Machine Learning Prediction of Glass and Melting Transitions in High-Performance Polymers: A case study of poly(aryl ether ketones) and conjugated polymers

Brierley-Croft, Sebastian John ORCID: 0009-0008-0092-5958 (2025) Machine Learning Prediction of Glass and Melting Transitions in High-Performance Polymers: A case study of poly(aryl ether ketones) and conjugated polymers. PhD thesis, University of Leeds.

Metadata

Supervisors: Mattsson, Johan and Olmsted, Peter D. and Hine, Peter J.
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Keywords: quantitative structure–property relationships; machine learning; conjugated polymers; high-performance polymers; Bayesian modelling; glass transition temperature; melting temperature
Awarding institution: University of Leeds
Academic Units: The University of Leeds > Faculty of Maths and Physical Sciences (Leeds) > School of Physics and Astronomy (Leeds)
Date Deposited: 22 May 2026 10:50
Last Modified: 22 May 2026 10:50
Open Archives Initiative ID (OAI ID):

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