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Automated Experiment in SPM: Bayesian Optimization for efficient searching of parameter space to maximize functional response

Published online by Cambridge University Press:  30 July 2021

Rama Vasudevan ,
Kyle Kelley ,
Jacob Hinkle ,
Hiroshi Funakubo ,
Sergei Kalinin ,
Stephen Jesse  and
Maxim Ziatdinov
Rama Vasudevan
Affiliation:
Oak Ridge National Laboratory, United States
Kyle Kelley
Affiliation:
Oak Ridge National Laboratory, United States
Jacob Hinkle
Affiliation:
Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States
Hiroshi Funakubo
Affiliation:
Tokyo Institute of Technology, United States
Sergei Kalinin
Affiliation:
Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States
Stephen Jesse
Affiliation:
Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, United States
Maxim Ziatdinov
Affiliation:
Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States

Abstract

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Type
Full System and Workflow Automation for Enabling Big Data and Machine Learning in Electron Microscopy
Information
Microscopy and Microanalysis , Volume 27 , Supplement S1 , August 2021 , pp. 470 - 471
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

Jesse, S. et al. Ann. Rev. Phys. Chem. 65, 519 (2014).CrossRefGoogle Scholar
Shahriari, B. et al. Proc. IEEE 104, 148 (2015).Google Scholar
This research was conducted at and supported by the Center for Nanophase Materials Sciences, which is a US DOE Office of Science User Facility.Google Scholar