NSF and industry partners fund new research to use emerging data analytics tools for more efficient polymer manufacturing
Five NSF-supported teams aim to accelerate the AI-driven discovery of polymers that can be produced more efficiently and with less waste
The U.S. National Science Foundation has awarded five projects to support fundamental research that enables the accelerated discovery and manufacturing of polymers using state-of-the-art data science. Combined, the five project teams were awarded $9.8 million, $7.3 million from NSF and $2.5 million in funding and in-kind donations from Procter & Gamble, PepsiCo, BASF, Dow and IBM, through the Molecular Foundations for Sustainability: Sustainable Polymers Enabled by Emerging Data Analytics program.
"Polymers, including plastics, are widely used globally from food packaging to medical devices to consumer products due to their ability to be designed for different uses," says Judith Burstyn, director of the NSF Division of Chemistry. "By combining fundamental chemistry with cutting-edge data tools such as artificial intelligence, the research teams seek to design new polymers that can be manufactured at scale more efficiently and be more readily biodegraded or chemically broken down into parts that can be reused, all while retaining the polymer’s functionality."
In addition to advancing fundamental knowledge, this investment seeks to develop a skilled technical workforce with expertise in both emerging data tools and chemistry. This workforce will have the skillset to tackle complex, system-level challenges in the sustainability of polymer production.
The following projects are funded by the partnership:
AI-Driven Design of Architecturally Varied and Deconstructable Polymers for a Comprehensive Circular Plastics Economy
Led by Washington University in St. Louis (Christopher Cooper) and UC Berkeley (Brooks Abel)
Data-Driven Discovery of Oxygen Barrier Materials for Sustainable Packaging
Led by Massachusetts Institute of Technology (Bradley Olsen, Zachary Smith) with University of Minnesota (Marc Hillmyer) and University of Florida (Janani Sampath)
D-Diameter - Data-Driven Innovation Advancing Macromolecular Engineering Towards Efficient Recycling
Led by Northwestern University of Chicago (Linda Broadbelt) and Colorado State University (Eugene Chen)
Informatics-Driven Design of Recyclable Polymers for Packaging
Led by Georgia Institute of Technology (Ramamurthy Ramprasad, Ryan Lively, Vinayak Agarwal, Will Gutekunst)
Predictive Discovery of Sustainable Biopolymers via Multi-Attribute Descriptor System, Robotics/Machine Learning Workflow, and Open-Data Platform
Led by University of Maryland, College Park (Po-Yen Chen, Teng Li, Sanghamitra Dutta) and Iowa State University (Greg Curtzwiler)