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Physisorption and chemisorption of CO2 on Fe-MIL-88B derivatives: Impact of the functional groups on the electronic properties and adsorption tendency - A theoretical investigation.
Ha, Nguyen Thi Thu; Thao, Ha Thi; Ha, Nguyen Ngoc.
Afiliação
  • Ha NTT; Faculty of Chemistry, Hanoi National University of Education, 100000, 136 Xuan Thuy, Cau Giay, Ha Noi, Viet Nam. Electronic address: ntt.ha@hnue.edu.vn.
  • Thao HT; Faculty of Chemistry, Hanoi National University of Education, 100000, 136 Xuan Thuy, Cau Giay, Ha Noi, Viet Nam.
  • Ha NN; Faculty of Chemistry, Hanoi National University of Education, 100000, 136 Xuan Thuy, Cau Giay, Ha Noi, Viet Nam. Electronic address: hann@hnue.edu.vn.
J Mol Graph Model ; 112: 108124, 2022 05.
Article em En | MEDLINE | ID: mdl-35065402
ABSTRACT
The carbon dioxide adsorption process on Fe-MIL-88B-X (X = -H, -OH, -CH3, -CN, -F, -NH2) derivatives was investigated using a combination of the density functional theory approach, taking into account van der Waals (vdW) interactions (DFT-D2) method, conformer search algorithm (CREST) combined with the partially polarizable generic force-field (GFN-FF) and the Climbing Images - Nudge Elastic Band (CI-NEB) method. The results demonstrate that CO2 may be adsorbed on different active sites via chemisorption or physisorption. The contribution of the vdW interactions to chemisorption and physisorption nodes has been determined. The presence of functional groups has been shown to have a substantial effect on the electronic characteristics of the Fe-MIL-88B, such as ionization energy (IP), electron affinity (EA), and the global electrophilic index (GEI), and therefore on CO2 selective adsorption in a certain direction. The correlation between adsorption energy and the parameters IP, EA, and GEI was analyzed through a multivariable linear regression method.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Mol Graph Model Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Mol Graph Model Ano de publicação: 2022 Tipo de documento: Article