Ground State Structure of Cu Nanoclusters

The study of metal clusters has attracted much attention in recent years. Noble metal nanoparticles are of particular interest since their chemical, thermodynamic, electronic, and optical properties make them interesting candidates as building blocks of nanostructure materials. Delineation of these properties requires a complete and definitive characterization of the cluster’s geometrical structure. To find the ground state structure for a cluster, the potential-energy surface (PES) needs to be searched. In this paper, we proposed an efficient hierarchical search method to determine a ground state structure of copper clusters using an effective Monte Carlo simulated annealing method, which employs the Aggregate-Volume-Bias Monte Carlo (AVBMC) algorithm. Incorporated in the Monte Carlo method, is an efficient Embedded Atom Method (EAM) potential developed by the authors.