论文标题
Spinney：python半导体中第一原理计算的后处理。
Spinney: post-processing of first-principles calculations of point defects in semiconductors with Python
论文作者
论文摘要
了解和预测半导体和绝缘体中点缺陷的热力学特性将极大地帮助设计新型材料，并允许调整现有材料的性能。实际上，基于密度功能理论（DFT）和超级细胞方法的第一原理计算已成为研究固体中点缺陷的标准工具。然而，在稀释极限中，最感兴趣的新型半导体材料的设计，原始DFT计算需要广泛的后处理。 Spinney是一种开发的开源Python包装，其目的是处理第一原理计算，以获得几量的感兴趣，例如确保缺陷系统的热力学稳定性，缺陷电荷过渡水平，缺陷形成能量的化学潜在极限，包括对有限量效应的静电效应效应效应，以及有限量效应效果和置换率和最初的载体。在本文中，我们使用C-BN，掺杂MG的GAN，TIO2和ZnO作为示例演示了Spinney代码的功能。
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 defectladen 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, Mg-doped GaN, TiO2 and ZnO as examples.
