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Towards Machine Vision-enabled STEM EELS for High-throughput Quantification of Grain Boundary Electronic Structure

Published online by Cambridge University Press:  30 July 2020

Sai Muktevi ,
David Carreon  and
William Bowman
Sai Muktevi
Affiliation:
Dept. of Computer Engineering, University of California, Irvine, Irvine, California, United States
David Carreon
Affiliation:
Dept. of Computer Science, University of California, Irvine, Irvine, California, United States
William Bowman
Affiliation:
University of California, Irvine, Irvine, California, United States

Abstract

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Type
Advances in Modeling, Simulation, and Artificial Intelligence in Microscopy and Microanalysis for Physical and Biological Systems
Information
Microscopy and Microanalysis , Volume 26 , Supplement S2 , August 2020 , pp. 3098 - 3099
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Copyright
Copyright © Microscopy Society of America 2020

References

Bowman, WJ, Kelly, MN, Rohrer, GS, Hernandez, CA, Crozier, PA (2017) Enhanced ionic conductivity in electroceramics by nanoscale enrichment of grain boundaries with high solute concentration. Nanoscale, 9:17293–17302. https://doi.org/10.1039/C7NR06941CCrossRefGoogle ScholarPubMed
Bowman, WJ, Darbal, A, Crozier, PA (2019) Linking Macroscopic and Nanoscopic Ionic Conductivity: A Semiempirical Framework for Characterizing Grain Boundary Conductivity in Polycrystalline Ceramics. ACS Applied Materials & Interfaces, https://doi.org/10.1021/acsami.9b15933CrossRefGoogle Scholar
Uusimaeki, T, Wagner, T, Lipinski, H-G, Kaegi, R (2019) AutoEM: a software for automated acquisition and analysis of nanoparticles. Journal of Nanoparticle Research, 21(6):122. https://doi.org/10.1007/s11051-019-4555-9CrossRefGoogle Scholar