Digital SERS Detection of Synthetic Colorants in Black Tea Using Defect-Engineered Monolayer WS₂

Molecular sensing is of great importance in the field of food safety, as food safety constitutes the fundamental baseline for safeguarding public health. However, the application of surface-enhanced Raman spectroscopy (SERS) in this domain remains challenging due to significant fluctuations in signal intensity when low-concentration harmful additives are detected in food samples. To address this, we propose a digital SERS approach based on a two-dimensional (2D) flat WS₂ monolayer and Poisson distribution statistics. This method utilizes a plasma-treated WS₂ monolayer as a highly sensitive SERS substrate and was validated through the digital SERS detection of crystal violet (CV) in both single and mixed solutions. The results demonstrate that the detection limit for CV can reach as low as 1 × 10^-18 M, with no interference observed in mixed solutions, indicating excellent quantitative detection capability. Furthermore, this strategy was applied to detect synthetic colorants in black tea, where it also exhibited outstanding sensitivity and accuracy. Specifically, the limits of detection for sunset yellow and erythrosine are 10^-14 M and 10^-18 M, respectively. In summary, by combining a highly uniform 2D SERS substrate with digital SERS technology, this study not only expands the application scope of 2D SERS substrates but also enhances their potential for the high-precision and efficient quantitative analysis of multiple analytes in complex food samples.