The accumulation of plastic waste worldwide poses a serious threat to wildlife and ecosystems. Catalytic processes that convert plastic waste into valuable chemicals and fuels offer a promising solution. However, real-life plastic waste mixtures have highly diverse composition and structural complexity, and accurate identification of the components within the mixtures is a prerequisite for their effective separation and recycling.

In a study published in Nature, Prof. XU Shutao from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences, in collaboration with the team of Prof. WANG Meng and Prof. MA Ding from Peking University, developed a solid-state nuclear magnetic resonance (NMR) technology to characterize the separation and recycling processes of real-life plastic waste mixtures.

Solid-state NMR spectroscopy has the advantage of directly analyzing insoluble samples, making it a powerful tool for studying complex polymer systems. In this study, the researchers utilized an innovative solid-state NMR method:¹H-¹³C Frequency Switched Lee Goldburg Heteronuclear Correlation (FSLG-HETCOR) NMR.

By optimizing key parameters such as spinning rate, contact time, and homonuclear decoupling field strength, and using ¹³C-labeled tyrosine hydrochloride as a reference, the researchers obtained high-resolution "fingerprint" spectra of individual plastic components from an eight-plastic mixture containing polystyrene (PS), polylactic acid (PLA), polyurethane (PU), polycarbonate (PC), polyvinyl chloride (PVC), polyethylene terephthalate (PET), polyethylene (PE), and polypropylene (PP).

The obtained spectra by the novel solid-state NMR method achieved high signal intensity and good resolution in the indirect dimension, allowing for precise identification of various functional groups in the plastic mixture and enabling real-time tracking of their chemical evolution.

Furthermore, the researchers demonstrated the feasibility, effectiveness, and universality of this method by monitoring the full catalytic separation and transformation of real-life plastic waste mixtures. The NMR-based analysis enabled the mapping of each step in the conversion process—from complex mixtures to multiple high-value chemicals products.

"Solid-state NMR provides a way to identify individual components in plastic waste mixtures. It acts as a 'guiding eye' for the separation and catalytic transformation processes," said Prof. XU. 

By identifying characteristic functional group signals in plastic waste mixtures, this study lays a solid foundation for the effective separation and transformation. It also paves the way for integrating existing transformation processes into a unified framework, providing technical support for scalable industrial solutions to plastic pollution.