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Article Tier 2 Detection Methods Food & Water Nanoplastics Sign in to save

Sensitive detection of PET and PP nanoplastics in tea beverages using gold nanorod-enhanced SERS: Mechanism, quantification, and safety implications

Journal of Hazardous Materials 2025 5 citations

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Researchers developed a gold nanorod-enhanced surface-enhanced Raman spectroscopy method for detecting nanoplastics in tea beverages at very low concentrations. The technique achieved detection limits of 1.4 micrograms per milliliter for polypropylene and 0.46 micrograms per milliliter for PET nanoplastics, significantly outperforming traditional Raman microscopy. The method was successfully validated across green tea, black tea, oolong tea, and jasmine tea samples with high accuracy and repeatability.

In this study, SERS platform utilizing gold nanorods (AuNRs) as enhancement substrates was developed for the highly sensitive detection of 203 nm polypropylene (PP) and 220 nm polyethylene terephthalate (PET) nanoplastics (NPs). AuNRs with varying aspect ratios were synthesized by modulating the concentration of AgNO. AuNRs-2 (with a longitudinal peak position at 679 nm) exhibited the best enhancement performance under 532 nm excitation wavelength. Furthermore, it was confirmed that a stable composite structure formed between the AuNRs and NPs via electrostatic adsorption, which significantly increased the hotspot density and signal intensity. Based on the optimized substrate, a quantitative detection model was established for PP and PET NPs, achieving detection limits of 1.4 μg/mL and 0.46 μg/mL, respectively. These values are superior to those obtained using the traditional microscopic Raman method, highlighting the influence of material-specific adsorption mechanisms on the enhancement effect. This method was successfully applied to the detection of NPs in tea beverage samples, including green tea, black tea, oolong tea, and jasmine tea. The results demonstrated excellent linearity (R > 0.90), recovery rates (86.35 %-97.99 %), and repeatability (RSD < 6.62 %), thereby validating the stability and reliability of the method in complex food matrices.

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