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Shiraiwa, Manabu
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article
Predicting glass transition temperature and melting point of organic compounds via machine learning and molecular embeddings
Abstract
<jats:p>We developed tgBoost a machine learning model to predict glass transition temperature (<jats:italic>T</jats:italic>g) of organic species considering their molecular structure and functionality for better predictions of the phase state of secondary organic aerosols.</jats:p>