A Comparative Study of Molecular Dynamics Approaches for Simulating Ionic Conductivity in Solid Lithium Electrolytes

Dounia Shaaban Kabakibo, Félix Therrien, Yoshua Bengio, Michel Côté, Hongyu Guo, Homin Shin, Alex Hernández-García

Keywords: Solid-state, batteries, electrolytes, ionic conductivity, molecular dynamics, energy storage, crystal, inorganics.

Abstract: Accurate prediction of ionic conductivity is critical for the design of highperformance solid-state electrolytes in next-generation batteries. We benchmark molecular dynamics (MD) approaches for computing ionic conductivity in 21 lithium solid electrolytes for which experimental ionic conductivity has been previously reported in the literature. Specifically, we compare simulations driven by density functional theory (DFT) and by universal machine-learning interatomic potentials (uMLIPs), namely a MACE foundation model. Our results suggest comparable performance between DFT and MACE, with MACE requiring only a fraction of the computational cost. The framework developed here is designed to enable systematic comparisons with additional uMLIPs and fine-tuned models in future work.

Submission Track: Paper Track (Tiny Paper)

Submission Category: AI-Guided Design + Automated Material Characterization

Submission Number: 51