An evolutionary algorithm for global minimum search of binary atomic clusters

We propose an evolutionary algorithm (EA) for global optimization of binary atomic clusters. The method is applied to binary Lennard–Jones (BLJ) clusters as a testing ground, while a limited set of results for mixed argon–krypton clusters are also reported. We show that the method is effective in discovering all global minima of BLJ clusters for nuclearities up to N = 50 and different values of the atoms size ratio. Moreover, one new global minimum has been discovered for N = 38 and size ratio 1.05.