Prediction of Properties of Polymer Composite Formulations Using Ensemble Models With Feature Generation

ABSTRACT The development of polymer composites remains largely dependent on trial‐and‐error experimentation, despite increasingly complex performance requirements in industrial applications. An interpretable machine‐learning framework is presented for the simultaneous prediction of nine mechanical, thermal, electrical, and physicochemical properties of polymer composites using an industry‐derived dataset comprising 112 commercial products. Unlike most prior studies that focus on a single propert