Multi-excitation wavelength of gold nanocluster-based fluorescence sensor array for sulfonamides discrimination

Sulfonamides (SAs) are widely used in many fields because of their advantages, including low price, wide antibacterial spectrum, and high stability. However, their accumulation in the human body leads to a variety of serious diseases. Therefore, it is necessary to design a convenient, effective, and sensitive method to detect SAs. Moreover, the fluorescence excitation spectrum has rich information characteristics, especially for the interaction between fluorophore and quencher via various mechanisms. However, the excitation wavelength-guided sensor array construction does not draw proper attention. To address these issues, we used BSA-AuNCs as a single probe to construct a sensor array for the detection of five SAs. The selected SAs showed different quenching effects on the fluorescence intensities of BSA-AuNCs. The changes in the fluorescence intensity at different excitation wavelengths (lambda = 230, 250, and 280 nm) have been applied to construct our sensor array and address the distinguishability between the selected SAs. With helping of pattern recognition methods, five different SAs have been identified at three different concentrations. Additionally, qualitative analysis at different moral ratios and quantitative analysis at nanogram concentrations have been considered. Moreover, the proposed sensor array was successfully used to distinguish between different SAs in commercial milk with an accuracy of 100 %. This study provides a simple and powerful approach to SAs detection. Also, it shows a broad application prospect in the field of food and drug monitoring.

Automated summary

Sulfonamides are widely used but their accumulation in the human body can cause serious diseases. Therefore, a convenient, effective, and sensitive method to detect them is needed. In this study, a sensor array using BSA-AuNCs was constructed to detect five Sulfonamides, and the changes in fluorescence intensity at different excitation wavelengths were used for identification. This method shows great potential in the fields of food and drug monitoring.