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Updated: Feb 15, 2026

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management
Published on: June 23, 2023
Managing dose-, damage- and data-rates in multi-frame spectrum-imaging
Lewys Jones1,2,3, Aakash Varambhia3, Richard Beanland4
1School of Physics, Trinity College Dublin, Dublin 2, Ireland.
Abstract:
As an instrument, the scanning transmission electron microscope is unique in being able to simultaneously explore both local structural and chemical variations in materials at the atomic scale. This is made possible as both types of data are acquired serially, originating simultaneously from sample interactions with a sharply focused electron probe. Unfortunately, such scanned data can be distorted by environmental factors, though recently fast-scanned multi-frame imaging approaches have been shown to mitigate these effects. Here, we demonstrate the same approach but optimized for spectroscopic data; we offer some perspectives on the new potential of multi-frame spectrum-imaging (MFSI) and show how dose-sharing approaches can reduce sample damage, improve crystallographic fidelity, increase data signal-to-noise, or maximize usable field of view. Further, we discuss the potential issue of excessive data-rates in MFSI, and demonstrate a file-compression approach to significantly reduce data storage and transmission burdens.
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