Chemically engineered unzipped multiwalled carbon nanotube and rGO nanohybrid for ultrasensitive picloram detection in rice water and soil samples - Dkhar D.S.; Kumari R.; Chandra P. (My University, 2025)
Picloram (4-Amino-3,5,6-trichloro pyridine-2-carboxylic acid) is a chlorinated herbicide that has been discovered to be tenacious and relatively durable in both soil and water. It is known to have adverse and unpleasant effects on humans causing several health complications. Therefore, the determination of picloram is profoundly effective because of its bio-accumulative and persistent nature. Because of this, a sensitive, rapid, and robust detection system is essential to detect traces of this molecule. In this study, we have constructed a novel nanohybrid system comprising of an UZMWCNT and rGO decorated on AuNPs modified glassy carbon electrode (UZMWCNT + rGO/AuNPs/GCE). The synthesized nanomaterials and the developed system were characterized using techniques such as SEM, XRD, SWV, LSV, EIS, and chronoamperometry. The engineered sensor surface showed a broad linear range of 5 × 10–2 nM to 6 × 105 nM , a low limit of detection (LOD) of 2.31 ± 0.02 (RSD < 4.1%) pM and a limit of quantification (LOQ) of 7.63 ± 0.03 pM. The response time was recorded to be 0.2 s, and the efficacy of the proposed sensor system was studied using rice water and soil samples collected from the agricultural field post filtration. The calculated recovery % for picloram in rice water was found to be 88.58%—96.70% (RSD < 3.5%, n = 3) and for soil it was found to be 89.57%—93.24% (RSD < 3.5%, n = 3). In addition, the SWV responses of both the real samples have been performed and a linear plot have been obtained with a correlation coefficient of 0.97 and 0.96 for rice and soil samples, respectively. The interference studies due to the coexisting molecules that may be present in the samples have been found to be negligible. Also, the designed sensor has been evaluated for stability and found to be highly reproducible and stable towards picloram detection. © 2023, The Author(s).