Structural optimization of Pt-Pd-Rh trimetallic nanoparticles using improved genetic algorithm

Metallic nanoparticles have received considerable attention due to their superior catalytic properties. In this study, we proposed an improved genetic algorithm to optimize atomic structures of Pt-Pd-Rh trimetallic nanoparticles with various sizes and compositions. In the improved genetic algorithm, a layered coordinate ranking method and an effective fitness function were introduced to enhance its searching capability. The optimized results show that Pt and Pd atoms prefer to segregate on the surface, while Rh atoms tend to aggregate inside. Meanwhile, Pd atoms exhibit stronger surface segregation than Pt ones. Furthermore, the distribution of atomic coordination number was investigated.