Subnano Pt Particles from a First-Principles Stochastic Surface Walking Global Search

Subnano transition metal particles have wide applications in chemistry. For the complexity of their potential energy surface, it has long been a great challenge for both theory and experiment to determine the structure of subnano clusters and thus predict their physiochemical properties. Here we explore the structure configurations for 35 subnano Pt-N (N = 12-46) clusters using a first-principles Stochastic Surface Walking (SSW) global search. For each cluster, thousands of structure candidates are collected from a parallel SSW search. This leads to the finding of 20 new global minima in 3S clusters, which reflects the essence of a first-principles global search for revealing the structure of subnano transition metal clusters. PtN subnano clusters with N being 14, 18, 22, 27, 36, and 44 have higher stability than their neighboring size clusters and are characterized as magic number clusters. These Pt-N subnano clusters exhibit metallic characteristics with a diminishing HOMO-LUMO gap, much poorer binding energy (by 1-1.7 eV), and a much higher Fermi level (by 1-1.5 eV) than bulk metal, implying their high chemical activity. By analyzing their structures, we observe the presence of a rigid core and a soft shell for PtN clusters and find that the core shell 3-D architecture evolves as early as N > 22. For these core shell clusters, a good core-shell lattice match is the key to achieve the high stability.