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Spin-Component-Scaled Double Hybrids: An Extensive Search for the Best Fifth-Rung Functionals Blending DFT and Perturbation Theory.
- Source :
- Journal of Computational Chemistry; Oct2013, Vol. 34 Issue 27, p2327-2344, 18p
- Publication Year :
- 2013
-
Abstract
- Such fifth-rung functionals approach the performance of com-posite ab initio methods such as G3 theory at a fraction of their computational cost, and with analytical derivatives avail-able. In this article, we provide a critical analysis of the varia-bles and components that maximize the accuracy of DHs. These include the selection of the exchange and correlation functionals, the coefficients of each component [density func-tional theory (DFT), exact exchange, and perturbative correla-tion in both the same spin and opposite spin terms], and the addition of an ad-hoc dispersion correction; we have termed these parametrizations "DSD-DFT" (Dispersion corrected, Spin-component scaled, Double-hybrid DFT). Somewhat surpris-ingly, the quality of DSD-DFT is only mildly dependent on the underlying DFT exchange and correlation components, with even DSD-LDA yielding respectable performance. Simple, non-empirical GGAs appear to work best, whereas meta-GGAs offer no advantage (with the notable exception of B95c). The best correlation components appear to be, in that order, B95c, P86, and PBEc, while essentially any good GGA exchange yields nearly identical results. On further validation with a wider variety of thermochemical, weak interaction, kinetic, and spectroscopic benchmarks, we find that the best functionals are, roughly in that order, DSD-PBEhB95, DSD-PBEP86, DSD-PBEPW91, and DSD-PBEPBE. In addition, DSD-PBEP86 and DSD-PBEPBE can be used without source code modifications in a wider variety of electronic structure codes. Sample job decks for several commonly used such codes are supplied as electronic Supporting Information. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01928651
- Volume :
- 34
- Issue :
- 27
- Database :
- Complementary Index
- Journal :
- Journal of Computational Chemistry
- Publication Type :
- Academic Journal
- Accession number :
- 91863027
- Full Text :
- https://doi.org/10.1002/jcc.23391