pymatgen-analysis-defects: A Python package for analyzing point defects in crystalline materials

Abstract

Since the combinatorics of point defects in crystalline materials can be daunting, it is important to have a software package that can be easily integrated into high-throughput workflows to manage these complex calculations. However, most users of defect analysis packages will not need to run thousands of calculations, so it is important to have code focused purely on the defect analysis and relegate the high-throughput workflow aspect to a separate package. A focus of the present package is also to provide a base library for the analysis of point defects without invoking any high-throughput workflow frameworks. Even though this package was designed with high-throughput in mind and developed alongside a high-throughput workflow framework, it is not dependent on any particular workflow framework and can be used as a standalone analysis package. Additionally, a well-known problem in the simulation of point defects is the fact that current structure optimization techniques can miss the ground state structure based on the initial guess in a sizable minority of cases, so the ability to easily re-visit and re-optimize structures is crucial to building a reliable database of point defects. Towards that end, we have developed a Python package, pymatgen-analysis-defects, and integrated it with the popular atomate2 workflow framework to provide a complete set of tools for simulating, analyzing, and managing the results of point defect calculations.