New System Targets Recycled Plastic Content Detection

University at Buffalo researchers develop AI-powered method to quickly verify recycled plastic content in commercial products.

Mar. 24, 2026 at 6:00am

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Researchers at the University at Buffalo have developed a new method that combines several scientific testing techniques, along with artificial intelligence, to create a reliable way to differentiate recycled plastic from new plastic. The goal is to provide companies, regulatory agencies, and other organizations a quick and reliable tool to verify recycled material content and enforce recycling regulations.

Why it matters

Verifying recycled plastic content claims has been a challenge, as recycled plastics look and chemically resemble new plastics. This new method aims to help improve the quality of plastic products, reduce plastic waste, and support a more circular economy by providing a way to accurately measure recycled content.

The details

The researchers used four sensing techniques - triboelectric testing, dielectric/impedance spectroscopy, capacitance analysis, and mid-infrared spectroscopy - to identify subtle differences between new and recycled plastics, such as microscopic impurities and broken polymer chains. They then utilized machine learning to analyze the data from these tests and build a model that can determine the percentage of recycled content in PET plastic samples with over 97% accuracy.

  • The study was published on March 24, 2026.

The players

Amit Goyal

SUNY Distinguished Professor and SUNY Empire Innovation Professor in the UB Department of Chemical and Biological Engineering, and the corresponding author of the study.

University at Buffalo

The university where the research was conducted and the New York State Center for Plastics Recycling Research and Innovation is located.

New York State Center for Plastics Recycling Research and Innovation

The center that provided funding for the research, supported by a grant from the New York State Environmental Protection Fund and administered by the New York State Department of Environmental Conservation.

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What they’re saying

“Our goal is to create a quick and reliable tool that can be used to verify recycled material content, as well as enforce recycling regulations.”

— Amit Goyal, SUNY Distinguished Professor and SUNY Empire Innovation Professor

“This is an ideal example of combining cutting-edge innovation in science and engineering with AI for social good, and to potentially realize significant societal impact.”

— Amit Goyal, SUNY Distinguished Professor and SUNY Empire Innovation Professor

What’s next

The team's future work will involve combining the different sensing techniques and machine learning model into a portable device to enable widespread, real-time monitoring of recycled plastics in commercial products.

The takeaway

This new method provides a reliable way to verify recycled plastic content claims, which will help improve the quality of plastic products, reduce plastic waste, and support a more circular economy by enabling better enforcement of recycling regulations.