The structure of metal-oxide interfaces investigated by genetic algorithms

Abstract

A global optimization study of oxide-supported metallic nanoparticles was carried out. Cu55 supported on SiO2(0001), TiO2(110) and ZnO(0001) substrates were used as model systems to investigate the preferred metal/oxide interface structure and conformation. The charge optimized many-body (COMB) potentials, coupled to genetic algorithm (GA) searches, were utilized to determine the structural motif of the supported nanoparticle. A second GA optimization was made to study the formation of mixed oxides between the particle and the support. Finally, the effect of oxygen vacancies and oxygen excess at the metal/oxide interface was investigated following the same framework as before. DFT re-optimization of the neutral Cu55- ZnO lower energy structures, for both the mixed and ideal interfaces, was performed.