How accurate can Kohn-Sham density functional be for both main-group and transition metal reactions
© 2024 Wiley Periodicals LLC.
Veröffentlicht in: | Journal of computational chemistry. - 1984. - 45(2024), 32 vom: 15. Nov., Seite 2878-2884 |
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Weitere Verfasser: | , |
Format: | Online-Aufsatz |
Sprache: | English |
Veröffentlicht: |
2024
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Zugriff auf das übergeordnete Werk: | Journal of computational chemistry |
Schlagworte: | Journal Article DFT REST double hybrid machine‐learning strong‐correlation |
Zusammenfassung: | © 2024 Wiley Periodicals LLC. Achieving chemical accuracy in describing reactions involving both main-group elements and transition metals poses a substantial challenge for density functional approximations (DFAs), primarily due to the significantly different behaviors for electrons moving in the s,p-orbitals or in the d,f-orbitals. MOR41, a representative dataset of transition metal chemistry, has highlighted the PWPB95-D3(BJ) functional, a B2PLYP-type doubly hybrid (bDH) approximation equipped with an empirical dispersion correction, as the leading functional thus far (Dohm et al., J Chem Theory Comput 2018;14: 2596-2608). However, this functional is not among the top bDH methods for main-group chemistry (Goerigk et al., Phys Chem Chem Phys. 2017;19: 32184). Conversely, bDH methods such as DSD-BLYP-D3, proficient in main-group chemistry, often falter for transition metal chemistry. Herein, taking advantage of the home-made Rust-based Electronic-Structure Toolkits, we examine a suite of XYG3-type doubly hybrid (xDH) methods. We confirm that the trade-off in descriptive accuracy between main-group and transition metal systems persists within the realm of perturbation theory (PT2)-based xDH methods. Notably, however, our study ushers in a pivotal advance with the recently proposed renormalized xDH method, R-xDH7-SCC15. This method not only distinguishes itself among the elite methods for main-group chemistry, but also achieves an unprecedented accuracy for the MOR41 dataset, outperforming all other reported DFAs. The efficacy of R-xDH7-SCC15 stems from the successful integration of a renormalized PT2 correlation model (rPT2) and a machine-learning strong-correlation correction (SCC15), marking a significant step forward in the realm of computational chemistry |
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Beschreibung: | Date Revised 08.11.2024 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
ISSN: | 1096-987X |
DOI: | 10.1002/jcc.27488 |