Nicholls, Daniel 
ORCID: 0000-0003-1677-701X, Wells, Jack, Stevens, Andrew, Zheng, Yalin ORCID: 0000-0002-7873-0922, Castagna, Jony and Browning, Nigel D ORCID: 0000-0003-0491-251X
(2022)
Sub-Sampled Imaging for STEM: Maximising Image Speed, Resolution and Precision Through Reconstruction Parameter Refinement.
Ultramicroscopy, 233.
p. 113451.
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6_updated_ULTRAM-D-21-00143_R1.pdf - Author Accepted Manuscript Download (4MB) | Preview |
Abstract
Sub-sampling during image acquisition in scanning transmission electron microscopy (STEM) has been shown to provide a means to increase the overall speed of acquisition while at the same time providing an efficient means to control the dose, dose rate and dose overlap delivered to the sample. In this paper, we discuss specifically the parameters used to reconstruct sub-sampled images and highlight their effect on inpainting using the beta-process factor analysis (BPFA) methodology. The selection of the main control parameters can have a significant effect on the resolution, precision and sensitivity of the final inpainted images, and here we demonstrate a method by which these parameters can be optimised for any image in STEM. As part of this work, we also provide a link to open source code and a tutorial on its use, whereby these parameters can be tested for any datasets. When coupled with the hardware necessary to rapidly sub-sample images in STEM, this approach can have significant implications for imaging beam sensitive materials and dynamic processes.
| Item Type: | Article |
|---|---|
| Divisions: | Faculty of Science and Engineering > School of Engineering |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 13 Jan 2022 11:49 |
| Last Modified: | 18 Jan 2023 21:16 |
| DOI: | 10.1016/j.ultramic.2021.113451 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3146464 |
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