Band gaps of crystalline solids from Wannier-localization–based optimal tuning of a screened range-separated hybrid functional

Dahvyd Wing, Guy Ohad, Jonah B. Haber, Marina R. Filip, Stephen E. Gant, Jeffrey B. Neaton, Leeor Kronik*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

71 Citations (Scopus)

Abstract

Accurate prediction of fundamental band gaps of crystalline solid-state systems entirely within density functional theory is a long-standing challenge. Here, we present a simple and inexpensive method that achieves this by means of nonempirical optimal tuning of the parameters of a screened range-separated hybrid functional. The tuning involves the enforcement of an ansatz that generalizes the ionization potential theorem to the removal of an electron from an occupied state described by a localized Wannier function in a modestly sized supercell calculation. The method is benchmarked against experiment for a set of systems ranging from narrow band-gap semiconductors to large band-gap insulators, spanning a range of fundamental band gaps from 0.2 to 14.2 electronvolts (eV), and is found to yield quantitative accuracy across the board, with a mean absolute error of ∼0.1 eV and a maximal error of ∼0.2 eV.

Original languageEnglish
Article numbere2104556118
Number of pages8
JournalProceedings of the National Academy of Sciences of the United States of America
Volume118
Issue number34
Early online date20 Aug 2021
DOIs
Publication statusPublished - 24 Aug 2021

Funding

This work was supported via US-Israel NSF-Binational Science Foundation (BSF) Grant DMR-1708892 and by the Israel Ministry of Defense. Computational resources were provided by the National Energy Research Scientific Computing Center, DOE Office of Science User Facilities supported by the Office of Science of the US Department of Energy under Contract DE-AC02-05CH11231. Additional computational resources were provided by the Extreme Science and Engineering Discovery Environment (XSEDE) supercomputer Stampede2 at the Texas Advanced Computing Center (TACC) through the allocation TG-DMR190070. Publisher Copyright: © 2021 National Academy of Sciences. All rights reserved.

All Science Journal Classification (ASJC) codes

  • General

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