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In situ Transmission Electron Microscopy for Data-driven Modeling of Nanoparticle Evolution

Published online by Cambridge University Press:  30 July 2021

James Horwath
Affiliation:
University of Pennsylvania, United States
Peter Voorhees
Affiliation:
Northwestern Universtiy, United States
Eric Stach
Affiliation:
University of Pennsylvania, Philadelphia, Pennsylvania, United States

Abstract

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Type
New Frontiers in In-Situ Electron Microscopy in Liquids and Gases (L&G EM FIG Sponsored)
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

Horwath, , Zakharov, D., Megret, R., Stach, E., “Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images”, npj Computational Materials 6 108 (2020).CrossRefGoogle Scholar
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P.H and E.A.S acknowledge support through the National Science Foundation, Division of Materials Research, Metals and Metallic Nanostructures Program under Grant 1809398. This research used resources of the Center for Functional Nanomaterials, which is a U.S. DOE Office of Science Facility, at Brookhaven National Laboratory under Contract No. DE-SC00127044Google Scholar