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DeepSTEM: Deep-Learning-Based Object Function Reconstruction for In Situ STEM

Published online by Cambridge University Press:  22 July 2022

Yeongdong Lee
Affiliation:
Center for Multidimensional Carbon Materials, Institute for Basic Science (IBS), Ulsan, Republic of Korea
Jongyeong Lee
Affiliation:
Center for Multidimensional Carbon Materials, Institute for Basic Science (IBS), Ulsan, Republic of Korea
Handolsam Chung
Affiliation:
Center for Multidimensional Carbon Materials, Institute for Basic Science (IBS), Ulsan, Republic of Korea Department of Materials Science and Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
Jaemin Kim
Affiliation:
Center for Multidimensional Carbon Materials, Institute for Basic Science (IBS), Ulsan, Republic of Korea Department of Materials Science and Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
Zonghoon Lee*
Affiliation:
Center for Multidimensional Carbon Materials, Institute for Basic Science (IBS), Ulsan, Republic of Korea Department of Materials Science and Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
*
*Corresponding author: [email protected]

Abstract

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Type
Insights into Phase Transitions in Functional Materials by In Situ/Operando TEM: Experiment Meets Theory
Copyright
Copyright © Microscopy Society of America 2022

References

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This work was supported by the Institute for Basic Science (IBS-R019-D1).Google Scholar