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An Improved Self-Adaptive Differential Evolution with the Neighborhood Search Algorithm for Global Optimization of Bimetallic Clusters
journal contribution
posted on 2022-05-09, 19:22 authored by Wei-Hua Yang, Ya-Meng Li, Jian-Xiang Bi, Rao Huang, Gui-Fang Shao, Tian-E Fan, Tun-Dong Liu, Yu-Hua WenGlobal optimization of multicomponent
cluster structures is considerably
time-consuming due to the existence of a vast number of isomers. In
this work, we proposed an improved self-adaptive differential evolution
with the neighborhood search (SaNSDE) algorithm and applied it to
the global optimization of bimetallic cluster structures. The cross
operation was optimized, and an improved basin hopping module was
introduced to enhance the searching efficiency of SaNSDE optimization.
Taking (PtNi)N (N = 38
or 55) bimetallic clusters as examples, their structures were predicted
by using this algorithm. The traditional SaNSDE algorithm was carried
out for comparison with the improved SaNSDE algorithm. For all the
optimized clusters, the excess energy and the second difference of
the energy were calculated to examine their relative stabilities.
Meanwhile, the bond order parameters were adopted to quantitatively
characterize the cluster structures. The results reveal that the improved
SaNSDE algorithm possessed significantly higher searching capability
and faster convergence speed than the traditional SaNSDE algorithm.
Furthermore, the lowest-energy configurations of (PtNi)38 clusters could be classified as the truncated octahedral and disordered
structures. In contrast, all the optimal (PtNi)55 clusters
were approximately icosahedral. Our work fully demonstrates the high
efficiency of the improved algorithm and advances the development
of global optimization algorithms and the structural prediction of
multicomponent clusters.
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faster convergence speedbond order parametersadaptive differential evolutionptni )< subwork fully demonstratesglobal optimization algorithmstraditional sansde algorithm55 sub38 subneighborhood search algorithmmulticomponent cluster structuresbimetallic cluster structuresimproved sansde algorithmneighborhood searchcluster structuresglobal optimization> subimproved algorithmn sansde optimizationimproved selfmulticomponent clustersbimetallic clustersdisordered structuresvast numbertruncated octahedralstructural predictionsecond differencesearching efficiencyresults revealrelative stabilitiesquantitatively characterizehigh efficiencycross operationconsuming dueconsiderably timeapproximately icosahedral