to endure chemical and physical stresses in the chemical looping system. Moreover, this testing needs to be done at different operational scales since the stresses on carrier differ as the scale increases. Attaining good attrition resistance is important to reduce particle makeup which decreases the overall operating cost. Ryden et al. developed a customized jet cup experiment to measure attrition resistance of several carriers used in chemical looping operation at Chalmer University of Technology [22]. They reported that crushing strength index and attrition resistance couldn’t be directly corelated, however a high crushing strength of above 2 N showcased higher attrition resistance and reported acceptable for CLC. Important to outline, the attrition resistance changed after multiple redox changes and was reported a function of the calcination temperature for some of the carriers described in the study. Addition of support also plays a key role in increasing the mechanical strength of the carrier [23]. Researchers have also investigated mesoporous supports to improve the reactivity of oxygen carriers however, challenges with respect to strength and attrition have yet to be examined [24,25,p. 100]. Use of advanced characterization techniques such as X-ray diffraction, scanning electron microscopy and transmission electron microscopy can provide information of carrier morphology pre- and post-reaction. This can help further improve the phase stability, reactivity, and mechanical strength. The steps outlined above are general principles for carrier development and are usually carried out in an iterative manner. The following sections will discuss some recent developments of carrier for both CLC and CLHG application and are intended to serve as the guidelines for formulating new carriers.

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3.1 Materials for chemical looping combustion (CLC) Two reactor CLC is an energy efficient alternative to the conventional catalytic combustion processes. It is classified as a type of oxy-fuel combustion where there is no direct contact of fuel and gaseous oxygen source, i.e., generally air. In this route, the indirect transfer of oxygen from the oxidizing gas to the fuel is facilitated through a solid oxygen carrier. As mentioned earlier, the oxygen carrier is the most important aspect of CLC and its design attributes such as activity, recyclability, strength, environmental impacts, and physical properties are critical in determining the success of the process. Oxygen carrier choice may vary depending on the fuel to be processed since they follow slightly different reaction mechanism for solid and gas fuel as illustrated in Fig. 3. Nevertheless, the key attributes concerning carrier development remain same irrespective of type of fuel processed. Until now more than 2000 carriers have been investigated, primarily composed of transition metal oxides, owing to their excellent redox characteristics, high strength and resistant to high temperature and pressure operations. Majority of them have focused on Iron (Fe), Copper (Cu), Manganese (Mn), and Nickel (Ni). A brief overview of the findings relating to these metal oxides as CLC carriers is discussed next.

3.1.1 Iron-based oxygen carriers Iron oxide has been studied widely by several researchers on account of it being cheap, good OCC and reactivity. Nature based ores such as Ilmenite or Hematite have received most attention. Ilmenite is an ore of iron and titanium with a chemical formula FeTiO3. This ore’s characteristics are supplemented by the presence of TiO2 in the matrix, which acts as a support and provides thermal stability during redox operation. It is known for its nontoxic nature, low cost and high strength.

CO2 H2O

H2O

CO2 H2O

H2O

CO2 H2O

CO2

Oxygen-Carrier Char

Volatiles CO H2

Volatiles Oxygen-Carrier CO H2

Coal

H2O

Syngas

Syngas-CLC (gas fuel)

O2

Char Coal

CO2 Oxygen-Carrier

H2O and/or CO2

CO2

iG-CLC (solid fuel)

CLOU (solid fuel)

FIG. 3 Combustion reaction mechanism for solid and gas fuels [26].

3 Material development

The ore has been tested for both solid and gas fuel. Leion et al. tested the feasibility of ilmenite for CLC using syngas (50% H2, 50% CO) as fuel in a laboratory fluidized bed reactor setup. The carrier maintained its reactivity even after 37 cycles. The oxidation produced Fe2TiO5 + TiO2 with intermediate of Fe2O3 or Fe2O3TiO2, while the reduction with syngas produced ilmenite [27,28]. However, the carrier showcased an inferior performance when CH4 was used as fuel as most of the CH4 passed through the fluidized bed without reacting due to poor reactivity. Syngas on the other hand was found to be very reactive, with most of the CO being converted to CO2. The fluidization properties and strength of the carrier were also reported to be acceptable for CLC application. During the initial redox cycles, the carrier strength generally decreases due to the mechanical stresses in the reactor, especially in fluidized and moving bed reactors. Decrease in strength in initial cycles is generally accompanied by an increase in porosity and become stable thereafter. Cuadrat et al. also studied the feasibility of ilmenite for the CLC by performing 100 cycles using syngas as the reactant in a fluidized reactor [29]. They reported an appearance of an Fe-enriched external layer on the carrier surface after 100 cycles due to the outward diffusion of Fe. Consequently, this resulted in a decrease in OCC due to the phase segregation between Fe and the support TiO2. However, the fluidization properties and attrition values were found acceptable. Further, they also tested it for the solid fuel coal, where they investigated effect of coal size and temperature of reactor. It was reported the gasification and combustion reactions were favored at higher temperatures with gasification having a minor dependence on coal particle size [30]. Strohle et al. studied CLC using hard coal in a bigger scale of 1 MWth pilot plant. Upon introducing the coal, it led to its gasification after which ilmenite carrier was reduced by the gasified products leading to the formation of gaseous products with approximately 27% oxygen demand [31,32]. Operational issues such as char loss, was reported leading to a lower reduction of ilmenite in the reducer and entrainment of coal particles. Pulverized coal was suggested to reduce the char loss. Fan et al. used pulverized coal as fuel to test CLC in a 250 and 25 kW pilot plants. They operated using a countercurrent moving bed reducer configuration where better solids conversion was observed when compared to fluidized beds. The coal conversion was reported around 96% with CO2 selectivity of around 97% at the reducer outlet. Using pulverized coal also resulted in a low carbon carryover to oxidizer (less than 2%) [16,33]. The unique moving bed mode has also been studied at a bigger scale, while utilizing syngas as the feed. Apart from ilmenite, researchers have also explored other low-cost iron oxide-based carriers such as red mud containing 30– 70% Fe2O3, industrial wastes containing 97.43% Fe2O3, pyrite cider containing 65.5% Fe2O3.These alternatives contained some inert supports like Al2O3, TiO2, SiO2 which provided thermal stability. In addition, group IA and IIA alkali metal oxides were found in small quantities that enhanced fuel reactivity by imparting catalytic activity [34]. Nonetheless, they exhibited issues related to their strength and redox cycle stability over the extended testing. Comprehensive research is needed to explore better understanding of these cheaper alternatives.

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3.1.2 Copper-based oxygen carriers Cu-based carriers work differently compared to most other transition metal oxides. Some of salient features of copper are: (1) Second cheapest option after iron. (2) High OCC. (3) Both reduction and oxidation reactions for Cu based carriers are exothermic. (4) Exhibit chemical looping oxygen uncoupling (CLOU) characteristics. However, one of the major drawbacks of copper is its low melting point compared to other metals such as Fe, Ni and Mn. Consequently, most of the CLC experiments with Cu-based carriers are carried at or below 800°C to avoid CuO decomposition to Cu2O resulting in a loss of OCC. Adanez et al. tested 40–80% Cu oxides on several supports such as Al2O3, sepiolite, TiO2, SiO2, ZrO2 at different calcination temperatures. CH4 was employed as the fuel in Thermogravimetric analyzer (TGA) setup for performance comparison study [35]. The crushing strength of Cu based carriers were reported high when sintering was carried at lower temperatures of 950 °C and paired with SiO2 or TiO2. Also, it was reported the strength increased with an increase in calcination temperature however Cu carriers were limited by the low melting point of copper. The SiO2 or TiO2 supports performed well in terms of reactivity too. Diego et al. further investigated three synthesis methods for the Cu-based carriers, i.e., mechanical mixing, coprecipitation and impregnation [36, p. 1749-175]. The samples were subjected to both CH4 and syngas as feed and it was found the CH4 exhibited lower reaction rates compared to syngas. Moreover, the samples prepared by wet impregnation with SiO2 and TiO2 binders exhibited best reactivity and crushing strength in the multicycle TGA tests. Adanez et al. also tested CLC in a 10 kW prototype involving CuO impregnated on Al2O3 with CH4 as fuel [37,p. 10]. The prototype involved two interconnected fluidized bed reactors that were operated for 200 h. No operational issues such as coking, or agglomeration were reported. Chuang et al. explored CO as reactant to investigate different compositions of CuO-Al2O3 employing different synthesis techniques. They found co-precipitation method performed superior as compared to mechanical mixing or wet impregnation as the latter led to agglomeration issues due to poor CuO dispersion. Moreover, it was found the pH influenced the OCC of the carriers, and a higher pH led to a higher strength of the carrier. Forero et al. studied syngas as fuel at a bigger scale of 500 W system designed and built at the Instituto de Carboquı´mica (ICB-CSIC). The carrier used was prepared by impregnation method and didn’t exhibit any operational issue of coking, attrition, or agglomeration in the 40 h of testing [38]. γ-Al2O3 was used as binder in the test which transformed to α-Al2O3 at high temperature and fused with CuO to form CuAl2O4. However, this didn’t significantly affect the reactivity across cycles due to similar reducible behavior of CuO and CuAl2O4. Different syngas compositions were tested with feed ratios of CO/H2 ¼ 1 and CO/ H2 ¼ 3, wherein it was observed that the former had higher combustion efficiency. Nevertheless, when CO was present in higher quantity, the combustion efficiency decreased slightly as it was found that the WGS reaction played a key role and consumed excess CO to produce CO2. Cabello et al. performed long term testing of Cubased carrier impregnated on a commercial alumina to examine its applicability for CLC at an industrial scale [39]. The 500 W system at ICB-CSIC was used for the

3 Material development

study and CH4 was the fuel source. The commercial alumina was found to maintain its reaction rate after 60 h of testing. Carrier’s attrition rate was found to decrease rapidly over first few hours before stabilizing at 0.02% h1. According to the authors, this rate corresponds to 5000 h of particle lifetime. Combustion efficiency was also reported to reach near 100% at an oxygen carrier to fuel ratio of 1.5–2. Yan et al. explored the bimetallic Cu-based carriers where the Cu was mixed with other transition metals such as Mn, Fe, Co, and Ni to understand its synergism [40]. Four compositions 80Cu20Mn, 40Cu60Fe, 60Cu40Co and 60Cu40Ni were tested in a fixed bed reactor with CO as fuel at 950 °C. All carriers maintained their OCC for 20 cycles except 60Cu40Co. However, the fuel conversion decreased significantly for all carriers except 80Cu20Mn due to sintering of solids surface concluding Mn addition was beneficial. In summary, the Cu-based have been reported promising for CLC owing to its low cost and high OCC.

3.1.3 Manganese-based oxygen carriers Manganese oxide-based carriers have received attention due to their CLOU ability. These carriers are also relatively cheap, though expensive than iron and copper. Besides, these have been reported to have high OCC and are environmentally benign. In an early study, Cho et al. compared Fe, Ni, Cu and Mn oxide carriers supported on Al2O3 for the CLC [41]. Two interconnected fluidized bed reactors were used for assessment with CH4 as fuel at 950 °C for all carriers except 850 °C for Cu. It was revealed in this study that Mn based carriers performed poorly as compared to carriers. The fresh carrier phase (Mn3O4, MnO2, MnAl2O4) reduced to (MnO, MnAl2O4) with MnAl2O4 phase being an inactive phase during redox cycle. The solids conversion was revealed to be lower than the theoretical value due to the low porosity of carriers attributed to sintering at high temperature of 1300 °C which led to low porosity. Crushing strength was found better than Ni but was inferior to Febased carriers. The study concluded that Mn-based carrier was not suitable for CLC unless more modifications are carried out. Exploring the feasibility of Mn oxides carrier further, Abad et al. tested CLC in a 300 W fluidized bed reactors setup [42]. Herein, the carrier was supported on magnesium stabilized zirconia (Mn3O4/MgZrO2) and tests were carried at different temperatures ranging from 1073 to 1223 K. Low attrition and no agglomeration or deactivation of carrier was observed during the 70 h of combustion experiment; however, particle loss was reported during first hour of operation. Syngas as fuel performed better than CH4, reaching near 100% combustion efficiency while the CH4 performed better at elevated temperatures and when a low fuel to carrier ratio was employed. This operation revealed Mn3O4/Mg-ZrO2 particles sintered at 1423 K was acceptable for CLC. Shulman et al. investigated mixture of Mn oxides with other transition metals and SiO2 as support, synthesized using freeze granulation method. Objective of study was to explore the CLOU behavior of the carriers at different temperatures with CH4 as fuel. Results concluded that Mn/Fe carriers synthesized at 1100 °C maintained reactivity in terms of CH4 conversion and crushing strength after long term testing. CLOU increased at elevated temperature with maximum uncoupling rate observed at 900 °C for the

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Mn/Fe and Mn/Ni carriers. Mn/Fe carrier performed best, leading to high CH4 conversion and gas yield of 0.95. The study emphasizes the CLOU property of Mn-based carriers for CLC applications. Linderholm et al. tested manganese ore in a 10 kW unit with pet coke as the solid fuel [43]. The unit comprised interconnected fluidized bed reactors operated at 970 °C where the ore cycled between Mn3O4 and MnO phase although it was reported to lack CLOU properties at 970 °C. Interestingly, Mn2O3/Mn3O4 exhibited CLOU behavior at 800 °C however the temperature is low when considering the industrial relevance of CLC. Though this limitation can be overcome by mixing Mn with Fe [43 (p. 808-822),44–46]. Expanding on this idea, Bhavsar et al. evaluated Fe/Mn based mono and mixed metallic oxygen carriers with CeO2 as support (MnxFe1x-CeO2) using CH4 as fuel in the TGA reactor and fixed bed setup [47]. Inclusion of CeO2 imparted phase and redox stability for all compositions of Fe/Mn. Pure Mn-CeO2 showed higher reactivity than Fe-CeO2 (Fe2O3/Fe3O4  11% vs Mn3O4/MnO  22%). For bimetallic carriers, high Fe concentrated carriers led to dealloying, leading to loss of synergistic effect of both metals during reduction. However, the Mn rich carriers performed superior to Mn-CeO2 in both TGA and fixed bed. The strength of carriers should be examined to explore its applicability for scale up using the fluidized bed or moving bed reactors. Mei et al. studied feasibility of Mn minerals using gaseous fuels CH4 and syngas [48]. The mineral carriers showed lower reactivity with CH4 as compared to syngas. Reactivity decreased in the first 10 cycles, thereafter, becoming stable. The manganese minerals MnSA and MnGBHNE from South Africa and Gabon were reported suitable for CLC based on attrition resistance and reactivity performance. Further, the mineral carriers were analyzed with solid fuel bituminous coal in a temperature range of 900–1000 °C [49]. The minerals showed higher gasification rates than ilmenite during first few cycles due to the catalytic activity imparted by K, Na, and Ca present in minerals like the low-cost iron oxide carriers such as red mud, industrial wastes mentioned earlier However, the mineral carriers did not sustain high activity and rate decreased after a few cycles because of loss of these elements. MnGBHNE exhibited 1.5 times higher gasification rate than MnSA and Ilmenite after prolonged testing. The study estimated a 99% CO2 capture efficiency at 1000 °C with MnGBHNE at 300 kg/MWth. Arjmand et al. also explored different manganese ores employing solid fuels Mexican petroleum coke and Swedish wood char. They also observed an enhanced rate of gasification due to the presence of alkali elements as impurities. It was concluded the Mn ores demonstrated higher reactivity than ilmenite toward gasification product CO and H2. CLOU behavior of these ores were also studied, however they performed poorly after first few cycles.

3.1.4 Nickel-based oxygen carriers Ni based carriers in general have a high affinity toward carbonaceous fuels however, Ni is an expensive metal and is also toxic in nature [50]. Similar to copper, both reduction and oxidation with NiO carriers are exothermic when syngas is used as fuel, however the reduction reaction is endothermic when CH4 is used as fuel. NiO interaction with supports has been widely studied in literature since many

3 Material development

supports react with NiO to form unreactive phases that result in poor reactivity of carriers over extended redox cycles. Ishida et al. reported NiO particles supported on YSZ (Yttria-stabilized zirconia; stabilized by addition of 8% Y2O3, NiO/YSZ (weight ratio of 3:2)) showed excellent properties for CLC. The carrier showcased good oxidation rate, solids conversion and physical strength when tested in a TGA apparatus with syngas as fuel (reduction at 600 °C and oxidation at 1000 °C). Pure NiO and Fe2O3/YSZ performance were compared where the reduction rates for all three carriers were acceptable, however pure NiO and Fe2O3 showed very slow oxidation rates rendering them impractical. This diminished performance was attributed to the decrease of oxygen permeability resulting from particle size reduction for pure NiO and cracks formation in Fe2O3 particles. On other hand, the YSZ supported sample exhibited high permeability thereby enhancing oxygen diffusion and reaction rate. Nonetheless, this result validates that a support is pivotal for NiO-based carriers. The mechanical strength of YSZ carrier was also found acceptable. A process estimation revealed an increase in thermal efficiency with CO2 emission rate of 0.33 kg/kWh [51]. Carbon deposition was observed initially which was later avoided by sending small amount of steam with fuel. The carrier was labeled acceptable for H2 fueled CLC integrated with gas turbine cycle [52]. Exploring NiO further, Jin et al. investigated spinel structured NiAl2O4 as a support material for NiO and compared it with YSZ [53]. NiO/NiAl2O4 exhibited higher strength, faster redox kinetics and regenerability as compared to NiO/YSZ. Additionally, NiAl2O4 is 20% cheaper than YSZ which ratifies its applicability better. Idea of using NiAl2O4 stemmed when Al2O3 was used as binder, it led to formation of inert NiAl2O4 during calcination, thereby reducing effective OCC. Therefore, the stable NiAl2O4 was explored as binder with excess Ni at NiO:NiAl2O4 ¼ 6:4, ensuing superior performance. A mixture of CoO and NiO at equimolar ratio supported on YSZ (NiO-CoO/YSZ) was also investigated by Jin and colleagues [54]. The bimetallic mixture showed lower reaction rates compared to NiO/YSZ due to the formation of NiCoO2 which decreased driving force of reaction. However, the combination exhibited superior resistance to carbon deposition due to synergistic effect of Ni and Co. It also performed excellent in regenerability and strength scale. In another study, performance of NiO-CoO/YSZ and NiO/NiAl2O4 employing CH4 and coal gas as fuel was assessed [55]. Interestingly, NiO/NiAl2O4 was reported to show higher reduction activity compared to the bimetallic carrier at a lower temperature with better selectivity toward combustion. NiO-CoO is revealed to catalyze methanation and WGS (water gas shift) reaction thus affecting reduction. Besides, coal gas was found better than natural gas for CLC owing to its higher exothermicity of overall process. In a separate comparison study of several metal oxides involving Fe, Ni, Cu and Mn embedded on Al2O3, NiO exhibited highest reduction rate but performed poorly in strength tests [41]. Formation of unreactive phase NiAl2O4 is reported here too. Probing further, Johansson and group studied bimetallic oxide mixture of iron and nickel oxide [56]. Incorporating small amount of NiO (3 wt%) in the iron oxide carrier emanated superior performance. The carrier produced twice the amount of CO2 during reduction compared to individual oxides. This synergistic effect was ascribed to the catalytic activity

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of Ni that accelerated the CH4 reforming to syngas (CO and H2) which consequently reacted at a faster rate with the iron oxide to form CO2 and H2O. The carrier also avoided coking and defluidization. Corbella et al. explored rutile (TiO2) as a support while varying NiO concentration [57]. Upon testing in a fixed bed setup, it was deduced that the carrier’s reactivity did not depend on Ni loading. Surprisingly, the support rutile was found as additional oxygen source that changed phase during reduction after donating its oxygen. Raman spectroscopy of reduced carrier revealed graphitic carbon deposition due to methane thermal decomposition fueled by nickel’s catalytic activity. High solids reduction rate was observed, apparent by the sharp decrease in the CO2 molar fraction curve at the reducer outlet. Nevertheless, the reactive TiO2 support with NiO requires deeper understanding. Further, a 20-cycle test at 900 °C was performed where a slight performance decay and significant increase of porosity was observed, thereby risking cracks formation leading to loss of strength in long term. Cho et al. extensively studied the carbon formation for NiO carrier at different temperatures in a fluidized bed reactor setup [58]. Minor carbon deposition was observed up until 80% of solids conversion after which the deposition rate accelerated significantly. Regardless, the real systems are operated at high fuel conversion regime where the oxygen is in excess, so the carbon formation would not be an issue. Siwardane and group studied bentonite as a support for NiO using synthesis gas in a TGA setup [59]. Reaction rate depended on the particle size with smaller size showing higher reactivity likely due to lower diffusion resistance. Enhanced fuel reactivity was recorded at higher pressures due to faster kinetics. SEM analysis concluded no noticeable change in morphology for smaller particles tested in the temperature range of 700–800 °C. A spinel support MgAl2O4 was studied by Johansson et al. which showed high CH4 conversions and attrition resistance in a fluidized bed setup. Common conclusions reported for NiO are that it requires a support to enhance its strength and redox stability and most importantly the support should be inert and non-reactive to NiO. Besides, operating Ni based carrier in a controlled high fuel conversion regime will ensue no carbon deposition. The studies discussed above showcase the intricacies in carrier development and outlines the role of appropriate support selection and carrier characterization. The key findings of the studies are tabulated in Table 1.

3.2 Materials for chemical looping hydrogen generation (CLHG) Explained in Section 2, CLC scheme can be utilized for H2 production by addition of another reactor. Similar to CLC, the performance of the carrier is among the most critical aspects of the performance of a chemical looping system. For the CLHG scheme, the carrier must have good kinetics in addition to feasible thermodynamics toward steam oxidation. In addition, the fuel used for CLHG is usually coal, natural gas, or syngas. Hence, it is also essential for the material to have good resistance against carbon deposition. Otherwise, the carbon deposited on the carrier particles could go to the steam oxidizer and form CO2 and CO, thus reducing the purity of hydrogen produced. Several supports have shown to improve the oxygen mobility

Table 1 Key findings of several oxygen carriers for CLC. Fuel used

Carrier used

CH4 Syngas (1:1 CO:H2)

FeTiO3

Coal

Iron based oxygen carrier

Bituminous coal

Ilmenite Manganese ore

Natural gas: C1.14H4.25O0.01N0.005

Fe/Mn-synthetic

Mixtures of CH4, CO, CO2, H2, H2O and N2

FeTiO3

Hard coal Blend of hard coal and torrefied biomass CH4

Ilmenite Iron ore

CH4

C7R3: Cu ore with red mud (30 wt%) CuO/Al2O3

CH4

Cu14γAl_Commercial

CO

80Cu20Mn

Reactor used

Temperature in °C

Fluidized bed reactor Moving bed reactor Fluidized bed reactor Fluidized bed reactor Fluidized bed reactor Fluidized bed reactor Fixed bed reactor Fluidized bed reactor Fluidized bed reactor Fixed bed reactor

970 975

Performance data

Reference

y ¼ xCO2/(xCO2 + xCO + xCH4) y ¼ 0.5 (methane) y ¼ 1 (syngas) CO2 purity ¼ 99.7% Fuel conversion ¼ 97.9%

[27]

970

Carbon efficiency 98%

[43]

1000

Combustion efficiency 96%

[46]

900

–

[30]

880–1500

–

[32]

900

[60]

800

CO2 selectivity ¼ 95% Fuel selectivity ¼ 86% Fuel conversion ¼ 100%

[37,p. 10]

800

Combustion efficiency 100%

[39]

950

Carbon conversion 100%

[40]

850

[16]

Continued

Table 1 Key findings of several oxygen carriers for CLC—cont’d Reactor used

Temperature in °C

Cu-based oxygen carrier

Fluidized bed reactor

Syngas Natural gas

Mn3O4/Mg-ZrO2

CH4

41M8F1100: 80Mn3O4/ 20Fe2O3

Syngas CH4

Fe2O3:Mn3O4-Mn:Fe of 2:1

CH4

MnxFe1x—CeO2: x ¼ 0.8

H2, CO, and CH4

H2, CO and CH4 Bituminous coal char

MnSA: Mn-39.8%, Fe14.6% MnGBHNE: Mn-46.6%, Fe-5.1% MnGBHNE: Mn-46.6%, Fe-5.1%

Fluidized bed reactor Fluidized bed reactor Fluidized bed reactor Fixed bed reactor Fluidized bed reactor

Fuel reactor— 800 Air reactor— 1000 800–1000

CH4

N6AN: 60NiO-40NiAl2O4

Natural gas C1.14H4.25O0.01N0.005

NiO based particles and FeTiO3 mixed oxide N6AM1400: 60 wt% NiO supported on MgAl2O4

Fuel used

Carrier used

Syngas

Fluidized bed reactor Fluidized bed reactor Fluidized bed reactor

Performance data

Reference

Combustion efficiency 99%

[38]

Combustion efficiency >99.9% for syngas, 99% for natural gas

[42,p. 300]

900

Gas yield ¼ 0.96 at mass conversion ¼ 0.99

[61]

950

–

[44]

900

–

[47]

950

–

[48]

900

–

[49]

950

Rate of mass conversion ¼ 0.066 min1, for mass conversion in the interval 0.863–0.98.

[41]

900

Combustion ¼ 90%

[62]

3 Material development

in the oxygen carrier that can help in resisting carbon deposition. For these reasons, several materials in combination with different supports have been studied by researchers across the globe. The most recent work on carrier development for CLHG predominantly utilizes Fe as the primary component. Fan et al. have successfully demonstrated high purity hydrogen generation in a 25 kWth subpilot and 250 kWth pilot CLHG scheme using Fe-based oxygen carriers [63,64,p. 250]. Fe has the ability to exist in multiple oxidation states in form of Fe, FeO, Fe3O4 and Fe2O3. In addition, its shows good activity toward steam oxidation, has low cost, and is nontoxic. Several inert supports have been tested with Fe to improve its chemical and mechanical properties. Besides, the effect of various dopants, including rare earth metals like Yttrium (Y), Samarium (Sm), Gadolinium (Gd), and Lanthanum (La), have also been studied. These dopants help tailor the properties of the oxygen carrier as per the process requirements. Different metals like Nickel (Ni), Copper (Cu), and Cobalt (Co) have also been added to Fe-based oxygen carriers to form multi-metal oxygen carriers with superior properties. These multi-metallic carriers show superior reactivity and stability properties due to various kinds of synergistic effects between the active components. Studies on the bulk Fe carrier show that although Fe possess a good activity toward CLHG, it has a poor stability across the redox cycles. A study by Li et al. tested unsupported Fe2O3 for H2 production using K-10 char as the fuel [65]. An H2 yield of 1000 mL g1 of K-10 char at 1073 K was achieved. The SEM and BET analysis revealed slight sintering of carriers. Moreover, the sintering can worsen with increase in temperature, making use of supports and binder mandatory. Hence, many researchers have studied several inert metal oxides as supports to improve the reactivity and stability of Fe2O3 for CLHG. Xiang et al. tested the effect of using CeO2, ZrO2, Al2O3 as supports for Fe2O3 at 1123 K [66,p. 2]. Fe2O3 supported on ZrO2 showed the highest H2 yield, while Fe2O3 supported on Al2O3 showed the lowest. Least carbon deposition was observed for Fe2O3 supported on CeO2, but the carrier suffered sintering across cycles. However, despite of sintering it still maintained a high reactivity due to the good oxygen mobility property of CeO2. In addition, the formation of CeFeO3 perovskite was found to be responsible for the high reactivity of Fe2O3/CeO2. Al2O3, SiO2, MgAl2O4, ZrO2, and YSZ (yttrium-stabilized zirconia) were tested in a follow-up investigation. The hydrogen yield and reactivity decreased in the following order: Fe2O3/MgAl2O4 > Fe2O3/ZrO2 > Fe2O3/YSZ > Fe2O3/Al2O3 > Fe2O3/SiO2. Fe2O3 supported on YSZ exhibited the lowest carbon deposition. The porosity of Fe2O3/ MgAl2O4 increased with redox cycles, leading to a high H2 yield, whereas Fe2O3/ SiO2 underwent severe sintering due to formation of iron silicate [58]. A comparative study was also conducted between Fe2O3 supported on Al2O3 and Fe2O3 supported on MgAl2O4. Fe2O3 supported on MgAl2O4 showcased superior carbon deposition resistance as compared to Fe2O3 supported on Al2O3. Another study on TiO2 support revealed that Fe2O3 supported on TiO2 displayed poor reactivity and stability across redox cycles due to the formation of FeTiO3 [67].

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Apart from addition of supports, another strategy for enhancing the performance of oxygen carriers is through the addition of dopants and promoters. Xiang et al. studied the effect of doping Fe2O3 supported on CeO2 with Zr [68]. The results indicated that Ce0.75Zr0.25O2 displayed the best reactivity, stability, and H2 yield with almost no carbon deposition. The generated Ce0.75Zr0.25O2 phase exhibited improved oxygen mobility and thermal stability as compared to the undoped carrier. Moreover, further investigation revealed that the Zr doping inhibits the migration of Fe from bulk to surface, preventing sintering. A follow up study on the effect of doping rare-earth metals like Y, Sm, and La to Fe2O3 supported on CeO2 was conducted [69]. Both Y and Sm were able to suppress the migration of iron cations that resulted in improved redox stability of the carriers. Among these, Ce0.8Sm0.2O1.9 showed the highest redox reactivity and produced 100% pure H2. The dopants incorporated into CeO2 increased the concentration of oxygen vacancies, thereby promoting oxygen mobility and reactivity. In the case of La, it migrated out and formed LaFeO3 leading to poor reactivity. Liu et al. studied the effect of doping Gd on Fe2O3 supported on CeO2 in which Fe2O3/Gd0.3Ce0.7O2 exhibited a stable redox performance across 50 cycles [70]. It was observed that doping these metals forms excess oxygen vacancies, improving lattice oxygen diffusion in the carriers. This study concluded that the oxygen vacancies in a carrier play a major role in the performance of carriers could be optimized by tailoring the oxygen vacancy concentration. Some studies have also been carried out to investigate alkali metal-based promoters’ effect. A study by Xiang et al. showed that the addition of K2CO3 as a promoter weakened carbon formation on Fe2O3 supported on Al2O3 [71]. However, this carbon deposition resistance was obtained at the cost of decreased carrier reduction activity. Another study by Wu et al. also corroborated the promotion effect by alkali metal-based additive through KNO3 addition in the CLHG process [72]. The addition of KNO3 to iron ore resulted in improved reduction kinetics, H2 yield, and carbon deposition. It also reduced the sintering of carriers across the redox cycles. In another study by Jiang et al., iron ore modified using copper and potassium had significant effects on the reactivity and H2 yield due to the formation of active ferrites like CuFe2O4 and K2Fe4O7 [73,74]. In this case too, the carrier with additives showcased lower carbon deposition. Liu et al. studied the addition of NaAlO2 to Fe2O3 supported on Al2O3 for CLHG using coal as fuel [75]. The addition of NaAlO2 improved the carbon conversion and H2 yield by 10.7% and 9.6%, respectively. A deeper investigation revealed the formation of NaFeO2 that loosens the structure between Fe2O3 and Al2O3, thus improving the degree of dispersion of Fe2O3 on Al2O3. This resulted in improved surface morphology and pore structure which enabled an enhancement in reactivity and stability of the carrier. Adding different metals to Fe-based carriers can improve the reactivity and stability due to various kinds of synergistic effects between these components. Tu et al. investigated NiFe2O4 as a carrier for CLHG [76]. The methane reduction kinetics for the NiFe2O4 carrier were poor and improved significantly with addition of some extra NiO to the carrier. The study revealed that adding extra NiO to

3 Material development

NiFe2O4 could promote the O release rate, which is an essential parameter for the reduction kinetics. Moreover, the addition of Ce and Zr further improved the oxygen release rate. These bimetallic modified carriers, i.e., NiO/ZrO2- and NiO/ CeO2-modified Ni-ferrite, displayed a high H2 yield. This was because NiFe2O4 was converted to alloy Fe0.64Ni0.36 during the reduction step. Hence, more Fe was converted to Fe3O4 which improved H2 yield. Adding CeO2 and ZrO2 also provided the carriers with good structural stability. An illustration of the phase transformation and structural changes for Ni-Ce(Zr)/Ni-ferrite for a complete CLHG redox cycle is shown in Fig. 4. Xiao et al. studied the synergistic effect of several binary metal oxide carriers for CLHG [77]. A series of M0.6Fe2.4Oy (M ¼ Ni, Cu, Co, Mn) binary spinel material was studied. Among these, Cu and Co exhibited a stable performance across redox cycles with good reactivity and H2 yield [78]. Further, the mixed Co-Cu-Fe oxide Cu0.25Co0.75Fe2O4 showcased an H2 generation of 0.47 mmol g1 min1 at a relatively low temperature of 823 K. A deeper investigation revealed that the addition of Cu to CoFe2O4 facilitated the oxygen-ion diffusion through the bulk that resulted in a significant improvement in the overall hydrogen yield. Xiao et al. compared the performance of Cu-Fe-Al-O mixed spinel oxide to Fe2O3. The mixed spinel oxide showed good redox stability for 20 cycles compared to Fe2O3, which got deactivated within the first few cycles. The H2 yield was also improved by 3.5 times. Further investigations revealed that the spinel support could resist the sintering of Cu and Fe active compositions, resulting in improved performance. Xiang et al. studied the use of Ca2Fe2O5 for CLHG using CO as the fuel [79,p. 5]. The advantage of Ca2Fe2O5, apart from its high oxygen release and storage capacity and excellent thermal stability, is that it can undergo complete regeneration in reaction with steam and

FIG. 4 Mechanism of the Ni-Ce(Zr)/Ni-ferrite redox [76].

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hence eliminates the necessity of a third air reactor to regenerate solids. The carrier showed a stable conversion of 93.7% for both reduction and oxidation over 20 cycles. The study showed that the presence of Ca enabled the reduction of Fe3+ to Fe0 in one step. Hence, a synergistic effect between Ca and Fe resulted in an active and stable oxygen carrier for two-step CLHG. A summary of the investigated oxygen carriers for CLHG is shown in Table 2.

4. Process intensification The design and development of oxygen carriers remains at the core of chemical looping technology platform. However, just developing a perfect oxygen carrier formulation is not enough for the chemical looping technology to succeed. To ensure its success, the synergy between oxygen carriers, reactor design and subsequent process optimization must be explored. This section delves into the fundamentals of various reactor designs and provides guidelines on their selection based on application. Moreover, importance of operational strategies and process optimization that have the potential to increase process yields are illustrated.

4.1 Reactor design Reactor design dictates the fuel-carrier contact pattern which in turn governs the thermodynamics of the reaction occurring in the reactor [92]. Thus, apart from a carrier with good reactivity and recyclability, an optimized reactor design is crucial in obtaining high fuel conversions and product yields. As a chemical looping system consists of multiple interconnected reactors, a fundamental understanding of multi-phase flow hydrodynamics is necessary for optimal design of each reactor. This section delves into various reactor designs utilized for chemical looping combustion and hydrogen production. As mentioned in Section 2, different reactor configurations are developed for energy generation and hydrogen production. However, in each configuration, the combustor reactor is responsible for regeneration of the spent oxygen carriers and is usually designed as a fluidized bed. Fluidized bed offers good heat-transfer characteristics which is essential for maintaining a constant temperature. Efficient heat dispersion also protects the oxygen carriers as sintering and agglomeration due to hot-spot formation is avoided [6]. Moreover, in the case where the system is operated to generate electricity, good heat transfer is key which is offered by fluidized bed. Design basis of the combustor volume depends on factors such as the residence time requirement and the solid circulation flow rate. The cross section of the combustor needs to be adjusted such that the velocity of gas traveling through the combustor is higher than the minimum fluidization velocity of the oxygen carriers, but lower than the terminal velocity [93]. Moreover, the physical properties of the oxygen carriers affect the minimum fluidization velocities and thus must also be taken into

Table 2 Key findings of several oxygen carriers for CLHG. Fuel used

Carrier used

Coal

Na0.5Fe4Al6: 0.5 wt%-NaAlO2@40Fe2O3-60Al2O3

CH4 CO

NiO/ZrO2-modified Ni-ferrite (Ni/Fe ¼ 1:2) NiO/CeO2-modified Ni-ferrite (Ni/Fe ¼ 1:2) Cu0.2Fe0.8(FeAl)Ox spinel

CO

Fe2O3/Ce0.8Sm0.2O1.9

CO

Cu0.25Co0.75Fe2O4

CO

Fe2O3/Gd0.3Ce0.7O2δ

CH4

Fe2O3-CeO2/LaNiO3

CO

Fe2O3/Ce0.6Sm0.15Zr0.25O1.925

CO

Coal char CO

10% KNO3-decorated iron ore. (Iron ore: 83.25%Fe2O3, 7.06%-SiO2, 5.32%-Al2O3, 4.37%-other minerals.) K-decorated Fe2O3/Al2O3. Fe2O3/Al2O3/K2CO3: 70/30/ 3.5 Fe2O3@CeO2

CO

Fe2O3/Ce0.75Zr0.25O2

Reactor used

Temperature in °C

Hydrogen yield in mL/ g

Reference

Fluidized bed reactor Fixed bed reactor Fixed bed reactor Fluidized bed reactor Fixed bed reactor Fixed bed reactor Fixed bed reactor Fluidized bed reactor Fluidized bed reactor

900

1470

[75]

800

219.52

[76]

700

156.8

[80]

850

885

[69]

550

210.336

[78]

750

191.968

[70]

800

16

[81]

850

54.3

[82]

900

80

[72]

900

1450

[83]

850

136

[84]

850

45.3

[68]

Fixed bed reactor Fixed bed reactor Fluidized bed reactor

Continued

Table 2 Key findings of several oxygen carriers for CLHG—cont’d Fuel used CO

Carrier used

CO

CeO2-modified iron-based oxygen carriers OC-C3: 65%-Fe2O3, 5%-CeO2, 30%-Al2O3, n(C6H8O7H2O)/n(PEG400) ¼ 3 Fe2O3/Ce0.8Sm0.2O1.9

CO

5Fe1.67Cu10K (3:1 Fe:Cu, 10:100 KNO3:Hematite)

CO

NiFeAlO4

Syngas

Fe2TiO5

CH4

Fe2O3@MgFeAlOx

CH4

Fe2O3/CeZrO4

CO

Ca2Fe2O5

Syngas

Iron-based ceramic-supported oxygen carrier

CO

Fe60Al40 (60%Fe2O3 + 40%Al2O3)

CH4

20 wt% Fe2O3/ZrO2

Reactor used

Temperature in °C

Hydrogen yield in mL/ g

Reference

Fixed bed reactor

900

220

[85]

Fluidized bed reactor Batch fluidized bed reactor Fixed bed reactor Fixed bed reactor Fluidized bed reactor Fluidized bed reactor Fixed bed reactor Moving bed reactor Fluidized bed reactor Moving bed reactor

850

99.904

[86]

850

–

[73]

900

–

[87]

900

–

[88]

900

–

[89]

800

–

[90]

950

–

[79]

700–975

–

[64]

900

0.112

[67]

800

–

[91]

4 Process intensification

FIG. 5 Different reducer reactor configurations (A) fixed bed (B) moving bed (C) fluidized bed.

consideration while designing the combustor. The oxygen carriers are usually circulated pneumatically from the combustor to the reducer by coupling it with a riser. Designing the reducer is not as straightforward as that of a combustor since both kinetic and thermodynamic considerations must be accounted for. Moreover, there exist three fundamental operational modes—fluidized bed, moving bed and fixed bed-based on the gas-solid contact in which way the reducer can be designed as depicted in Fig. 5. Depending on the application, reaction conditions and oxygen carrier, particular design mode can be selected for the reducer. Fluidized bed reducers can be designed as bubbling fluidized beds, spout-fluidized bed, and circulating bed. The first two involve a countercurrent gas-solid flow while the circulating fluidized bed operates under cocurrent gas-solid flow [94]. In bubbling fluidized beds, there are issues with fuel conversion as there is a possibility that gas inside bubble is bypassed through the bed without reacting with the carrier [95,96]. Moreover, for solid fuels such as coal and biomass, char elutriation can occur which results in inferior product yields as fuel remains unconverted. To overcome these shortcomings, solid inventory in the bed has to be increased which can lead to infeasible reactor height to diameter ratio and increased operating costs [94,97]. To improve the solid fuel conversion a two-stage reactor design can be adopted. It involves a bubbling bed and a turbulent fluidized bed operating in series [94]. The turbulent section helps improve the char conversion and thus improves the product yield. In the case of spout-fluidized beds, greater fuel conversions are obtained as higher residences times for fuel are attained as compared to bubbling fluidized beds [98]. However, higher solid inventory is required in a spout fluidized bed which increases the operating cost and runs into the risk of gas slugging which can substantially reduce the fuel conversion [94].

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CHAPTER 13 Advances in chemical looping combustion technology

Moving bed reducers contrarily to fluidized bed, involve solids moving down the reactor bed in a continuous manner with fuels injected either from the bottom (gaseous fuels) or from the middle (solid fuels). Thermodynamics of moving bed enable complete and partial combustion of fuels when operated in countercurrent and cocurrent mode, respectively [6,8]. Moreover, operating in countercurrent (complete combustion) configuration allows maximum fuel conversion with negligible char elutriation, especially in the case of solid fuels. This is because, when solids are fed to the moving bed, the moving bed reducer is divided into two sections. In the section above the solid feed, volatiles and gasified char from the fuel react with the carriers in a countercurrent way forming CO2 and H2O. Moreover, in the section below the feed, char is gasified by an enhancer gas which is flowing from the bottom of the bed. This was exemplified through coal combustion developed at the Ohio State University was termed as “Coal Direct Chemical Looping” (CDCL) [16]. Moving bed system ensures full fuel conversion while achieving higher oxygen carrier conversion as compared to fluidized beds. This allows for higher electricity generation as amount of electricity generated is directly proportional to the oxygen carrier conversion. Moreover, in the case of Fe-based oxygen carriers, the thermodynamics of the moving bed system can be leveraged to produce high purity hydrogen as shown in Sections 2 and 3.2. As Fe-based carriers are moving down the reducer, Fe2O3 reacts with gases along the length of the bed to form Fe/FeO at the bottom. This solid mixture can be oxidized in steam to produce high purity H2. However, in the case of fluidized beds, due to the back mixing of the solids inside the reducer, conversion of Fe2O3 is restricted only till Fe3O4, which renders H2 generation infeasible as steam cannot oxidize Fe3O4 to Fe2O3 [8]. Deeper reduction of the oxygen carrier using moving bed allows for lower solid inventory than fluidized beds while achieving high fuel conversion and superior process flexibility. However, operating a moving bed while maintaining proper gas sealing and pressure balance can be challenging and requires diligent design and operational procedure. Apart from fluidized beds and moving bed configurations, fixed bed reactors have also been tested for both electricity generation and H2 production [99–103]. As there is no movement of oxygen carriers in a fixed bed, oxygen carriers with comparatively lower mechanical strength and higher reactivity can be employed. As the reactivity of oxygen carriers is higher, fixed beds require the least amount of solid inventory as compared to fluidized bed and moving bed reducers. Moreover, multiple parallel units of fixed beds can be operated to continuously process the incoming fuel. As there is no back mixing issue in fixed beds, deep reduction of oxygen carriers is possible, allowing H2 production using steam when Fe based carriers are used. However, there are certain inherent problems in operation of fixed bed reducers such as carbon deposition and hot spot formation [9]. As the fuel gas is moving through the fixed bed there is oxidation state gradient across the length of the bed. The oxygen carriers near the fuel injection port are reduced to their metallic oxidation state which can lead to cracking of carbonaceous fuels. This results in carbon deposition which can severely damage the oxygen carriers. Moreover, the heat transfer characteristics of fixed beds are inferior as compared to moving bed and fluidized bed reducers,

4 Process intensification

which can lead to hot spot formation during the exothermic regeneration step. These hot spots cause sudden localized temperature spurts resulting in sintering of oxygen carriers and loss of reactivity. Thus, fixed beds need to be meticulously designed and operated after considering the reaction conditions and expected product yields. Although the above-mentioned reactor designs constitute majority of chemical looping systems worldwide, design of reactors is still an ongoing area of research with new designs being explored continuously. One such design is the single reactor internally circulating fluidized bed which utilizes a single vessel with internally separated chambers. The two chambers act as reducer and combustor, respectively with a L-type connection acting a solid flow facilitator while maintaining a gas seal. Other designs such as the rotary kiln and gravity-assisted reactors are also being researched [104].

4.2 Process optimization and operational strategies Process Intensification is essential in the current chemical engineering scenario, as it enables reduction in energy consumption and cost of production. By using simulation software such as ASPEN Plus, Chemcad, etc. processes can be optimized to increase the overall efficiency. Process simulations also allow informed selection of the operating conditions as parameters such as cold gas efficiency, effective thermal efficiency, exergy efficiency can be compared [105,106]. Moreover, mass and heat integration of chemical looping system with the entire chemical plant can be achieved through process simulations resulting in tight process intensification. Tight process intensification indicates that chemical plant is operating under minimal heat and material losses and maximum performance is achieved [107]. Process simulations are also useful when investigating possible perturbations to the system under consideration. The material and energy flows in the CLC system can be integrated with the other streams in the process to design novel process schemes. Thus, advanced operational strategies can be explored for CLC systems, saving the time and cost of experiments [108]. Herein three advanced operating strategies that were a direct result of meticulous process simulations are discussed—Fuel injection location, staged injection strategy, and modularization. As discussed earlier, the inherent nature of CLC system eliminates the need for a downstream CO2 separation unit or an upstream ASU. However, depending on the type of fuel used, it is imperative to alter the gas-solid modes of contact to ensure maximum fuel conversion. Process simulation can be employed in such cases to ascertain the appropriate feed location [109]. For instance, it was found that for moving bed systems, the solid fuel should be injected in the middle of the reducer whereas the gaseous fuel should be injected in the bottom of the reducer to ensure complete fuel conversion in combustion-based applications. In addition, process simulations can also be conducted to vary the oxygen carrier to fuel ratio in the reactor to find the optimal range for maximum yield [16,110,111]. A staged injection strategy can be implemented when there exists a waste gas stream such as tail gas from some other unit in the plant that contains mainly

405

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CHAPTER 13 Advances in chemical looping combustion technology

CO2 with some amount of reducing gases such as CH4, CO, H2. Usually, extracting heat from such a low reducing power stream is challenging [112,113]. However, in a CLC system, staged injection can be adopted wherein the gas stream with lower reducing power is injected in the middle of the moving bed reducer while the main fuel stream with higher reducing power is injected at the bottom [114]. Since there are fully oxidized carrier particles in the top of the reducer, the oxidizing power of these particles is high. Thus, they can oxidize the waste gas stream to high purity CO2 and H2O. This staged injection strategy results in increased product yield while utilizing same amount of fuel. Use of multiple reducers (modularization) combined with a single combustor can be an excellent way of handling multiple fuels at a same time without compromising the product purity. Kong et al. reported use of two reducer reactors to produce Dimethyl Ether from natural gas, which resulted in decreasing the natural gas requirement by 9.6% over the conventional process and 5% over the conventional chemical looping process for the same DME production capacity. While one of the reducers is operating in the syngas production mode with cocurrent fuel injection, the other reducer is operated countercurrently with the off gases from the methanol production unit for combustion. The rationale behind such operation is that the energy required for syngas production (done in first reducer) can be supplied by the second reducer—combustor pair (second reducer operating in combustion mode) while achieving CO2 capture. Moreover, both the reducers can operate individually at different solids flowrate, thus giving a better control over the process. Use of same combustor decreases capital costs and increases the energy efficiency, while maintaining the self-heat reliance (autothermicity) [112,115]. Apart from process optimization, process simulations can also aid carrier development. Joshi et al. reported process simulations for a Cu-Ca based oxygen carrier for CDCL system that can carry out both CO2 and SO2 separation within the system. In comparison with the conventional CDCL system, wherein an additional SO2 scrubber unit would be required downstream before generating capture ready CO2, the designed process produces a stream of SO2 by using an additional reactor. Similarly, the thermodynamic performance of any material and process can be evaluated using process simulations [110].

5. Conclusions and future research The world today is undergoing a major shift from fossil fuel-based energy economy to renewable fuel-based energy economy. This change is driven by the rising concerns of global warming and climate change which stipulates decarbonization in the energy sector. However, fossil fuels cannot be easily abandoned as the demand for both energy and goods has reached an unprecedented value, which renewable based energy sources cannot meet at the present time. Chemical looping with its inherent advantages has the potential to act as a bridge between fossil fuels and renewable fuels-based energy systems. The technology offers a unique virtue of

5 Conclusions and future research

utilizing combustion chemistry while inherently capturing CO2, to either directly generate power or to produce valuable chemicals (H2 or syngas) that can be used as building blocks for a variety of consumer products. As chemical looping involves splitting of reaction into multiple sub-reactions, looping carriers that act as oxygen transfer media, are the most important aspect of this technology. These carriers swing between their regenerated and reduced (reacted) state which enable complete fuel conversion with selective product formation. As a result, carriers with good selectivity, reactivity, mechanical strength, and attrition resistance need to be formulated for the technology to succeed. Apart from development of appropriate carrier, process intensification is also essential to meet product yields while operating at maximum efficiency. This can be achieved by designing reactors with configurations that enable maximum throughput. Moreover, depending on application, process optimization using simulations and modeling can be carried out to obtain an operational strategy that provides highest economic gains. This chapter outlines the relationship between various aspects required for developing chemical looping. The oxygen carriers developed for CLC and CLHG applications mostly comprise single and multi-metal oxides, spinels, perovskites and brownmillerites. The selection of active component of the carrier is crucial as it dictates the reaction thermodynamics of the process. Although several transition metals showcase redox behavior, Fe-based carriers are preferred for CLHG as they can undergo steam oxidation to form Fe3O4 from Fe/FeO to produce H2, are low in cost and non-toxic in nature. Even for CLC, a large number of studies are performed on Fe-based carriers as they are relatively cheaper and exhibit good reactivity. Apart from Fe-based carriers, Cu, Mn, and Ni based carriers are also developed for CLC applications. Cu and Mn oxides undergo oxygen uncoupling which increases the fuel oxidation kinetics. Ni based carriers inherently exhibit good reactivity toward carbonaceous species making Ni a strong candidate for CLC based application. However, active component is just one aspect of an oxygen carrier. In order to endure the harsh chemical and physical stresses of both the CLC and CLHG system, the carrier must possess longterm chemical stability and high mechanical strength. This is achieved by incorporating carrier with supports such as TiO2, CeO2, Al2O3¸ MgAl2O4, etc. These supports provide the necessary the stability required by the carriers. Moreover, dopants and promoters are also added to further enhance the reactivity and strength. This selection of active component along with support and/or dopant and promoters is where research is mainly focused for any chemical looping system. Depending on the specific application, cost, and ease of availability of materials, selection process can be made more efficient by performing thermodynamic analysis and conducting experiments. The experiments should involve rigorous testing of long-term reactivity of carriers with evaluation of factors such as sintering, attrition resistance and phasesegregation. Reactor design of the reducer is another important aspect as it controls gas solid contact mechanism which affects the product yield, vessel sizing, process economics, and longevity of the carrier itself. However, the choice of reactor type is heavily influenced by the desired application and the oxygen carrier involved. Fluidized bed

407

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CHAPTER 13 Advances in chemical looping combustion technology

reactor is good in terms of heat and mass transfer but faces its own operational challenges such as high solids flowrate, gas channeling, non-uniform solids conversion, etc. Moreover, due the back mixing occurring in fluidized bed, H2 generation in Febased system is difficult. Moving bed reactors on the other hand achieve equilibrium thermodynamic product yields due to greater control over the solid and fuel residence time. Moreover, the thermodynamics of the moving bed system can be leveraged to produce high purity hydrogen in the case of Fe-based carriers. However, operation of a moving bed while maintaining proper gas sealing and pressure balance can be challenging and requires diligent design and operational procedure. Fixed bed reactors have the least operational complexity with possibility of generating both power and H2. They require the lowest solid inventory and have less stringent mechanical strength requirement as compared to fluidized beds and moving bed reactors. However, there are certain inherent problems in operation of fixed bed reducers such as carbon deposition and hot spot formation. Determining which reactor configuration is most suitable for the application depends on the fuel being processed, product yield requirement, operational experience, and characteristics of oxygen carrier. Once oxygen carrier and the reactors are optimized for the process, further process intensification can be carried out for increasing the efficiencies and to obtain higher economic gains. Tight process intensification, i.e., heat and material integration across the chemical plant can be carried out to increase waste energy recovery and decrease utility usage. This can be achieved by performing process simulations which helps understand the inefficiencies in the process that can be improved to obtain additional gains and make the overall technology competitive with conventional technologies. Moreover, process optimization can lead to development of advanced operational strategies such as modularization and stage injection that further increases the overall throughput of the plant.

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CHAPTER

Chemistry diagnostics for monitoring

14

Katharina Kohse-H€ oinghausa, Alison M. Ferrisb, Johan Zetterbergc, d Deanna A. Lacoste , Peter Fjodorowe, Steven Wagnerf, Liming Caig, Charlotte Rudolphh, Judit Za´dori, Yuyang Lij, Lena Ruwek, Nina Gaiserl, Zhandong Wangm, and Klaus Peter Geiglel Department of Chemistry, Bielefeld University, Bielefeld, Germany, bDepartment of Mechanical Engineering, Stanford University, Stanford, CA, United States, cCombustion Physics, Department of Physics, Lund University, Lund, Sweden, dKing Abdullah University of Science and Technology, Clean Combustion Research Center, Thuwal, Saudi Arabia, eInstitute for Combustion and Gas Dynamics—Reactive Fluids, University of Duisburg Essen, Duisburg, Germany, fInstitute for Reactive Flows and Diagnostics, Technical University of Darmstadt, Darmstadt, Germany, gSchool of Automotive Studies, Tongji University, Shanghai, China, hInstitute for Combustion and Gas Dynamics—Thermodynamics, University of Duisburg-Essen, Duisburg, Germany, iCombustion Research Facility, Sandia National Laboratories, Livermore, CA, United States, jSchool of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China, kPhysikalischTechnische Bundesanstalt (PTB), Braunschweig, Germany, lInstitute of Combustion Technology, German Aerospace Center (DLR), Stuttgart, Germany, mNational Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, Anhui, China a

Abbreviations* *Note that some abbreviations will be introduced in several sub-chapters to facilitate independent reading. AI artificial intelligence APCI atmospheric pressure chemical ionization AP-XPS ambient pressure X-ray photoemission spectroscopy, see also XPS CARS coherent anti-Stokes Raman scattering/spectroscopy CFD computational fluid dynamics CI compression ignition CID collision-induced dissociation CP-MS chirped-pulse microwave spectroscopy CRDS cavity ring-down spectroscopy DFB distributed feedback DME dimethyl ether EFISH electric-field-induced second harmonic Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00017-5 Copyright # 2023 Elsevier Inc. All rights reserved.

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EI FIR FTIR GC GHG HAXPES HCCI HESXRD HPLC i2PEPICO ICAS ICL IDT IR ISF JSR KHP LAS LEED LES LIF LII LTO MBMS MIR ML MS NIR NTC NTLAF OME OTMS PAC PAH PEPICO PES PFR PI PICS PIE PIMS PIV PLIF PM PM-IRRAS PtL QCL

electron ionization far-infrared, see also IR, MIR, NIR Fourier-transform infrared, see also IR gas chromatography greenhouse gas hard X-ray photoelectron spectroscopy homogeneous charge compression ignition high-energy surface X-ray diffraction high-performance liquid chromatography double-imaging photoelectron photoion coincidence, see also PEPICO intracavity absorption spectroscopy inter-band cascade laser ignition delay time infrared, see also FTIR, MIR, NIR international sooting flame (workshop/community) jet-stirred reactor ketohydroperoxide laser absorption spectroscopy, see also TDLAS low-energy electron diffraction large-eddy simulation laser-induced fluorescence, see also PLIF laser-induced incandescence low-temperature oxidation molecular-beam mass spectrometry, see also MS mid-infrared, see also IR, FIR, NIR machine learning mass spectrometry, see also MBMS, OTMS, PIMS near-infrared, see also IR, FIR, MIR negative temperature coefficient nonlinear two-line atomic fluorescence oxymethylene ether orbitrap mass spectrometer, see also MS plasma-assisted combustion polycyclic aromatic hydrocarbon photoelectron photoion coincidence, see also i2PEPICO photoelectron spectrum, see also TPES plug-flow reactor photoionization photoionization cross section photoionization efficiency photoionization mass spectrometry, see also MS, SVUV-PIMS particle image velocimetry planar laser-induced fluorescence, see also LIF particulate matter polarization-modulated infrared reflection-absorption spectroscopy power-to-liquid quantum cascade laser

1 Introduction: Only 25 years

SAF SI SOR SVUV-PIMS TDLAS TNF TOF TPES UV VUV XPS

sustainable aviation fuel spark ignition surface optical reflectance synchrotron vacuum ultraviolet photoionization mass spectrometry, see also PIMS, VUV tunable diode laser absorption spectroscopy, see also LAS turbulent non-premixed flame (workshop/community) time-of-flight threshold photoelectron spectrum, see also PES ultraviolet, see also VUV vacuum ultraviolet, see also UV, SVUV-PIMS X-ray photoemission spectroscopy, see also AP-XPS

1. Introduction: Only 25 years Counting down to 2046, time is short to bring in more sustainable processes [1,2]. Sustainability should not be confounded with decarbonization, however, given carbon’s importance in molecules that support life. Nevertheless, carbon-containing small molecules play a pivotal role in the development of climate and environment, and their balance, impacted by human activity, must be controlled: “From a physical science perspective, limiting human-induced global warming to a specific level requires limiting cumulative CO2 emissions, reaching at least net zero CO2 emissions, along with strong reductions in other greenhouse gas emissions. Strong, rapid and sustained reductions in CH4 emissions would also limit the warming effect resulting from declining aerosol pollution and would improve air quality” [2]. It is typically assumed that transformation processes involving technology and infrastructure may take decades [3–6]. Conditions for more rapid energy-related system changes were analyzed by Sovacool [7] from ten selected case studies focusing on fuels and prime movers; in these cases, the respective transformation took less than a generation, specifically between 1–16 years, affecting in total about one billion people. Challenges associated with system transformation should thus not be generally regarded as unsurmountable in the 25 years envisaged here. Pursuing sustainable development goals [1] must include all sectors—power, transport, industry, buildings, space heating, agriculture, etc.—and requires taking big strides in view of climate developments [2]. Energy- and resource-efficient, preferably circular processes with low greenhouse gas (GHG) and local emissions that are based to a large extent on renewables are considered to be key elements in favorable transition scenarios [3,4]. The sectors with the most significant challenges are energy-intensive industries [3,4]. Especially, but not only when fossil fuels are used to supply necessary process heat, alternative solutions are required for high-energyinput industrial processes; these encompass multiple targets in the chemical sector, in refineries, in the production of metals, cement, glass, ceramics as well as of paper and

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cardboard [3–7]. Beyond process integration and efficient energy management [8], the need for minimum waste and circular processes necessitates avoiding or valorizing waste streams [4,9,10]. Optimization examples relying on suitable computational frameworks have been presented, e.g., for eco-industrial parks [8], plastics [9] and organic waste [10]. Regarding the chemical sector, difficulties arise not only from the scale of such processes, but also from the diversity of chemical transformations which precludes a single blueprint solution. For many of the above-mentioned energy-intense processes, changes of quite different process details may promise greenhouse gas abatements for each given case. Recurrent features, nevertheless, pertain to heat recovery, design of furnaces, ovens, kilns, boilers, industrial burners, pre-heaters and heat exchangers; opportunities for potential improvements include—on the technology side—electrification, catalysis, carbon capture, chemical looping, plasma enhancement, oxy-fuel combustion and membrane separation instead of heat-based separation processes, and—on the feedstock side—alternative options such as biomass, renewable methane, hydrogen and other hydrogen-rich compounds [4,6]. In any case, reliable information on the reaction process is a key requirement, demanding suitable instruments and techniques for monitoring, metering and control, favorably with sensors that can provide such information in situ and in real-time. Combustion processes, at least in the general public, are often discussed merely in conjunction with light-duty transportation, mainly regarding electrification of the powertrain as a replacement option for the internal combustion engine. However, combustion-related technology is found in many of the above chemical and reaction engineering contexts, and combustion knowledge could be a profound source for innovations in the industrial sector [11]. Additionally, the transportation sector will need low- or zero-carbon options beyond those concerning light-duty vehicles, namely for aviation, marine and long-range road transportation. One consideration is to use biomass as a renewable feedstock that contains carbon, but its amount is likely insufficient for all fuel uses on a global scale. Also, often-discussed concerns regarding its exploitation include issues with biodiversity, food, land use and irrigation. Synthesis protocols, potentially from CO2 as a starting material, are therefore being discussed to provide, for example, future high-performance aviation fuels [12]. Chemical and combustion knowledge combined is thus advantageous to produce suitable fuels for transportation and industrial purposes from available feedstocks, to understand their combustion behavior and to use them in efficient, low-emission systems [11–17]. Combustion processes also matter in a further area of public concern, namely fire safety and prevention for natural as well as urban areas, industrial installations and transportation environments. Knowledge beyond mere empirical relations is needed to describe pertinent details of such combustion processes that occur under highly diverse conditions. Important aspects include fluid dynamics and flame spread, but also chemical information such as thermochemistry, surface chemistry, ignition reactions as well as the nature, properties and potential toxicity of emissions [18–20]. Note that aerosols and GHG emissions from wildfires and biomass burning are also factors impacting climate and environment [18,21,22].

1 Introduction: Only 25 years

Chemistry solutions are furthermore important in the development of halogenfree, effective flame retardants [23–25] and in understanding their combustionrelated reactions [26,27]. Ubiquitous hydrocarbon-based chemical products such as polymers and plastics introduce high flammability and thermal load, demanding chemical knowledge to design non-hazardous, non-toxic fire retardants [23]. Sustainable solutions could also be expected from use of cellulosic biomass for this purpose, adopting similar biorefinery concepts and processes to produce valuable chemicals—such as fire retardants—as those employed for the conversion of biomass to biofuels [24]. Carbon-based (nano-)materials constitute another category of compounds that have shown useful flame-retarding properties [25]. Again, crosslinking combustion and chemistry, flame synthesis processes have demonstrated the potential to grow a plethora of useful functional materials, examples including carbon nanostructures that could also be applied in fire prevention and multiple oxides that could serve as catalysts [28–31]. Understanding the complex reaction behavior in such synthesis systems is again a prerequisite to design desired material functionalities and to enable process control and upscaling. From the above examples involving different fields such as high-energy industrial processes, long-range heavy-duty transportation, fire prevention and material synthesis, it may be safely assumed that combustion-related science and technology will remain important for the next 25 years and potentially beyond. It is also evident that related research and development should consider multiple linkages with chemistry [32]. Diagnostics and sensing methods and devices continue to be a prerequisite for in-depth understanding, model development, optimization and control of reactive systems [33]. They will be key to determine major process parameters and important chemical agents in the respective reaction processes and to allow for prediction and control of performance, byproducts and emissions. The importance of a direct inspection of the process in question is in line with the statement of Smyth: “Flame measurements are the ultimate arbiter of how well we understand the controlling chemical mechanisms and transport processes” [34], made in a 1994 collection of articles edited by Glassman [35] on the (then) next 25 years of combustion. Since then, the potential of diagnostics has grown tremendously as shown in some recent review articles [36–48], importantly also with a focus on combustion chemistry [43–45] and particulate formation [46–48]. What are the key requirements regarding combustion chemistry and diagnostics? It is instructive to approach this question by inspecting some older literature—going back even more than 25 years—to analyze some earlier developments as a potential basis for projections into the future. For example, in his address to the attendees of the Seventh International Combustion Symposium 1958, Sir Cyril Hinshelwood, then president of the Royal Society, summarized achievements and spelt out fundamental aspects of combustion that would need attention [49]. Although many details of the reaction mechanisms of fuel oxidation were unclear at that time, key issues he mentioned included chain branching, sensitivity of the reaction pathways to the molecular fuel structure, the importance of oxygenated intermediates including peroxides and aldehydes, and—as specifically intriguing—both, the existence of an “anomalous” temperature-dependent reactivity varying with molecular structure

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and that of cool flames [49]. Such issues have kept combustion researchers involved until quite recently, as one can appreciate from reviews on oxygenated intermediates in low-temperature oxidation [50], on the reactivity of oxygenated fuels [51] and on cool flames [52]. Sessions on the spectroscopy and structure of flames at early Combustion Symposia covered topics such as the mechanisms of combustion reactions, including those of radicals, the determination of rate coefficients for elementary reactions and the interpretation of emission and absorption spectra and of chemiluminescence in flames. Seminal summaries were provided by Norrish [53] on the study of combustion reactions with photochemical methods and by Gaydon [54] regarding the use of shock tubes for this purpose. In the discussed cases, information from the reactive system was obtained, for example, by relying on absorption spectroscopy [53,54] as an early—and still important—combustion chemistry diagnostic technique. Time histories and spectroscopic transition probabilities for a number of free radicals could be determined, supporting quantitative concentration measurements [54], and timedependent monitoring of the absorption spectra of radicals after initiation of the reactions by short-pulse flashlamps enabled analysis of combustion-relevant behavior such as knock [53]. Some important incentives for in-depth investigations into combustion processes were perceived fuel shortages or crises that raised discussions about a future fuel spectrum and emphasized the need for higher efficiency, and—at the same time—increasing concerns about air pollution that demanded concepts for cleaner combustion and exhaust gas aftertreatment [54–59]. Interestingly, Weinberg [56], almost 50 years ago, mentioned in terms of future fuels “producing some, e.g., H2, CH3OH (if only as a method of storage and transmission of power)” and “growing” fuels, e.g., using anaerobic digestion. Such suggestions regarding synthetic fuels and biofuels remain important today and for the future. Similarly, his suggestions of improved process control and stability through recirculation, plasma enhancement or pulsed combustion may be appreciated, concepts that have meanwhile been introduced, refined or revisited and analyzed in more detail [60–63]. Methods including high-speed photography, exhaust gas analysis with gas chromatography and mass spectrometry as well as temperature measurements had permitted, as reported by Agnew 1985 [58], examining and confirming hypotheses about complex combustion processes such as in engines. Detailed chemical mechanisms regarding the formation of pollutant emissions [64,65] and in situ flow-stopping diagnostics have experienced rapid development since then and have been instrumental in revealing details of combustion processes from laboratory to application, significantly benefitting from the introduction of lasers [66]. Common expectations in the 1994 article compilation edited by Glassman [35] for the next 25 years—to the time of today—included more advanced diagnostics, more detailed understanding of pertinent chemical reaction pathways, more reliable methods of theory and more computer power coupled with better algorithms for more extensive simulations. In short, these advances were thought to enable exploration of more complex systems than in the 1990s and offer better predictive capabilities for

2 Methodology: Teaming up

combustion system design and operation. All these developments occurred and matter for today’s status of combustion science. But is a continuation of this trajectory for the next 25 years realistic? Will we expect “just” better methods, more comprehensive data, finer details, deeper understanding, higher-quality predictions? Is exploration of increasingly complex targets the goal? Or will today’s boundary conditions [1,2], in view of defossilization and circular processes [3–10], impose different needs for combustion chemistry diagnostics for 2046?

2. Methodology: Teaming up As a senior professor, I have found it unwise to speculate about needs for the next 25 years without consideration of ideas and opinions of researchers who—different from myself—will probably be active professionals at that time. I have thus asked a number of colleagues to support me writing this chapter. To provide a spectrum of potential answers, I have encouraged 13 persons with different specializations encompassing experiments, simulation and theory, in different career stages from doctoral student to professor, in different age groups (from below 30 to above 50) and in different locations to share their thoughts. Asked about their potential occupation in 25 years, answers range from science consultant and independent researcher to full professor, but most wish to remain in academia and research. Some have also expressed further wishes, such as bridging between academia and industry; contributing to societally important developments; building on relations between science, technology and economics for future innovations; fostering the education of future generations of academics and interacting with the general public. Each co-author was given the instruction to provide a concise sub-chapter reporting about their and their collaborators’ own current research (Status 2021), their immediate research plans for the next five years (Preview for 2026), and their ideas for the transition toward combustion chemistry diagnostics needs in 25 years (2030 and beyond). I have tried to preserve the authenticity of these sub-chapters while grouping and editing. The structure of this suite of visions is not thought to be one technique per sub-chapter, but rather a mix of diagnostics, monitoring and sensing targets, research questions and future demands for diagnostics in a carbon-neutral context. Diagnostic methods include variants of absorption spectroscopy (Sections 3.1, 3.4, and 3.5), mass spectrometry (Sections 3.9–3.12), photoelectron photoion coincidence spectroscopy (Sections 3.8 and 3.11) and a large number of other techniques, also addressing measurement of electric fields (Section 3.3), of surface properties (Section 3.2), diagnostics in new spectral ranges (Sections 3.4 and 3.5) and at high pressures (Sections 3.1, 3.3, 3.11, and 3.12). Sensor development (Section 3.4) and the use of advanced large-scale facilities and beamlines (Sections 3.2, 3.9–3.12) are considered important as are data strategies (Sections 3.1, 3.5, 3.6, 3.8, 3.10, and 3.11) to permit chemistry diagnostics and process monitoring in the future. Systems with promise for carbon reduction include engines (Sections 3.6, 3.7, and 3.11), catalytic

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(Section 3.2), plasma-enhanced (Section 3.3), reforming (Sections 3.1 and 3.7) and further industrial (Section 3.5) processes such as nanoparticle synthesis (Sections 3.4 and 3.13) and polygeneration to achieve flexible power, heat and chemical production as well as energy storage (Section 3.7). A large shift is foreseen regarding future fuels, with new demands for chemical diagnostics concerning their reactivity, ignition and oxidation properties (Sections 3.1, 3.8, 3.9, and 3.12) as well as their impact on emissions (Sections 3.10 and 3.13); fuels will include hydrogen (Section 3.1), sustainable aviation fuels (Sections 3.1, 3.11, and 3.13), synthetic and other low-carbon fuels (Sections 3.9–3.11 and 3.13) such as ammonia (Sections 3.1, 3.6, 3.9, and 3.13). Chemical model development to simulate respective processes of interest (Sections 3.1, 3.6–3.9) must go hand in hand with diagnostics, considering innovations in theoretical chemistry (Section 3.8), automatic mechanism generation (Sections 3.6 and 3.7) and uncertainty analysis (Section 3.6). Furthermore, multiplexing, combinative and collaborative strategies are recommended (Sections 3.1–3.3, 3.7, 3.8, 3.12, and 3.13). A number of aspects are thus interwoven in the subsequent sections, and only their full reading and appreciation will provide a more comprehensive view into the future.

3. Results: 1+13 visions Preceding the 13 individual contributions, I will briefly summarize my thoughts in the same spirit. Note that I have already tried to give partial previous answers in recent perspective and review articles [32,33]. To me, diagnostics and especially chemistry diagnostics appear eminently useful for a multitude of purposes. Diagnostic methods and techniques that can reveal details on chemical species and reactions are not only suited to investigate combustion problems and systems but can address a wider scope of chemical process technology as sketched above. One obvious focus with similarities to combustion systems could be gas-phase-involving processes occurring at moderate to high temperatures and at ambient to elevated pressures. I would like to differentiate between several types of diagnostics that may be envisioned for different requirements. First, “fundamental” diagnostics can provide information directly on the chemical species involved under selected reaction conditions, without which details of the chemical reaction process will remain hypothetical and thus unresolved. Relevant diagnostics may require highly advanced and refined tools and techniques that are only hosted in dedicated laboratories or may involve large-scale facilities such as synchrotrons and free electron lasers. The insight gained on fundamental aspects of reaction processes, mostly under more idealized conditions, will provide clues for mechanisms that could be used to model the process with the aim of optimization, upscaling and transfer to different boundary conditions. Second, “monitoring” diagnostics may be useful to capture the key variables influencing the process, with potentially limited information on reactive chemical species, but targeting the process dynamics including flow field, fluctuations and

3 Results: 1+13 visions

gradients. Such diagnostics may build upon information gained from the first, fundamental kind: From such results, major conditions of interest might be derived, and monitoring the process may then provide in-depth performance information that might lead to design modifications. Third, “sensing” diagnostics can serve for process control in the field or in the technical environment in question, tracking key intermediate or product species or potential emissions in situ and in real-time. Sensors can be helpful to keep the process within a predefined window of operation and provide signals for control when the specifications are about to be no longer met. Self-diagnosis and calibration during the process might offer particular guidance for control. Chemistry diagnostics research and applications in the future will target different reactions, in different environments, for different purposes than today. A wide space of opportunity is open between the extremes of providing comprehensive chemical and dynamic information for fundamental reasons on the one side, and establishing reliable, economical, on-site sensing for active process control on the other. Within that space of opportunity, new devices, new techniques, new combinations of tools, made possible by advances in material science, optoelectronics and photonics can provide a multitude of interesting and useful solutions. Diagnostics can be fruitfully complemented and enhanced by combination with theory, modeling, uncertainty analysis, data strategies and informatics. Looking into the crystal ball, some advances in selected areas could influence the knowledge that we may gain in the future in the field of chemical processes, including ultrafast diagnostics of molecules, structures and molecular rearrangements [67–70], theoretical advances to describe chemical reactions and mechanisms [71–75] and quantum computing for chemistry [76,77]. These developments could prove valuable mainly for the fundamental questions in the diagnostics hierarchy sketched above. Among diagnostics to investigate complex fundamental reaction chemistry and chemical engineering questions under challenging conditions, laser absorption spectroscopy offers high potential as one technique of choice, more than 50 years after it was discussed for combustion chemistry analysis by Norrish [53] and Gaydon [54] as mentioned above. Absorption methods are currently employed to combustion systems, based on a variety of laser sources including quantum cascade and supercontinuum lasers and in part relying on frequency modulation, dual-comb techniques, spectroscopic databases and spectral fitting methods [63,78–83]. Such techniques, for example, are also suitable beyond the study of fundamental aspects, but are certainly not the only solution for direct process inspection. Further diagnostic methods provide their particular strengths to address the multitude of fundamental research questions in the transition toward carbon-reduced and carbon-neutral processes, and some of them are mentioned in the following sub-chapters. Diagnostics for monitoring and sensing purposes need methods and tools with specific capabilities: They should be non-invasive, fast, multiplex, self-calibrating, portable, reliable, stable, usable by non-specialists and best, all of the above. Fiber optic sensors [84], sensors using surface plasmon resonance [85] and flexible

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plasmonic metamaterial sensor platforms offering multiplexing functions [86] can provide interesting properties for gas sensing in industry and the environment as well as for process optimization and control in a variety of systems [84,85]. Miniaturized spectrometers [87,88] relying on vibrational spectroscopy for molecular fingerprinting are being developed for use in other industrial sectors at different, potentially less challenging boundary conditions, but such concepts might be valuably developed further for different applications. Miniaturization and non-expert usage go along with need for evaluation and calibration algorithms, spectroscopic libraries and background data sources that can enable fast and accurate measurements through respective programs and digital applications [88]. Such instruments are designed for the field rather than for the laboratory, e.g., regarding spectral range or sensitivity, but offer time savings by rapid on-site measurements without posterior expert evaluations. Smartphone-like platforms for process analytics and optimization have been described for reaction design in chemical synthesis [89], and such concepts could possibly be exploited for different environments. With the Internet of Things, integration of remotely located sensors for environmental pollution assessment as well as process automation and control seem to be under way [90], and these and other developments might provide novel stimuli for chemical process diagnostics. As stated in Ref. [90]: “Finally, sustainability will become an immensely important aspect for analytical chemistry with respect to waste produced, energy consumed and enabling on demand local production.” It is mandatory, of course, that for all measurements, in large-scale facilities, in the laboratory, in the combustion system and in the chemical engineering facility, uncertainties must be reliably assessed [91].

3.1 Alison M. Ferris: Sensor innovations for omnivorous energy and propulsion systems 3.1.1 Status 2021: Shock tubes and optical diagnostics The design of next-generation, combustion-based energy and propulsion systems relies on our detailed understanding of combustion phenomena, including chemical kinetics and flame propagation dynamics. As an experimental kineticist, my research focuses on using optical diagnostics and shock tubes to study the underlying chemical reactions and mechanisms that govern the combustion of conventional and nextgeneration fuels. Optical diagnostics can be used to measure global combustion properties (e.g., ignition delay time), or can provide in situ monitoring of temperature, species mole fraction, and even individual reaction rates; a shock tube is an impulse heater that can generate near-quiescent temperature and pressure conditions relevant to energy and propulsion systems (e.g., 500–10,000+ K and 0.01–1000+ atm), thereby enabling fundamental study of fuel chemistry in an environment free from interfering facility effects (e.g., engine swirl, lubrication, etc.) [92]. The low-temperature combustion regime has recently garnered particular interest due to its complexity and the prevalence of non-ideal combustion phenomena at low temperatures. As a PhD student in Professor Ron Hanson’s research group at Stanford University, I developed two experimental approaches to enhance our ability

3 Results: 1+13 visions

to study low-temperature combustion kinetics in a shock tube: A combined laser absorption spectroscopy (LAS)-gas chromatography (GC) speciation diagnostic [93] and a new method for measuring laminar burning velocity at previously unexplored unburned gas temperatures (>500 K) [94]. The combined LAS-GC methodology allowed us to gain greater insight into the pyrolysis of ethylene [93] and to quantify the diversity of intermediate species formed in low-temperature n-heptane oxidation [95]. Development of the shock-tube laminar burning velocity approach has enabled observation of previously unseen, high-temperature laminar burning velocity trends [96] and yielded the highest-temperature measurements of propane and ethane laminar burning velocity yet available [94]. There is consensus in the combustion community that we must expand our focus beyond petroleum-derived hydrocarbons. Indeed, this shift can already be felt, from the prevalence of clean-energy funding opportunities to the kinds of fuels and energy systems now being studied. For example, as a research scientist in the Hanson group, I now oversee two new areas of research: development of an infrared (IR) spectrum-based, low-volume prescreening tool to aid in the design of sustainable aviation fuels (SAFs), and investigation of shock wave reforming as a potential means for producing hydrogen from hydrogen-rich fuels, including methane or natural gas. Both of these research areas make use of diagnostics or experimental approaches that were refined in the study of conventional hydrocarbons but have been expanded to incorporate newer analytical or experimental techniques (e.g., machine learning, long-test-time capabilities, etc.). It is precisely this combination of new and established methods that will enable us to address the biggest scientific challenges of today. Looking to the future, there is need for a two-pronged approach to achieve defossilization: Research is needed to expedite the development of cleaner fuel alternatives compatible with existing energy and propulsion systems to more immediately offset emissions, and research is needed to enable development of carbon-free, next-generation, paradigm-shifting energy and propulsion technologies. Advancements in chemistry sensing and monitoring will be critical in achieving these near- and long-term goals.

3.1.2 Preview for 2026: Cleaner fuels, property prescreening and performance prediction In the near-term, there is urgent need for the rapid development and deployment of low-polluting, drop-in fuels, or fuels that can be used in existing energy and propulsion technologies without the need for engine or fuel system modification. It is widely expected that light-duty and public transportation vehicles will trend toward electrification in the coming years [97]—a welcome development that will help reduce global dependence on petroleum-derived liquid fuels. However, other transportation industries (e.g., aviation) remain heavily reliant on liquid fuels, particularly those derived from petroleum, and will continue to rely on liquid fuels for decades to come. Additionally, electric vehicles are only as clean as the electricity used to obtain their charge, and as of 2020, more than 60% of electricity generated globally is

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derived from fossil fuels [98]. There is clearly an urgent need to accelerate the development of cleaner-burning fuels for use in sectors for which electrification is neither practical nor feasible—most notably fuels used in aviation and those used for electricity generation—and where transitions to more advanced, cleaner energy infrastructures are still decades away. A primary hurdle preventing broad realization of SAFs in the aviation sector is the significant amount of time, financial resources, and fuel volume (thousands of gallons [99]) needed to develop these fuels and attain certification. As a result, the development of low-volume, fuel prescreening methods is an active area of research [100]. A promising new prescreening approach uses IR absorption spectra of gas-phase fuels, measured using a Fourier-transform infrared (FTIR) spectrometer, to predict physical and chemical fuel properties (e.g., viscosity, initial boiling point, derived cetane number, etc.). Wang et al. developed two different strategies to successfully infer physical and chemical fuel properties from FTIR spectra, both of which use machine learning algorithms to extract latent features and patterns from the high-resolution spectra [101,102]. Although this initial work was limited to the 3-μm spectral region, subsequent, ongoing work has shown that extending the spectral region of interest to include the full 2–15 μm region greatly increases the predictive ability of the models and allows for the analysis of more diverse fuel blends. A particularly promising aspect of this work is its potential use in kinetic model development. In the recently developed hybrid chemistry (HyChem) modeling approach [103], kinetic parameters, including rate coefficients of lumped fuel pyrolysis reactions and their associated stoichiometric coefficients, are derived from shock tube and flow reactor speciation data. Observations suggest it is possible to directly correlate spectral features with HyChem parameters, thereby enabling development of new, FTIR-based kinetic models for real fuels. This approach is particularly exciting because it means that a single measurement—a fuel’s FTIR spectrum—can be used to predict not just the fuel’s physical and chemical properties, but to predict ignition and flame propagation characteristics and pyrolysis and oxidation products as well (see Fig. 1). This new approach leverages chemistry monitoring data, broad spectral analysis and machine learning to greatly accelerate the drop-in fuel development process for both liquid and gaseous fuels.

3.1.3 2030 and beyond: Sensors for energy and propulsion systems using various low-carbon fuels Looking to the longer-term future, advancements in chemistry sensing and monitoring will likely be needed in three areas: (1) To enable next-generation energy and propulsion systems to accept fuels derived from a variety of feedstocks, (2) to enable widespread use of hydrogen-rich fuels, and (3) to enable low-cost, real-time monitoring of hydrogen. Omnivorous energy and propulsion systems: For sectors where complete defossilization is expected to take decades, innovation will be needed to develop propulsion systems capable of accepting fuels with slight compositional variance, derived from a wide range of feedstocks. These kinds of “omnivorous” energy or

3 Results: 1+13 visions

FIG. 1 Schematic illustration of the workflow for a potential prescreening tool, capable of predicting chemical and physical properties as well as combustion behavior, based solely on a real fuel’s FTIR spectrum.

propulsion systems will likely be necessary to optimize fuel production efficiency and minimize added emissions due to long-distance fuel transport; ideally, fuel feedstocks abundant to a particular region would be leveraged to produce fuel for that region. In practice, an omnivorous energy or propulsion system will only be possible through advancements in sensors, chemistry monitoring, and control systems. First, a fuel characterization sensor, similar in concept to the FTIR-based prescreening tool described previously (e.g., [104]), would be needed upstream of the system’s combustion chamber to enable real-time prediction of the fuel’s combustion behavior. This predictive data would feed into a control system that governs fuel and oxygen/air control, as well as combustion timing. Next, in situ monitoring of key markers or product species (e.g., unburned fuel, oxygen, carbon monoxide) would be used to assess combustion efficiency, enabling real-time adjustment of fuel/air flow and/or combustion phasing to optimize fuel consumption. While feedback control systems of this kind already exist in everyday vehicles (for example, O2 sensors in cars/trucks [105]), it is the predictive fuel performance aspect of this system that would be revolutionary and would ultimately lead to broader adoption of fuels produced from sustainable feedstocks. Hydrogen-rich fuels: The promise of a hydrogen economy has received much attention recently, yet significant challenges stand in the way of this paradigm shift becoming a reality. Hydrogen is difficult and costly to transport safely, it is produced primarily via steam-methane reforming (an electricity- and water-intensive, CO2-producing process [106]), and its combustion characteristics (e.g., burning velocity and ignition delay time) are approximately an order of magnitude faster than those of current fuels [107], foreshadowing significant complications in the deployment of hydrogen as a fuel in practical combustion devices. One potential solution to the indicated challenges, among others, is to deploy hydrogen-carrying fuels instead of pure hydrogen. Ammonia, for example, is a promising hydrogen carrier that is easy to store and transport and exhibits thermodynamic properties similar to propane

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FIG. 2 Simulated ignition delay times for stoichiometric hydrogen (H2), ammonia (NH3), a natural gas surrogate (1% C3H8, 3.5% C2H6, 95.5% CH4), and a blend of 5% H2/95% NH3 at 20 atm, using the NUIGMech 1.1 kinetic model [109].

[108]. Ammonia by itself is not a suitable hydrocarbon fuel replacement, due to its slow burning velocity and ignition delay time [108], but mixtures of ammonia and hydrogen have been shown to behave similarly to conventional hydrocarbon fuels (see Fig. 2). Even so, heightened NOx formation is anticipated in the oxidation of ammonia, meaning additional aftertreatment may be needed to mitigate emissions. Overall, innovations in fuel reforming technology will likely be necessary to optimize partial or complete conversion of hydrogen-rich fuels to hydrogen, and chemistry monitoring diagnostics will play an important role in assessing the validity of these new technologies and their associated emissions. Real-time H2 monitoring: With hydrogen playing an increasing role in the energy landscape, the ability to measure and monitor hydrogen composition will become paramount. Direct measurement of H2 is possible using a variety of methods, most of which are based on gas sampling or point measurements using catalytic, thermal conductivity, or resistance-based techniques [110,111]. H2 is a particularly challenging species to measure optically, due to its diatomic, homonuclear structure. Laser-based diagnostics that have succeeded in the measurement of H2 include cavity-enhanced and scattering techniques. However, most of these approaches are too costly, too large, or insufficiently rugged for deployment in everyday energy and propulsion systems. Recent advances in H2 detection technology (e.g., combined LAS and wavelength modulation spectroscopy [112] and plasmonic metal-polymer hybrid nanomaterials [113]) have yielded promising results. However, there is still need for a cheap, compact, real-time H2 sensor to guide the upcoming integration of H2 into the energy infrastructure.

3 Results: 1+13 visions

3.2 Johan Zetterberg: Combinations—A seed for change? 3.2.1 Status 2021: Cross-fertilization from combustion diagnostics to catalytic processes In the face of climate change and recent reminders thereof, it is more vital than ever to take new approaches and seek new avenues in the combustion arena. Research in combustion science has a long and very successful history and attacks an immensely complex and multifaceted problem. We have come a long way to understand the fundamentals both theoretically and experimentally, but one of the most impressive hurdles having been overcome is that of getting researchers from so many disciplines to work together. The whole chain from fundamental chemists and physicists to very applied engineers, in academia and industry, have together pushed the frontier for both, new fundamental science and direct integration into advanced combustion devices, contributing to a better society and more energy-efficient processes. This successful collaboration and the habit of interdisciplinary work is what I truly believe is needed to move forward faster. Being a physicist by training and having worked on the development of laser and optical diagnostics to study combustionrelated phenomena during my PhD research, the daily interaction with chemists and mechanical engineers, modelers and other experimentalists made me quickly realize that relying on the expertise of others made me grow in my own niche and increased my understanding of the respective phenomena. This collaborative environment guided my next step, leaving the direct connection to combustion and steering toward heterogeneous catalysis and surface science. By using in situ techniques that were developed in the combustion community, such as planar laser-induced fluorescence (PLIF) [114,115] and degenerate four-wave mixing [116], new insights into the catalytic process and the interface region between the solid catalyst surface and the gas were attained. For example, new understanding was gained by imaging the gas phase over the catalytically active surface and by spatially resolving where on the surface the reaction begins and how the gas phase distribution in the reactor changes with the temperature and activity of the catalytic sample [117]. Such approaches certainly also raised awareness in the community of the actual conditions close to the surface in which measurements are performed [117,118]. Combining these techniques with surface diagnostic methods such as high-energy surface X-ray diffraction (HESXRD) [119] to study the surface structure as well as polarization-modulated infrared reflection-absorption spectroscopy (PM-IRRAS) [120] to measure adsorbates on the surface—simultaneously or sequentially but at the same conditions—offers new insights on cause and effect of problems, for example. The surface-science domain of catalysis has, over the last decades, moved toward realistic pressures. The use of electron-based diagnostic techniques to determine structure and adsorbates on the surface such as low-energy electron diffraction (LEED) and X-ray photoemission spectroscopy (XPS), have historically limited the pressure range for surface scientists, but technical advances such as ambient pressure XPS (AP-XPS) and hard X-ray photoelectron spectroscopy (HAXPES) have

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changed this situation, and the Polaris beamline at Petra III in Hamburg holds the world record for XPS on CO oxidation up to 1 bar [121]. With increasing pressure, new challenges are introduced. Fluid dynamics then starts to dictate the sample environment with mass-transport-limited reactions and concentration gradients [122] that directly influence the sample surface and its activity. As a consequence, it becomes vital to measure several parameters simultaneously by combining experimental techniques. In the combustion community, this has been the aim for decades, especially when cause and effect problems are to be solved. However, this multi-pronged approach has been as yet less followed by the surface science community. In any case, it is highly important to link an atomistic understanding of catalysis and its practical applications.

3.2.2 Preview for 2026: Combining gas-phase chemistry diagnostics and surface science In the upcoming years, the continuation of combining different techniques will become even more valuable, both in laboratory environments and at large-scale facilities such as synchrotrons. As an example, the HIPPIE beamline at the MAX IV synchrotron in Lund offers the possibility to combine PM-IRRAS with AP-XPS [123]. However, for this development to push forward faster, the user base for these facilities should be even broader; also, the users must bring in new techniques and expertise to support the continuous development of the endstations. User demands would help upgrade the infrastructure with complementary techniques, many of which can also be used in home laboratories—maybe combined with other techniques—for pre-studies, efficient planning of expensive measurements at large facilities and also as diagnostics on their own. Users at these beamlines come from different communities, increasing the chance of cross pollination between areas which paths would otherwise never cross. Inspired by the Combustion Research Facility at Sandia and their mobile endstation [124] that is used by several groups to study kinetics at the Advanced Light Source in Berkeley, we in Lund are working on this approach for catalysis and electrochemistry [125]. Our initial measurements combined PLIF to image gas phase species close to the surface with 2D surface optical reflectance (2D-SOR) [126,127] to follow oxide formation and HESXRD at the Petra III synchrotron in Hamburg to determine the surface structure; the feasibility and potential of this approach was demonstrated [128,129] and led to the creation of an in-house combined set-up for PLIF, 2D-SOR, PM-IRRAS and IR thermometry to follow the evolution of the reaction on the sample. The resulting set-up is mobile to enable use of some or all the diagnostics combined at a synchrotron, to take advantage of the synchrotron’s unique techniques and capabilities, and to access as many parameters as possible simultaneously. This combination of techniques is not dependent on the research area: Complex fields that experience transport processes, kinetics and sometimes non-thermal equilibrium will all rely on in situ measurements of several parameters simultaneously to disentangle the intricate details in their respective processes. With such research infrastructures as described above, and when given opportunities to meet, we may be on our way toward a greater mix between disciplines in the future. Let us speculate on what that future might hold.

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3.2.3 2030 and beyond: Synergy and collaborative research to achieve carbon neutrality Recent years have shown an increased focus on interdisciplinary work in different areas. The level of knowledge in the disciplines is too deep and the tools used are too varied to be covered by one research group. In the future this situation will be even more prominent, as new technologies, techniques and models will be more complicated and often expensive. For a carbon-neutral future I believe that a greater overlap between several disciplines is needed. Combinations such as combustion/plasma [130], combustion/ catalysis [131] and plasma/catalysis [132] are “new” areas that hold great potential and we have only scratched the surface. Local, small-scale production of energy and chemicals can potentially cut down emissions where, as an example, a farm provides its own fuel and artificial fertilizer by reforming methane to convert it (via hydrogen) to methanol and (with nitrogen) to ammonia using plasma-enhanced catalysis at reasonable temperatures and pressures. The question is—how do we get there? In all above-mentioned combinations, the same or similar diagnostic tools can be used. Tools developed to study chemical species or flows in combustion can be used (and are used) to study catalysis and plasma processes. Surface-related techniques, developed in surface and materials science, can be used to understand the surfacerelated aspects in combustion and plasma environments, and the combination of the techniques can unveil the connection and synergy of the different phenomena. To act toward the UN sustainable development goals [1], however, the interaction of disciplines is not enough, but connections between fundamental research, applied research and industry within each discipline must also be strengthened—we need to get fundamental research through an implementation stage to the end user more quickly. Research centers and collaborations where the connection between disciplines and the chain from fundamental research to industry are represented and where these can work together in mutual respect and understanding will be crucial in the transition from a fossil-based to a carbon-neutral society, as illustrated in Fig. 3. Researchers working with chemical diagnostics therefore occupy a unique position. They have worked with interdisciplinary approaches, often within successful collaborations with engineers, modelers, chemists, physicists and the industry, and they have often solved communication difficulties between different cultures. When techniques are combined so are people, creating larger interaction regions. If gazes can be lifted and views broadened, researchers and their techniques can be the glue that ties these different areas together to help facilitate change.

3.3 Deanna A. Lacoste: Diagnostics of charged and excited species in combustion 3.3.1 Status 2021: Analyzing plasma-enhanced combustion For the purpose of monitoring combustion processes, charged or excited particles are often used, for example in chemiluminescence imaging or in flame detection by ionic probes. However, compared to the ground state species involved in combustion chemistry, the knowledge of these transient and energetic species, and their impact on combustion, is minimal. In combustion chemistry, the common practice is to

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FIG. 3 Schematic illustration of collaboration between areas and the connection between fundamental research, applied research and industry. Increased interactions between disciplines are key, the largest hurdles are lack of communication and incentives.

consider atoms and molecules in their ground states, even though in reality combustion phenomena involve, if only in minor amounts, charged particles (e.g., electrons, H3O+), and excited ones (e.g., OH*, CH*). With the broadening of combustion conditions to address environmental issues, their role could become significant, especially under extreme thermodynamic conditions. In plasma-assisted combustion (PAC), with the primary concept to enhance combustion by means of an electric field, thus using a minimum amount of energy and causing fewest pollutant penalties, the role of charged and excited particles is critical. Their quantification and the understanding of their contribution on the flame-plasma coupling has attracted the effort of the PAC community, using experimental, modeling and numerical tools [130]. Experimentally, measurements of species both relevant to plasma and combustion chemistry, such as OH, CH, O or H, have been targeted. However, due to the lack of reliable and sensitive measurement techniques, the excited states of these species could not be quantified. For example, in Del ContBernard et al. [61], we used the PLIF technique on several rotational lines of CH and OH radicals to determine the impact of non-equilibrium plasma discharges on a laminar methane-air flame. Fig. 4 illustrates these measurements, with examples of PLIF images obtained for the base flame (left column) and for the flame enhanced by plasma (right column). Row (a) presents the CH results, while rows (b) and (c) allow the comparison of OH PLIF fields obtained for excitation of the OH (A, v’¼0, O12(4)) and the OH (A, v’¼1, S21(2)) lines, respectively. While the former

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FIG. 4 Examples of CH and OH PLIF images for different excitation lines, without plasma discharges (left column) and with non-equilibrium plasma discharges (right column). Color scale is arbitrary, but intensities are consistent. Reproduced from D. Del Cont-Bernard, T.F. Guiberti, D.A. Lacoste, Laser-induced fluorescence investigation of the chemical impact of nanosecond repetitively pulsed glow discharges on a laminar methane-air flame, Proc. Combust. Inst. 38 (2021) 6641–6649.

is visible in the flame and in the burned gases only, the latter is also visible in the plasma discharge filament, ahead of the flame tip (see Fig. 4c). This result highlights that there are excited species in flames, and that these species are not necessarily in thermal equilibrium. With the currently available diagnostics, we could not access quantitative results from this experimental campaign. Charged and excited species are usually unstable at ambient conditions; therefore, they must be measured in situ, i.e., in the reactive environment where they are produced. Typically, their number density is relatively low, and their spatial distribution might be narrow. For all these reasons, the most appropriate diagnostics to investigate these species are spectroscopy-based laser techniques with excellent spatial and temporal resolution.

3.3.2 Preview for 2026: Diagnostic needs in systems with charged and excited particles To fully understand the effects of charged and excited particles in combustion, in addition to direct measurements of targeted species, measurements of rotational and vibrational temperatures [133,134] as well as quantification of the local electric

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field [135,136] are necessary. Indeed, the reduced electric field (the electric field divided by the number density of particles) is a key parameter in charged particle chemistry. Implementation of these techniques in reactive and unsteady environments such as detonation fronts or turbulent flames at elevated pressure is challenging and requires further work. In the coming five years, it would be very beneficial to reach the stage of quantitative measurements of the spatial and temporal evolution of the electric field and temperatures in unsteady combustion. By joining our effort with those of chemical modelers, the results obtained would allow us to answer the question of the significance of charged particles and excited species in combustion chemistry. For example, it would then be possible to establish the adequate level of chemical kinetic modeling for quantitative prediction of detonation properties. For electric field (Efield) measurements in combustion environment, one of the most promising techniques is electric-field-induced second harmonic (EFISH) generation. In short, this technique is based on the ability of electric fields to generate second-harmonic light from an incident source. The intensity of the second harmonic signal is proportional to the square of the electric field and the square of the incident light intensity. By using short (picosecond or femtosecond) laser sources, this technique enables measurement of unsteady electric fields. Set-ups for this technique are quite simple. However, there are challenges in calibration and deconvolution procedures. In order to reach quantitative Efield measurements from EFISH signals, further development is necessary for turbulent and/or stratified combustion. There are several laser techniques to measure the temperature of reactive flows. In combustion and in PAC, femtosecond and picosecond coherent anti-Stokes Raman spectroscopy (fs- and ps-CARS) have been used to measure both the rotational and vibrational temperatures of nitrogen [137]. These techniques are reliable and precise but extremely expensive and difficult to operate. For example, in 2021, only a few combustion laboratories in the world have direct access to an fs-CARS system. To generalize their use to a broader pool of scientists, development of cheaper and more robust lasers is necessary.

3.3.3 2030 and beyond: Combinative diagnostics for “augmented” combustion systems While the optimization of 4-stroke gasoline engines spanned over more than a century, the next generation of combustion engines will not have this luxury of time to achieve high efficiency, no CO2 emissions, low pollutant emissions, and competitive economic profitability. With the arrival of new thermodynamic cycles, the emergence of new fuels and the development of “augmented” combustion strategies such as PAC, the current knowledge of turbulent hydrocarbon flames at moderate pressures will not be of much help. If the next few years of research confirm that for future combustion systems, charged or excited species cannot be neglected, diagnostics commonly used in non-equilibrium low-temperature plasma physics would be very beneficial. Langmuir probes could become a common tool to measure electron temperature and electron density in combustion, and a more systematic analysis of the light from

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the reaction zone, by optical emission spectroscopy, could be added to the current toolbox of combustion diagnostics. To accelerate the understanding of new combustion phenomena, combining multiple diagnostics during a single experiment is the way to go. For example, simultaneous, single-shot OH, H2O, O2, H2 and N2 imaging of a carbon-free non-premixed turbulent flame have been recently performed [138]. The diagnostics used were PLIF and planar Raman spectroscopy. From the simultaneous imaging of these species, for the first time, mixture fraction, temperature, and scalar dissipation rate images could be obtained in flames featuring differential diffusion. However, the cost and complexity of simultaneous laser diagnostics is a strong limitation to fast progress. The development of national or international structures (i.e., laboratories, institutes, or research centers), dedicated to reactive flow diagnostics would be very useful. Having access to simultaneous measurements of temperature, pressure, electric field, and targeted species would allow the combustion community at large to focus on key questions for a carbon neutral future. In the meantime, scientists developing advanced diagnostics in these laboratories or institutes would get a stronger impact than just showcasing their solutions on basic combustion experiments. Similar to the management of large equipment (e.g., synchrotrons), reactive flow measurement laboratories could be accessible through project selections or funding-dependent time allocated. Ideally, they would offer various combinations of techniques based on laser absorption, fluorescence, scattering (Mie, Raman, Rayleigh, Thomson) and/or emission, covering a large spectral range from vacuum ultraviolet to microwave. Finally, another important point to accelerate deep understanding and discoveries is to combine approaches. This requires a platform where scientists can first, learn a common language, and second, work together in solving complicated problems. In the recent past, workshops like the TNF workshop (www.tnfworkshop.org) have been extremely beneficial for the understanding of turbulent flames, bringing together experts in experimental combustion, optical diagnostics, modeling, chemistry and numerical simulations. Similar workshops for carbon-free fuels, plasma-assisted combustion, and combustion at extreme conditions could make the difference in the success of new combustion-based energy conversion devices.

3.4 Peter Fjodorow: Intracavity absorption spectroscopy: Combining robustness with highly-sensitive and broadband detection 3.4.1 Status 2021: Ultra-high-sensitivity diagnostics for chemical species A deep understanding of complex physico-chemical processes in such fields as, e.g., nanoparticle synthesis, combustion engines, gas turbines or shock tubes, is only possible with in situ spectroscopic diagnostic techniques that offer high sensitivity, species selectivity and high time-resolution. Precise measurements of species concentrations and temperatures, coupled with a robustness to broadband losses (originating from, e.g., light scattering and absorption by particles, or beam steering), are prerequisites for the acquisition of valid data in these harsh environments. Additionally, to unravel complex chemical reaction kinetics that are usually

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governed by various intermediates present in trace amounts only, a capability of multi-species detection is indispensable. One of the suitable techniques for these tasks is laser-based intracavity absorption spectroscopy (ICAS). In contrast to the conventional spectroscopic scheme light source ! sample ! detector, here the sample is placed inside the laser resonator. The laser light passes through the laser gain medium and the sample many times, resulting in large effective absorption path lengths, i.e., in extreme sensitivity. Broadband losses are compensated by the broadband laser gain medium, while the narrow-band losses (due to absorption by the sample) are not compensated, such that the corresponding absorption lines are directly imprinted onto the laser emission spectrum. This mechanism is based on the gain competition of laser modes (frequencies) within the homogeneous linewidth of the gain and makes ICAS ideally suitable for measurements in “dirty” environments. The use of broadband laser media also enables simultaneous measurement of multiple absorption lines, which becomes especially important in situations with so-far unknown species compositions. Such measurements can provide the species’ concentrations (from absorption strengths), the total pressure (from line broadening), as well as the temperature (from the relative absorption from different quantum states). Furthermore, ICAS can be implemented for spectroscopic studies of strongly broadened absorption lines, e.g., in high-pressure environments or in liquids. The latter point is particularly interesting for green energy technologies, such as hydrogen production and battery research (e.g., monitoring of electrolyte degradation). Finally, the achievable time resolution with ICAS can be in the nanosecond range, enabling studies of fast processes. Since ICAS was proposed about five decades ago at the P.N. Lebedev Physical Institute in Moscow [139], it has been the subject of several reviews [140,141] and was employed in a wide range of hostile environments, including simultaneous concentration measurements of various molecular species in flames [142], identification and specification of chemical reactions in flames [143], simultaneous determination of temperature, pressure and concentrations of gaseous samples in shock tubes [144], measurements of absorption cross-sections of gas-phase FeO in a shock tube [145] as well as monitoring of single transient processes in plasmas with microsecond time resolution [146]. The ultra-high sensitivity of ICAS is related to its extremely long effective absorption path length. The highest sensitivity with ICAS was achieved with a dye laser and was comparable to a single-path absorption length of Leff ¼ 70,000 km [140]. Although other lasers show lower effective absorption path lengths, they enable comparable or even higher sensitivities once they address stronger rotational-vibrational transitions located in the near-infrared (NIR) and especially in the mid-infrared (MIR) spectral regions.

3.4.2 Preview for 2026: Developments for the mid-infrared regime Chasing ever lower detection limits, a recent trend observable in spectroscopy is the exploration of the MIR spectral range, mostly by using quantum cascade lasers (QCLs). For ICAS this route has also tremendous potential for significant progress.

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QCLs, however, generally show low sensitivities with ICAS, limiting the effective absorption path length to less than 50 m [147]. The limiting mechanism is the typically strong four-wave mixing, which is desirable for frequency-comb generation, but is highly detrimental for the ICAS process since it undermines the necessary mode competition [140]. However, recent developments of broadband MIR solid-state [148] and glass lasers [149] are expected to promote the conquest of the MIR by ICAS. In contrast to QCLs, these types of lasers enable sensitivities of up to 107 m [150]. The most promising MIR solid-state lasers for ICAS applications are based on Cr2+- and Fe2+-doped chalcogenide crystals. The chalcogenide hosts feature broad infrared transparency, high thermal conductivity, low phonon cut-off, and low optical losses. Besides that, strong electron-phonon coupling between dopants and host matrices leads to significant broadening of the amplification bands, resulting in ultrabroad MIR tunability that exceeds 1000 nm, with individual emission widths of 10– 100 nm. In particular, when doped with chromium, such lasers provide access to the spectral range of 1.9–3.6 μm [151,152], while iron-doping allows to cover the range of 3.5–6.8 μm [148,153]. Since these spectral regions contain strong absorption lines of a variety of species, the corresponding laser sources are particularly interesting for various tasks of chemical diagnostics and monitoring, including medical, environmental, security and combustion applications of ICAS. Most of the published work on Cr2+- and Fe2+-doped chalcogenides was primarily focused on optimization of different laser parameters, whereas only few contributions investigated applications with ICAS. In particular, several systems based on Cr:ZnSe have been demonstrated, e.g., [154], while only recently a promising ICAS system based on Fe:ZnSe has been developed [155]. After a few further improvements of the latter system, extremely low detection limits of the order of partsper-quadrillion (ppq) are expected. Another class of promising MIR lasers is based on rare-earth-doped chalcogenide glasses. Compared to transition-metals (e.g., Cr and Fe), rare earths as dopants have the advantage of long upper-state lifetimes (ms instead of μs), which reduces the requirements on pump power/energy. Furthermore, compared to crystalline materials, glasses enable the fabrication of fibers, with the advantages of diffractionlimited beam quality and compact design. Nevertheless, only a recent progress in the synthesis of low-loss chalcogenide glasses [156] enabled first demonstrations of corresponding rare-earth glass lasers in the 4–6 μm range [149,157]. These developments are expected to have a high impact on ICAS-based diagnostics. It becomes clear that the potential of MIR solid-state and glass lasers is enormous, but barely exploited up to now. Therefore, the adaptation of emerging laser technology for ICAS measurements in the MIR is expected to become a dominant research direction.

3.4.3 Beyond 2030: Miniaturization for broad-band, time-resolved, high-sensitivity multi-parameter measurements Future chemical diagnostics challenges will require compact, efficient and versatile tools. The route for the corresponding ICAS transformation will therefore be directed toward miniaturization and employment of emerging innovations. Besides the

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above-mentioned technologies, different concepts from other research fields will be implemented, such as e.g., artificial intelligence and machine learning for data acquisition and evaluation, or novel MIR detectors. Several ideas for future ICAS systems are sketched in the following. A particularly interesting concept is the development of a fully fiber-based ICAS system that includes a tapered section for evanescent-field spectroscopy. In general, the fiber geometry offers several unique advantages. First of all, a fiber can be coiled up to a diameter of about five centimeters, thus enabling very compact experimental set-ups. Second, fibers facilitate highly modular laser systems, since different active fibers can be spliced between passive fibers with appropriate coatings, i.e., highlyreflective or anti-reflective. Especially time-resolved ICAS diagnostics can further benefit from the fiber geometry due to the possibility of simple increase of the resonator length by splicing long pieces of passive fiber. This concept allows low-noise single-shot measurements and has already been demonstrated in the NIR [144,146]. However, to maximize the detection sensitivity, it must be transferred to the MIR, and for this purpose, the above-mentioned rare-earth-doped chalcogenide glasses are particularly promising. Finally, fibers enable evanescent-wave spectroscopy in a section that is drawn (tapered) thinner than the light-field diameter [158]. By splicing such a section (or multiple sections) between corresponding passive and active fiber elements, an all-fiber ICAS system could be constructed, enabling intracavity measurements without open-path sections. Such a system would be ultimately compact and alignment-free. It would be especially suitable for diagnostics in the liquid phase, e.g., in situ monitoring of electrolyte properties of novel battery materials. Another interesting concept is the development of ICAS systems based on compact dye lasers. Traditional dye lasers are bulky and unpleasant to maintain, primarily due to the requirement of dye-liquid circulation (to ensure depopulation of triplet energy levels), and the typically large pump lasers. Recent developments, however, show that compact and efficient dye lasers can be realized by replacing the dye liquid with a rotating dye-polymer disc [159] and employing recently emerged high-power blue laser diodes as pump sources [160]. Furthermore, novel dyes are being developed [161], such that compact dye-laser based ICAS systems can become powerful spectroscopic tools in the visible spectral range. Although at first sight the visible range seems less attractive than the infrared, it has enormous potential for diagnostics of various compounds, such as e.g., metal oxides. Among others, iron oxides (FexOy) are particularly promising nanoparticles that are already used e.g., for magnetic materials and in medicine (being non-toxic). However, the controlled synthesis of specific FexOy nanoparticles is limited due to the insufficient understanding of the underlying mechanisms [162]. And this is where dye-laser based ICAS can make a significant impact. A first demonstration of this capability has been reported recently: Absorption cross-sections (and associated oscillator strengths) of gas-phase FeO have been measured for the first time [145]. Fig. 5 shows the corresponding single-shot cross-section data, including assignment of the involved transitions.

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FIG. 5 Single-shot absorption cross-section spectrum of gas-phase FeO measured in a shock tube at T ¼ 2200 K, p ¼ 1.3 bar and Leff ¼ 260 m. The assigned transitions with their quantum numbers J are indicated by vertical lines. Adapted from P. Fjodorow, M.R. Lalanne, D. He, M. Nanjaiah, A. Pilipodi-Best, V.M. Baev, S. Cheskis, J. Herzler, M. Fikri, I. Wlokas, C. Schulz, I. Rahinov, Determination of gas-phase absorption cross-sections of FeO in a shock tube using intracavity absorption spectroscopy near 611 nm, Proc. Combust. Inst. 38 (2021) 1637–1645.

These results highlight the capability of ICAS to enable broadband, timeresolved and highly-sensitive measurements in harsh environments. This study has been performed with a homemade old-fashioned liquid-dye laser, with the associated problems mentioned above. The development of compact and easy-to-use ICAS systems based on polymer-dye lasers (but also on fiber and crystal lasers) will significantly simplify highly-sensitive multi-parameter measurements in different environments. As a consequence, ICAS will make a valuable contribution to a carbon-neutral future by generating new insights in such fields as nanoparticle synthesis, battery research and hydrogen production.

3.5 Steven Wagner: Bringing light to complex reactive processes 3.5.1 Status 2021: Multiplex absorption sensors for industrial applications While existing chemical production and energy conversion processes are being optimized regarding efficiency and pollutant emission, new ways to produce chemicals or convert energy are being developed at the same time. Increasing demands on climate neutrality and environmental safety require more detailed understanding of such processes to prevent unwanted emissions—e.g., formaldehyde emissions from

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syn-fuels [163]—or other undesired impacts, such as material fouling [164]. Many next-generation processes employ high temperatures, high pressures or even corrosive atmospheres (e.g., ammonia or iron combustion). Upscaling to industrial production facilities and control in daily use demand new sensors which can withstand harsh environments while offering reliability, sensitivity and accuracy for long operation times [38]. In our group, we develop such sensor systems based on tunable diode laser absorption spectroscopy (TDLAS) [165] and its modifications to measure gas species mole fractions, gas temperatures, gas distributions or liquid film parameters [166]. This method is robust against process disturbances like background emission (from heated walls) and broadband absorption (from particles), can realize high temporal (up to MHz) as well as spatial resolution (using linear hyperspectral absorption spectroscopy approaches [167]) and can be integrated into almost any process environment to measure important quantities in situ with high accuracy. A main goal—and simultaneously the greatest challenge—is the transfer of measurement accuracy from a laboratory environment to a real industrial process without losing out on all other advantages. Importantly, the accurate analysis of highly reactive chemical processes relies strongly on fast in situ detection of relevant parameters [168] as demonstrated in the example in Fig. 6. Here, all species mole fractions were obtained simultaneously from a single-sensor set-up during an engine test cycle, and the approach can thus prove the earlier occurrence of the NO maximum compared to the temporally well-correlated increase of CO, CH4 and NH3 less than 3 seconds later. Using different, decoupled sensors could easily lead to time shifts between the measurements and thus to misinterpretations of the process. The demand for further pollutant reduction and improved chemical reaction efficiency increases the need for a closer view into the chemical reactions and therefore necessitates detection of continuously smaller amounts of certain gas species (e.g., NxOy or CxHy), requiring strongly improved measurement sensitivity. Currently, a preference is seen in absorption spectroscopy to shift from the near-infrared (NIR) to the mid-infrared (MIR) spectral range where stronger, mostly fundamental, absorption bands are located. However, many technological advantages of diode lasers are not or less available in the MIR. Main drawbacks in the MIR range are underperforming photodiodes and cameras and as yet an unavailability of robust photonic fiber devices (e.g., fiber-pigtailed laser, fiber combiner/splitter). To compensate for such disadvantages, individually-manufactured devices may be constructed upon consumer request—at increased sensor cost, however—or a direct but challenging attachment of the lasers to the process (no fiber delivery) may be chosen. More detailed investigations of complex processes also require more simultaneously acquired parameters, including mole fractions, temperature, pressure, etc. The number of species is limited when using one laser per molecule, while the interaction of molecules in a complex gas matrix cannot be described fully with current spectroscopic models, considering e.g., line broadening effects. Recent trends to a more efficient use of the spectroscopic information in a single spectrum [169] can provide more advanced diagnostics with less hardware investment, however. The .

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FIG. 6 Simultaneous single-sensor measurement of several exhaust gas species at the tailpipe of a gasoline engine test stand that permits temporal distinction between NO formation and apparent later emission of CO, CH4 and NH3. Adapted from L. Biondo, H. Gerken, L. Illmann, T. Steinhaus, C. Beidl, A. Dreizler, S. Wagner, Advantages of simultaneous in situ multispecies detection for portable emission measurement applications, SAE J. STEEP 2 (2021), https://doi.org/10.4271/13-02-02-0010.

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information about the process is encoded in the spectrum—and the more spectroscopic information is extracted from one spectrum, the more process information can be determined. Therefore, more fundamental knowledge is needed about interaction of the chemical process environment and spectroscopic parameters, based on new and advanced evaluation models or algorithms. Artificial intelligence (AI) in its current state can only be a transition technology to extract more information from the measurement data. AI for laser spectroscopy is currently only a brute force, black box approach and cannot provide higher accuracy or better performance compared to physical or semi-physical approaches; consequentially, it should only be used if all other tools fail.

3.5.2 Preview for 2026: Robust sensor development for complex chemical compositions is not only a hardware issue The sensitivity of a sensor for species measurements in complex chemical processes will be further increased by continuing to shift laser absorption spectroscopy to the MIR relying on new developments in fiber and detection hardware. More robust quantum cascade lasers (QCLs), with a performance closer to already robust distributed feedback (DFB) diode lasers or inter-band cascade lasers (ICLs) will be available. This new QCL generation will enable use of the wavelength range above 6 μm. Additionally, the intra-pulse mode approach [170] will provide high-speed and high-sensitivity opportunities also in industrial applications (see Fig. 7). For this

FIG. 7 Fiber-coupled process interface of laser and detector for MIR inspection of reactive processes.

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purpose, the QCL should work at laser dye temperatures close to room temperature (20–80 °C), with low power consumption and preferably, direct fiber coupling. Insight into reactive systems, regarding environmental protection as well as optimization of energy conversion and chemical processes, always requires exact species identification. The expansion of in situ measurement methods (like absorption spectroscopy) to a more selective diagnostic is necessary. The discrimination of the different species in a mixture of compounds with formulae NxOy or CxHy by conventional physical models based on quantum mechanics parameters will continue to fail due to computational limits. New scientific approaches and developments of sophisticated algorithms will lead to the use of semi-physical evaluation models and the application of artificial intelligence on data extraction. But especially for AI, a deeper understanding of the effect of the machine learning algorithms is necessary to preserve the proven robustness of laser-based methods. Some publications already show interesting approaches to apply AI to spectroscopic problems [171,172], covering only the first steps, however, compared to conventional methods. There is always a range of possible solutions in the results of a neural network. Deeper understanding in the sense of spectroscopy means the understanding of input layer filter effects on the raw data, the implementation of physical constraints to limit the solution space and the interpretation of the residual results. A more detailed uncertainty discussion of AI approaches based on strong research efforts with a focus on spectroscopy (not on algorithm development) can lead to an increasingly trustworthy use of AI-based brute force methods. Since no measurement method can measure all process parameters or physical conditions (e.g., gas, liquid, particulate matter), combining or merging several methods will gain more attention. The correlation of quantities in time and space requires the simultaneous and synchronous application of different measurement principles. Here the transfer of more measurement methods to the robustness level of absorption spectroscopy will be challenging, but first steps will be expected at this point.

3.5.3 2030 and beyond: Spectroscopy needs advanced data evaluation strategies The shift toward more sensitive spectral ranges will continue based on new developments of lasers, photodiodes and photonic fibers. This will bring absorption spectroscopy not only deeper into the MIR, but also to the far-infrared (FIR) and into the ultraviolet (UV) spectral ranges. Since absorption measurement sensitivities also rely on the absorption path length, the advances in MIR, FIR and UV will reduce the required path length and therefore enable the development of micro-sensor devices that can be distributed in a process environment as sensor network. Miniaturization will also show further advances, like increase of robustness, higher availability and sustainability. Integrated in mobile systems, micro-sensors can be used to identify pollutant sources. They can be integrated into fuel cell systems (stationary or mobile) to optimize the operation conditions and to realize transient control loops for higher efficiency.

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Tomographic systems based on laser absorption spectroscopy will also be used as sensors for large-scale chemical reactors and power plants. The transition from fossil fuel to synthetic fuels or hydrogen leads to new challenges in the stable and efficient operation of chemical and energy conversion processes. With next-generation sensors and fiber networks for tomographic reconstruction (2D or 3D), the diagnostic of transient processes and the control of the process boundary conditions (e.g., wall temperatures, fuel rate) will enable the operation of processes at their stability limits or maybe beyond. The huge amount of data acquired by such measurement systems cannot be evaluated using today’s conventional strategies. New data mining approaches and hybrid algorithms, between physical model and artificial intelligence, will extract the parameters of interest directly during the data acquisition. These advanced evaluation procedures will use data harvesting for process control but keep raw data sets for detailed investigation. Self-documenting software together with sophisticated metadata protocols will enable data reuse by external research institutes or citizen science. Such crowd-based reuse, together with advanced sensor networks, will assist identifying climate- or environment-relevant sources or sinks of pollutants and greenhouse gases. The identification of pollutant sources can thus be more reliably compared with environmental sensors far away from the process.

3.6 Liming Cai: Future model development driven by advanced combustion diagnostics 3.6.1 Status 2021: Theory-informed and data-driven model development The co-optimization of fuels and engines opens the unprecedented possibility to enhance combustion performance and to reduce pollutant emissions simultaneously. For this, a deep knowledge about fuel combustion behaviors and underlying reaction kinetics in the form of chemical kinetic models is an important prerequisite. Conventionally, the fuel-specific chemical mechanisms are generated following the concept of reaction class and rate rule, and upon a well-validated base mechanism of small molecules. The concept of reaction class and rate rule derives the elementary reactions and specifies their rate parameters based on available knowledge about kinetically similar species and reactions. While this approach is valid due to the analogies between such molecules, it introduces inevitable uncertainties into the model parameters, which propagate into the uncertainties of model predictions. Therefore, the models must be validated with measurements conducted in fundamental laboratory configurations covering a wide range of initial conditions; models are then commonly improved by modifying the rate parameters of sensitive elementary reactions for better agreement between model prediction and experimental data, as widely demonstrated in the literature [173,174]. Reliable and accurate data form the backbone of model development, which is one of the major contributions of combustion diagnostics. Various pioneering studies [74,173] have aimed to develop theory-informed models by estimating the parameters of all species and reactions included in the

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models using quantum chemistry methods. Nevertheless, these calculated values are also associated with uncertainties, whose joint effects can be significant in terms of model prediction. In this regard, experimental data are highly valuable to constrain model parameters inversely. With the rapid development and application of advanced diagnostics techniques, the detection of previously unobserved intermediates and the discrimination of isomers have provided significantly deeper insights into combustion systems [32]. More comprehensive datasets become available, providing unique information for model development and validation. Nevertheless, this also leads to increased efforts of the conventional model development and refinement, since the kinetic knowledge improved by diagnostics measurement and theoretical exploration has contributed to a growing complexity of chemical kinetic models [173]. Automatic model optimization is a promising solution to replace the conventional model refinement based on the time- and resource-consuming manual tuning [175,176]. It calibrates the rate parameters within their uncertainty limits to achieve good agreement between model and data. A number of studies have demonstrated its capability to improve the model prediction accuracy successfully by using various mathematical algorithms, including polynomials chaos expansion [177,178] and Bayesian inference [179]. In addition, research efforts have also been dedicated to enabling kinetically reasonable and appropriate model optimization, for instance, by calibrating the rate rules instead of individual reactions [179] and by taking the pressure dependence of elementary reactions into account [180]. This data-driven model development becomes especially important with growing model complexity and increased diversity of datasets for particular fuels. In addition, it also attracts increasing interest in terms of the cross-sectional application of machine learning and big-data analysis approaches in combustion research.

3.6.2 Preview for 2026: Toward accurate uncertainty assessment While advanced diagnostic methods facilitate the acquisition of more comprehensive datasets and while the automatic model optimization provides the possibilities to incorporate these datasets into the model development in an efficient manner, there are still various challenges associated with model development. As mentioned earlier, extended knowledge on the combustion kinetics increases the model complexity and size substantially. To reduce the efforts of model refinement, it is often assumed that the model prediction uncertainties are solely attributed to the uncertainties in rate parameters and thus only the rate parameters are subjected to calibration, despite the fact that a number of studies have demonstrated remarkable impact of species’ thermochemical and transport properties on the model prediction [181,182]. Although this assumption reduces the dimensionality of the model optimization problem and simplifies the research, it inevitably induces error compensation by neglecting uncertainties in thermochemical and transport properties, and it may thus cause potential misunderstandings regarding the fuel’s reaction kinetics gained from the modified reaction mechanism.

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Therefore, our recent and intended research aims to evaluate and understand the influence of species parameters on the model predictions for different targets. First, the sensitivities on the thermochemistry and transport data should be quantified to identify the key species and their parameters that significantly affect the numerical results for fundamental laboratory reactors and flames. Second, it is of ultimate importance to quantify the joint impact of species parameters on the model prediction by using uncertainty propagation algorithms. While our previous studies [182,183] have demonstrated that the prediction of ignition delay times of hydrocarbon fuels at intermediate temperatures is strongly affected by their thermochemistry (see Fig. 8), its influence on other combustion behaviors and targets, such as flame structures, remains largely unexplored. Last but not least, novel mathematical approaches are required to accelerate the aforementioned numerical investigations, for instance for an efficient calculation of parameter sensitivities. By taking the species parameters into account as well, the number of uncertain parameters and the computational costs increase significantly. The adjoint-based approach has been applied successfully in our previous work [184,185] for the simultaneous and efficient estimation of sensitivity coefficients with respect to the kinetic, thermochemical and transport parameters, considering nitrogen oxide formation in methane/air flames and laminar burning velocities of ammonia/air flames. It should be noted that the analysis of the joint impacts of reaction kinetic data with thermochemical and transport properties is also of high relevance for combustion diagnostics research, as it allows identification of the most informative experimental conditions for the uncertainty minimization of parameter uncertainties, which in turn leads to the minimum model prediction uncertainties.

FIG. 8 Model prediction uncertainties for ignition delay times of a stoichiometric diethyl ether/air mixture due to uncertainties in species’ enthalpy of formation Δhf (298 K) and in standard entropy s0 (298 K). Reprinted from F. vom Lehn, L. Cai, H. Pitsch, Sensitivity analysis, uncertainty quantification, and optimization for thermochemical properties in chemical kinetic combustion models, Proc. Combust. Inst. 37 (2019) 771–779.

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3.6.3 2030 and beyond: Identifying the most informative experiments In a long-term perspective, it is expected that—with further development and upgrading of diagnostic techniques—additional reactive intermediates, which cannot be observed currently, will be detectable and measurable with well-quantified uncertainties. This will provide, on the one hand, deeper insights into the combustion kinetics, and on the other hand, more valuable information for model development. By using automatic model optimization methods based on improved knowledge about the reaction kinetics, thermochemistry and transport properties, it can also be expected that very accurate chemical mechanisms will be developed in an efficient manner. Nevertheless, even if measurements of all possible targets and quantities are feasible, another concern arises. Are all of the measurements equally informative in terms of the reduction of model uncertainties? The information provided by different data sets and data points can be correlated [179]. For instance, one measurement may not provide additional information to another one conducted at very similar conditions. This decreases the practical value of considering all possible data for constraining the model parameters. As found in one of our recent studies [186], model prediction uncertainty in ignition delay times of dimethyl ether can be reduced by 90%, by only taking the ten experimental data points among a total of 127 measurements into account that can be identified as most informative for the uncertainty minimization by a model-based experimental design framework. Given the large diversity of potential future fuel candidates, it is desirable to obtain the maximum information with minimal investigation efforts. Besides the development of new combustion diagnostics, future measurements should thus be directed by the information on the uncertainty correlations between model parameters and experiments, in order to select the most informative measurement targets and conditions for future model refinement. Thus, important aspects to be explored in the future include the identification of the most valuable experiments and the integration of the experimental investigation and the model development into a combined and iterative process by applying advanced mathematical methods and tools [186]. The prior models can be first generated automatically based on the conventional concept of reaction classes and rate rules [187], potentially combined with novel strategies of automatized quantum chemistry calculations [74,188]. Model-based design of experiments will then be adapted to consider uncertainties in the experimental data, their correlations with parameter uncertainties and ultimately the resulting model prediction uncertainties jointly during the model development process [186,189]. Specific experiments and conditions will be identified interactively and dynamically within the model development procedure from the set of available facilities and diagnostics techniques, such that the highest and most valuable ones are selected for the model uncertainty minimization. Finally, an accurate model could be obtained after several iterative model optimization steps, which can then serve as the basis of detailed computational fluid dynamics simulations for the design of complex combustion devices. Similar approaches as described here for combustion systems can be useful for any reactive processes in a future carbon-neutral context.

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3.7 Charlotte Rudolph: Flexible polygeneration and exergy storage: A glimpse into the future from a modeling perspective 3.7.1 Status 2021: The combustion engine as a flexible chemical reactor The flexible use of combustion engines using carbon-based fuels—as, for example, natural gas—in the context of polygeneration or energy storage processes opens up new possibilities: These include further integration of renewable energies and efficient use of energy resources to ensure a continuous energy supply. For such purposes, the combustion engine is rather used as a chemical reactor providing high temperatures and pressures by means of the compression stroke. High-temperature reactions are promoted such as partial oxidation or pyrolysis, which convert the reactant(s) to higher-energy chemicals such as H2, C2H4, C6H6, or CH3OH on demand. The expansion stroke leads to rapid quenching of the mixtures, inhibiting the formation of unwanted species such as soot or soot precursors. First experimental approaches of this kind are already found in the early 20th century, e.g., by Szeszich [190] and Karim and Wierzba [191], who used a spark ignition (SI) or compression ignition (CI) engine, respectively, to generate chemicals, such as H2 and CO, and work simultaneously. Increasing interest in this approach has been pointed out in the recent review by Ashok et al. [192]. However, most experimental work, as shown by Atakan et al. [193], is related to a feasibility assessment of the approach itself at specific conditions. But to find optimal conditions or general behaviors with respect to the formation of useful species, numerical approaches are being increasingly used. Numerical evaluation strategies can also be important to investigate approaches that currently cannot be put into practice due to technical or financial limitations or to unknown and probably hazardous performance outcomes. Accordingly, Schr€ oder et al. [194] have assessed the separation of the chemicals produced in a polygeneration process in a homogeneous charge compression ignition (HCCI) engine both, thermodynamically and economically. Gossler et al. [195] used mathematical optimization combined with kinetic-thermodynamic piston engine simulations to figure out optimum conditions for performing methane dry reforming. We have presented a novel concept recently [196,197] that uses a piston engine for chemical energy storage. As a first insight into this novel concept, it is shown that kinetic-thermodynamic simulations are mandatory to gauge the general viability of the process, i.e., without harming engines and to save time and money in the search for reasonable and feasible conditions. In this context, two numerical models are combined so that the shortest possible computing time is required: First, we preferably use a single-zone model, in which the assumption of a homogeneous combustion or reactor volume ascertains that much simpler energy and species conservation equations have to be solved, and that further phenomena such as diffusion problems cannot occur. Second, the kinetic model used in these simulations should contain only as much detail—or more precisely, only so many species—as needed for the corresponding calculation. The accuracy of these two models should be sufficiently high to permit general conclusions or predictions. For example, the following three conditions should be met: (1) The combustion phasing should be predicted

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to exclude conditions that could lead to knocking, (2) pressure and temperature curves should be predicted to limit their maximum with respect to the material strength and (3) the species present in the product gas should be predicted to find useful production conditions and to adjust the separation accordingly.

3.7.2 Preview for 2026: Process control in a polygeneration process Recent research [193] has shown that one of the biggest challenges in the polygeneration and energy storage process is the absence of fuel conversion at certain temperatures, without which respective products cannot be generated. Most approaches are concerned with using various additives to increase the reactivity of the reactants and control the ignition timing or reaction onset. These include, for example, the addition of dimethyl ether (DME) or, most recently, ozone [198]. Since ozone causes a shift in ignition and reaction onset temperatures toward lower values [199], it can have a positive effect on the generation of species that are produced particularly at low or medium temperatures, as e.g., CH3OH or C2H4 [200]. However, especially regarding ozone kinetics directly prior to ignition in an HCCI engine at fuel-rich conditions, there are still large gaps in our knowledge. Therefore, a monitoring technique—e.g., laserinduced fluorescence (LIF)—is desirable to enable in situ measurements of intermediates immediately prior to the ignition to be able to control the combustion phasing and to accurately predict ignition timing and species production with respect to optimization or parameter studies. Process control in HCCI engines is a very current research topic, and other promising diagnostics such as pressure sensors with the ability to measure ion currents show promising results regarding operation performance and emission reduction [201]. In addition to the effects that occur in the homogeneous mixture and can be described with gas-phase chemistry, thermal and chemical effects must be considered that occur at the cold wall layers, e.g., reaction quenching, changes of the fluid and flow characteristics or oil deposits. These effects influence the entire combustion cycle, including combustion phasing, the intermediates responsible for ignition, and the products. Research articles on this topic include the work of Persson et al. [202] and Hultqvist et al. [203] who experimentally investigated near-wall chemistry. Most current work focuses on studies using computational fluid dynamics (CFD)/multi-zone model simulations, however, and they are not related to HCCI engine-based polygeneration and energy storage. Another approach to increase the reactivity of the mixture is using catalytic wall coatings, as in the work of Anderson et al. [204] and Yun et al. [205]. In these studies, a variable-volume reactor with a catalytic coating was used for methane steam reforming. An adaption of this approach could also become interesting for HCCI-engine-based polygeneration and energy storage processes to control the reactivity and reaction onset, requiring precise information about the involved surface reactions, however. The combination of monitoring techniques regarding (gas-phase) intermediates and wall behavior with ion current pressure sensors could close the diagnostic gap related to ignition timing and combustion phasing, thus bringing a lot of valuable information that could allow numerical models (engine models, kinetic models) to be further reduced without having to accept a loss of accuracy. This could be extended

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to various systems, e.g., for enhancing fuel-rich ammonia combustion in terms of hydrogen storage [206] or converting low-calorific waste or residual gases from the production of chemicals to use them energetically and chemically.

3.7.3 2030 and beyond: Combinative in situ measurements enable automatic selection of optimum operation conditions In a carbon-neutral future, a focus will be on the diversity of energy systems and thus also on the diversity of potential reactants for chemical and energy conversion. Especially for a HCCI-engine-based polygeneration and energy storage system, a strong increase can be expected in the number of parameters, including fuels, equivalence ratios and oxidizers (e.g., O2, O3, air) and the respective operation range. Accordingly, the number of models, mechanisms and boundary conditions relevant to simulate and optimize such a system will also increase. Kinetic simulations of such a variable system must rely on rather detailed elementary mechanisms with multiple species, potentially including soot formation sub-mechanisms as e.g., provided by Pejpichestakul et al. [207]. In contrast, numerous reduced mechanisms are available that are tailored exactly and exclusively to the desired conditions of the system being modeled, e.g., for fuel-rich methane-based fuels [208]. A similar picture applies when choosing the heat transfer correlation as described by Broekaert et al. [209]. To meet the demands of flexible, diverse future fuel-oxidizer systems, an automatic reduction algorithm is needed that responds to the specific requirements, adjusts the model accordingly based on in situ/online measurements and provides feedback to the system regarding optimal conditions for the desired operation mode (power, polygeneration or energy storage) and/or products (see Fig. 9). Such in situ/online measurements should combine several diagnostic tools to provide comprehensive insight and close any gaps prior to ignition and at the end of the cycle. Suitable techniques for this purpose can include and combine various laser and optical diagnostics including LIF and high-speed imaging in appropriate spectral regimes to monitor chemistry-related data, sensors to diagnose combustion phasing and in-cylinder pressure [201] and thermographic phosphors to measure the in-cylinder temperature and to obtain information about the heat flux through the cylinder walls [210,211]. A future energy system could benefit enormously from an HCCI-engine-based polygeneration or energy storage process, chiefly if it can be used to react flexibly to supply and demand and to produce the desired products as purely as possible. The necessary numerical and diagnostic tools could then be used to intelligently control such a system.

3.8 Judit Za´dor: Theoretical chemistry in combustion diagnostics 3.8.1 Status 2021: The interplay of chemistry diagnostics and theoretical chemistry The goal of the following paragraphs is to outline the relationship between theory and diagnostics, to examine the contribution of theoretical chemistry to some important modern diagnostic tools, and to enumerate new questions offered by theory to diagnostics.

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FIG. 9 Artificial-intelligence-controlled model reduction and performance optimization based on in situ diagnostics.

Modelers today have an array of databases and tools to access chemical kinetic mechanisms, which have grown dramatically in size and in predictive power. The role of many important intermediates in reactive systems is now well understood, enabling the streamlined assembly of mechanisms both by humans and automatically by the computer [212]. Theoretical chemical kinetics has made tremendous progress in the last decade [74,213], enabled by developments in the accuracy of electronic structure methods and in the theoretical framework and related code for master equation calculations, and it is able to provide very good estimates for most rate coefficients in a broad pressure and temperature range. Furthermore, automation has also gained momentum in theoretical kinetics, and with KinBot [214] and similar tools [215] it is now easier than ever to systematically improve reaction mechanisms, challenging diagnostic tools to provide rich and well-resolved data against which the theoretical predictions can be tested (see Fig. 10). At this point perhaps theory offers an easier and clearer path than diagnostics to characterize chemical mechanisms. The most widely used and powerful experimental tools to uncover the details of combustion chemistry are based on photoionization mass spectrometry (PIMS) using synchrotron radiation sources [216]. This near-universal method can probe many intermediates in complex reacting mixtures at once, can expose new chemistry and has been used in a wide range of reactor types. Nevertheless, the typical PIMS experiments are limited in their isomeric resolution abilities to no more than three or four species at a given mass-to-charge ratio (m/z), and so these experiments in general do not provide the desired isomer resolution to constrain models sufficiently. Moreover, experimental calibration is largely limited to stable species, while many

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FIG. 10 Unimolecular reaction channels starting from γ-valerolactone (central structure) as explored by KinBot at the B3LYP/6-311++G(d,p) level of theory. Blue lines signify previously reported channels, while solid green and the dotted light gray lines are new ones. The green lines indicate a barrier height lower than the lowest homolytic bond breaking pathway. Reproduced from R. Van de Vijver, J. Za´dor, KinBot: automated stationary point search on potential energy surfaces, Comp. Phys. Comm. 248 (2020) 106947.

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of the key intermediates are short-lived radicals. The unknown ionization thresholds, photoionization efficiency (PIE) curve shapes, and even photoionization cross sections, however, can be calculated, as e.g., demonstrated in Ref. [217]. It has also been recognized that different conformers of a species can have quite different adiabatic ionization thresholds, and it is likely that the lowest ionization energy does not arise from the lowest energy conformer [218]. To roughly double the isomeric resolution, one very promising experimental technique is photoelectron photoion coincidence (PEPICO) spectroscopy [219,220] which nevertheless also requires theory to establish the photoelectron spectrum (PES) for most species. For PEPICO, low-lying excited states can complicate the calculations, requiring multireference or other excited state calculations to interpret the detected spectra for species without a known spectrum.

3.8.2 Preview for 2026: Resolving isomers and conformers with the aid of experiments and theory In the coming years theory will likely increase and improve its contribution to the interpretation of photoionization (PI)-based experiments. Automated tools for kinetics could also explore the ionization potentials for the various conformers with relatively little modifications and allow the routine inclusion of conformer-dependent ionization energies in the data analysis. Such computational tools can also readily predict whether large geometry change or fragmentation are likely. For certain important classes of species in low-temperature oxidation of organic molecules RH (such as ROO, QOOH, OOQOOH, HOOPOOH, KHP and ROOH) [50,221], ionization often causes fragmentation even near threshold. For radicals the ionization often involves more than one potential energy surface, typically a singlet and a triplet. For ROO radicals the lowest state is typically triplet [222], while for QOOH radicals it is a singlet, but commonly involves rearrangement and concomitantly, has poor Franck-Condon overlap with the ion. While there are some systems where the fragmentation has been explored theoretically, there are no general tools available, especially to capture the variety of possible fragmentation pathways for larger, substituted species. In recent work by Sheps et al. [223], for complex species such as OOQOOH and second-O2 addition products, KinBot [214] was successfully used to automatically explore the cation potential energy surface and aid the identification of the PIMS experiments to identify the species. The calculation of absolute photoionization cross sections using Dyson orbitals is likely to become more accurate and widespread based on fundamental ab initio developments [224]. While the current PI-based experiments are nearing their limit in isomer resolution, theoretically we are now able to capture even finer effects, such as the recently highlighted impact of stereochemistry [225]. There are two emerging techniques that are likely to take off in the next few years to better underpin the theory experimentally. Tandem mass spectrometry (MS) can study the structure of larger and more complex species, such as polycyclic aromatic hydrocarbons (PAHs), see e.g., [226]. Understanding fragmentation patterns of larger molecules in tandem MS is difficult, yet holds the key to deciphering their structure. Unlike in the PIMS

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experiments, fragmentation is a desired process and is achieved by collision-induced dissociation (CID), where the cations gain the energy for dissociation via collisions with Ar atoms in a tunable manner. To solve the inverse problem for complex systems, automated ab initio frameworks that can provide structural information about the species that resulted in the observed fragments are desirable. These could be achieved by a combination of direct dynamics, collisional energy transfer, and RRKM calculations. An entirely different approach, chirped microwave spectroscopy, has also gained traction in diagnostics [227]. In this case the interpretation of the data requires the geometries and dipole moments of the species, which can be obtained from electronic structure calculations, although the accuracy of the calculations needs to be very high given the resolution of the experimental technique. Moreover, microwave spectra of combustion systems are not only complicated by isomers, but also by conformers, which essentially renders theory an integral part of this diagnostic tool.

3.8.3 2030 and beyond: Theory, experiment and data strategies combined Going forward, there can be two goals in diagnostic work. One is to validate the theoretically derived chemical mechanisms in detail and detect missing species and reactions. From a theoretical perspective, the key intermediates are short-lived, unstable or highly reactive species. At the same time, these are precisely the ones that are hard to quantify experimentally. For instance, QOOH radicals are ubiquitous in autoignition, but because of their short lifetime, there are only a few specially prepared systems in which these species were successfully studied directly, see e.g., [228,229]. Detection of weakly bound radicals [74,230], such as HCO, and watching their reactions in mixtures present another set of complications. Therefore, beyond 2030, it would be desirable to redefine what in situ and direct measurements mean. An important observation is that the powerful multiplexed experiments mentioned in the previous sections are data-heavy, which makes the analysis of the results tedious and prone to errors or may require undesired simplifications, because the researchers must know what to look for in the sea of data. One can envision the rise of machine learning (ML) and automation in the analysis of multiplexed data. For instance, Zaleski and Prozument [231] have developed a neural network approach that is trained on fictitious molecular structures that can be used to analyze a complex rotational spectrum. Similar approaches could become standard in many diagnostic experiments, including PIMS-based ones. Approaching the problem from another angle, there are efficiencies to be gained from rigorous experimental design strategies [232], with multiscale informatics [74,233] playing a key role in developing mechanisms. However, at some point the complexity of reacting mixtures becomes intractable even with theory, for instance when mixtures of large-molecular-weight fuels ignite, or during PAH formation, not to mention practical situations where the composition of the fuel blend is ill-defined or variable. In that regime, bottom-up theoretical approaches will run out of steam, but diagnostics can still give chemical insight about the underlying chemical reactivity trends. This is the possible second goal of

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diagnostics for the future. Hansen et al. [234] have shown that across a large dataset of flame measurements, the maximum mole fractions of some intermediates are well correlated independently of the flame conditions. They show how this information can be used to develop mechanisms and envision that similar data-driven approaches combined with ML will play a pivotal role in future studies. This idea also appears in Buras et al. [235], where the authors use ML to correlate measurements of OH and HO2 radicals in a dilute, low-pressure experiment with ignition delay times (IDTs) calculated for high-pressure and non-dilute conditions, see Fig. 11. Theoretical kinetics makes convincing predictions in chemical reactivity not only regarding isomer specificity but also in demanding topics such as excited states and non-adiabatic processes [74,236], termolecular reactions [74,237] and nonBoltzmann distributions [3,238]. Especially with the emergence of plasma-assisted combustion, non-adiabatic chemistry will become more important, allowing experimentalists to embark on the exciting challenge of validating many of the theoretical predictions. Increasingly complex chemistry is also expected to take place in the interaction of gas-phase species with surfaces. Understanding these heterogeneous catalytic processes is essential for chemical transformations toward a carbon-neutral future,

FIG. 11 Parity plot and histogram of convolutional neural-network-derived correlation between the explicitly simulated 1st-stage IDT and predicted 1st-stage IDT using OH/HO2 plug-flow reactor (PFR) training data. Dashed lines represent factor of two errors. Reproduced from Z.J. Buras, C. Safta, J. Za´dor, L. Sheps, Simulated production of OH, HO2, CH2O, and CO2 during dilute fuel oxidation can predict 1st-stage ignition delays, Combust. Flame 216 (2020) 472–484.

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and theory will become a powerful support also for these purposes [239,240]. Similarly, electrochemical systems—often multi-phase and exhibiting directional species migration—that are important in future carbon-neutral contexts, will await similarly powerful combinations of theory and chemical diagnostics.

3.9 Yuyang Li: Chemistry diagnostics and control of low-carbon fuels for the upcoming carbon-neutral era 3.9.1 Status 2021: Diagnostics for reactivity control The world is facing great threat from climate change caused by enormous emissions of greenhouse gases [241], where CO2 emitted from fossil fuel combustion in energy, transportation and industry applications is recognized as their major anthropogenic source. China as the world’s second-largest economic entity has a strong need to reduce its carbon emission that is almost one third of the global carbon emission. China signed the Paris Agreement in 2016 with a promise last year to reach the carbon emission peak in 2030 and carbon neutrality in 2060 [242]. An urgent need results to apply low- or zero-carbon fuels such as hydrogen, ammonia, syngas, biogas and liquid biofuels in practical combustion devices [243]. This pertains not only to internal combustion engines, gas turbines and power plants, but also to industrial combustion, e.g., in the production of cement and glass, the synthesis of nanomaterials and the removal of chemical hazards and pollutants. Chemistry diagnostics for low-carbon fuels become crucial for their practical use. Knowledge on both, their global combustion properties and chemical composition during their combustion remains largely insufficient, different from conventional hydrocarbon fuels that have been widely used in practical combustion devices for about a century. For example, ammonia and biogas have lower reactivity than conventional hydrocarbon fuels, which may cause low combustion stability, while hydrogen and DME show higher reactivity, which may cause flashback and high NOx emission because of the high flame temperatures. Ammonia and biofuels also exhibit different pollutant emission features from hydrocarbon fuels. Therefore, the control of the reaction chemistry for low-carbon fuels becomes an important issue. My group has focused on the chemistry diagnostics and reactivity control of lowcarbon fuels for about ten years. For chemistry diagnostics, we have adopted two major approaches. First, we have developed a high-pressure laminar flame propagation measurement method that can provide crucial understanding for global combustion reactivity. It is a long-standing challenge to precisely measure the high-pressure laminar flame propagation for high-boiling-point fuels, especially liquid low-carbon fuels. We have solved the problem of protecting the quartz window under high pressures by proposing a dual-surface-protection and self-sealing optical path design method in a constant-volume combustion vessel [244]. Laminar burning velocity measurements have thus been performed for liquid low-carbon fuels like methanol, propanol isomers, butanol isomers, cyclopentanone, pentanone isomers, acetic acid and propanoic acid at initial pressures up to 20 atm. The method has also been adopted to analyze specific reaction systems. For example, we have investigated

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FIG. 12 Laminar burning velocities of NH3/(50%NO/50%N2) mixtures at 1 atm and 298 K. Symbols denote experimental results, lines simulations with the present and previous models. Reproduced from B. Mei, S. Ma, X. Zhang, Y. Li, Characterizing ammonia and nitric oxide interaction with outwardly propagating spherical flame method, Proc. Combust. Inst. 38 (2021) 2477–2485.

the interaction kinetics of NO with ammonia in a combustion system using an NO/N2 atmosphere as the oxidizer [245] (Fig. 12). Interestingly, this approach permitted to constrain specific kinetics more strongly than flame speciation data that are conventionally considered as better validation targets for reaction kinetics. Secondly, we have further developed the molecular-beam sampling technique in synchrotron vacuum ultraviolet photoionization mass spectrometry (SVUV-PIMS), using a novel, more compact design to improve the detection sensitivity down to 0.1 ppm. As a result, the methylperoxy radical was unambiguously detected in the low-temperature oxidation of acetaldehyde [246], while cooling effects of the sampling probe have been found to induce low-temperature oxidation chemistry in the premixing zone of laminar premixed flames [247]. For the reactivity control, my group has aimed at understanding fuel and oxidizer effects on combustion reactivity and pollutant formation. We have performed measurements and modeling analysis on fuel-specific, fuel-blending, fuel-cracking and oxygen-enrichment effects for low-carbon fuels such as biofuels, syngas and ammonia [248–250]. It has been concluded that the differences in fuel decomposition pathways and radical pools caused by such effects can lead to dramatically different pyrolysis and combustion reactivities, while the formation pathways of PAHs can also be influenced by fuel structural features and fuel interactions. Furthermore, control strategies have been designed to enhance the combustion reactivity or inhibit PAH formation. For example, we have proposed oxygen-enrichment and precracking strategies for ammonia combustion and obtained significant reactivity

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FIG. 13 Schlieren images of stoichiometric NH3/O2/N2 flames with oxygen content varying from 21% to 45% at 1 atm, showing that oxygen enrichment can substantially enhance the combustion reactivity. R is the flame radius. Reproduced from B. Mei, X. Zhang, S. Ma, M. Cui, H. Guo, Z. Cao, Y. Li, Experimental and kinetic modeling investigation on the laminar flame propagation of ammonia under oxygen enrichment and elevated pressure conditions, Combust. Flame 210 (2019) 236–246.

enhancement (Fig. 13), especially at high pressure, leading to an improved combustion intensity of ammonia for stationary gas turbine applications [249,250].

3.9.2 Preview for 2026: Diagnostics for unconventional, low-carbon fuels In the next few years, the research for low-carbon fuel chemistry is expected to grow rapidly and more and more groups will be involved in this field. In particular, the rapid increase of solar energy and wind energy shares in primary energy supply will raise the risk of power grid fluctuations due to the unstable supply of these renewable energies [251,252]. Therefore, unconventional low-carbon fuels that can be produced from captured CO2 using surplus solar and wind energy have the potential as energy storage agents, making their role in global energy systems more significant than ever imagined. Chemistry diagnostics and the reactivity control of these fuels, including acids, aldehydes, ketones and oxymethylene ethers, deserve greatly enhanced attention. Regarding research needs in the next five years, several key research topics will be particularly valued. 1. Advances in experimental and diagnostic tools, with special attention on exploring the kinetics of unconventional low-carbon fuels, will be highly desired [32]. These fuels have different combustion characteristics and chemical structures, leading to a number of challenges for present experimental and diagnostic tools. For example, the corrosiveness of acids and the pre-reactions of aldehydes with oxidizers require sophisticated design of experimental tools, and

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low-concentration reactive intermediates in flames and low-temperature oxidation of these unconventional fuels require advances in mass spectrometric and optical spectroscopic tools. 2. It will be of special interest to derive the knowledge underneath the limited knowledge of chemical diagnostics that we can observe currently. For example, there are still rate constants of numerous elementary reactions unmeasured and most of the chemical speciation information undetectable, especially for unconventional low-carbon fuels. This requires development and applications of informative tools based on artificial intelligence and machine learning, which have been recently successfully applied in many fields of combustion research, such as the uncertainty analysis of rate constants and kinetic models [232]. 3. The chemistry control of unconventional low-carbon fuels and their application in practical combustion will also be an interesting topic, as it requires more understanding of the combustion characteristics and pollutant formation of these fuels and the control strategies considering the scenarios in practical combustion devices. This remains insufficiently understood for conventional low-carbon fuels like biodiesels [253].

3.9.3 2030 and beyond: Chemistry diagnostics for and beyond combustion If we move our line of sight to 2030 and beyond, the question—not only in China— will arise about the position of combustion in a carbon-reduced or near-carbonneutral era. It can be imagined that a large fraction of fuels (or even very close to all) will be renewable low-carbon fuels for gas turbines, internal combustion engines and power plants. Then, our understanding of many low-carbon fuels has been greatly deepened. However, new fuels always emerge as a consequence of advances in fuel production technologies. Thus, chemistry diagnostic tools and control strategies will still need to be further developed. Another possible opportunity will come from the arrival of potentially revolutionary computer technologies, as e.g., the quantum computer [254,255] that can provide a supreme level of computation resources and might greatly propel computer-aided chemical diagnostics and high-fidelity numerical simulation with detailed chemistry. It should also be emphasized that in addition to power generation where combustion may have a reducing contribution from the present dominance, many industry applications will still need to use combustion to provide heat sources and exothermic environments in 2030 and beyond. Therefore, chemistry diagnostics and control of low-carbon fuels have the need to cross-fertilize with various unconventional reaction environments. These may include multi-element reactions for flame synthesis [29,30], coupling with catalytic reactions [32,256] and plasma-assisted combustion [130]. In summary, chemistry diagnostics and control of low-carbon fuels is a rapidly growing field with a brilliant future considering the expected irreversible change to a carbon-neutral era, where the combustion community will make highly significant contributions just like we did in the fossil energy era.

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3.10 Lena Ruwe: Gaining knowledge on fuel-specific gas-phase reactions using molecular-beam mass spectrometry 3.10.1 Status 2021: Mass spectrometry to analyze fuel-structuredependent reaction chemistry Although significant progress has been made in the development of sustainable propulsion systems, the transformation from fossil fuels toward renewable energy sources requires a transition phase to meet the existing energy demand in the mobility sector. During this transition phase, conventional liquid fuels will continue to play an important role, especially in long-distance and heavy traffic, due to their high energy densities, existing storage and distribution infrastructure and established engine combustion concepts. The optimization and control of energy conversion systems toward an improved efficiency in combination with a reduction of both, CO2 and harmful emissions is therefore of great importance, and fundamental knowledge of the relevant combustion chemistry is required to achieve this dual goal. Molecular-beam mass spectrometry (MBMS) has established itself as one of the most versatile and advanced diagnostic tools for fundamental chemical analysis of combustion systems [257], as this method provides reliable information on the fuel-specific gas-phase kinetics in the form of detailed and quantitative species data sets and can easily be coupled with various experiments [258–261]. Although certain caveats must be respected (see Section 3.8), MBMS enables the simultaneous detection of most of the species involved in the combustion process without prior knowledge of their chemical identity, which is advantageous compared to other methods such as gas chromatography or laser diagnostics [45]. Typically, a gas sample is withdrawn from the respective experiment by a quartz probe and guided into the two-stage differentially pumped vacuum chamber of the mass spectrometer forming a molecular beam that is guided into the ionization volume. Here, the molecules are ionized either by electron ionization (EI) or by synchrotron-based photoionization (PI), and subsequently the ions are separated by time-of-flight (TOF) mass spectrometry. While EI-MBMS allows for the simultaneous detection of radicals and stable species, isomer discrimination can be achieved using the PI-MBMS method. Since efficiency and pollutant emissions of technical combustion processes are significantly linked to the respective molecular fuel structure, detailed information on the underlying combustion chemistry is a key requirement to optimize these parameters. To achieve a general understanding on the gas-phase reactions of technically relevant fuels, it is required to systematically study the reaction pathways for individual fuel components. Recently, we have investigated the high-temperature oxidation kinetics of selected C5 hydrocarbons (i.e., featuring five carbon atoms in their molecular structures), namely 2-methyl-2-butene, 1-pentene and n-pentane. These were chosen as prototypes for branched and linear, saturated and unsaturated fuel components that feature different CdC and CdH binding situations. Flames of these fuels were systematically studied using a combination of PI- and EI-MBMS [260,261]. We could demonstrate that the formation tendency of growth species such as PAHs, which are considered as important soot precursor molecules, increases significantly in the sequence n-pentane < 1-pentene < 2-methyl-2-butene [261].

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FIG. 14 Flame-sampled mass spectra illustrating the growth chemistry in a mass range between m/z ¼ 70 u and m/z ¼ 202 u that seems to follow the same reaction steps for 2M2B and 1-pentene. The given molecular structures are thought to provide guidance on some of the structures to be expected; isomeric forms are meant to be included as well. Note that the 1-pentene signal was multiplied by a factor of 4 for better visualization. € Reproduced from L. Ruwe, K. Moshammer, N. Hansen, K. Kohse-Hoinghaus, Influences of the molecular fuel structure on combustion reactions towards soot precursors in selected alkane and alkene flames, Phys. Chem. Chem. Phys. 20 (2018) 10780–10795, with permission from the PCCP Owner Societies.

The reason lies in significant differences in the molecular structure of important intermediates, which are formed in early fuel decomposition steps and which serve as key building blocks in the PAH formation as we could show by a detailed analysis of the fuel-dependent consumption pathways. Despite this fuel-specific influence, PAH formation follows similar reaction pathways regardless of the molecular fuel structure [261], as revealed through identical intervals of the most pronounced mass peaks in flame-sampled mass spectra which are shown in Fig. 14.

3.10.2 Preview for 2026: In-depth chemical diagnostics to identify pathways to undesired emissions In combustion applications, soot formation is known to occur to a significant extent when using fossil fuels, e.g., Diesel fuel. It can be expected that soot emissions will be reduced as the proportion of internal combustion engines fueled by

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fossil fuels decreases due to replacement by modern propulsion systems. From a scientific perspective, however, a focus should persist to be placed on the PAH chemistry, since the formation and reaction pathways of these aromatic structures are also of crucial interest beyond combustion chemistry [262]. As shown by Kaiser and Hansen [262], interdisciplinary studies combining the knowledge, methods and approaches from different research fields will provide completely new perspectives. In the near future, internal combustion engines will still continue to make up a large proportion of the propulsion systems with the currently used fossil fuels. These will, however, be increasingly replaced by synthetic fuels which could be operated within the existing fleet with slight modifications. As discussed by Dieterich et al. [263], the production of carbon-neutral fuels via Power-to-Liquid (PtL) processes is gaining rising attention. Nevertheless, due to numerous technological, political and economic aspects but also scientifically, the identification of the optimal PtL process route and the selection of the most promising product remains a challenge [263]. Potential fuel candidates typically feature oxygenated molecular structures and a reduced number of CdC bonds. These include promising alternative fuels such as dimethyl ether and oxymethylene ethers [263–266] but also alcohols, esters and further ethers. Although the use of oxygenated fuels goes along with reductions in CO2 and particulate matter (PM) [267], it must be ensured that no other undesired pollutants are emitted. For ethanol, for example, it was shown that the reduction in PM is associated with a significant increase in the concentration of toxic aldehydes [268,269]. The development of synthetic fuels must therefore be accompanied by a critical assessment of potential fuel candidates not only with regard to their production route and performance, but also to their combustion chemistry. With the aid of chemicalkinetic combustion models that are validated with appropriately chosen experiments and further reduced for the respective application, it is possible to transfer detailed chemical knowledge to practically relevant combustion processes and to support their optimization. The development of such combustion models, especially for synthetic fuels, will still be required within the next five years. Therefore, validation experiments combined with suitable diagnostic techniques, which are conducted under a wide range of combustion conditions, i.e., different pressure and temperature regimes, will continue to be necessary. For this reason, also MBMS will remain an important pillar for providing in-depth chemical information on combustion processes. To provide detailed species data for engine-related conditions with MBMS, the respective experiments should be modified to achieve higher pressure ranges in the near future. Moreover, the numerous existing experimental data in the literature should be combined in databases, classified according to structural motifs, and examined for correlations. Such approaches as already demonstrated on a small scale by Hansen et al. [234] can provide more general knowledge on how the gas-phase chemistry is affected by certain functional groups and structural motifs and can therefore support the optimization of modeling approaches that are based on distinct reaction classes [179,188].

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3.10.3 2030 and beyond: Automatic data generation and analysis for combustion and beyond In the future, it should become possible to perform and evaluate experiments for studying the gas-phase chemistry fully automatically so that a huge amount of data for various temperature and pressure regimes can be generated and finally be stored in an open-access database. Because of the large data volume, it will then be impossible to analyze the data in a traditional way. Instead, a big-data analysis approach will be required that searches a compilation of data for patterns without specific questions in mind. Exemplary studies [260,270,271] have demonstrated—on a small scale—an analysis of signal ratios for selected flame data and have discovered, based on this approach, some interesting relationships. It can therefore be assumed that a big-data analysis approach will reveal further previously unknown relationships. For such a data analysis approach, experimental uncertainties must be taken into account, which can be quite large for MBMS experiments. For the PI-MBMS technique, it is known that quantitative species data are significantly affected by the chosen photoionization cross section (PICS) from the literature [272,273] that is used in the data evaluation. To reduce such uncertainties, it is consequently required to determine the PICS with a smaller and known uncertainty, considering also the potential of theory to provide such important information (see Section 3.8). Not only would the combustion community benefit from such results, but it would also be an interdisciplinary progress, as PICS are also needed in other research fields. Detailed understanding on the formation pathways of important gas-phase species, including e.g., hydroperoxides as well as polycyclic aromatic hydrocarbons, will continue to be of great interest in 2030 and beyond, as these species are not only responsible for processes such as two-stage fuel ignition in internal combustion engines or soot formation. It has been recognized that these play decisive roles, respectively, in the formation and evolution of secondary organic aerosols in the atmosphere [50] as well as in the atmospheres of planets and their moons, cold molecular clouds and circumstellar envelopes [262]. In the future, advanced experimental methods such as MBMS, especially when complemented with chemical kinetic modeling, could favorably be used to investigate gas-phase chemistry in further areas that require the detection of transient species, including not only current topics in atmospheric chemistry and astrochemistry but increasingly also catalyst development [50,262,274,275]. Knowledge acquired and analytical methods utilized today in combustion chemistry can thus be highly valuable in future interdisciplinary contexts.

3.11 Nina Gaiser: Alternative fuel combustion and prospects for PEPICO spectroscopy 3.11.1 Status 2021: Using PEPICO to understand oxymethylene ether combustion Fossil resources continue to deliver the largest share of global energy [276,277], with 24% of the global CO2 emissions in 2015 stemming from the transportation sector [276]. Combustion of fossil fuels impacts global warming, and fossil-fuel emissions have adverse effects on air quality and health [278]. Replacing fossil fuels with clean,

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sustainable, carbon-neutral energy carriers is indispensable to achieve the goals of the Paris agreement [279]. Especially alternative biogenic and synthetic fuels show great potential regarding their production in CO2-neutral processes and active reduction of soot and other pollutant emissions by targeted fuel design. Chemical insight and detailed reaction mechanisms are needed to understand the combustion chemistry of such alternative fuels and to provide better predictions of the combustion process. The design of engines can benefit from this approach, and the behavior of new fuels as blend-ins can be forecasted. Reactive, often still elusive intermediate species can play a key role in these chemical processes, but they are typically short-lived and only present in trace amounts in the reactive mixture. Their detection requires fast and sensitive diagnostic methods including MBMS or PIMS as established in situ diagnostics for detailed investigation of gas-phase reactions in reactive flows (see Sections 3.8–3.10). Our current research focuses on oxymethylene ethers (OMEs)—oxygenated fuels of general formula CH3O(CH2O)nCH3 (with n¼0–5) discussed as an alternative for Diesel fuels [277]. For this purpose, we use advanced instrumentation, specifically PEPICO spectroscopy applying VUV synchrotron radiation to determine species profiles in flow reactors and laminar flames. In reactor environments, the respective gas mixture is diluted by argon to avoid heat release and self-sustaining reactions, and the reactions are studied following a temperature profile determined by external heating. Laminar flames are investigated in low-pressure conditions to widen the reaction zone, as shown in Fig. 15. Samples from the reaction zone are rapidly expanded into high vacuum forming a molecular beam that is guided into the ion source. Chemical reactions are thus frozen so that even highly reactive species are preserved and can be detected. Tunable monochromatic vacuum ultraviolet radiation allows for soft ionization. The double-imaging i2PEPICO spectrometer enables simultaneous detection of electrons and ions formed during the ionization process: photoelectron and photoion kinetic energy distributions are measured by velocity map imaging. From such mass-selected threshold photoelectron spectra, isomeric species cannot only be distinguished by their photoionization energies, but also by their photoelectron spectra (PES) which serve as a spectroscopic fingerprint for clear identification [274,280,281]. Threshold photoelectron-spectra (TPES) of methyl formate measured during the oxidation of OME4 are given in Fig. 15 as an example [282]. With this i2PEPICO approach, we could recently separate the two isomeric intermediates ethanol and dimethyl ether in the oxidation of OME1–5 (Fig. 15) [283]. We were able to show that for all OMEs, ethanol was the dominant intermediate at the chosen conditions, which does not correspond to the predictions of kinetic models [283]. These results can directly be used to improve non-isomer-selective experimental results as well as reaction mechanisms.

3.11.2 Preview for 2026: Analyzing alternative fuel combustion for practical applications Replacing combustion-based power units worldwide within short time scales is extremely challenging, and consequently, the transportation sector will still be largely powered by combustion in 2026. Although their number is increasing,

FIG. 15 Left: Schematic sketch of the i2PEPICO set-up for laminar flames. Top right: threshold photoelectron spectra serving as a spectroscopic fingerprint, here of methyl formate measured in an OME4 flame. Bottom right: Photoionization efficiency curves of dimethyl ether and ethanol.

€ € Adapted from (Top right) N. Gaiser, T. Bierkandt, H. Zhang, S. Schmitt, P. Oßwald, J. Zinsmeister, P. Hemberger, S. Shaqiri, T. Kasper, K. Kohse-Hoinghaus, M. Kohler, M. Aigner, Systematic study on laminar low-pressure oxymethylene ether (OME0-4) flames using molecular beam mass spectrometry and synchrotron photoionization, Paper Presented at 30. Deutscher Flammentag, Hannover, Germany (online), Sept. 28–29, 2021. (Bottom right) N. Gaiser, T. Bierkandt, P. Oßwald, J. Zinsmeister, T. Kathrotia, € S. Shaqiri, P. Hemberger, T. Kasper, M. Aigner, M. Kohler, Oxidation of oxymethylene ether (OME0-5): an experimental systematic study by mass spectrometry and photoelectron photoion coincidence spectroscopy, Fuel 313 (2022) 122650.

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electrified vehicles will not govern the global market then. Conventional cars with a combustion engine, including hybrid cars, will still be introduced and most of those currently in use will not be retired from service in 2026. The same applies for air or marine traffic, for which high-energy-density carriers will remain vital for longdistance and heavy-duty transportation. In all areas, replacing or blending petroleum-based fuels with specially designed CO2-neutral fuels will not only decrease carbon emissions, but can also reduce NOx and soot emissions. Focusing our research on alternative synthetic fuels and investigating their combustion chemistry will not lose importance by 2026. Specifically, efforts may shift to longer-chain OMEs, their isomers or cyclic variants that show potential to optimize the performance of this Diesel substitute [277]. In a comparison of the linear OME2 and its branched isomer trimethoxymethane, we could already show that trimethoxymethane might be used as a blend-in for OME2 to lower the reaction temperature [284], which can have a positive reduction effect on the formation of thermal NOx. Blending rates of OMEs or other synthetic fuels for Diesel engines must rise continuously to achieve the intended increase in the utilization of alternative fuels after 2026. Using a pure OME mix or higher blending rates requires adaptation of engine features, e.g., change of sealings [277]. Even though OMEs are not prone to soot emissions, as we could confirm in reactor studies for the OME fuels up to OME5 [283], currently unregulated emissions must be considered. Special attention should be devoted to aldehyde emissions, recognizing formaldehyde as the dominant intermediate species in OME combustion [282,283]. In future steps, our research of alternative fuels is moving toward practical applications. The low-temperature chemistry of OMEs and other alternative fuels will be examined in a high-pressure flow reactor coupled to MBMS and FTIR spectroscopy to reproduce more realistic conditions. Alternative fuels, pure and as blends, will be investigated in a variable engine test bench. Octane and cetane numbers will be determined and a focus on emissions (NOx, soot precursors) will apply using different particle and gas-phase analysis instruments, including FTIR spectrometers as well as condensation particle counters and engine exhaust particle sizers. Such unique instrumentation is expected to bridge the gap between laboratory conditions and applied, alternative fuel combustion; specifically, using air as the oxidizer deserves investigation in greater detail. Therefore, higher mass resolution at the PEPICO endstation would be desirable to discriminate between nitrogen-, carbonand oxygen-containing species. A combination of high mass resolution and i2PEPICO spectroscopy is technically not feasible. Modifications of the current approach could include an additional reflectron time-of-flight photoionization mass spectrometer, at a separate endstation or interchangeable at the current one, which might allow measuring all involved species with high precision. Optimistically, research endeavors using these different diagnostics, combining MBMS to unravel gas-phase kinetics with emission measurements, will accelerate the introduction of alternative fuels into our daily life. It cannot be neglected, however, that politics, industry and public opinion must support the use of alternative fuels to make such options fruitful.

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3.11.3 2030 and beyond: Future fields for PEPICO diagnostics In 2030 and beyond, chemical propulsion will still play an important role worldwide even if battery techniques make a leap in innovation. Aviation demand has an annual growth rate of several percent, with an average aircraft lifetime of more than two decades [276]. Synthetic fuels will thus remain a long-term solution with CO2-neutral fuels—hopefully—an integral part of the global transportation sector. A wide spectrum of future synthetic fuels will go along with an increasing demand to analyze their combustion behavior, also by using PEPICO spectroscopy. Fuel producers will have a strong interest in making their CO2-neutral fuels increasingly efficient over time, especially for alternative jet fuels. Such sustainable aviation fuels (SAFs) are normally composed of several hundred components [285]. Digital databases, as for example the DLR SimFuel Platform [286], already contain models for fuel-related behavior. Such databases enable the simulation and evaluation of new, alternative fuels using physics-based models as well as machine learning, providing fuel assessment/screening and specific fuel design [287]. They must be fed by composition and performance values of several fuels and physical properties of single components. Fuel characterization regarding chemical composition and properties using analytic tools is under way [288]. It should be recognized that isomers behave differently in fuel assessments, and to provide reliable simulated fuel compositions, one must distinguish between isomers in the liquid phase. Although not yet feasibly explored, coupling existing experimental set-ups that are isomer-selective and can detect more than 100 species simultaneously (e.g, by chromatographic methods) and the PEPICO technique with regard to fuel screening would substantially improve a systematic fuel design process toward cleaner and more efficient, CO2-neutral fuels. In this context it may be of interest that an upgrade of the Swiss Light Source is planned, leading to increased brightness and coherent fraction of the synchrotron radiation and with much improved (by a factor of 30–35) performance values and a finer beam at the same intensity [289]. While PEPICO spectroscopy is a great tool for the investigation of species and isomers, it has the major disadvantage of being typically tied to a synchrotron endstation. Beamtime is often limited due to the high demand of different research groups and the high costs of operation. Laboratory-based VUV radiation sources therefore become attractive. Couch et al. [290] have reported tabletop VUV photoionization and PEPICO spectroscopy for isomer-specific detection. In their work, VUV radiation is derived from a commercial femtosecond laser system, allowing data to be collected at 10 kHz and tunability along the odd harmonics of the driving laser [290]. At the current state, the photoelectron resolution is insufficient to resolve vibrational structure, so no threshold photoelectron spectra were measured, and the achievable energy range was too high for the investigation of combustion chemistry. Hemberger et al. [274] recently discussed that the drawbacks of such tabletop approaches compared to synchrotron radiation are not compensable in the near future. However, beyond 2030, improvements can be expected to make tunable VUV radiation readily available at the laboratory as a welcome game changer for combustion chemistry diagnostics.

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3.12 Zhandong Wang: Detective work with advanced techniques: How to identify and measure previously elusive species 3.12.1 Status 2021: Low-temperature chemistry diagnostics Low-temperature oxidation (LTO) of organic compounds is a key chemical process, for which a good understanding in terms of a reliable kinetic mechanism and model is crucial. This concerns the design of internal combustion engines as well as demands for improved safety in gas-phase oxidation processes. The basis of the LTO has been gradually formed since the 1980s [221,291,292]. At present, the main reactions accepted to explain the LTO chemistry of alkanes are summarized in Fig. 16 [50]. The LTO of large saturated methyl esters, alcohols and ethers, while still underexplored, could also feature the same type of chemistry. As shown in Fig. 16, the chemical routes are described as three propagation cycles initiated by H-abstraction from the fuel molecule (RH) to form a fuel radical. Subsequent O2 addition to the fuel radical and subsequent derivatives occurs, leading

FIG. 16 Reaction scheme for the low-temperature oxidation of alkanes. Adapted and updated from Z. Wang, O. Herbinet, N. Hansen, F. Battin-Leclerc, Exploring hydroperoxides in combustion: history, recent advances and perspectives, Prog. Energy Combust. Sci. 73 (2019) 132–181.

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to a multitude of highly oxygenated intermediate species which can undergo isomerization, scission and chain-branching reactions. Important species include alkenes, cyclic ethers, peroxides, hydroperoxides, hydroperoxyalkyl and hydroperoxyalkyl peroxy radicals, ketoalkoxy radicals and ketohydroperoxides (KHPs). These are elusive species but are key to explain the high reactivity of alkanes at low temperature and the occurrence of autoignition. The formation of KHPs had no direct evidence until 2010, where the C4-KHPs and the C1-C4 alkyl hydroperoxides were directly detected during the LTO of n-butane using a jet-stirred reactor (JSR) coupled with synchrotron VUV photoionization mass spectrometry (SVUV-PIMS) [293]. The results were confirmed in 2015 using a photolysis flow tube as a reactor [294]. The detection and confirmation of the ketohydroperoxide intermediate have opened the door to a wide range of hydroperoxide measurements in the LTO chemistry. Very recently, we have reviewed the progress in understanding LTO processes with particular interest on the detection, identification, quantification and kinetics of hydroperoxides [50]. As Fig. 16 shows, several cycles of O2 addition are possible, with increasingly more complex reaction intermediates that are challenging to corroborate experimentally, especially since larger organic molecules may offer structure-specific reaction pathways starting from different abstraction sites of the parent molecule. To explore the structure-specific possibility of a third O2 addition, we have carried out systematic studies on the LTO of normal alkanes, branched alkanes, cycloalkenes and molecules featuring aldehyde, ketone, alcohol, ether and ester functions [295–297]. Using JSR-SVUV-PIMS and an atmospheric pressure chemical ionization (APCI) source coupled with an orbitrap mass spectrometer (OTMS), we have successfully detected highly oxygenated intermediates with four and five oxygen atoms added to the fuel molecule, and a generalized reaction scheme has been proposed as Cycle 3 (see Fig. 16).

3.12.2 Preview for 2026: Coupling advanced mass spectrometry with high-pressure reactors Due to its well-defined physical properties and because it can be simulated with a zero-dimensional approach, the JSR is an ideal laboratory reactor that has been coupled to various analytic tools such as gas chromatography [298], FTIR spectroscopy [299] and mass spectrometry [296]. Rich chemical knowledge, especially on stable products in LTO processes, has been gained using this configuration. A JSR coupled with cavity ring-down spectroscopy (CRDS) has shown potential for quantitative measurements of elusive species in LTO [300,301]. JSRs coupled with SVUV-PIMS have been powerful instruments to discover the species distribution and reaction mechanism of the LTO chemistry, especially regarding the complex oxygenated intermediates with carbonyl, carboxy and peroxy groups [43,217,293]. However, present JSRs coupled to SVUV-PIMS work primarily at a pressure of 1 bar, far below the practical pressures of combustion engines (60 bar for Diesel engines, and 120 bar for HCCI engines) [50]. Thus, one stringent task in the next five years is to develop LTO reactors for laboratory use that can bear much higher pressures and to further couple them with SVUV-PIMS and other advanced diagnostic tools.

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A JSR with a sampling probe has already been operated at pressures up to 40 bar but was not coupled with the on-line SVUV-PIMS method [302]. Using off-line diagnostic methods, recent work of Belhadj et al. [303,304] demonstrated a highpressure effect on the LTO process of n-heptane. They operated the JSR at 10 bar and collected the products in a trap to then separate and analyze them by highperformance liquid chromatography (HPLC) and APCI-OTMS. Compared with the LTO of n-heptane at 1 bar, the reactions at 10 bar produce very complex species, such as hydroperoxides, keto-hydroperoxides, cyclic ethers, carboxylic acids, ketones, diones and other highly oxygenated molecules. The results suggest that the previously established LTO mechanisms and kinetic models at 1 bar cannot fully represent those at high pressures. Therefore, on-line measurement systems permitting comprehensive species analysis and species quantification are preferred. Recently, we have designed a high-pressure JSR system working from 1 to 10 bar and successfully coupled it with SVUV-PIMS at the Hefei Light Source [305]. Pressure effects on the detected species are evident from Fig. 17, which also shows signal intensities of the ketohydroperoxide.

FIG. 17 Experimental (symbols) and simulated (lines) profiles of n-heptane, C2H4, CH2O, and the keto-hydroperoxide (*experimental signal intensity) in n-heptane low-temperature oxidation at pressures 1, 5 and 10 bar (residence time 2 s, equivalence ratio 1.0, fuel inlet mole fraction 0.005). Adapted from W. Chen, Q. Xu, H. Lou, Q. Di, C. Xie, B. Liu, J. Yang, H.L. Gall, L.S. Tran, O. Herbinet, F. BattinLeclerc, Z. Wang, Variable pressure jet-stirred reactor to study low-temperature oxidation chemistry by synchrotron photoionization mass spectrometry, Combust. Flame 240 (2022) 111946.

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Recent work by Zhao et al. [306,307] even pushed the pressure limit of JSRs to supercritical pressures up to 100 atm. They studied n-butane oxidation in the presence of CO2 at 100 atm [307] and carried out propane oxidation at pressures of 10 and 100 atm over a temperature range of 500–900 K [306]. They observed a weak negative temperature coefficient (NTC) behavior at 100 atm with the intermediate temperature oxidation shifted to lower temperatures [306]. Furthermore, the results showed that CO2 addition at supercritical conditions has little effect on the LTO. Detailed evaluation of high-pressure effects on low-temperature oxidation chemistry were only possible by successful coupling of such high-pressure JSRs with on-line SVUV-PIMS and other advanced diagnostics as, e.g., CRDS.

3.12.3 2030 and beyond: Combinative diagnostics for elusive species Molecular-beam mass spectrometry relies on probe sampling to enable sufficient cooling of the reactants and intermediates, while laser techniques are non-invasive. For their application, limitations must be considered, however, regarding the detection, identification and quantification of more complex intermediates: (1) Small Franck-Condon overlaps may preclude the sensitive detection of some important intermediates; (2) species and isomeric identification from photoionization efficiency curves may be unreliable; (3) significant uncertainties of cross sections might preclude a complete quantitative interpretation of the spectra; (4) access to synchrotron radiation facilities is highly competitive and therefore limited; (5) spectroscopic measurements such as CRDS need prior knowledge of the intermediates [50]. In the longer perspective, these challenges could be overcome by combining both, mass spectrometry and CRDS with a JSR system or by developing and coupling new diagnostic techniques with JSRs. A simultaneous measurement from mass spectrometry and CRDS could provide complementary information of the LTO intermediates and improve the accuracy of kinetic data. Further techniques could include PEPICO spectroscopy for isomer-resolved diagnostics in complex environments [281,308], which might also become a useful tool for the advanced diagnostics of hydroperoxides in LTO environments. In view of the limited access to synchrotron radiation facilities, laser-based mass-spectrometric diagnostic techniques have already been implemented in the laboratory, achieving ionization by four-wave mixing and APCI [50,309]. While these ionization techniques coupled with highresolution mass spectrometers permit exact determination of the molecular formula, quantification issues remain concerning the conversion of the mass spectra into mole fraction profiles—an area that would again profit from close interaction of experiment and theory. It is worth testing other advanced diagnostic techniques such as two-dimensional mass spectrometry (2D-MS) and chirped-pulse microwave spectroscopy (CP-MS) for the study of the LTO chemistry [310,311]. The 2D-MS technique, currently being developed for flame-sampling experiments, is expected to provide structural information using the collision-induced fragmentation pattern [226]. A use of CP-MS might enable unique identification capabilities as it is known to provide the most accurate molecular structures [312]. Challenges remain, however, in applying these

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techniques to the detection, identification and quantification of low-temperature oxidation intermediates. With increasing concerns regarding energy sustainability and renewability, future studies of low-temperature oxidation at higher pressures and lower temperatures using these laboratory reactors and diagnostic techniques would provide more useful data to validate detailed kinetic models and guide engine design to achieve higher fuel efficiency, lower emissions and greater fuel flexibility.

3.13 Klaus Peter Geigle: Chemistry diagnostics to resolve phenomena in soot-forming combustion processes 3.13.1 Status 2021: Laser diagnostics to probe particulate formation Particle emissions have been an important research focus in conventional combustion devices such as internal combustion and aero-engines and, consequently, pollutant emissions have been reduced significantly over the past decades. Understanding combustion chemistry—which involves monitoring the chemical reaction progress—is key to suppress undesired particulate emissions and tailor particle properties for nanoparticle production. Particle analytics alone, however, do not resolve the mechanisms leading to soot formation but only enable access to trends [313], without understanding the detailed pathways and influencing factors. Substantial recent gains in knowledge emerged from combining in situ, non-intrusive soot diagnostics with other measurement techniques and applying those to turbulent, pressurized flame conditions. In this context, accurate temperature measurements [48] are of utmost importance for any detailed combustion chemistry investigation, while the flow field in turbulent combustion determines air-fuel mixing and the residence time of pockets of fuel-rich gas composition [314]. Complementary laser-based diagnostics address gas-phase species relevant for soot formation, for example OH or polycyclic aromatic hydrocarbons [315]. While initial work of our team employed laser diagnostics at conventional repetition rates of 10 Hz, recent transfer of kHz diagnostics to increased pressure conditions has widened the horizon on soot formation by correlated measurements of soot, OH or fuel distribution and the three-component flow field [316,317], see Fig. 18. This approach is specifically important to resolve the relatively slow soot formation history in contrast to individual snapshots derived from low-repetition-rate diagnostics. The demand for access to further species has been satisfied by complementary large-eddy simulation (LES) [317] (Fig. 18). The described experimental activities focusing on ethylene as a fuel serve for the validation and development of numerical tools to further improve predictive modeling capabilities. This is achieved by application of different laser-based diagnostics to the conditions of interest, which guarantees non-intrusivity; the laser-induced effects are mostly specific due to the choice of wavelength and provide an instantaneous characterization of the quantity of interest due to the short laser pulse duration. The interested reader is referred to [46,318–320] for further details of the employed diagnostics, namely laser-induced incandescence (LII) and fluorescence (LIF), coherent anti-Stokes Raman scattering (CARS) and particle image velocimetry (PIV). Other recent implementations of correlated diagnostics to support model

3 Results: 1+13 visions

FIG. 18 Experimental visualization of multiple quantities in a gas turbine model combustor (left, red: OH, blue: fresh gas inflow, pockets labeled with arrows: rich burned gases, central region: lean burned gases); data interpretation is supported by LES modeling (right, color scale does not exceed values of 0.007) as presented in Ref. [317]; the pressurized swirl flame burns from bottom to top. Selection of instances was done on purpose, thus agreement for one individual quantity would be easy to achieve—the whole variety of quantities matches surprisingly well, however.

€ K.P. Geigle, R. Hadef, I. Boxx, C.D. Carter, M. Grader, P. Gerlinger, Time-resolved study Adapted from M. Stohr, of transient soot formation in an aero-engine model combustor at elevated pressure, Proc. Combust. Inst. 37 (2019) 5421–5428.

development exist, see for example [321–323], where nonlinear two-line atomic fluorescence (NTLAF), time-resolved LII and scattering are used to complement the suite of diagnostics.

3.13.2 Preview for 2026: Probing soot formation for an extended fuel spectrum Research for the upcoming 5 years as related to soot and monitoring of chemical species is not expected to be revolutionary but will rather build on the current state-ofthe-art. The increasing awareness of the urgent needs to tackle the climate crisis, however, will accelerate the respective research efforts. Sustainable fuels or energy carriers will be in the focus of research for the next years, and particle formation for those fuels or mixtures will persist as a hot topic for the transition period. This is even more relevant in the aviation sector as mid- and long-term aircraft will—necessarily— rely on liquid fuels for the foreseeable future, which translates to the need for sustainable aviation fuels (SAFs) and related research in the context of the climate situation. Production of carbon-based nanoparticles that exhibit specific properties will continue to drive the demand for an improved understanding of particle formation pathways. As mentioned above, for both, desired and undesired particle formation, complementary diagnostics will be required to monitor the formation process. Potential fuels and energy carriers for the future are (“green,” i.e., renewably produced)

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hydrogen, synthetic hydrocarbon fuels, biomass-based liquids and ammonia. While ramping up the production, mixtures with conventional fuels are likely to be used, specifically for cases where a significantly different combustion behavior is expected. Consequently, soot research maintains its relevance under modified conditions with a focus on changes in combustion behavior and emissions. The International Sooting Flame (ISF) community has already expressed a strong demand for research on validation data for other fuels than ethylene, specifically hydrogen admixtures or complex liquid fuels. Such results are urgently needed to develop and validate combustion chemistry models toward conventional liquid, but also increasingly diverse alternative fuels. First steps have been done [324–326] yet require intensification. Beyond improved understanding and development of modeling tools, soot research serves to classify existing and future SAFs for their emission behavior. Particulate emissions are one (important) criterion for the selection of appropriate SAFs and fuel design. Research on these topics demands development or maturation of selective optical diagnostics for specific larger hydrocarbons, PAH or soot precursors in general. Especially for in-flame PAH LIF, lots of open questions concerning selectivity and quantification exist as detailed in Refs. [327,328]; alternatively, innovative sampling/detection methods with low intrusiveness might be adopted for technical conditions [328]. Again, development of areo-engine combustors is a field in which the demand for added information, i.e., more, better, more accurate or detailed diagnostics will remain key. Another field for near-future research to improve the understanding of processes is either the development of unconventional combinations of diagnostics or coupling of even more diagnostics than possible in the past—if the added value is worth the effort. One key parameter in understanding soot formation at technical conditions is the soot maturity. A respective measurement tool might be based on the LII fluence response of soot [329,330] and is demanded by the research community. An emerging trend, which will speed up in the next years, is the use of machine learning algorithms in handling large data sets. Evaluation of correlated imaging data, specifically when acquired at kHz repetition rates will significantly benefit from these methods [331].

3.13.3 2030 and beyond: Adapting present diagnostics to demands for a carbon-neutral future Ammonia is one of the fuels discussed as future alternatives, and fundamental research of its combustion behavior as well as technology development for gas turbines, marine engines or other applications are on their way [108,332]. Hydrogen addition to conventional fuels will be another field for research. Both will foster the demand for model development and validation data: How much and by which mechanisms does the admixture of novel or alternative fuels to conventional combustion affect the particle formation, as addressed for example in Ref. [333]. Beyond the currently used laser-based diagnostics such as LII, OH and PAH LIF, specific diagnostics for those mixtures will have to be adapted to technical combustion

4 Conclusions: The clock is ticking

conditions. Potential diagnostics for this purpose are two-photon ammonia LIF [334] or Raman scattering, preferably in imaging mode [335,336]. With increasing market penetration of dual-fuel applications paving the transition toward combustion of pure components, the requirements for diagnostics will (have to) adapt toward robustness. Non-intrusive in situ hydrogen sensors can also serve for monitoring the various production pathways of sustainable aviation fuels and delivering improved understanding in those fields. Diagnosing combustion species—OH, PAH, soot, fuel, others to be developed—under realistic conditions will remain a large challenge, yet essential for future development, and requires innovative endoscopic solutions for pulsed high-power lasers as, for example, indicated in Ref. [337]. While fundamental research will remain important to further improve the understanding of innovative fuel mixtures, an increased demand for mobile yet sophisticated diagnostic systems is expected. Adaptation of tomographic laser absorption approaches from characterizing exhaust plumes toward in situ process diagnostics will be beneficial while also experiencing challenges for sufficient optical access [338,339]. Beyond the use of our “conventional” combustion diagnostics for understanding and monitoring thermal energy conversion, fuel production or particle synthesis, application to other fields is expected to grow. Among those are environmental monitoring and industry processes (chemistry, steel, cement) which can benefit from “our” diagnostics and experiences from combustion. 2050 will still see combustion present in our daily life, primarily using sustainable fuels such as liquid synthetic fuels, hydrogen or ammonia. In most cases where soot emissions are currently undesired, respective diagnostics won’t be required any more, while monitoring capability for gaseous species will remain relevant for further process optimization. For particle synthesis however, soot diagnostics and related research will persist beyond 2050.

4. Conclusions: The clock is ticking The preceding sub-chapters, while indicating different research requirements and directions from multiple perspectives, address several common motifs that may be considered as interesting avenues for future investigation. Diagnostic techniques, whether of fundamental, monitoring or sensing character, will be required to provide insight into a process, and in particular to follow the chemical reaction progress in laboratory studies and practical applications. Techniques must be refined, further developed or newly conceived to adapt to new purposes and changing conditions toward carbon neutrality. Consistently, a need for high-energy-density liquid fuels for the mid-term future has been pointed out, especially for aviation and maritime transport. Aiming for fast reduction of greenhouse gas emissions has consequences for the fuel spectrum and therefore introduces new research targets regarding their oxidation behavior and chemical reaction mechanisms. With diagnostic techniques that have enabled successful study of the present, mainly fossil fuels, a profound basis is available

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to investigate the combustion chemistry of alternative, synthetic or bio-derived fuels. While research on the production and suitability of new fuel classes should be closely monitored, it appears currently reasonable to assume that ammonia and oxymethylene ethers will belong among those carbon-neutral or carbon-reduced fuels that merit further attention in the short- to mid-term. However, combustion chemistry research must not only consider non-fossil fuels but also changes in reaction conditions, including different pressure, temperature and mixture ranges, catalytically supported processes, plasma enhancement or polygeneration. Furthermore, assessing fuel-system combinations in terms of the carbon balance and sustainable development criteria, (i.e., considering not only greenhouse gas emissions, but also water and resource management and ecosystem aspects), will increasingly need information also on upstream processing. Therefore, the diagnostic method pool tested through combustion research may be valuably applied or adapted also to inspect processes such as biomass or waste pyrolysis and syngas production. A large step forward could be the further development of chemically sensitive diagnostics that can target a multitude of species and identify their molecular structures, such as e.g., photoionization molecular-beam mass spectrometry and PEPICO spectroscopy. Although these and other techniques have contributed to a wealth of information, mainly from rather idealized laboratory experiments, a possible extension of their application range toward realistic process conditions would be highly beneficial. The combination of such techniques and their potential future modifications with the existing—and potentially further-developed—laser-based methods might permit unraveling crucial process details that could lead to game-changing insights. Experiments, even with an extended combination of techniques, will always be limited to detect or measure certain observables. Although the number of previously elusive species that could be recently identified with the aid of highly advanced diagnostic techniques seems to promise extensive screening of a given reactive species pool, the potential of theory to provide insightful information on species, spectra, ionization energies, cross sections, reaction coefficients, pressure and temperature dependences as well as thermodynamic quantities and transport properties cannot be over-estimated. Proceeding jointly and interdependently, experiment and theory can provide mutual support with opportunities for cross-examination of their respective results that can then valuably improve process models of predictive capability. In addition, the importance of machine learning, computer-based data analysis, and computer-aided model development as well as of data sharing and curation strategies is highlighted in the above sub-chapters as an area for future consideration. Data strategies will assist in restricting uncertainties, inspecting and combining existing data, testing model assumptions against the entire accessible and documented body of experiments, designing experiments with particular sensitivity to important gaps in knowledge, finding optimum reduced models for particular process conditions, and supporting non-expert-handled sensors positioned in the field with rapid and accurate evaluation of such real-time measurements from data resources. As much as it may be appealing to dream in the style of science fiction, it cannot be useful to just wait for disruptive changes in tools and methods. Also, necessary

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transformations will not be achieved relying solely on technological innovations. Further requirements include international cooperation, adequate legislative and administrative frameworks, compliance with new regulations and believable narratives to motivate behavioral changes. Transparent procedures on the administrative side and openness for scientific argumentation in the general public may help enabling and driving transformative actions. Additional key aspects include economic feasibility and an inclusive, global perspective regarding fair and sustainable development [1]. Even though diagnostics and sensors for chemical processes in a carbon-neutral future are only a small part of the large puzzle, a common motif to address the 25 years questions in this volume could be to balance between a consecutive path of “near-term marginal changes” [4] and bold visions that may create new approaches that we cannot even imagine today.

Acknowledgments Consultations and discussions with a considerable number of colleagues are gratefully acknowledged. Specifically, AF wishes to extend thanks for valuable discussions to Prof. Ron Hanson, Dr. Christopher Strand, Dr. Sean Cassady, and Dr. Jiankun Shao; JZe to Dr. Andreas Ehn and Dr. Sara Blomberg; CR to Prof. Burak Atakan and Dr. Dennis Kaczmarek; LR to Dr. Kai Moshammer and NG to Dr. Patrick Oßwald at their respective institutions. LC would like to thank Mr. Florian vom Lehn, RWTH Aachen, for fruitful discussions and valuable suggestions. KKH is grateful to Dr. Steffen Schmitt, Bielefeld University, Prof. Burak Atakan, University of Duisburg-Essen, and Dr. Nils Hansen, Sandia National Laboratories, Livermore, for critical reading and helpful suggestions. Financial support of CR by the Deutsche Forschungsgemeinschaft (DFG) within the framework of the DFG research unit FOR 1993 “Multifunctional conversion of chemical species and energy” (project number 229243862) is gratefully acknowledged. JZa acknowledges support by the Division of Chemical Sciences, Geosciences and Biosciences, Office of Basic Energy Sciences (BES), US Department of Energy (USDOE). Sandia National Laboratories is a multi-mission laboratory managed and operated by the National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the USDOE’s National Nuclear Security Administration under contract DE-NA-0003525. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the USDOE or the US Government.

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CHAPTER

High-pressure spectroscopy and sensors for combustion

15

R. Mitchell Spearrina and Christopher S. Goldensteinb University of California Los Angeles, Los Angeles, CA, United States, bPurdue University, West Lafayette, IN, United States

a

1. Motivation for high-pressure combustion and its role in pathway to carbon neutrality The bridge to carbon neutrality within propulsion and power systems will undoubtedly involve continued improvements in fuel efficiency, which has an inverse relationship with emissions. High-pressure combustion enables thermodynamic cycle benefits including increased fuel efficiency. As such, it is expected that future ultralow emission engine concepts, regardless of fuel, will require improved understanding of combustion chemistry and device performance at elevated pressures. For the purposes of this text, we will define high pressure as greater than 20 bar. This represents the domain of most modern gas turbines, reciprocating engines, and rockets. It should be noted that future ultraefficient engine concepts have been proposed with extreme combustion pressures in the hundreds of bar [1, 2]. Among other experimental and modeling challenges at high combustion pressures, a critical gap persists in combustion diagnostics. Here, we elaborate on challenges, recent progress, and future needs in high-pressure combustion diagnostics.

2. Challenges for high-pressure spectroscopy and sensing Acquiring successful laser spectroscopy measurements in high-pressure gases is more challenging due to several optical and spectroscopic complexities. First, simply securing high-quality optical access is more challenging at high pressures since this may require using smaller windows or stronger window materials with potentially less desirable transmission curves, especially at high temperatures (e.g., sapphire). This is exacerbated further by the fact that beam steering, induced by density gradients in the test gas, is more pronounced at high pressures. Second, spectroscopic complexities virtually all stem from the increased collision frequency in the gas, which can impact the shape of absorbance, emission/fluorescence, and Raman Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00005-9 Copyright # 2023 Elsevier Inc. All rights reserved.

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spectra via various collisional processes (e.g., collision broadening, line mixing). Due to their complexity, describing key aspects of these topics and their ramifications upon measurement accuracy is the focus of this section.

2.1 Collisional processes There are numerous collisional processes which impact the magnitude and/or shape (i.e., distribution in wavelength or frequency space) of spectroscopic signals. This section will clarify a few of those that are most relevant to combustion diagnostics. Collisional quenching refers to collision-induced population transfer out of an excited (typically electronic) state. This leads to a reduction in the magnitude of laser-induced fluorescence (LIF) signals and, therefore, often causes the signal-tonoise ratio of LIF diagnostics to decrease with increasing pressure and all else equal. In comparison, collisional broadening refers to a spectral broadening of absorption, emission, and Raman transitions. As a result, this primarily alters the shape of spectra and causes individual transitions to overlap in frequency space. Collisional line mixing refers to a collisional coupling of upper and lower states. This ultimately leads to shifted absorption between transitions and effectively narrows absorption bands and/ or absorption features resulting from clusters of closely spaced transitions. Of course, there are many other collisional processes (e.g., Dicke narrowing) that can impact molecular spectra [3]; however, these typically have a small impact at high pressures. The sections that follow will focus on collisional broadening and line mixing due to their large impact on absorption, emission, and Raman spectra at high pressures. The remainder of the chapter has a more specific focus on laser absorption spectroscopy.

2.2 Collisional broadening Collisional broadening is most easily understood through uncertainty principle arguments. For example, when inelastic collisions reduce a molecule’s lifetime in an absorbing or emitting state, Heisenberg’s uncertainty principle states that the energy associated with that state must become increasingly uncertain. As a result, this enables molecules in the said state to absorb photons with a range of energies (i.e., frequencies), thereby spectrally broadening the transition. In addition, collisional broadening can result from elastic dephasing collisions perturbing molecular rotation and, to a lesser extent, vibration which in turn alters the acceptable range of photon frequencies that can be absorbed or emitted by/from a given state. Last, elastic angular-momentum altering collisions can also cause collisional broadening by reorienting the angular momentum vector of the dipole [4]. Somewhat miraculously, the net result from these processes can typically be accounted for via a single parameter, ΔνC, which represents the ensemble-averaged (i.e., speed independent) collisional-broadening full width at half maximum (FWHM) of a given transition and is given by Eq. (1). Δνc ¼ P

X χ B 2γ AB ðTÞ B

(1)

2 Challenges for high-pressure spectroscopy and sensing

2

2

1 atm 10 atm 100 atm

1.5

Absorbance

Absorbance

1.5

1

0.5

0 1800

1 atm 10 atm 100 atm

1

0.5

1900

2000

2100

2200

Frequency, cm

-1

2300

2400

0 2000

2005

2010

2015

2020

2025

2030

Frequency, cm-1

FIG. 1 Simulated absorbance spectra of 1% CO at 2000 K and various pressures for a path length of 10 cm.

Here, P is the gas pressure, χ B is the mole fraction of collision partner B, γ AB is the collisional-broadening coefficient for a given transition of species A colliding with species B, and T is the gas temperature. Fig. 1 illustrates the impact of collisional broadening on the absorbance spectra of CO’s fundamental vibration bands near 4.7 μm. The spectra were calculated using the HITEMP2010 database [5] using a spectroscopic model similar to that described in [6]. At 1 atm, the absorbance spectrum consists of primarily well-isolated lines and regions of near-zero absorbance are often accessible within 1 cm1 of a transition. At 10 atm, the collisional FWHM of each transition is 10 larger and now the majority of absorption transitions partially overlap and non-absorbing regions are not in close proximity to any line, even far into the P-branch beyond 5 μm, where the line spacing is largest. At 100 atm, individual lines can no longer be observed and the absorbance spectrum is continuous. Under such conditions, it is also likely necessary to account for line mixing in the spectroscopic model, especially in the R-branch due to the reduced spacing of transitions. Accurately modeling collisional broadening typically boils down to knowing (1) the mole fraction of the major collision partners and (2) collisionalbroadening coefficients for the transitions of interest and pertinent collision partners. The former can frequently be determined with reasonable accuracy from measurements and/or major product assumptions. The latter is often available in spectroscopic databases, most notably the HITRAN and HITEMP databases [5, 7], at least for collisions with pseudo species air and the absorber/emitter itself. And these parameters are known to be quite accurate for many small molecules (e.g., CO, NO, CO2) with some exceptions (e.g., H2O) that continue to improve [4]. Collisional-broadening coefficients for collisions with other major species found in combustion gases (e.g., CO2, H2O) and air are becoming increasingly available in such databases; however, at present they are more

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widely available in the literature (e.g., see Section 3.2.3 in [4] and references therein). As a last resort, hard-sphere-based scaling relations can also be used to estimate collisional-broadening coefficients with reasonable accuracy [8–10]. This approach follows kinetic theory based approximations discussed in Chapter 8 of [11]. While pronounced collisional broadening does inevitably make it more difficult to accurately model molecular spectra, especially for complex mixtures and/ or for species whose collisional-broadening coefficients vary dramatically with collision partner (e.g., H2O, NH3) [4, 12, 13], this fact alone does not necessarily complicate accurate determination of gas properties. For example, many LAS techniques can reliably infer the collisional-broadening in situ via spectral-fitting routines and then merely use the integrated absorbances to determine gas properties [8]. Instead, often the more problematic consequence of increased collisional broadening is the absence of non-resonant wavelengths in the spectral detection window, which can be leveraged to infer the incident light intensity in LAS experiments or the background blackbody emission levels for emission spectroscopy. In such cases, more complex diagnostic strategies must be used to overcome this challenge, some examples of which are discussed in the sections which follow.

2.3 Line mixing Line mixing is a spectroscopic phenomenon resulting from molecular collisions, which induce a change in rotational energy, typically within the same vibrational energy level. At sufficiently high gas densities and collision frequencies, such collision-induced state population transfers can result in an intensity exchange between lines [3]. This effect is pronounced in spectrally dense regions, such as bandheads, or within line clusters, where line spacing is small, but can occur in many spectral domains at very high gas pressures. A set of general criteria for line mixing are worth noting: (1) neighboring transitions or lines must be from the same species; (2) the lines must be similar in upper and lower-state energies such that transfers are purely rotational; (3) the transitions must be similar in nuclear spin; and (4) collisionbroadened linewidths must be similar or greater than line spacing. This last criterion connects line mixing to gas pressure. As discussed in the previous section, collisional broadening scales linearly with pressure. Given typical values of line spacing (determined by rotational constants) and broadening coefficients, the vibrational band structure of many molecules are prone to line mixing at gas pressures above 20 bar, and at lower pressures for select molecular spectra. Recent studies of prominent combustion gases including CO, CO2, NO, and CH4 indicate the importance of appropriately modeling line-mixing effects at such pressures in order to accurately simulate or interpret molecular spectra [14–17]. Fig. 2 highlights some examples of line-mixing distortions for infrared bandheads of CO and CO2 as well as a CH4 line cluster at combustion conditions.

2 Challenges for high-pressure spectroscopy and sensing

FIG. 2 Line-mixing effects measured at bandheads of CO and CO2 and a rotational manifold of CH4 at elevated temperatures [14–16].

Line mixing and broadening are related collisional processes, albeit with greater modeling complexities associated with line mixing. Notably, the collisionalbroadening coefficient can be approximated as a summation of the state-to-state population transfer rates between lower and upper states, per Eq. (2). 2 3 X 14 X γJ ¼ R 00 00 + RJ0 !K0 5 2 J00 6¼K00 J !K 0 0 J 6¼K

(2)

For collisional broadening, we are simply accounting for the total number of statechanging collisions that reduce lifetime, whereas for line mixing, we are concerned with the individual state-to-state rates, demanding a more rigorous modeling treatment. Here, we omit the details of such modeling for the sake of brevity, but give a short overview of the pertinent details and point the reader to various sources that more thoroughly describe line-mixing theory [3, 18, 19]. Accounting for line-mixing effects involves modeling rotational-state population transfer rates (RJ!K ). While purely theoretical models exist, it is common to take an empirical or semiempirical approach to modeling line mixing with measurement data. Two empirical modeling frameworks include (1) perturbative treatment (PT) theory, also termed as first-order line mixing, and (2) exponential gap laws. In general, the PT theory is often more appropriate for examining localized line mixing at modest pressures, whereas exponential gap laws can provide convenient rotational-state scaling (based on the difference or gap in state energies) across large sets of lines that comprise an entire branch or band with only a few coefficients, and tends to work better at higher pressures [16, 20, 21]. In either case, the relaxation matrix formalism is typically used to capture the population transfer rates and incorporate into spectral simulations [22].

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3. Laser absorption strategies for high-pressure sensing Performing laser absorption spectroscopy measurements in high-pressure combustion environments often reduces to resolving a change in absorption (or differential absorption) over some range of wavelengths within the tuning range of the laser. This is especially true for narrowband diagnostics. It should be noted that fixedwavelength absorption methods, while useful in relatively quiescent environments, are prone to error in practical combustion environments due to background radiation, window fouling, particle scattering, vibration-induced transmission losses, and beam steering. Here, we focus on spectrally resolved LAS techniques, wherein the resolution of spectral structure, and separation of this information from other light attenuation or gain sources, enables much more robust sensing [4].

3.1 Narrowband LAS diagnostics At present, the majority of LAS diagnostics developed for combustion applications have utilized robust, semiconductor lasers which are instantaneously monochromatic but wavelength tunable over a narrow bandwidth (typically 1–2 cm1) [4]. Such diagnostics typically employ distributed-feedback (DFB) tunable diode lasers (TDLs) in the near infrared, and quantum-cascade lasers (QCLs) or interbandcascade lasers (ICLs) in the mid-to-far infrared. These lasers offer numerous attributes, most significantly: low cost, low noise, narrow linewidth, robustness, ease of use, wide availability throughout the infrared, and potential for fast (≫kHz) wavelength scanning across absorption transitions. A key limitation for high-pressure sensing with narrowband lasers, as already mentioned, is that their tuning range is often less than the collisionally broadened linewidths (or that of blended features) at high pressures, particularly at high scan rates (e.g., > 1 kHz). The consequence of this is threefold: (1) differential absorption within the laser spectral bandwidth diminishes with pressure; (2) at some pressure, quantitative lineshape information cannot be neglected via spectral integration and must be modeled accurately for the quantitative interpretation of differential absorption structure, and (3) a non-absorbing baseline intensity is difficult to recover. Nonetheless, numerous narrowband laser absorption sensors have been developed and utilized at high pressures with rigorous efforts to overcome the aforementioned challenges [23–31]. Narrowband LAS diagnostics for high-pressure gases in harsh combustion environments typically utilize differential absorption techniques, including wavelength-modulation spectroscopy (WMS), to avoid the need to infer the baseline light intensity and background emission. In perhaps the simplest form, differential absorption measurements are acquired by repeatably scanning the wavelength of a laser across a predetermined and fixed spectral window. If the corresponding change in laser intensity is known, for example, from a previous background measurement, and non-absorbing transmission losses are constant on the timescale of the scan, then the relative change in light intensity measured across the scan can be

3 Laser absorption strategies for high-pressure sensing

connected to the change in absorbance of the target species via Beer’s law. This change in absorbance (i.e., differential absorbance) can then be compared to spectroscopic models to infer thermodynamic properties of the gas [31]. Alternatively, a variety of WMS techniques employing some form of intensity normalization [32–35] can be utilized to acquire near-background-free measurements that are immune to non-absorbing transmission losses and background emission that vary slowly in time compared to the modulation frequency. However, in contrast to conventional differential absorbance techniques, the wavelength and intensity of the laser are modulated sinusoidally at frequency fm and a lock-in amplifier or digital lock-in filters are used to extract specific harmonic signals of interest, most frequently, the first and second harmonics (i.e., 1f and 2f). Frequently, the wavelength of the laser is also scanned in time at a frequency much less than the modulation frequency to provide measurements of WMS harmonic spectra [33]. With DFB lasers and small to moderate absorbance levels, the 1f signal is dominated by the laser’s intensity modulation, while the 2f signal is nearly background free and, in the limit of small modulation depths, closely resembles the second derivative of the absorption lineshape. Ultimately, measurements of WMS signals can be compared to those produced using calibration-free WMS models [32, 33], see example in Fig. 3, in order to infer thermodynamic properties of the test gas. While several WMS techniques have been utilized successfully in harsh, high-pressure environments, ultimately they also often suffer from reduced signal levels as the absorbance spectra of interest become increasingly broad and flat in wavelength space on the scale of the laser’s modulation depth. As a result, successful operation of a differential absorption or WMS-based LAS diagnostics at high pressures requires targeting wavelength regions where the absorbance spectra exhibit shape and curvature, which are favorable, given the scanning limitations of the laser [25]. One approach to address the first challenge of narrowband laser absorption spectroscopy (diminishing differential absorption associated with collisional broadening and blending of lines) is to probe spectral lines and features that maintain spectral

FIG. 3 Wavelength-modulation spectroscopy of CO and CO2 in bipropellant rocket combustor, highlighting line-mixing effects that enhance differential absorbance while causing near order or magnitude disagreement with traditional spectral modeling at close to 100 bar [36]

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structure at elevated pressures. A simple way to accomplish this is to target molecules and lines with intrinsically low collisional-broadening coefficients [25]. For example, Fig. 4 illustrates that the absorbance spectrum of H2O near 4030 cm1 exhibits regions with relatively high curvature and differential absorbance within the wavelength-modulation bounds achievable with commercially available DFB TDLs at modulation frequencies near 100 kHz. Goldenstein et al. [25] leveraged these attributes to maintain large WMS-2f/1f signals at high pressures and provide measurements of temperature and H2O concentration at up to 50 bar in a shock tube and later in a pulsed-detonation combustor [27]. The collisional-broadening coeffipffiffiffiffiffiffiffiffiffiffi cient scales with collision frequency, γ AB  d AB = μAB, such that a combination of small molecular size and large mass minimize collisional broadening. Of major combustion species (CO, H2O, CO2, OH), carbon monoxide tends to have the smallest line broadening coefficients, while low-J water lines tend to have the highest. More recent efforts targeting CO infrared absorption for rocket combustion analysis have been performed at pressures up to 60 bar exploiting these relationships using narrowband sources [29]. In addition to molecule-specific broadening, lines with high-rotational energy (high J) also tend to have lower collisional broadening due to larger rotational-state spacing and lower probability of state-changing collisions.

FIG. 4 Absorbance spectrum of H2O at 25 bar near 4030 cm1 illustrating the existence of large curvature and differential absorbance as well as optimal bounds for performing WMS-2f/ 1f measurements with a DFB TDL probing high-rotational-energy lines. Adapted from C.S. Goldenstein, R.M. Spearrin, J.B. Jeffries, R.K. Hanson, Wavelength-modulation spectroscopy near 2.5 μm for H2O and temperature in high-pressure and -temperature gases, Appl. Phys. B 116 (2014) 705–716, https://doi.org/10.1007/s00340-013-5754-1.

3 Laser absorption strategies for high-pressure sensing

Fig. 4 shows an example of sustained differential absorption of high-J water lines at elevated pressure. In this case, the J-dependence can overcome the molecular size and mass dependence. Another approach to maximize spectral structure within narrowband source tuning range is to deliberately target and utilize line-mixing effects, which have a narrowing effect on line clusters or bands. This spectral narrowing can effectively offset line broadening in certain spectral regions and can be particularly pronounced in rovibrational bandheads, where lines are spectrally dense. Recent work has shown that strategies targeting the R-branch bandheads of CO and CO2 in the infrared using narrowband diode and interband-cascade lasers have enabled in situ combustor measurements up to 105 and 80 bar, respectively, highlighted in Fig. 3 [31, 36]. In sum, while narrowband sources limit spectral range, strategic approaches with careful wavelength selection and rigorous spectral modeling can enable measurements at high pressures.

3.2 Broadband LAS diagnostics A wide range of broadband light sources suitable for laser absorption measurements in combustion gases continue to be developed and numerous researchers have exploited such light sources to facilitate measurements at high pressures [4]. Ultimately, these diagnostics benefit from the greater diversity of spectral information collected, which can (1) facilitate determination of the non-absorbing baseline in situ in harsh, high-pressure environments, (2) overcome decreased temperature sensitivity induced by blended transitions, and (3) help assign interfering absorbance to the appropriate species. That being said, it is important to note that broadband LAS diagnostics also must have fast (i.e., short) time resolution to ensure that gas conditions and, to some extent, beam steering are frozen during the measurement time. This section will focus on discussing the status of broadband LAS diagnostics that meet this need. In the near-infrared, vertical cavity surface-emitting lasers (VCSELs) [37, 38], Fourier-domain mode-locked (FDML) lasers [39, 40], supercontinuum lasers [41–43], and dual frequency-comb spectrometers (DCSs) [44] have been used to acquire high-speed (>kHz) measurements of temperature and several species, but most have been based on H2O due to its unusually strong overtone and combination bands. Some impressive early work was conducted with FDMLs by Kranendonk et al. [39] and Caswell [40], who demonstrated 100 kHz measurements of temperature and H2O in homogeneous-charge compression-ignition (HCCI) engines at up to 18 and 30 bar, respectively. This work demonstrated the utility of broadband (40 nm) H2O absorption in the near-IR, and the development of a microelectromechanical system (MEMS) VCSEL now enables similar measurements with a turn-key laser system (see Ref. [38] and the references therein). Supercontinuumlaser-based diagnostics have also recently been used successfully to acquire measurements of temperature, pressure, and H2O in a rapid-compression machine (RCM) at even higher pressures (up to 65 bar) and over an even larger bandwidth

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FIG. 5 Optical setup of DCS used to measure temperature and methane at 1.4 kHz in a rapidcompression machine. Adapted from A.D. Draper, R.K. Cole, A.S. Makowiecki, J. Mohr, A. Zdanowicz, A. Marchese, N. Hoghooghi, G.B. Rieker, Broadband dual-frequency comb spectroscopy in a rapid compression machine, Opt. Express 27 (8) (2019) 10814–10825.

(500 cm1)) near 1.4 μm [43], but at a lower rate (10 kHz). This approach relied on a grating spectrometer and line-imaging camera to acquire spectrally resolved measurements. More recently, a DCS emitting near 1660 nm has been used by Draper et al. [44] to acquire measurements of temperature and CH4 at 1.4 kHz (0.71 ms time resolution) at up to 21 bar in an RCM. The experimental setup is shown in Fig. 5, and an example broadband spectrum measured (with and without apodization) at 1 atm, as well as a measured temperature time history acquired in an RCM are shown in Fig. 6. All that said, it is clear that today’s researchers have the ability to acquire useful measurements of gas properties at combustion-engine-relevant pressures via broadband laser absorption in the near-infrared and these capabilities are expected to improve as the optical hardware and diagnostic strategies mature. However, unfortunately, these methods are limited to only a few combustion species and require significantly more complex and expensive optical setups compared to narrowband LAS diagnostics. In the mid-infrared, broadband light sources suitable for LAS are even less mature; however, several exciting and promising technologies have emerged and they have already enabled high-fidelity broadband LAS measurements, including external-cavity quantum-cascade lasers (EC-QCLs) [46], DCSs [47, 48], and ultrafast lasers [45, 49, 50]. EC-QCLs are the lowest cost option and exhibit the smallest footprint. They have recently been used to acquire broadband absorption

FIG. 6 Example DCS measurements of methane absorbance spectra near 1650 nm (left) and measured temperature time history in a rapidcompression machine (right). Adapted from A.D. Draper, R.K. Cole, A.S. Makowiecki, J. Mohr, A. Zdanowicz, A. Marchese, N. Hoghooghi, G.B. Rieker, Broadband dual-frequency comb spectroscopy in a rapid compression machine, Opt. Express 27 (8) (2019) 10814–10825.

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measurements of several hydrocarbons in shock-tube experiments, but with modest time resolution (approximately 1 ms) and they are only available in a few spectral windows. They have also not been applied to high-pressure combustion gases yet, although they are well suited for such applications. For example, Strand et al. [46] used an EC-QCL to acquire measurements of C2H4 between 8.5 and 11.7 μm in shock-heated gases with a time resolution of 3 ms. DCSs have also emerged in the mid-IR in several architectures and their broad bandwidth makes them attractive for high-pressure measurements; however, to our knowledge they have also not been applied to study high-pressure combustion gases yet [47, 48]. Ultrafast lasers in combination with optical parametric oscillators (OPOs) [50] or optical parametric amplifiers (OPAs) [45, 49] have enabled high-speed (5–20 kHz), broadband measurements of numerous species in the mid-IR, namely the 3–5 μm window. Tancin and Goldenstein [45] recently demonstrated the ability to measure temperature and CO over an 80 nm bandwidth near 5 μm in multi-phase propellant flames at up to 40 bar with ultrafast (sub-nanosecond) time resolution and a 5 kHz repetition rate using ultrafast laser absorption spectroscopy (ULAS). Fig. 7 illustrates a CAD rendering of a typical ULAS experimental setup and Fig. 8 illustrates example single-shot time histories of gas temperature and CO column density (χ COL) as well as representative single-shot absorbance spectra of CO near 5 μm. The ultrafast time resolution of ULAS is ideal for “freezing” highly transient environments, while the broad bandwidth facilitates in situ determination of the non-absorbing baseline and improves temperature sensitivity by measuring a wide range of transitions with a large difference in lower-state energy. Further, at high pressures, the instrument broadening incurred from utilizing a grating spectrometer to spectrally resolve the ultrashort pulses is less significant compared to the transition linewidths, thereby effectively

FIG. 7 Schematic illustrating the optical setup used to characterize high-pressure propellant flames with a broadband mid-infrared ULAS diagnostic [45].

FIG. 8 Example single-shot, broadband ULAS measurements of CO absorbance spectra near 5 μm and corresponding time histories of temperature and CO column density (χ COL) acquired in AP-HTPB propellant flames at 20 and 40 bar. Results taken from R. Tancin, C. Goldenstein, Ultrafast-laser-absorption spectroscopy in the mid-infrared for single-shot, calibration-free temperature and species measurements in low- and high-pressure combustion gases, Opt. Express 29 (19) (2021) 30140–30154, https://doi.org/10.1364/oe.435506.

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removing a disadvantage of this approach. However, while ULAS is well suited for characterizing high-pressure combustion gases and accessing a wide range of species across the UV to far-infrared, at present it requires the use of more complicated and less portable hardware.

3.3 Research needs for the next 25 years Advances in high-pressure diagnostic capability are needed to enable the next generation of high-efficiency combustion systems, including those using low-carbon or carbon-neutral fuels. As described in the prior sections, very few laser diagnostic methods (few species-specific techniques) are useful at the high-pressure conditions (>20 bar) of most modern combustion engines. Laboratory experiments are more often carried out at lower pressures with some assumption of pressure scalability. However, non-linear properties near and above the critical point of reactant and product mixtures bring into question the reliability of such assumptions. This is also evident in spectroscopic interactions, wherein non-linear effects such as line mixing can dramatically distort spectra at supercritical pressures and invalidate traditional lowpressure scaling laws, which are often extrapolated to high pressures. Some specific needs are outlined below. More comprehensive and improved spectroscopic models are needed to support the interpretation of high-pressure spectra from narrowband and broadband sources. This will require high-pressure spectroscopy studies that investigate line mixing and broadening effects for target species with a range of collision partners typical of combustion gas mixtures. Experiments that examine high-pressure mixing and broadening in hydrogen and water vapor (which will undoubtedly be a major combustion product in the low-carbon future) are particularly needed. Such experiments with water vapor are challenging due to low vapor pressure of water at ambient temperature. Collisional effects on molecular spectra associated with major unstable intermediates (such as OH) are also needed, but perhaps even more challenging. Strategies to directly or indirectly address these experimental issues are needed, as line mixing and broadening have a strong composition dependence. Coupled theoretical studies are likely required to help extend understanding to areas where wellcontrolled experiments are not practical. Continued light source development is needed to increase the number of accessible species and parameters that can be probed via spectroscopy in high-pressure combustion environments. Extended tuning range of semiconductor narrowband sources and expanded domain (e.g., far-IR or UV) would very likely enable higher-pressure capability for more species. The maturity of broadband sources is also greatly needed. Although broadband sources have an obvious advantage in spectral bandwidth to overcome the issue of collisional broadening, the performance limitations in other areas have limited deployment and utility in combustion environments. Areas of needed improvement (depending on the source type) include spectral scan speed or repetition rate, stability in power and wavelength, scan repeatability and noise, spectral resolution, size, and cost. The integration of more robust

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effects for laser absorption spectroscopy at extreme combustion pressures, Proc. Combust. Inst. (2020), https://doi.org/10.1016/j.proci.2020.08.037. S.T. Sanders, D.W. Mattison, L. Ma, J.B. Jeffries, R.K. Hanson, Wavelength-agile diodelaser sensing strategies for monitoring gas properties in optically harsh flows: application in cesium-seeded pulse detonation engine, Opt. Express 10 (12) (2002) 505–514. K.D. Rein, S. Roy, S.T. Sanders, A.W. Caswell, F.R. Schauer, J.R. Gord, Measurements of gas temperatures at 100 kHz within the annulus of a rotating detonation engine, Appl. Phys. B Lasers Opt. 123 (3) (2017) 88. L.A. Kranendonk, X. An, A.W. Caswell, R.E. Herold, S.T. Sanders, R. Huber, J.G. Fujimoto, Y. Okura, Y. Urata, High speed engine gas thermometry by Fourier-domain modelocked laser absorption spectroscopy, Opt. Express 15 (23) (2007) 15115–15128. A.W. Caswell, Water Vapor Absorption Thermometry for Practical Combustion Applications (Ph.D. thesis), University of Wisconsin, 2009. S.T. Sanders, Wavelength-agile fiber laser using group-velocity dispersion of pulsed super-continua and application to broadband absorption spectroscopy, Appl. Phys. B Lasers Opt. 75 (6–7) (2002) 799–802, https://doi.org/10.1007/s00340-002-1044-z. N.G. Blume, V. Ebert, A. Dreizler, S. Wagner, Broadband fitting approach for the application of supercontinuum broadband laser absorption spectroscopy to combustion environments, Meas. Sci. Technol. 27 (1) (2016) 015501, https://doi.org/10.1088/0957-0233/ 27/1/015501. T. Werblinski, P. Fendt, L. Zigan, S. Will, High-speed combustion diagnostics in a rapid compression machine by broadband supercontinuum absorption spectroscopy, Appl. Opt. 56 (15) (2017) 4443–4453. A.D. Draper, R.K. Cole, A.S. Makowiecki, J. Mohr, A. Zdanowicz, A. Marchese, N. Hoghooghi, G.B. Rieker, Broadband dual-frequency comb spectroscopy in a rapid compression machine, Opt. Express 27 (8) (2019) 10814–10825. R. Tancin, C. Goldenstein, Ultrafast-laser-absorption spectroscopy in the mid-infrared for single-shot, calibration-free temperature and species measurements in low- and high-pressure combustion gases, Opt. Express 29 (19) (2021) 30140–30154, https:// doi.org/10.1364/oe.435506. C.L. Strand, Y. Ding, S.E. Johnson, R.K. Hanson, Measurement of the mid-infrared absorption spectra of ethylene (C2H4) and other molecules at high temperatures and pressures, J. Quant. Spectrosc. Radiat. Transf. 222 (2019) 122–129, https://doi.org/10.1016/ j.jqsrt.2018.10.030. N.H. Pinkowski, S.J. Cassady, C.L. Strand, R.K. Hanson, Quantum-cascade-laser-based dual-comb thermometry and speciation at high temperatures, Meas. Sci. Technol. 32 (3) (2020) 035501. A.S. Makowiecki, D.I. Herman, N. Hoghooghi, E.F. Strong, R.K. Cole, G. Ycas, F.R. Giorgetta, C.B. Lapointe, J.F. Glusman, J.W. Daily, Mid-infrared dual frequency comb spectroscopy for combustion analysis from 2.8 to 5 μm, Proc. Combust. Inst. 38 (1) (2021) 1627–1635. R.J. Tancin, Z. Chang, M. Gu, V. Radhakrishna, R.P. Lucht, C.S. Goldenstein, Ultrafast laser-absorption spectroscopy for single-shot, mid-infrared measurements of temperature, CO, and CH4 in flames, Opt. Lett. 45 (2) (2020) 583–586. Z.E. Loparo, E. Ninnemann, Q. Ru, K.L. Vodopyanov, S.S. Vasu, Broadband midinfrared optical parametric oscillator for dynamic high-temperature multi-species measurements in reacting systems, Opt. Lett. 45 (2) (2020) 491–494.

CHAPTER

Bio-derived sustainable aviation fuels—On the verge of powering our future

16

Mukul Tomara, Abhinav Abrahama, Keunsoo Kimb, Eric Mayhewc, Tonghun Leeb, Kenneth Brezinskya, and Patrick Lyncha Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, United States, bDepartment of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, cWeapons and Materials Research Directorate, US Army Combat Capabilities Development Command Army Research Laboratory, Adelphi, MD, United States

a

1. Overview Aviation fleets play an indispensable role in generating economic growth and connecting people, cultures, and businesses worldwide. The aviation industry contributes a 3.5% share (2.7 trillion US Dollars) to global Gross Domestic Product (GDP), and it is growing at a fast pace [1,2]. According to the most recent estimate for the next 20 years by the International Civil Aviation Organization (ICAO), air traffic will rise by an average of 4.3% annually. Envisioning this scenario, aviation will then promote $1.5 trillion of GDP to the worldwide economy and even more (appx. $5.7 trillion) if the global tourism impact is taken into account [3]. Beyond integrating national and international trade and tourism, the industry also provides vital support to critical sectors of society including healthcare, education, defense, and the space industry. The modern aviation sector is a reliable, rapid transportation network. Yet, it is also particularly exposed with respect to remediating the impact of climate crises and warming impact, now and increasingly into the future. For the foreseeable future, especially in the context of the retrospective cost of the current and near-future transportation fleet, liquid hydrocarbon fuels will remain paramount, if only for energy density purposes. This is especially true for defense aviation. Yet aviation’s reliance upon conventional petroleum-based fuels, their imperfect efficiency, coupled with harmful emissions, present key challenges to long-term deep decarbonization [4]. Environmental concerns in this sector have risen dramatically since 1990. Out of 43 billion tons of CO2 production by humans, 918 million tons are generated alone Combustion Chemistry and the Carbon Neutral Future. https://doi.org/10.1016/B978-0-323-99213-8.00013-8 Copyright # 2023 Elsevier Inc. All rights reserved.

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from flights worldwide in 2019 [5]. A similar scenario is observed in the United States, where among all transportation sources, aviation accounts for 6.7% of greenhouse gas (GHG) (i.e. CO2, CH4, N2O, and hydrofluorocarbons [HFCs]) emissions in comparison to 75.2% from the on-road transportation [6]. Depending on the annual air traffic increase as well as decarbonization scenarios for ground transportation, it is anticipated that the proportion from aviation will rise steeply if these trends are extrapolated ahead [7]. In view of these rising concerns, the current energy system requires sustainable alternatives that can result in cleaner combustion and improve the sustainability of the aviation sector without hindering the momentum of economic development. The second section of this chapter briefly highlights these concerns. Among all the chemical-based alternatives to liquid petroleum bases evaluated to date, including hydrogen, natural gas, and methane, Bio-derived Sustainable Aviation Fuel (BSAF) or bio-jet fuels, the product of edible, inedible, and waste biomass is considered a very promising potential “drop-in” substitute fuel for the millions of existing aircraft engines [8–10]. The term “drop-in” here refers to the fuels that can be easily blended with the conventional jet fuels or at times can be used in neat form with the existing fueling infrastructure. Owing to their potential carbon-neutrality, biodegradability, safe handling, and generally appropriate physiochemical properties, research and development of sustainable biofuel production technologies has drawn large and increasing attention worldwide. Therefore, the third part of this chapter provides an overview of BSAFs. This section includes requirements on fuel properties, available conversion pathways, and current and potential biofuel feedstocks and their underutilized potential. Several challenges on the production side, particularly limited feedstock, high production costs, engine operational issues, and lack of indicated and dedicated government policies, etc., are highlighted in challenges [11–13]. Despite the attractions of BSAF, especially considering the ambition for decarbonization, their viability as a drop-in fuel is still unresolved. In light of the above efficient production pathways, potentially viable feedstock, and properties of the resultant fuels, the challenges associated with drop-in fuels both on the fundamental chemistry side and on the engine retro fitment side are highlighted. Although scientists and engineers are working on different aspects to enable this technology, including engine retro fitments and fuel reformulation approaches, focus toward drop-in fuels is paramount [14]. In this context, the fourth section of the chapter emphasizes biofuel technological advancement, its limitations, and challenges. Finally, we conclude with a detailed discussion on a new window of opportunities for BSAF within and then beyond the current state of the art. This includes novel future pathways to mitigate the challenges in the roadmap of BSAF commercialization and achieve the sustainability goals for the aviation industry, potential strategies for closer property matching, and strategies for modeling and dealing with varied and uncontrolled properties, most prominently ignition properties. We also briefly provide an outlook on some challenges and opportunities in BSAF for advanced propulsion topics.

2 Why bio-fuels?

2. Why bio-fuels? The energy scenario of the world is highly uncertain, and its future projections are difficult to predict. Several factors including volatility in energy prices, economic growth rate, demographic shifts, technological developments, government policies, and consumer behavior are responsible for shaping the global energy market [15]. Energy consumption rates are generally gauged based on the amount of energy consumed from all available sources per year. The chart in Fig. 1 shows the total energy consumption of the top 15 energy-consuming countries in 2020. As can be seen, China and India account for more than 2/3 of the energy consumed by the top non-OECD (Organization for Economic Cooperation and Development) countries, whereas, the share of United States remain highest (i.e., 87.7 EJ) among the OECD countries. Due to global lockdown measures and transport restrictions in the year 2020, overall decreases in energy consumption of 7.6% in United States, 7% in European countries, 4.8% in Japan and Canada, 3% in India and South Korea, and 2% in Australia and Brazil were observed compared to the previous year. This is evident in the primary energy consumption statistics, see Fig. 2A. The only rise in energy demand was registered for the leading consumer- China-with a 2.2% increase over the previous year, irrespective of the lockdown measures [16,18]. Nevertheless, the previously mentioned decrease in demand is thought to be short-lived for non-OECD countries and is expected to return to pre-pandemic levels soon in the coming years, in line with their development objectives. Alternatively, for OECD countries, the demand for energy (and primary energy sources) is also expected to rise, but with a steady rate compared to non-OECD countries partly attributable to increasingly stringent efficiency standards despite growth. The exception for OECD countries is coal

FIG. 1 Primary energy consuming countries in 2020 and their total consumption in Exajoules [16].

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FIG. 2 World primary energy (A) consumption through 2050 and (B) percentage share comparison of different sources, predicted by EIA based on WEPS model [17].

2 Why bio-fuels?

consumption, expected to decrease due to its environmental concerns, the continued shift to natural gas, and the subsequent lack of investment in coal-powered plants. Further down the line, we highlight the long-term energy projection of the world through 2050, which is based on the WEPS (World Energy Projection System) report prepared by EIA (US Energy Information Administration) in 2021 [17]. WEPS is an integrated economic assumption-based model which emphasizes on long-term correlations among energy supply, consumption, and prices in regional markets throughout [19]. Taking a look at the total primary energy consumption by different energy sources in Fig. 2, the demand for liquid fuels is expected to remain dominant, despite increased share of renewable energy usage to almost identical, i.e., 27% of global energy consumption. The consumption for liquid fuel is estimated to be 199.08 quadrillion Btu in 2022, and is anticipated to grow 24.8% in 2050. Among liquid fuels, the demand for motor gasoline, distillate, and jet fuels are expected to be remain on top, attributed to the increase in the world’s population and amplification of passenger and freight travel in the next 28 years. However, the actual problem does not lie with the ever-increasing energy demand per se, if it can be achieved with supply and alternative energy technologies in the long run. Increasing global energy related CO2 emissions across the projection period are of concern, despite new policies, improved energy efficiency, and increased renewables growth through the projection period. Moreover, if the emission levels of OECD and non-OECD countries are compared, the latter alone account for 35% higher CO2 emissions over 2020, compared to OECD countries, which increase about 5% [20]. This is because of the reliability of non-OECD countries on fossil-based products (especially coal) to meet the growing demand, resulting in higher average carbon intensity. Fig. 3 illustrates the long-term projection of the energy-related net CO2 emissions for both OECD and non-OECD countries highlighting the contribution of different

FIG. 3 Net CO2 emissions projection by different energy sources [20].

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primary sources (liquid fuels, coal, and natural gas). Major differences can be observed for projected emissions from coal usage. However, liquid fuels act as a catalyst in emission growth rate with similar scenarios for both the OECD and nonOECD regions [20]. Ultimately, the energy projections review highlights that liquid fuels are important when it comes to consumption or net CO2 emissions. Further breaking down the demand for liquid fuels on the basis of energy sectors, transportation alone consumes 60–70% of their total availability [21]. Consequently, their share in the global CO2 emission is also notably higher. As can be noticed in Fig. 4A, highlighting the share of different sectors in 2020, the transportation sector alone leads to 20.2% rise in global CO2 emissions, comparable to industrial combustion but less than the power industry with 21.7% and 36.5%, shares respectively. Within the transportation modes, some predictions have decarbonization goals achieved by 2070, except for medium/heavy-duty trucks, shipping, and the aviation sector. Fig. 4B shows the projection of the long run global CO2 emissions in Gt (Gigatons) predicted by the International Energy Agency (IEA) based on their Sustainable Development Scenario (SDS). The SDS model for transportation is based on vehicles life-time, electrification scope, alternative low-carbon fuels acceptation, and sustainability upgrades in passenger movability and freight services [21]. The forecast shows a reducing trend of emissions with each passing year after 2025 for all modes of transport. The overall CO2 emission is projected to decrease from 6.7 Gt in 2010 to 0.9 Gt by 2070. This is mainly a reflection of transition toward electric vehicles infrastructure. The passenger car industry, where nearly 90% of the total passenger car is expected to be electrified and the remaining 10% will be driven by hydrogen-based fuel cell technologies, is expected to achieve net zero CO2 emission by 2070. For shipping and aviation, where global CO2 reduction trend is comparatively slow, the curtailment of CO2 emissions from these sectors is a formidable task and requires significant upgrades. This appears especially true of aviation, where the global CO2 reduction pace is expected to be slowest. Perhaps measures like structural shifts in passenger and freight mobility, adoption of low-carbon fuels, and technological modification resulting in energy efficiency improvement over the next half-century can be a significant step ahead. The present air transport network contributes to worldwide CO2 emission and its repercussions, such as climate change, and it requires a persistent solution. Replacing the energy of conventional jet fuel with batteries is not a viable solution, largely due to specific energy and energy density considerations. Instead, improving the fuel efficiency technologies by adopting minor retro fitments and simultaneously promoting low-carbon based biofuels can bring significant reduction in not only emission trajectory but also curb the rising demand for conventional jet fuels. The volatility in the prices of jet fuel is a matter of economic and geopolitical concern on top of the environmental concern. Many airlines use kerosene-based petroleum fuel, whose prices are dependent on the global price of crude oil. Crude availability and prices are vulnerable to supply shocks; many recent events, including recently a global pandemic, war, and political instability, have affected crude oil

2 Why bio-fuels?

FIG. 4 Global CO2 emission (A) percentage share by different energy sector in 2020 and (B) projected amount by different transportation modes until 2070, predicted by IEA based on SDS model [21].

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FIG. 5 Variation in jet fuel price with respect to crude oil rate of change over the years [22].

supply. Fig. 5 shows the jet fuel price per gallon compared with the crude oil price per barrel over 10 years. Fluctuations in jet fuel prices further cause substantial disruption in the airlines’ financial status and eventually the end-users, as 20–30% of the airline’s total expenses are related to jet fuel costs [23]. With consistent growth over the years, the transportation (people and goods) sector used approximately 35% of the world’s energy in 2020 [17]. Within this, the aviation industry alone consumed 8% of the energy used for transportation [24]. In terms of impact to climate, Friedlingstein et al. [25] showed that aviation fleets contribute a 2.5% share of the world CO2 emissions. From the early 90s to date, CO2 emissions from the aviation industry have grown by 54%, and based on the rising air transport demand, they are anticipated to rise annually by 4.3% through the middle of the century according to a report published by Climate Action Network (CAN) and International Coalition for Sustainable Aviation (ICSA) [26]. Additionally, the overall share of non-CO2 emissions contributed by aviation fleets to global climate change is even greater. Two-thirds of the total aviation emissions are nonCO2 based, such as NOx, soot, sulfate aerosols, and water vapor trails, which are far more responsible for global warming effects in comparison to CO2 emissions. This can be demonstrated based on a study by Lee et al. [27] estimating overall effect of both CO2 and non-CO2 based aviation emissions by calculating radiative forcing. Radiative forcing is the measure of change in balance of radiation striking the earth’s atmosphere and going out to the space. The results showed an approximate of 3.5% effective radiative forcing associated with global aviation. To mitigate warming tied to emissions, governments, national bodies, the aviation industry, and international institutes are introducing stringent emission standards to tackle these environmental concerns and ensure compatibility with the 2016 Paris Agreement. The airworthiness standard formulated by the Federal

2 Why bio-fuels?

Aviation Administration (FAA), United States, and European Aviation Safety Agency (EASA) by the European Commission is one such step forward toward the goal [28]. Researchers and stakeholders are also exploring different alternative energy sources for transportation fuels. While the use of cheaper US natural gas has driven a decrease in emissions in stationary power generation [29,30], conversions of natural gas to jet fuel do not seem to have bright prospects to serve as a drop-in jet fuel [31,32], nor does the use of natural gas in transportation turbines. Among the reasons for this include (i) Lower heating value and mass density requiring engine retro fitment for existing aircraft, and (ii) methane leakage concerns. Although combustion of natural gas leads to lower CO2 emissions, a leakage of just 1% of the fuel erases those global warming benefits. Ultimately, the expansion of electric and hydrogen-based fuel cell technologies may have a role in aviation after substantial breakthroughs in energy density, but not for the foreseeable future. Small aircrafts though represent an easier target for both these technologies, but there are substantial barriers to their widespread adoption. In fact, due to the ever-rising air travel demand and associated emissions, it is one-step forward, two-steps back for aviation. Therefore, low-carbon alternative fuel seems the most appropriate near-term use solution especially in terms of existing fleet fueling infrastructure. Moreover, increasing aviation demand and high capital cost provide significant barriers to companies trying to transition their fleets, including developing potential novel supply chains for new aircraft (e.g., rare earths for supplies of batteries, etc.). It is also unclear if this is wise from an energy security standpoint [33–35]. There are enormous technical challenges associated with the transition, most significantly to the poor specific energy and energy density provided by batteries relative to jet fuel. For illustrative purpose, take the example of Boeing 747-300, it almost requires 120,000 lb of jet fuel for its 5 h of flight duration (excluding some extra fuel in case it needs to a stay longer in air). Substituting the same amount of fuel energy might require a battery weighing 5.8 M pounds—which is around 7 times the weight of a plane fully fueled [36]. Thus, multiplication of battery weight with the initial load that the aircraft needs to carry requires additional energy and seems not to be a feasible approach. There are opportunities to make emissions improvements with the existing fleet, by utilizing alternative fuels that can mimic the useful properties of petroleum fuels. Additionally, improvements in efficiency and operability are possible with hybridelectric technologies and innovative new aerodynamic designs with lighter and stronger composite materials. However, the potential improvements from these efforts are limited and can reduce overall aviation CO2 emissions by only
5%, which is nowhere close to fulfilling short-to-mid-term aviation emissions reduction goals [37]. Alternatively, bioenergy extracted from widely available renewable sources offers a path to renewable jet fuels. Biomass-derived synthesized paraffinic kerosene (Bio-SPK) blended with conventional jet fuel as a “drop-in” fuel can lease new life to

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the existing millions of aircraft engines while sharply reducing emissions by 2050. In this regard, biofuel researchers and stakeholders worldwide are working on emerging technologies and probing future pathways. Comparing bio- and fossil-derived jet fuels in terms of CO2 and pollutants, the level of CO2 emission is the same. The difference comes when the net climate effect is accounted for. In the case of fossil-based fuels, new carbon emissions are introduced at multiple stages, due to their extractive origins. Whereas, due to bio-based fuels’ renewable sources (crop residue, waste/residual biomass, used cooking oil) and cleaner production methods, the emission of new carbon is less and can potentially degrade over time [37]. Considering these benefits, biofuels are increasingly attractive fuel sources as prominent international agencies and government agencies consider the significant environmental benefits. International Air Transport Association (IATA) has endorsed the advisory of reporting CO2 emissions in an effort to cut down the international flights emission rate to the 2020 level by 2026 and then reduce it to one-half of the 2005 emission level over time [38]. The plan states that incoming and outgoing international flights of all the major countries will be required to report their CO2 status annually. Similarly, to facilitate the production of sustainable biofuels, the US administration is also leading from the front and is planning to increase dramatically the production rate of bio-derived jet fuels to 3 billion gallons by 2030. Thus, all these combined efforts and initiatives are convincing proof that the scale-up of bio-jet fuels has already started and will continue if an appropriate setup for its commercialization is established.

3. Overview of bio-derived jet fuels

3.1 Overview of fuel properties requirements Bio-derived jet fuels (also termed renewable jet fuels, bio-jet fuels, and sustainable aviation fuels in various literature) or BSAF (for short in this chapter) having comparable properties to conventional jet fuels have gained interest to address the needs of both emission policymakers and aviation stakeholders. Due to their biological and waste source origin, distinct structures, chemical compositions, and favorable physicochemical properties, these low-carbon fuels have huge potentials to offer clean combustion and other operational efficiency improvements in the near term [39,40]. Multi-component conventional commercial jet fuels (such as Jet A in United States and Jet A-1 in EU) are made up of a mixture of many normal alkanes, cyclo-alkanes, and iso-alkanes and fewer aromatics and olefins. These molecules have carbon chain lengths ranging between C8 and C16 [41]. The aromatic content in conventional jet fuel lies in the range 8–25% by volume. In addition, traces of nitrogen, sulfur, and oxygen containing compounds are also present in the fuel [42]. The presence of these components and their concentration substantially affects the physicochemical properties of the fuel. Higher hydrogen-to-carbon ratio of alkanes and iso-alkanes results in higher heat-to-weight ratio, promoting cleaner

3 Overview of bio-derived jet fuels

combustion of fuel. Cyclo-alkanes lower the heat release per unit weight by reducing hydrogen-to-carbon ratio, although they offer an advantage of reducing fuel freezing point, which is an important fuel property when it comes to the aircraft high altitude operation [43]. Fuels rich in aromatics have higher density, better water solubility, lower heating value, and high surface tension, contributing to smoke formation which further has detrimental effects on the combustion chamber and turbine blades [44]. On the other hand, aromatics improve the energy density and reduce fuel leakage issues by preventing the shrinkage of old O-ring seals [42]. Thus, for better operability of engine, a fuel’s aromatic content should lie within an optimal range. While there are a few composition restrictions in fuels, i.e. for sulfur (ranging from 300–3000 ppm by weight), aromatics (max 25% by volume), etc., the majority of fuel characteristics are based on physical properties. These properties include flow properties (such as density, viscosity, and surface tension which additionally affect spray atomization), flash point, freezing point, and boiling characteristics (distillation parameters affecting liquid to vapor rate of transformation) [45,46]. Therefore, in general, there exists standard limits set by fuel properties’ governing bodies required for the fuels to be certified. Fuel certification is a systematic process discussed and referenced later in Section 4.2. The ASTM (American Society for Testing and Materials) D1655 specifications defined for fuel physicochemical properties are as follows [46,47]: 1. 2.

Fuel minimum energy density by mass (typically 33.17 Gk/m3 at 15 °C). Fuel maximum distillation temperature at 10% recovery point (205 °C), final boiling point (300 °C). 3. Maximum allowable temperature of the fuel freezing point (47 °C). 4. Maximum acceptable limit of deposits during a standardized heating test (7 mg/100 mL). 5. Maximum allowable viscosity (8 mm2/s at 20 °C), and density (771–836 at 20 °C). 6. Maximum acidity (total acid number 0.015 mg KOH/g). 7. Minimum allowable limit of fuel flash point (38 °C). 8. Maximum allowable limit in standardized wear test of fuel (wear scar diameter 0.85mm). Apart from these properties, due to the significance of fuel calorific value, the ASTM has also specified standards for chemical properties such as hydrogen content, smoke point and net heat of combustion [48]: 9. Minimum net heat of combustion (42.8 MJ/kg). 10. Minimum hydrogen content (13.4% by mass) 11. Minimum smoke point (25 mm). Alternative fuels, intended for use as a substitute jet fuels, are distinguishable based on their performance, operability, and drop-in compatibility. All these parameters are necessary for safer, general usage and execution of specific tasks assigned to the aircrafts. The majority of physicochemical properties of jet fuels are derived from long chain hydrocarbon mixtures and their composition (e.g. aromatics don’t burn

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cleanly due to their low net heat of combustion and have important soot precursors thus resulting in 90% of particulate emissions) [44]. Similarly, the presence of minor components such as nitrogen and oxygen results in deposit formation and sometimes even affects the long-term stability and drop-in compatibility of the fuel [49]. Developing new fuels, perhaps with an approach of eliminating heavy multi-ring aromatics and lowering overall aromatic content can significantly reduce emissions, minimize hotspots and improve specific energy. However, as the aromatics add other beneficial properties, one route forward is use of cycloalkanes and organic compounds such as decalins and ethyl benzene respectively, which have the tendency to maintain the existing O-ring swelling properties, thus compensating the heavier aromatics properties [23]. Secondly, incorporating fuel additives and engine retro fitment approach (discussed in the later sections) can also be a promising solution for improving the combustion characteristics and bring down the harmful emissions. Considering the property requirements, high quality bio-fuels are needed for use as drop-in jet fuels, which can be achieved by coupling efficient production pathway with potential feedstock. The subsequent sub-section provides insight about focused chemical/biological routes for efficient conversion of biomass to jet fuels.

3.2 Overview of bio-derived jet fuels production-pathways With an objective to meet the demand of the aviation industry, numerous conversion pathways have been developed in the past. Some of these approved pathways of biojet fuel production are already in use while others are undergoing tests against ASTM standards, as listed in Table 1. The following sections below describes each process in detail.

3.2.1 Hydroprocessing of oil-to-jet (OTJ) fuel The OTJ process of bio-derived jet fuel production is categorized into different types depending on the hydrotreatment of triglycerides: (1) Hydroprocessed Esters and Fatty Acids (HEFA) also sometimes referred to as Hydroprocessed Renewable Jet (HRJ) fuel, (2) Catalytic Hydrothermolysis (CH) also known as hydrothermal liquefaction-based biofuel, (3) Hydrotreated Depolymerized Cellulosic Jet Fuel (HDCJ), is in the mix, but has yet to receive ASTM blending approval. 1. HEFA-SPK This is the most popular and versatile bio-derived jet fuel production pathway used at an industrial scale and is a primarily preferred pathway in the defense sector. Synthetic paraffinic kerosene derived from HEFA is considered the fuel with highest potential for “drop-in,” with excellent ignition properties, lower aromatics, and low sulfur content, thus resulting in cleaner burning and lower greenhouse gas emissions [50]. The process aim of the hydrogenation is to convert different levels of unsaturated fatty acids (carbon double bond chain) present in the renewable fats and oils to completely saturated ones (carbon single bond chain). The initial step involves the breakdown or conversion of the double-bonded triglyceride, carried

Table 1 List of conversion pathways, status as of 2022, applications and appropriate feedstock. ASTM approval

Pathway/subcatagory Oil-to-jet (OTJ)

HEFA-SPK

2011

Catalytic hydrothermolysis (CH) Hydrotreated depolymerized cellulosic jet (HDCJ)

2020

Alcohol-to-Jet (ATJ)

Direct sugar to hydrocarbon (DSHC)

Fischer-Tropsch (FT)

Lignin to jet (LTJ)

Test against ASTM ongoing 2016

Biological conversion

2014

Catalytic upgrading

Test against ASTM ongoing 2009

Test against ASTM ongoing

Flight/company

Feedstock

References

B747-400/Boeing B737-800/Boeing Ralls-Royce Falcon 20/Dassault Aviation T-33/ Lockheed N/A

Vegetable oils, used cooking oils, tallow, Jatropha oil

[50–52]

Soybean oil, camelina oil, jatropha oil, wet biomass, vegetable oils Wet or dry lignocellulosic biomass

[47]

B737-800/Boeing A-10C/Fairchild Aircraft G3-7725/GOL LH190/Lufthansa AF 6313/ AIRFRANCE N/A

Post-harvest residual biomass

[31,54,56,57]

Sugarcane, beets

[58–61]

Furfural, GVL, HMF

[47,62–66]

C-17 Globemaster III/Boeing B-52 Stratofortress/ Boeing N/A

Woody feedstock, municipal solid waste

[58,67–81]

Lignocellulose such as poplar tree, wheat straw

[9,82–88]

[53–56]

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out in the presence of a conventional catalyst and exclusive hydrogen supply. The point when molecules of triglyceride are broken down into three-chain fatty acids is termed as complete hydrogenation. During this process, hydrogen along with the catalyst used for hydrotreatment is added to the saturated fatty acid chain. The next step is reduction of long hydrocarbon chains within the range of jet fuels by continuous hydrogen supply. The outcome results in conversion of glycerol compounds into propane and a chain of saturated fatty acids. Thereafter, oxygen is separated from the fatty acid chains. Depending on the required side product and hydrogen supply, the oxygen separation can be done in different ways. For example, an H2O molecule can be produced by a hydrodeoxygenation pathway; CO2 can be produced by a decarboxylation process; and lastly, CO and H2O are produced if the decarbonylation reaction is carried out with the fatty acids [89]. Although, some traces of oxygen will be present in the fuel produced, these prevent further contamination while in the fuel supply because of oxidation. Note that the role of hydrogen supply, catalyst selection, and reaction parameters (time, temperature, pressure) are very crucial and require proper handling if complete saturation of fatty acids and proper separation of byproduct glycerol is to be achieved at the end of the reaction. Generally, the catalysts which have been explored include NiMo/γ-Al2O3 and CoMo/γ-Al2O3, whereas temperature and pressure range 250–400 °C and 10–18 bar respectively [51]. To improve combustion properties, after the completion of the hydrogenation reaction, the final product undergoes different processes either isomerization, cracking, or cyclization, to obtain iso-alkanes, aromatics, or lighter hydrocarbons. Lastly, the distillation process is carried out to separate the fuel from other products. Thus, the product obtained has similar jetfuel-like properties and can be easily blended (50% by volume, ASTM certified), stored, and transported with the existing infrastructure of aviation fuels. The process overview summarization is illustrated in Fig. 6. Some of the studies in the past have also highlighted the lower tendency of hydrogenated fuel to oxidation as compared to biodiesel fuel [52]. Moreover, the overall process of HEFA is energy efficient as the hydrogenation reaction is exothermic. The energy released in the first step of the reaction can be used to remediate the energy requirement cost of the whole process, thus making the process economical and environmentally friendly. 2. Catalytic hydrothermolysis (CH) of oil-to-jet fuel The method has been developed and patented by Applied Research Associates, Inc. to produce sustainable aromatic drop-in fuel [58]. The process uses oil extracted from edible/inedible sources and wet biomass (such as algae) as a feedstock. The process contains multiple steps starting from cracking, hydrolysis, decarboxylation, and isomers formation to cyclization, which converts triglycerides into straight/ branched-chain and cyclic hydrocarbons like HEFA. The only difference is in initial stage after triglyceride formation. The oil first undergoes catalytic hydrothermolysis before being further processed for upgradation as shown in Fig. 6. The reaction is carried out at a temperature range of 450–475 °C and set pressure limits of 210 bar with or without catalyst and water. The final products obtained after completion

3 Overview of bio-derived jet fuels

FIG. 6 Process pathway of HEFA/CH-to-BSAF production [52,58].

of the reaction are carboxylic acids and other oxygenated compounds along with an unsaturated fatty acid molecule, which is later treated to undergo decarboxylation and hydrotreating process for saturation and separation of oxygen. After treatment, the product obtained generally has 6–28 carbon atoms in its structure, with n-, iso-, and cyclo-alkanes and aromatics. Therefore, at the final step, fractional distillation is carried out to obtain jet fuel with hydrocarbons ranging between C8 to C16, which satisfies both ASTM and military fuel standards and exhibits excellent combustion characteristics and cold and flow properties. 3. HDCJ Although the process is still in evaluation for approval, the hydrotreated depolymerized cellulosic method is capable of upgrading bio-oils that can produce drop-in jet fuels by adopting limited thermochemical routes. The process primarily is comprised of two stages: pyrolysis of biomass followed by hydrothermal liquefaction or upgrading processes such as hydrocracking, hydrotreating (at times when products after pyrolysis requires more extensive upgrading). The initial step of process involves the thermal decomposition of biomass in the absence of oxygen, resulting in oils, gases, charcoal, and water as the intermediate products. The intermediate products are highly dependent on the process conditions. For example, if the charcoal is the desired intermediate product, the temperature of the reaction should be maintained (800 °C) are required for gas generation [53]. In the past, literature has also highlighted various fast pyrolysis techniques with an objective to improve

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the overall efficiency of the process. One such pathway is heating the biomass to 600 °C followed by a sudden cooling step, thus quenching the vapors to produce bio-oil [54]. Additionally, some of the studies have also shown the significance of catalysts such as zeolites in improving the quality of bio-oil obtained after pyrolysis. The catalytic pyrolysis not only increases the aromatic content in the bio-oil, but also reduces the upgrading step feedstock undergoes after the liquefaction process [55]. In the second stage, the intermediate product obtained after pyrolysis undergoes treatment in a hot, high-pressure water environment until the biopolymeric structures are broken down into liquid fuels. This process is termed biomass hydrothermal liquefaction. The reaction parameters include operating temperature and pressure typically in range of (300–400 °C), (50–200 bar), respectively and with a reaction time of not more than 30 minutes [53]. Unlike non-catalytic pyrolysis, the product obtained after hydrothermal liquefaction is of high quality, with little or no oxygen or water content. However, in the case of handling complex biomass feedstock or obtaining desired product of choice, the hydrothermal liquefaction is followed by two-step hydroprocessing and catalytic cracking at the end. Considering this approach, “Licella,” one of the global leaders in hydrothermal liquefaction industry developed a breakthrough patented Catalytic Hydrothermal Reactor (Cat-HTR) technology which integrates hydrothermal liquefaction and upgrading processes together in a single-stage process [56]. The process claims to be much more energy and time efficient and in parallel can handle a wide variety of biomasses. Furthermore, in comparison to pyrolysis, the oil obtained is much more stable with high yield and can be easily pre-treated with petroleum crude in a refinery.

3.2.2 Oligomerization of alcohol-to-jet (ATJ) fuel As the name suggests, the fuel is derived from alcohols with short chain (C1-C4) as well as medium-straight-chain (C9-C15) fatty alcohols. Feedstock with sugar-rich or lignocellulosic biomass are the best-suited choice for the ATJ process [90]. In pursuit of alternative fuels, among all alcohols, the resulting fuels starting from methanol, ethanol, and butanol have shown the most promising properties to serve as “drop-in” fuels for jet engines. The fuel production pathway via methanol also known as the PtL (Power-to-liquid) process aims at using green hydrogen (derived from renewable electricity and water) and CO2 (derived from industrial sites/direct air capture) for the synthesis of methanol and subsequently to refined jet fuel following standard upgrading/conversion route. However, due to relatively high cost and low scalability, the process has yet to receive ASTM certification [91]. With an objective to fulfill the rising demand and compete with high quality conventional jet fuels, the ATJ process was developed. Generally, ATJ is a three-step process i.e., (1) Alcohol dehydration, (2) Olefin oligomerization, (3) Hydrogenation and fractional distillation in order to obtain the desired biofuel as shown in Fig. 7 [47]. However, starting from biomass, initially, the sugar enriched biomass raw material is converted to ethanol by undergoing a hydrolysis process. The output results in the release of sugar, which is further fermented to convert into ethanol. The reaction route, reaction condition, and parameter range to be selected in the

3 Overview of bio-derived jet fuels

FIG. 7 Process pathway for oligomerization of alcohol-to-jet (ATJ) fuel production [47].

ATJ process are highly dependent on the intermediates required. The most common intermediates include ethylene, propylene, higher alcohols, and carbonyls. However, considering the catalyst cost, efficiency, and complexity of the process, the preferred intermediates are ethylene, propylene, and butylene. In continuation of the discussion on the ATJ production route, the alcohol obtained after hydrolysis is dehydrated to remove any traces of water content and impurities with a suitable dehydrating agent. Thus, dehydration yields an alkene molecule as an intermediate. To synthesize long-chain molecules, the alkene monomers are reacted in the oligomerization reaction. However, during oligomerization, the intermediate product (olefins) at times remains unsaturated. Following this, in the past numerous companies have come up with solution pathways based on the feedstock choice. For example, Chevron Phillips has developed a specific Ziegler oligomerization process dedicated to ethanol feedstock [58]. Thus, the final product resulting in oligomerization contains a vast range of long carbon chains. Wright et al. [92] achieved a 96% conversion rate with multiple oligomers (carbon chains ranging from C8, C12, C16, and C20) while converting 1-butene. Usually, the carbon length lies in the range of C14 to C20 in standard jet fuel. To increase the carbon chain length, sometimes the C8 olefins are dimerized, resulting in higher jet fuel yield in a given feedstock unit. Thereafter, in the third step of hydrogenation, the olefins are treated in the hydrogen atmosphere to yield a synthetic paraffinic kerosene compound stream. Finally, fractional distillation is performed to separate bio-jet fuel from other product streams such as naphtha and biodiesel.

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As compared to other bio-jet fuels, the ATJ process has a unique advantage in the form of the low aromatic content present in the fuel synthesized. Due to the low aromatic content concentration achievable by the ATJ process, the jet fuel produced is well suited for use with the existing nitrile O-rings seals used in older aircraft. This difference in aromaticity was a problem encountered by the US Army when switching from JP4 to JP8 fuel [93]. Given this advantage linked with ATJ fuels, it has a stronger potential of being used as a “neat” or 100% bio-derived sustainable jet fuel in the near future.

3.2.3 Direct sugar to hydrocarbon (DSHC) fuel 1. Biological conversion route Bio-jet fuels can be produced by fermentation of sugars from feedstock such as sugarcane, beets, etc. The fermentation process of making hydrocarbons from sugars varies depending on the feedstock used and the type of microbial organisms used for fermentation. Direct conversion of sugars to hydrocarbons, as shown in Fig. 8 is a multistep process that can be aerobic or anaerobic. To produce the hydrocarbon from sugars, feedstock must be pretreated to make it suitable for enzymatic hydrolysis and to release the hemicellulose sugars. This is achieved by treating the feedstock with sulfuric acid, and this process is performed at around 200 °C [59]. The environment has to be maintained at a pH of approximately 5, using agents such as ammonia to ensure that enzymatic hydrolysis is occurring. The presence of acetate could inhibit the enzymatic hydrolysis process, and therefore steps must be taken to remove acetate from the feedstock. Removal of acetate (deacetylation) is performed by treating the feedstock with sodium hydroxide. Deacetylation helps reduce the cost of post-processing and ensures that the maximum amount of sugar is extracted from the feedstock and is available for hydrolysis [59]. Enzymatic hydrolysis is the process of conversion of cellulose to glucose using cellulase enzymes [60]. Cellulase is a mixture of enzymes that consist of

FIG. 8 Process pathway of DSHC (biological/catalytic upgrading)-to-jet fuel production [9].

3 Overview of bio-derived jet fuels

endoglucanases, exoglucanases, and β-glucosidase. Endoglucanase has a high affinity to cellulose and cuts the cellulose randomly and releases the free ends, exoglucanases act on the reducing or non-reducing ends of the highly crystalline cellulose fibers, and β-glucosidase converts small cellulose fragments to glucose [60]. Cellulase enzymes are produced by using cellulolytic fungi. Milala et al. [61] discuss the production of enzymes using Aspergillus niger in submerged culture with rice husks, maize straw, millet, and corn straw as substrates. During the hydrolysis of the cellulose, the viscosity of the mixture falls, and once hydrolysis of the pretreated feedstock is completed, the product is sent for conversion to hydrocarbons. However, further treatment is sometimes performed to obtain concentrated sugars through processes like evaporation [59]. The product obtained from hydrolysis usually contains insoluble solid substances such as lignin that could potentially affect the biological conversion to hydrocarbons. The insoluble solid substances might interfere with the oxygen uptake rate and result in incomplete conversion to hydrocarbons [59]. These insoluble solids are filtered out before converting to hydrocarbons and are typically used for heating purposes. Once the insoluble solids are filtered out, aerobic microbial organisms are introduced into the sugar slurry, unlike the production of ethanol, which uses anaerobic microbial organisms. After converting processed sugars to hydrocarbons, the resulting product contains mainly water and hydrocarbon products. The hydrocarbons are then separated from the aqueous phase via centrifugation and decantation and then further processed to obtain the hydrocarbons in their purest form possible. The aqueous phase contains inorganic compounds, including ammonium sulfate, and therefore must be sent to a treatment plant to remove them [59]. The energy input of bio-jet fuels produced from the direct conversion of sugar to hydrocarbons is very low due to the low temperature of fermentation [47]. Research is being conducted to study the genes in microbial organisms that could help in speeding up the conversion of sugars to hydrocarbons. In 2010, LS9 Inc., a biofuel startup founded in 2005, reported identifying a specific gene that could potentially convert the sugars to hydrocarbons in a one-step fermentation process [58]. 2. Catalytic upgrading sugar-to-jet pathway Catalytic upgraded liquid hydrocarbon production is a multistep process involving many chemical transformations such as decarboxylation, CdO hydrogenolysis, dehydration, and hydrogenation [62]. The initial steps of catalytic conversion of sugar to hydrocarbons are the same as that of the biological conversion. The biomass feedstock is pretreated for enzymatic hydrolysis by following a process similar to the biological conversion route. The insoluble solids are filtered from the hydrolysate and are used to produce heat using a combustor. The hydrolysate is then concentrated using ion exchange resin catalysts. This hydrolysate is then converted to polyhydric alcohols through hydrogenation or hydrogenolysis, both in the presence of hydrogen. Hydrogenation converts the hydrolysate into polyhydric alcohols, and hydrogenolysis produces short-chain oxygenated compounds from the hydrolysate. The resulting products are then sent to Aqueous Phase Reforming (APR). APR converts the

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products through various reactions such as generating hydrogen through reforming, hydrogenolysis, deoxygenation and hydrogenation of carbonyls, and dehydrogenation of alcohols. The products produced from APR are hydrogen, alkenes, oxygenates, and CO2. The hydrogen is used to convert highly reactive carbohydrates to less reactive mono-oxygenated species [64]. Since the products are obtained by processing sugar, they contain a maximum of six carbon atoms. However, aviation fuels typically use fuels with a larger number of carbon atoms, between 9–16 atoms [62]. So to produce bio-jet fuels, these products have to be converted to products with a higher number of carbon atoms which is achieved by using oxygen removing techniques combined with CdC coupling reactions [94]. These coupling reactions include aldol condensation reactions and oligomerization. Oxygenates produced in the APR process are converted into alkanes through aldol condensation and dehydration or hydrogenation-dehydration processes. Oxygenates undergoing dehydration or hydrogenation-dehydration process results in alkenes or alkanes [58]. After undergoing aldol condensation, oxygenates undergo hydrogenation or hydrogenolysis to be converted to alkanes. The process pathway diagram is shown in Fig. 8. Kunkes et al. [66] developed a method for converting sugar to a specific class of hydrocarbons by cascading the reactors. The products from one reactor are fed as input to the next reactor, and the sugar is deoxygenated with hydrogen over a PtRe/C catalyst to convert to monofunctional hydrocarbons. The next step of the process is the adsorption and dehydrogenation of the hydrocarbons with CdC cleavage and adsorption of CO on the catalyst surface. The adsorbed species undergo CdO bond cleavage resulting in desorption to form alcohols, carboxylic acids, ketones, and heterocyclic compounds [62]. Fuel produced using the DSHC is estimated to be $4–7.8/gallon, and the production cost increases significantly from initial to final processes but contributes the least to greenhouse gas (GHG) emissions [58]. In addition, during catalytic conversion of sugar to hydrocarbons, a reduction of yield by 30% can be expected if the inhibitors are not properly removed, and a reduction in the feed solids can result in a decrease in yield.

3.2.4 Fischer-Tropsch biomass-to-fuel pathway Fischer-Tropsch (FT) synthesis is the process of producing biofuels in liquid form from syngas [47]. Syngas is a gas mixture containing mainly hydrogen and carbon monoxide along with methane and carbon dioxide in smaller quantities. The process of producing syngas from biomass is referred to as biomass gasification. Syngas can be made from biomass feedstock in multiple ways. It can be produced using either entrained flow reactors or fluidized bed reactors [67,74,75]. Some of the requirements of the reactors to produce the desired type of synthetic gas that can be used as syngas are pressure, temperature, amount of inert gases and hydrocarbons present, reactor configuration, particle size, and catalysts used [76]. The H2:CO ratio is maintained at around 2 to avoid the water-gas shift reaction. The syngas produced from

3 Overview of bio-derived jet fuels

biomass is then converted into liquid hydrocarbons to be used as bio-jet fuels. If the operating temperature is below 1000 °C, usually when fluidized bed reactors are used, tar is produced and has to be removed. Thereafter, once the gasification is completed, and the syngas is produced, it is passed through the acid gas removal system [77]. This system ensures the removal of the acid gasses such as H2S, CO2, and sulfides. After cleaning the gas, the syngas enters the FT reactor to undergo the FT synthesis. FT synthesis is a surface polymerization reaction that happens at temperatures between 200 °C and 300 °C and pressure at ranges from 10 to 60 bar. Reaction (R1) shows the step followed by the FT polymerization reaction to produce a growing chain of CH2 monomers. Reactions (R2) and (R3) show the simplified version of the steps involved in the formation of alkanes and alkenes [78,79]. Oxygenated compounds with other functional groups such as alcohols, carboxylic acids, and aldehydes are also produced along with alkanes and alkenes. Iron and cobalt are used as catalysts for product desorption in the FT process [95]. Other catalysts used include nickel and ruthenium. Ruthenium is the best suited for the FT process, but it is very expensive and is therefore substituted by iron or cobalt catalysts. The low-temperature process, between 200–240 °C, operates using iron as the catalyst, and the high-temperature process uses iron or cobalt as the catalyst for the FT synthesis [80,81]. The type of catalyst used influences the type of product produced by the FT synthesis [47]. 2nH2 + nCO!  ðCH 2 Þn + nH 2 O

(R1)

ð2n + 1ÞH2 + nCO!Cn H 2n+2 + nH2 O

(R2)

2nH2 + nCO!Cn H 2n + nH 2 O

(R3)

Since the FT process is an exothermal reaction, steps must be taken to prevent the system from overheating, by removing the heat from the system, usually using a water-cooled setup, and periodically removing the catalyst, thus slowing down the reaction. Bio-jet fuel produced using the FT process is free of sulfur and therefore is a much cleaner fuel when compared to conventional aviation fuels. The part of the syngas that has not been used during the FT synthesis, also called the tail gas, is reused to assist with the hydrogenation and hydrocracking of the product of FT synthesis [47] as shown in Fig. 9. The tail gas is usually a mixture of hydrogen, nitrogen, argon, water, and hydrocarbons. The product obtained from the FT synthesis is a mixture of various products and must be refined to get the individual products. This can be achieved by using a conventional refinery, where the mixture will undergo a set of processes to separate products. Hydrogenation of the FT mixture is used to produce naphtha, and the hydrocracking of the FT products results in separating the FT mixture into bio-jet fuels [47]. Although the FT process is achieved by using the catalytic reaction with the syngas, it is also possible to produce bio-jet fuels by the process of fermentation. The

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FIG. 9 Process pathway of FT-BtL fuel production [9].

biomass is converted to syngas using the methods described above. Once the syngas is produced, it can undergo fermentation. It is important to remember that the syngas has to be cooled before fermentation begins [68]. Various microbial organisms are used in the fermentation process, and the type of bio-jet fuels produced during fermentation depends on the type of microbial organisms used. For example, Clostridium bacteria use the Ljungdahl pathway to produce ethanol and 2,3-butanediol from the fermentation of the syngas [69]. The product obtained after fermentation can then be converted into bio-jet fuels using the alcohol-to-jet fuel method described in the previous section. A great advantage of the Fischer Tropsch-Biomass-to-Fuel (FT-BtL) technique is that the process does not depend on the type of biomass used since any biomass can be gasified. The efficiency of the FT-BtL process is estimated to be between 28–40%, from feedstock to end products [95]. The major cost comes from the price of feedstock, and since the feedstock has to be transported to the processing centers, perhaps internationally, the feedstock price mainly depends on the oil price or the transportation cost at the time. The plants are expected to be huge to accommodate the high capital costs [70]. According to Tijmensen et al., the pretreatment, gas cleaning sections, and gasification can comprise almost 75% of the total capital cost [71]. An increase of 50% in the biomass cost can result in a 15–18% increase in the liquid fuel cost, and an economical and consistent source of feedstock is essential for long-term operation [72]. The lowest production cost was estimated to be approximately $28.8 per GJ for FT processes that use biomass accompanied by the use of a reformer. The production of the bio-jet fuels using the FT process is viable only if premiums are considered for the production of bio-jet fuels [73]. Nevertheless, a reduction in the production cost of bio-jet fuels through the FT process could be achieved over time as the learning curve increases and much better techniques are employed to produce bio-jet fuels through the FT process.

3 Overview of bio-derived jet fuels

3.2.5 Lignin to jet fuel pathway As the name suggests, lignin to jet pathway is a new pathway that produced bio-jet fuels by conversion of lignin to bio-jet fuels. Limited studies have been done in the past on this bio-jet fuel production mechanism, and the pathway has yet to gain ASTM approval to be used as an aviation fuel. Lignocellulose consists of cellulose and hemicellulose that can be used for producing low-value fuels [84]. Lignin is a hydrophobic polymer, which can also be obtained by hydrolysis of cellulose and hemicellulose. Before undergoing processes that produce bio-jet fuels from lignin, lignin is subjected to a variety of pretreatments including physical, chemical, and biological processes. Changes in the pH, temperature, and pressure during the processing results in change of the type of the jet fuel produced. The most common processes used for extract of lignin is the organosolv process and the ionic liquid extraction method. During the organosolv process, the lignin is mixed with an alkali or acid catalyst and an aqueous organic solvent [82]. This results in the separation of lignin and hemicellulose from the cellulose and the lignin after extraction from the aqueous solvent is highly pure and low on sulfur and ash. Although the aqueous solvent used for dissolving of the lignin is usually a mixture of ethanol and water [83], it could also be acidic solutions such as formic or acetic acid [85,86]. An advantage of using acidic solvents is that the lignin extracted is only slightly contaminated by the catalysts used. Ionic liquid extraction is the process of dissolving lignin in ionic liquids (IL) by breaking the non-covalent bonds present in lignocellulose [84]. Although there are multiple methods by which IL dissolves and separates the lignin, the most common method is using antisolvents to separate the components of the biomass as individual components. This method also has the advantage of extracting high quality lignin from the biomass. Kim et al. used 1-ethyl-3-methylimidazolium acetate purified ionic liquid lignin to extract biomass from poplar biomass [87]. The overview of Lignin-to-jet fuel production pathway is illustrated in Fig. 10. Once the lignin is extracted, it undergoes depolymerization through processes such as fast pyrolysis and hydrogenolysis [9]. During fast pyrolysis, the lignin is subjected to extreme heat in the absence of oxygen to break the lignin polymers into monomers and dimers. Hydrogenolysis is used for producing monomeric phenols and results in aromatic hydrocarbons with 6 to 11 carbon atoms. Although depolymerization of

FIG. 10 Process pathway of lignin-to-jet fuel production [9].

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lignin gives bio-oils, these bio-oils cannot be used as jet fuels since they have high viscosity, have high oxygen content, and are unstable [88]. Therefore, to be used as jet fuels, these bio-oils have to be deoxygenated under high pressures and temperatures through hydro deoxygenation (HDO) processes. The catalysts used for HDO are usually transition metals such as metal nitrides and metal oxides. The product obtained after catalytic upgrading is usually alkylated cycloalkanes or aromatic hydrocarbons that can be blended with conventional fuels to be used as aviation fuels [9].

3.3 Feedstock overview for bio-derived sustainable jet fuel production The cheap and continuous availability of sustainable biomass can be a great leap ahead in tackling the approximately billion liters requirement of fuel used by the aviation industry per year, while meeting future carbon minimizing targets. Numerous biomass feedstock have been explored down the generations (see Fig. 11) with an objective to meet the demand of the aviation industry. The primary characteristics of good feedstock are cultivation requirements, location feasibility, appropriate storage time, and cheap and readily available coupling to a production pathway [96]. Based on all these parameters, the feedstock are primarily classified by generation (gen in short) as follows:

3.3.1 First-Gen feedstock Feed crops such as soy, rapeseed, palm oil, sugarcane, corns, sunflower, peanut, wheat, and almost all the edible oil-producing plants come in the category of first-generation (Ist gen) feedstock. These crops have a lower content of unsaturated fatty acids (straight-chained) and fewer impurities resulting in higher oil yield

FIG. 11 Classification of feedstock for bio-jet fuel production.

3 Overview of bio-derived jet fuels

[97,98]. This makes them an excellent fit mainly for two ASTM-approved synthetic paraffinic kerosene (SPK) fuel production processes, namely Hydro processed esters and fatty acids (HEFA) and Alcohol to Jet (ATJ). Their process pathways along with other ASTM certified processes have been discussed in the previous sub-section of the chapter. Despite their utility, considering the land use requirement of edible oils and present energy security concerns, there are limitations and concerns about their mass-scale use. The major concern is the food vs fuel debate on edible oil, especially applicable for densely populated and developing countries. Secondly, the cultivation of crops such as corns, soybean, etc., requires a lot of water, time, and arable land, which might lead to exasperating water concerns, deforestation, and secondary concerns from the increased use of fertilizers in the future [99,100]. Though edible oil has extensive benefits, the long-term complications as a fuel resource can be understood by considering the example of the widely popular palm oil and the most reliable and only industrially implemented bio-jet fuel producing process, HEFA. Due to its easy availability and high energy output, palm oil can bridge the gap of the higher cost of hydrogen involved in HEFA (vide supra) and can reduce the overall cost to a great extent. Because of this, a vast increase of about 12 million hectares in the production of palm oil was observed between 2000–2012 in the tropical forests of Malaysia and Indonesia, which are the largest producers of palm oil worldwide [101]. To meet the rising demand, the countries are losing their well-balanced biodiversity and degrading peatlands, whose consequences are going to be witnessed sometime soon. Still, there are some exceptions. The United States with immense land and relatively sparser population has been able to leverage corn as a current best-fit resource for ethanol production on the excess scale. LanzaTech developed a gas fermentation technology that is capable of producing ethanol from direct gas fermentation using a novel microbial bioreactor. A life cycle assessment of this technology reports that the greenhouse emissions were at least 60% lower than the conventional aviation fuels [102]. In the span of 2019–20, out of 4.9 billion US corn bushels, 35% was targeted for ethanol feedstock [103,104]. Of the total ethanol production of the United States, 94% is derived from corn. According to the Renewable Fuel Association statistics, the ethanol production share of United States reached 13.93 billion gallon in 2020, which is 53% of the world production. On this account, ATJ technologies there are of high interest for SPK production [52]. In light of these facts, the lineup of Ist gen feedstock for bio-jet fuels production requires dedicated effort starting from environmental bodies to policy-makers and scientific and planning agencies worldwide.

3.3.2 Second-Gen feedstock Moving ahead, to remediate the food vs fuel concern, research has led to inedible oils, the feedstock of which are now known as IInd generation feedstock. These are divided into two main categories (1) Non-edible oil energy crops and (2) Waste biomass, which itself is further divided into sub-categories of farms and forest residues, food waste, and municipal trash [96,97]. Unlike edible oil feedstock, the oil production from nonedible sources requires some extra effort and has to undergo

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multiple filtration and treatment process due to the presence of higher unsaturated fatty acid content. In the same way, sugar-based IInd feedstock requires pretreatment in the presence of enzymes/microbes or has to go through a thermochemical transformation to extract trapped sugar in the complex plant cell wall made up of lignocellulose matrix. Therefore, with the integration of advanced technologies in the extraction process of energy from IInd feedstock, the high cost of production is one major limitation to their large-scale adoption. Despite this cost, other factors such as easier availability, the requirement of less fertile land, and resilience to climate sensitivity are some of the advantages of the IInd gen energy crops [105]. So far, in the search for a potential non-edible energy crop feedstock, the most extensive research has been conducted on using Jatropha (Jatropha curcas), Karanja (Pongamia pinnata), Polanga (Calophyllum inophyllum), Mahua (Madhu indica), Neem (Azadirachta indica), Rubber seed (Hevea brasiliensis), Switchgrass (Panicum virgatum), and Silvergrass (Miscanthus) owing to their availability and low-cost high yielding oil (around 35–65%) present in their kernels [106,107]. These crops are primarily found in tropical regions due to the favorable weather conditions in those regions. Asian countries such as India, a rich bio-diverse land, has more than 47,000 species of these, and underutilized oil-bearing plants and trees in 70% of the geographical area surveyed now, according to the Government of India, National Biodiversity report [108]. Abundant availability of non-edible crops can be a reliable approach for meeting the feedstock requirement of biofuel production and preventing edible crops diversion toward fuel generation. However, due to poor infrastructure, lack of government funding, and inadequate policies, the majority of feedstock available are still unexplored to their full potential, Kusum (Schleichera oleosa) [109] is one such rare crop, whose prospects are discussed in a later section of the chapter. Concisely, the tropical countries with high jet fuel demand and issues like food vs fuel concerns can use diversification of underutilized nonedible oils as a breakthrough step forward. Efforts in this direction can improve self-sufficiency and reduce the burden of importing fuels. Besides inedible energy crops, waste biomass such as waste cooking oil (WCO) and animal fats also serves as IInd gen feedstock for bio-jet fuel production. This sustainable approach not only helps in treatment of waste by reducing carbon footprints but also mitigates the challenges of cheaper and continuous feedstock availability. In comparison to the cost, used cooking oil is almost 1/3rd of the cost of fresh edible oil. Extensive studies in the past have shown promising aspects and fuel production pathways via waste/used oil [110]. The findings gathered illustrated the importance of waste biomass in fuel production. If the oil extraction from the waste resources is streamlined, it can play a role in the aviation sector by strengthening the biofuel production processes especially HEFA by countering the expensive hydrogen required to carry out this process.

3.3.3 Third-Gen feedstock To overcome further challenges or limitations associated with Ist and IInd generation feedstock, researchers are working on increasing the feasibility of algae for use as fuel-producing feedstock. With no food value, high yield capacity, no dedicated land

3 Overview of bio-derived jet fuels

requirement, and comparatively low-cost requirements (only sunlight, basic nutrients, and CO2 source required), it can penetrate those areas where edible and inedible feedstock fall short. This unicellular organism has excellent photosynthesis ability, high productivity, and free fatty acid (FFA) content (2–19% w/w and even up to 50% w/w in some hybrid species) making algae the best-fit candidate. It is expected to give large-scale production benefit in terms of bio-jet fuel production [97,99]. Biofuels stakeholders are making huge investments to counter the logistic as well as technological challenges currently faced during cultivation, harvesting, and oil extraction techniques. In addition, to simplify and diversify the pathways of production, different thermochemical routes including pyrolysis and hydrothermal liquefaction techniques are also being developed concurrently [111,112]. Nevertheless, to date, no economically viable pathway to produce algae-derived jet fuel on an industrial scale is available, research and trials are currently under different stages of development and have shown some prospects.

3.3.4 Fourth-Gen feedstock Returning to the raw materials in the first, second, and third generations, the feedstock are either biomass (plant or animal-based) or waste. Unlike fossil fuels which are based on ancient photosynthesis, biofuels derived from renewable resources are the product of present day photosynthetic activity i.e., solar energy to chemical energy. Undoubtedly, the energy obtained from these sources is valuable and useful for specific countries rich in biodiversity, but it is still dependent on the organic source material (biomass), thus highlighting a concern on their road to implementation on a worldwide scale. This limitation in particular impelled the search for new feedstock whose exhaustibility is not limited. They must meet the requirements of being inexpensive and readily available as well. These new feedstock could bring about a positive revolution in the realm of the aviation industry, exploring pathways to become carbon neutral; however, technological advancement is needed at all levels to establish how the concept of energy extraction from these sources can be made predominant in the current energy supply chain. Although efforts are underway in exploring different resources, genetic modification of algae species is among the new approaches. Currently, the extensive research primarily focused on different production pathways including (1) production of biological solar fuels by modified photosynthetic microorganisms, (2) electro biofuels i.e., merging photovoltaics and microbial process, (3) development of synthetic cell factory- microorganisms specifically modified to extract bioenergy or chemicals of high value [97,113]. After all, microorganisms can be a potential IVth gen biomass, as the future fuel production technology from solar aims to shift to photo-biological fuel production systems. The idea is to tailor microorganisms, which will consume solar energy at a faster rate, convert and collect the fuel simultaneously in a photo-bioreactor with higher yield rates. Thus, eliminating the need of harvested biomass [114]. Hence, new cultivation techniques, policies, and measures are required in order to achieve industrial-scale production of microbes, algae in particular.

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4. Limitations and challenges for the bio-jet fuels 4.1 Commercialization challenges

Cost and feedstock availability are the major challenges for bio-jet fuels. Shastri et al. [115] has discussed feedstock production and the challenges associated with it in detail. Feedstock production and transportation costs make up 35-50% of the total production cost [116]. Currently, biomass is primarily procured through harvesting non-edible crops (energy crops). The reason for this shift has been because of the increase in global food prices, as well as food security concerns around the world [117], as discussed previously. Since energy crops have to be cultivated in a large quantity, long-term investment is necessary for the cultivation of energy crops, which could indirectly affect the cultivation of food crops. For example, if it were more profitable to cultivate energy crops than food crops, then it would lead to competition with the food supply, as farmers would prefer to cultivate energy crops to food crops. This tradeoff therefore affects the global food supply chain. A large increase in cultivation could also result in depletion of water resources and cause water-related issues. For example, an increase in the production of palm oil has been linked to an increase in greenhouse gas emissions and deforestation [118]. The fertilizers used in the cultivation of the energy crops could also lead to an increase in GHG emissions as the fertilizer production facilities use natural gas and thus contribute to GHG emissions [119,120]. The low energy density of biomass when compared to crude oil is a significant challenge in the production of bio-jet fuels. An average energy density of 15–20 MJ kg1 for biomass is considerably lower than the energy density of crude oil, which is around 42 MJ kg1 [65]. This implies that a large amount of biomass is required to produce bio-jet fuels in large quantities. Another major challenge is the monoculture of crops [52]. Lack of diversity in the cultivation of both energy and food crops results in a reduction in the feedstock available for the production of bio-jet fuels. The cultivation of crops and the quality of crops produced is dependent on the season, and therefore, certain crops are available for only a certain period depending on when they can be harvested. Although municipal wastewater treatment plants can be used to grow cultures of microalgae to be used as biomass for the production of bio-jet fuels, the wastewater lacks sufficient nutrients required when microalgae cultures are converted to bio-jet fuels using a lipid extraction process [121]. Also, microalgae cultures cultivated using wastewater are low in lipid contents, and therefore the amount of fuel extracted from them is also limited [122]. Even though there are ways to ensure that the wastewater contains the necessary nutrients by adding nutrients to the wastewater, this could lead to an increase in the overall cost. It is possible to cultivate microalgae using freshwater sources, but it will require increased production costs. Transportation of bio-jet fuels is another major challenge in the biofuels industry. Importing a vast amount of oil like palm oil for bio-jet fuel production from another country could have an adverse impact on the environment. As the rate of importation of oils increases, it could lead to geopolitical considerations not unlike the current

4 Limitations and challenges for the bio-jet fuels

situation with conventional petroleum. Transportation of feedstock and bio-jet fuels over long distances results in a significant increase in the GHG emissions as well as the total production costs [52]. Bio-jet fuel is distributed from the refinery using rail, trucks, and pipelines, which are still under development. The pipelines are contaminated over time since particulate matter from pipelines mixes with the bio-jet fuel while in transit, leading to the presence of impurities in the bio-jet fuels. These impurities could affect the properties of the bio-jet fuels or may contaminate the equipment that uses the bio-jet fuel later. Therefore, these contaminants have to be removed from the bio-jet fuel at the destination, which leads to an increase in the overall cost of bio-jet fuel transportation and storage, as expensive equipment is required to filter the contaminants from the bio-jet fuel. Storage of feedstock is yet another challenge in bio-jet fuel production. The storage requirements for feedstock vary, and therefore multiple storage options are required if multiple types of feedstock are used. The storage is also dependent on climatic conditions. The need for adequately maintained storage facilities increases the total energy consumption and costs [123]. Lignocellulosic feedstock has to be stored in dry conditions to overcome losses in the dry matter. Vegetable oils like palm oil are stored in storage tanks, and the temperature has to be maintained to ensure that the oil does not lose its quality over time. These maintenance requirements increase the total production costs of the bio-jet fuels. Covered biomass storage is estimated to be $5.44/t (2014), and open biomass storage is estimated to be $4.13/t (2014) [52]. Another challenge is the cost of bio-fuel synthesis at the refineries. Pretreatment of biomass is a labor-intensive process and consumes a large amount of energy [124]. Separation and purification are the processes that drive the cost at the refineries. For example, the integration of biomass gasification and the FT process requires a gas cleaning system since the products from gasification contain unwanted chemicals that need to be removed. Eliminating some processes or substituting some processes with more efficient processes could reduce the cost of production. Most of the processes done in refineries require high temperature and pressure conditions as well as hydrogen in large quantities, which means high production costs [57]. The lengthy and costly process to obtain ASTM certification of the pathways used in the production of bio-jet fuels further slows down the mass production of bio-jet fuels. Even though the production pathway for bio-jet fuels through FT synthesis was approved by ASTM in 2009, the large-scale production facilities are still under construction. An efficient reactor for biomass gasification is still not yet developed, leading to an increase in the production cost [124]. The cleaning of syngas is an essential step in the production of bio-jet fuels, but the cleaning process is expensive, and the emissions from this process are hazardous to humans. An efficient and cheap syngas cleaning process has yet to be developed. Finally, the lack of essential policies is the other challenge of bio-jet fuel production. Government intervention is required to improve the infrastructure and international collaboration to increase the production of bio-jet fuels. Although there appears to be a renewed push in the US in the past year [125] toward reducing

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the carbon footprint in the aviation sector by substitution of hydrocarbon fuels with biofuels, most of these efforts have previously focused on the ground transportation sector and not the aviation sector. Implementation of regulations on the use of bio-jet fuels is a very slow process, as agreements between countries have to be reached through negotiations, which take time.

4.2 Meeting properties requirements and certification of aviation fuels In comparison to the conventional aviation fuels, bio-jet fuels generally contain lower sulfur content, higher oxygen content (up to 11% by weight), higher viscosity, higher flash point, and lower heating value. Generally, some of the bio-jet fuel properties lie well within the effective range; however, there exist certain properties (e.g. high viscosity, surface tension, and lower calorific value), which can lead to deficient engine performance and poorer combustion and emission characteristics. Several reasons are responsible for this nature of bio-jet fuels. The low heating value can be attributed to the more oxygenated nature of the fuel [126]. Studies in the past have reported bio-jet obtained from Jatropha oil using HEFA process tends to have high viscosity, which interferes with fuel atomization and can deteriorate the combustion characteristics. Rehman et al. [127] reported that the high viscosity can be reduced by initially undergoing transesterification of the Jatropha oil. In another instance, bio-jet fuel produced using FT process contains no aromatics or sulfur and has to be mixed with conventional fuels to be used as aviation fuel. However, the low aromatic content could sometimes result in problems such as additive compatibility with fuel and leakage issues when engine material is not compatible with the fuel. Although there are techniques such as additions of cycloalkanes and olefins (as discussed in Section 3) to improve this, in other cases conventional engine retro fitment can be done for successful operation of alternative bio-jet fuels. The National Jet Fuel Combustion Program (NJFCP) has focused upon ignition delay, lean blow out, altitude relight, and cold start among other performance criteria. Past combustor test studies have shown that combustion phenomena such as lean blow out and ignition delay are significantly linked to cetane number of the fuel [128,129]. Cetane number (CN and derived cetane number DCN) is an important property defined for compression ignition engines that signifies ignition characteristics of the fuel, especially in low temperature conditions (700–1100 K). It is not a property specified for jet fuels in the certification process, but conventional jet fuels have cetane numbers in the range of 30 s to 50 s. Cetane number is highly dependent on molecular composition. For example, Sasol IPK (Iso-paraffinic Kerosene) synthetic jet fuels have lower amounts of n-paraffins in comparison to iso- and cyclo-paraffins and therefore have low DCNs (33.46) and freezing points ( CH4 + F-24_R F-24 + OH => OH2 + F-24_R F-24 + O2 => H2 + F-24_R F-24 + HO2 => H2O2 + F-24_R F-24 + O => OH + F-24_R F-24_R => (F-24_R pyrolysis products) F-24_R + O2 => F-24_RO2 F-24_RO2 => F-24_R + O2 (CRECK modeling n-dodecane) F-24_RO2 => F-24_QOOH F-24_QOOH => F-24_RO2 F-24_QOOH = HO2 + F-24_Q F-24_Q => (F-24Q pyrolysis products) F-24_QOOH + O2 = F-24_O2QOOH F-24_O2QOOH = OH + F-24_OQ’OOH F-24_OQ’OOH => CH2O + OH + (F-24_OQ* pyrolysis products)

Before optimization A b Ea 1.53E+27 7.66E-02 3.17E-07 2.96E+09 1.78E+15 6.98E+04 8.94E+01 6.47E+12 2.50E+10 5.00E+13 2.00E+12 1.00E+11 8.50E+12 3.50E+16 4.00E+11 1.50E+12 1.00E+14

-2.58 4.76 5.75 1.02 0.06 2.94 3.86 0 0 0 0 0 0 0 0 0 0

8.77E+04 1.29E+03 5.75E+03 2.13E+02 4.45E+04 1.28E+04 7.65E+02 2.71E+04 0 3.10E+04 1.70E+04 1.25E+04 2.56E+04 7.10E+04 0 0 4.21E+04

After optimization A b Ea 1.61E+27 4.51E-01 2.95E-06 2.22E+10 7.72E+15 6.67E+05 1.19E+01 1.92E+12 1.13E+10 2.93E+14 7.14E+11 1.00E+10 8.20E+13 3.50E+17 9.19E+10 1.67E+12 1.00E+13

-0.59 6.41 6.71 2.91 -1.92 3.25 4.80 0 0 0 0 0 0 0 0 0 0

9.19E+04 1.29E+03 5.46E+03 2.23E+02 4.26E+04 1.22E+04 7.79E+02 2.57E+04 0 3.23E+04 1.79E+04 1.30E+04 2.69E+04 6.74E+04 0 0 4.02E+04

5 Bio-derived sustainable aviation fuels

An ATJ (POSF 11498) detailed mechanism from HyChem [151] is used as a base mechanism, and a lumped reaction model for NTC chemistry and low-temperature chemistry is added as a sub-mechanism. According to two-dimensional gas chromatographic (GCxGC) analysis, the real ATJ fuel can be represented as C12.540.10H27.050.19. For the existing chemical kinetics computation, the mixture compositions are approximated as integer values: C13H28. The mechanism comprises three parts: the HyChem ATJ lumped mechanism for high-temperature combustion, a lumped RO2-QOOH cycle mechanism for low-temperature combustion, and the USC Mech II for a detailed foundation chemistry model. The same approach used in F-24 is applied to select the set of reactions to be optimized. Therefore, only the rate coefficients of low-temperature chemistry reactions represented in Table 4 are modified to develop a data-driven chemical kinetic mechanism for ATJ. Pre-exponential factors were modified within one order of magnitude and activation energies within 20%. Table 4 shows the parameters of the outcome mechanism. Although the reaction parameters of the high-temperature combustion pathway did not change, the results show good agreement under high-temperature combustion. However, there was a difference between the original low-temperature chemistry and the modified lowtemperature chemistry. The optimized values are reasonable based on group additivity, as the properties of lumped species lie between those of isooctane and isocetane. The developed data-driven mechanisms (ARLMech-HC-ATJ and the alternate model) in Cantera and CHEMKIN format can be found in the published journal paper to appear.

Table 4 The kinetic parameters of the lumped reactions in the C-1 HyChem model and detailed model of isododecane (base), the optimized model using genetic algorithm (red).

Estimated low T sub mechanism

HyChem C-1

Reaction ATJ=> (ATJ pyrolysis products) ATJ + H => H2 + ATJ_R ATJ + CH3 => CH4 + ATJ_R ATJ + OH => OH2 + ATJ_R ATJ + O2 => H2 + ATJ_R ATJ + HO2 => H2O2 + ATJ_R ATJ + O => OH + ATJ_R ATJ_R => (ATJ_R pyrolysis products) ATJ_R + O2 => ATJ_RO2

=> ATJ_R + O2 => ATJ_QOOH ATJ_QOOH => ATJ_RO2 ATJ_RO2 ATJ_RO2

ATJ_QOOH = HO2 + ATJ_Q ATJ_Q => (ATJQ pyrolysis products) ATJ_QOOH + O2 = ATJ_O2QOOH ATJ_O2QOOH = OH + ATJ_OQ’OOH ATJ_OQ’OOH => CH2O + OH + ATJ_OQ* ATJ_OQ* => (ATJ_OQ* pyrolysis products)

Before optimization A B Ea 2.83E+26 8.72E+05 4.64E+00 4.88E+10 1.49E+15 9.03E+03 7.85E+04 1.44E+11 1.15E+11 2.06E+10 2.06E+10 2.71E+10 8.50E+12 1.00E+16 4.52E+11 1.98E+10 6.26E+13 1.39E+19

-2.58 2.4 3.46 0.51 0 2.77 2.5 0 0 0 0 0 0 0 0 0 0 0

8.02E+04 2.58E+03 4.60E+03 6.40E+01 4.30E+04 1.05E+04 1.11E+03 3.08E+04 7.15E+03 2.16E+04 2.16E+04 1.47E+04 2.56E+04 7.10E+04 0.00E+00 2.04E+04 3.90E+04 4.41E+04

After optimization A b Ea 2.83E+26 8.72E+05 4.64E+00 4.88E+10 1.49E+15 9.03E+03 7.85E+04 1.12E+12 9.66E+10 5.25E+13 9.70E+10 5.81E+10 1.76E+13 1.34E+17 2.20E+10 1.04E+12 1.15E+11 3.92E+18

-2.58 2.4 3.46 0.51 0 2.77 2.5 0 0 0 0 0 0 0 0 0 0 0

8.02E+04 2.58E+03 4.60E+03 6.40E+01 4.30E+04 1.05E+04 1.10E+03 3.01E+04 0.00E+00 3.01E+04 2.10E+04 1.26E+04 2.43E+04 5.54E+04 0.00E+00 1.93E+04 2.71E+04 5.44E+04

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The developed models for ATJ and F-24 were then evaluated under the same conditions as experiments to evaluate the predictive capabilities for autoignition characteristics of the F-24 and ATJ blends, as shown in Fig. 15. Modeling was carried out with Cantera 2.5 using a closed homogeneous reactor. The simple merged mechanism does an excellent job of representing the overall trends at the conditions studied, but the model fails to represent blending results with accuracy. The discrepancies between the modeling and experimental results in NTC and lowtemperatures regimes are apparent. The importance of alkylation (also known as co-oxidation) reactions among blended or multi-fuel components in low-temperature chemistry is a debated topic. Several researchers [223–226] insisted that co-oxidation between the individual components is important, but others [160,218,225] argue that it is less important as combining two different single mechanisms can represent the entirety mixture mechanism. An alkylation reaction is a reaction transferring an alkyl group from one molecule to another molecule. R1 + R2 H ¼ R1 H + R2

(R4)

Under NTC and low-temperature regimes, a common pathway of alkyl radical reaction is with active radicals and oxygen molecules (H, OH, O, HO2, and O2). Most

FIG. 15 Data-driven kinetic model results of simple merged F-24 and ATJ at Pc ¼2 MPa and equivalence ratio (phi)¼1.0. Lines and dots are simulation results and experimental results, respectively.

5 Bio-derived sustainable aviation fuels

single component mechanisms include the further reaction with regenerated active radicals. H abstracted fuel’s alkyl radical can also be considered active radicals to react with less reactive fuel molecules. If we consider a co-oxidation reaction between two fuel components, an alkylation (co-oxidation) reaction can be considered as additional pathways of chain propagating or branching steps by radical exchange. The initial guess for rate constants for the alkylation reactions were developed from the PRF mechanism by Ra et al. [165]. Sufficiently large boundaries are given to the reaction between the alkyl radical of F-24 and ATJ, which is substituted for the reaction between isooctane and normal heptyl radicals in the base mechanism. Ignition delay predictions using the mechanism with alkylation reaction were validated with experimental data, as shown in Fig. 16. As can be seen, the model prediction is in excellent agreement with the results in the experimental results. This section suggests readily available chemical kinetic mechanisms of BSAFs based on data-driven optimization techniques. However, the research prompts further questions and opportunities for additional study into the generalization and the improvement of these kinetic models. To conclude this section, additional future work is proposed to help advance the general state of knowledge of SAF chemical kinetics.

FIG. 16 Data-driven Kinetic model results of F-24/ATJ blends with alkylation reaction at Pc ¼2 MPa and equivalence ratio (phi)¼1.0. Lines and dots are simulation results and experimental results, respectively.

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5.5.5 Future opportunities: Reference mechanisms of pure components and blending Assessing jet fuels’ relevant pure hydrocarbon components is crucial to understanding the autoignition characteristics of real multi-component fuels. It will provide the fundamental knowledge of fuels’ combustion and the influence of specific chemical species on the ignition of fuels. Hydrocarbon species in conventional and alternative fuels can be broadly classified into four major groups: normal alkanes, isoalkanes, cycloalkanes, and aromatics. The classification, the carbon number, and isomer structure will also affect the chemical combustion process through isomerization and thermal decomposition. In addition to pure components’ study, examining mixtures of each neat component could provide additional insight for understanding multi-component fuels. The reactivity of blends of pure components is not easily predicted, and there is no perfect model to simulate blending effects on autoignition characteristics. For example, one of the alkylation reactions (co-oxidation) represents the blending effects in lowtemperature chemistry vide supra. However, systemically evaluating the blending effects of different species should be performed to provide a detailed understanding of blending effects on ignition behavior.

5.5.6 Future opportunities: Generalization and extension of HyChem style models This chapter focused on HyChem models because of their relative simplicity and accuracy. HyChem is an easy and efficient approach to develop chemical kinetic mechanisms of newly introduced fuels, avoiding the exhausting endeavor of building surrogates. The current HyChem framework is fuel-dependent and requires experimental information, including the detailed chemical composition of fuels and the time history of pyrolysis products. Specifically, the HyChem model relies on advanced species diagnostic techniques for one specific fuel, which provides the time evolution and yield data for its pyrolysis products. Generalized and standardized devices for measuring these critical intermediates from fuels with low uncertainty (appx. 1% uncertainty in true temperature, 20% uncertainty in species measurements) would be extremely beneficial for developing models. The most promising standardizable device with low uncertainty suitable for these measurements is probably still the shock tube. With detailed fuels’ chemical information, a minimalist function group (MFG) approach [227], a database developed from the efforts proposed in the previous section can be utilized to develop chemical kinetic models of completely new fuels. Instead of building surrogates of fuels, the properties are anticipated by matching functional groups. Both high-temperature and low-temperature chemistry can be simplified by analyzing the functional groups of fuels rather than the analysis of chemical structures. Based on analysis of functional groups, the HyChem approach can be generalized as semi-fuel-dependent for various types of fuels with principal lumped reactions. With the database including single components, traditional jet fuels, and alternative fuels, data-driven and machine learning-based chemical kinetic

5 Bio-derived sustainable aviation fuels

development can be achieved. Using the training fuel database and the knowledge of single components and blending effects, the approach would become an efficient and feasible solution to assess alternative fuels and BSAFs.

5.5.7 Future opportunities: Improvement of low-temperature chemistry and optical diagnostics Low-temperature combustion conditions are significant as the ignition and combustion processes are sensitive to fuel composition and are often important at the edges of stable operation of practical combustion systems. Unlike high and intermediatetemperature combustion chemistry, low temperature chemical kinetics is a complicated process involving a series of alkylperoxy radical and hydroperoxyalkyl radical reactions. Typically, ignition of fuel components can be divided into two stages at low temperatures: chain branching process involving alkylperoxy radicals and thermal decomposition of radicals, including OH radical chain branching. Measurements of critical species in well-designed experiments will be able to provide the constraints for developing chemical kinetic models. At this point, CH2O, isobutylene, and CO are suggested as good target species or markers of negative temperature coefficient and low-temperature chemistry behavior of the fuels for developing chemical kinetic models.

5.6 BSAF fuel property sensing 5.6.1 Current status As already discussed, bio-jet fuels can exhibit different fuel properties due to the variation in their chemical compositions. This variation poses a challenge for making stable drop-in fuels. Even though ASTM approves fuels that have similar fuel properties to those of conventional fuels, there exist properties that are different for each fuel (see above discussion on cetane number). These differences can sometimes cause a drop in the efficiency of the engine, which if persistent can require retrofitting. It is recommended that the fuel dispensed for use with aircraft engines via ships have to be tested every day by an analyst trained on ASTM standards to ensure that there is no degradation/contamination of composition of the fuel. More advanced tests are currently performed in laboratories on ground, with standardized equipment, potentially away from airport or depots making these tests expensive [228]. Statistical models have been used in predicting physiochemical properties of fuels in an effort to overcome the inconvenience of the standardized methods. There is potential for comprehensive physiochemical properties analysis based on chemometrics coupled to gas chromatography (GC), nuclear magnetic resonance spectroscopy (NMR), or mass spectrometry (MS). We particularly highlight vibrational spectroscopy techniques including Raman scattering [229–232] and infrared (IR) absorption [229–231,233–243] with examples of correlating fuel properties to spectral responses. These spectroscopic techniques offer nondestructive, rapid, and potentially compact methods and have received sporadic attention over the years, more so on the refining/characterization side than on the fuel/engine side.

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For brevity, we highlight only a few examples here, which would be relevant to BSAFs. Handheld near infrared (NIR) analyzers [237] have been assessed for rapid estimation of jet fuel properties like American Petroleum Industry (API) gravity, % aromatics, cetane index, etc. Cunha et al. [233] has investigated the performance of linear and non-linear ML models in developing a relation between NIR spectra of biodiesel fuel and its properties. Scheuermann [244] has determined the amount of synthetic fuel in a JetA1/synthetic fuel blend with a precision of