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Finding Features from Microscopes to Simulations Via Ensemble Learning and Atomic Manipulation

Published online by Cambridge University Press:  22 July 2022

Ayana Ghosh
Affiliation:
Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Kevin M. Roccapriore
Affiliation:
Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Bobby Sumpter
Affiliation:
Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Ondrej Dyck
Affiliation:
Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Maxim Ziatdinov
Affiliation:
Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Sergei V. Kalinin
Affiliation:
Department of Materials Science and Engineering, University of Tennessee, Knoxville, TN, USA

Abstract

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Type
Artificial Intelligence, Instrument Automation, And High-dimensional Data Analytics for Microscopy and Microanalysis
Copyright
Copyright © Microscopy Society of America 2022

References

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This effort (machine learning) is based upon work supported by the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences Data, Artificial Intelligence Nanoscale Science Research (NSRC AI) Centers program (A.G., BGS, S.V.K.). The STEM experiments were supported by the DOE, Office of Science, Basic Energy Sciences (BES), Materials Sciences and Engineering Division (O.D.) and by the DOE, Office of Science, Basic Energy Sciences (BES), Materials Sciences and Engineering Division (K.M.R., S.V.K.). Work was performed and partially supported (M.Z) at Oak Ridge National Laboratory's Center for Nanophase Materials Sciences (CNMS), a DOE Office of Science User Facility. This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE).Google Scholar