Machine Learning Fundamentals for Material Informatics paired with Machine Learning Models for Predicting Polymer Solubility

Assoc. Prof. Blair Brettmann
Lecture of the lecture cycle
28.11.2024 10:45, Lecture room A

Artificial intelligence and machine learning have become essential tools in predicting material properties to aid in the accelerated design of new materials. Polymer solubility, critical for new formulations and solution processing, is one such property. However, current models are limited by inadequate experimental datasets that cannot capture the complexity and detail for many features contributing to polymer solubility. I will introduce basic concepts in machine learning for material property prediction and demonstrate the use of machine learning models for polymer solubility prediction for a wide range of polymers and solvents.

The lecture is presented in English