AiiDA-defects: an automated and fully reproducible workflow for the complete characterization of defect chemistry in functional materials

Abstract

Abstract Functional materials that enable many technological applications in our everyday lives owe their unique properties to defects that are carefully engineered and incorporated into these materials during processing. However, optimizing and characterizing these defects is very challenging in practice, making computational modelling an indispensable complementary tool. We have developed an automated workflow and code to accelerate these calculations (AiiDA-defects), which utilises the AiiDA framework, a robust open-source high-throughput materials informatics infrastructure that provides workflow automation while simultaneously preserving and storing the full data provenance in a relational database that is queryable and traversable. This paper describes the design and implementation details of AiiDA-defects, the models and algorithms used, and demonstrates its use in an application to fully characterize the defect chemistry of the well known solid-state Li-ion conductors LiZnPS4. We anticipate that AiiDA-defects will be useful as a tool for fully automated and reproducible defect calculations, allowing detailed defect chemistry to be obtained in a reliable and high-throughput way, and paving the way toward the generation of defects databases for accelerated materials design and discovery.