3D Atomic Structure of Supported Metallic Nanoparticles Estimated from 2D ADF STEM Images: A Combination of Atom‐Counting and a Local Minima Search Algorithm. Issue 12 (10th November 2021)

• Record Type: Journal Article
• Authors: Arslan Irmak, Ece; Liu, Pei; Bals, Sara; Van Aert, Sandra
• Is Part Of: Small methods. Volume 5:Issue 12(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-11-10
• Subjects: 3D characterization -- local minima search algorithm -- molecular dynamics simulations -- quantitative annular dark‐field scanning transmission electron microscopy -- supported nanoparticles; Nanotechnology -- Methodology -- Periodicals; Nanotechnology -- Periodicals; Periodicals; 620.5028
• DOI: 10.1002/smtd.202101150
• Languages: English
• ISSNs: 2366-9608

Abstract

Abstract: Determining the 3D atomic structure of nanoparticles (NPs) is critical to understand their structure‐dependent properties. It is hereby important to perform such analyses under conditions relevant for the envisioned application. Here, the 3D structure of supported Au NPs at high temperature, which is of importance to understand their behavior during catalytic reactions, is investigated. To overcome limitations related to conventional high‐resolution electron tomography at high temperature, 3D characterization of NPs with atomic resolution has been performed by applying atom‐counting using atomic resolution annular dark‐field scanning transmission electron microscopy (ADF STEM) images followed by structural relaxation. However, at high temperatures, thermal displacements, which affect the ADF STEM intensities, should be taken into account. Moreover, it is very likely that the structure of an NP investigated at elevated temperature deviates from a ground state configuration, which is difficult to determine using purely computational energy minimization approaches. In this paper, an optimized approach is therefore proposed using an iterative local minima search algorithm followed by molecular dynamics structural relaxation of candidate structures associated with each local minimum. In this manner, it becomes possible to investigate the 3D atomic structure of supported NPs, which may deviate from their ground state configuration. Abstract : The combination of atom counting based on annular dark‐field scanning transmission electron microscopy images and an iterative local minima search algorithm followed by molecular dynamics structural relaxation accurately reveals the 3D atomic structure of supported metallic nanoparticles. The proposed approach provides crucial information to understand the structure–property relationship of supported metallic nanoparticles even at high temperatures.