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Structural evolution in gold nanoparticles using artificial neural network based interatomic potentials
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DOI：10.1063/1.5142903.png)
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Abstract
En 中文
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-Au-13 was identified at Au-60 [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 Au-160, Au-327, and Au-571, which can be recognized as new magic numbers. Au-923 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).
Keywords:
GENERALIZED GRADIENT APPROXIMATION
INITIO MOLECULAR-DYNAMICS
TOTAL-ENERGY CALCULATIONS
EMBEDDED-ATOM-METHOD
CATALYTIC-ACTIVITY
GLOBAL OPTIMIZATION
AU NANOCLUSTERS
CLUSTERS
SURFACES
TRANSITION
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