An innovative electrochemical approach for selective and sensitive urea sensing using NiNPs modified GCE

Area of Science:

• Electrochemistry
• Nanomaterials Science
• Environmental Monitoring

Background:

• Urea contamination from waste sources requires simple, selective, and sensitive detection methods for food and environmental safety.
• Existing methods may lack the necessary sensitivity or selectivity for accurate urea quantification in complex matrices.
• Electrochemical sensing offers a promising platform for developing rapid and cost-effective analytical tools.

Purpose of the Study:

• To develop an innovative electrochemical sensor for sensitive and selective urea detection.
• To utilize nickel nanoparticles (NiNPs) modified glassy carbon electrode (GCE) for enhanced urea sensing performance.
• To validate the sensor's efficacy in real-world environmental samples.

Main Methods:

• Synthesis of stable colloidal nickel nanoparticles (NiNPs) using tris base and ascorbic acid.
• Modification of GCE surface with synthesized NiNPs via drop-casting.
• Electrochemical characterization using cyclic voltammetry (CV) and square wave voltammetry (SWV) in NaOH electrolyte.
• Spectroscopic and morphological analysis (UV-Vis, FTIR, Raman, XRD, SEM, TEM) for NiNPs characterization.

Main Results:

• NiNPs/GCE exhibited enhanced electrochemical charge transfer and catalytic activity for urea oxidation.
• Tris-capped NiNPs demonstrated superior performance compared to malic acid-capped counterparts.
• Square wave voltammetry enabled selective urea detection with a linear range of 0.0625-1.25 mM.
• Achieved a low detection limit of 28.8 µM (S/N=3) with high urea recovery (>98.7% in municipal wastewater, >94% in agricultural wastewater).

Conclusions:

• The NiNPs/GCE electrochemical sensor provides a highly sensitive and selective platform for urea detection.
• The developed method is robust and effective for monitoring urea contamination in environmental samples.
• This approach offers a simple and efficient solution for addressing urea detection challenges.