Trace Detection Of Explosives Research Articles

Design of atomically-thin-body field-effect sensors and pattern recognition neural networks for ultra-sensitive and intelligent trace explosive detection

There has been enormous demand for detecting trace concentrations of chemical molecules and in particular low-volatile explosives through electronic instrumentation, which however, still faces significant shortcomings in both detectability and selectivity to date. In this work, we propose a novel sensor strategy that incorporates arrays of atomically-thin-body field-effect sensors for highly-scalable, ultra-sensitive trace explosive sensors with fast response to ultra-low analyte concentrations. Sensor performance and functionalization are theoretically simulated through system-level considerations using various kinetic, electrostatic, quantum mechanics, and drift-diffusion models. Moreover, by implementing custom-built neural network models for pattern recognition, we successfully achieved automatic, accurate detection of four different types of analytes with concentrations down to 0.02 part per trillion. The intelligent sensors have the capability to differentiate analyte types with 100% accuracy and predict the concentration values with ~10% of relative error simultaneously. We envision the proposed sensor platform, design metrics, deep learning methods and the combination of these innovations will be a promising yet practical solution towards ultra-sensitive trace explosive detection and can be extended to a wide range of molecular sensing applications.

Wireless Nano Senor Network (WNSN) for Trace Detection of Explosives: The Case of RDX and TNT

Wireless Nano Senor Network (WNSN) for Trace Detection of Explosives: The Case of RDX and TNT

UV-FIA: UV-induced fluoro-immunochemical assay for ultra-trace detection of PETN, RDX, and TNT

Fluorescence quenching based immunoassay format for the detection of a trace amount of some nitro-explosives with a high degree of selectivity is reported in this study. The immunoassay comprises anti-explosive antibodies functionalized microtitre strips specific to the targeted explosives, pentaerythritol tetranitrate (PETN), 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), and 2,4,6-trinitrotoluene (TNT). UV induced photolysis of nitro-explosive bound to targeted antibodies generates primarily nitrite ions which after the quick reaction with the detector molecule, 2,3-diaminonaphthalene (DAN), a fluorophore, quenches its fluorescence intensity, however, proportionately undergo cyclization to produce a highly fluorescent product, 2,3-naphthotriazole (NAT). The synthesized product, NAT, was verified using various chromatographic and spectrophotometric techniques. This newly developed antibody-based detection method, utilizing DAN dye, demonstrated a high selectivity towards PETN, RDX, and TNT. This method can be used as an economical testing kit for direct quantification of explosives, implying the great potential for quick, low-cost trace detection of explosives.

Unleashing the power from commercial off-the-shelf ion mobility spectrometer

Commercial off-the-shelf (COTS) ion mobility spectrometers (IMS) are widely used for the trace detection of drugs and explosives in security applications and are designed to be operated by non-technical users. In non-technical user mode, the detection algorithm of the COTS IMS evaluates the sample data against the programmed parameters for a specific and limited list of target substances, and reports if any of the programmed target substances are detected. The simplicity in operation is offset by the loss of analytical information available from the spectral details. In this work, we present for the first time a COTS IMS being operated in technical user mode in the field, analyzing packages selected for customs examination. The COTS IMS was used in combination with a Fourier transform infrared (FTIR) spectrometer to evaluate the effectiveness of presumptive field testing. Three case studies are presented to demonstrate the usefulness of operating COTS IMS in technical user mode: to corroborate results obtained from the FTIR, to indicate the presence of unprogrammed substances, and to indicate the presence of substances in minor to trace amounts that were not identified by the FTIR. This work also demonstrates the use of IMS in negative mode to identify the citrate salt form of a drug.

Infrared backscatter imaging spectroscopy of trace analytes at standoff

We are developing a proximal noncontact detection technique for trace amounts of hazardous materials using diffuse reflectance infrared spectral signatures. Spectroscopy is performed at a distance by tuning a quantum cascade laser system through its wavelength range (6-11 μm) as the active illumination source and collecting a portion of the diffusely reflected light from the target onto an MCT focal plane array. The signals from each collected frame are binned and processed into an image hypercube that contains spectral and spatial information. The primary motivation of this work is to protect the loss of life by detecting trace explosives on contaminated surfaces before attacks occur. Here, we present results from backscatter experiments on trace samples with low loading and fill factors on glass substrates and compare them with a conventional benchtop analysis technique, FTIR diffuse reflectance. The backscatter results illustrate the ability to detect explosives at 1 m distance at the nanogram level, which is beyond the capability of the benchtop FTIR diffuse reflectance measurement.

Graphene-Based Sensing of Gas-Phase Explosives

Graphene based sensors have shown excellent potential in the trace detection of specific gases which are hazardous to humans or environmentally toxic. Sensor designs incorporating pristine graphene, graphene oxide, and nanopatterned graphene have been the focus of much recent experimental and computational research. The application of graphene based sensors in the trace detection of explosives has seen relatively limited study, due in part to the difficulties of conducting experiments using the nitramine and aromatic explosives of central interest. Computational studies of explosive sensors are not subject to hazardous materials handling constraints, and may be used to complement experimental research on the development of low weight, low power, graphene-based sensors. Ab initio models of five different graphene nanoribbon sensor configurations have been developed, and their chemiresistive response to three widely used explosives and four background gases has been investigated. The results indicate that t...

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.

Porous Silicon Photonic Crystals Coated with Ag Nanoparticles as Efficient Substrates for Detecting Trace Explosives Using SERS.

Picric acid (PA) is an organic substance widely used in industry and military, which poses a great threat to the environment and security due to its unstable, toxic, and explosive properties. Trace detection of PA is also a challenging task because of its highly acidic and anionic character. In this work, silver nanoparticles (AgNPs)-decorated porous silicon photonic crystals (PS PCs) were controllably prepared as surface-enhanced Raman scattering (SERS) substrates using the immersion plating solution. PA and Rhodamine 6G dye (R6G) were used as the analyte to explore the detection performance. As compared with single layer porous silicon, the enhancement factor of PS PCs substrates is increased to 3.58 times at the concentration of 10−6 mol/L (R6G). This additional enhancement was greatly beneficial to the trace-amount-detection of target molecules. Under the optimized assay condition, the platform shows a distinguished sensitivity with the limit of detection of PA as low as 10−8 mol/L, the linear range from 10−4 to 10−7 mol/L, and a decent reproducibility with a relative standard deviation (RSD) of ca. 8%. These results show that the AgNPs-modified PS PCs substrates could also find further applications in biomedical and environmental sensing.

Recent Developments in Spectroscopic Techniques for the Detection of Explosives.

Trace detection of explosives has been an ongoing challenge for decades and has become one of several critical problems in defense science; public safety; and global counter-terrorism. As a result, there is a growing interest in employing a wide variety of approaches to detect trace explosive residues. Spectroscopy-based techniques play an irreplaceable role for the detection of energetic substances due to the advantages of rapid, automatic, and non-contact. The present work provides a comprehensive review of the advances made over the past few years in the fields of the applications of terahertz (THz) spectroscopy; laser-induced breakdown spectroscopy (LIBS), Raman spectroscopy; and ion mobility spectrometry (IMS) for trace explosives detection. Furthermore, the advantages and limitations of various spectroscopy-based detection techniques are summarized. Finally, the future development for the detection of explosives is discussed.

Rapid Quantitative Analysis of Multiple Explosive Compound Classes on a Single Instrument via Flow-Injection Analysis Tandem Mass Spectrometry.

A flow-injection analysis tandem mass spectrometry (FIA MSMS) method was developed for rapid quantitative analysis of 10 different inorganic and organic explosives. Performance is optimized by tailoring the ionization method (APCI/ESI), de-clustering potentials, and collision energies for each specific analyte. In doing so, a single instrument can be used to detect urea nitrate, potassium chlorate, 2,4,6-trinitrotoluene, 2,4,6-trinitrophenylmethylnitramine, triacetone triperoxide, hexamethylene triperoxide diamine, pentaerythritol tetranitrate, 1,3,5-trinitroperhydro-1,3,5-triazine, nitroglycerin, and octohy-dro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine with sensitivities all in the picogram per milliliter range. In conclusion, FIA APCI/ESI MSMS is a fast (<1 min/sample), sensitive (~pg/mL LOQ), and precise (intraday RSD < 10%) method for trace explosive detection that can play an important role in criminal and attributional forensics, counterterrorism, and environmental protection areas, and has the potential to augment or replace several of the existing explosive detection methods.

Impact of surface chemistry on the adhesion of an energetic small molecule to a conducting polymer surface

The modification of the surface chemistry of a film is a key strategy to enhance the binding of molecules of interest in various sensing and detection applications. For example, the adhesion of explosive residues to a swab is critical for the detection of trace explosives in air transportation environments, and it can be enhanced by increasing the affinity of the swab to target molecules through favored chemical interactions. Here, the surface chemistries of polypyrrole (PPy) films were systematically tuned through the electropolymerization of thin layers of N-substituted pyrrole monomers to evaluate their interactions with a model explosive compound, trinitrotoluene (TNT). The surface groups examined included carboxylic acid, methyl, and amino-phenyl groups, in order to address a wide range of chemical functionalities. The interaction between the functionalized PPy films with TNT was compared with the interactions between TNT and commercial swabbing materials in a vapor deposition process. The amount of TNT deposited from the vapor phase on each of the different films was quantified by the ultraviolet–visible (UV–vis) light absorbance of the Meisenheimer complex formed from the interaction of TNT with a basic solution. The PPy films with surface functionalities that allowed for hydrogen bonding displayed the highest deposition of TNT, while Teflon-coated commercial materials had the lowest interaction with TNT. Thus, this work provides insight into the surface groups of interest for the enhanced collection of trace explosives as well as the critical design criteria for the next generation of swabbing materials.

Aerobic Transformation of 2,4-Dinitrotoluene by Escherichia coli and Its Implications for the Detection of Trace Explosives.

DNT (2,4-dinitrotoluene), a volatile impurity in military-grade 2,4,6-trinitrotoluene (TNT)-based explosives, is a potential tracer for the detection of buried landmines and other explosive devices. We have previously described an Escherichia coli bioreporter strain engineered to detect traces of DNT and have demonstrated that the yqjF gene promoter, the sensing element of this bioreporter, is induced not by DNT but by at least one of its transformation products. In the present study, we have characterized the initial stages of DNT biotransformation in E. coli, have identified the key metabolic products in this reductive pathway, and demonstrate that the main DNT metabolite that induces yqjF is 2,4,5-trihydroxytoluene. We further show that E. coli cannot utilize DNT as a sole carbon or nitrogen source and propose that this compound is metabolized in order to neutralize its toxicity to the cells.IMPORTANCE The information provided in this article sheds new light both on the microbial biodegradability of nitroaromatic compounds and on the metabolic capabilities of E. coli By doing so, it also clarifies the pathway leading to the previously unexplained induction of the E. coli yqjF gene by 2,4-dinitrotoluene, an impurity that accompanies 2,4,6-trinitrotoluene (TNT)-based explosives. Our improved understanding of these processes will serve to molecularly enhance the performance of a previously described microbial bioreporter of buried landmines and other explosive devices, in which the yqjF gene promoter serves as the sensing element.

Trace detection of explosives with a unique large volume injection gas chromatography-mass spectrometry (LVI-GC-MS) method

Highly sensitive splitless programmed temperature vaporizing (PTV)-large volume injection (LVI)-GC-MS-negative chemical ionization (NCI) method was developed and validated for the trace detection of explosives and related compounds from environmental matrices.

A New Wipe-Sampling Instrument for Measuring the Collection Efficiency of Trace Explosives Residues.

Trace explosives detection, a crucial component of many security screening environments, commonly employs wipe-sampling. Since collection of an explosive residue is necessary for detection, it is important to have a thorough understanding of the parameters that affect the efficiency of collection. Current wipe-sampling evaluation techniques for explosive particles have their limits: manual sampling (with fingers or a wand) is limited in its ability to isolate a single parameter and the TL-slip/peel tester is limited to a linear sample path. A new wipe-sampling instrument, utilizing a commercial off-the-shelf (COTS) 3D printer repurposed for its XYZ stage, was developed to address these limitations. This system allowed, for the first time, automated two-dimensional wipe-sampling patterns to be studied while keeping the force and speed of collection constant for the length of the sampling path. This new instrument is not only capable of investigating the same parameters as current technology (wipe materials, test surfaces, forces of collection, and linear sample patterns), it has added capabilities to investigate additional parameters such as directional wipe patterns (i.e. "L" and "U" shapes, square, and serpentine) and allowing for multiple lines to be sampled during a single collection without the need for adjustments by the user. In this work, parametric studies were completed using 1,3,5-trinitroperhydro-1,3,5-triazine (RDX) and the COTS 3D printer for wipe-sampling to establish collection efficiencies for numerous scenarios. Trace explosives detection in field screening environments could be greatly improved with the ability to comprehensively investigate how a wide range of parameters individually affect collection by wipe-sampling. A screener who knows how to properly interrogate any given surface will be much more efficient at detecting trace explosives.

On the effectiveness of joint laser and gas chromatographic remote detection of explosive traces

On the effectiveness of joint laser and gas chromatographic remote detection of explosive traces

Recent advances in ambient mass spectrometry of trace explosives.

Ambient mass spectrometry has evolved rapidly over the past decade, yielding a plethora of platforms and demonstrating scientific advancements across a range of fields from biological imaging to rapid quality control. These techniques have enabled real-time detection of target analytes in an open environment with no sample preparation and can be coupled to any mass analyzer with an atmospheric pressure interface; capabilities of clear interest to the defense, customs and border control, transportation security, and forensic science communities. This review aims to showcase and critically discuss advances in ambient mass spectrometry for the trace detection of explosives.

Fabrication of a self-assembled and flexible SERS nanosensor for explosive detection at parts-per-quadrillion levels from fingerprints.

Apart from high sensitivity and selectivity of surface-enhanced Raman scattering (SERS)-based trace explosive detection, efficient sampling of explosive residue from real world surfaces is very important for homeland security applications. Herein, we demonstrate an entirely new SERS nanosensor fabrication approach. The SERS nanosensor was prepared by self-assembling chemically synthesized gold triangular nanoprisms (Au TNPs), which we show display strong electromagnetic field enhancements at the sharp tips and edges, onto a pressure-sensitive flexible adhesive film. Our SERS nanosensor provides excellent SERS activity (enhancement factor = ∼6.0 × 106) and limit of detection (as low as 56 parts-per-quadrillions) with high selectivity by chemometric analyses among three commonly military high explosives (TNT, RDX, and PETN). Furthermore, the SERS nanosensors present excellent reproducibility (<4.0% relative standard deviation at 1.0 μM concentration) and unprecedentedly high stability with a "shelf life" of at least 5 months. Finally, TNT and PETN were analyzed and quantified by transferring solid explosive residues from fingerprints left on solid surfaces to the SERS nanosensor. Taken together, the demonstrated sensitivity, selectivity, and reliability of the measurements as well as with the excellent shelf life of our SERS nanosensors obviate the need for complicated sample processing steps required for other analytical techniques, and thus these nanosensors have tremendous potential not only in the field of measurement science but also for homeland security applications to combat acts of terror and military threats.

Portable and Reliable Surface-Enhanced Raman Scattering Silicon Chip for Signal-On Detection of Trace Trinitrotoluene Explosive in Real Systems.

There is an increasing interest in the development of surface-enhanced Raman scattering (SERS) sensors for rapid and accurate on-site detection of hidden explosives. However, portable SERS methods for trace explosive detection in real systems remain scarce, mainly due to their relatively poor reliability and portability. Herein, we present the first demonstration of a portable silicon-based SERS analytical platform for signal-on detection of trace trinitrotoluene (TNT) explosives, which is made of silver nanoparticle (AgNP)-decorated silicon wafer chip (0.5 cm × 0.5 cm). In principle, under 514 nm excitation, the Raman signals of p-aminobenzenethiol (PABT) modified on the AgNP surface could be largely lit up due to the formation of electronic resonance-active TNT-PABT complex. In addition, the surface of AgNPs and silicon substrate-induced plasmon resonances also contribute the total SERS enhancement. For quantitative evaluation, the as-prepared chip features ultrahigh sensitivity [limit of detection is down to ∼1 pM (∼45.4 fg/cm2)] and adaptable reproducibility (relative standard deviation is less than 15%) in the detection of TNT standard solutions. More importantly, the developed chip can couple well with a hand-held Raman spectroscopic device using 785 nm excitation, suitable for qualitative analysis of trace TNT even at ∼10-8 M level from environmental samples including lake water, soil, envelope, and liquor with a short data acquisition time (∼1 min). Furthermore, TNT vapors diffusing from TNT residues (∼10-6 M) can be detected by using such a portable device, indicating its feasibility in determination of hidden samples.

Eye-safe near-infrared trace explosives detection and imaging.

We report the development of a non-contact no-reagents system operating in the eye-safe 1560-1800 nm wavelength range for standoff trace detection of explosives and high-speed imaging. Experimental results are provided for a number of chemicals including explosives on a variety of surfaces at sub-microgram per cm2 concentration. Chemically specific images were collected at 0.06 ms per pixel. Results from this effort indicate that the combination of modern industrial fiber lasers and nonlinear optical spectroscopy can address next generation eye-safe trace detection of chemicals including explosives.

Characterization of nitrated sugar alcohols by atmospheric-pressure chemical-ionization mass spectrometry.

The nitrated sugar alcohols mannitol hexanitrate (MHN), sorbitol hexanitrate (SHN) and xylitol pentanitrate (XPN) are in the same class of compounds as the powerful military-grade explosive pentaerythritol tetranitrate (PETN) and the homemade explosive erythritol tetranitrate (ETN) but, unlike for PETN and ETN, ways to detect MHN, SHN and XPN by mass spectrometry (MS) have not been fully investigated. Atmospheric-pressure chemical-ionization mass spectrometry (APCI-MS) was used to detect ions characteristic of nitrated sugar alcohols. APCI time-of-flight mass spectrometry (APCI-TOF MS) and collision-induced dissociation tandem mass spectrometry (CID MS/MS) were used for confirmation of each ion assignment. In addition, the use of the chemical ionization reagent dichloromethane was investigated to improve sensitivity and selectivity for detection of MHN, SHN and XPN. All the nitrated sugar alcohols studied followed similar fragmentation pathways in the APCI source. MHN, SHN and XPN were detectable as fragment ions formed by the loss of NO2 , HNO2 , NO3 , and CH2 NO2 groups, and in the presence of dichloromethane chlorinated adduct ions were observed. It was determined that in MS/MS mode, chlorinated adducts of MHN and SHN had the lowest limits of detection (LODs), while for XPN the lowest LOD was for the [XPN-NO2 ]- fragment ion. Partially nitrated analogs of each of the three compounds were also present in the starting materials, and ions attributable to these compounds versus those formed from in-source fragmentation of MHN, SHN, and XPN were distinguished and assigned using liquid chromatography APCI-MS and ESI-MS. The APCI-MS technique provides a selective and sensitive method for the detection of nitrated sugar alcohols. The methods disclosed here will benefit the area of explosives trace detection for counterterrorism and forensics. Copyright © 2016 John Wiley & Sons, Ltd.