https://doi.org/10.1051/epjap/2025002
Original Article
Edge-Detected 4DSTEM - effective low-dose diffraction data acquisition method for nanopowder samples in an SEM instrument
1
EMAT, University of Antwerp, Groenenborgerlaan 171, Antwerp 2020, Belgium
2
Nanolab center of excellence, University of Antwerp, Groenenborgerlaan 171, Antwerp 2020, Belgium
* e-mail: nikita.denisov@uantwerpen.be
Received:
8
November
2024
Accepted:
22
January
2025
Published online: 18 February 2025
The appearance of direct electron detectors marked a new era for electron diffraction. Their high sensitivity and low noise opens the possibility to extend electron diffraction from transmission electron microscopes (TEM) to lower energies such as those found in commercial scanning electron microscopes (SEM). The lower acceleration voltage does however put constraints on the maximum sample thickness and it is a-priori unclear how useful such a diffraction setup could be. On the other hand, nanoparticles are increasingly appearing in consumer products and could form an attractive class of naturally thin samples to investigate with this setup. In this work we present such a diffraction setup and discuss methods to effectively collect and process diffraction data from dispersed crystalline nanoparticles in a commercial SEM instrument. We discuss ways to drastically reduce acquisition time while at the same time lowering beam damage and contamination issues as well as providing significant data reduction leading to fast processing and modest data storage needs. These approaches are also amenable to TEM and could be especially useful in the case of beam-sensitive objects.
Key words: 4DSTEM / edge detection / LEND / electron diffraction / nanopowder / SEM
Publisher note: This article was originally published without open access due to a production error. On 27 February 2025, the copyright of the article has been changed to @ N. Denisov et al., Published by EDP Sciences, and the article is forthwith distributed under the Terms of the Creative Commons Attribution License 4.0.
© N. Denisov et al., Published by EDP Sciences 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
