Spinney: Post-processing of first-principles calculations of point defects in semiconductors with Python

Understanding and predicting the thermodynamic properties of point defects in semiconductors insulators would greatly aid design novel materials allow tuning existing ones. As a matter fact, first-principles calculations based on density functional theory (DFT) supercell approach have become standard tool for study solids. However, dilute limit, most interest semiconductor materials, “raw“ DFT require an extensive post-processing. Spinney is open-source Python package developed with aim processing to obtain several quantities interest, such as chemical potential limits that assure stability defect-laden system, defect charge transition levels, formation energies, including electrostatic corrections finite-size effects, carrier concentrations. In this paper we demonstrate capabilities code using c-BN, GaN:Mg, TiO2 ZnO examples. Program Title: CPC Library link program files: https://doi.org/10.17632/2xp4ddwmgx.1 Developer’s repository link: https://gitlab.com/Marrigoni/spinney Code Ocean capsule: https://codeocean.com/capsule/4970623 Licensing provisions: MIT Programming language: 3 External libraries: NumPy [1], SciPy [2], Pandas [3], Matplotlib [4], ASE [5] Nature problem: Post-processing order important laden systems dilute-limit: values ensuring stability, energies thereof state-of-the-art schemes equilibrium carriers Solution method: Flexible low-level interface allowing post-processing raw fist-principles data provided by any computer code. High-level parsing produced popular codes VASP WIEN2k. Additional comments restrictions unusual features: An documentation available at: https://spinney.readthedocs.io