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

被引:21
作者
Arrigoni, Marco [1 ]
Madsen, Georg K. H. [1 ]
机构
[1] TU Wien, Inst Mat Chem, A-1060 Vienna, Austria
关键词
First-principles; Point defects; Charged defects; Thermodynamic stability; Density functional theory; !text type='Python']Python[!/text; OXYGEN VACANCIES; 1ST PRINCIPLES; ENERGY; GAN; NITRIDE;
D O I
10.1016/j.cpc.2021.107946
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Understanding and predicting the thermodynamic properties of point defects in semiconductors and insulators would greatly aid in the design of novel materials and allow tuning the properties of existing ones. As a matter of fact, first-principles calculations based on density functional theory (DFT) and the supercell approach have become a standard tool for the study of point defects in solids. However, in the dilute limit, of most interest for the design of novel semiconductor materials, the "raw" DFT calculations require an extensive post-processing. Spinney is an open-source Python package developed with the aim of processing first-principles calculations to obtain several quantities of interest, such as the chemical potential limits that assure the thermodynamic stability of the defect-laden system, defect charge transition levels, defect formation energies, including electrostatic corrections for finite-size effects, and defect and carrier concentrations. In this paper we demonstrate the capabilities of the Spinney code using c-BN, GaN:Mg, TiO2 and ZnO as examples. (C) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页数:9
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