Multivariate Optimization of Electrochemical Sensing Parameters for Bisphenol A Detection Using an AgNPs/g-C 3 N 4 /IL@GCE via Box-Behnken Design

We developed an electrochemical sensor for detecting BPA using AgNPs/g-C 3 N 4 /IL@GCE. Graphitic carbon nitride was synthesized by the calcination of melamine at 550 °C. In contrast AgNPs were synthesized via a green tea extract method, and the nanocomposite was dropcast onto the GCE surface along with 1-butyl-3-methylimidazolium methyl sulfate (BMIM-MeSO 4 ) ionic liquid as a binder. Morphology was characterized, and response surface methodology (RSM) using Box-Behnken Design (BBD) was used as a concurrent strategy to optimize pH, scan rate, and deposition time. Independent validation experiments conducted at multiple interior points within the design space showed good agreement between predicted and experimental responses, with prediction errors of 6.29%–10.11% for oxidation peak current and 1.63%–5.24% for oxidation potential. Applying the optimized conditions, the sensor linearized BPA detection over the concentration range of 1–10 μM, with a limit of detection of 0.66 μM, and a limit of quantification of 2.20 μM. The sensor showed excellent recovery (99.16%–102.26%) of BPA present in real water samples. The improved electrocatalytic activity of the sensor interfaces was due to the synergistic effects of AgNPs and g- C 3 N 4. The novelty of this research was the use of an RSM-BBD approach to systematically optimize a green synthesized AgNPs/g-C 3 N 4 nanocomposite electrode, enabling predictive modelling to show reasonable electrochemical sensitivity towards BPA detection.