A silicon micromachined force sensor for scanning force microscopy.

Abstract

This research illustrates the application of silicon micromachining techniques to the fabrication of an integrated force sensor for a scanning force microscope (SFM). The essential element of the SFM is a microprobe which uses a cantilever equipped with a sharp stylus as a force sensor for scanning a surface. To yield reproducible SFM-mapped images, it is crucial that the physical dimensions of the cantilever and its stylus be consistent. A batch process using silicon micromachining techniques for fabricating the microprobes has been developed. The process ensures consistent dimensions for the cantilevers and their sharp scan tips. Scanning electron micrographs of the scan tips show that curvature radii of these tips are less than 60 nm and the tip aspect ratios are about 1.25:1. The process is also compatible with the fabrication of on-chip integrated circuits for multi-channel scan capability and electronic read-out. SFM imaged surface topographies from various samples demonstrate that an SFM can achieve resolutions from 1 nm to 10 nm. Comparing the SFM images produced by tips fabricated in our facility with images produced by commercial tips, the former images represent more accurate surface topographies than the later ones. Scanning results also illustrate the significant artifact due to the effects of tip geometry on an SFM image. Tip-geometry-induced artifacts can be reduced by using appropriate image processing techniques provided knowledge of the tip geometry is reliable. The tip geometry can be reconstructed by scanning well-known calibration patterns and performing image processing on the scanning result. Cylinders having diameters of 4 $\mu$m and heights of 1.2 $\mu$m fabricated in our facility were used as calibration patterns. The close match between the reconstructed tip image and the scanning electron micrograph of the tip confirms the validity of our approach. It also demonstrates the importance of having an accurate imaging model for the surface recovery.