Miniature physical sphere-in-contact models of heterogeneous catalysts and metal nanoparticles

Article


Zeinalipour-Yazdi, C.D. and Pullman, D.P. 2023. Miniature physical sphere-in-contact models of heterogeneous catalysts and metal nanoparticles. Journal of Molecular Modeling. 29 (10), p. 312. https://doi.org/10.1007/s00894-023-05721-2
TypeArticle
TitleMiniature physical sphere-in-contact models of heterogeneous catalysts and metal nanoparticles
AuthorsZeinalipour-Yazdi, C.D. and Pullman, D.P.
Abstract

Context
Physical molecular models have played a fundamental role in the understanding of chemical reactions on heterogeneous catalysts and on metal nanoparticles. To date, these physical models have been based on separate models of the metal nanoparticle (NP) or surface and of the substrate and the molecular structure of reactant and product adsorbates and their intermediates. In this paper, we try to provide a new miniature physical molecular model, the sphere-in-contact model of heterogeneous catalysts and metal nanoparticles that can build inexpensive, small and efficient molecular models that can be transported or shipped easily and that depict the chemical reaction as a whole, showing reactants, intermediates, products, the metal nanoparticle bound to the substrate which can give information about a reaction mechanism. These models reveal that there are certain rules with respect to the kind of sites you observe at the metal NP interface with the support by small movement of the nanoparticle.

Methods
We have used in this study physical molecular models using the sphere-in-contact model. This is the first time such physical models are built for heterogeneous catalytic reactions and metal nanoparticles, and they are constructed out of spheres that fuse together when exposed to water.

KeywordsMetal nanoparticles; Molecular models; Sphere-in-contact; Heterogeneous catalyst; Physical models
Sustainable Development Goals9 Industry, innovation and infrastructure
Middlesex University ThemeSustainability
PublisherSpringer
JournalJournal of Molecular Modeling
ISSN1610-2940
Electronic0948-5023
Publication dates
Online13 Sep 2023
Print13 Sep 2023
Publication process dates
Submitted30 Jun 2023
Accepted04 Sep 2023
Deposited18 Nov 2025
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1007/s00894-023-05721-2
PubMed ID37700099
Related Output
Has versionhttps://nul.repository.guildhe.ac.uk/id/eprint/1057
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