Range-separated hybrid functionals for accurate prediction of band gaps of extended systems


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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Yang, Jing</dc:creator>
  <dc:creator>Falletta, Stefano</dc:creator>
  <dc:creator>Pasquarello, Alfredo</dc:creator>
  <dc:date>2023-06-02</dc:date>
  <dc:description>In this work, we systematically evaluate the accuracy in band gap prediction of range-separated hybrid functionals on a large set of semiconducting and insulating materials and carry out comparisons with the performance of their global counterparts. We observe that all the range-separated hybrid functionals that correctly describe the long-range dielectric screening significantly improve from standard hybrid functionals such as PBE0 and HSE06. Among this group, the choice of the short-range Fock exchange fraction and the screening length can further reduce the predicted error. We then propose a universal expression for the selection of the inverse screening parameter as a function of the short-range and long-range Fock exchange fractions, which results in a mean absolute error as small as 0.15 eV for band gap prediction.</dc:description>
  <dc:identifier>https://archive.materialscloud.org/record/2023.87</dc:identifier>
  <dc:identifier>doi:10.24435/materialscloud:vd-v4</dc:identifier>
  <dc:identifier>mcid:2023.87</dc:identifier>
  <dc:identifier>oai:materialscloud.org:1758</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>Materials Cloud</dc:publisher>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>density-functional theory</dc:subject>
  <dc:subject>hybrid functional</dc:subject>
  <dc:subject>Quantum ESPRESSO</dc:subject>
  <dc:title>Range-separated hybrid functionals for accurate prediction of band gaps of extended systems</dc:title>
  <dc:type>Dataset</dc:type>
</oai_dc:dc>