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65 results

Page 1 of 4

  • Structured Illumination Electron Ptychography at the Atomic Scale

  • Philipp Pelz, Hannah DeVyldere, Peter Ercius, Mary Scott
  • Journal:
    Microscopy and Microanalysis / Volume 28 / Issue S1 / August 2022
    Published online by Cambridge University Press:
    22 July 2022, pp. 388-390
    Print publication:
    August 2022
    • Article
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  • py4DSTEM: A Software Package for Four-Dimensional Scanning Transmission Electron Microscopy Data Analysis

  • Benjamin H. Savitzky, Steven E. Zeltmann, Lauren A. Hughes, Hamish G. Brown, Shiteng Zhao, Philipp M. Pelz, Thomas C. Pekin, Edward S. Barnard, Jennifer Donohue, Luis Rangel DaCosta, Ellis Kennedy, Yujun Xie, Matthew T. Janish, Matthew M. Schneider, Patrick Herring, Chirranjeevi Gopal, Abraham Anapolsky, Rohan Dhall, Karen C. Bustillo, Peter Ercius, Mary C. Scott, Jim Ciston, Andrew M. Minor, Colin Ophus
  • Journal:
    Microscopy and Microanalysis / Volume 27 / Issue 4 / August 2021
    Published online by Cambridge University Press:
    21 May 2021, pp. 712-743
    Print publication:
    August 2021
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      • Open access
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  • 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.

  • Chemical and bonding analysis of liquids using liquid cell electron microscopy

  • Peter Ercius, Jordan A. Hachtel, Robert F. Klie
  • Journal:
    MRS Bulletin / Volume 45 / Issue 9 / September 2020
    Published online by Cambridge University Press:
    10 September 2020, pp. 761-768
    Print publication:
    September 2020

  • Liquid cell transmission electron microscopy (TEM) has become an essential tool for studying the structure and properties of both hard and soft condensed-matter samples, as well as liquids themselves. Liquid cell sample holders, often consisting of two thin window layers separating the liquid sample from the high vacuum of the microscope column, have been designed to control in situ conditions, including temperature, voltage/current, or flow through the window region. While high-resolution and time-resolved TEM imaging probes the structure, shape, and dynamics of liquid cell samples, information about the chemical composition and spatially resolved bonding is often difficult to obtain due to the liquid thickness, the window layers, the holder configuration, or beam-induced radiolysis. In this article, we review different approaches to quantitative liquid cell electron microscopy, including recent developments to perform energy-dispersive x-ray and electron energy-loss spectroscopy experiments on samples in a liquid environment or the liquid itself. We also cover graphene liquid cells and other ultrathin window layer holders.

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