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Title: Machine learning and Design of Experiment for High Throughput Synthesis

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. Los Alamos National Laboratory
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE). Fuel Cell Technologies Program (EE-3F)
OSTI Identifier:
1557199
Report Number(s):
LA-UR-19-28160
DOE Contract Number:  
89233218CNA000001
Resource Type:
Conference
Resource Relation:
Conference: ElectroCat Mtg ; 2019-08-13 - 2019-08-14 ;
Country of Publication:
United States
Language:
English
Subject:
Material Science

Citation Formats

Ahmed, Towfiq, Karim, Mohammad Rezaul, and Holby, Edward F. Machine learning and Design of Experiment for High Throughput Synthesis. United States: N. p., 2019. Web.
Ahmed, Towfiq, Karim, Mohammad Rezaul, & Holby, Edward F. Machine learning and Design of Experiment for High Throughput Synthesis. United States.
Ahmed, Towfiq, Karim, Mohammad Rezaul, and Holby, Edward F. Tue . "Machine learning and Design of Experiment for High Throughput Synthesis". United States. https://www.osti.gov/servlets/purl/1557199.
@article{osti_1557199,
title = {Machine learning and Design of Experiment for High Throughput Synthesis},
author = {Ahmed, Towfiq and Karim, Mohammad Rezaul and Holby, Edward F.},
abstractNote = {},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {8}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

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