Davis Jack B A, Shayeghi Armin, Horswell Sarah L, Johnston Roy L
School of Chemistry, University of Birmingham, Birmingham, B15 2TT, UK.
Nanoscale. 2015 Sep 7;7(33):14032-8. doi: 10.1039/c5nr03774c. Epub 2015 Aug 4.
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.
一种新的开源并行遗传算法——伯明翰并行遗传算法被引入，用于金属纳米颗粒的直接密度泛函理论全局优化。该程序采用池遗传算法方法，以有效利用大规模并行计算资源。通过将伯明翰并行遗传算法应用于含10至20个原子的铱团簇的全局优化，展示了其缩放能力，这是一个具有重要催化作用且有有趣尺寸特异性效应的体系。这是首次针对这种尺寸的铱团簇进行此类研究，并且该并行算法被证明能够突破先前的尺寸限制进行缩放，并准确表征这些更大体系尺寸的结构。通过在密度泛函理论水平上直接对体系进行全局优化，该代码捕捉到了亚纳米尺寸铱团簇中常见的立方结构。
