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Prediction of ELNES and Quantification of Structural Properties Using Artificial Neural Network

Published online by Cambridge University Press:  30 July 2020

Shin Kiyohara ,
Masashi Tsubaki  and
Teruyasu Mizoguchi
Shin Kiyohara
Affiliation:
Tokyo Institute of Technology, Yokohama, Kanagawa, Japan
Masashi Tsubaki
Affiliation:
National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo, Japan
Teruyasu Mizoguchi
Affiliation:
The University of Tokyo, Meguro-ku, Tokyo, Japan

Abstract

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Type
Advances in Modeling, Simulation, and Artificial Intelligence in Microscopy and Microanalysis for Physical and Biological Systems
Information
Microscopy and Microanalysis , Volume 26 , Supplement S2 , August 2020 , pp. 2100 - 2101
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Copyright
Copyright © Microscopy Society of America 2020

References

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Kiyohara, S. et al. , submitted.Google Scholar
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Mizoguchi, T. and Kiyohara, S., Microscopy, (2020), p. 1.Google Scholar
Kiyohara, S. and Mizoguchi, T., in preparation.Google Scholar
Jain, A. et al. , APL Materials, 1 (2013), p. 011002.10.1063/1.4812323CrossRefGoogle Scholar
The authors acknowledge funding from JST-PRESTO (JPM-JPR16NB 16814592), MEXT, under grantnos. 18J11573, 17H06094, 19H00818 and 19H05787 as well as the special fund of the Institute of Industrial Science, University of Tokyo (Tenkai5504850104)Google Scholar