Professor Dutta Part of UMD Team Receiving Grant from NSF MPS SPEED Program

As Co-PI, Professor Sanghamitra Dutta is part of a team that has received a grant from the National Science Foundation’s Molecular Foundations for Sustainability: Sustainable Polymers Enabled by Emerging Data Analytics (MFS-SPEED) program. ECE Affiliate Faculty member Po-Yen Chen will lead the study. Chen is a member of the UMD Chemical and Biomolecular Engineering Department.

The team will receive $1.8M over three years to accelerate the discovery of high-performance and biodegradable polymer nanocomposites with tunable properties using artificial intelligence.

Using robotic platforms, artificial intelligence, and materials chemistry, an integrated platform will be developed to rapidly identify, design, and test polymer composite films with customizable properties, such as mechanical strength, optical clarity, and moisture absorption. Explainable machine learning will guide the discovery of promising new biopolymer candidates with desirable properties even before experimentation, thus drastically reducing the search space.

The project will design a unified framework to encode molecular structure, processing conditions, and life cycle assessment metrics for multiple biopolymer components that are generally recognized as safe. A robotics-enabled workflow will then allow for the generation and analysis of thousands of composite formulations, followed by training machine learning models to predict their properties. Counterfactual explanations, a technique from explainable machine learning, will be leveraged for efficient inverse design. Ultimately, the data, tools, and models from the project will be disseminated through a cloud-based platform that enables forward and reverse materials design.

The project will expand the accessible design space for biodegradable polymers and speed up the development of next-generation materials that combine high performance with low impact on resources.

Other collaborators on this project include Teng Li, a professor of mechanical engineering, and researchers at Iowa State University.

The NSF states that MSF-SPEED funding supports cross-disciplinary, collaborative research focused on the discovery and ultimate manufacturing of new sustainable polymers or sustainable pathways to existing polymers using state-of-the-art data science.

For more information: Predictive Discovery of Sustainable Biopolymers via Multi-Attribute Descriptor System, Robotics/Machine Learning Workflow, and Open-Data Platform

Published December 4, 2025