Accurate and Numerically Efficient r2SCAN Meta-Generalized Gradient Approximation-Reference-Cited by-同舟云学术

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Accurate and Numerically Efficient r2SCAN Meta-Generalized Gradient Approximation

Published:2020-09-02 Issue:19 Volume:11 Page:8208-8215
ISSN:1948-7185
Container-title:The Journal of Physical Chemistry Letters
language:en
Short-container-title:J. Phys. Chem. Lett.

Author:

Furness James W.¹^ORCID,Kaplan Aaron D.²^ORCID,Ning Jinliang¹^ORCID,Perdew John P.²³,Sun Jianwei¹^ORCID

Affiliation:

1. Department of Physics and Engineering Physics, Tulane University, New Orleans, Louisiana 70118, United States

2. Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, United States

3. Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States

Funder

Basic Energy Sciences

Publisher

American Chemical Society (ACS)

Subject

General Materials Science,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpclett.0c02405

Reference65 articles.

1. Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

2. Persson, K. About the Materials Project. 2020; https://materialsproject.org/about.

3. Generalized Gradient Approximation Made Simple

4. Restoring the Density-Gradient Expansion for Exchange in Solids and Surfaces

5. Regularized Gradient Expansion for Atoms, Molecules, and Solids

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