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Will they co-crystallize?

Abstract:
LawrencebA data-driven approach to predicting co-crystal formation reduces the number of experiments required to successfully produce new co-crystals. A machine learning algorithm trained on an in-house set of co-crystallization experiments results in a 2.6-fold enrichment of successful co-crystal formation in a ranked list of co-formers, using an unseen set of paracetamol test experiments.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1039/C7CE00587C

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Institution:
University of Oxford
Division:
MPLS
Department:
Chemistry
Sub department:
Inorganic Chemistry
Role:
Author
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University College Cork 2013 Research Fund More from this funder
Publisher:
Royal Society of Chemistry Publisher's website
Journal:
CrystEngComm Journal website
Volume:
19
Pages:
5336-5340
Publication date:
2017-07-01
Acceptance date:
2017-07-05
DOI:
Source identifiers:
703047
Pubs id:
pubs:703047
UUID:
uuid:24e0e4a1-4d27-4878-a2cb-ea511bacc185
Local pid:
pubs:703047
Deposit date:
2017-07-05

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