| dc.description |
Metrological data from sample surfaces can be obtained by using a variety of profilometry methods. Atomic Force Microscopy (AFM), which relies on contact inter-atomic forces to extract topographical images of a sample, is one such method that can be used on a wide range of surface types, with possible nanometer range resolution. However, AFM images are commonly distorted by convolution, which reduces metrological accuracy. This type of distortion is more significant when the sample surface contains high aspect ratio features such as lines, steps or sharp edges - structures commonly found in semiconductor devices and applications. Aiming at mitigating these distortions and recovering metrology soundness, we introduce a novel image deconvolution scheme based on the principle of stereo imaging. Multiple images of a sample, taken at different angles, allow for separation of convolution artifacts from true topographic data. As a result, perfect sample reconstruction and probe shape estimation can be achieved in certain cases. Additionally, shadow zones, which are areas of the sample that cannot be probed by the AFM, are greatly reduced. Most importantly, this technique does not require a priori probe characterization. It also reduces the need for slender or sharper probes, which, on one hand, induce less convolution distortion but, on the other hand, are more prone to wear and damage, thus decreasing overall system reliability. |
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