DFT global optimisation of gas-phase and MgO-supported sub-nanometre AuPd clusters

Abstract

The Birmingham Parallel Genetic Algorithm (BPGA) has been adopted for the global optimization of free and MgO(100)-supported Pd, Au and AuPd nanocluster structures, over the size range N = 4–10. Structures were evaluated directly using density functional theory, which has allowed the identification of Pd, Au and AuPd global minima. The energetics, structures, and tendency of segregation have been evaluated by different stability criteria such as binding energy, excess energy, second difference in energy, and adsorption energy. The ability of the approach in searching for putative global minimum has been assessed against a systematic homotop search method, which shows a high degree of success.