Quantum Materials - 16

Abstract

Metallic nanoparticles (NPs) show high catalytic reactivity, and the combination of nanoparticles and substrates is one of the important factors to affect the reactivity. Besides this, the particle size and shapes also play an important role. [1] To treat nano-scale metallic nanoparticles on substrates, large calculation models with several thousand atoms are required. In this study, we have investigated the interaction between a gold nanoparticle (AuNP) and MgO substrate using our own large-scale DFT code, CONQUEST [2, 3].
First, we calculated AuNPs in several sizes from 1nm (13 atoms) to 4nm (2057 atoms) with three different structures (Oh, Ih and Dh). It was found that the shape of the nanoparticle clearly affects the atomic and electronic structures. As the particle sizes increase, it becomes difficult to distinguish which atom has more characteristic electronic structure, i.e., which site can be active. Combination with machine learning has enabled it to find characteristic sites efficiently in large complex system.
Principal component analysis (PCA) for local density of states (LDOS) shows the clear site-dependence of the electronic structure of the surface atoms (Fig.1 (a)). By using the same PCA projeciton, the difference of LDOS between isolated and supported AuNPs are found as in Fig. 1(b). The point corresponding to the vertex atom at the interface is far from the other vertex atoms, which means that the LDOS of the vertex atom at the interface is changed dramatically due to the interaction with the MgO substrate [4].