4 papers
Influence of Exchange-Correlation Functionals and Neural Network Architectures on Li-Ion Conductivity in Solid-State Electrolyte from Molecular Dynamics Simulations with Machine-Learning Force Fields
Zicun Li, Huanjing Gong, Ruijuan Xiao +1
With the rapid advancement of machine learning techniques for materials simulations, machine-learned force fields (MLFFs) have become a powerful tool that complements first-princip…
Revealing the Staging Structural Evolution and Li (De)Intercalation Kinetics in Graphite Anodes via Machine Learning Potential
Liqi Wang, Xuhe Gong, Zicun Li +2
Revealing the dynamic structural evolution and lithium transport properties during the charge/discharge processes is crucial for optimizing graphite anodes in lithium-ion batteries…
Gas-solid Reaction Dynamics on LiPSCl Surfaces: A Case Study of the Influence of CO and CO/O Atmospheres Using AIMD and MLFF Simulations
Zicun Li, Xinguo Ren, Jinbin Li +2
In recent years, rapid progress has been made in solid-state lithium batteries. Among various technologies, coating the surface of electrodes or electrolytes has proven to be an ef…
Mechanistic Insights into Temperature Effects for Ionic Conductivity in Li6PS5Cl
Zicun Li, Jianxing Huang, Xinguo Ren +3
Ensuring solid-state lithium batteries perform well across a wide temperature range is crucial for their practical use. Molecular dynamics (MD) simulations can provide valuable ins…