Benchmarking exchange-correlation potentials with the mstar60 dataset: Importance of the nonlocal exchange potential for effective mass calculations in semiconductors
Magdalena Laurien, Oleg Rubel

TL;DR
This paper benchmarks various exchange-correlation functionals for calculating effective masses in semiconductors, highlighting the importance of nonlocal exchange in hybrid functionals like HSE06 for accuracy.
Contribution
It introduces the mstar60 dataset and demonstrates the critical role of nonlocal exchange in effective mass calculations, providing insights for computational material science.
Findings
HSE06 provides the most accurate effective masses among tested functionals.
Omission of nonlocal exchange causes significant errors in effective mass calculations.
TB-mBJ overestimates effective masses but can be scaled for practical estimates.
Abstract
The accuracy of effective masses predicted by density functional theory depends on the exchange-correlation functional employed, with nonlocal hybrid functionals giving more accurate results than semilocal functionals. In this article, we benchmark the performance of the Perdew-Burke-Ernzerhof (PBE), Tran-Blaha modified Becke-Johnson (TB-mBJ), and the hybrid Heyd-Scuseria-Ernzerhof (HSE06) exchange-correlation functionals and potentials for the calculation of effective masses with perturbation theory. We introduce the mstar60 dataset, which contains 60 effective masses derived from 18 semiconductors. The ratio between experimental and calculated effective masses is for PBE, for TB-mBJ, for HSE06. We reveal that the nonlocal exchange in HSE06 enlarges the optical transition matrix elements leading to the superior accuracy of the hybrid…
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Taxonomy
TopicsAdvanced Chemical Physics Studies · Machine Learning in Materials Science · Heusler alloys: electronic and magnetic properties
