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Morphology of Cu clusters supported on reconstructed polar ZnO (0001) and (000[1]) surfaces†

Higham, Michael D., Mora-Fonz, David, Sokol, Alexey A., Woodley, Scott M. and Catlow, C. Richard A. ORCID: 2020. Morphology of Cu clusters supported on reconstructed polar ZnO (0001) and (000[1]) surfaces†. Journal of Materials Chemistry A: materials for energy and sustainability 8 (43) , pp. 22840-22857. 10.1039/D0TA08351H

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Unbiased Monte Carlo procedures are applied to investigate the structure of Cu clusters of various sizes deposited over reconstructed polar ZnO surfaces. Four distinct reconstructed polar ZnO surfaces (two Zn terminated (0001) reconstructions and two O terminated (000[1 with combining macron]) reconstructions) were investigated, having previously been determined to be the most stable under typical conditions, as revealed by the grand canonical ensemble studies. Random sampling was performed considering ∼400 000 random initial structural configurations of Cu atoms over the ZnO surfaces, with each structure being optimised using interatomic potential techniques, and the most stable resultant structures being refined using a plane-wave DFT approach. The investigation reveals the key role of surface adatoms and vacancies arising from the reconstruction of the polar ZnO surface in determining the morphology of deposited Cu clusters. Strong Cu–Zn interactions play an essential role in Cu cluster growth, with reconstructed polar ZnO surfaces featuring sites with undercoordinated Zn surface atoms promoting highly localised three dimensional Cu cluster morphologies, whist reconstructions featuring undercoordinated O atoms tend to result in more planar Cu clusters, in order to maximise the favourable Cu–Zn interaction. This is the first study that evaluates the thermodynamically most stable Cu/ZnO structures using realistic reconstructed ZnO polar surfaces, and thus provides valuable insights into the factors affecting Cu cluster growth over ZnO surfaces, as well as model catalyst surfaces that can be utilised in future computational studies to explore catalytic activity for key processes such as CO2 and CO hydrogenation to methanol.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Chemistry
Cardiff Catalysis Institute (CCI)
Advanced Research Computing @ Cardiff (ARCCA)
Additional Information: This article is licensed under a Creative Commons Attribution 3.0 Unported Licence
Publisher: Royal Society of Chemistry
ISSN: 2050-7488
Funders: Science & Technology Facilities Council (STFC)
Date of First Compliant Deposit: 11 November 2020
Date of Acceptance: 13 October 2020
Last Modified: 09 Nov 2022 09:36

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