Determination of Nicotine in Human Saliva Using Electrochemical Sensor Modified with Green Synthesized Silver Nanoparticles Using Phyllanthus reticulatus Fruit Extract

In this study, for the first time, Phyllanthus Reticulatus fruit extract was utilized as a reducing agent in the synthesis of silver nanoparticles (Ag-NPs). For sample analysis, a number of approaches were employed. The synthesized Ag-NPs have a spherical shape and a homogeneous in size. The well-known crystal structure and optical energy absorption spectrum of Ag-NPs were respectively revealed by the XRD and UV-VIS analysis. This new method is simple and eco-friendly for producing silver and other noble metals in large quantities. The Ag-NPs modified glassy carbon electrode was prepared for nicotine oxidation which indicated that Ag NPs had the ability to enhance the electron transfer rate of the oxidation process. In 0.1 M phosphate buffer (pH of 7.4), a significant increase in the oxidation peak current of nicotine was observed at the modified electrode. Cyclic voltammetry, amperometry, and electrochemical impedance spectroscopy characterizations showed that Ag-NPs had better electrocatalytic performance toward nicotine (NIC) oxidation with good stability, and selectivity. This sensor showed a linear response with the concentration of NIC in the range of 2.5 to 105 mu M. The limit of detection (LOD) was estimated to be 0.135 mu M. The interference analysis was carried out on the Ag-NPs/GCE with various molecules like acetic acid, ascorbic acid, calcium chloride, glucose, magnesium chloride, urea, and uric acid. Hence, these molecules did not interfere with NIC detection, indicating a perfect selectivity of Ag-NPs/GCE. Moreover, the Ag-NPs/GCE sensor was effectively applied to detect NIC in a real-world sample (saliva) of a tobacco chewer. Furthermore, the Ag-NPs/GCE sensor exhibited very good stability and repeatability in human saliva samples. Finally, Ag-NPs/GCE was also successfully applied to detect spiked nicotine in saliva samples with high recovery value, indicating its high accuracy and effectiveness in NIC analysis.