Zhang Hongye, Peng Runlai, Wen Huihui, Xie Huimin, Liu Zhanwei
School of Technology, Beijing Forestry University, Beijing 100083, People's Republic of China.
School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, People's Republic of China.
Nanotechnology. 2022 Jul 1;33(38). doi: 10.1088/1361-6528/ac780f.
Geometric phase analysis (GPA) is a powerful tool to investigate the deformation in nanoscale measurement, especially in dealing with high-resolution transmission electron microscopy images. The traditional GPA method using the fast Fourier transform is built on the relationship between the displacement and the phase difference. In this paper, a nano-grid method based on real-space lattice image processing was firstly proposed to enable the measurement of nanoscale interface flatness, and the thickness of different components. Then, a hybrid method for lattice image reconstruction and deformation analysis was developed. The hybrid method enables simultaneous real-space and frequency-domain processing, thus, compensating for the shortcomings of the GPA method when measuring samples with large deformations or containing cracks while retaining its measurement accuracy.
几何相位分析（GPA）是纳米尺度测量中研究变形的有力工具，尤其适用于处理高分辨率透射电子显微镜图像。传统的使用快速傅里叶变换的GPA方法基于位移与相位差之间的关系。本文首先提出了一种基于实空间晶格图像处理的纳米网格方法，用于测量纳米尺度界面平整度和不同组分的厚度。然后，开发了一种用于晶格图像重建和变形分析的混合方法。该混合方法能够同时进行实空间和频域处理，从而在测量大变形或含裂纹样品时弥补了GPA方法的不足，同时保持其测量精度。
