pymatgen-analysis-defects: A Python package foranalyzing point defects in crystalline materials
Jimmy‐Xuan Shen, Joel B. Varley
Abstract
Point defects can often determine the properties of semiconductor and optoelectronic materials. Due to the large simulation cell and the higher-cost density functionals required for defect simulations, the computational cost of defect calculations is often orders of magnitude higher than that of bulk calculations. As such, managing and curating the results of the defect calculations generated by a single user has the potential to save a significant amount of computational resources. Moreover, eventually building a high-quality, persistent defects database will significantly reduce the computational cost of defect calculations for the entire community.
Topics & Concepts
Python (programming language)Computer scienceMaterials scienceProgramming languageMachine Learning in Materials ScienceAdvanced Semiconductor Detectors and MaterialsAdvanced Surface Polishing Techniques