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Title: py4DSTEM: A Software Package for Four-Dimensional Scanning Transmission Electron Microscopy Data Analysis

Journal Article · · Microscopy and Microanalysis
ORCiD logo [1];  [2];  [1]; ORCiD logo [1];  [3];  [3];  [4];  [1];  [3]; ORCiD logo [5];  [3];  [1];  [6];  [6];  [7];  [7];  [7];  [1];  [1];  [1] more »;  [3];  [1];  [3];  [1] « less
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Univ. of California, Berkeley, CA (United States)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
  4. Humboldt-Univ. zu Berlin (Germany)
  5. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of Michigan, Ann Arbor, MI (United States)
  6. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  7. Toyota Research Inst., Los Altos, CA (United States)

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 two-dimensional (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 that include data wrangling, calibration, analysis, and 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 also implement 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 and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities Division; National Science Foundation (NSF); US Department of the Navy, Office of Naval Research (ONR); USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division; USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC02-05CH11231; DMR 1548924; N00014-17-1-228; KC22ZH; 89233218CNA000001
OSTI ID:
1798795
Alternate ID(s):
OSTI ID: 1894621
Journal Information:
Microscopy and Microanalysis, Vol. 27, Issue 4; ISSN 1431-9276
Publisher:
Microscopy Society of America (MSA)Copyright Statement
Country of Publication:
United States
Language:
English

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