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 PtN (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 35 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 PtN 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.