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A dual-probe system for autofluorescence-free determination of trace-level polystyrene nanoplastics.

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Scientists developed a super-sensitive new test that can detect tiny plastic particles (nanoplastics) in drinking water, saltwater, and beverages like tea, even at extremely low concentrations that older methods often miss. This matters because nanoplastics are increasingly showing up in our food and water, and having a reliable way to detect them is a key first step toward understanding how much we're exposed to and what that might mean for our health. The tool is also flexible enough to be adapted for detecting other harmful contaminants in the future.

Polymers

Nanoplastics (NPs) are new types of pollutants that have emerged in food which has attracted widespread attention. However, due to the small size and low concentration, and the complexity of food matrices, the selective and sensitive determination of NPs in food is challenging. Herein, we report a dual-probe system for determination of trace-level polystyrene (PS) NPs with high sensitivity and selectivity. The proposed dual-probe system was composed of magnetic FeO nanoparticles functionalized with PS-specific peptides (FeO@Au-PSBP) and a high-quality Li-doped ZnGaO:Cr persistent luminescence nanoparticles (PLNPs) modified with ethylene glycol chitosan. By integrating peptide-based specific recognition, persistent luminescence signaling, and magnetic separation with pH-switchable charge reversal, the proposed system enables effective capture and sensitive detection of PS NPs in complex matrices. Under the optimized conditions, the method showed a linear range of 50-800 pg mL and a detection limit of 8.11 pg mL. The precision for the determination of 50 pg mL PS NPs was 5.24% (RSD, n = 11). The method was successfully applied to the analysis of PS NPs in different matrices, including bottled purified water, saltwater (3.5% salinity), artificial lake water, and tea beverage, with recoveries ranging from 91.25% to 110.53%. More importantly, the proposed system can be readily adapted for the analysis of other targets by replacing the recognition unit, providing a versatile and selective sensing strategy for trace-level hazardous analytes.

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