Electrostatic Self Assembly of Metal‐Free Hexagonal Boron Nitride/Protonated Carbon Nitride (h‐BN/PCN) Nanohybrid: A Synergistically Upgraded 2D/2D Sustainable Electrocatalyst for Sulfamethazine Identification

Abstract

AbstractIn the scientific community, developing a non‐enzymatic detection tool for highly reliable and sensitive identification of the targeted biomolecules is challenging. Sulfamethazine (SMZ), a bacterial inhibitor frequently used as an antibacterial medicine, can cause antimicrobial resistance (AMR) in humans if taken in excess. Hence, there is a need for a reliable and rapid sensor that can detect SMZ in food and aquatic environments. The goal of this study aims to develop a novel, inexpensive 2D/2D hexagonal boron nitride/protonated carbon nitride (h‐BN/PCN) nanohybrid that can function as an electrocatalyst for SMZ sensing. The as‐synthesized material‘s crystalline, structural, chemical, and self‐assembly properties were thoroughly characterized by XRD, HR‐TEM, XPS, HR‐SEM, FT‐IR, and ZETA potential and electrochemical sensing capacity of the suggested electrodes was optimized using CV, EIS, DPV, and i‐t curve techniques. The above nanohybrid of h‐BN/PCN‐modified GCE exhibits improved non‐enzymatic sulfamethazine sensing behaviour, with a response time of less than 1.83 s, a sensitivity of 1.80 μA μM−1 cm−2, a detection limit of 0.00298 μM, and a range of 10 nM to 200 μM. The electrochemical analysis proves that the conductivity of h‐BN has significantly improved after assembling PCN due to the large surface area with active surface sites and the synergistic effect. Notably, our constructed sensor demonstrated outstanding selectivity over a range of probable interferents, and electrochemical studies indicate that the suggested sensor has improved functional durability, rapid response, impartial repeatability, and reproducibility. Furthermore, the feasibility of an h‐BN/PCN‐modified sensor to detect the presence of SMZ in food samples consumed by humans has been successfully tested with high recovery percentages.