A highly sensitive Sonogel-Carbon electrochemical sensor based on multi-walled carbon nanotubes and gold nanoparticles for dopamine detection in the presence of ascorbic acid

Abstract

In this study, we present a high-performance electrochemical matrix based on a Sonogel–Carbon electrode synergistically modified with gold nanoparticles and carboxylated multi-walled carbon nanotubes. Not only does the resulting electrochemical sensor exhibit high selectivity towards dopamine, even in the presence of high concentrations of ascorbic acid, but it also demonstrates superior electrocatalytic performance compared to conventional glassy carbon electrodes. Surface morphology and composition were characterized using scanning electron microscopy coupled to X-ray energy dispersive spectroscopy, while electrochemical characterizations were performed using cyclic voltammetry and electrochemical impedance spectroscopy. Differential pulse voltammetry was employed to investigate the analytical performance of the electrochemical sensor for dopamine detection. The nanocomposite-modified Sonogel-Carbon electrode shows two wide linear ranges of 0.5–100 μmol L −1 and 100–1000 μmol L −1 with excellent sensitivity values of 0.468 μΑ/μmol L −1 and 0.021 μΑ/μmol L −1 , respectively, a low detection limit of 0.04 μmol L −1 and good reproducibility (RSD (%) = 3.55, n = 5) and repeatability (RSD (%) = 1.43, n = 5). Moreover, the electrochemical sensor was successfully assessed in artificial human serum and real pharmaceutical samples, highlighting its strong potential for dopamine sensing applications. • Cost-effective Sonogel-Carbon electrodes synthesized via a fast and green fabrication protocol. • Simple surface modification enables highly selective dopamine detection at low concentrations. • Dual linear ranges achieved with enhanced sensitivity and resolution over standard electrodes. • Superior electrochemical performance demonstrated over glassy carbon counterparts. • Reliable dopamine detection in artificial serum validates clinical potential of the SNGC-based platform.