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A Fukui function-guided genetic algorithm. Assessment on structural prediction of Sin (n = 12–20) clusters

dc.contributor.authorYañez O.
dc.contributor.authorVásquez-Espinal A.
dc.contributor.authorInostroza D.
dc.contributor.authorRuiz L.
dc.contributor.authorPino-Rios R.
dc.contributor.authorTiznado W.
dc.date.accessioned2020-09-02T22:30:37Z
dc.date.available2020-09-02T22:30:37Z
dc.date.issued2017
dc.identifier10.1002/jcc.24810
dc.identifier.citation38, 19, 1668-1677
dc.identifier.issn01928651
dc.identifier.urihttps://hdl.handle.net/20.500.12728/6649
dc.descriptionTheoretical 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 Sin 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 Si13 and Si16, 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. © 2017 Wiley Periodicals, Inc.
dc.language.isoen
dc.publisherJohn Wiley and Sons Inc.
dc.subjectclusters
dc.subjectFukui function
dc.subjectgenetic algorithm
dc.subjectpotential energy surface exploration
dc.subjectGenetic algorithms
dc.subjectIsomers
dc.subjectMolecular physics
dc.subjectPotential energy
dc.subjectPotential energy surfaces
dc.subjectQuantum chemistry
dc.subjectSilicon
dc.subjectBiased initial population
dc.subjectCandidate identifications
dc.subjectClusters
dc.subjectFukui functions
dc.subjectGuided genetic algorithms
dc.subjectLow-lying structures
dc.subjectStructural characterization
dc.subjectTheoretical study
dc.subjectClustering algorithms
dc.subjectarticle
dc.subjectclinical article
dc.subjectgenetic algorithm
dc.subjecthuman
dc.subjecthuman experiment
dc.subjectisomer
dc.subjectprediction
dc.subjecttheoretical study
dc.titleA Fukui function-guided genetic algorithm. Assessment on structural prediction of Sin (n = 12–20) clusters
dc.typeArticle


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