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Title: Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry

Abstract

Not provided.

Authors:
 [1];  [1]; ORCiD logo [2];  [3]; ORCiD logo [2]
  1. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States; Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
  2. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
  3. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States; Laboratorium für Physikalische Chemie, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
Publication Date:
Research Org.:
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1612842
DOE Contract Number:  
SC0018096
Resource Type:
Journal Article
Journal Name:
Industrial and Engineering Chemistry Research
Additional Journal Information:
Journal Volume: 57; Journal Issue: 42; Journal ID: ISSN 0888-5885
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
Engineering

Citation Formats

Nandy, Aditya, Duan, Chenru, Janet, Jon Paul, Gugler, Stefan, and Kulik, Heather J. Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry. United States: N. p., 2018. Web. doi:10.1021/acs.iecr.8b04015.
Nandy, Aditya, Duan, Chenru, Janet, Jon Paul, Gugler, Stefan, & Kulik, Heather J. Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry. United States. doi:10.1021/acs.iecr.8b04015.
Nandy, Aditya, Duan, Chenru, Janet, Jon Paul, Gugler, Stefan, and Kulik, Heather J. Mon . "Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry". United States. doi:10.1021/acs.iecr.8b04015.
@article{osti_1612842,
title = {Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry},
author = {Nandy, Aditya and Duan, Chenru and Janet, Jon Paul and Gugler, Stefan and Kulik, Heather J.},
abstractNote = {Not provided.},
doi = {10.1021/acs.iecr.8b04015},
journal = {Industrial and Engineering Chemistry Research},
issn = {0888-5885},
number = 42,
volume = 57,
place = {United States},
year = {2018},
month = {9}
}