Advancing on ametrine pesticide detection through surface-enhanced Raman spectroscopy and Ag colloid: Understanding the pH effect and the adsorption mechanism supported by theoretical calculation

Abstract

The excessive use of pesticides has detrimental effects on the ecosystem, leading to soil contamination and the spread of pollution beyond the targeted areas. Concerns arise regarding the permissible limits of pesticides, typically around 10⁻⁸ mol/L. In this study, we employed surface-enhanced Raman spectroscopy (SERS), a highly sensitive and selective technique, to investigate the behavior of the pesticide ametrine (AMT) on silver colloids. The Ag nanoparticles (AgNPs) exhibited an average size of (26 ± 2) nm and a zeta potential of (−30 ± 1) mV in the absence of AMT, which decreased to (−24 ± 1) mV in the presence of AMT, resulting in mild AgNPs aggregation, with the average diameter of AgNPs increasing to approximately 300 nm. This aggregation is advantageous, as they provide active sites for pesticide detection. Besides, the purification method employed ensured that AMT remained undegraded, and various conformations of AMT were simulated using Ag clusters to study the SERS effect. Comparison with the experimental spectra indicated that the SERS-4 conformer closely resembled the experimental spectrum, suggesting simultaneous interaction between the Ag surface and the sulfur (S) and nitrogen (N) atoms of the AMT triazine ring. Notably, changes in the AMT molecule were observed with pH variations: at pH below 5, hydroxylation occurred, resulting in an Ag–Cl stretching at 241 cm⁻¹ in the SERS spectra. Conversely, at pH above 5 (pH 6–13), the presence of bands at 230 and 219 cm⁻¹ in the SERS spectra indicate the formation of Ag–N and Ag–S bonds, respectively, between the AMT and the AgNPs. Furthermore, the study successfully detected AMT at pH 7, establishing a limit of detection (LOD) of 1.36 × 10⁻⁸ mol/L (3 ppb) based on the SERS spectra. These findings underscore the applicability of the SERS technique in the sensitive and selective detection of AMT, offering a promising approach for monitoring the presence of this pesticide in environmental samples.