The Birmingham parallel genetic algorithm and its application to the direct DFT global optimisation of IrN (N=10-20) clusters
The Birmingham parallel genetic algorithm and its application to the direct DFT global optimisation of IrN (N=10-20) clusters
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DOI：
10.1039/c5nr03774c
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发表时间：
2015-01-01
期刊：
影响因子：
6.7
通讯作者：
Johnston, Roy L.
中科院分区：
文献类型：
--
作者：
Davis, Jack B. A.;Shayeghi, Armin;Johnston, Roy L.
介绍了一种新的开源并行遗传算法--Birmingham并行遗传算法，用于金属纳米颗粒的直接密度泛函全局优化。该计划利用池遗传算法的方法，大规模并行计算资源的有效利用。伯明翰并行遗传算法的缩放能力证明通过其应用程序的铱簇的全球优化与10至20个原子，催化重要的系统与有趣的特定尺寸的影响。这是第一次研究其类型的铱集群的这种大小和并行算法被证明是能够超越以前的规模限制和准确地表征这些较大的系统尺寸的结构。通过直接在理论的密度泛函水平上对系统进行全局优化，代码捕获了通常在亚纳米尺寸的Ir簇中发现的立方结构。
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.