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High-Throughput Intelligent Analysis of High and Low-Loss EELS

Published online by Cambridge University Press:  30 July 2021

Chaitanya Gadre ,
Xingxu Yan ,
Christopher Addiego  and
Xiaoqing Pan
Chaitanya Gadre
Affiliation:
Department of Physics and Astronomy, University of California, Irvine, CA92697, Irvine, California, United States
Xingxu Yan
Affiliation:
Department of Materials Science and Engineering, University of California - Irvine, Irvine, California, United States
Christopher Addiego
Affiliation:
University of California - Irvine, IRVINE, California, United States
Xiaoqing Pan
Affiliation:
Department of Physics and Astronomy, University of California, Irvine, CA92697, Irvine, California, United States

Abstract

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Type
Advanced Imaging and Spectroscopy for Nanoscale Materials Characterization
Information
Microscopy and Microanalysis , Volume 27 , Supplement S1 , August 2021 , pp. 626 - 628
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

Haberfehlner, Georg, et al. "Benefits of direct electron detection and PCA for EELS investigation of organic photovoltaics materials." Micron 140 (2021): 102981.CrossRefGoogle ScholarPubMed
Cueva, Paul, et al. "Data processing for atomic resolution electron energy loss spectroscopy." Microscopy and Microanalysis 18.4 (2012): 667-675.CrossRefGoogle ScholarPubMed
Rocklin, Matthew. "Dask: Parallel computation with blocked algorithms and task scheduling." Proceedings of the 14th python in science conference. Vol. 126. Austin, TX: SciPy, 2015.Google Scholar
This work was supported by the Department of Energy (DOE) under Grant DE-SC0014430. The authors acknowledge the use of facilities and instrumentation at the UC Irvine Materials Research Institute (IMRI) supported in part by the NSF MRSEC program (DMR-2011967).Google Scholar