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

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.:
OSTI Identifier:
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
Wiley Blackwell (John Wiley & Sons)
Country of Publication:

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.
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.
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.
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}

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