Polymer chemistry informed neural networks (PCINNs) for data-driven modelling of polymerization processes
Nicholas Ballard, Jon Larrañaga, Kiarash Farajzadehahary, José M. Asua
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.
Topics & Concepts
PolymerizationPolymerArtificial neural networkChemistryPolymer sciencePolymer networkComputer sciencePolymer chemistryChemical engineeringOrganic chemistryArtificial intelligenceEngineeringMachine Learning in Materials ScienceFuel Cells and Related MaterialsEnhanced Oil Recovery Techniques