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.
The process of drug discovery can be accelerated by increasing the information content of bioassays and by employing assay platforms that are amenable to high throughput screening techniques. In this paper, we demonstrate how the combination of soft lithography with controlled surface chemistry achieves these goals in a wide spectrum of bioassays. A number of soft lithographic methods can be used to generate micro-structures for the purposes of increasing assay density, diversity of test conditions and improving assay detection qualities. In addition, soft lithography, combined with specific surface chemistry modification procedures and protein engineering, may be used to control the localized molecular and biological properties of substrates, thereby enabling the development of new types of bioassays. The developed methodologies are simple, easily implemented, and lend themselves well to automation. Experimental results and prototypes are presented to illustrate the capabilities of these new techniques. For example, soft lithography and surface chemistry are employed for chemically patterning substrates, stenciling biological entities onto substrates and confining solutions. As a result, information-rich, highdensity bioassays can be obtained where biological targets, surface properties and medium solutions are carefully determined and controlled.
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.