Machine learning glass transition temperature of polymers

• Published in: Heliyon Vol. 6; no. 10; p. e05055
• Main Authors: Zhang, Yun, Xu, Xiaojie
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.10.2020; Elsevier
• Subjects: Gaussian process regression; Glass transition temperature; Machine learning; Materials chemistry; Materials science; normal distribution; Physical chemistry; Polymer; regression analysis; Physical chemistry; Machine learning; Gaussian process regression; Materials science; Polymer; Glass transition temperature; Materials chemistry

As an important thermophysical property, polymers' glass transition temperature, Tg, could sometimes be difficult to determine experimentally. Modeling methods, particularly data-driven approaches, are promising alternatives to predictions of Tg in a fast and robust way. The molecular traceless...