Key challenges and prospects for optical standoff trace detection of explosives

Noncontact Detection of Absorbed Dinitrotoluene Using Laser Electrospray Mass Spectrometry

Noncontact detection of the explosive signature molecule 2,4-dinitrotoluene (DNT) from both metal and sand substrates using laser electrospray mass spectrometry (LEMS) is investigated. The measurement of DNT mass spectral signal intensity as a function of laser vaporization energy reveals that the optimal laser pulse energy for metal (0.4 mJ) is lower than that for dielectric substrates (1.2 mJ). The effects of laser spot area and laser power density on the LEMS analysis of DNT were studied at fixed laser pulse energies. The LEMS signal intensity of DNT is modeled as the product of laser spot area and laser power density. The model shows that both parameters contribute to the measured signal intensity, in agreement with experimental data. Furthermore, investigations of the DNT signal intensity as a function of nine different sampling tube positions were conducted to improve the capture efficiency of laser-vaporized analytes. The limit of detection (LoD) for DNT using LEMS is 15 ng through noncontact detection using a Venturi pump remote sampling system.

Nanosculptured tungsten oxide: High-efficiency SERS sensor for explosives tracing

The accurate and rapid identification of explosives and their toxic by-products is an important aspect of safety protocols, forensic investigations and pollution studies. Herein, surface-enhanced Raman scattering (SERS) is used to detect different explosive molecules using an improved substrate design by controllable oxidation of the tungsten surface and deposition of Au layers. The resulting furrow-like morphology formed at the intersection of the tungsten Wulff facets increases nanoroughness and improves the SERS response by over 300 % compared to the untreated surface. The substrate showed excellent reproducibility with a relative standard deviation of less than 15 % and a signal recovery of over 95 % after ultrafast Ar/O2 plasma cleanings. The detection limit for the "dried on a surface" measurement case was better than 10-8 M using the moving scanning regime and an acquisition time of 10 s, while for the "water droplets on a surface" scenario the LoD is 10-7, which is up to 2 orders of magnitude better than the UV-Vis spectroscopy method. The substrates were successfully used to classify the molecular fingerprints of HMX, Tetryl, TNB and TNT, demonstrating the efficiency of a sensor for label-free SERS screening in the practice of monitoring traces of explosives in the water medium.

Method to derive the infrared complex refractive indices n(λ) and k(λ) for organic solids from KBr pellet absorption measurements

Obtaining the complex refractive index vectors n(ν~) and k(ν~) allows calculation of the (infrared) reflectance spectrum that is obtained from a solid in any of its many morphological forms. We report an adaptation to the KBr pellet technique using two gravimetric dilutions to derive quantitative n(ν~)/k(ν~) for dozens of powders with greater repeatability. The optical constants of bisphenol A and sucrose are compared to those derived by other methods, particularly for powdered materials. The variability of the k values for bisphenol A was examined by 10 individual measurements, showing an average coefficient of variation for k peak heights of 5.6%. Though no established standards exist, the pellet-derived k peak values of bisphenol A differ by 11% and 31% from their single-angle- and ellipsometry-derived values, respectively. These values provide an initial estimate of the precision and accuracy of complex refractive indices that can be derived using this method. Limitations and advantages of the method are discussed, the salient advantage being a more rapid method to derive n/k for those species that do not readily form crystals or specular pellets.

Analytical Tools and Methods for Explosive Analysis in Forensics: A Critical Review

This review summarizes (i) compositions and types of improvised explosive devices; (ii) the process of collection, extraction and analysis of explosive evidence encountered in explosive and related cases; (iii) inter-comparison of analytical techniques; (iv) the challenges and prospects of explosive detection technology. The highlights of this study include extensive information regarding the National & International standards specified by USEPA, ASTM, and so on, for explosives detection. The holistic development of analytical tools for explosive analysis ranging from conventional methods to advanced analytical tools is also covered in this article. The most important aspect of this review is to make forensic scientists familiar with the challenges during explosive analysis and the steps to avoid them. The problems during analysis can be analyte-based, that is, interferences due to matrix or added molding/stabilizing agents, trace amount of parent explosives in post-blast samples and many more. Others are techniques-based challenges viz. specificity, selectivity, and sensitivity of the technique. Thus, it has become a primary concern to adopt rapid, field deployable, and highly sensitive techniques.

Hyperspectral imaging in forensic science: an overview of major application areas

Analysis of evidence is a challenge. Crime scene materials are complex, diverse, sometimes of an unknown nature. Forensic science provides the most critical applications for their examination. Chemical tests, analytical methods, and techniques to process the evidence must be carefully selected by the forensic scientist. Ideally, it may be interpreted, analyzed, and judged in the original context of the crime scene. In this sense, hyperspectral imaging (HSI) has been employed as an analytical tool that maintains the integrity of the samples/objects for multiple and sequential analysis and for counter-proof exams. This paper is an overview of forensic science trends for the application of HSI techniques in the last ten years (2011-2021). The examination of documents was the main area of exploration, followed by bloodstain analysis aging process; trace analysis of explosives and gunshot residue. Chemometric tools were also addressed since they are crucial to obtain the most important information from the samples. There are great challenges in applying HSI in forensic science, but there have been clear technological and scientific advances, and a solid foundation has been built for the use of HSI in real-life cases.

Instant Fingerprint Discrimination for Military Explosive Vapors by Dy3+ Doping a La2O3-Based Cataluminescence Sensor System

With the intensification of explosive-based terrorism attack and environmental concerns, the innovation of high-efficiency and portable sensors for facile, rapid, and reliable monitoring of explosives has become one of the major demands in societies. Herein, a reliable and easy-to-use cataluminescence sensor system based on Dy³⁺ doping La₂O₃ nanorod catalysts has been developed for the identification and detection of six types of military explosive vapors, including homologous compounds and even isomers. The efficient discrimination is to make full use of the thermodynamic and kinetic information that can be extracted from the catalytic oxidation process of explosive molecules on various sensing materials, that is, the response signal and response time to generate the fingerprint of each target compound, while the rapid detection of the strategy can be manifested in response toward six military explosive vapors within 2.5 s and recover within 4 s. Meanwhile, the quantitative analysis of the explosives by the sensor system was realized based on 0.8%Dy:La₂O₃ with optimal catalytic activity, and the detection limits of NB, m-MNT, m-DNB, PNT, DNT, and TNT can reach 0.62, 0.49, 0.63, 0.38, 0.023, and 0.067 μg mL^-1. In this research, we also constructed a novel sensor device and detection platform for explosive monitoring, which is of great significance for providing a new sensing principle for the efficient identification of explosives.

Remote Raman Detection of Trace Explosives by Laser Beam Focusing and Plasmonic Spray Enhancement Methods

Remote Raman spectroscopy is a technique that can detect and identify different target molecules through Raman vibrational modes from a remote distance. However, the current remote Raman technique is restricted by poor detection sensitivity, and it is still extremely challenging for trace explosive detection. Here, in order to achieve trace explosive detection from a remote distance, we innovatively propose two enhanced Raman spectroscopy methods by using a plasmonic spray and a laser beam focusing/Raman signal collecting instrument. In brief, a facile convex lens can converge the laser beam and collect Raman scattering signals, and a plasmonic spray can be used for surface-enhanced Raman scattering. Under the combination of the above enhancement methods, we achieve remote Raman detection of a variety of trace explosives with a concentration of ∼1 μg/cm² from a distance of 30 m. These novel methods demonstrate a simple approach that significantly improves the capability of remote detection of trace chemicals for further applications.

Spectral Considerations for Standoff Infrared Detection of RDX on Reflective Aluminum

This paper examines infrared spectroscopic effects for the standoff detection of an explosive material, hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), inkjet printed on an aluminum surface. Results of a spectroscopic study are described, using multiple optical setups. These setups were selected to explore how variations in the angles of incidence and collection from the surface of the material result in corresponding variations in the spectral signatures. The goal of these studies is to provide an understanding of these spectral changes since it affects standoff detection of hazardous materials on a reflective substrate. We demonstrate that variations in spectral effects are dependent on the relative surface concentration of the deposited RDX. We also show that it is reasonable to use spectroscopic data collected in a standard laboratory infrared spectrometer outfitted with a variable angle reflectometer set at 0° as reference spectra for data collected in a standoff configuration. These results are important to provide a systematic approach to understanding infrared (IR) spectra collection using standoff systems in the field, and to allow for comparison between such data, and data collected in the laboratory. Although the precise results are constrained to a specific material system (thin layers on a reflective substrate), the approach and general discussion provided are applicable to a broad range of IR standoff sensing techniques and applications.

Colorimetric optical nanosensors for trace explosive detection using metal nanoparticles: advances, pitfalls, and future perspective

Warfare threats and acts of terror are challenging situations encountered by defense agencies across the globe and are of growing concern to the general public, and security-minded policy makers. Detecting ultra-low quantities of explosive compounds in remote locations or under harsh conditions for anti-terror purposes as well as the environmental monitoring of residual or discarded explosives in soil, remains a major challenge. The use of metal nanoparticles (NPs) for trace explosive detection has drawn considerable interest in recent years. For nano-based explosive sensor devices to meet real-life operational demands, analytical parameters such as, long-shelf life, stability under harsh conditions, ease-of-use, high sensitivity, excellent selectivity, and rapid signal response must be met. Generally, the analytical performance of colorimetric-based nanosensor systems is strongly dependent on the surface properties of the nanomaterial used in the colorimetric assay. The size and shape properties of metal NPs, surface functionalisation efficiency, and assay fabrication methods, are factors that influence the efficacy of colorimetric explosive nanosensor systems. This review reports on the design and analytical performances of colorimetric explosive sensor systems using metal NPs as optical signal transducers. The challenges of trace explosive detection, advances in metal NP colorimetric explosive design, limitations of each methods, and possible strategies to mitigate the problems are discussed.

An autonomous bioluminescent bacterial biosensor module for outdoor sensor networks, and its application for the detection of buried explosives

We describe a miniaturized field-deployable biosensor module, designed to function as an element in a sensor network for standoff monitoring and mapping of environmental hazards. The module harbors live bacterial sensor cells, genetically engineered to emit a bioluminescent signal in the presence of preselected target materials, which act as its core sensing elements. The module, which detects and processes the biological signal, composes a digital record that describes its findings, and can be transmitted to a remote receiver. The module is an autonomous self-contained unit that can function either as a standalone sensor, or as a node in a sensor network. The biosensor module can potentially be used for detecting any target material to which the sensor cells were engineered to respond. The module described herein was constructed to detect the presence of buried landmines underneath its footprint. The demonstrated detection sensitivity was 0.25 mg 2,4-dinitrotoluene per Kg soil.

3D spectral fluorescence signature of cerium(III)-melamine coordination polymer: A novel sensing material for explosive detection

Hidden or buried explosives are the most common scenario by terrorist attacks; therefore explosive vapour detection is a vital demand. Explosives are electron deficient materials; the vicinity of explosives to fluorescent material can encounter electron migration. This study reports on facile synthesis of cerium (III)-melamine coordination polymer (CeM-CP) with exclusive optical properties. CeM-CP demonstrated novel spectral fluorescence properties over visible and infrared bands when stimulated with UVA LED source at 385 nm of 100 mW power. Stimulated CeM-CP demonstrated unique spectral fluorescence signal at 400, 700, and 785 nm. These fluorescent signals were correlated to cerium coordination with four nitrogen atoms; vacant orbital will be available for electron excitation migration. Spectral fluorescent signals were quenched as CeM-CP was subjected to TNT vapours. Hyperspectral imaging offered 3D plot of fluorescence signature. The main outcome is that complete fluorescence signal attenuation was achieved at 785 nm. CeM-CP could act as as a novel sensing element for explosive vapour detection.

Computer vision vs. spectrofluorometer-assisted detection of common nitro-explosive components with bola-type PAH-based chemosensors

Computer vision (CV) algorithms are widely utilized in imaging processing for medical and personal electronics applications. In sensorics CV can provide a great potential to quantitate chemosensors' signals. Here we wish to describe a method for the CV-assisted spectrofluorometer-free detection of common nitro-explosive components, e.g. 2,4-dinitrotoluene (DNT) and 2,4,6-trinitrotoluene (TNT), by using polyaromatic hydrocarbon (PAH, PAH = 1-pyrenyl or 9-anthracenyl) – based bola-type chemosensors. The PAH components of these chemical bolas are able to form stable, bright emissive in a visual wavelength region excimers, which allows their use as extended matrices of the RGB colors after imaging and digital processing. In non-polar solvents, the excimers have poor chemosensing properties, while in aqueous solutions, due to the possible micellar formation, these excimers provide “turn-off” fluorescence detection of DNT and TNT in the sub-nanomolar concentrations. A combination of these PAH-based fluorescent chemosensors with the proposed CV-assisted algorithm offers a fast and convenient approach for on-site, real-time, multi-thread analyte detection without the use of fluorometers. Although we focus on the analysis of nitro-explosives, the presented method is a conceptual work describing a general use of CV for quantitative fluorescence detection of various analytes as a simpler alternative to spectrofluorometer-assisted methods.

Simplified computer vision-assisted algorithm for the excimer fluorescence "turn-off" detection of nitro-analytes in aqueous media is described.

Highly fluorescent scandium-tetracarboxylate frameworks: selective detection of nitro-aromatic compounds, sensing mechanism, and their application

Recently, exploring new luminescent metal-organic frameworks (LMOFs) to selectively detect nitro-aromatic compounds (NACs) has been a hot topic of research. Simultaneously, it is still a challenging issue to understand the sensing mechanism of luminescent MOFs interacting with NACs at the molecular level. In this work, highly fluorescent Sc-tetracarboxylate frameworks (Sc-EBTC) have been successfully synthesized through a solvothermal method. The as-prepared Sc-EBTC crystals have good thermal stability, chemical stability as well as strong fluorescence (λ_ex = 320 nm and λ_em = 400 nm), and they can detect various NACs rapidly (as short as 30 s), selectively and efficiently by the "turn-off" fluorescence mechanism. The detection limits of Sc-EBTC toward 2,4-DNP and 4-NP are quantified to be 5.71 ppb and 6.26 ppb, respectively. Furthermore, to better understand the sensing mechanism, we attempt to use solid-state NMR and X-ray photoelectron spectroscopy to vividly characterize the charge transfer caused by the interaction between NAC molecules and the MOF at the molecular level. Additionally, test strips were made successfully for the practical detection of the NACs. This study demonstrates that the MOF constructed from the H₄EBTC ligands might be a promising candidate for the detection of trace NACs.

Recent Developments in the Field of Explosive Trace Detection

Explosive trace detection (ETD) technologies play a vital role in maintaining national security. ETD remains an active research area with many analytical techniques in operational use. This review details the latest advances in animal olfactory, ion mobility spectrometry (IMS), and Raman and colorimetric detection methods. Developments in optical, biological, electrochemical, mass, and thermal sensors are also covered in addition to the use of nanomaterials technology. Commercially available systems are presented as examples of current detection capabilities and as benchmarks for improvement. Attention is also drawn to recent collaborative projects involving government, academia, and industry to highlight the emergence of multimodal screening approaches and applications. The objective of the review is to provide a comprehensive overview of ETD by highlighting challenges in ETD and providing an understanding of the principles, advantages, and limitations of each technology and relating this to current systems.

Standoff pump-probe photothermal detection of hazardous chemicals

A novel pump-probe Photothermal methodology using Quartz Tuning Fork (QTF) detector has been demonstrated for the first time. A tunable mid-IR Quantum Cascade Laser (QCL) and a CW fixed wavelength visible laser have been used as the pump and probe beam respectively. The developed Photothermal (PT) technique is based on Quartz Tuning Fork (QTF) detector for the detection of hazardous/explosive molecules adsorbed on plastic surface and also in aerosols form. PT spectra of various trace molecules in the fingerprinting mid- infrared spectral band 7-9 µm from distance of 25 m have been recorded. The PT spectra of explosives RDX, TNT and Acetone have been recorded at very low quantities. Acetone is the precursor of explosive Tri-Acetone Tri-Phosphate (TATP). The experimentations using pump and probe lasers, exhibit detection sensitivity of less than 5 μg/cm2 for RDX, TNT powders and of ~ 200 nl quantity for Nitrobenzene (NB) and Acetone (in liquid form) adsorbed on surfaces, from a distance of ~ 25 m. The sensitivity of the same order achieved from a distance of 15 m by using only a mid-IR tunable pump laser coupled to QTF detector. Thus the pump-probe PT technique is more sensitive in comparison to single tunable QCL pump beam technique and it is better suited for standoff detection of hazardous chemicals for homeland security as well as for forensic applications.

Standoff Chemical Detection Using Laser Absorption Spectroscopy: A Review

Remote chemical detection in the atmosphere or some specific space has always been of great interest in many applications for environmental protection and safety. Laser absorption spectroscopy (LAS) is a highly desirable technology, benefiting from high measurement sensitivity, improved spectral selectivity or resolution, fast response and capability of good spatial resolution, multi-species and standoff detection with a non-cooperative target. Numerous LAS-based standoff detection techniques have seen rapid development recently and are reviewed herein, including differential absorption LiDAR, tunable laser absorption spectroscopy, laser photoacoustic spectroscopy, dual comb spectroscopy, laser heterodyne radiometry and active coherent laser absorption spectroscopy. An update of the current status of these various methods is presented, covering their principles, system compositions, features, developments and applications for standoff chemical detection over the last decade. In addition, a performance comparison together with the challenges and opportunities analysis is presented that describes the broad LAS-based techniques within the framework of remote sensing research and their directions of development for meeting potential practical use.

Interpol review of detection and characterization of explosives and explosives residues 2016-2019

This review paper covers the forensic-relevant literature for the analysis and detection of explosives and explosives residues from 2016-2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/Resources/Documents#Publications.

Raman spectroscopy for detection of ammonium nitrate as an explosive precursor used in improvised explosive devices

Raman spectroscopy was evaluated as a sensor for detection of ammonium nitrate (NH₄NO₃, AN), fuel oil (FO), AN-water solutions, and AN- and FO-soil mixtures deposited on materials such as glass, synthetic fabric, cardboard and electrical tape to simulate field conditions of explosives detection. AN is an inorganic oxidizing salt that is commonly used in fertilizers and mining explosives, however, due to its widespread accessibility, AN-based explosives are also utilized for the manufacture of improvised explosive devices (IED). Pure AN crystals were ground to powder size and deposited on several substrates for Raman analysis, whereas FO was analysed in a quartz cuvette. To simulate field conditions samples of powdered AN, AN-water solutions (0.1% to 10.0% AN w/w), AN-soil (50% to 90% AN w/w) and FO-soil (50% to 75% FO w/w) were prepared and deposited on the clutter materials. Raman spectra were acquired at integration times between 0.1 and 30 s, and 3 replicate Raman measurements were carried out for each sample. The spectral window observed ranged from 300 to 3800 cm^-1. Several characteristic Raman bands were found, namely, at 710 cm^-1 (NO₃^-) and 1040 cm^-1 (NO₃^-) for AN; 1440-1470 cm^-1 (CH) and 2800-3000 cm^-1 (CH) for FO; 3000-3500 cm^-1 (OH) for water; and 615 cm^-1 (CCl), 1254 cm^-1 (CH), 1400 cm^-1 (CH₂) and 1600 cm^-1 (aromatic ring) for polyvinyl chloride (PVC, electrical tape). The effect of the AN concentration and integration time on the total and net Raman intensities, relative standard deviation, signal-to-noise ratio and relative limit of detection was evaluated. The relative limit of detection of AN in water was 0.1% (1 mg/g), and absolute limit of detection was 1.0 μg. The optimum integration time (≈10 s) for the Raman sensor to capture the analyte signals was estimated based on the Raman figures of merit as a function of the integration time.

Optimization of ultraviolet Raman spectroscopy for trace explosive checkpoint screening

Raman spectroscopy has long been considered a gold standard for optically based chemical identification, but has not been adopted in non-laboratory operational settings due to limited sensitivity and slow acquisition times. Ultraviolet (UV) Raman spectroscopy has the potential to address these challenges through the reduction of fluorescence from background materials and increased Raman scattering due to the shorter wavelength (relative to visible or near-infrared excitation) and resonant enhancement effects. However, the benefits of UV Raman must be evaluated against specific operational situations: the actual realized fluorescence reduction and Raman enhancement depend on the specific target materials, target morphology, and operational constraints. In this paper, the wavelength trade-space in UV Raman spectroscopy is evaluated for one specific application: checkpoint screening for trace explosive residues. The optimal UV wavelength is evaluated at 244, 266, and 355 nm for realistic trace explosive and explosive-related compound (ERC) residues on common checkpoint materials: we perform semi-empirical analysis that includes the UV penetration depth of common explosive and ERCs, realistic explosive and ERC residue particle sizes, and the fluorescence signal of common checkpoint materials. We find that while generally lower UV wavelength provides superior performance, the benefits may be significantly reduced depending on the specific explosive and substrate. Further, logistical requirements (size, weight, power, and cost) likely limit the adoption of optimal wavelengths. Graphical abstract.

Non-Destructive Trace Detection of Explosives Using Pushbroom Scanning Hyperspectral Imaging System

The aim of this study was to investigate the potential of the non-destructive hyperspectral imaging system (HSI) and accuracy of the model developed using Support Vector Machine (SVM) for determining trace detection of explosives. Raman spectroscopy has been used in similar studies, but no study has been published which is based on measurement of reflectance from hyperspectral sensor for trace detection of explosives. HSI used in this study has an advantage over existing techniques due to its combination of imaging system and spectroscopy, along with being contactless and non-destructive in nature. Hyperspectral images of the chemical were collected using the BaySpec hyperspectral sensor which operated in the spectral range of 400–1000 nm (144 bands). Image processing was applied on the acquired hyperspectral image to select the region of interest (ROI) and to extract the spectral reflectance of the chemicals which were stored as spectral library. Principal Component Analysis (PCA) and first derivative was applied to reduce the high dimensionality of the image and to determine the optimal wavelengths between 400 and 1000 nm. In total, 22 out of 144 wavelengths were selected by analysing the loadings of principal components (PC). SVM was used to develop the classification model. SVM model established on the whole spectrum from 400 to 1000 nm achieved an accuracy of 81.11%, whereas an accuracy of 77.17% with less computational load was achieved when SVM model was established on the optimal wavelengths selected. The results of the study demonstrate that the hyperspectral imaging system along with SVM is a promising tool for trace detection of explosives.

Poly(thymine)-CuNPs: Bimodal Methodology for Accurate and Selective Detection of TNT at Sub-PPT Levels

Accurate, sensitive, and selective detection of explosives is of vital importance in antiterrorism and homeland security. Fluorescence sensors are prevalent for sensitive and fast in-field explosive detection but are sometimes compromised by accuracy and stability due to the similar structures of explosives, photobleaching, and complex sample matrixes. Herein, we developed a first bimodal methodology capable of both sensitive in-field fluorescence detection and accurate laboratory mass spectrometric quantification of 2,4,6-trinitrotoluene (TNT) by utilizing the characteristic fluorescent and mass spectrometric response of copper nanoparticles (CuNPs). An excellent selectivity was also realized by involving aptamer recognition. The methodology is capable of detecting TNT at subpart per trillion (PPT) levels, with a detection limit of 0.32 pg mL^-1 by inductively coupled plasma mass spectrometry (ICPMS) and 0.17 ng mL^-1 by fluorimetry. The signal response was accurate and stable for at least 60 days by ICPMS. Thanks to the biospecificity of the aptamer, this bimodal methodology is potentially applicable to a large panel of explosives.

Real time recognition of explosophorous group and explosive material using laser induced photoacoustic spectroscopy associated with novel algorithm for time and frequency domain analysis

Energy-rich bonds such as nitrates (NO₃^-) and percholorates (ClO₄^-) have an explosive nature; they are frequently encountered in high energy materials. These bonds encompass two highly electronegative atoms competing for electrons. Common explosive materials including urea nitrate, ammonium nitrate, and ammonium percholorates were subjected to photoacoustic spectroscopy. The captured signal was processed using novel digital algorithm designed for time and frequency domain analysis. Frequency domain analysis offered not only characteristic frequencies for NO₃^- and ClO₄^- groups; but also characteristic fingerprint spectra (based on thermal, acoustical, and optical properties) for different materials. The main outcome of this study is that phase-shift domain analysis offered an outstanding signature for each explosive material, with novel discrimination between explosive and similar non-explosive material. Photoacoustic spectroscopy offered different characteristic signatures that can be employed for real time detection with stand-off capabilities. There is no two materials could have the same optical, thermal, and acoustical properties.

Analytical procedure to assess the performance characteristics of a non-spectroscopic infrared optical sensor for discrimination of chemical vapors

An optical-filter-based sensor that was designed to mimic human color vision was recently developed. This sensor uses three mid-infrared optical filters to discriminate between chemicals with similar, strongly overlapping mid-infrared absorption bands. This non-spectroscopic technique requires no spectral scanning. This paper defines the selectivity and specificity of this biomimetic sensor. Receiver operating characteristic curves are presented for each target chemical. These results demonstrate that the sensor is highly selective and can provide discrimination with no false positives for three similar target chemicals-acetone, hexane, and fuel oil-while rejecting potential interferents.