arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2003.09523cond-mat.mtrl-scicond-mat.mes-hallphysics.app-ph
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py4DSTEM:一个用于四维扫描透射电子显微镜数据集多峰分析的软件包

py4DSTEM: a software package for multimodal analysis of four-dimensional scanning transmission electron microscopy datasets

Benjamin H Savitzky, Lauren A Hughes, Steven E Zeltmann, Hamish G Brown, Shiteng Zhao, Philipp M Pelz, Edward S Barnard, Jennifer Donohue, Luis Rangel DaCosta, … 展开作者

Benjamin H Savitzky, Lauren A Hughes, Steven E Zeltmann, Hamish G Brown, Shiteng Zhao, Philipp M Pelz, Edward S Barnard, Jennifer Donohue, Luis Rangel DaCosta, Thomas C. Pekin, Ellis Kennedy, Matthew T Janish, Matthew M Schneider, Patrick Herring, Chirranjeevi Gopal, Abraham Anapolsky, Peter Ercius, Mary Scott, Jim Ciston, Andrew M Minor, Colin Ophus

摘要:

扫描透射电子显微镜(STEM)允许在从微米到原子的长度尺度上对材料进行成像、衍射和光谱分析。通过使用高速直接电子检测器,现在可以在每个探头位置处记录衍射电子束的完整2D图像,通常是探头位置的2D网格。这些4D-STEM数据集包含丰富的信息,包括局部结构、方向、变形、电磁场和其他样本相关属性的签名。然而,提取这些信息需要复杂的分析流程,从数据处理到校准,再到分析,再到可视化,同时还要保持对成像失真和伪影的鲁棒性。在本文中,我们介绍了py 4DSTEM,一个用于测量4D-STEM数据集的材料属性的分析工具包,用Python语言编写,并以开源许可证发布。我们详细描述了数据集校准和各种4D-STEM属性测量的算法步骤,并给出了几个实验数据集的结果。我们还在py 4DSTEM中实现了一种适用于电子显微镜数据的简单通用文件格式,该格式使用开源HDF 5标准。我们希望这个工具将有利于研究社区,有助于推动电子显微镜数据和计算方法的发展标准,并邀请社区为这个正在进行的完全开源项目做出贡献。

英文摘要:

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full 2D image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields and other sample-dependent properties. However, extracting this information requires complex analysis pipelines, from data wrangling to calibration to analysis to visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail, and present results from several experimental datasets. We have also implemented a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open source HDF5 standard. We hope this tool will benefit the research community, helps to move the developing standards for data and computational methods in electron microscopy, and invite the community to contribute to this ongoing, fully open-source project.

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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