Abstract

The development of an efficient sensor based on a novel three-components nanocomposite is presented for the detection of heavy metal ions (Cd2+ and Pb2+) in water. For the preparation of three-components nanocomposite surface, the polydopamine reduced graphene oxide (PyDA/RGO) composite was initially prepared by a one-step polymerization of dopamine (DA) on RGO followed by surface modification of the prepared composite with cysteine (Cys). The formation of three-components nanocomposite surface (i.e., Cys/PyDA/RGO) was initially confirmed through physical characterization techniques, including X-ray diffraction and infrared spectroscopy, whereas scanning electron microscopy revealed the surface morphology after each step of sensor fabrication. The electrochemical properties of the sensing platform were evaluated through electrochemical techniques, including cyclic voltammetry and electrochemical impedance spectroscopy with an external ferri‐−/ferrocyanide redox probe. The prepared three-components nanocomposite on disposable pencil graphite electrode (Cys/PyDA/RGO/PGE) showed an improved charge transfer rate as compared to PyDA/RGO/PGE and bare PGE electrode. Targeted heavy metal ions were detected on the sensor surface using differential pulse voltammetry with greater sensitivity, showing detection limits of 0.77 and 1.13 ppb for Cd+2 and Pb+2 ions in citrate buffer solution, respectively. The sensor demonstrated comparable performance in the tap water samples.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.