Mapping strain at the atomic scale with PyNanospacing: An AI-assisted approach to TEM image processing and visualization

The diverse spectrum of material characteristics, including band gap, mechanical moduli, color, phonon and electronic density of states, along with catalytic and surface properties, are intricately intertwined with the atomic structure and the corresponding interatomic bond lengths. This interconnection extends to the manifestation of interplanar spacings within a crystalline lattice. Analysis of these interplanar spacings and the comprehension of any deviations-whether it be lattice compression or expansion, commonly referred to as strain, hold paramount significance in unraveling various unknowns within the field. Transmission Electron Microscopy (TEM) is widely used to capture these atomic-scale ordering, facilitating direct investigation of interplanar spacings. However, creating critical contour maps for visualizing and interpreting lattice stresses in TEM images remains a challenging task. This study introduces an open-source, AI-assisted application, developed entirely in Python, for processing TEM images to facilitate strain analysis through advanced visualization techniques. This application is designed to process a diverse range of materials, including nanoparticles, 2D materials, pure crystals, and solid solutions. By converting local variations in interplanar spacings into contour maps, it provides a visual representation of lattice expansion and compression. With highly versatile settings, as detailed in this paper, the tool is readily accessible for TEM image-based material analysis. It facilitates an in-depth exploration of strain engineering by generating strain contour maps at the atomic scale, offering valuable insights into material properties.

材料特性的多样谱系涵盖带隙、力学模量、颜色、声子态密度与电子态密度，以及催化与表面性质，其与原子结构及对应原子间键长存在紧密的内在关联。这一关联也体现在晶体晶格内的晶面间距表现中。对这些晶面间距的分析，以及对各类偏差——即通常所称的应变的晶格压缩或膨胀——的理解，对于解析该领域内诸多未知问题具有至关重要的意义。透射电子显微镜（Transmission Electron Microscopy, TEM）被广泛用于捕捉这类原子尺度的有序结构，助力晶面间距的直接观测。然而，在透射电子显微镜图像中生成用于可视化与解析晶格应力的关键等高线图，仍是一项富有挑战性的工作。本研究推出一款完全基于Python开发的开源AI辅助应用程序，用于处理透射电子显微镜图像，借助先进可视化技术实现应变分析。该应用可处理涵盖纳米颗粒、二维材料、纯晶体与固溶体在内的多种材料体系。通过将晶面间距的局部差异转换为等高线图，该应用可直观呈现晶格的膨胀与压缩状态。如本文所述，该工具具备高度灵活的配置参数，可便捷应用于基于透射电子显微镜图像的材料分析工作。通过生成原子尺度的应变等高线图，该工具可助力应变工程的深入探索，为理解材料特性提供极具价值的参考视角。