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A Fukui function‐guided genetic algorithm. Assessment on structural prediction of Si n ( n = 12–20) clusters
Author(s) -
Yañez Osvaldo,
VásquezEspinal Alejandro,
Inostroza Diego,
Ruiz Lina,
PinoRios Ricardo,
Tiznado William
Publication year - 2017
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.24810
Subject(s) - maxima and minima , cluster (spacecraft) , genetic algorithm , fukui function , algorithm , function (biology) , population , atom (system on chip) , matching (statistics) , characterization (materials science) , computer science , potential energy surface , identification (biology) , mathematics , chemistry , materials science , physics , mathematical optimization , molecule , nanotechnology , statistics , quantum mechanics , biology , mathematical analysis , sociology , embedded system , biochemistry , electrophile , evolutionary biology , programming language , catalysis , demography , botany
Theoretical studies are essential for the structural characterization of clusters, when it comes to rationalize their unique size‐dependent properties and composition. However, the rapid growth of local minima on the potential energy surface (PES), with respect to cluster size, makes the candidate identification a challenging undertaking. In this article, we introduce a hybrid strategy to explore the PES of clusters. This proposal involves the use of a biased initial population of a genetic algorithm procedure. Each individual in this population is built by assembling small fragments, according to the best matching of the Fukui function. The performance of a genetic algorithm procedure. The performance of the method is assessed on the PES exploration of medium‐sized Si n clusters ( n = 12–20). The most relevant results are: (a) the method converges at almost half of the time used by the canonical version of the GA and, (b) in all the studied cases, with the exception of Si 13 and Si 16 , the method allowed to identify the global minimum (GM) and other important low‐lying structures. Additionally, the apparent deficiency of the proposal to identify the GM was corrected when a Si atom, or other low‐lying isomers, were considered to build the clusters. © 2017 Wiley Periodicals, Inc.