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

arXiv 2301.01231 ↗First posted 3 Jan 2023cs.LG cond-mat.soft q-bio.BMcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 13 of its 56 references that are in the map. First posted on arXiv 3 Jan 2023.

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References · 13

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1 more
  1. 2022A graph representation of molecular ensembles for polymer property predictioncited by 20

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