M06-SX screened-exchange density functional for chemistry and solid-state physics

Ying Wang, Pragya Verma, Lujia Zhang, Yaqi Li, Zhonghua Liu, Donald G. Truhlar, Xiao He

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Screened-exchange hybrid density functionals are especially recommended for solid-state systems because they combine the advantages of hybrid functionals with the correct physics and lower computational cost associated with the attenuation of Hartree–Fock exchange at long range. We present a screened-exchange hybrid functional, M06-SX, that combines the functional form of the local revM06-L functional with a percentage of short-range nonlocal Hartree–Fock exchange. The M06-SX functional gives good results not only for a large set of training data but also for several databases quite different from the training data. The mean unsigned error (MUE) of the M06-SX functional is 2.85 kcal/mol for 418 atomic and molecular energies (AME418) in Minnesota Database 2019, which is better than all five other screened-exchange hybrid functionals tested in this work. The M06-SX functional also gives especially good results for semiconductor band gaps, molecular dissociation energies, noncovalent interactions, barrier heights, and electronic excitation energies excluding long-range charge transfer excitations. For the LC18 lattice constants database, the M06-SX functional gives an MUE of only 0.034 Å. Therefore, the M06-SX functional is well suited for studying molecular chemistry as well as solid-state physics.

Original languageEnglish (US)
Pages (from-to)2294-2301
Number of pages8
JournalProceedings of the National Academy of Sciences of the United States of America
Volume117
Issue number5
DOIs
StatePublished - Feb 4 2020

Bibliographical note

Funding Information:
This work was supported by the Ministry of Science and Technology of China (2016YFA0501700); National Natural Science Foundation of China (21922301, 21903024, 21673074, 21761132022, U1805235, 31770832, and 31570782); Huxiang High-Level Talent Gathering Project of Hunan Province (Grant 2019RS1034); Shanghai Municipal Natural Science Foundation (Grant 18ZR1412600); Youth Top-Notch Talent Support Program of Shanghai; the New York University (NYU)–East China Normal University (ECNU) Center for Computational Chemistry at NYU Shanghai; and the Nanoporous Materials Genome Center by the US Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences under Award DE-FG02-17ER16362. We also thank the Supercomputer Center of ECNU (ECNU Multifunctional Platform for Innovation 001) and Minnesota Supercomputing Institute for providing computer resources.

Funding Information:
ACKNOWLEDGMENTS. This work was supported by the Ministry of Science and Technology of China (2016YFA0501700); National Natural Science Foundation of China (21922301, 21903024, 21673074, 21761132022, U1805235, 31770832, and 31570782); Huxiang High-Level Talent Gathering Project of Hunan Province (Grant 2019RS1034); Shanghai Municipal Natural Science Foundation (Grant 18ZR1412600); Youth Top-Notch Talent Support Program of Shanghai; the New York University (NYU)–East China Normal University (ECNU) Center for Computational Chemistry at NYU Shanghai; and the Nanoporous Materials Genome Center by the US Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences under Award DE-FG02-17ER16362. We also thank the Supercomputer Center of ECNU (ECNU Multifunctional Platform for Innovation 001) and Minnesota Supercomputing Institute for providing computer resources.

Publisher Copyright:
© 2020 National Academy of Sciences. All rights reserved.

Keywords

  • Band gap
  • Condensed-matter theory
  • Kohn–Sham density functional theory
  • Lattice constants
  • Molecular energetics

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