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In Situ Micro/Nanoplastic Sensing Technologies: Optical, Electrochemical and Biosensor Approaches

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Tiny plastic particles are everywhere in our environment, and this review rounds up the latest tools scientists are building to detect them faster and more accurately—from light-based sensors to electronic and biology-based detectors. The big takeaway is that portable electrochemical devices (think small, sensor-based gadgets) currently show the most promise for real-world testing of water, food, or other samples on the spot. This matters because better detection tools are the first step toward understanding how much plastic we're actually exposed to and what it might mean for our health.

Micro- and nanoplastic (MNP) pollution has emerged as a global environmental and health concern, driving the rapid development of sensor technologies for faster, more sensitive, and field-deployable detection. This review synthesizes recent advances in optical, electrochemical, and biosensor platforms for MNP analysis and compares their analytical performance and practical feasibility. Optical sensors, including plasmonic, spectroscopic, and colorimetric systems, enable label-free and often rapid detection with material discrimination capability, and are well-suited for screening applications, though they commonly exhibit higher detection limits and matrix interference. Electrochemical sensors demonstrate the highest analytical sensitivity overall, frequently reaching low µg L−1 to ng mL−1 levels, with strong potential for miniaturization and on-site deployment; performance is further enhanced by nanostructured electrodes, photoelectrochemical designs, and signal amplification strategies. Biosensors incorporating peptides, aptamers, enzymes, or engineered proteins provide improved polymer selectivity and enable targeted detection, but face challenges related to stability, cross-reactivity, and reproducibility in complex samples. Practically, portable electrochemical and simple optical colorimetric platforms are currently the most feasible for field use, while hybrid bio-electrochemical systems show the highest performance potential. Future research should prioritize robust selective recognition elements, antifouling interfaces, standardized validation protocols, mixed-polymer quantification models, and integration with machine learning to enable reliable, real-world MNP monitoring.

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