Optimization of polyvinyl alcohol binder on PANI coated pencil graphite electrode in doubled chamber microbial fuel cell for glucose biosensor

In this study, a cost-effective and environmentally friendly polyvinyl alcohol (PVOH) binder was studied by binding Polyaniline (PANI) on pencil graphite (PG) to form a PANI/PG electrode. The physicochemical properties of in-situ chemically synthesized PANI were characterized by ultraviolet-visible spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), Thermogravimetric-differential thermal analyzer (TGA-DTA), X-ray diffractometer (XRD), and Scanning electron microscopy-energy dispersive X-ray analyzer (SEM-EDX). The electrochemical properties of PANI coated on PG with different PVOH binder ratios were addressed by linear sweep voltammetry (LSV) and electrochemical impedance spectroscopy (EIS). In addition to power production and wastewater treatment, microbial fuel cells (MFC) are also a promising technology for biosensor applications. This study contributes to the MFC self-powered biosensor activity and its optimizations. For these optimizations, a two-factor, four-level Central Composite design model was performed for the optimization of PVOA binder loading influence on PANI-modified PG anode two-chambered MFC fed by glucose. From the statistically designed model, the two independent factors were developed to correlate them with MFC sensitivity. Thus, for this model, values of R-squared and adjusted R-squared were 0.9916 and 0.9776, respectively, and this dem-onstrates that the proposed model was significant. The optimum values of maximum glucose-fed MFC sensitivity were observed at a mass of PVOH and initial glucose concentration values of ~& nbsp;15.293 wt% and ~& nbsp;0.718 mM, respectively. The result shows the achievement of 4.464 mu A mM(-1) cm(-2) sensitivity, which is significant compared with values of 4.443 mu A mM(-1) cm(-2) of sensitivity obtained after four experimental runs. Their sensitivity difference was found to be 0.021 (2.1%), and the model prediction was adequate to sense glucose in MFC.& nbsp;& nbsp;