High-throughput screening

of enzyme-mimicking MOFs and their optimisation towards alcohols

• Auteur / Autrice : Lucas Bitencourt theodoroviez
• Direction : Benjamin Katryniok, David Balcells badia, Fabio Bellot noronha
• Type : Projet de thèse
• Discipline(s) : Mécanique des solides, des matériaux, des structures et des surfaces - UCCS
• Date : Inscription en doctorat le 01/06/2024
• Etablissement(s) : Centrale Lille Institut en cotutelle avec Université de Oslo
• Ecole(s) doctorale(s) : École doctorale Sciences de la matière, du rayonnement et de l'environnement
• Partenaire(s) de recherche : Laboratoire : UCCS - Unité de Catalyse et Chimie du Solide

Mots clés

Mots clés libres

Mof

Catalyse hybride

Criblage catalytique

Mof

Hybrid catalysis

High throughput screening

Résumé

This project aims to study the performance of MOFs (metal organic framework) as catalysts for the selective oxidation of methane to methanol. MOFs containing complex mono-Fe or di-Fe sites. High-throughput catalytic tests under different reaction conditions will be performed to correlate the physicochemical properties with the activity, selectivity and stability of the catalyst. The development of catalysts would be supported by a machine learning approach obtained through theoretical calculations. The most promising catalysts will be tested under capillary reaction conditions.

This project aims to study the performance of MOFs (metal organic frameworks) as catalysts for the selective oxidation of methane to methanol. The MOFs contain mono-Fe or di-Fe complex sites. High-throughput catalytic tests under different reaction conditions will be carried out to establish a correlation between the physicochemical properties and the activity, selectivity and stability of the catalyst. The development of the catalysts will be supported by a machine learning approach based on theoretical calculations. The most promising catalysts will be tested under capillary reaction conditions.