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Compressed STEM Simulations

Published online by Cambridge University Press:  22 July 2022

A. W. Robinson ,
D. Nicholls ,
J. Wells ,
A. Moshtaghpour ,
A. I. Kirkland  and
N. D. Browning
A. W. Robinson*
Affiliation:
Mechanical, Materials, & Aerospace Engineering, University of Liverpool, Liverpool, U.K
D. Nicholls
Affiliation:
Mechanical, Materials, & Aerospace Engineering, University of Liverpool, Liverpool, U.K
J. Wells
Affiliation:
Distributed Algorithms CDT, University of Liverpool, Liverpool, U.K
A. Moshtaghpour
Affiliation:
Mechanical, Materials, & Aerospace Engineering, University of Liverpool, Liverpool, U.K Rosalind Franklin Institute, Harwell Science & Innovation Campus, Didcot, U. K
A. I. Kirkland
Affiliation:
Rosalind Franklin Institute, Harwell Science & Innovation Campus, Didcot, U. K Department of Materials, University of Oxford, Oxford, U. K
N. D. Browning
Affiliation:
Mechanical, Materials, & Aerospace Engineering, University of Liverpool, Liverpool, U.K 5. Physical & Computational Science, Pacific Northwest National Lab, Richland, WA, USA Sivananthan Laboratories, Bolingbrook, IL, USA
*
*Corresponding author: [email protected]

Abstract

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Type
Artificial Intelligence, Instrument Automation, And High-dimensional Data Analytics for Microscopy and Microanalysis
Information
Microscopy and Microanalysis , Volume 28 , Supplement S1 , August 2022 , pp. 3116 - 3117
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Copyright
Copyright © Microscopy Society of America 2022

References

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This work was performed in the Albert Crewe Centre (ACC) for Electron Microscopy, a shared research facility (SRF) fully supported by the University of Liverpool. This work was also funded by the EPSRC Centre for Doctoral Training in Distributed Algorithms (EP/S023445/1) and Sivananthan Labs. The authors would also like to recognise the efforts of Ivan Lobato et al. for their development of MULTEM, without which this research would have not been possible.Google Scholar