DFT and GEGA genetic algorithm optimized structures of Cuν n(ν = ±1, 0, 2; n = 3-13) clusters

摘要

We report a study on small copper clusters Cuν n (ν = ±1, 0, 2; n = 3_13) where the minimum energy structures were computed through a joint gradient embedded genetic algorithm (GEGA) technique, and further density functional theory (DFT) geometry reoptimization of the best GEGA cluster structures for each size and charge. Our results are compared to previous ab initio and DFT calculations, when available in the literature, and it is shown than a number of never reported structures for some clusters have been found. From an extensive calibration of some of the DFT commonly used approximate functionals and basis sets, a discussion on its performance and efficiency for Cu cluster calculations is provided. All GEGA found structures are subject to a second step DFT reoptimization process, at the final reported level of theory, BLYP/6-311+G(d), and it is observed that the symmetry found initially by GEGA for almost all of the 66 clusters studied is kept during the DFT reoptimization, which shows the reliability of the initial search algorithm employed. Several geometry-related-properties of these clusters are discussed and compared with some results available in the literature.