Dept. of Materials Science and Engineering Spring Seminar Series: Rampi Ramprasad

Description

Rampi Ramprasad, chair of Materials Science and Engineering at the Georgia Institute of Technology, will give a talk titled "Polymer Informatics: Algorithmic Advances & Materials Design" for the Department of Materials Science and Engineering.

Abstract:

Polymers display extraordinary diversity in their chemistry, structure, and applications. However, finding the ideal polymer possessing the right combination of properties for a given application is non-trivial as the chemical space of polymers is practically infinite. This daunting search problem can be mitigated by surrogate models, trained using machine learning algorithms on available property data, that can make instantaneous predictions of polymer properties. I will present versatile, interpretable, and scalable schemes to build such predictive models. Our ''multi-task learning'' approach efficiently, effectively, and simultaneously learns and predicts multiple polymer properties. It is thus a powerful tool to solve "forward materials problems," i.e., property predictions. I will also discuss new approaches to solve "inverse materials problems," i.e., identifying materials that satisfy target property criteria. These forward and inverse method developments are expected to have a significant impact on data-driven materials discovery, as will be illustrated using a few examples.