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Deep Learning Enabled Atom-by-Atom Analysis of 2D materials on the Million-Atom Scale

Published online by Cambridge University Press:  30 July 2021

Chia-Hao Lee ,
Abid Khan ,
Di Luo ,
Chuqiao Shi ,
Yue Zhang ,
M. Abir Hossain ,
Arend van der Zande ,
Bryan Clark  and
Pinshane Huang
Chia-Hao Lee
Affiliation:
University of Illinois at Urbana-Champaign, United States
Abid Khan
Affiliation:
University of Illinois at Urbana-Champaign, United States
Di Luo
Affiliation:
University of Illinois at Urbana-Champaign, United States
Chuqiao Shi
Affiliation:
Rice University, United States
Yue Zhang
Affiliation:
University of Illinois at Urbana-Champaign, United States
M. Abir Hossain
Affiliation:
University of Illinois at Urbana-Champaign, United States
Arend van der Zande
Affiliation:
University of Illinois at Urbana-Champaign, United States
Bryan Clark
Affiliation:
University of Illinois at Urbana-Champaign, United States
Pinshane Huang
Affiliation:
University of Illinois at Urbana-Champaign, United States

Abstract

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Type
Emerging Low-Dimensional Nanomaterials and Their Heterostructures
Information
Microscopy and Microanalysis , Volume 27 , Supplement S1 , August 2021 , pp. 904 - 906
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

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Lin, R. et al. , arXiv: 2012.09093 (2020)Google Scholar
Lee, C.-H. et al. , Nano Lett. 20.5 (2020), p. 3369-3377CrossRefGoogle Scholar
Qian, Q. et al. , Nanoscale 12.3 (2020), p. 2047-2056CrossRefGoogle Scholar
This work was supported by the DOE award number DE-SC0020190 and was carried out in part in the Materials Research Laboratory at UIUC.Google Scholar