MFS-SPEED: Informatics-Driven Design of Recyclable Polymers for Packaging

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

This award will study how to create packaging materials that can be easily recycled or biodegraded at the end of their use. Traditional packaging materials, often made from plastics, are difficult to recycle. Using cutting-edge artificial intelligence and physical lab experimentation, this project will seek to develop next-generation materials that not only meet the performance needs of food and goods packaging but also break down safely or can be reused as raw material—helping to reduce waste and reliance on new plastic. The research will train students in pioneering, interdisciplinary science while building tools and data that can benefit the broader scientific and industrial communities. The team will aim to turn their discoveries into real-world solutions that will support a circular economy. This project will study the design and development of high-performance polymers tailored for circular packaging applications, focusing on two synergistic recycling strategies: chemical recycling via ring-opening polymerization (ROP) and biodegradation through polyesters such as polyhydroxyalkanoates (PHAs). The project will integrate polymer informatics, synthetic chemistry, and materials testing to overcome the performance limitations that currently hinder recycling of plastics-based packaging materials. Machine learning-driven Virtual Forward Synthesis (VFS) and predictive artificial intelligence (AI) modeling will guide the design of novel polymers, drawing on extensive datasets to be produced in the program. Promising candidates will be synthesized, tested for mechanical, thermal, and barrier properties, and refined through iterative experimental-computational feedback. This integrated framework has the potential to yield recyclable and biodegradable polymers suitable for packaging applications, with broad implications for reducing plastic waste. This Molecular Foundations for Sustainability: Sustainable Polymers Enabled by Emerging Data Analytics (MFS-SPEED) award is co-funded by the NSF through the Division of Chemistry (CHE), the Directorate for Mathematical and Physical Sciences (MPS), and the Division of Innovation and Technology Ecosystems (ITE) in the Directorate for Technology, Innovation, and Partnerships (TIP). Additional MFS-SPEED funding is provided by Procter & Gamble, PepsiCo, Dow, BASF, and IBM. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.