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Kick–Fukui: A Fukui Function-Guided Method for Molecular Structure Prediction
Author(s) -
Osvaldo Yáñez,
Rodrigo BáezGrez,
Diego Inostroza,
Ricardo PinoRios,
Walter A. RabanalLeón,
Julia ContrerasGarcía,
Carlos Cárdenas,
William Tiznado
Publication year - 2021
Publication title -
journal of chemical information and modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 160
eISSN - 1549-960X
pISSN - 1549-9596
DOI - 10.1021/acs.jcim.1c00605
Subject(s) - maxima and minima , fukui function , population , density functional theory , function (biology) , statistical physics , chemistry , computational chemistry , physics , mathematics , mathematical analysis , biochemistry , demography , electrophile , evolutionary biology , sociology , biology , catalysis
Here, we introduce a hybrid method, named Kick-Fukui, to explore the potential energy surface (PES) of clusters and molecules using the Coulombic integral between the Fukui functions in the first screening of the best individuals. In the process, small stable molecules or clusters whose combination has the stoichiometry of the explored species are used as assembly units. First, a small set of candidates has been selected from a large and stochastically generated (Kick) population according to the maximum value of the Coulombic integral between the Fukui functions of both fragments. Subsequently, these few candidates are optimized using a gradient method and density functional theory (DFT) calculations. The performance of the program has been evaluated to explore the PES of various systems, including atomic and molecular clusters. In most cases studied, the global minimum (GM) has been identified with a low computational cost. The strategy does not allow to identify the GM of some silicon clusters; however, it predicts local minima very close in energy to the GM that could be used as the initial population of evolutionary algorithms.

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