关键词: 固态电解质界面膜, 形成和生长机理, 分子动力学, 动力学蒙特卡罗, 机器学习

Abstract:

Lithium metal anodes in lithium-ion batteries (LIBs) have garnered significant research interest due to their exceptionally high theoretical specific capacity. However, their high reactivity can trigger a series of complex degradation reactions of electrolyte components, ultimately forming a solid electrolyte interface (SEI) on the electrode surfaces. This SEI passivation layer suppresses the continuous loss of electrolytes but can significantly affect the cycling performance of the LIBs. Consequently, understanding the formation and growth mechanisms of SEI at the atomic/molecular level has become a major research focus in recent years. This study summarizes the latest research progress on the structure, composition, and growth process of SEI using various theoretical approaches. Particularly, it introduces some successful examples of classical molecular dynamics, reactive force field molecular dynamics, first-principles molecular dynamics, machine learning force field molecular dynamics, and kinetic Monte Carlo methods in SEI modeling. In addition, this study discusses the limitations of current theoretical approaches in simulating the formation and growth mechanisms of SEI. Finally, this study proposes that combining machine learning methods and kinetic Monte Carlo approaches to enhance the simulations of the formation and growth processes of SEI over long-time domains.

Key words: solid electrolyte interphase, growth and formation mechanism, molecular dynamics, kinetics Monte Carlo, machine learning