Sensor plasmônico de fibra ótica plástica em u para glifosato em água - Bombardi, Franciele Mendes de Lima (2025)
This work reports the development of a U-shaped plasmonic fiber optic sensor for detecting glyphosate, a possible human carcinogen, in water. The sensor uses the localized surface plasmon resonance (LSPR) effect to detect the presence of the herbicide. Cysteamineencapsulated gold nanoparticles (cys-AuNPs) were synthesized and deposited on the surface of the polymeric optical fiber using the dip-coating technique. The interaction between glyphosate and the nanostructured film was analyzed with optical techniques. The results showed that the sensor presented a significant response to the presence of glyphosate in water, with a limit of detection (LOD) of 17 nM (or 2.9 μg/L). This LOD is comparable to those obtained by other techniques, such as high-performance liquid chromatography (HPLC), and complies with most international standards for water potability. The sensor also proved to be reproducible and specific for glyphosate and not being affected by other compounds present in the water, such as aminomethylphosphonic acid (AMPA) and glufosinate-ammonium. In addition, the dip-and-dry technique allowed the detection of the herbicide for field application, with subsequent analysis in the laboratory, without loss of sensitivity for up to three weeks. The study of the glyphosate interaction for different deposition times of the cys-AuNPs film on polymethyl methacrylate (PMMA) sheets demonstrated that films with 37% surface coverage, obtained with a 30 s deposition time, favor the interaction with the analyte and increase the sensor sensitivity. Characterization by surface enhanced raman spectroscopy (SERS) and scanning electron microscopy (SEM) confirmed this observation, indicating an enhanced interaction between the cys-AuNPs and glyphosate. The developed sensor has great potential for application in water quality monitoring, especially in detecting glyphosate at low concentrations. The technique has advantages such as fast detection, low cost, portability, and specificity, making it promising for developing real-time and in situ detection systems.