Robust and efficient calculation of activation energy by automated path search and density functional theory

TL;DR

This paper introduces an automated method combining dynamic programming and density functional theory to efficiently calculate activation energies for ionic diffusion in solid electrolytes, reducing computational costs for high-throughput screening.

Contribution

The authors develop a novel approach that automates the search for diffusion paths and accurately calculates activation energies, improving efficiency over traditional methods.

Findings

Accurately calculated activation energies for beta-Li3PS4 in different crystal directions.

Reduced computational cost by limiting NEB calculations to essential paths.

Validated method with results consistent with previous studies.

Abstract

Because inorganic solid electrolytes are one of the key components for application to all-solid-state batteries, high-ionic-conductivity materials must be developed. Therefore, we propose a method of efficiently evaluating the activation energy of ionic diffusion by calculating a potential-energy surface (PES), searching for the optimal diffusion path by an algorithm developed using dynamic programming (DP), and calculating the corresponding activation energy by the nudged elastic band (NEB) method. Taking beta-Li3PS4 as an example, the activation energy of Li-ion diffusion was calculated as 0.43, 0.25, and 0.40 eV in the a-, b-, and c-axis directions, respectively, which is in good agreement with previously reported values. By comprehensively searching for the lowest energy path by PES-DP, the arbitrariness of the path selection can be eliminated, and the activation energy must only be calculated using the NEB method a few times, which greatly reduces the computational cost required for evaluating activation energy and enables the high-throughput screening of solid state electrolytes.