Strain-Dependent Ionic Transport in Li3YCl6 Solid Electrolytes
Wei-Fan Huang, Jin Dai, Jiahui Pan, and Mingjian Wen

TL;DR
This study uses machine learning-enhanced molecular dynamics to explore how lattice strain affects ionic transport in Li3YCl6 electrolytes, revealing strain as a key design parameter for solid-state batteries.
Contribution
It demonstrates how lattice strain modulates Li+ diffusion mechanisms and diffusivity in Li3YCl6, providing insights for electrolyte design.
Findings
Tensile strain enhances ionic diffusivity; compressive strain suppresses it.
Li+ diffusion exhibits a two-regime Arrhenius behavior with a crossover at temperature T_c.
Strain influences activation barriers and pre-exponential factors differently across regimes.
Abstract
Solid-state batteries require electrolytes that sustain high ionic conductivity under the mechanical environment of a functioning cell. Lattice strain, arising from stack pressure, thermal cycling, or lattice mismatch at interfaces, can either enhance or suppress Li+ transport in solid electrolytes, yet how it couples to the underlying diffusion mechanism remains poorly understood. Using Li3YCl6 halide superionic conductor, we address this with large-scale molecular dynamics simulations driven by an Atomic Cluster Expansion (ACE) machine learning interatomic potential trained on first-principles data. The ACE model faithfully reproduces experimental and \textit{ab initio} structural, mechanical, and transport properties of Li3YCl6. We find that Li+ diffusion in Li3YCl6 follows a two-regime Arrhenius behavior, crossing over at a critical temperature from one-dimensional hopping at…
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