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Co-Self-AssembledMonolayer Enables Sensitive SERSDetection of Nanoplastics via Spontaneous Hotspot Entrapment
Summary
Researchers developed a SERS detection strategy for nanoplastics using co-self-assembly of silver nanoparticles and nanoplastic particles into a monolayer, enabling 90% of nanoplastics in solution to transfer to the monolayer within 30 seconds and become uniformly entrapped in plasmonic hotspots. The method achieved quantitative detection of 80, 300, and 800 nm polystyrene nanoplastics in the range of 0.01-2 mg/L with a detection limit in the microgram-per-litre range.
Identification and quantitative analysis of nanoplastics (NPs) in the environment are extremely challenging. Surface-enhanced Raman scattering (SERS) is a promising technique, but conventional solid SERS substrate-based detection faces difficulties such as ensuring NPs make contact with hotspots, dealing with uneven particle distribution, and poor detection repeatability. Herein, we propose a simple and sensitive SERS detection strategy by co-self-assembling silver (Ag) nanoparticles and NPs in a monolayer. 90% of NPs in solution spontaneously transfer to the monolayer within 30 s. More importantly, a single NP can be uniformly entrapped in Ag nanoparticle SERS “hotspots”, resulting in a significant enhancement of the intrinsic Raman signal. This enhancement enables quantitative detection in the range of 10–2–2 mg/L for 80, 300, and 800 nm polystyrene (PS) NPs, with a low detection limit of 10–2 mg/L. The method allows for the identification of various plastic types, including PS, poly(methyl methacrylate) (PMMA), polyethylene terephthalate (PET), and polyformaldehyde (POM). This method was used to determine the efficacy of NP generation from bulk PS foam through physical (sand friction) and biological (mealworm ingestion) routes. Moreover, NPs in real seawater collected from a rocky beach were quantitatively analyzed. The coassembly monolayer-based SERS detection provides a straightforward and sensitive technique for identification and quantitative analysis of NPs.