Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published November 30, 2023 | Published
Journal Article Open

Understanding Ionic Diffusion Mechanisms in Li₂S Coatings for Solid-State Batteries: Development of a Tailored Reactive Force Field for Multiscale Simulations

Abstract

In order to investigate Li2₂S as a potential protective coating for lithium anode batteries using superionic electrolytes, we need to describe reactions and transport for systems at scales of >10,000 atoms for time scales beyond nanoseconds, which is most impractical for quantum mechanics (QM) calculations. To overcome this issue, here, we first report the development of the reactive analytical force field (ReaxFF) based on density functional theory (DFT) calculations on model systems at the PBE0/TZVP and M062X/TZVP levels. Then, we carry out reactive molecular dynamics simulations (RMD) for up to 20 ns to investigate the diffusion mechanisms in bulk Li₂S as a function of vacancy density, determining the activation barrier for diffusion and conductivity. We show that RMD predictions for diffusion and conductivity are comparable to experiments, while results on model systems are consistent with and validated by short (10–100 ps) ab initio molecular dynamics (AIMD). This new ReaxFF for Li₂S systems enables practical RMD on spatial scales of 10–100 nm (10,000 to 10 million atoms) for the time scales of 20 ns required to investigate predictively the interfaces between electrodes and electrolytes, electrodes and coatings, and coatings and electrolytes during the charging and discharging processes.

Copyright and License

© 2023 The Authors. Published by American Chemical Society. Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).

Acknowledgement

M.D. thanks: the HPC resources of CINECA, i.e., Galileo 100 for Project ISCRA C, 'ISc92: SEILIM' and the WAG/Caltech computational resources. W.A.G. thanks Hong Kong Quantum AI Lab, AIR@In-noHK, Hong Kong Government, for financial support for this research. The financial support provided by the European Union Horizon 2020 SUBLIME Grant Agreement ID: 875028 is gratefully acknowledged.

Conflict of Interest

The authors declare no competing financial interest.

Files

jp3c04991_si_002.zip
Files (3.7 MB)

Additional details

Created:
December 6, 2023
Modified:
December 6, 2023