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Liquid metasurface for size-independent detection of microplastics

Talanta 2024 4 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 55 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Mingfu Zhao, Feng Chen, Bin Zhang, Hong Liu, Z. Li, Gengchen Li, Minggang Zhao, Ye Ma

Summary

Researchers developed a liquid metasurface sensor that can detect and quantify microplastics regardless of their size, overcoming a major limitation of existing detection methods. The technology uses surface-enhanced Raman scattering on a self-assembled liquid surface to eliminate the size-dependent detection problems that plague conventional solid substrates. This advancement could make it significantly easier to accurately measure microplastic contamination in environmental samples.

Polymers
Body Systems

Microplastics (MPs) are widely distributed in water, soil, and air, drawing a global concern as a cause of chronic diseases and immune system disruption. Though as one of the most promising techniques in MP detection, the surface-enhanced Raman scattering (SERS) is heavily dependent on the distribution of the "hot spots" and the size of MPs, known as "coffee ring effect" and "size effect" respectively, imposing major challenges in the quantitative detection of various sized MPs on conventional SERS substrates. Here we present a self-healing metasurface based on plasmonic nanoparticle (NP) array at the liquid-liquid interface (LLI) and air-liquid interface (ALI). The fluidic nature of the metasurface and the repulsive forces between NPs offer atomic-level flatness and uniform distribution for "hot spots". Additionally, MPs are dissolved in the oil phase, uniformly enriched in the form of polymer molecular chains on the liquid metasurface, irrespective of the size of the MPs. This molecular dispersity of the dissolved MPs enhances the overlap between the "hot spots" and scattering volume of MPs, significantly improving the intensity and reproducibility of SERS. The sensing platform is successfully applied in trace detections of various MPs (PS, PET, PMMA, and PC), and validated in real samples.

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