Polymer Chemistry Informed Neural Networks (PCINNs) for data-driven modelling of polymerization processes
This repository contains code for the implementation of Polymer Chemistry Informed Neural Networks (PCINNs), a method that combines kinetic models of polymerization processes with neural network training to improve predictive accuracy. The approach mitigates common challenges, such as data limitations and poor extrapolation, by leveraging domain knowledge to enhance model reliability. More details are described in our paper.
This repository is licensed under CC BY-NC 4.0. For more information please refer to the license section.