Sep 2026
Machine Learning Interatomic Potentials for Modeling Solid-State Batteries
Atomistic simulations can provide critical insights into the fundamental behavior of battery materials. A necessary input for such simulations is a description of the potential energy surface (PES). Over the past decade, machine learning interatomic potentials (MLIPs) have emerged as a powerful approach to model the...
Mgcini Keith Phuthi, Grace Wei, Bryant Y. Li et al.
· Chemistry of Materials · 0 citations