Simulated annealing method for metal nanoparticle structures optimization

Abstract

The goal of this paper is to develop an efficient method to search for metal and bimetal nanoparticle structures with the lowest possible potential energy. This is a global optimization problem. In computational complexity theory, global optimization problems are NP-hard, meaning that they cannot be solved in polynomial time. Because of the severe difficulty of finding the global minimum, the simulated annealing algorithm was selected as main strategy. At the first step we use the lattice Monte Carlo method with different lattices. Then we relax the resulting nanoparticle structures at low temperature within molecular dynamics, choosing one of them as approximation of the global minimum. The numerical solution of an optimal cluster structure of Ag (200) shows the efficiency of the proposed method.