Journal article
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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Authors
Funding
+ Engineering and Physical Sciences Research Council / Science and Technology Facilities Council
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Funding agency for:
Wicker, J
Bibliographic Details
- 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
Item Description
- Keywords:
- Subjects:
- Pubs id:
-
pubs:491096
- UUID:
-
uuid:b3473de9-35b6-4e72-9804-e3e5dfc74f42
- Local pid:
- pubs:491096
- Source identifiers:
-
491096
- Deposit date:
- 2014-12-04
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Terms of use
- Copyright holder:
- The Royal Society of Chemistry
- Copyright date:
- 2015
- Notes:
- Copyright © The Royal Society of Chemistry 2014. The full-text of this article is not currently available in ORA, but you may be able to access the article via the publisher copy link on this record page.
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