Publications

We demonstrate a pump-probe approach for the detection of organophosphonate compounds on substrates, in which the pump pulse fragments the parent molecule and the released phosphorous monoxide (PO) fragment is probed using laser-induced fluorescence. © 2011 OSA.

We review three photofragmentation detection approaches, describing the detection of (1) vapor-phase mercuric chloride by photofragment emission, (2) vapor-phase nitro-containing compounds by photofragmentation-ionization, and (3) surface-bound organophosphonate compounds by photofragmentation-laser-induced fluorescence. © 2010 Optical Society of America.

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As part of the U.S. Department of Homeland Security Detect-to-Protect program, a multilab [Sandia National Laboratories (SNL), Lawrence Livermore National Laboratories (LLNL), Pacific Northwest National Laboratory (PNNL), Oak Ridge National Laboratory (ORNL), and Los Alamos National Laboratory (LANL)] effort is addressing the need for useable detect-to-warn bioaerosol sensors for public facility protection. Towards this end, the SNL team is employing rapid fluorogenic staining to infer the protein content of bioaerosols. This is being implemented in a flow cytometry platform wherein each particle detected generates coincident signals of forward scatter, side scatter, and fluorescence. Several thousand such coincident signal sets are typically collected to generate a probability distribution over the scattering and fluorescence values. A linear unmixing analysis is performed to differentiate components in the mixture. After forming a library of pure component distributions from measured pure material samples, the distribution of an unknown mixture of particles is treated as a linear combination of the pure component distributions. The scattering/fluorescence probability distribution data vector a is considered the product of two vectors, the fractional profile f and the scattering/ fluorescence distributions from pure components P. A least squares procedure minimizes the magnitude of the residual vector e in the expression a = fP T + e. The profile f designates a weighting fraction for each particle type included in the set of pure components, providing the composition of the unknown mixture. We discuss testing of this analysis approach and steps we have taken to evaluate the effect of interferents, both known and unknown.

As part of the U.S. Department of Homeland Security Detect-to-Protect (DTP) program, a multilab [Sandia National Laboratories (SNL), Lawrence Livermore National Laboratories (LLNL), Pacific Northwest National Laboratory (PNNL), Oak Ridge National Laboratory (ORNL), and Los Alamos National Laboratory (LANL)] effort is addressing the need for useable detect-to-warn bioaerosol sensors for public facility protection. Towards this end, the SNL team is investigating the use of rapid fluorogenic staining to infer the protein content of bioaerosols. This is being implemented in a flow cytometer wherein each particle detected generates coincident signals of correlated forward scatter, side scatter, and fluorescence. Several thousand such coincident signal sets are typically collected to generate a distribution describing the probability of observing a particle with certain scattering and fluorescence values. These data are collected for sample particles in both a stained and unstained state. A linear unmixing analysis is performed to differentiate components in the mixture. In this paper, we discuss the implementation of the staining process and the cytometric measurement, the results of their application to the analysis of known and blind samples, and a potential instrumental implementations that would use staining.

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A discussion on an active gas imager that can potentially improve system performance and reliability in Smart Leak Detection and Repair covers conventional single-wavelength imaging; differential imaging; methane detection; modification for detecting fugitive emissions relevant to refineries and chemical plants; and system description. This is an abstract of a paper presented at the AWMA's 99th Annual Conference and Exhibition (New Orleans, LA 6/20-23/2006).

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