Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-23T04:18:20.037Z Has data issue: false hasContentIssue false
  • English
  • Français

Doing More with Less: Artificial Intelligence Guided Analytics for Electron Microscopy Applications

Published online by Cambridge University Press:  22 July 2022

Sarah Akers ,
Marjolein Oostrom ,
Christina Doty ,
Matthew Olstza ,
Derek Hopkins ,
Kevin Fiedler  and
Steven R. Spurgeon
Sarah Akers
Affiliation:
National Security Directorate, Pacific Northwest National Laboratory, Richland, WA, United States
Marjolein Oostrom
Affiliation:
National Security Directorate, Pacific Northwest National Laboratory, Richland, WA, United States
Christina Doty
Affiliation:
National Security Directorate, Pacific Northwest National Laboratory, Richland, WA, United States
Matthew Olstza
Affiliation:
Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA, United States
Derek Hopkins
Affiliation:
Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, United States
Kevin Fiedler
Affiliation:
Mathematics and Statistics Department, Washington State University Tri-Cities, Richland, WA, United States
Steven R. Spurgeon*
Affiliation:
Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA, United States Department of Physics, University of Washington, Seattle, WA, United States
*
*Corresponding author: [email protected]

Abstract

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
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. 2988 - 2989
Check for updates
Copyright
Copyright © Microscopy Society of America 2022

References

Ede, JM, Mach. Learn.: Sci. Technol. 2 (2021), p. 011004.Google Scholar
Doty, C et al. , Computational Materials Science 203 (2022), p. 111121.CrossRefGoogle Scholar
Olszta, M et al. , Microscopy and Microanalysis 27(S1) (2021), p. 2986.CrossRefGoogle Scholar
Akers, S et al. , npj Computational Materials 7(1) (2021), p.1.CrossRefGoogle Scholar
This research was supported by the Energy Storage Materials Initiative/Investment (ESMI), under the Laboratory Directed Research and Development (LDRD) Program at Pacific Northwest National Laboratory (PNNL). Some code development was supported by the Chemical Dynamics Initiative/Investment (CDi), under the LDRD Program at PNNL. PNNL is a multi-program national laboratory operated for the U.S. Department of Energy (DOE) by Battelle Memorial Institute under Contract No. DE-AC05-76RL01830.Google Scholar