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Merging Deep Learning, Chemistry, and Diffraction for High-Throughput Material Structure Prediction

Published online by Cambridge University Press:  05 August 2019

Matthew L. Gong ,
Brandon D. Miller ,
Ray R. Unocic ,
Khallid Hattar ,
Bryan Reed ,
Dan Masiel ,
Tolga Tasdizen  and
Jeffery A. Aguiar
Matthew L. Gong
Affiliation:
Idaho National Laboratory, Nuclear Materials Department, Idaho Falls, IdahoUSA. University of Utah, Scientific Computing Imaging Institute, Department of Electrical and Computer Engineering, Salt Lake City, UtahUSA.
Brandon D. Miller
Affiliation:
Idaho National Laboratory, Nuclear Materials Department, Idaho Falls, IdahoUSA.
Ray R. Unocic
Affiliation:
Oak Ridge National Laboratory, Center for Nanophase Materials Science, Oak Ridge, TennesseeUSA.
Khallid Hattar
Affiliation:
Sandia National Laboratories, Center for Integrated Nanotechnologies Albuquerque, New MexicoUSA.
Bryan Reed
Affiliation:
Integrated Dynamic Electron Solutions, Pleasanton, CaliforniaUSA.
Dan Masiel
Affiliation:
Integrated Dynamic Electron Solutions, Pleasanton, CaliforniaUSA.
Tolga Tasdizen
Affiliation:
University of Utah, Scientific Computing Imaging Institute, Department of Electrical and Computer Engineering, Salt Lake City, UtahUSA.
Jeffery A. Aguiar
Affiliation:
Idaho National Laboratory, Nuclear Materials Department, Idaho Falls, IdahoUSA.

Abstract

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Type
Data Acquisition Schemes, Machine Learning Algorithms, and Open Source Software Development for Electron Microscopy
Information
Microscopy and Microanalysis , Volume 25 , Supplement S2 , August 2019 , pp. 168 - 169
Copyright
Copyright © Microscopy Society of America 2019 

References

[1]Vasudevan, R.K. et al. , ACS Nano. 8 (2014). doi:10.1021/nn504730n.Google Scholar
[2]Vasudevan, R.K. et al. , Appl Phys Lett. 106 (2015). doi:10.1063/1.4914016.Google Scholar
[3]Dongarra, J et al. , Int J High Perform Comput Appl. 25 (2011). doi:10.1177/1094342010391989.Google Scholar
[4]Work supported through the INL Laboratory Directed Research& Development (LDRD) Program under DOE Idaho Operations Office Contract DE-AC07-05ID14517. This work was performed, in part, at the Center for Integrated Nanotechnologies, an Office of Science User Facility operated for the U.S. Department of Energy (DOE) Office of Science. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. DOE's National Nuclear Security Administration under contract DE-NA-0003525. The views expressed in the article do not necessarily represent the views of the U.S. DOE or the United States Government. In part, this research was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility.Google Scholar