Issue 9, 2016

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

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

Supplementary files

Article information

Article type
Paper
Submitted
15 Jan 2016
Accepted
03 Feb 2016
First published
04 Feb 2016
This article is Open Access
Creative Commons BY license

Phys. Chem. Chem. Phys., 2016,18, 6676-6682

Author version available

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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