MODELING THE DEGRADATION OF SCANNING ELECTROCHEMICAL MICROSCOPE IMAGES DUE TO SURFACE-ROUGHNESS

Visualization of surface roughness is widely used in electrochemical applications to provide a measure of the quality of a deposit or to determine the extent of localized corrosion. Generating high-resolution three-dimensional images of conducting or insulating surfaces in situ via scanning electrochemical microscopy (SECM) is one method. A three-dimensional image of a substrate is determined by measuring the variation in the tip current due to perturbations in the diffusion layer. Although surface roughness significantly distorts the resulting image, current models relating the tip current to the tip-substrate spacing assume that the substrate is perfectly flat. The quality of SECM images is enhanced currently by heuristic techniques. In this paper, a method for rigorously modeling the blurring process is presented. The model can be used as a basis for restoring SECM images. In particular, it may be feasible to resolve features smaller than the tip by scanning an image with a small sampling interval relative to the tip size and using knowledge of the blurring process to deconvolve the image.