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Automated Acquisition and Deep Learning of 2D Materials on the Million-Atom Scale

Published online by Cambridge University Press:  22 July 2022

Chia-Hao Lee ,
Abid Khan ,
Yue Zhang ,
M. Abir Hossain ,
Arend van der Zande ,
Bryan Clark  and
Pinshane Huang
Chia-Hao Lee
Affiliation:
Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Abid Khan
Affiliation:
Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Yue Zhang
Affiliation:
Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
M. Abir Hossain
Affiliation:
Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Arend van der Zande
Affiliation:
Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Bryan Clark
Affiliation:
Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Pinshane Huang*
Affiliation:
Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
*
*Corresponding author: [email protected]

Abstract

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Type
Artificial Intelligence, Instrument Automation, And High-dimensional Data Analytics for Microscopy and Microanalysis
Information
Microscopy and Microanalysis , Volume 28 , Supplement S1 , August 2022 , pp. 3062 - 3063
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Copyright
Copyright © Microscopy Society of America 2022

References

Lee, CH et al. , Nano Letters 20 (2020), p. 3369.CrossRefGoogle Scholar
Code available at: https://github.com/ClarkResearchGroup/stem-learningGoogle Scholar
This work is supported primarily through DOE BES under DE-SC0020190. Additional support from AFOSR FA9550-7-1-0213. This work was carried out in part in the Materials Research Laboratory at UIUC.Google Scholar