Polymer reaction engineering meets explainable machine learning

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Jelena Fiosina, Philipp Sievers, Marco Drache, Sabine Beuermann

Published: 01 Jan 2023, Last Modified: 06 Oct 2025Comput. Chem. Eng. 2023EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•Explainable ML models for polymerization modeling are proposed.•Data for training ML models are provided by in-house kinetic Monte Carlo simulator.•ML-based approach for reverse engineering of polymerization processes is proposed.•The proposed ML models allow for creating of polymers with tailored properties.