Adaptive Approach Strategy for Efficient Scanning Ion Conductance Microscopy Based on Non-monotonic Approach Curves

Abstract Scanning ion conductance microscopy (SICM) enables high-resolution, noncontact, in situ characterization of specimens in liquid environments, providing simultaneous access to three-dimensional (3D) topographical, electrical, and mechanical properties. Despite its versatility, the inherent imaging principle limits scanning speed, presenting a significant challenge to further development. This work introduces an adaptive scanning strategy leveraging the distinctive nonmonotonic (“rise-then-fall”) approach curve observed in asymmetric self-referenced SICM (ASR-SICM). By employing a two-stage approach strategy, the nanopipette modulates its velocity based on its proximity to the sample surface, thereby enhancing both temporal resolution and imaging fidelity. The effectiveness of the proposed method was evaluated through finite element simulations and theoretical calculations, where the influences of electrolyte configuration and nanopipette structural parameters on the approach curve and feedback range were systematically analyzed. Additionally, the impact of different threshold settings on scanning time was examined. Subsequently, approach curves under different electrolyte conditions were measured on PDMS substrates, and the imaging accuracy was evaluated using fixed macrophages. Finally, comparative experiments on micropatterned polydimethylsiloxane (PDMS) substrates and MCF-7 cells demonstrate that the proposed method achieves equivalent average pixel rates up to 3.02 times and 1.85 times that of the conventional method, respectively, with the mean square error (MSE) on PDMS as low as 62.4% of the conventional value. These findings validate the potential of the adaptive scanning approach to overcome the scanning speed limitations of SICM, improving both imaging efficiency and quality.