Extending DFT-based genetic algorithms by atom-to-place re-assignment via perturbation theory: A systematic and unbiased approach to structures of mixed-metallic clusters

Abstract

Energy surfaces of metal clusters usually show a large variety of local minima. For homo-metallic species the energetically lowest can be found reliably with genetic algorithms, in combination with density functional theory without system-specific parameters. For mixed-metallic clusters this is much more difficult, as for a given arrangement of nuclei one has to find additionally the best of many possibilities of assigning different metal types to the individual positions. In the framework of electronic structure methods this second issue is treatable at comparably low cost at least for elements with similar atomic number by means of first-order perturbation theory, as shown previously [F. Weigend, C. Schrodt, and R. Ahlrichs, J. Chem. Phys. 121, 10380 (2004)]. In the present contribution the extension of a genetic algorithm with the re-assignment of atom types to atom sites is proposed and tested for the search of the global minima of PtHf12 and [LaPb7Bi7](4-). For both cases the (putative) global minimum is reliably found with the extended technique, which is not the case for the "pure" genetic algorithm.

[Co@Sn6Sb6]3−: An Off‐Center Endohedral 12‐Vertex Cluster

“…Thus, we first carried out a systematic search of energetically lowest lying minima for 1 in order to estimate the energetic distance from the observed to other topologies. This was done with a genetic algorithm extended by atom‐type assignment via perturbation theory . Within this algorithm, the individual optimizations were carried out at density functional level (the number of generations was set to 30, the size of each generation to 25; in each generation the 13 energetically least favorable structures were replaced with newly generated ones; for further details see Supporting Information).…”

Pool-BCGA: a parallelised generation-free genetic algorithm for the ab initio global optimisation of nanoalloy clusters

“…6,8 For this reason, the strategy was developed of optimising selected structures with DFT after searching by means of atomistic models using the second-moment approximation to the tight-binding model (SMATB). 34 The traditional generation based BCGA program is a sequential code where local optimisations of individuals are not independent from one-another. 10 This procedure notably enables the theoretical investigation of elaborate mono-and bimetallic clusters using a GA with results consistent with experiments.…”

The Birmingham parallel genetic algorithm and its application to the direct DFT global optimisation of IrN(N = 10–20) clusters

“…[25][26][27][28][29] This work presents the global optimisation of Ir N (N = 10 − 20) clusters directly at the DFT level of theory. [25][26][27][28][29] This work presents the global optimisation of Ir N (N = 10 − 20) clusters directly at the DFT level of theory.…”