Interfacial capacitance using nanocomposite sensors as a deterministic bioelectrochemical information for complex...

The accuracy of electrochemical transduction in diagnostics is governed by the precise characterization of interfacial events. However, conventional electrical double-layer models often fail to capture the physicochemical complexity of real biological matrices. In biofluids, macromolecular crowding and adsorption create a heterogeneous electrode-electrolyte interface. It remains challenging to connect the variations in interfacial capacitance with specific physicochemical properties of the bulk sample. Here, we demonstrate that interfacial capacitance functions as quantifiable information of the biomatrix state, enabling rapid, label-free detection of water adulteration in milk through the newly established mathematical framework. Using developed high-density multiwalled carbon nanotube paste electrodes, we derive a constitutive model that resolves capacitive contributions as functions of the water volume fraction and the applied potential scan rate. Our results reveal that signal components traditionally discarded as background noise instead capture the non-linear modulation of capacitance induced by biomatrix variations, yielding a strong predictive correlation with reference adulteration levels (R² = 0.9962). These findings advance a paradigm shift in bioelectroanalysis by redefining interfacial capacitance as an information-rich variable, thereby establishing a foundation for biosensing in biochemically dense environments.