Computational evaluation of the chemical warfare agents capture performances of robust MOFs - Université de Montpellier Accéder directement au contenu
Article Dans Une Revue Microporous and Mesoporous Materials Année : 2019

Computational evaluation of the chemical warfare agents capture performances of robust MOFs

Résumé

A series of stable MOFs containing zirconium or titanium ions as metal centers was screened to assess their capture performances for nerve agents including sarin and soman as well as their standard simulants, i.e. the dimethyl-methyl-phosphonate and diisopropyl fluorophosphate. These Monte Carlo simulations revealed that some of these MOFs show very high uptakes that significantly outperform those of other families of porous materials and interestingly they exhibit a very high affinity for these toxic molecules at low loading. These combined features make them potentially attractive to act as nerve agent filters. This set of adsorption data was further rationalized to establish structure-adsorption performances relationship and Monte Carlo simulations were combined with Density Functional Theory calculations to gain more insight into the adsorption mechanism in play. Finally, the choice of reliable simulants to accurately mimic the adsorption behavior of real toxic molecules in MOFs has been further discussed and in particular it has been established that soman is better described considering the pinacolyl methylphosphonate rather than the standard dimethyl-methyl-phosphonate and diisopropyl fluorophosphate simulants.

Domaines

Chimie
Fichier principal
Vignette du fichier
S138718111930054X.pdf (3.17 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-02100606 , version 1 (21-10-2021)

Licence

Identifiants

Citer

C. Vieira Soares, A.A. Leitão, Guillaume Maurin. Computational evaluation of the chemical warfare agents capture performances of robust MOFs. Microporous and Mesoporous Materials, 2019, 280, pp.97-104. ⟨10.1016/j.micromeso.2019.01.046⟩. ⟨hal-02100606⟩
111 Consultations
96 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More