Abstract
Development in lattice strain mapping using four-dimensional scanning transmission electron microscopy (4D-STEM) method now offers improved precision and feasibility. However, automatic and accurate diffraction analysis is still challenging due to noise and the complexity of intensity in diffraction patterns. In this work, we demonstrate an approach, employing the blob detection on cross-correlated diffraction patterns followed by a lattice fitting algorithm, to automate the processing of four-dimensional data, including identifying and locating disks, and extracting local lattice parameters without prior knowledge about the material. The approach is both tested using simulated diffraction patterns and applied on experimental data acquired from a Pd@Pt core-shell nanoparticle. Our method shows robustness against various sample thicknesses and high noise, capability to handle complex patterns, and picometer-scale accuracy in strain measurement, making it a promising tool for high-throughput 4D-STEM data processing.
| Original language | English |
|---|---|
| Article number | 113513 |
| Journal | Ultramicroscopy |
| Volume | 236 |
| DOIs | |
| State | Published - Jun 2022 |
| Externally published | Yes |
Funding
This work was supported by start-up fund from the College of Engineering and Department of Materials Science and Engineering at North Carolina State University. Electron microscopy was performed at the Analytical Instrumentation Facility (AIF) at North Carolina State University, which is supported by the State of North Carolina and the National Science Foundation (award number ECCS-2025064). The AIF is a member of the North Carolina Research Triangle Nanotechnology Network (RTNN), a site in the National Nanotechnology Coordinated Infrastructure (NNCI). The authors thank Prof. Jianbo Wu from Shanghai Jiao Tong University and Prof. Hui Zhang from Zhejiang University for providing the Pd@Pt octahedral nanoparticles. The python source code of AutoDisk and a demo are available on GitHub at https://github.com/swang59/AutoDisk_Demo. Additional raw data of the 4D-STEM experiment is available upon request to the corresponding author. This work was supported by start-up fund from the College of Engineering and Department of Materials Science and Engineering at North Carolina State University. Electron microscopy was performed at the Analytical Instrumentation Facility (AIF) at North Carolina State University, which is supported by the State of North Carolina and the National Science Foundation (award number ECCS-2025064). The AIF is a member of the North Carolina Research Triangle Nanotechnology Network (RTNN), a site in the National Nanotechnology Coordinated Infrastructure (NNCI). The authors thank Prof. Jianbo Wu from Shanghai Jiao Tong University and Prof. Hui Zhang from Zhejiang University for providing the Pd@Pt octahedral nanoparticles.