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

Kevin J. Major; Kenneth J. Ewing; Jasbinder S. Sanghera; Thomas C. Hutchens; Menelaos K. Poutous; Matthew G. Potter; Christopher R. Wilson; Ishwar D. Aggarwal; Mikella E. Farrell; Ellen L. Holthoff; Paul M. Pellegrino

doi:10.1117/12.2304349

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16 May 2018 High-confidence discrimination of explosive materials on surfaces using a non-spectroscopic optical biomimetic sensing method

Kevin J. Major, Kenneth J. Ewing, Jasbinder S. Sanghera, Thomas C. Hutchens, Menelaos K. Poutous, Matthew G. Potter, Christopher R. Wilson, Ishwar D. Aggarwal, Mikella E. Farrell, Ellen L. Holthoff, Paul M. Pellegrino

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Proceedings Volume 10629, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XIX; 106290P (2018) https://doi.org/10.1117/12.2304349
Event: SPIE Defense + Security, 2018, Orlando, Florida, United States

Abstract

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.

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Kevin J. Major, Kenneth J. Ewing, Jasbinder S. Sanghera, Thomas C. Hutchens, Menelaos K. Poutous, Matthew G. Potter, Christopher R. Wilson, Ishwar D. Aggarwal, Mikella E. Farrell, Ellen L. Holthoff, and Paul M. Pellegrino "High-confidence discrimination of explosive materials on surfaces using a non-spectroscopic optical biomimetic sensing method", Proc. SPIE 10629, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XIX, 106290P (16 May 2018); https://doi.org/10.1117/12.2304349

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