Quantifying the localized electrical interface using a force-controlled scanning ion conductance microscopy

The electrical double layer (EDL) at solid-liquid interfaces provides a natural transduction pathway for understanding interfacial electrical properties without physical signal conversion and convolution. However, the EDL's ultrashort characteristic length and complex signal decoupling pose challenges for conventional techniques in achieving reliable measurements. Moreover, a critical gap remains in the underlying measurement theory. We hypothesize that a measurement platform combining EDL-mediated localized charge characterization with quantitative electrokinetic modeling can open new avenues for advancing interfacial science.

We developed a force-controlled scanning ion conductance microscopy (FCSICM) platform that enables high-resolution mapping of interface charge distribution. The ion current rectification (ICR) sensitivity was systematically evaluated across diverse interfacial conditions, including bias voltages, substrate polarities, and electrolyte concentrations. To bridge these observations and theories, a physically interpretable electrokinetic transport model was developed. Furthermore, the platform's versatility was demonstrated on diverse patterns and structures, where the high-aspect-ratio microgrooves are inaccessible to most conventional scanning probe microscopy tips.

Force-feedback ensures stable probe-EDL engagement. The ICR results reveal a pronounced dependence of FCSICM on interfacial conditions, with the rectification ratio peaking (I_PDL/I_Glass = 1.5) at higher bias voltage (±1 V) and lower concentration (1 mM) due to Debye length expansion and enhanced ionic selectivity. The quantitative electrokinetic model faithfully reproduces current-voltage characteristics (RMS error = 0.009), transforming ion rectification from qualitative observation into a quantitative analytical tool. Synchronous topography and surface charge mapping across engineered substrates yielded excellent consistency, clearly differentiating distinct material interfaces. These findings collectively establish FCSICM as a promising tool for understanding interfacial science.