English

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

Machine Learning 2023-01-04 v1 Soft Condensed Matter Biomolecules

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.

Keywords

Cite

@article{arxiv.2301.01231,
  title  = {Machine Learning Approach to Polymerization Reaction Engineering: Determining Monomers Reactivity Ratios},
  author = {Tung Nguyen and Mona Bavarian},
  journal= {arXiv preprint arXiv:2301.01231},
  year   = {2023}
}

Comments

4 figures in paper, 4 figures in supplementary

R2 v1 2026-06-28T08:01:14.892Z