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Global Optimisation Strategies for Nanoalloys

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Clusters

Part of the book series: Challenges and Advances in Computational Chemistry and Physics ((COCH,volume 23))

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Abstract

The computational prediction of thermodynamically stable metal cluster structures has developed into a sophisticated and successful field of research. To this end, research groups have developed, combined and improved algorithms for the location of energetically low-lying structures of unitary and alloy clusters containing several metallic species. In this chapter, we review the methods by which global optimisation is performed on metallic alloy clusters, with a focus on binary nanoalloys, over a broad range of cluster sizes. Case studies are presented, in particular for noble metal and coinage metal nanoalloys. The optimisation of chemical ordering patterns is discussed, including several novel strategies for locating low-energy permutational isomers of fixed cluster geometries. More advanced simulation scenarios, such as ligand-passivated, and surface-deposited clusters have been developed in recent years, in order to bridge the gap between isolated, bare clusters, and the situation observed under experimental conditions. We summarise these developments and consider the developments necessary to improve binary cluster global optimisation in the near future.

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Acknowledgments

R.L.J. acknowledges members of his research group and collaborators, past and present, for their contributions to his research in the area of nanoalloy GO and development of GO strategies. C.J.H. wishes to acknowledge the School of Chemistry at the University of Birmingham, and the EPSRC for funding his PhD studies in the Johnston group. Both authors are grateful to Mark Oakley for supplying data on combined GO approaches, and acknowledge support from EU COST Action MP0903:NANOALLOY and EPSRC Critical Mass Grant (EP/J010804/1) “TOUCAN: TOwards an Understanding of CAtalysis on Nanoalloys”.

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  1. Department of Physics, Chalmers University of Technology, Gothenburg, Sweden

    Christopher J. Heard

  2. School of Chemistry, University of Birmingham, Edgbaston, Birmingham, UK

    Roy L. Johnston

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  1. Department of Chemistry, University of Leuven, Leuven, Belgium

    Minh Tho Nguyen

  2. Department of chemistry and physics, McNeese State University, Lake Charles, Louisiana, USA

    Boggavarapu Kiran

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Heard, C.J., Johnston, R.L. (2017). Global Optimisation Strategies for Nanoalloys. In: Nguyen, M., Kiran, B. (eds) Clusters. Challenges and Advances in Computational Chemistry and Physics, vol 23. Springer, Cham. https://doi.org/10.1007/978-3-319-48918-6_1

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