Selective Fabrication of an Electrochemical Sensor for Pb²⁺ Based on Poly(pyrrole-co-o–toluidine)/CoFe2O4 Nanocomposites

We report the synthesis of a novel nanocomposites based Poly(pyrrole-co-o-toluidine) copolymer and cobalt ferrite (CoFe2O4) as an electrochemical sensor for selective Pb2+detection. The general abbreviation of these new materials are given as P(Py-co-OT)/CF nanocomposites (P(Py-co-OT)/CF NCs). The synthesis was performed via in situ-chemical oxidative polymerization method at different CoFe2O4 weight ratio (5%, 10%, 30%, 50% and 70%), whereas CoFe2O4 nanoparticle (NPs) was synthesized by an egg white method prior the nanocomposite formation. The structural, morphological, thermal, magnetic, electrical and electrochemical properties of pure P(Py-co-OT), CoFe2O4 and P(Py-co-OT)/CF NCs were characterized by XRD, FTIR, TGA-DTG, SEM-EDX, TEM, VSM and electrical conductivity. The results of XRD and FTIR confirmed the formation of P(Py-co-OT)/CF NCs with the component CoFe2O4 showing spinel structure. The analysis of TGA-DTG presented that CoFe2O4 NPs improved the thermal stability of NCs indicated the presence of some interactions between the interface of P(Py-co-OT) and CoFe2O4 NPs, which affects the chemical and physical properties of the NCs. The ac conductivity was also examined as a function of temperature. The measures showed a decrease in the conductivity of NCs when increasing the insulating CoFe2O4 NPs contents. A cost-effective and reliable electrochemical sensor selective to Pb2+ ion was fabricated using P(Py-co-OT)/CF NCs on glassy carbon (GCE). It was found that the P(Py-co-OT)/CF10 NCs exhibit excellent detection of Pb2+ ion. The proposed Pb2+ ion sensor was performed linearly over the large concentration range of 0.1 nM ∼ 0.01 mM labelled as linear dynamic range (LDR). The sensitivity as well as detection limit were estimated to be 22.39 μAμM−1cm−2 and 42.39 ±2.12 pM, respectively. The desired ionic sensor-based on P(Py-co-OT)/CF10 NCs/binder/GCE was found as efficient to detect Pb2+ ion in environmental and biological samples significantly. The analytical sensor performances such as reproducibility, sensitivity, stability, validation, and response time were reliable and significant.