Accurate and Numerically Efficient r<sup>2</sup>SCAN Meta-Generalized Gradient Approximation
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Pre-printDate
2020-10-01Author
Furness, JWKaplan, AD
Ning, J
Perdew, JP
Sun, J
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http://hdl.handle.net/20.500.12613/4237
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10.1021/acs.jpclett.0c02405Abstract
Copyright © 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 work
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http://dx.doi.org/10.34944/dspace/4219