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arXiv 2201.00297cond-mat.mtrl-sciphysics.app-ph
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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

Sihan Wang, Tim Eldred, Jacob Smith, Wenpei Gao

摘要:

使用四维扫描透射电子显微镜(4D-STEM)方法在晶格应变映射方面的发展现在提供了更高的精度和可行性。然而,由于衍射图样中的噪声和强度的复杂性,自动和准确的衍射分析仍然是具有挑战性的。在这项工作中,我们展示了一种方法,采用斑点检测交叉相关的衍射图案,然后晶格拟合算法,自动处理四维数据,包括识别和定位磁盘,并提取本地晶格参数,而无需事先了解的材料。该方法都是使用模拟的衍射图案进行测试,并应用于从Pd@Pt核壳纳米粒子获得的实验数据。我们的方法显示出对各种样品厚度和高噪声的鲁棒性,处理复杂图案的能力,以及应变测量的皮米级精度,使其成为高通量4D-STEM数据处理的有前途的工具。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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