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Título
Assessment of density functional approximations for N2 and CO2 physisorption on benzene and graphene
Año del Documento
2022
Editorial
Wiley
Descripción
Producción Científica
Documento Fuente
Journal of Computational Chemistry, 2022, vol. 43, n. 21, p. 1403-1419
Résumé
Experimental isotherms of N2 and CO2 on carbon-based porous materials and models of the physisorption of gases on surfaces are used to obtain the pore size distribution (PSD). An accurate modelization of the physisorption of N2 and CO2 on the surface of carbon-based porous materials is important to obtain accurate N2 and CO2 storage capacities and reliable PSDs. Physisorption depends on the dispersion interactions. High precision ab initio methods, such as CCSD(T), consider accurately the dispersion interactions, but they are computationally expensive. Double hybrid, hybrid and DFT-based methods are much less expensive. In the case of graphene, there are experimental data of the adsorption of N2 and CO2 on graphite that can be used to build the Steele interaction potential of these gases on graphene. The goal is to find out hybrid and/or DFT methods that are as accurate as the CCSD(T) on benzene and as accurate as the experimental results on graphene. Calculations of the interaction energy curves of N2 and CO2 on benzene and graphene have been carried out using the CCSD(T) method and several double hybrid, hybrid, and DFT methods that consider the dispersion interactions. The energy curves on benzene have been compared to the CCSD(T) and the energy curves on graphene have been compared with the Steele energy curves. The comparisons indicate that double hybrids with dispersion corrections and ωB97 based DFT methods are accurate enough for benzene. For graphene, only the PBE-XDM functional has a good agreement with the Steele energy curves.
Materias Unesco
22 Física
23 Química
Palabras Clave
DFT
Dispersion interactions
Gas storage
Graphene
Physisorption
Pore size distribution
ISSN
0192-8651
Revisión por pares
SI
Patrocinador
Junta de Castilla y León, (Grant VA124G18)
Ministerio de Ciencia e Innovación, (Grant PGC2018-093745-B-I00, PID2020-117742GB-I00)
Ministerio de Ciencia e Innovación, (Grant PGC2018-093745-B-I00, PID2020-117742GB-I00)
Version del Editor
Propietario de los Derechos
© 2022 The Author(s)
Idioma
eng
Tipo de versión
info:eu-repo/semantics/publishedVersion
Derechos
openAccess
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