Fabrication of Carbon Nanocoils / Metallated Porphyrin Based Nanocomposites for Electrochemical Sensing of Phenolic Compounds

Abstract

Identification and estimation of chemical compounds in different environments has always been a major concern since it is an important issue in the areas ranging from environmental control to clinical diagnosis. The exponential progress of electrochemistry research endeavors in the last decade has led the way to a considerable reconnaissance in developing different electrochemical strategies for assessing various environmental pollutants and biomolecules. With the advent of nanotechnology, the use of carbon nanomaterials in the field of sensing has improved the signal response of the sensors. This research details new avenues in the development of supramolecular assemblies of four different metallated tetraphenylporphyrins and carbon nanocoils to prepare nanosensors for the detection of phenolic compounds. Stateof- the-art analytical techniques were used for the characterization of the as prepared materials (pristine and nanocomposites). Cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), differential pulse voltammetry (DPV) and chronocoulometry (ChrC) were used to characterize and evaluate the performance of the prepared nanosensors. The characteristics of the as prepared nanosensors like accuracy, reproducibility, repeatability, selectivity, kinetics of the analyte sensing on the electrode interface, linear range, limit of detection (LoD), limit of quantification (LoQ) and sensitivity were also evaluated. The first research endeavor was to prepare carbon nanocoils/zinc tetraphenylporphyrin (CNCs/Zn-TPP) nanocomposite decorated glassy carbon electrode (GCE) for electrochemical detection of catechol (CC) and hydroquinone (HQ) in a wide linear range i.e., 25 to 1500 μM. LoD, LoQ and sensitivity for catechol were found to be 0.9 μM, 3.1 μM and 0.48 μAμM-1cm-2, respectively. LoD, LoQ and sensitivity for HQ were found to be 1.5 μM, 5.1 μM and 0.35 μAμM-1cm-2, respectively. Well resolved peaks for CC and HQ were obtained in binary mixture with anodic peak potential difference, ΔEpa(CC-HQ), of 110 mV representing efficient sensing ability of sensor. Second work includes the fabrication of CNC/copper tetra(pxviii methoxyphenyl)porphyrin (CuTMePP)/glassy carbon sensor for the efficient and selective detection of dopamine (neurotransmitter); thus demonstrated two linear concentration trends i.e., 0.10 to 100 μM and 100 to 800 μM. LoD, LoQ and sensitivity of the electrode in the concentration range of 0.10 to 100 μM was 50 nM, 167 nM and 1.76 μAμM-1cm-2, respectively using CV. With DPV, the LoD, LoQ and sensitivity were found to be 64 nM, 211 nM and 0.75 μAμM-1cm-2, respectively obtained in a concentration range of 0.10 to 100 μM. Thirdly, we constructed carbon nanocoils/manganese tetraphenylporphyrin convened glassy carbon electrode (CNC/MnTPP/GC) for the streamlined electrochemical sensing of tyrosine at pH 5 with a significant linearity in the concentration range of 0.05 to 100 μM of tyrosine, that illustrated a low limit of detection (21 nM) and sensitivity of 0.12 μAμM-1cm-2, using DPV. While our fourth research venture includes silver-tetraphenylporphyrin (AgTPP) and carbon nanocoils (CNC) nanocomposite decorated GCE to electrochemically detect bisphenol A (BPA). Different loading amounts of AgTPP on CNC were tested for BPA and CNC/AgTPP/GC (1:3) displayed excellent performance as compared to CNC/AgTPP/GC (1:1) and CNC/AgTPP/GC (1:2). Moreover, CNC/AgTPP/GC (1:3) showed an irreversible adsorption-controlled kinetics towards BPA detection and displayed linear dynamic concentration range of 0.019 μM to 16.55 μM in a pH 7.0 with LoDs in two sets of linear ranges were 3.7 nM and 152 nM, respectively. Additionally, our sensing platforms exhibit comparable and somehow better results to those reported in the literature. Additionally, the fabricated sensors presented repeatable and reproducible results with wide linear ranges, better selectivity, and excellent percentage recoveries towards analytes in real sample analysis.