AUTOMATON: A Program That Combines a Probabilistic Cellular Automata and a Genetic Algorithm for Global Minimum Search of Clusters and Molecules

Abstract

A novel program for the search of global minimum structures of atomic clusters and molecules in the gas phase, AUTOMATON, is introduced in this work. This program involves the following: first, the generation of an initial population, using a simplified probabilistic cellular automaton method, which allows easy control of the adequate distribution of atoms in space; second, the fittest individuals are selected to evolve, through genetic operations (mating and mutations), until the best candidate for a global minimum surfaces. In addition, we propose a simple way to build the descendant structures by establishing a ranking of genes to be inherited. Thus, by means of a chemical formula checker procedure, genes are transferred to the offspring, ensuring that they always have the appropriate type and number of atoms. It is worth noting that a fraction of the fittest group is subject to mutation operations. This program also includes algorithms to identify duplicate structures: one based on geometric similarity and another on the similar distribution of atomic charges. The effectiveness of the program was evaluated in a group of 45 molecules, considering organic and organometallic compounds (benzene, cyclopentadienyl anion, and ferrocene), Zintl ion clusters [Sn9–m–nGemBin](4–n)– (n = 1–4 and m = 0–(9–n)), star-shaped clusters (Li7E5+, E = BH, C, Si, Ge) and a variety of boron-based clusters. The global minimum and the lowest-energy isomers reported in the literature were found for all the cases considered in this article. These results successfully prove AUTOMATON’s effectiveness on the identification of energetically preferred structures of a wide variety of chemical species.