Kick-Fukui: A Fukui Function-Guided Method for Molecular Structure Prediction

Osvaldo Yañez, Rodrigo Báez-Grez, Diego Inostroza, Ricardo Pino-Rios, Walter A. Rabanal-León, Julia Contreras-García, Carlos Cardenas, William Tiznado

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)3955-3963
Number of pages9
JournalJournal of Chemical Information and Modeling
Volume61
Issue number8
DOIs
Publication statusPublished - 23 Aug 2021

ASJC Scopus subject areas

  • Chemistry(all)
  • Chemical Engineering(all)
  • Computer Science Applications
  • Library and Information Sciences

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