Kevin J. Major

Comparative discrimination spectral detection method for the identification of vapors using overlapping broad spectral filters.

We present a comparative discrimination spectral detection approach for the identification of chemical vapors using broad spectral filters. We applied the method to flowing vapors of as-received and non-interacting mixtures for the detection of the volatile components of a target chemical in the presence of interferents. The method is based on measurements of the overall spectral signature of the vapors, where the interferent spectrum largely overlaps the target spectrum. In this work we outline the construction of a set of abstract configuration-space vectors, generated by the broadband spectral components from sampled chemical vapors, and the subsequent vector-space operations between them, which enable the detection of a target chemical by comparative discrimination from interferents. The method was applied to the C-H vibrational band from 2500 to 3500 cm−1, where there is large spectral signal overlap between the chosen target chemical and two interferents. Our results show clear detection and distinction of the target vapors without ambiguity.

Optical Filter Selection for High Confidence Discrimination of Strongly Overlapping Infrared Chemical Spectra

Optical filter-based chemical sensing techniques provide a new avenue to develop low-cost infrared sensors. These methods utilize multiple infrared optical filters to selectively measure different response functions for various chemicals, dependent on each chemicals infrared absorption. Rather than identifying distinct spectral features, which can then be used to determine the identity of a target chemical, optical filter-based approaches rely on measuring differences in the ensemble response between a given filter set and specific chemicals of interest. Therefore, the results of such methods are highly dependent on the original optical filter choice, which will dictate the selectivity, sensitivity, and stability of any filter-based sensing method. Recently, a method has been developed that utilizes unique detection vector operations defined by optical multifilter responses, to discriminate between volatile chemical vapors. This method, comparative-discrimination spectral detection (CDSD), is a technique which employs broadband optical filters to selectively discriminate between chemicals with highly overlapping infrared absorption spectra. CDSD has been shown to correctly distinguish between similar chemicals in the carbon-hydrogen stretch region of the infrared absorption spectra from 2800-3100 cm(-1). A key challenge to this approach is how to determine which optical filter sets should be utilized to achieve the greatest discrimination between target chemicals. Previous studies used empirical approaches to select the optical filter set; however this is insufficient to determine the optimum selectivity between strongly overlapping chemical spectra. Here we present a numerical approach to systematically study the effects of filter positioning and bandwidth on a number of three-chemical systems. We describe how both the filter properties, as well as the chemicals in each set, affect the CDSD results and subsequent discrimination. These results demonstrate the importance of choosing the proper filter set and chemicals for comparative discrimination, in order to identify the target chemical of interest in the presence of closely matched chemical interferents. These findings are an integral step in the development of experimental prototype sensors, which will utilize CDSD.

Filter-based chemical sensors for hazardous materials

The development of new techniques for the detection of homemade explosive devices is an area of intense research for the defense community. Such sensors must exhibit high selectivity to detect explosives and/or explosives related materials in a complex environment. Spectroscopic techniques such as FTIR are capable of discriminating between the volatile components of explosives; however, there is a need for less expensive systems for wide-range use in the field. To tackle this challenge we are investigating the use of multiple, overlapping, broad-band infrared (IR) filters to enable discrimination of volatile chemicals associated with an explosive device from potential background interferants with similar chemical signatures. We present an optical approach for the detection of fuel oil (the volatile component in ammonium nitrate-fuel oil explosives) that relies on IR absorption spectroscopy in a laboratory environment. Our proposed system utilizes a three filter set to separate the IR signals from fuel oil and various background interferants in the sample headspace. Filter responses for the chemical spectra are calculated using a Gaussian filter set. We demonstrate that using a specifically chosen filter set enables discrimination of pure fuel oil, hexanes, and acetone, as well as various mixtures of these components. We examine the effects of varying carrier gasses and humidity on the collected spectra and corresponding filter response. We study the filter response on these mixtures over time as well as present a variety of methods for observing the filter response functions to determine the response of this approach to detecting fuel oil in various environments.

Surface transmission enhancement of ZnS via continuous-wave laser microstructuring

Fresnel reflectivity at dielectric boundaries between optical components, lenses, and windows is a major issue for the optics community. The most common method to reduce the index mismatch and subsequent surface reflection is to apply a thin film or films of intermediate indices to the optical materials. More recently, surface texturing or roughening has been shown to approximate a stepwise refractive index thin-film structure, with a gradient index of refraction transition from the bulk material to the surrounding medium. Short-pulse laser ablation is a recently-utilized method to produce such random anti-reflective structured surfaces (rARSS). Typically, high-energy femtosecond pulsed lasers are focused on the surface of the desired optical material to produce periodic or quasi-periodic assemblies of nanostructures which provide reduced surface reflection. This technique is being explored to generate a variety of structures across multiple optical materials. However, femtosecond laser systems are relatively expensive and more difficult to maintain. We present here a low power and low-cost alternative to femtosecond laser ablation, demonstrating random antireflective structures on the surface of Cleartran ZnS windows produced with a continuous-wave laser. In particular, we find that irradiation with a low-powered (<10 mW), defocused, CW 325nm-wavelength laser produces a random surface with significant roughness on ZnS substrates. The transmission through the structured ZnS windows is shown to increase by up to 9% across a broad wavelength range from the visible to the near-infrared.

Evaluation of a biomimetic optical-filter based chemical sensor for detection of hazardous chemical vapors in the infrared

Detection of concealed hazardous materials is a pressing need for the global defense community. To address this need, the development of reliable and readily-deployable sensing devices is a key area of research. A multitude of infrared sensing techniques are being studied which allow for reliable sensing of concealed threats. Continued development in this field is working to increase the selectivity of such infrared sensors, while at the same time reducing their complexity, size and cost. We have recently developed a biomimetic optical filter based approach, based on human color vision, that utilizes multiple, broadband, overlapping infrared (IR) filters to clearly discriminate between hazardous target chemicals and interferents with very similar mid-IR spectral signatures. This technique was extensively studied in order to select filters which provide optimum selectivity for specific chemical sets. Using this knowledge, we designed and assembled a gas-phase sensor which uses three broadband mid-IR filters to detect and discriminate between a target chemical, fuel oil, and various interferents with strongly overlapping IR absorption bands in the carbon – hydrogen stretch region of the IR absorption spectrum 2700 cm-1 - 3300 cm-1 (3.0 μm - 3.7 μm). We present an overview of the design and performance of this filter-based system and explore the ability of this system to detect and discriminate between strongly overlapping target and interferent chemicals. The detection results using the filter-based system are compared to numerical methods to demonstrate the operation of this methodology. We present the results of experiments with both target and interferent chemicals present with chemicals both in and out of the detection set, and discuss future field development and application of this approach.

Optical performance of random anti-reflection structures on curved surfaces

Random anti-reflection structured surfaces (rARSS) have been reported to improve transmittance of optical-grade fused silica planar substrates to values greater than 99%. These textures are achieved using reactive-ion etching techniques and often result in transmitted spectra with no measurable interference effects (fringes) for a wide range of wavelengths. The inductively-coupled reactive ion plasma (ICP-RIE) used in the fabrication process to etch the rARSS is anisotropic, and thus well-suited for planar components. The improvement in spectral transmission has been found to be independent of optical incidence angles, for values from 0° to ±30°. Qualifying and quantifying the rARSS performance on curved substrates, such as concave and convex lenses, is required to optimize the fabrication of a desirable AR effect on opticalpower elements. In this work, rARSS was fabricated on fused silica plano-convex and plano-concave lenses, using an optimized ICP-RIE process, to maximize optical transmission in the range from 500 nm to 1100 nm. Results are presented from optical transmission tests of matched sets of varying curvature lenses with rARSS at a wavelength of 633nm. The transmission was measured as a function of radial distance from the apex of each lens, and shows the anisotropic dependence of the etch process. The transmittance profiles between the different sphericity of the tested lenses as well as the matched sets of concave and convex surfaces are compared. The measured angle-of-incidence dependence of planar silica versus silica lenses with rARSS is also presented.

Filter selection criteria for the discrimination of strongly overlapping chemical spectra

Increasing the selectivity of sensors, while at the same time reducing their complexity, size and cost, are challenges to the sensing community. To this end, an area of exploration has been the development of filter-based chemical sensors. We have recently introduced an approach that utilizes multiple, broadband, infrared (IR) filters to enable discrimination of target chemicals, in the presence of potential interferents that have IR spectral signatures in a limited waveband. Our analysis technique, comparative discrimination spectral detection (CDSD), utilizes a set of broad IR transmission filters, to discriminate between a specific target chemical and multiple interferents with strongly overlapping IR spectra. We have demonstrated the ability of this technique to correctly distinguish between chemicals in the carbon – hydrogen stretch region of the IR absorption spectrum (2700 – 3300 cm-1; 3.0 – 3.7 μm). We present a numerical study exploring the choices of desired optical filter sets, and the resulting overall discrimination by these filter sets. Filter parameter choices, such as the peak transmission position and bandwidth, are fundamental in filter-based chemical sensing discrimination systems. In this paper, we describe a systematic numerical approach used to explore how optical filter properties, and filter overlap affect corresponding discrimination results. We describe the interaction between the overlapping spectra and various filter sets on both target and interferent chemicals. We discuss which filter parameters provide optimum selectivity for specific target chemicals and how this information can be utilized to select filters for future direct-filter sensors based on this methodology.

Modulation of CdSe fluorescence using palladium nanoparticles

The increasing demand for clean, efficient energy has strongly influenced the direction of nanoscale research. One of the most promising areas of solar energy production lies with cadmium selenide quantum dots (CdSe QDs). As a means to improve the efficiency of solar energy conversion in QDs, metal nanoparticles have been examined. It has been shown that in certain systems the presence of these metal nanoparticles increase electron - hole charge separation thus providing extended times for electron harvesting. Most of the systems currently explored utilize gold nanoparticles, which is unsurprising due to the vast amount of synthetic methods for these particles and their plasmonic effects on the QDs. We seek to further examine these unique metal nanoparticle -quantum dot interactions through the study of CdSe QD - palladium nanoparticle systems. We employ both steady-state and time resolved ensemble fluorescence spectroscopy to observe the effects of increasing palladium nanoparticle concentrations on both the fluorescence intensity and lifetime of various CdSe QDs. We find that decreasing separation distance between the particles through increasing palladium concentration, leads to a stronger interaction between the particles. We find expected fluorescence quenching of the QDs at higher concentrations of palladium. At low palladium concentrations however we observe a unique fluorescence enhancement of the QDs. We use this data to explore the relative contributions of energy and electron transfer between the particles and determine the conditions under which the maximum effects of these interactions are observed.

Enabling standoff detection of hazardous materials using a fiber optic coupled quantum cascade infrared laser system

The global defense community requires new approaches for standoff detection of chemical, biological, radiological, nuclear and explosive (CBRNE) threats. Such standoff detection methods must be capable of discriminating the target hazardous materials from the environmental background. Therefore these sensors must exhibit high selectivity. High selectivity detection of CBRNE threats can be accomplished using infrared (IR) spectroscopy, which produces a unique spectral “fingerprint” of the target chemical, enabling discrimination of the target chemical from other chemicals in the background. Standoff detection using IR spectroscopy however requires that enough of the incident source light may be collected at the detector; therefore a high-power source is needed. Commercially available quantum cascade laser (QCL) sources are capable of projecting high power, coherent laser light at targets down range from the source. In order to collect complete IR spectra throughout the entire fingerprint region, the output of multiple QCL modules are combined into a single exit aperture. This is typically achieved using mirrors and other optics which are susceptible to vibrational and temperature misalignments in field systems. In order to provide a more ruggedized solution to combining the beam output of multiple QCL modules, we developed a unique chalcogenide optical fiber beam combiner which combines the output of four commercial QCL modules. This allows for scanning across a spectral range from 6.01 – 11.20 μm encompassing parts of both the IR functional groups and fingerprint regions. We demonstrate the ability of this QCL system to generate high quality IR spectra of hazardous materials.

High-confidence discrimination of explosive materials on surfaces using a non-spectroscopic optical biomimetic sensing method

Field detection of chemical, biological, radiological, nuclear and explosive (CBRNE) threats requires the development of highly selective sensors with low size, weight, power and cost (SWaP-c). Recent developments have demonstrated that an optical biomimetic sensing approach, based on human-eye color detection can provide high-confidence discrimination of target chemicals while rejecting potential interferents with similar chemical structures. This biomimetic sensing method operates by identifying differences in the overlap between target and interferent chemical infrared absorption bands utilizing three, overlapping, optical bandpass filters. This method is non-spectroscopic and requires only the use of commercially available, off-the-shelf optical components. This approach has been demonstrated for volatile chemical vapors in the mid-wave-infrared (3 – 5 μm). Based on this success, experimental studies of this biomimetic sensing approach have been expanded further into the long wave infrared spectral region (6 – 12 μm) and for detection of explosives on surfaces, including aluminum and plastics. We present discrimination results using this biomimetic sensing approach for explosive samples on surfaces in both the mid- and long- wave infrared. Numerical data, along with experimentally collected data, are discussed. We demonstrate that this method is capable of discriminating between similar explosives on surfaces as well as between these explosives and potential environmental interferents. We present the results of these experiments and discuss potential transition of this approach to future field-ready stand-off devices and applications.