Strategic Design of Conductive Biopolymer Surface Coatings for Sensing and Remediation Applications

Abstract

Advancement in the utility of conductive polysaccharide-based (i.e., agar, alginate, pectin, cellulose) composite materials for charge transfer applications requires effective surface functionalization and dopant matching to overcome limitations in electron transfer in these dielectric materials. A promising approach is the design of a biomimetic nanocomposite material, coupled with Fe-carboxyl coordination chemistry to photoinitiate the radical polymerization of polyaniline (PANI) in a uniform manner throughout a templated polymer matrix. Results have shown the feasibility of establishing a responsive carbon-based sensor, capable of modulating charge transfer performance in the presence of differing dopants (i.e., hydrochloric acid, sulfuric acid, polyelectrolyte). The aim of this work is to expand upon previous findings by unraveling the dopant-specific charge transport mechanisms as they relate to the polarizability and mobility of the dopant. Additionally, a network-level understanding of how changing the identity of the polymer backbone and the conductive polymer (i.e., aniline, pyrrole, thiophene) alters the charge transfer efficiency and overall stability of the conductive matrix. Current-voltage (I-V) sweeps reveal that these n-doped conductive polymer nanocomposites show enhanced current flow and reduced internal resistance compared to non-functionalized controls. Lastly, once the network reached an equilibrated state, the addition of a model contaminant (mucin) showed a decrease in the potential; however, upon an applied voltage, the contaminant was removed, and the system recovered to its original state. Alternatively, the network was also evaluated for the remediation of model pollutants. Results show that upon an applied voltage in simulated textile wastewater, there was a 10% degradation of methylene blue within 1 hour. Thus, the backbone/dopant/conducting polymer relationship is critical to achieving optimal performance with various applications.