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Data-driven and constrained optimization of semi-local exchange and nonlocal correlation functionals for materials and surface chemistry.
Trepte, Kai; Voss, Johannes.
Afiliación
  • Trepte K; SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, California, USA.
  • Voss J; SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, California, USA.
J Comput Chem ; 43(16): 1104-1112, 2022 Jun 15.
Article en En | MEDLINE | ID: mdl-35474584
ABSTRACT
Reliable predictions of surface chemical reaction energetics require an accurate description of both chemisorption and physisorption. Here, we present an empirical approach to simultaneously optimize semi-local exchange and nonlocal correlation of a density functional approximation to improve these energetics. A combination of reference data for solid bulk, surface, and gas-phase chemistry and physical exchange-correlation model constraints leads to the VCML-rVV10 exchange-correlation functional. Owing to the variety of training data, the applicability of VCML-rVV10 extends beyond surface chemistry simulations. It provides optimized gas phase reaction energetics and an accurate description of bulk lattice constants and elastic properties.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: J Comput Chem Asunto de la revista: QUIMICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: J Comput Chem Asunto de la revista: QUIMICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos
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