Progressing the analysis of Improvised Explosive Devices: Comparative study for trace detection of explosive residues in handprints by Raman spectroscopy and liquid chromatography

Forensic analytical aspects of homemade explosives containing grocery powders and hydrogen peroxide

Homemade explosives become a significant challenge for forensic scientists and investigators. In addition to well-known materials such as acetone peroxide trimer, black powder, or lead azides, perpetrators often produce more exotic and less recognized Homemade Explosives (HMEs). Mixtures of hydrogen peroxide with liquid fuels are widely acknowledged as powerful explosives. Interestingly, similar explosive properties are found in mixtures of numerous solid materials with H2O2. Notably, powdered groceries, such as coffee, tea, grounded spices, and flour, are particularly interesting to pyrotechnics enthusiasts due to their easy production using accessible precursors, which do not attract the attention of security agencies. H2O2-based HMEs may become a dangerous component of improvised explosive devices for terrorists and ordinary offenders. For the four most powerful mixtures-HMEs based on coffee, tea, paprika, and turmeric-molecular markers useful for identification using the GC-MS technique have been proposed. Furthermore, the observed time-dependent changes in mixtures of H2O2 with these food products were studied and evaluated as a potential method for assessing the age of the evidence and reconstructing timelines of crimes. The paper also discusses the usefulness of FT-IR spectroscopy for identifying H2O2-based HMEs.

Raman spectroscopy combined with machine learning algorithms to detect adulterated Suichang native honey

Zhejiang Suichang native honey, which is included in the list of China’s National Geographical Indication Agricultural Products Protection Project, is very popular. This study proposes a method of Raman spectroscopy combined with machine learning algorithms to accurately detect low-concentration adulterated Suichang native honey. In this study, the native honey collected by local beekeepers in Suichang was selected for adulteration detection. The spectral data was compressed by Savitzky–Golay smoothing and partial least squares (PLS) in sequence. The PLS features taken for further analysis were selected according to the contribution rate. In this study, three classification modeling methods including support vector machine, probabilistic neural network and convolutional neural network were adopted to correctly classify pure and adulterated honey samples. The total accuracy was 100%, 100% and 99.75% respectively. The research result shows that Raman spectroscopy combined with machine learning algorithms has great potential in accurately detecting adulteration of low-concentration honey.

Influence of Ball Bearing Size on the Flight and Damage Characteristics of Blast-Driven Ball Bearings

This paper presents insights into the influence of ball size on the flight characteristics and damage of a ball bearing embedded in a rear detonated cylindrical charge. It includes results from a post-test damage analysis of ball bearings from previously reported experiments. Computational simulations using Ansys Autodyn were used to provide extra information about the velocity variation during flight and the damage sustained by the ball bearings during the blast event. The influence of bearing size (diameter and mass) was investigated using the validated simulation models to extend the dataset beyond the initial experimental work. The peak bearing velocity is influenced by the charge mass to ball bearing mass ratio and the aspect ratio of the charge. Larger ball bearings require extra momentum to accelerate them to higher velocities, but their higher surface area means a greater portion of the explosive charge is involved in transferring kinetic energy to the projectile. Tensile spalling was to be the major damage mechanism within the ball bearings. The charge aspect ratio also influenced the hydrostatic pressure propagation within the ball bearing itself, affecting the location and degree of internal cracking within the bearings. These findings will prove valuable to blast protection engineers considering the effects of embedded projectiles in improvised explosive devices.

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.

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.

Chemical Classification of Explosives

This work comprehensively reviews some fundamental concepts about explosives and their two commonly used classifications based on either their velocity of detonation or their application. These classifications are highly useful in the military/legal field, but completely useless for the chemical determination of explosives. Because of this reason, a classification of explosives based on their chemical composition is comprehensively revised, discussed and updated. This classification seeks to merge those dispersed chemical classifications of explosives found in literature into a unique general classification, which might be useful for every researcher dealing with the analytical chemical identification of explosives. In the knowledge of the chemical composition of explosives, the most adequate analytical techniques to determine them are finally discussed.

Methodologies Applied to Fingerprint Analysis

This systematic review deals with the last 10 years of research in analytical methodologies for the analysis of fingerprints, regarding their chemical and biological constituents. A total of 123 manuscripts, which fit the search criteria defined using the descriptor "latent fingermarks analysis," were selected. Its main instrumental areas (mass spectrometry, spectroscopy, and innovative methods) were analyzed and summarized in a specific table, highlighting its main analytical parameters. The results show that most studies in this field use mass spectrometry to identify the constituents of fingerprints, both to determine the chemical profile and for aging. There is also a marked use of mass spectrometry coupled with chromatographic methods, and it provides accurate results for a fatty acid profile. Additional significant results are achieved by spectroscopic methods, mainly Raman and infrared. It is noteworthy that spectroscopic methods using microscopy assist in the accuracy of the analyzed region of the fingerprint, contributing to more robust results. There was also a significant increase in studies using methods focused on finding new developers or identifying components present in fingerprints by rapid tests. This systematic review of analytical techniques applied to the detection of fingerprints explores different approaches to contribute to future studies in forensic identification, verifying new demands in the forensic sciences and assisting in the selection of studies for the progress of research.

Analysis of samples of explosives excavated from the Baltic Sea floor

After World War II, conventional and chemical ammunition containing mainly secondary and primary explosives was dumped in the sea. Explosives have medium toxicity to aquatic organisms, earthworms and indigenous soil microorganisms. Therefore, environmental monitoring is required, especially for dumped munitions. The main aspect of this work was to analyse the samples of lumps and sediments taken from the Baltic seabed. These samples were potentially explosives. The main goal of the study was to identify the type and composition of studied materials. In order to determine the chemical composition of samples of explosives, we used as follows: GC-MS/MS, LC-HRMS and NMR. Additionally, to determine the energetic properties we performed microcalorimetric-thermogravimetric analysis. Based on the obtained results, the composition of this explosive was TNT (41%), RDX (53%), aluminium powder (5%), and degradation products (below 1%). The resulting composition indicates that the analysed material can be classified in the "torpex" family, widely used during World War II. Regarding the results of the microcalorimetric analysis, we can conclude that excavated fragments of explosives are in very good condition and they still can detonate after being initiated. Therefore, there is a threat that they could be used for criminal or terrorist purposes.

Forensics: evidence examination via Raman spectroscopy

Forensic science can be broadly defined as the application of any of the scientific method to solving a crime. Within forensic science there are many different disciplines, however, for the majority of them, five main concepts shape the nature of forensic examination: transfer, identification, classification/individualization, association, and reconstruction. The concepts of identification, classification/individualization, and association rely greatly on analytical chemistry techniques. It is, therefore, no stretch to see how one of the rising stars of analytical chemistry techniques, Raman spectroscopy, could be of use. Raman spectroscopy is known for needing a small amount of sample, being non-destructive, and very substance specific, all of which make it ideal for analyzing crime scene evidence. The purpose of this chapter is to show the state of new methods development for forensic applications based on Raman spectroscopy published between 2015 and 2017.

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.

Selective Monitoring of Oxyanion Mixtures by a Flow System with Raman Detection

Raman spectroscopy is a selective detection system scarcely applied for the flow analysis of solutions with the aim of detecting several compounds at once without a previous separation step. This work explores the potential of a portable Raman system in a flow system for the selective detection of a mixture of seven oxyanions (carbonate, sulphate, nitrate, phosphate, chlorate, perchlorate, and thiosulphate). The specific bands of these compounds (symmetric stretching Raman active vibrations of carbonate at 1068 cm^−1, nitrate at 1049 cm^−1, thiosulphate at 998 cm^−1, phosphate at 989 cm^−1, sulphate at 982 cm^−1, perchlorate at 935 cm^−1, and chlorate at 932 cm^−1) enabled their simultaneous detection in mixtures. Although the oxyanions’ limit of detection (LOD) was rather poor (in the millimolar range), this extremely simple system is very useful for the single-measurement detection of most of the oxyanions in mixtures, without requiring a previous separation step. In addition, quantitative determination of the desired oxyanion can be performed by means of the corresponding calibration line. These are important advantages for controlling in-line processes in industries like those manufacturing fertilizers, pharmaceuticals, chemicals, or food, among others.

The discrimination of 72 nitrate, chlorate and perchlorate salts using IR and Raman spectroscopy

Inorganic oxidizing energetic salts including nitrates, chlorates and perchlorates are widely used in the manufacture of not only licit pyrotechnic compositions, but also illicit homemade explosive mixtures. Their identification in forensic laboratories is usually accomplished by either capillary electrophoresis or ion chromatography, with the disadvantage of dissociating the salt into its ions. On the contrary, vibrational spectroscopy, including IR and Raman, enables the non-invasive identification of the salt, i.e. avoiding its dissociation. This study focuses on the discrimination of all nitrate, chlorate and perchlorate salts that are commercially available, using both Raman and IR spectroscopy, with the aim of testing whether every salt can be unequivocally identified. Besides the visual spectra comparison by assigning every band with the corresponding molecular vibrational mode, a statistical analysis based on Pearson correlation was performed to ensure an objective identification, either using Raman, IR or both. Positively, 25 salts (out of 72) were unequivocally identified using Raman, 30 salts when using IR and 44 when combining both techniques. Negatively, some salts were undistinguishable even using both techniques demonstrating there are some salts that provide very similar Raman and IR spectra.

Toward wearable sensors: optical sensor for detection of ammonium nitrate-based explosives, ANFO and ANNM

An imine-functionalized polymer displays selective fluorimetric response to the component of ANFO and ANNM, ammonium nitrate and nitromethane!