The Journal of Physical Chemistry Letters· 2020Q1
Accurate and Numerically Efficient r<sup>2</sup>SCAN Meta-Generalized Gradient Approximation
- 1,236citations
- Q1SCImago
- 2020year
Short summary
A new meta-generalized gradient approximation, r²SCAN, restores transferable accuracy of SCAN while maintaining rSCAN's numerical performance.
AI-generated from the title and abstract; the full text is not read.
Key points
- Introduced r²SCAN, a new meta-generalized gradient approximation.
- r²SCAN restores transferable accuracy of SCAN.
- r²SCAN maintains the numerical performance of rSCAN.
- The new functional adheres to exact constraints, unlike rSCAN.
AI-generated from the title and abstract; the full text is not read.
Abstract
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.
The authors' abstract, as published at the source. The Journal of Physical Chemistry Letters, 2020 · DOI ↗
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Field: Spectroscopy
SpectroscopyChemistry