Bridging the Gap Between Simulated and Experimental Ionic Conductivities in Lithium Superionic Conductors
Ji Qi, Swastika Banerjee, Yunxing Zuo, Chi Chen, Zhuoying Zhu, H.C., Manas Likhit, Xiangguo Li, Shyue Ping Ong

TL;DR
This paper introduces a method using moment tensor potentials trained on advanced DFT functionals to accurately predict ionic conductivities and activation energies in lithium superionic conductors, bridging the gap between simulations and experiments.
Contribution
The study develops a new approach with moment tensor potentials trained on van der Waals functional data, improving the accuracy of ionic conductivity predictions in LSCs.
Findings
Accurate lattice parameters lead to better conductivity predictions.
Identification of a low-temperature transition between Arrhenius regimes.
Diffusion pathways expand and change dimensionality with temperature.
Abstract
Lithium superionic conductors (LSCs) are of major importance as solid electrolytes for next-generation all-solid-state lithium-ion batteries. While molecular dynamics have been extensively applied to study these materials, there are often large discrepancies between predicted and experimentally measured ionic conductivities and activation energies due to the high temperatures and short time scales of such simulations. Here, we present a strategy to bridge this gap using moment tensor potentials (MTPs). We show that MTPs trained on energies and forces computed using the van der Waals optB88 functional yield much more accurate lattice parameters, which in turn leads to accurate prediction of ionic conductivities and activation energies for the LiLaTiO, LiYCl and LiPS LSCs. NPT MD simulations using the optB88 MTPs also reveal that…
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Taxonomy
TopicsAdvanced NMR Techniques and Applications · Advanced Battery Materials and Technologies · Inorganic Fluorides and Related Compounds
