Accurate and Numerically Efficient r<sup>2</sup>SCAN Meta-Generalized Gradient Approximation
Permanent link to this recordhttp://hdl.handle.net/20.500.12613/4237
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AbstractCopyright © 2020 American Chemical Society. The recently proposed rSCAN functional [ J. Chem. Phys. 2019 150, 161101 ] is a regularized form of the SCAN functional [ Phys. Rev. Lett. 2015 115, 036402 ] that improves SCAN's numerical performance at the expense of breaking constraints known from the exact exchange-correlation functional. We construct a new meta-generalized gradient approximation by restoring exact constraint adherence to rSCAN. The resulting functional maintains rSCAN's numerical performance while restoring the transferable accuracy of SCAN.
Citation to related workAmerican Chemical Society (ACS)
Has partJournal of Physical Chemistry Letters
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