Novel nano-engineered environmental sensor based on polymelamine/graphitic-carbon nitride nanohybrid material for sensitive and simultaneous monitoring of toxic heavy metals.

Heavy metal ions (HMIs) pollution is always a serious issue worldwide. Therefore, monitoring HMIs in environmental water is an important and challenging step to ensure environmental health and human safety. In this study, we spotlight an effortless, single-step in-situ electrochemical polymerization deposition technique to fabricate a novel, low-cost, efficient, nano-engineered poly(melamine)/graphitic-carbon nitride nanonetwork (PM/g-C 3 N 4) modified screen-printed carbon electrode (SPE) for sensitive, selective, and simultaneous electrochemical monitoring of toxic HMIs in environmental waters. g-C 3 N 4 nanomaterial was prepared using melamine as a precursor via pyrolysis technique. As-prepared g-C 3 N 4 and melamine monomer were electrochemically in-situ polymerized/deposited over pre-anodized SPE (ASPE) using cyclic voltammetry technique. XRD, XPS, and SEM were engaged to characterize the developed electrode. The fabricated PM/g-C 3 N 4 /ASPE was applied as an environmental sensor to selective and simultaneous electrochemical detection of Pb2+ and Cd2+ ions using differential pulse voltammetry technique. The developed sensor displayed excellent selectivity and sensitivity towards Pb2+ and Cd2+ with limit of detections of 0.008 µM and 0.02 µM, respectively. The fabricated PM/g-C 3 N 4 /ASPE sensor exhibits superior stability, repeatability, good anti-interference, and applicability for recognition of Pb2+ and Cd2+ ions in real water samples. These results proved that developed environmental sensor is low-cost, efficient, practical platform for rapid, selective, simultaneous monitoring of HMIs in the environment. [Display omitted] • New nano-engineered poly(melamine)/graphitic-carbon nitride based nanohybrid electrode. • Applied as environmental sensor for sensitive and simultaneous monitoring of heavy metals. • The developed sensor is low-cost and efficient for real-time analysis and monitoring. [ABSTRACT FROM AUTHOR]