Machine Learning Approach to Polymerization Reaction Engineering: Determining Monomers Reactivity Ratios
Year: 2023
Type: preprint
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.
Source: arXiv (Cornell University)
Authors: Nguyen, Tung, Bavarian, Mona
Institution: University of Nebraska–Lincoln
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: green
Funder: University of Nebraska-Lincoln
OpenAlex ID: W4313533503