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cond-mat.mtrl-sci2026
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…
cond-mat.mtrl-sci2025
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…
cond-mat.mtrl-sci2024
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…