Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-26T10:48:25.934Z Has data issue: false hasContentIssue false
  • English
  • Français

Bayesian Inference for Materials Physics from STEM Data: The Probability Distribution of Physical Parameters from Ferroelectric Domain Wall Observations

Published online by Cambridge University Press:  30 July 2021

Christopher Nelson ,
Rama Vasudevan ,
Xiaohang Zhang ,
Maxim Ziatdinov ,
Eugen Eliseev ,
Ichiro Takeuchi ,
Anna Morozovska  and
Sergei Kalinin
Christopher Nelson
Affiliation:
Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States
Rama Vasudevan
Affiliation:
Oak Ridge National Laboratory, United States
Xiaohang Zhang
Affiliation:
University of Maryland, Maryland, United States
Maxim Ziatdinov
Affiliation:
Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States
Eugen Eliseev
Affiliation:
Institute for Problems of Materials Science, National Academy of Sciences of Ukraine, United States
Ichiro Takeuchi
Affiliation:
University of Maryland, Maryland, United States
Anna Morozovska
Affiliation:
Institute of Physics, National Academy of Sciences of Ukraine, United States
Sergei Kalinin
Affiliation:
Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States

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
Quantum Materials Probed by High Spatial and Energy Resolution in Scanning/Transmission Electron Microscopy
Information
Microscopy and Microanalysis , Volume 27 , Supplement S1 , August 2021 , pp. 1212 - 1214
Check for updates
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

Jia, C. L. et al. , Nature Materials 6 (2007), p. 64.CrossRefGoogle Scholar
Liu, Y., et al. , J. Mater. Res. 32 (2017), p. 847.Google Scholar
This work was supported by the U.S Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division.Google Scholar