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

Abstract

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.

Document Details

Document Type
Pub Defense Publication
Publication Date
May 21, 2021
Source ID
10.1017/s1431927621000477

Entities

People

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

Tags

Fields of Study

  • Physics

Readers

  • Computer Vision.
  • Database Systems and Applications
  • Nanoscale Plasmonic Nanotechnology

Technology Areas

  • Directed Energy
  • Microelectronics