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Title: Property Prediction of Organic Donor Molecules for Photovoltaic Applications Using Extremely Randomized Trees

Authors:
ORCiD logo [1];  [2];  [1];  [1];  [1]
  1. Department of Electrical and Computer Engineering Northwestern University Evanston IL, 60208 USA
  2. Institute for Public Health and Medicine, Feinberg School of Medicine, Center for Health Information Partnerships Northwestern University Chicago IL, 60611 USA
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1560891
Grant/Contract Number:  
SC0014330; SC0019358
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Molecular Informatics
Additional Journal Information:
Journal Name: Molecular Informatics Journal Volume: 38 Journal Issue: 11-12; Journal ID: ISSN 1868-1743
Publisher:
Wiley Blackwell (John Wiley & Sons)
Country of Publication:
Germany
Language:
English

Citation Formats

Paul, Arindam, Furmanchuk, Alona, Liao, Wei‐keng, Choudhary, Alok, and Agrawal, Ankit. Property Prediction of Organic Donor Molecules for Photovoltaic Applications Using Extremely Randomized Trees. Germany: N. p., 2019. Web. https://doi.org/10.1002/minf.201900038.
Paul, Arindam, Furmanchuk, Alona, Liao, Wei‐keng, Choudhary, Alok, & Agrawal, Ankit. Property Prediction of Organic Donor Molecules for Photovoltaic Applications Using Extremely Randomized Trees. Germany. https://doi.org/10.1002/minf.201900038
Paul, Arindam, Furmanchuk, Alona, Liao, Wei‐keng, Choudhary, Alok, and Agrawal, Ankit. Tue . "Property Prediction of Organic Donor Molecules for Photovoltaic Applications Using Extremely Randomized Trees". Germany. https://doi.org/10.1002/minf.201900038.
@article{osti_1560891,
title = {Property Prediction of Organic Donor Molecules for Photovoltaic Applications Using Extremely Randomized Trees},
author = {Paul, Arindam and Furmanchuk, Alona and Liao, Wei‐keng and Choudhary, Alok and Agrawal, Ankit},
abstractNote = {},
doi = {10.1002/minf.201900038},
journal = {Molecular Informatics},
number = 11-12,
volume = 38,
place = {Germany},
year = {2019},
month = {9}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1002/minf.201900038

Citation Metrics:
Cited by: 5 works
Citation information provided by
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