Michael Sailor, William Trogler, Sonia Letant, Honglae Sohn, Stephane Content, Thomas Schmedake, Jun Gao, Peter Zmolek, Jamie Link, Yeshaiahu Fainman, Fang Xu, Paul Shames
Nanocrystalline porous silicon films (nanodots) and polymeric silicon wires (nanowires) have been used to detect chemicals in gas and liquid phase. Transduction mechanisms using quantum confinement derived photoluminescence and optical reflectivity have been used. Photoluminescence intensity is modulated by energy or electron transfer induced quenching, and a shift of the Fabry-Perot reflectivity fringes from thin nanocrystalline films occurs upon molecular absorption. Examples of irreversible detection and reversible sensing modes for explosives, nerve warfare agents, and various odors of commercial interest will be provided. A catalyst can be incorporated into the nanomaterials to provide specificity for the analyte of interest.
Porous silicon chips have been used to detect vapors of explosives and a simulant for the nerve agents Sarin, Soman, and GF using two different transduction modes: reflectivity and photoluminescence. Detection of nitroaromatic compounds is achieved by monitoring the photoluminescence of a nanocrystalline porous Si film on exposure to the analyte of interest in a flowing air stream. Photoluminescence is quenched on exposure to the nitroaromatic. Detection limits of 2 ppb and 1 ppb were observed for 2,4-dinitrotoluene, and 2,4,6-trinitrotoluene, respectively (exposure times of 5 min for each, in air). Specificity for detection is achieved in a two-channel system using catalytic oxidation of the nitroaromatic.
The detection of nitroaromatic molecules by porous silicon films has been explored using direct and indirect detection methods. In the direct method, detection is achieved by monitoring the photoluminescence of a nanocrystalline porous Si films upon exposure to the analyte of interest. Photoluminescence is quenched upon adsorption of the nitroaromatic, presumably via an electron transfer mechanism. For nitrobenzene a detection limit of 350 ppm (after an exposure time of < 2 minutes) was observed. For 2,4-dinitrotoluene, a much lower detection limit of 250 ppb (after an exposure time of < 6 minutes) was obtained. Both the detection limit and the response time of the material can be lowered by the use of a catalyst (PtO2 at 250 degree(s)C) in the carrier gas line upstream of the porous silicon detector. The enhanced sensitivity comes from catalytic oxidation of the nitroaromatic to NO2, which irreversibly oxidizes the surface of the porous Si, providing an integrating function. The demonstrated limit for NO2 detection is 70 ppb. A complementary detection technique involving measurement of spectral shifts of a porous Si film Fabry-Perot interferometer upon oxidation will also be presented.
We present a study on a high-speed optoelectronic system for implementing space variant transforms (SVT) in image and signal processing using a Hough Transform (HT) as an example. The HT has been found to be highly useful in applications requiring detection of lines, ellipses and hyperbolic shapes, such as radar detection and data fusion, topographical map analysis, etc. However, the implementation of a SVT such as HT, is computation and memory intensive, e.g. HT of an image of dimension N X N requires greater than N3 operations. All-electronic systems remain inadequate when real time SVT processing of large data sets is required. In this paper we show that an optoelectronic (OE) system employing parallel processing can perform such SVT requiring on the order of only N steps. We show that our proposed OE system can HT an input image of dimension N equals 1024 in 2.1 ms.
We introduce a novel method of modeling PLZT phase modulators. Traditionally, modeling has been based upon fitting the constant quadratic electro-optic coefficient to empirical data. Our characterization has shown that the electro-optic coefficient is not a constant and that the electro-optic effect saturates at electric field strengths that exist in standard surface electrode device configurations. We have also found that the additional effects of light scattering and depolarization, which depend on the strength of the applied electric field, are significant factors for modeling device design and optimization.
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