Structural evolution in gold nanoparticles using artificial neural network based interatomic potentials

Abstract

Relativistic effects of gold make its behavior different from other metals. Unlike silver and copper, gold does not require symmetrical structures as the stable entities. We present the evolution of gold from a cluster to a nanoparticle by considering a majority of stable structural possibilities. Here, an interatomic potential (artificial neural network), trained on quantum mechanical data comprising small to medium sized clusters, gives exceptional results for larger size clusters. We have explored the potential energy surface for "magic" number clusters 309, 561, and 923. This study reveals that these clusters are not completely symmetric, but they require a distorted symmetric core with amorphous layers of atoms over it. The amorphous geometries tend to be more stable in comparison to completely symmetric structures. The first ever gold cluster to hold an icosahedron-Au13 was identified at Au60 [S. Pande et al., J. Phys. Chem. Lett. 10, 1820 (2019)]. Through our study, we have found a plausible evolution of a symmetric core as the size of the nanoparticle increases. The stable cores were found at Au160, Au327, and Au571, which can be recognized as new magic numbers. Au923 is found to have a stable symmetric core of 147 atoms covered with layers of atoms that are not completely amorphous. This shows the preference of symmetric structures as the size of the nanoparticle increases (<3.3 nm). © 2020 Author(s).