Defects in WS2 monolayer calculated with a nonlocal functional: any difference from GGA?

IF 2.9 Q3 CHEMISTRY, PHYSICAL Electronic Structure Pub Date : 2023-03-17 DOI:10.1088/2516-1075/acc55d
Daria Kieczka, T. Durrant, Katherine L Milton, K. Goh, M. Bosman, A. Shluger
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引用次数: 1

Abstract

Density functional theory (DFT) with generalised gradient approximation (GGA) functionals is commonly used to predict defect properties in 2D transition metal dichalcogenides (TMDs). Since GGA functionals often underestimate band gaps of semiconductors and incorrectly describe the character of electron localisation in defects and their level positions within the band gap, it is important to assess the accuracy of these predictions. To this end, we used the non-local density functional Perdew—Burke—Ernzerhof (PBE)0-TC-LRC to calculate the properties of a wide range of intrinsic defects in monolayer WS2. The properties, such as geometry, in-gap states, charge transition levels, electronic structure and the electron/hole localisation of the lowest formation energy defects are discussed in detail. They are broadly similar to those predicted by the GGA PBE functional, but exhibit numerous quantitative differences caused by the degree of electron and hole localisation in charged states. For some anti-site defects, more significant differences are seen, with both changes in defect geometries (differences of up to 0.5 Å) as well as defect level positions within the band gap of WS2. This work provides an insight into the performance of functionals chosen for future DFT calculations of TMDs with respect to the desired defect properties.
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用非局部泛函计算WS2单层缺陷:与GGA有何区别?
具有广义梯度近似(GGA)泛函的密度泛函理论(DFT)通常用于预测二维过渡金属二硫族化合物(TMDs)中的缺陷性质。由于GGA泛函经常低估半导体的带隙,并错误地描述了缺陷中电子局部化的特征及其在带隙内的能级位置,因此评估这些预测的准确性很重要。为此,我们使用非局部密度泛函Perdew-Burke-Ernzerhof(PBE)0-TC-LRC来计算单层WS2中各种本征缺陷的性质。详细讨论了最低形成能缺陷的性质,如几何结构、间隙态、电荷跃迁能级、电子结构和电子/空穴局部化。它们与GGA-PBE泛函预测的结果大致相似,但由于带电态中电子和空穴的局域化程度,表现出许多定量差异。对于一些反位点缺陷,可以看到更显著的差异,缺陷几何形状都发生了变化(差异高达0.5 Å)以及WS2的带隙内的缺陷能级位置。这项工作深入了解了为TMDs的未来DFT计算选择的泛函在所需缺陷特性方面的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.70
自引率
11.50%
发文量
46
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