Modeling of coating ingredients via group contribution methods based on machine learning
This thesis develops a data-driven framework for predicting polymer properties using machine learning and chemically informed molecular representations. Polymer performance arises from complex interactions between molecular structure and formulation composition, which makes property prediction challenging. It can be se...