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Title: Machine learning for quantum dynamics: deep learning of excitation energy transfer properties

Understanding the relationship between the structure of light-harvesting systems and their excitation energy transfer properties is of fundamental importance in many applications including the development of next generation photovoltaics.
Authors:
 [1] ;  [1] ; ORCiD logo [1]
  1. Department of Chemistry and Chemical Biology, Harvard University, Cambridge, USA
Publication Date:
Grant/Contract Number:
SC0001088
Type:
Published Article
Journal Name:
Chemical Science
Additional Journal Information:
Journal Volume: 8; Journal Issue: 12; Related Information: CHORUS Timestamp: 2017-11-20 13:32:36; Journal ID: ISSN 2041-6520
Publisher:
Royal Society of Chemistry (RSC)
Sponsoring Org:
USDOE
Country of Publication:
United Kingdom
Language:
English
OSTI Identifier:
1409485