Biomimetic Optical-Filter Detection System for Discrimination of Infrared Chemical Signatures

Abstract

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.

Discrimination Between Explosive Materials and Isomers Using a Human Color Vision-Inspired Sensing Method

“…This system was based off a similar approach to that previously reported in the literature for discrimination of different gas phase chemicals. 18,19 A significant difference between previously reported results and the current work is that this work is focused on evaluating the capability of the human-color vision-based IR filter approach to discriminate between different solid explosives on surfaces. A block diagram schematic, along with an image of the assembled breadboard system, is provided in Fig.…”

“…These calculated vector coordinates correlate with experimental results obtained from the laboratory optical breadboard. 18 Two sets of CDSD analyses were conducted; the first used a surface concentration of 100 µg/cm 2 for each explosive (RDX, PETN, and HMX) as the training data, and the second used an RDX sample with 500 µg/cm 2 and 100 µg/cm 2 PETN and HMX samples as training data. This allowed for the evaluation of CDSD analysis to discriminate RDX from PETN and HMX using a mixture of α-, and β-RDX (100 µg/cm 2 RDX sample) and α-RDX (500 µg/cm 2 sample) as training data.…”

“…Previous work has demonstrated that by using three infrared (IR) optical bandpass filters, high-confidence discrimination between chemical vapors with similar IR absorption bands is possible. 17–19…”

Non-spectroscopic sensing enabled by electro-optical reservoir computer

“…This sub-section describes the operating principle and the modelling procedures of the sensing component used in this work. It is inspired by the biomimetic design which previously has been demonstrated successfully for chemical [18][19][20] and biological sample [21] detection. The biomimetic sensor mimics the operation of the human eyes, which are capable of discriminating over 100,000 shades of (visible) colour over an environmental background despite being equipped with only three main types of cone cells [22,23].…”

“…Research on colour sensitivity of mantis shrimp (Haptosquilla trispinosa), which has 12 different types of photosensitive cell covering different light wavelengths and polarisations, however, found that higher number of unique photoreceptors does not mean an improvement in colour discimination [25]; Mantis's spectral discrimination Δ𝜆 is in the region of 15 to 25 nm in comparison to humans' which is in the region of 1 to 8 nm [25,26] over the visible light region. In [18][19][20][21], a trichromat, three-colour, biomimetic sensor has been constructed in the mid-infrared range of light and a multi-variate statistics tool based on a patented comparative-discrimination spectral detection (CDSD) technique [20,27] has been used to perform the vectorial signal processing. In the present work, we have adopted a biomimetic sensor with a similar trichromat architecture, but the EORC is used for signal processing.…”