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Uncovering In-Plane Domain Structures in Two-Dimensional Ferroelectric SnSe Using Machine-Learning Assisted 4D-STEM

Published online by Cambridge University Press:  22 July 2022

Chuqiao Shi
Affiliation:
Department of Materials Science and NanoEngineering, Rice University, Houston, TX,
Nannan Mao
Affiliation:
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA
Jing Kong
Affiliation:
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA
Yimo Han*
Affiliation:
Department of Materials Science and NanoEngineering, Rice University, Houston, TX,
*
*Corresponding author: yh76@rice.edu

Abstract

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Type
Developments of 4D-STEM Imaging - Enabling New Materials Applications
Copyright
Copyright © Microscopy Society of America 2022

References

Barraza, L. et al. Rev Mod Phys 93, 011001 (2021).10.1103/RevModPhys.93.011001CrossRefGoogle Scholar
Shi, C. et al. arXiv preprint arXiv:2111.06496, (2021).Google Scholar
Han, Y. et al. Nano Lett 18, 37463751 (2018).10.1021/acs.nanolett.8b00952CrossRefGoogle Scholar
The authors acknowledge funding from the Welch Foundation (C-2065-20210327).Google Scholar