Login / Signup

Accurate and Numerically Efficient r2SCAN Meta-Generalized Gradient Approximation.

James W FurnessAaron D KaplanJinliang NingJohn P PerdewJianwei Sun
Published in: The journal of physical chemistry letters (2020)
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.
Keyphrases
  • computed tomography
  • magnetic resonance imaging
  • magnetic resonance
  • type diabetes
  • density functional theory
  • mass spectrometry
  • weight loss