In complex environments, the ability to identify the constituent chemicals within a mixture is extremely important. By utilizing a Pearson correlation algorithm to compare sets of multi‐wavelength resonance‐Raman signatures, we demonstrate the automated identification of chemicals within a mixture. Applying a linear mixture model, we are also able to estimate the fractional volumetric abundances contained therein. The multi‐wavelength resonance‐Raman signature used for identification is obtained by illuminating the unknown mixture with a series of 21 sequential laser wavelengths. This signature is then compared with the signatures of a set of known chemicals. By maximizing the Pearson correlation coefficient between the signature of the mixture and a weighted superposition of the signatures of the pure chemicals, we are able to determine the mixture components with 100% accuracy. The linear superposition of the selected chemicals, which minimizes the least squares distance between the signatures of the mixture, and its mathematical recreation determines the corresponding fraction, by volume, of each chemical within the mixture. Copyright © 2012 John Wiley & Sons, Ltd.

Abstract : The Swept Wavelength Optical Resonant Raman Detector (SWOrRD) at the Naval Research Laboratory is scanned through the 220 nm to 260 nm window of the ultraviolet and generates two dimensional spectral maps allowing for rapid identification of chemical materials. We create a library of chemicals whose Raman spectral features partially overlap and then measure the mixtures created by combinations of the library set. The library and mixtures are identically processed and loaded into a detection program. This system, utilizing a linear combination model enables the deconvolution of the multi chemical liquid mixture and a reconstitution of the fractional molecular abundances.

Recently, researchers at the Naval Research Laboratory have developed the SWORrD system for measuring two-dimensional Raman Spectra. The device consists of a tunable 2d ultraviolet laser that illuminates the sample at various wavelengths (210-300 nm) and collects a single Raman spectrum at each laser wavelength. The single spectra are combined to form a two-dimensional spectrum (laser wavelength by scattered wavenumber). In this paper we introduce a novel method for the detection of known agents ('targets') within measured 2d spectra. Our method is bases on 'linear mixed pixel' techniques from hyperspectral imagery; in particular, we generalize the Adaptive Subspace Detector (ASD) to a form suitable for SWORrD samples. Our detector uses the individual laser runs to define a set of points within wavenumber space; the set of points corresponding to a 2d spectra defines a particular subspace that contains each material. These subspaces are then used with ASD to identify targets. We include experimental results using real-world data to illustrate our results.

A cylindrical sample cell is adapted to the problem of increasing the scattered-light signal from an optically thin liquid sample. The ends of the cylinder are coated with specularly reflecting aluminum to increase the signal by reflecting the stimulating light beam through the medium multiple times. The circumference of the cylinder is similarly coated to increase the fraction of the emitted light that is collected and sent into the slit of a spectrometer. Such a cell can greatly increase the signal measured by an analysis system without any modifications to the system.

We are developing tunable-multi-wavelength resonance-Raman spectroscopy and algorithms to enable rapid detection and identification of bacteria and chemicals in complex environments. The system, dubbed SWOrRD, is capable of illuminating a sample containing many chemicals or biological agents with a sequence of laser wavelengths between 210nm and 2000nm; a range which encompasses the resonant frequencies of cells, microorganisms, cellular metabolites, and many chemicals; and measures the resonance-Raman spectra of light scattered from the sample at each laser wavelength. These multiple spectra, which contain much more information about the bond structure that is contained in a single spectrum, are analyzed by a linear-mixture algorithm, based on NRL's ORASIS, to determine the chemical and bacteriological constituents of the sample. The current status of the research will be described.

We present results of the design and testing of a modified optical Šolc notch filter for use in the deep ultraviolet (DUV, 190-300 nm) spectral range. The filter was designed to block a specific wavelength in this region. In addition, a sequence of blocked wavelengths occurs at wavelengths both shorter and longer than the specified wavelength. For Raman applications utilizing tunable lasers, the provision of multiple blocked wavelengths by a single filter may be especially useful. The filter design presented here produces extinction ratios >240 with transmission minima ~1 nm full width at half-maximum. Specific results are shown for the Raman spectra of Teflon excited at 248.4 nm.

The first two-dimensional (2D) resonance Raman spectra of TNT, RDX, HMX, and PETN are measured with an instrument that sequentially and rapidly switches between laser wavelengths, illuminating these explosives with forty wavelengths between 210 nm and 280 nm. Two-dimensional spectra reflect variations in resonance Raman scatter with illumination wavelength, adding information not available from single or few one-dimensional spectra, thereby increasing the number of variables available for use in identification, which is especially useful in environments with contaminants and interferents. We have recently shown that 2D resonance Raman spectra can identify bacteria. Thus, a single device that identifies the presence of explosives, bacteria, and other chemicals in complex backgrounds may be feasible.

Detection of microorganisms and chemicals using multi-wavelength resonance-Raman spectroscopy is described. Combined with a proper algorithm, this technique may lead to contactless sensor, capable of real-time detection of biological and chemical threats in complex environments.

We present the first measurements of two-dimensional resonant-Raman spectra and demonstrate the applicability of the method to the identification of bacteria, including differentiation of genetically similar species. A new device that sequentially illuminates bacteria with different ultraviolet wavelengths and measures a spectrum at each was developed for this purpose. We anticipate that information within such two-dimensional spectra will allow identification of bacteria and chemicals in environments containing multiple organisms and chemicals, leading, for example, to instruments that rapidly identify bacteria in hospital and food plant settings, for screening large populations, and for biochemical-threat warning systems.

: We present results of experiments on very-high Mach number (> 100) shocks and very-high Mach number and Reynolds number (> 100, 106) turbulence. Such high Mach number hydrodynamics are initiated with a powerful laser pulse driver. We show that shocks created with a laser driver follow the Taylor-Sedov self-similar solution and scale via the Sachs scaling law just like shocks created by more traditional methods. In one experiment we examined laser- produced-shock solid-surface interactions and observed expected phenomena such as Marsh stems and triple points, and also measured a new phenomenon termed a blast wave decursor. In second experiment we found that shocks become unstable if they propagate through a gas which has a low adiabatic index and we measured the growth rate of the instability. In a third experiment we have shown that a high Mach number shock dramatically enhances the structure of a turbulent field through which it passes and that the shock is itself badly distorted. This result is unexpected since common wisdom has it that high Mach number shocks would self-heal as they pass through a turbulent field. Turbulence, Shock.