Introduction to Computational Electrochemistry

Hyungjun Kim is a Professor at the Department Chemistry, Korean Advanced Institute of Science and Technology (KAIST), Republic of Korea. He obtained his Ph.D. in Chemistry in 2009 from Caltech. After three and a half years in a senior researcher position at KAIST, he started his faculty position at KAIST in 2013. He is an author of more than 220 peer-reviewed journal papers, and now also a junior member of the Korean Academy of Science and Technology. His main research interest is in developing new computational methods for material simulations and electrochemical interfaces. Stefan Ringe is an Associate Professor at the Department of Chemistry, Korea University, Republic of Korea. He obtained his Ph.D. in Theoretical Chemistry from the Technical University of Munich in 2017. After Postdoctoral research stays at Stanford University, USA and KAIST, he became an Assistant Professor at DGIST (Daegu, Rep. of Korea), from where he transferred to Korea University in 2022. His research interest focusses on computational electrochemistry in all its challenges, from the simulation and optimization of materials, electrolytes and their interfaces to multi-scale modelling of realistic devices. He is an author of more than 40 peer-reviewed journal papers with his milestone papers focussing on electrochemical CO2 reduction.Leanne D. Chen is an Associate Professor at the University of Guelph, Canada. She received her PhD from Stanford University in 2017, took up a two-year postdoctoral position at Caltech until 2019, then started her independent career in 2020. She currently leads a creative and collaborative group with a common goal of using quantum chemistry methods to gain fundamental insight and reduce our reliance on fossil fuels for energy applications. As an early-career researcher, she has secured more than half a million CAD in funding and has given 39 invited talks around the world. Her contributions to the field of computational electrocatalysis are evidenced by a series of contributions in high-impact venues including Journal of the American Chemical Society, ACS Catalysis, and Nature Communications, with a total of 38 publications.

• Part I: Fundamentals in Computational Electrochemistry Editor Prologue: Overview of Current Developments and Challenges in Methods and Models Section A: Quantum Chemical Modeling of Electrochemical Interfaces 1. Electrochemical Potential and Its Representation in Quantum Chemical Modeling 2. Electrochemical Capacitance and Its Representation in Quantum Chemical Modeling Section B: Surrogate Atomistic Models of Electrochemical Interfaces 3. Electric Double Layer Structure, Capacitance, and Phase Transitions from Hybrid Quantum-Classical Simulations 4. Electric Double Layer: From Quantum Chemical to Classical Depictions 5. Machine-Learning for Next-Generation Computational Electrochemistry 6. The Importance of Potentiostats for Correctly Replicating Electrochemical Conditions Section C: Continuum Modeling of Electrochemical Interfaces 7. Next-Generation Continuum Solvation Models for Modeling Electrochemical Interfaces 8. Mastering the Use of Continuum Solvation Methods for Modeling Electrochemistry 9. Hybrid Density-Functional Theoretical Models of Electric Double Layers Section D: Kinetic and Multi-Scale Modeling of Electrochemical Processes 10. Theoretical Foundations Behind First-Principles Electrochemical Barriers 11. Multi-Scale Modeling for Electrochemical Energy Conversion Part II: Computational Electrocatalysis Editor Prologue: Advances in Electrocatalysis Driven by Computational Simulations Section A: Electrocatalyst Design in the Static Equilibrium Limit 12. Computational Design of Catalysts for Oxygen Evolution Reaction 13. Microenvironment Effects in Catalysis 14. A Systematic Approach for Modelling Disordered Surfaces 15. Nanomaterials and Active Site Engineering for Electrocatalysis 16. Toward Data‐and Mechanistic‐Driven Volcano Plots in Electrocatalysis 17. Towards a Computational Hydrogen Electrode 2.0: References in Electrochemistry Section B: Insights into Electrocatalysis from Ab Initio Molecular Dynamics 18. Insights into Electrochemical CO2 Reduction from Ab Initio Molecular Dynamics 19. Insights into Oxygen Reduction Reaction Kinetics from Ab Initio Molecular Dynamics Section C: First Principles-Driven Kinetic and Multi-Scale Modeling of Electrocatalytic Processes 20. Nonadiabatic Proton-Coupled Electron Transfer at Surfaces 21. Towards Affordable First-Principles Electrochemical Barriers 22. Deciphering Electrocatalytic Processes from First-Principles, Continuum Modeling, and Multi-Scale Simulations Part III: Computational Modeling of Energy Storage Editor Prologue: Next Generation Energy Storage Systems Enabled by Computational Modeling Section A: Energy Storage Modeling in the Static Equilibrium Limit 23. First-Principles Insights into Energy Storage of MXenes 24. Combining Theory and Experiments for Insights into Lithium-Ion Batteries Section B: Dynamics and Kinetics of Energy Storage Systems 25. Computational Design of Battery Electrolytes 26. Ion and Electron Transport in Electrochemical Energy Storage Devices and Materials 27. Hybrid Quantum-Classical Simulations of MOF Capacitors Section C: Data-Driven Energy Storage System Design 28. Applying Machine Learning Methods to Electrode Materials for Li-Ion Batteries 29. Machine Learning and Multiscale Modelling in Materials Design 30. A Data-Driven Approach to Materials Design and Discovery Part IV: Summary and Perspectives 31. Conclusion