Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study

TL;DR

This study uses machine learning-enhanced molecular dynamics to investigate lithium-ion transport mechanisms and stability in amorphous Ti-doped lithium phosphorus sulfide, revealing how Ti concentration affects conductivity and channel stability.

Contribution

It introduces a highly accurate machine learning force field enabling large-scale MD simulations to analyze Li-ion transport and stability in Ti-doped LPS materials.

Findings

Li-ion transport occurs via free-volume diffusion in disordered Li-S polyhedra.

Ionic conductivities and activation energies match experimental data.

Transport channel stability is enhanced at 10% and 20% Ti doping.

Abstract

Mixed ionic-electronic conductors (MIECs) exhibit both high ionic and electronic conductivity to improve the battery performance. In this work, we investigate the mechanism and stability of transport channels in our recently developed MIEC material, amorphous Ti-doped lithium phosphorus sulfide (LPS), using molecular dynamics (MD) simulations with a 99\% accurate machine-learning force field (MLFF) trained on \textit{ab-initio} MD data. The achieved MLFF helps efficient large-scale MD simulations on LPS with three Ti concentrations (10\%, 20\%, and 30\%) and six temperatures (25$^\mathrm{o}$C to 225$^\mathrm{o}$C) to calculate ionic conductivity, activation energy, Li-ion transport mechanism, and configurational entropy. Results show that ionic conductivities and activation energies are consistent with our recent experimental values. Moreover, Li-ion transport occurs via free-volume diffusion facilitated by the formation of disordered Li-S polyhedra. The enhanced stability of transport channels at 10\% and 20\% Ti doping, compared to 0\% and 30\%, is observed by analyzing the vibrational and configurational entropy of these disordered Li-S polyhedra. Overall, this study highlights the utility of MLFF-based large-scale MD simulations in explaining the transport mechanism and the stability of Li-ion in Ti-doped LPS electrolyte with significant computational efficiency.