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Will it crystallise? Predicting crystallinity of molecular materials

Abstract:

Predicting and controlling crystallinity of molecular materials has applications in a crystal engineering context, as well as process control and formulation in the pharmaceutical industry. Here, we present a machine learning approach to this problem which uses a large input training set which is classified on a single measurable outcome: does a substance have a reasonable probability of forming good quality crystals. While the related problem of crystal structure prediction requires reliable...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1039/C4CE01912A

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Chemistry
Sub department:
Inorganic Chemistry
Oxford college:
Worcester College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Chemistry
Sub department:
Inorganic Chemistry
Role:
Author
Publisher:
Royal Society of Chemistry Publisher's website
Journal:
CrystEngComm Journal website
Volume:
17
Issue:
9
Pages:
1927-1934
Publication date:
2015-01-01
DOI:
EISSN:
1466-8033
ISSN:
1466-8033
Source identifiers:
491096
Keywords:
Subjects:
Pubs id:
pubs:491096
UUID:
uuid:b3473de9-35b6-4e72-9804-e3e5dfc74f42
Local pid:
pubs:491096
Deposit date:
2014-12-04

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