Accurate and Numerically Efficient r2SCAN Meta-Generalized Gradient Approximation
Accurate and Numerically Efficient r2SCAN Meta-Generalized Gradient Approximation
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DOI：
10.1021/acs.jpclett.0c02405
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发表时间：
2020-10-01
影响因子：
5.7
通讯作者：
Sun, Jianwei
中科院分区：
文献类型：
--
作者：
Furness, James W.;Kaplan, Aaron D.;Sun, Jianwei
最近提出的rSCAN泛函[J.太棒了。2019150,161101]是扫描功能的正规化形式。莱特牧师。2015115,036402]这提高了SCAN的数值性能，但代价是打破了精确交换关联泛函的约束条件。通过恢复对rSCAN的精确约束，我们构造了一种新的亚广义梯度逼近。所得到的泛函在保持rSCAN的数值性能的同时恢复了扫描的可传递精度。
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.