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 relia...
Expand abstract
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Authors
Funding
+ Engineering and Physical Sciences Research Council / Science and Technology Facilities Council
More from this funder
Funding agency for:
Wicker, J
Bibliographic Details
- Publisher:
- Royal Society of Chemistry Publisher's website
- Journal:
- CrystEngComm Journal website
- Volume:
- 17
- Pages:
- 1927-1934
- Publication date:
- 2014-11-01
- DOI:
- EISSN:
-
1466-8033
- ISSN:
-
1499-8033
Item Description
- Language:
- English
- Keywords:
- Subjects:
- UUID:
-
uuid:9a3c1eac-9487-4c5d-9327-7227e4ef979b
- Local pid:
- ora:9535
- Deposit date:
- 2014-12-05
Related Items
Terms of use
- Copyright holder:
- The Royal Society of Chemistry
- Copyright date:
- 2014
- 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.
Metrics
If you are the owner of this record, you can report an update to it here: Report update to this record