论文标题
AutoDisk：4D-STEM中的自动衍射处理和应变映射
AutoDisk: Automated Diffraction Processing and Strain Mapping in 4D-STEM
论文作者
论文摘要
现在，使用四维扫描透射电子显微镜（4D-STEM）方法在晶格应变映射中的开发现在提供了提高的精度和可行性。但是，由于噪声和衍射模式中强度的复杂性，自动和准确的衍射分析仍然具有挑战性。在这项工作中，我们演示了一种方法，在交叉相关的衍射模式上采用了斑点检测，然后使用晶格拟合算法，以自动化四维数据的处理，包括识别和定位磁盘，并在没有材料的事先了解的情况下提取局部lattice参数。使用模拟衍射模式测试了该方法，并应用于从PD@PT核心壳纳米粒子中获取的实验数据。我们的方法显示了针对各种样品厚度和高噪声，处理复杂模式的能力以及应变测量中的尺度精度的鲁棒性，这使其成为高通量4D-STEM数据处理的有前途的工具。
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 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.
