Dataset Information

The effect of double counting, spin density, and Hund interaction in the different DFT+U functionals.

ABSTRACT: A systematic comparative study has been performed to better understand DFT+U (density functional theory?+?U) method. We examine the effect of choosing different double counting and exchange-correlation functionals. The calculated energy distribution and the Hund-J dependence of potential profile for representative configurations clearly show the different behaviors of each DFT+U formalism. In particular, adopting spin-dependent exchange-correlation functionals likely leads to undesirable magnetic solution. Our analyses are further highlighted by real material examples ranging from insulating oxides (MnO and NiO) to metallic magnetic systems (SrRuO₃ and BaFe₂As₂). The current work sheds new light on understanding DFT+U and provides a guideline to use the related methods.

SUBMITTER: Ryee S

PROVIDER: S-EPMC6015075 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The effect of double counting, spin density, and Hund interaction in the different DFT+U functionals.

Ryee Siheon S Han Myung Joon MJ

Scientific reports 20180622 1

A systematic comparative study has been performed to better understand DFT+U (density functional theory + U) method. We examine the effect of choosing different double counting and exchange-correlation functionals. The calculated energy distribution and the Hund-J dependence of potential profile for representative configurations clearly show the different behaviors of each DFT+U formalism. In particular, adopting spin-dependent exchange-correlation functionals likely leads to undesirable magneti ...[more]

PMID: 29934623

Similar Datasets

Project description:Researchers carrying out calculations using the DFT method face the problem of the correct choice of the exchange-correlation functional to describe the quantities they are interested in. This article deals with benchmark calculations aimed at testing various exchange-correlation functionals in terms of a reliable description of the electron density distribution in molecules. For this purpose, 30 functionals representing all rungs of Jacob's Ladder are selected and then the values of some QTAIM-based parameters are compared with their reference equivalents obtained at the CCSD/aug-cc-pVTZ level of theory. The presented results show that the DFT method undoubtedly has the greatest problems with a reliable description of the electron density distribution in multiple strongly polar bonds, such as C=O, and bonds associated with large electron charge delocalization. The performance of the tested functionals turned out to be unsystematic. Nevertheless, in terms of a reliable general description of QTAIM-based parameters, the M11, SVWN, BHHLYP, M06-HF, and, to a slightly lesser extent, also BLYP, B3LYP, and X3LYP functionals turned out to be the worst. It is alarming to find the most popular B3LYP functional in this group. On the other hand, in the case of the electron density at the bond critical point, being the most important QTAIM-based parameter, the M06-HF functional is especially discouraged due to the very poor description of the C=O bond. On the contrary, the VSXC, M06-L, SOGGA11-X, M06-2X, MN12-SX, and, to a slightly lesser extent, also TPSS, TPSSh, and B1B95 perform well in this respect. Particularly noteworthy is the overwhelming performance of double hybrids in terms of reliable values of bond delocalization indices. The results show that there is no clear improvement in the reliability of describing the electron density distribution with climbing Jacob's Ladder, as top-ranked double hybrids are also, in some cases, able to produce poor values compared to CCSD.

Dataset Information

The effect of double counting, spin density, and Hund interaction in the different DFT+U functionals.

Publications

The effect of double counting, spin density, and Hund interaction in the different DFT+U functionals.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets