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A simple and rapid preparation of Au-Ag alloy nanourchins flexible membrane for ultrasensitive SERS detection of microplastics in water environment
Summary
Researchers fabricated flexible gold-silver alloy nanourchins on a membrane substrate and demonstrated their use as a SERS sensor for rapid, sensitive detection of microplastics in water, achieving detection of multiple polymer types at low concentrations without complex sample preparation.
Microplastic (MP) pollution has emerged as a significant environmental concern in aquatic ecosystems. Consequently, the development of rapid, sensitive, and efficient methods for microplastic detection is of paramount importance. This study presents a novel Au-Ag alloy nano-sea urchin (AAA-NUs) flexible membrane fabricated via a straightforward vacuum filtration technique. This membrane demonstrates high efficiency in enriching and detecting polyvinyl chloride (PVC) and polyethylene (PE) microplastics in water samples. Initially, an asymmetric seed-mediated growth method was employed to synthesize AAA-NUs with numerous sharp tips and rough surface morphologies, thereby creating abundant nano-interstices that enhance surface-enhanced Raman scattering (SERS) signals effectively. Subsequently, by employing a straightforward vacuum filtration technique, a substantial quantity of AAA-NUs can be rapidly and uniformly deposited onto the polytetrafluoroethylene (PTFE) membrane. This process facilitates the formation of stable surface-enhanced Raman scattering (SERS) "hotspots," thereby significantly improving the sensitivity of the sensor. When water containing PE and PVC microplastics passes through the AAA-NUs membrane, these microplastics are captured efficiently. Leveraging the outstanding SERS enhancement of the AAA-NUs flexible membrane, this method achieves a low limit of detection (LOD) of 0.269 μg/mL and 0.373 μg/mL for PE and PVC, which was reduced by 1-2 orders of magnitude compared to conventional SERS substrates. With the growing prevalence of portable Raman spectrometers, this technology holds substantial promise for water quality assessment.
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