Challenges and opportunities in using Kinetic Monte Carlo for battery research and innovation

Abstract

With the increasing reliance on batteries, particularly in electric vehicles, understanding the kinetics of chemical reactions – especially undesired side reactions causing aging and failures – is crucial for improving safety and lifespan. Conventional macroscopic models used in battery management systems (BMS) often face limitations due to inaccuracies and difficulties in determining parameters, which leads to large uncertainties. In contrast, bottom-up approaches, like Kinetic Monte Carlo (KMC) simulations, offer more precise modeling by bridging molecular-scale phenomena with macroscopic models, balancing computational cost and accuracy. Traditionally utilized in catalysis, KMC is now showing potential in battery applications, although it faces challenges related to the combined presence of evolving solid interfaces (e.g., solid electrolyte interphase), complex electrochemical reactions, ion/electron transport and mechanical degradation during cycling. This perspective explores how KMC can assist computational and experimental chemists in understanding and obtaining critical physical/chemical parameters from microscopic-level insights, e.g., chemical composition and temporal concentration profiles. These insights can enhance BMS at the macroscopic level, optimize battery performance, and inspire innovative mitigation strategies. The perspective also highlights challenges in estimating rate constants, handling timescale disparities, and modeling complex environments, concluding with future research directions for this evolving field.