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

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 b...

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Bibliographic Details
Published in:Microscopy and microanalysis Vol. 27; no. 4; pp. 712 - 743
Main Authors: Savitzky, Benjamin H., Zeltmann, Steven E., Hughes, Lauren A., Brown, Hamish G., Zhao, Shiteng, Pelz, Philipp M., Pekin, Thomas C., Barnard, Edward S., Donohue, Jennifer, Rangel DaCosta, Luis, Kennedy, Ellis, Xie, Yujun, Janish, Matthew T., Schneider, Matthew M., Herring, Patrick, Gopal, Chirranjeevi, Anapolsky, Abraham, Dhall, Rohan, Bustillo, Karen C., Ercius, Peter, Scott, Mary C., Ciston, Jim, Minor, Andrew M., Ophus, Colin
Format: Journal Article
Language:English
Published: New York, USA Cambridge University Press 01.08.2021
Oxford University Press
Microscopy Society of America (MSA)
Subjects:
4D-STEM
Application programming interface
Calibration
Computer applications
Data analysis
Datasets
Diffraction
Electromagnetic fields
Electron beams
Experiments
Geometry
INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
Material properties
open source
Open source software
Programming languages
Reproducibility
Scanning electron microscopy
Scanning transmission electron microscopy
Sensors
Software and Instrumentation
Source code
Spectroscopy
STEM
Transmission electron microscopy
4D-STEM
open source
diffraction
calibration
STEM
ISSN:1431-9276, 1435-8115, 1435-8115
Online Access:Get full text
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Summary: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.
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USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities Division
National Science Foundation (NSF)
USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division
US Department of the Navy, Office of Naval Research (ONR)
USDOE National Nuclear Security Administration (NNSA)
AC02-05CH11231; DMR 1548924; N00014-17-1-228; KC22ZH; 89233218CNA000001
ISSN:1431-9276
1435-8115
1435-8115
DOI:10.1017/S1431927621000477