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<u>Accurate and numerically efficient r<sup>2</sup>SCAN meta-generalized gradient approximation</u>

ORAL

Abstract

There are two core goals in exchange-correlation functional design: accuracy and efficiency. Whilst modern semi-local functionals have greatly improved accuracy, this has often been at the cost of efficiency. In a recent publication [1] Bartók and Yates propose a regularised SCAN (rSCAN) that resolves these numerical problems for the SCAN functional [2] at the expense of breaking exact constraints and reducing accuracy. We present the r2SCAN functional [3] that restores exact constraint adherence while preserving regularisation. The r2SCAN functional combines the accuracy of SCAN with the numerical efficiency of rSCAN and presents a powerful tool for bringing high accuracy DFT to numerically sensitive and large-scale problems.

[1] A. P. Bartók, J. R. Yates, J. Chem. Phys. 150, 161101 (2019).
[2] J. Sun, A. Ruzsinszky, J. P. Perdew, Phys. Rev. Lett. 115, 036402 (2015).
[3] J. W. Furness, A. D. Kaplan, J. Ning, J. P. Perdew, and J. Sun, J. Phys. Chem. Lett. 11, 8208 (2020).

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Presenters

  • James Furness

    Tulane Univ, Tulane University, Physics and Engineering Physics, Tulane University

Authors

  • James Furness

    Tulane Univ, Tulane University, Physics and Engineering Physics, Tulane University

  • Aaron Kaplan

    Physics, Temple University, Temple University, Department of Physics, Temple University

  • Jinliang Ning

    Tulane University, Physics and Engineering Physics, Tulane University

  • John Perdew

    Physics, Temple University, Temple University, Physics, Temple Univesrity, Department of Physics and Department of Chemistry, Temple University, Department of Physics, Temple University

  • Jianwei Sun

    Tulane Univ, Physics, Tulane U., Tulane, Department of Physics and Engineering Physics, Tulane University, Physics and Engineering Physics, Tulane University, Tulane University, Tulane U.