Accurate and Numerically Efficient r(2)SCAN Meta-Generalized Gradient Approximation

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.