An Evolutionary Algorithm for the Global Optimization of Molecular Clusters: Application to Water, Benzene, and Benzene Cation

Abstract

We have developed an evolutionary algorithm (EA) for the global minimum search of molecular clusters. The EA is able to discover all the putative global minima of water clusters up to (H(2)O)(20) and benzene clusters up to (C(6)H(6))(30). Then, the EA was applied to search for the global minima structures of (C(6)H(6))(n)(+) with n = 2-20, some of which were theoretically studied for the first time. Our results for n = 2-6 are consistent with previous theoretical work that uses a similar interaction potential. Excluding the very symmetric global minimum structure for n = 9, the growth pattern of (C(6)H(6))(n)(+) with n ≥ 7 involves the (C(6)H(6))(2)(+) dimer motif, which is placed off-center in the cluster. Such observation indicates that potentials commonly used in the literature for (C(6)H(6))(n)(+) cannot reproduce the icosahedral-type packing suggested by the available experimental data.

Structural Features of Small Benzene Clusters (C6H6)n (n ≤ 30) As Investigated with the All-Atom OPLS Potential

“…It was possible to find new global minima for (C 6 H 6 ) 11 , (C 6 H 6 ) 14 , and (C 6 H 6 ) 15 , and the minima for n = 16−30 were first reported. The global minima proposed in ref 24 were confirmed by Llanio-Trujillo et al 25 with a different optimization method.…”

Optimization of a genetic algorithm for searching molecular conformer space

“…[22][23][24] Genetic algorithms (GAs) are commonly considered to be an "intelligent" stochastic method as some degree of "learning" occurs through the repeated selection of the fittest individuals, analogous to the process of Darwinian evolution. GAs have been applied to various chemical problems including geometries of transition metal clusters, 25 geometries of molecular clusters, 26 ligand docking, 27 and molecular design. 28 A genetic algorithm begins with a randomly generated set (population) of genomes, each of which has an associated fitness score which is evaluated by some fitness function.…”

Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces

“…This is easy for relatively small molecules, while it becomes more difficult when molecules are flexible or for relatively large clusters. In the contribution by Marques and coworkers [45], an approach is presented based on an evolutionary algorithm to find minimum energy structures [46], applied here to an aggregation of solvent molecules, aggregates and micro-solvation of ions.…”