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Machine Learning Assisted Pattern Matching: Insight into Oxide Electronic Device Performance by Phase Determination in 4D-STEM Datasets

Published online by Cambridge University Press:  30 July 2020

Alexander Zintler ,
Robert Eilhardt ,
Shuai Wang ,
Matus Krajnak ,
Patrick Schramowski ,
Wolfgang Stammer ,
Stefan Petzold ,
Nico Kaiser ,
Kristian Kersting  and
Lambert Alff
...Show all authors
Alexander Zintler
Affiliation:
Technical University of Darmstadt, Darmstadt, Hessen, Germany
Robert Eilhardt
Affiliation:
Technical University of Darmstadt, Darmstadt, Hessen, Germany
Shuai Wang
Affiliation:
Technical University of Darmstadt, Darmstadt, Hessen, Germany
Matus Krajnak
Affiliation:
Quanum Detectors Ltd., Harwell Oxford, England, United Kingdom
Patrick Schramowski
Affiliation:
Technical University of Darmstadt, Darmstadt, Hessen, Germany
Wolfgang Stammer
Affiliation:
Technical University of Darmstadt, Darmstadt, Hessen, Germany
Stefan Petzold
Affiliation:
Technical University of Darmstadt, Darmstadt, Hessen, Germany
Nico Kaiser
Affiliation:
Technical University of Darmstadt, Darmstadt, Hessen, Germany
Kristian Kersting
Affiliation:
Technical University of Darmstadt, Darmstadt, Hessen, Germany
Lambert Alff
Affiliation:
Technical University of Darmstadt, Darmstadt, Hessen, Germany
Leopoldo Molina-Luna
Affiliation:
Technical University of Darmstadt, Darmstadt, Hessen, Germany

Abstract

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Type
Four-dimensional Scanning Transmission Electron Microscopy (4D-STEM): New Experiments and Data Analyses for Determining Materials Functionality and Biological Structures
Information
Microscopy and Microanalysis , Volume 26 , Supplement S2 , August 2020 , pp. 1908 - 1909
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Copyright
Copyright © Microscopy Society of America 2020

References

Petzold, S, Zintler, A, et al. ., Adv. Electron. Mater. 10 (2019) 10.1002/aelm.201900484Google Scholar
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Ophus, C, Microsc. Microanal. 3 (2019) 10.1017/S1431927619000497Google Scholar
Johnstone, Duncan N., Crout, Phillip, et al. ., (2020) 10.5281/zenodo.3667613Google Scholar
Borodinov, N., Neumayer, , et al. npj Comput Mater 5, 25 (2019). 10.1038/s41524-019-0148-5Google Scholar
The authors acknowledge financial support from the Deutsche Forschungsgemeinschaft (DFG) under research grant MO 3010/3-1 and the European Research Council (ERC) “Horizon 2020” Program under Grant No. 805359-FOXON.Google Scholar