SERS-Based Detection of Arsenic by a Silver-Nanoflower-Covered Porous Silicon Sensor

A rapid and selective identification of hazardous water pollutants is important for the determination of water quality for drinking purpose. In this work, the high surface area of a porous silicon substrate is integrated with nanoflower bunches of silver to harness the enhanced plasmonic effect for SERS-based detection of arsenic trioxide impurities. The substrates are prepared by a metal-assisted chemical etching process followed by an electroless deposition technique. The etching process is facilitated by the presence of a silver nanoparticle-based seed layer deposited between 3 s and 10 s under this study. The developed porous silicon substrate shows a variation in pore size distribution as a function of seed layer deposition time and etching time. Further, the plasmonic effect is achieved by silver deposition on the developed porous substrates. FESEM images confirm the synthesis of silver nanoflower bunches, where growth and nanoparticle sizes in the bunches change as a function of seed layer and etching time. The developed substrates are hydrophobic in nature due to their nanostructured surface. SERS spectra of the developed substrates for the R6G analyte show that higher etching duration sample (15 min) provides a better SERS signal (EF ∼ 8.2 × 10 12 at 10 –15 M R6G). The enhanced Raman signal has contributions from both electromagnetic and chemical enhancement. However, the electromagnetic enhancement is dominant and ∼4.6 times higher in comparison to chemical enhancement, which points toward the excellent plasmonic properties of the developed silver nanoflower structures. These substrates are sensitive to detect 10 –10 M (∼0.02 ppb) arsenic trioxide, which is better than the standard acceptable limit of ∼10 ppb (5 × 10 –8 M), as recommended by WHO, EPA, and FSSAI. Therefore, we can say that our developed substrates have the potential to detect the environmentally hazardous compound arsenic trioxide by SERS sensing. These substrates have great potential due to their uniformity, low cost, and SERS signal reproducibility features.