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Utilising Unsupervised Machine Learning on Correlated EDS and 4DSTEM Data for Investigating the Structural Ordering Within Co2FeSi Thin Films

Published online by Cambridge University Press:  22 July 2022

Ercin Duran ,
Irene Azaceta ,
Adam Kerrigan ,
Vlado Lazarov  and
Alexander Eggeman
Ercin Duran
Affiliation:
Department of Materials, University of Manchester, Manchester, United Kingdom
Irene Azaceta
Affiliation:
Department of Physics, University of York, York, United Kingdom
Adam Kerrigan
Affiliation:
Department of Physics, University of York, York, United Kingdom
Vlado Lazarov
Affiliation:
Department of Physics, University of York, York, United Kingdom
Alexander Eggeman*
Affiliation:
Department of Materials, University of Manchester, Manchester, United Kingdom
*
*Corresponding author: alexander.eggeman@manchester.ac.uk

Abstract

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Type
Developments of 4D-STEM Imaging - Enabling New Materials Applications
Information
Microscopy and Microanalysis , Volume 28 , Supplement S1 , August 2022 , pp. 418 - 419
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Copyright
Copyright © Microscopy Society of America 2022

References

Gercsi, Z. et al. , Appl. Phys. Lett. 89, 082512 (2006), doi: 10.1063/1.2338025CrossRefGoogle Scholar
Zhu, W. et al. , J. Magn. Magn. Mater. 479, 179–184 (2019), doi: 10.1016/j.jmmm.2019.01.087CrossRefGoogle Scholar
Martineau, , et al. , Adv. Struct. Chem. Imaging 5, 3 (2019), doi: 10.1186/s40679-019-0063-3CrossRefGoogle Scholar
The authors gratefully acknowledge funding from the Royal Society and the Ministry of National Education of Turkey.Google Scholar