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Plasmonic filter paper for microplastic detection: SERS enhancement, size dependence, and quantitative limitations

RSC Advances 2025 Score: 48 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Minjeong Kim, Donggeon Lee, Dong‐Wook Shin, Sangyeob Lee, Choong‐Heui Chung, Jung‐Sub Wi

Summary

Researchers fabricated SERS-active gold-coated filter paper substrates and evaluated their performance for detecting microplastics, finding that SERS signal strength depends significantly on particle size and that the technique has inherent limitations for quantitative analysis of microplastic concentrations.

Polymers

The public concern over microplastic exposure in daily life has increased the demand for reliable detection methods. Surface-Enhanced Raman Scattering (SERS), a candidate method for microplastic analysis, enables chemical identification of microplastics at trace levels. This study evaluated the dependence of SERS on microplastic size and its inherent limitations in quantitative analysis. SERS-active substrates were fabricated by coating a gold film onto a conventional filter paper using oblique-angle deposition. The signal-enhancement effect of the SERS-active substrate was evaluated using electromagnetic simulations and experimental measurements of polystyrene microplastics. For 1 µm polystyrene microplastics, Raman signals were detectable even without SERS enhancement, indicating that plasmonic amplification is not essential for microplastics larger than a few micrometers. Meanwhile, 200 nm polystyrene particles require SERS for signal detection. Across both particle sizes, no definitive correlation was observed between the Raman signal intensity and particle concentration within the range of 10-1000 ppm. This highlights a limitation of SERS analysis for microplastic detection due to the fact that the sizes of the analytes are comparable to the size of the laser focal spot. Our findings demonstrate that using SERS to quantify microplastic concentrations without large-scale data analysis techniques, such as area mapping, can lead to misleading interpretations.

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