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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.

The polymers IP-Dip, IP-L, and IP-S are among the most commonly used photo-resists employed for the rapid prototyping of optical components using two-photon polymerization. Despite the widespread use of these polymers, measured data on their optical properties is scarce. Recently, the refractive index n of these polymers has been determined in the visible and nearinfrared spectral range. However, the accurate optical properties including extinction coefficient κ in the ultraviolet spectral range have not been reported yet. Here we report on accurate, ellipsometric measurements of the complex dielectric functions of two-photon polymerized IP-Dip, IP-L, and IP-S in the spectral range from 210 nm to 1500 nm. Model dielectric functions composed of oscillators with Lorentz, Gaussian, and Tauc-Lorentz broadenings are presented for all investigated polymers.

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Optical-filter-based chemical sensors have the potential to dramatically alter the field of hazardous materials sensing. Such devices could be constructed using inexpensive components, in a small and lightweight package, for sensing hazardous chemicals in defense, industrial, and environmental applications. Filter-based sensors can be designed to mimic human color vision. Recent developments in this field have used this approach to discriminate between strongly overlapping chemical signatures in the mid-infrared. Reported work relied on using numerically filtered FTIR spectra to model the infrared biomimetic detection methodology. While these findings are encouraging, further advancement of this technique requires the collection and evaluation of directly filtered data, using an optical system without extensive numerical spectral analysis. The present work describes the design and testing of an infrared optical breadboard system that uses the biomimetic mammalian color-detection approach to chemical sensing. The set of chemicals tested includes one target chemical, fuel oil, along with two strongly overlapping interferents, acetone and hexane. The collected experimental results are compared with numerically filtered FTIR spectral data. The results show good agreement between the numerically filtered data model and the data collected using the optical breadboard system. It is shown that the optical breadboard system is operating as expected based on modeling and can be used for sensing and discriminating between chemicals with strongly overlapping absorption bands in the mid-infrared.