Ab Initio Simulations on the Structure and Properties of Supported Core-Shell Pt Nanoparticles on Single-Layer MoS2

Gabriele Boschetto (Corresponding author), Aida Todri-Sanial (Corresponding author)

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Samenvatting

To effectively employ core-shell nanoparticles in catalysis and sensing necessarily requires a deep atomic-level understanding of their structural and electronic properties. Moreover, for both applications, nanoparticles are usually deposited over a support material which is known to lead to significant (and often unpredictable) changes in their properties and stability. In this work, we study a number of model Pt core-shell nanoparticles supported on single-layer molybdenum disulfide (MoS2). Our aim is to investigate the effect of the support on the properties of such nanoparticles, and we do so by means of first-principles simulations in the framework of density functional theory (DFT). Here, we show that the stability and the catalytic and/or sensing properties of the supported nanoparticles correlate with both strain and charge transfer, which are concurring and competing effects. Overall, our results suggest that core-shell Pt clusters supported on MoS2 may be successfully used in catalysis and in field-effect biosensing.

Originele taal-2Engels
Pagina's (van-tot)24666-24675
Aantal pagina's10
TijdschriftJournal of Physical Chemistry C
Volume127
Nummer van het tijdschrift51
DOI's
StatusGepubliceerd - 28 dec. 2023

Bibliografische nota

Publisher Copyright:
© 2023 American Chemical Society.

Financiering

The authors acknowledge funding from the European Union’s Horizon 2020 research and innovation programme, EU H2020 SmartVista project ( www.smartvista.eu ), grant agreement no. 825114. This work was granted access to the HPC/AI resources of IDRIS (Institut du Développement et des Ressources en Informatique Scientifique) under the allocation 2021-A0110811060 made by GENCI (Grand Équipement National de Calcul Intensif). The authors acknowledge funding from the European Union’s Horizon 2020 research and innovation programme, EU H2020 SmartVista project (www.smartvista.eu), grant agreement no. 825114. This work was granted access to the HPC/AI resources of IDRIS (Institut du Développement et des Ressources en Informatique Scientifique) under the allocation 2021-A0110811060 made by GENCI (Grand Équipement National de Calcul Intensif).

FinanciersFinanciernummer
Horizon 2020 Framework Programme825114
Grand Équipement National De Calcul Intensif

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