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Issue 9, 2016
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Global optimization of small bimetallic Pd–Co binary nanoalloy clusters: a genetic algorithm approach at the DFT level

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Abstract

The global optimisation of small bimetallic PdCo binary nanoalloys are systematically investigated using the Birmingham Cluster Genetic Algorithm (BCGA). The effect of size and composition on the structures, stability, magnetic and electronic properties including the binding energies, second finite difference energies and mixing energies of Pd–Co binary nanoalloys are discussed. A detailed analysis of Pd–Co structural motifs and segregation effects is also presented. The maximal mixing energy corresponds to Pd atom compositions for which the number of mixed Pd–Co bonds is maximised. Global minimum clusters are distinguished from transition states by vibrational frequency analysis. HOMO–LUMO gap, electric dipole moment and vibrational frequency analyses are made to enable correlation with future experiments.

Graphical abstract: Global optimization of small bimetallic Pd–Co binary nanoalloy clusters: a genetic algorithm approach at the DFT level

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Publication details

The article was received on 15 Jan 2016, accepted on 03 Feb 2016 and first published on 04 Feb 2016


Article type: Paper
DOI: 10.1039/C6CP00342G
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Citation: Phys. Chem. Chem. Phys., 2016,18, 6676-6682
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    Global optimization of small bimetallic Pd–Co binary nanoalloy clusters: a genetic algorithm approach at the DFT level

    M. Aslan, J. B. A. Davis and R. L. Johnston, Phys. Chem. Chem. Phys., 2016, 18, 6676
    DOI: 10.1039/C6CP00342G

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