Abstract
A new open-source parallel genetic algorithm, the Birmingham parallel genetic algorithm, is introduced for the direct density functional theory global optimisation of metallic nanoparticles. The program utilises a pool genetic algorithm methodology for the efficient use of massively parallel computational resources. The scaling capability of the Birmingham parallel genetic algorithm is demonstrated through its application to the global optimisation of iridium clusters with 10 to 20 atoms, a catalytically important system with interesting size-specific effects. This is the first study of its type on Iridium clusters of this size and the parallel algorithm is shown to be capable of scaling beyond previous size restrictions and accurately characterising the structures of these larger system sizes. By globally optimising the system directly at the density functional level of theory, the code captures the cubic structures commonly found in sub-nanometre sized Ir clusters.
Highlights
IntroductionNanosized materials are currently being investigated for potential use in a variety of applications
Nanosized materials are currently being investigated for potential use in a variety of applications. This is because the nanosizing effects seen in such materials result in properties different from those of the bulk material
Each was run in parallel with eight instances of the code operating on the pool
Summary
Nanosized materials are currently being investigated for potential use in a variety of applications This is because the nanosizing effects seen in such materials result in properties different from those of the bulk material. These properties can be tuned, normally through altering the size and shape of the cluster Metallic nanoparticles are such materials, with potential optical, magnetic and catalytic applications.[1] Small Ir nanoparticles, in particular, are currently used as catalysts for a range of organic reactions, including olefin hydrogenation, oligomerisation, and ring-opening of cycloalkanes.[2] Ir has been shown both experimentally[3] and theoretically[4] to exhibit significant nanosize-induced hydrogen adsorption capacity. Selective molecular recognition has been seen in supported Ir cluster-based catalysts.[6]
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