Green in Situ Synthesis of Clean 3D Chestnutlike Ag/WO3-x Nanostructures for Highly Efficient, Recyclable and Sensitive SERS Sensing.

Abstract

Surface-enhanced Raman scattering (SERS) has proven to be an effective technique for identifying and providing fingerprint structural information on various analytes in low concentration. However, this analytical technique has been plagued by the ubiquitous presence of organic contaminants on roughened SERS substrate surfaces, which not only often result in poorer detection sensitivity but also significantly affect the reproducibility and accuracy of SERS analysis. Herein, we developed a clean, stable, and recyclable three-dimensional (3D) chestnutlike Ag/WO3-x (0 < x < 0.28) SERS substrate by simple hydrothermal reaction and subsequent green in situ decoration of silver nanoparticles. None of the organic additives were used in synthesis, which ensures the substrate surfaces are completely clean and free of interferences from impurities. The innovative design combines the SERS enhancement effect and self-cleaning property, making it a multifunctional and reusable SERS platform for highly sensitive SERS detection. Using malachite green as a model target, the as-prepared SERS substrates exhibited good reproducibility (relative standard deviation of 7.5%) and pushed the detection limit down to 0.29 pM. The enhancement factor was found to be as high as 1.4 × 107 based on the analysis of 4-aminothiophenol. The excellent regeneration performance indicated that the 3D biomimetic SERS substrates can be reused many times. In addition, the fabricated substrate was successfully employed for detecting thiram in water with a detection limit of 0.32 nM, and a good linear relationship was obtained between the logarithmic intensities and the logarithmic concentrations of thiram ranging from 1 nM to 1 μM. More importantly, the resultant SERS-active colloid can be used for accurate and reliable determination of thiram in real fruit peels. These results predict that the proposed SERS system have great potential toward rapid, reliable, and on-site analysis, especially for food safety and environmental supervision.