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Title: Making machine learning a useful tool in the accelerated discovery of transition metal complexes

Authors:
ORCiD logo [1]
  1. Department of Chemical EngineeringMassachusetts Institute of Technology Cambridge Massachusetts
Publication Date:
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1546100
Grant/Contract Number:  
DE‐SC0018096
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Wiley Interdisciplinary Reviews: Computational Molecular Science
Additional Journal Information:
Journal Name: Wiley Interdisciplinary Reviews: Computational Molecular Science; Journal ID: ISSN 1759-0876
Publisher:
Wiley Blackwell (John Wiley & Sons)
Country of Publication:
United States
Language:
English

Citation Formats

Kulik, Heather J. Making machine learning a useful tool in the accelerated discovery of transition metal complexes. United States: N. p., 2019. Web. doi:10.1002/wcms.1439.
Kulik, Heather J. Making machine learning a useful tool in the accelerated discovery of transition metal complexes. United States. doi:10.1002/wcms.1439.
Kulik, Heather J. Fri . "Making machine learning a useful tool in the accelerated discovery of transition metal complexes". United States. doi:10.1002/wcms.1439.
@article{osti_1546100,
title = {Making machine learning a useful tool in the accelerated discovery of transition metal complexes},
author = {Kulik, Heather J.},
abstractNote = {},
doi = {10.1002/wcms.1439},
journal = {Wiley Interdisciplinary Reviews: Computational Molecular Science},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {8}
}

Journal Article:
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Works referenced in this record:

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