Machine Learning Approach to Polymerization Reaction Engineering: Determining Monomers Reactivity Ratios

Abstract

Here, we demonstrate how machine learning enables the prediction of comonomers reactivity ratios based on the molecular structure of monomers. We combined multi-task learning, multi-inputs, and Graph Attention Network to build a model capable of predicting reactivity ratios based on the monomers chemical structures.

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