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Size‐guided multi‐seed heuristic method for geometry optimization of clusters: Application to benzene clusters
Author(s) -
Takeuchi Hiroshi
Publication year - 2018
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.25349
Subject(s) - maxima and minima , cluster (spacecraft) , heuristic , global optimization , energy minimization , maxima , benzene , potential energy surface , geometry , surface (topology) , mathematical optimization , energy (signal processing) , algorithm , computer science , molecule , mathematics , physics , computational chemistry , chemistry , mathematical analysis , quantum mechanics , statistics , art , organic chemistry , performance art , art history , programming language
Since searching for the global minimum on the potential energy surface of a cluster is very difficult, many geometry optimization methods have been proposed, in which initial geometries are randomly generated and subsequently improved with different algorithms. In this study, a size‐guided multi‐seed heuristic method is developed and applied to benzene clusters. It produces initial configurations of the cluster with n molecules from the lowest‐energy configurations of the cluster with n − 1 molecules (seeds). The initial geometries are further optimized with the geometrical perturbations previously used for molecular clusters. These steps are repeated until the size n satisfies a predefined one. The method locates putative global minima of benzene clusters with up to 65 molecules. The performance of the method is discussed using the computational cost, rates to locate the global minima, and energies of initial geometries. © 2018 Wiley Periodicals, Inc.