Characterization of amorphous silica based catalysts using DFT computational methods

Frederik Tielens, Maciej Gierada, Jaroslaw Handzlik, Monica Calatayud

Research output: Contribution to journalArticlepeer-review

82 Citations (Scopus)

Abstract

Much of our current understanding of catalytic activity is derived from materials with well-defined structures, either molecular (i.e., homogeneous catalysts) or extended, ordered solids (i.e., heterogenous catalysts and surface science), and active sites in real catalysts are often assumed to closely resemble structures found in such ordered materials, at least locally. Yet many real catalysts involve amorphous materials and are much more active than their well-ordered counterparts would suggest. This implies that at least some active sites in amorphous materials are intrinsically different. One of these important and versatile amorphous materials is silica. The materials properties are based in many cases on the way molecules interact with the silica surface. Since several years we investigate silica and its role as support of transition metal oxide catalysts, but also the interaction with bio-organic systems, and this at different levels: from the phenomenological description of the interaction at the interface substrate-adsorbate (adsorption and self-assembling of biomolecules) to technologic applications (catalysis, ionic liquids), pharmaceutical (controlled delivery of drug molecules) and their plausible role in different scenarios in the origin of life. For this, we use the tools of quantum chemistry combined with experimental back up with the aim to improve the understanding of the complex chemical behavior of these silica based materials.

Original languageEnglish
Pages (from-to)3-18
Number of pages16
JournalCatalysis Today
Volume354
Early online date2019
DOIs
Publication statusPublished - 1 Sept 2020

Bibliographical note

Funding Information:
HPC resources and services were provided from GENCI-[CCRT/CINES/IDRIS] (Grant 2016-[x2016082022] ) and the CCRE of Université Pierre et Marie Curie are also acknowledged, and the Shared ICT Services Centre funded by the Vrije Universiteit Brussel , the Flemish Supercomputer Center (VSC) and FWO . Computational resources from the PL-Grid Infrastructure are acknowledged as well. MG acknowledges National Science Centre, Poland , Project No. 2015/19/N/ST4/00007 for financial support as well as the Vrije Universiteit Brussel for a financial support of a short research stay. JH acknowledges National Science Centre, Poland, Project No. 2015/19/B/ST4/01836 for financial support.

Funding Information:
HPC resources and services were provided from GENCI-[CCRT/CINES/IDRIS] (Grant 2016-[x2016082022]) and the CCRE of Université Pierre et Marie Curie are also acknowledged, and the Shared ICT Services Centre funded by the Vrije Universiteit Brussel, the Flemish Supercomputer Center (VSC) and FWO. Computational resources from the PL-Grid Infrastructure are acknowledged as well. MG acknowledges National Science Centre, Poland, Project No. 2015/19/N/ST4/00007 for financial support as well as the Vrije Universiteit Brussel for a financial support of a short research stay. JH acknowledges National Science Centre, Poland, Project No. 2015/19/B/ST4/01836 for financial support.

Publisher Copyright:
© 2019 Elsevier B.V.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

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