Wei Zan

Machine learning for predicting the glass transition and melting temperatures of polymers: molecular representations, model architectures, and interpretability

This review organizes machine-learning prediction of Tg and Tm around three pillars—molecular representation, model architecture, and interpretability—and foregrounds the features that separate polymer informatics from generic molecular machine learning: repeat-unit periodicity, chain-length-invariant encoding, copolym...