$2M NSF Grant Supports AI Project to Develop Stronger, More Sustainable Plastics

From the foam inside of our mattresses to components of our electronic devices and vehicles, plastics are a ubiquitous part of modern life, but they are an environmental challenge as well. Plastics manufacturing accounts for roughly 3.4% of global carbon emissions—a figure that could double by 2060—and the material can persist for centuries in oceans and landfills once discarded.

But a new $2 million National Science Foundation (NSF) grant is supporting a University of Maryland project to use artificial intelligence (AI) to accelerate the discovery of sustainable, biodegradable polymers—materials that could help reduce pollution and other environmental impacts from the global plastics industry. 

Biopolymers—derived from natural sources and designed to degrade safely—offer a promising alternative, but finding materials with the right combination of strength, clarity and moisture resistance is slow and labor-intensive.

The overall project is being led by UMD’s Po-Yen Chen, an assistant professor of chemical and biomolecular engineering, in collaboration with Teng Li, a professor of mechanical engineering, with additional contributions coming from researchers at Iowa State University. 

Sanghamitra Dutta, an assistant professor of electrical and computer engineering with an affiliate appointment in the University of Maryland Institute for Advanced Computer Studies, is serving as a co-principal investigator on the project.

Dutta will advance the use of interpretable AI—meaning that the processes of the AI algorithm can be studied by observers rather than remaining opaque—to guide the discovery of new biopolymers. Her work translates foundational research in ethical, interpretable machine learning into practical tools that can preemptively identify promising polymer candidates.

“This project is an important leap toward a new real-world application of interpretability that will enable rapid discovery of new biopolymers and promote a sustainable future,” said Dutta, who is a member of the University of Maryland Center for Machine Learning. 

Her approach, combined with multiscale simulations and high-throughput robotics, will allow the team to identify promising candidates before costly lab testing.

Pasan Dissanayake, a fourth-year electrical and computer engineering doctoral student and a recipient of UMD’s Outstanding Graduate Assistant Award, is supporting Dutta in the NSF-funded research.

Chen and Li, meanwhile, are working together to integrate AI, simulation and robotics into a system that can design and evaluate biopolymer nanocomposites with programmable properties—streamlining the path from computational prediction to experimental validation.

Harnessing the power of AI, the team aims to accelerate the development of high-performance, environmentally friendly materials. Their work addresses pressing environmental challenges and shows how interpretable AI can guide real-world scientific discovery—creating tools and knowledge that could benefit industries from packaging to health care.