In this study, we introduce an efficient approach to crossdisciplinary glucose biosensor technology through the development of hybrid nanocomposite materials. These materials were crafted from redoxactive polymers embedded in silica sol−gel matrices, intricately linked with phenazine mediators and reinforced with carbon nanotubes. By leveraging advanced analytical techniques, including NMR spectroscopy, scanning electron microscopy, and confocal microscopy, we characterized the structures of these redox-active polymers. Our investigation further addressed their electrochemical behaviors by employing cyclic voltammetry and impedance spectroscopy to elucidate their distinctive properties. Employing a complex analytical strategy and a computational approach, this study identified an optimal redox-active system that shows synergy between multiwalled nanotubes and engineered redox-active polymers. This polymer, which is composed of (3-aminopropyl)triethoxysilane and tetraethoxysilane at an optimized ratio of 20:80 vol %, is seamlessly integrated with a covalently bonded neutral red mediator. The resulting biosensor is capable of detecting glucose across a range of 0.01−0.92 mM with a low detection limit of 0.003 mM. Its operational stability is 1.9%, coupled with an unparalleled selectivity that holds promise for further enhancement through machine learning techniques. This machine learning breakthrough represents a significant leap forward in the accurate quantification of glucose in diverse samples, achieving a high degree of correlation with established methods. The composite material revealed in this research has implications for further applications in biosensing technology. The biocompatibility, nontoxicity, stability, and superior conductivity of the material underscore its potential in the field, opening possibilities for the development of blood glucose measurement techniques.
