Polymer chemistry informed neural networks (PCINNs) for data-driven modelling of polymerization processes

Abstract

A method for training neural networks to predict the outcome of polymerization processes is described that incorporates fundamental chemical knowledge. This permits generation of data-driven predictive models with limited datasets.