Prediction of mefenamic acid crystal shape by random forest classification
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Nakapraves, Siya and Warzecha, Monika and Mustoe, Chantal and Florence, Alastair J. (2022) Prediction of mefenamic acid crystal shape by random forest classification. In: CMAC Annual Open Day 2022, 2022-05-16 - 2022-05-18.
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Abstract
Research problem: Crystal shape is one of the key attributes affecting the bulk particle properties of a crystalline material as well as its downstream manufacturability1. However, the prediction of experimental crystal shapes remains very challenging. This research aims to explore the potential application of machine learning algorithms to solve this problem.
ORCID iDs
Nakapraves, Siya, Warzecha, Monika ORCID: https://orcid.org/0000-0001-6166-1089, Mustoe, Chantal and Florence, Alastair J. ORCID: https://orcid.org/0000-0002-9706-8364;Persistent Identifier
https://doi.org/10.17868/strath.00081754-
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Item type: Conference or Workshop Item(Poster) ID code: 81754 Dates: DateEvent16 May 2022PublishedSubjects: Medicine > Therapeutics. Pharmacology Department: Faculty of Science > Strathclyde Institute of Pharmacy and Biomedical Sciences
Strategic Research Themes > Advanced Manufacturing and Materials
Technology and Innovation Centre > Continuous Manufacturing and Crystallisation (CMAC)Depositing user: Pure Administrator Date deposited: 08 Aug 2022 10:41 Last modified: 11 Nov 2024 17:06 URI: https://strathprints.strath.ac.uk/id/eprint/81754
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