Search for the Lin0/+1/-1 (n=5-7) lowest-energy structures using the ab initio Gradient Embedded Genetic Algorithm (GEGA).: Elucidation of the chemical bonding in the lithium clusters

We report the study of small lithium clusters Li-n(0/+1/-1) (n = 5-7), performed via the novel Gradient Embedded Genetic Algorithm (GEGA) technique and molecular orbital analysis. GEGA was developed for searching of the lowest-energy structures of clusters. Results of our search, obtained using this program, have been compared with the previous ab initio calculations, and the efficiency of the developed GEGA method has thus been confirmed. The molecular orbital analysis of the found Li-n(0)/(+1/-1) (n = 5-7) clusters showed the presence of multiple (a and pi) aromatic character in their chemical bonding, which governs their preferable shapes and special stability.