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Related papers: Accurate and numerically efficient r$^2$SCAN meta-…

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The SCAN meta-GGA exchange-correlation functional [Phys. Rev. Lett. 115, 036402 (2015)] is constructed as a chemical environment-determined interpolation between two separate energy densities: one describes single orbital electron densities…

Materials Science · Physics 2022-02-02 James W. Furness , Aaron D. Kaplan , Jinliang Ning , John P. Perdew , Jianwei Sun

The Strongly Constrained and Appropriately Normed (SCAN) functional is a non-empirical meta-generalized-gradient approximation (meta-GGA) functional that satisfies all the known constraints that a meta-GGA functional can, but it also…

Materials Science · Physics 2020-04-29 Yoh Yamamoto , Alan Salcedo , Carlos M. Diaz , Md Shamsul Alam , Tunna Baruah , Rajendra R. Zope

The strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation (meta-GGA) functional is a milestone achievement of electronic structure theory. Recently, a revised and restored form (r$^2$SCAN) has been…

Materials Science · Physics 2026-03-18 Adonis Haxhijaj , Stefan Riemelmoser , Alfredo Pasquarello

A recent modification, r$^2$SCAN, of the SCAN (strongly constrained and appropriately normed) meta-GGA exchange-correlation functional mostly eliminates numerical instabilities and attendant integration grid sensitivities exhibited by SCAN.…

Chemical Physics · Physics 2020-09-30 Daniel Mejia-Rodriguez , S. B. Trickey

Constructed to satisfy all known exact constraints and appropriate norms for a semilocal density functional, the strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation functional has shown early promise…

Materials Science · Physics 2018-06-26 Eric B. Isaacs , Chris Wolverton

We propose modifications to the functional form of the SCAN density functional to eliminate numerical instabilities. This is necessary to allow reliable, automatic generation of pseudopotentials (including PAW potentials). The regularized…

Materials Science · Physics 2019-11-01 Albert P. Bartók , Jonathan R. Yates

We assess the accuracy and computational efficiency of the recently developed meta-generalized gradient approximation (metaGGA) functional, the restored regularized strongly constrained and appropriately normed (r$^2$SCAN), in transition…

Materials Science · Physics 2024-06-21 S. Swathilakshmi , Reshma Devi , Gopalakrishnan Sai Gautam

The ground-state energy, electron density, and related properties of ordinary matter can be computed efficiently when the exchange-correlation energy as a functional of the density is approximated semilocally. We propose the first meta-GGA…

Materials Science · Physics 2015-06-25 Jianwei Sun , Adrienn Ruzsinszky , John P. Perdew

We derive and motivate a Laplacian-level, orbital-free meta-generalized-gradient approximation (LL-MGGA) for the exchange-correlation energy, targeting accurate ground-state properties of $sp$ and $sd$ metallic condensed matter, in which…

Materials Science · Physics 2022-08-02 Aaron D. Kaplan , John P. Perdew

A central aim of materials discovery is an accurate and numerically reliable description of thermodynamic properties, such as the enthalpies of formation and decomposition. The r$^2$SCAN revision of the strongly constrained and…

The prominence of density functional theory (DFT) in the field of electronic structure computation stems from its ability to usefully balance accuracy and computational effort. At the base of this ability is a functional of the electron…

We combine a regularized variant of the strongly constrained and appropriately normed semilocal density functional [J. Sun, A. Ruzsinszky, and J. P. Perdew, Phys. Rev. Lett. 115, 036402 (2015)] with the latest generation semi-classical…

Machine learning techniques have received growing attention as an alternative strategy for developing general-purpose density functional approximations, augmenting the historically successful approach of human designed functionals derived…

Chemical Physics · Physics 2022-11-23 Kanun Pokharel , James W. Furness , Yi Yao , Volker Blum , Tom J. P. Irons , Andrew M. Teale , Jianwei Sun

The Jacob's ladder of density functional theory (DFT) proposes the compelling view that by extending the form of successful approximations -- being guided by exact conditions and selected (least empirical) norms -- upper rungs will do…

Materials Science · Physics 2025-02-25 Jacques K. Desmarais , Alessandro Erba , Giovanni Vignale , Stefano Pittalis

The construction of non-empirical density functional approximations is typically guided by the satisfaction of exact constraints. An important constraint is the recovery of the gradient expansion for slowly varying electron densities. In…

Chemical Physics · Physics 2025-12-10 Rohan Maniar , John P. Perdew

Accurate theoretical prediction of the band offsets at interfaces of semiconductor heterostructures can often be quite challenging. Although density functional theory has been reasonably successful to carry out such calculations and…

Despite their practical success, modern seq2seq architectures are unable to generalize systematically on several SCAN tasks. Hence, it is not clear if SCAN-style compositional generalization is useful in realistic NLP tasks. In this work,…

Computation and Language · Computer Science 2021-09-17 Rahma Chaabouni , Roberto Dessì , Eugene Kharitonov

Density functional theory (DFT) in chemistry and materials science aims for "chemical accuracy," but this goal is challenged by the need to approximate the exact exchange-correlation (XC) energy functional. The r$^2$SCAN, meta-generalized…

The strongly constrained and appropriately normed (SCAN) semilocal density functional [J. Sun, A. Ruzsinszky, J. P. Perdew \textit{Phys. Rev. Lett.} {\bf 115}, 036402 (2015)] obeys all 17 known exact constraints for…

Materials Science · Physics 2016-09-28 J. G. Brandenburg , J. E. Bates , A. Ruzsinszky , J. Sun , J. P. Perdew

Kohn-Sham density functional theory (DFT) is nowadays widely used for electronic structure theory simulations, and the accuracy and efficiency of DFT rely on approximations of the exchange-correlation functional. By inclusion of the kinetic…

Materials Science · Physics 2023-06-01 Renxi Liu , Daye Zheng , Xinyuan Liang , Xinguo Ren , Mohan Chen , Wenfei Li
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