Prediction of polymer properties from their structure by recursive neural networks

We propose a new approach for predicting polymer properties from structured molecular representations based on recursive neural networks. To this aim, a structured representation is designed for the modeling of polymer structures. This representation can also account for average macromolecule characteristics. Preliminarily, this model is applied to the calculation of the T-g of (meth)acrylic polymers with different stereoregularity.