Double pulse laser-induced breakdown spectroscopy of explosives: Initial study towards improved discrimination

Detecting trace explosive residues at standoff distances in real-time is a difficult problem. One method ideally suited for real-time standoff detection is laser-induced breakdown spectroscopy (LIBS). However, atmospheric oxygen and nitrogen contributes to the LIBS signal from the oxygen- and nitrogen-containing explosive compounds, complicating the discrimination of explosives from other organic materials. While bathing the sample in an inert gas will remove atmospheric oxygen and nitrogen interference, it cannot practically be applied for standoff LIBS. Alternatively, we have investigated the potential of double pulse LIBS to improve the discrimination of explosives by diminishing the contribution of atmospheric oxygen and nitrogen to the LIBS signal. These initial studies compare the close-contact (< 1 m) LIBS spectra of explosives using single pulse LIBS in argon with double pulse LIBS in atmosphere. We have demonstrated improved discrimination of an explosive and an organic interferent using double pulse LIBS to reduce the air entrained in the analytical plasma.     

Comparison of two laser-induced breakdown spectroscopy techniques for total carbon measurement in soils

The potentials of two advanced laser-induced breakdown spectroscopy (LIBS) techniques which are used to determine the total carbon content in soils have been examined. The first one is the combination of a single-pulse laser ablation with spark excitation of plasma plume triggering the gap between electrodes close to the target surface. The second one is a more conventional double-pulse LIBS. In both modes the calibration graphs have a nonlinear trend in the actual range of carbon contents and present a good R² value (0.97). In the combined laser-spark approach, using low-cost and portable laser instrumentation is possible, as well as inducing a micro-damage on the target surface. Certain regularities in the spectral line intensities of soil nutritious elements have been detected and appear to be connected to the total carbon content and to the soil origin.     

Detection of explosives in traces by laser induced breakdown spectroscopy: Differences from organic interferents and conditions for a correct classification

With the aim to study and to improve LIBS capability for detecting residues of energetic compounds in air surrounding, nine types of explosives and some potential interferents, placed in small quantities on a metallic support, were interrogated by a laser. Shot-to-shot behavior of the line intensities relative to the sample constituents was studied. The detected plasma was not stoichiometric and the line intensities, as well as their ratios, were changing even for an order of magnitude from one sampling point to another, particularly in the case of aromatic compounds. We explained some sources of such LIBS signal's behavior and this allowed us to establish a data processing procedure, which leads to a good linearization among the data sets. In this way, it was possible to determine some real differences between the LIBS spectra from explosives and interferents, and to correlate them with molecular formulas, with some known pathways for the molecule's decomposition and with successive chemical reactions in the plasma. Number spectral parameters, which distinguish the each studied explosive from other organic materials, were also determined and compared with previously published results relative to percentages of correct classifications for the same explosives. Experimental conditions for reliable recognition of the explosives by LIBS in air are also suggested, together with the parameters that should be considered or discarded from the classification procedure.     

Adsorption of oil into surfactant monolayers and structure of mixed surfactant+oil films

We describe a tensiometric method for determining the adsorption isotherm of an oil on a surfactant monolayer adsorbed at the air–water surface. The method involves measuring the surface pressure of oil, π_oil, as a function of its activity, a_oil, varied by changing the relative vapour pressure. We compare the isotherm of dodecane adsorption onto a C₁₂E₅ monolayer determined in this way with that measured directly using neutron reflectivity. The agreement between the two allows us to conclude that, at least for this system, addition of oil does not result in a change in the chemical potential of the surfactant. Structural analysis of the dodecane+C₁₂E₅ mixed film has been performed with neutron reflectivity using two contrasts. In one, only the surfactant chain region is highlighted, whilst in the other only the oil film is visible. We document, for the first time, changes in thickness and packing density of both the oil and surfactant chains in the mixed surfactant+oil layer upon increasing oil content. For a diverse range of other oil+surfactant systems, we have determined the initial (S_i) and equilibrium (S_e) spreading coefficients of oil by measuring π_oil following addition of liquid oil (at unit activity) to surfactant solution surfaces. Those systems in which S_e is close to zero display a repulsive van der Waals component of the disjoining pressure-oil film thickness isotherm, whilst with toluene as oil the calculated isotherm is attractive, consistent with non-spreading observed for this oil.     

ChemStable: a web server for rule-embedded naïve Bayesian learning approach to predict compound stability

Predicting compound chemical stability is important because unstable compounds can lead to either false positive or to false negative conclusions in bioassays. Experimental data (COMDECOM) measured from DMSO/H₂O solutions stored at 50 °C for 105 days were used to predicted stability by applying rule-embedded naïve Bayesian learning, based upon atom center fragment (ACF) features. To build the naïve Bayesian classifier, we derived ACF features from 9,746 compounds in the COMDECOM dataset. By recursively applying naïve Bayesian learning from the data set, each ACF is assigned with an expected stable probability (p _s ) and an unstable probability (p _uns ). 13,340 ACFs, together with their p _s and p _uns data, were stored in a knowledge base for use by the Bayesian classifier. For a given compound, its ACFs were derived from its structure connection table with the same protocol used to drive ACFs from the training data. Then, the Bayesian classifier assigned p _s and p _uns values to the compound ACFs by a structural pattern recognition algorithm, which was implemented in-house. Compound instability is calculated, with Bayes’ theorem, based upon the p _s and p _uns values of the compound ACFs. We were able to achieve performance with an AUC value of 84 % and a tenfold cross validation accuracy of 76.5 %. To reduce false negatives, a rule-based approach has been embedded in the classifier. The rule-based module allows the program to improve its predictivity by expanding its compound instability knowledge base, thus further reducing the possibility of false negatives. To our knowledge, this is the first in silico prediction service for the prediction of the stabilities of organic compounds.     

New challenges and insights in the detection and spectral identification of organic explosives by laser induced breakdown spectroscopy

With the objective of detection and identification of explosives, different organic compounds, including aromatic nitrocompounds, RDX, anthracene, 2,4-diaminotoluene (DAT), 4-methyl-3-nitroaniline (MNA) and pentaerythritol (PENT) have been analyzed by laser induced breakdown spectroscopy (LIBS). To avoid the secondary ionization and to discriminate between the spectral contribution due to air from that of the compound in the plasma generated in air, the emission signatures from atomic lines (C at 247.9 nm, H at 656.3 nm, N at 746.8 nm and O at 777.2 nm) and molecular bands (CN at 388.3 nm and C₂ at 516.5 nm) have been investigated in plasmas generated in air and in helium. The different possible pathways leading to the observation of molecular emissions have been studied, together with a discussion of the most useful tools for the explosives discrimination. Moreover, the effect of the laser fluence on the atomic and molecular emissions and their relationship with the oxygen balance of an organic explosive is presented.     

Laser-induced breakdown spectroscopy for detection of explosives residues: a review of recent advances, challenges, and future prospects

In this review we discuss the application of laser-induced breakdown spectroscopy (LIBS) to the problem of detection of residues of explosives. Research in this area presented in open literature is reviewed. Both laboratory and field-tested standoff LIBS instruments have been used to detect explosive materials. Recent advances in instrumentation and data analysis techniques are discussed, including the use of double-pulse LIBS to reduce air entrainment in the analytical plasma and the application of advanced chemometric techniques such as partial least-squares discriminant analysis to discriminate between residues of explosives and non-explosives on various surfaces. A number of challenges associated with detection of explosives residues using LIBS have been identified, along with their possible solutions. Several groups have investigated methods for improving the sensitivity and selectivity of LIBS for detection of explosives, including the use of femtosecond-pulse lasers, supplemental enhancement of the laser-induced plasma emission, and complementary orthogonal techniques. Despite the associated challenges, researchers have demonstrated the tremendous potential of LIBS for real-time detection of explosives residues at standoff distances. Figure This review discusses the application of laser-induced breakdown spectroscopy (LIBS) to the problem of explosive residue detection. LIBS offers the capability for real-time, standoff detection of trace amounts of residue explosives on various surfaces     

Vibrational emission analysis of the CN molecules in laser-induced breakdown spectroscopy of organic compounds

Laser-induced breakdown spectroscopy (LIBS) of organic materials is based on the analysis of atomic and ionic emission lines and on a few molecular bands, the most important being the CN violet system and the C₂ Swan system. This paper is focused in molecular emission of LIBS plasmas based on the CN (B²Σ–X²Σ) band, one of the strongest emissions appearing in all carbon materials when analyzed in air atmosphere. An analysis of this band with sufficient spectral resolution provides a great deal of information on the molecule, which has revealed that valuable information can be obtained from the plume chemistry and dynamics affecting the excitation mechanisms of the molecules. The vibrational emission of this molecular band has been investigated to establish the dependence of this emission on the molecular structure of the materials. The paper shows that excitation/emission phenomena of molecular species observed in the plume depend strongly on the time interval selected and on the irradiance deposited on the sample surface. Precise time resolved LIBS measurements are needed for the observation of distinctive CN emission. For the organic compounds studied, larger differences in the behavior of the vibrational emission occur at early stages after plasma ignition. Since molecular emission is generally more complex than that involving atomic emission, local plasma conditions as well as plume chemistry may induce changes in vibrational emission of molecules. As a consequence, alterations in the distribution of the emissions occur in terms of relative intensities, being sensitive to the molecular structure of every single material.     

A comparison of laser ablation inductively coupled plasma mass spectrometry,micro X-ray fluorescence spectroscopy,and laser induced breakdown spectroscopy for the discrimination of automotive glass

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), micro X-ray fluorescence spectroscopy (μXRF), and laser induced breakdown spectroscopy (LIBS) are compared in terms of discrimination power for a glass sample set consisting of 41 fragments. Excellent discrimination results (> 99% discrimination) were obtained for each of the methods. In addition, all three analytical methods produced very similar discrimination results in terms of the number of pairs found to be indistinguishable. The small number of indistinguishable pairs that were identified all originated from the same vehicle. The results also show a strong correlation between the data generated from the use of µXRF and LA-ICP-MS, when comparing µXRF strontium intensities to LA-ICP-MS strontium concentrations. A 266 nm laser was utilized for all LIBS analyses, which provided excellent precision (< 10% RSD for all elements and < 10% RSD for all ratios, N = 5). The paper also presents a thorough data analysis review for forensic glass examinations by LIBS and suggests several element ratios that provide accurate discrimination results related to the LIBS system used for this study. Different combinations of 10 ratios were used for discrimination, all of which assisted with eliminating Type I errors (false exclusions) and reducing Type II errors (false inclusions). The results demonstrate that the LIBS experimental setup described, when combined with a comprehensive data analysis protocol, provides comparable discrimination when compared to LA-ICP-MS and μXRF for the application of forensic glass examinations. Given the many advantages that LIBS offers, most notably reduced complexity and reduced cost of the instrumentation, LIBS is a viable alternative to LA-ICP-MS and μXRF for use in the forensic laboratory.     

Method validation parameters for drugs and explosives in ambient pressure ion mobility spectrometry

An approach using method validation (MV) parameters, otherwise known as analytical figures of merit was combined with electrospray ionization high performance ion mobility spectrometry (ESI-HPIMS) to describe an approach for evaluating drugs and explosives analysis in the field. MV parameters such as reduced mobility (K _o ), conditional reduced mobility (K _c ), resolving power (R _p ), theoretical plates (N), linearity, accuracy, precision, limit of detection (LOD), limit of quantitation (LOQ), repeatability, range, and reporting limit were investigated and developed for eleven drugs and six explosives. Our investigation estimated resolving power at 66 ± 0.64 for the ESI-HPIMS used. The LOD’s calculated ranged from 0.45–2.97 ng of material electrosprayed into the ESI-HPIMS. The LOQ’s calculated falls in the range 4.11–8.63 ng of material electrosprayed into the ESI-HPIMS. The key findings from this investigation were the following: K _c proves to be a measure of the identity of an explosive or drug ion; a parameter that may be applied to help aid IMS devices when detecting drugs and explosives. MV parameters, especially, K _c , introduced in this study is an effective parameter for establishing a unique identity of a drug or explosive. A control chart is an effective way to monitor the performance of an instrument and may be a useful tool for establishing reliability of confirmatory data in forensic investigations. MV parameters may be a reliable, accurate and unique identification marker for target drugs and explosives capable of differentiating these substances from false positive responses.     

The development of fieldable laser-induced breakdown spectrometer: No limits on the horizon

In this review, new trends in the development of fieldable instrumentation based on laser-induced breakdown spectroscopy (LIBS) and its recent applications is presented. Depending on the LIBS configuration we will distinguish between portable, remote and stand-off instruments. Moreover, the development of portable systems gives greater flexibility and also increases the range of LIBS applications. In general, portable instruments are employed in close-contact applications like immovable artworks, contaminated soils and environmental diagnostic, while remote and stand-off instruments are normally used in analytical applications at distances where access to the sample is difficult or hazardous. Although remote and stand-off instruments are both used for chemical analysis at distances, the instrumental configurations are completely different. In remote analysis, an optical fiber is employed to deliver the laser energy a certain distance. This approach has been usually restricted to industrial applications, bulk analysis in water, geological measurements and chemical analysis on nuclear stations. In the case of stand-off applications, the laser beam and the returning plasma light are transmitted in an open-path configuration. In this article we also discuss the instrumental requirements in the design of remote and stand-off instruments.     

Detection of liner surface defects in solid rocket motors using multilayer perceptron neural networks

Debonding problems along the propellant/liner/insulation interface are a critical point to the integrity and one of the major causes of structural failures of solid rocket motors. Current solutions are typically restricted to methods for assessing the integrity of the rocket motors structure and visually inspecting their components. In this context, this paper presents an improved algorithm to detect liner surface defects that may compromise the bonding between the solid propellant and the insulation. The use of Local Binary Patterns (LBP) provides a structural and statistical approach to texture analysis of liner sample images. Along with color information extraction, these two methods allow the representation of image pixels by feature vectors that are further processed by a Multilayer Perceptron (MLP) neural network classifier. The MLP neural network analyzes liner sample images and classifies each pixel into one of three classes: non-defect, foreign object, and defect. Several tests were executed varying different parameters to find the optimal MLP configuration, and as a result, the best classification accuracy of 99.08%, 90.66%, and 99.48% was achieved for the corresponding classes. Moreover, the defect size estimate showed that the MLP classifier correctly identified defects less than 1 mm long, with a relatively small number of training examples. Positive results indicate that the algorithm can identify liner surface defects with a performance similar to human inspectors and has the potential to assist or even automate the liner inspection process of solid rocket motors.     

Identification and discrimination of bacterial strains by laser induced breakdown spectroscopy and neural networks

A method based on laser induced breakdown spectroscopy (LIBS) and neural networks (NNs) has been developed and applied to the identification and discrimination of specific bacteria strains (Pseudomonas aeroginosa, Escherichia coli and Salmonella typhimurium). Instant identification of the samples is achieved using a spectral library, which was obtained by analysis using a single laser pulse of representative samples and treatment by neural networks. The samples used in this study were divided into three groups, which were prepared on three different days. The results obtained allow the identification of the bacteria tested with a certainty of over 95%, and show that only a difference between the bacteria can cause identification. Single-shot measurements were sufficient for clear identification of the bacterial strains studied. The method can be developed for automatic real time, fast, reliable and robust measurements and can be packaged in portable systems for non-specialist users.     

Fast and sensitive trace metal analysis in aqueous solutions by laser-induced breakdown spectroscopy using wood slice substrates

To perform fast and sensitive trace metal analysis in aqueous solutions by laser-induced breakdown spectroscopy (LIBS) based on only one single-pulse laser system, a wood slice has been used as a liquid absorber to transform liquid sample analysis to solid sample analysis using LIBS. High detection sensitivity and good reproducibility can be achieved with this approach. Calibration curves for five metal elements, Cr, Mn, Cu, Cd, and Pb under trace concentrations, have been obtained, and the limits of their detection were determined to be in the range of 0.029–0.59 mg L^− 1, 2–3 orders better than those obtained by directly analyzing liquid samples where the laser was focused on a liquid surface. The wood slice was very easy to handle and thus, the whole analysis process took only 4–5 min for each sample. This approach provides a more practical approach for fast and sensitive metal element analysis in aqueous solutions using LIBS, which is especially useful for monitoring toxic heavy metals in water.     

In-situ detection of single particles of explosive on clothing with confocal Raman microscopy

Confocal Raman microscopy is shown to detect picogram quantities of explosives in-situ on undyed natural and synthetic fibres, and coloured textile specimens leaving potentially evidential materials unaltered. Raman spectra were obtained from pentaerythritol tetranitrate (PETN), trinitrotoluene (TNT), and ammonium nitrate particles trapped between the fibres of the specimens. Despite the presence of spectral bands arising from the natural and synthetic polymers and dyed textiles, the explosive substances could be identified by their characteristic Raman bands. Furthermore, Raman spectra were obtained from explosives particles trapped between highly fluorescent clothing fibres. Raman spectra were collected from explosives particles with maximum dimensions in the range 5-10 μm. Spectra of the explosives on dyed and undyed clothing substrates were readily obtained in-situ within 90 s and without sample preparation.     

Hardness determination of bio-ceramics using Laser-Induced Breakdown Spectroscopy

Laser-Induced Breakdown Spectroscopy (LIBS) was applied to the analysis of bio-ceramic samples. The relationship between sample hardness and LIBS plasma properties was investigated, with comparison to conventional Vickers hardness measurements. The plasma excitation temperature T_e was determined using the line-to-continuum ratio for the Si (I) 288.16 nm emission line; we have demonstrated a linear relationship between sample surface hardness and plasma temperature. Results indicate that hardness determination based on measurements of T_e offers greater reproducibility than Vickers hardness measurements, under the conditions considered here. The validity of spectroscopic diagnostics based on LTE was confirmed.     

All-fiber-coupled laser-induced breakdown spectroscopy sensor for hazardous materials analysis

An all-fiber-coupled laser-induced breakdown spectroscopy (LIBS) sensor device is developed. A passively Q-switched Cr⁴⁺Nd³⁺:YAG microchip laser is amplified within an Yb fiber amplifier, thus generating high power laser pulses (pulse energy E_p = 0.8 mJ, wavelength λ = 1064 nm, repetition rate f_rep. = 5 kHz, pulse duration t_p = 1.2 ns). A passive (LMA) optical fiber is spliced to the active fiber of an Yb fiber amplifier for direct guiding of high power laser pulses to the sensor tip. In front of the sensor a plasma is generated on the surface to be analyzed. The plasma emission is collected by a set of optical fibers also integrated into the sensor tip. The spectrally resolved LIBS spectra are processed by application of principal component analysis (PCA) and analyzed together with the time-resolved spectra with neural networks. Such procedure allows accurate analysis of samples by LIBS even for materials with similar atomic composition. The system has been tested successfully during field measurements at the German Armed Forces test facility at Oberjettenberg.

The LIBS sensor is not restricted to anti-personnel mine detection but has also the potential to be suitable for analysis of bulk explosives and surface contaminations with explosives, e.g. for the detection of improvised explosive devices (IEDs).     

Influence of variable selection on partial least squares discriminant analysis models for explosive residue classification

Using a series of thirteen organic materials that includes novel high-nitrogen energetic materials, conventional organic military explosives, and benign organic materials, we have demonstrated the importance of variable selection for maximizing residue discrimination with partial least squares discriminant analysis (PLS-DA). We built several PLS-DA models using different variable sets based on laser induced breakdown spectroscopy (LIBS) spectra of the organic residues on an aluminum substrate under an argon atmosphere. The model classification results for each sample are presented and the influence of the variables on these results is discussed. We found that using the whole spectra as the data input for the PLS-DA model gave the best results. However, variables due to the surrounding atmosphere and the substrate contribute to discrimination when the whole spectra are used, indicating this may not be the most robust model. Further iterative testing with additional validation data sets is necessary to determine the most robust model.     

Standoff detection of explosives: critical comparison for ensuing options on Raman spectroscopy–LIBS sensor fusion

In general, any standoff sensor for the effective detection of explosives must meet two basic requirements: first, a capacity to detect the response generated from only a small amount of material located at a distance of several meters (high sensitivity) and second, the ability to provide easily distinguishable responses for different materials (high specificity). Raman spectroscopy and laser-induced breakdown spectroscopy (LIBS) are two analytical techniques which share similar instrumentation and, at the same time, generate complementary data. These factors have been taken into account recently for the design of sensors used in the detection of explosives. Similarly, research on the proper integration of both techniques has been around for a while. A priori, the different operational conditions required by the two techniques oblige the acquisition of the response for each sensor through sequential analysis, previously necessary to define the proper hierarchy of actuation. However, such an approach does not guarantee that Raman and LIBS responses obtained may relate to each other. Nonetheless, the possible advantages arising from the integration of the molecular and elemental spectroscopic information come with an obvious underlying requirement, simultaneous data acquisition. In the present paper, strong and weak points of Raman spectroscopy and LIBS for solving explosives detection problems, in terms of selectivity, sensitivity, and throughput, are critically examined, discussed, and compared for assessing the ensuing options on the fusion of the responses of both sensing technologies.     

Organic vapour sensing using localized surface plasmon resonance spectrum of metallic nanoparticles self assemble monolayer

The response of localized surface plasmon resonance (LSPR) spectra of gold and silver nanoparticles, and gold nanoshells to organic vapors was investigated. The surface area of nanomaterials was sufficiently high for quantitative adsorption of volatile organic compounds (VOCs). Surface adsorption and condensation of VOCs caused the environmental refractive index to increase from n = 1.00 in pure air to as high as n = 1.29 in near saturated toluene vapor. The extinction and wavelength shift of the LSPR spectra were very sensitive to changes in the surface refractive index of the nanoparticles. Responses of the LSPR band were measured with a real-time UV-vis spectrometer equipped with a CCD array detector. The response of silver nanoparticles to organic vapors was most sensitive in changes in extinction, while gold nanoshells exhibited red-shifts in wavelength (∼250 nm/RIU) when exposed to organic vapors. The LSPR spectral shifts primarily were determined by the volatility and refractive indices of the organic species. The T₉₀ response time of the VOC-LSPR spectrum was less than 3 s and the response was completely reversible and reproducible.