An Optimized Scanning Based AFM Fast Imaging Method

Atomic force microscopy (AFM) generally relies on a raster scanning method to obtain the sample morphology, which limits its scanning speed and application prospect. To solve this issue, this article proposes an optimized scanning-based fast imaging method to improve the scanning speed of the AFM system. More precisely, a class of novel tracking signals is constructed to achieve smooth scanning, for which the effect of the parameters is analyzed to provide a basis for trajectory optimization. The scanning performance of the proposed method is evaluated from such aspects as scanning uniformity, scanning coverage, scanning/imaging time, and imaging quality, wherein the scanning uniformity is analyzed with Hopkins statistic, while the scanning coverage is studied with the logistic regression. Based on these evaluation indexes, the scanning performance is investigated to determine the scanning parameters and generate the optimized trajectory. Moreover, a three-nearest-neighbor interpolation method is proposed to deal with the difficulty involved with nonlinear sampling imaging, which facilitates to reconstruct images with satisfactory quality. Finally, multiple convincing experiments and applications are implemented to further verify the good performance of the proposed method.