Paper
2 June 2003 Nano precision AFM imaging by stereo deconvolution: theory; applications, and experimental validation
Bernardo D. Aumond, Kamal Youcef-Toumi
Author Affiliations +
Abstract
Atomic Force Microscopy (AFM), a modality of SPM, has been used for capturing metrological data of a wide range of surface types, with possible nanometer range resolution. However, AFM images of high aspect ratio surface features such as lines, steps or sharp or sharp edges, are commonly distorted by convolution, which reduces metrological accuracy and data repeatability. In order to mitigate these limiting factors, we developed and implemented a novel AFM imaging mode and image deconvolution procedure that utilizes the principle of geometric reconstruction by stereo imaging. In this scheme, we combine multiple images of a sample, taken at different angles, allowing for the separation of convolution artifacts form true topographic data. The method is iteraive from an algorithmic standpoint and converges to a geometric reconstruction of the sample with minimal uncertainty. Most importantly, this technique does not require a priori probe characterization. It also reduces the need for slender or sharper probes, which are more prone to wear and damage, leading to loss of system reliability. In this paper, we briefly cover the fundamentals of the method and proceed to analyze validation result obtained via both simulation and experimentation. Resulting reconstructions obtained with this novel AFM stereo imaging approach are directly compared to white light interferometer and SEM data.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bernardo D. Aumond and Kamal Youcef-Toumi "Nano precision AFM imaging by stereo deconvolution: theory; applications, and experimental validation", Proc. SPIE 5038, Metrology, Inspection, and Process Control for Microlithography XVII, (2 June 2003); https://doi.org/10.1117/12.482649
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KEYWORDS
Atomic force microscopy

Statistical analysis

Convolution

Deconvolution

Metrology

Image processing

Interferometers

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