Identification and differentiation of commercial and military explosives via high performance liquid chromatography – high resolution mass spectrometry (HPLC-HRMS), X-ray diffractometry (XRD) and X-ray fluorescence spectroscopy (XRF): Towards a forensic substance database on explosives

Exploring gunshot residue detection in fingerprints by functionalized particle-coupled matrix-assisted laser desorption/ionization mass spectrometry

In firearm forensic investigations, detecting gunshot residue (GSR) is crucial for linking firearms to suspects and determining firing distance for forensic reconstruction. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF-MS) is emerging as a versatile and promising technological platform for fingerprint analysis. The capability of functionalized particles as an advanced dusting powder for visualizing latent fingerprints is widely recognized. This study aims to investigate the feasibility of employing functionalized magnetic fingerprint dusting powders for distinguishing regular and GSR fingerprints using MALDI-ToF-MS, thereby enhancing forensic evidentiary support. In this study, silica and carbon coated magnetic iron oxide particles were surface functionalized with phenyltriethoxy orthosilicate (PTEOS) or 3-aminopropyl triethoxysilane (APTES) to create hydrophobic and hydrophilic particles, respectively. Donor shooters' fingerprints, both GSR-containing and regular, were analyzed using these functionalized particles coupled with MALDI-ToF-MS. The results demonstrated effective fingerprint visualization and conclusive discrimination between GSR-containing and regular fingerprints through orthogonal partial least squares discriminant analysis. This technique provides enhanced sensitivity, speed, and adaptability compared to conventional methods, making it a promising choice for initial detection of GSR in latent fingerprints. Moreover, when subjected to thorough analysis using advanced instruments, it has the potential to significantly strengthen the probative value of fingerprint evidence in forensic investigations.

Evaluation of interferents in sampling materials for analysis of post-explosion residues (explosive emulsion/ANFO) using gas chromatography-mass spectrometry (GC/MS)

Chemical analysis aimed at identifying post-explosion residues is critical for investigating crimes or accidents involving explosives, establishing it as a vital area of forensic chemistry. In general, only trace amounts remain in samples analyzed for this purpose, making the presence of interferents a constant concern. Therefore, understanding the materials used from collection to sample preparation is essential for this type of analysis. This study focuses on organic contaminants in collection and laboratory materials analyzed by gas chromatography/mass spectrometry (GC/MS), complementing a previous study by Mauricio et al. (2020), which addressed inorganic contaminants in materials used for similar purposes in ion chromatography (IC). No prior studies have specifically investigated the potential organic interferences introduced by various materials commonly used in forensic laboratories for sample pre-processing, storage, and evidence collection in this context. Plastic films, bottle caps, disposable gloves, syringes, swabs, disposable cups, plastic tubes, and plastic pipettes were examined. GC/MS analyses revealed that certain materials, particularly syringe plungers, gloves, and plastic films, can interfere with the detection of post-explosion residues from explosive emulsions and ANFO (ammonium nitrate-fuel oil). These findings emphasize the importance of evaluating materials for potential interferences prior to sample collection and processing to minimize contamination risks. This study provides significant insights into how commonly used laboratory materials can impact forensic analysis, thereby enhancing the reliability of post-explosion residue analysis and supporting more accurate forensic investigations.

Improved preconcentration workflow for organic explosive traces in aqueous samples using solvent-assisted dispersive solid-phase extraction

The present study deals with the development of a solvent-assisted dispersive solid phase extraction method for the extraction of HMX, RDX, and TNT from aqueous samples. Benzophenone and methanol were selected as explosives sorbent and dispersive solvent respectively. Extraction parameters like pH, extraction time, amount of sorbent, volume and type of the disperser solvent and centrifuge time were optimized. Dispersion of 0.5 mL dispersive solution (4% (w/v) benzophenone in methanol) was performed by injection into the 5 mL aqueous sample (pH=7) using a 1.0 mL syringe. After centrifuge, the extracted explosives were analyzed by high performance liquid chromatography with ultraviolet detection (HPLC-Uv). The results indicated that the linear ranges with the correlation coefficients of 0.99 ≤ R2 were 1.6-204.6 μg L-1, 1.4-213.7 μg L-1 and 1.3-225.9 μg L-1 for HMX, RDX and TNT respectively. The limit of detection and limit of quantification obtained for each explosive were: 0.3 μg L-1 and 0.8 μg L-1 for HMX, 0.3 μg L-1 and 0.9 μg L-1 for RDX and 0.2 μg L-1 and 0.7 μg L-1 for TNT. Finally, the practical applicability of the developed method was evaluated for the extraction of some organic explosives in water samples followed their determination by HPLC-Uv.

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.

Development of a Gas Chromatography with High-Resolution Time-of-Flight Mass Spectrometry Methodology for BDNPA/F

Analysis of thermally labile compounds such as bis(2,2-dinitropropyl) acetal/formal (BDNPA/F), an energetic plasticizer, is usually performed via liquid chromatography (LC) as opposed to gas chromatography (GC) due to thermal decomposition in the inlet or the analytical column. While LC is a powerful technique, the analysis of volatile and semivolatile compounds is best suited to GC. Herein, a method was developed for a gas chromatograph coupled to high-resolution mass spectrometer (GC-HRMS), utilizing a programmable temperature vaporizer (PTV) inlet. A subset of the native compounds and several produced by the thermal decomposition of BDNPA/F in the inlet were evaluated by using multiple PTV inlet parameters to determine the optimal ramp rate and final temperature of the inlet (60 °C/min from 60 to 325 °C). The optimized GC-HRMS method nearly reduced all thermal decomposition, allowing for an excellent separation to be obtained. Furthermore, multiple ionization methods, including electron impact (EI), negative chemical ionization (NCI), and positive chemical ionization (PCI), were used to explore the many chemical differences between the BDNPA/F samples. A preliminary investigation of the benefits of using GC-HRMS to evaluate the chemical differences between unaged and aged BDNPA/F samples for unique insight was evaluated.

Enhancement of electrochemical detection performance towards 2,4,6-trinitrotoluene by a bottom layer of ZnO nanorod arrays

The ZnO nanostructure layers have been widely investigated as electrodes for sensors due to their intrinsic advantages such as high active area and low cost. In this work, to enhance the detection properties of ZnO nanostructural electrodes, self-organized ZnO nanorod arrays were synthesized using the chemical bath deposition (CBD) method on FTO glasses and ZnO nanoparticles. The fabricated ZnO electrodes on the two different substrates were characterized by SEM, TEM, XRD, and XPS. Subsequently, the detection performance of ZnO nanorod electrodes was electrochemically measured in a 2,4,6-trinitrotoluene (2,4,6-TNT) solution by CV and EIS. The differences in current densities between the ZnO electrodes were determined by the width of the ZnO nanorods, resulting in a ∼45% higher detection efficiency with F-CBD (the ZnO nanorods on FTO) electrodes compared to S-CBD (the ZnO nanorods on ZnO nanoparticles) electrodes.

Classification of local diesel fuels and simultaneous prediction of their physicochemical parameters using FTIR-ATR data and chemometrics

Class identification and prediction of physicochemical variables of eight diesel fuel brands collected from several stations within the Atlanta metropolitan area in the State of Georgia were investigated using principal component analysis (PCA), partial least squares discriminant analysis (PLS2-DA), and partial least squares regression (PLSR) as modeling techniques. The fuels were from a common pipeline, therefore, assumed to have very similar characteristics. Ten FTIR-ATR spectra per fuel brand were collected over the 650 - 4000 cm^-1 mid-infrared region, and the 80 x 3351 matrix was submitted to PCA to determine if there were any clusters. Following PCA, the 80 x 3351 matrix was split into a training matrix (56x3351) and a test matrix (24x3351). PLS2-DA models were built and evaluated for class identification using dummy variables (I,0) as input matrix. For physicochemical variable predictions, models were developed via PLSR using the FTIR-ATR spectra training matrix and physicochemical variables obtained from the Georgia Department of Agriculture Labs as input. Correlation coefficients of the eight fuels ranged from 0.9960 to 0.9998. PCA revealed all eight clusters of the diesel fuels, regardless of the tight correlation coefficients range. With a 1.0 ± 0.1 cut-off for fuel identification, the PLS2-DA models showed 100% correct predictions for four or five fuel brands, and 75% correct prediction for all eight fuel brands. PLSR predicted 100% correct physicochemical variables, with a RMSEP range of 0.019 to 1.132 for all 80 variables targeted.

Conductive printable electrodes tuned by boron-doped nanodiamond foil additives for nitroexplosive detection

An efficient additive manufacturing-based composite material fabrication for electrochemical applications is reported. The composite is composed of commercially available graphene-doped polylactide acid (G-PLA) 3D printouts and surface-functionalized with nanocrystalline boron-doped diamond foil (NDF) additives. The NDFs were synthesized on a tantalum substrate and transferred to the 3D-printout surface at 200 °C. No other electrode activation treatment was necessary. Different configurations of low- and heavy-boron doping NDFs were evaluated. The electrode kinetics was analyzed using electrochemical procedures: cyclic voltammetry and electrochemical impedance spectroscopy. The quasi-reversible electrochemical process was reported in each studied case. The studies allowed confirmation of the CV peak-to-peak separation of 63 mV and remarkably high heterogeneous electron transfer rate constant reaching 6.1 × 10⁻² cm s⁻¹ for 10 k ppm [B]/[C] thin NDF fitted topside at the G-PLA electrode. Differential pulse voltammetry was used for effective 2,4,6-trinitrotoluene (TNT) detection at the studied electrodes with a 87 ppb limit of detection, and wide linearity range between peak current density and the analyte concentration (0.064 to 64 ppm of TNT). The reported electrode kinetic differences originate primarily from the boron-dopant concentration in the diamond and the various contents of the non-diamond carbon phase.

Identification of Typical Solid Hazardous Chemicals Based on Hyperspectral Imaging

The identification of hazardous chemicals based on hyperspectral imaging is an important emergent means for the prevention of explosion accidents and the early warning of secondary hazards. In this study, we used a combination of spectral curve matching based on full-waveform characteristics and spectral matching based on spectral characteristics to identify the hazardous chemicals, and proposed a method to quantitatively characterize the matching degree of the spectral curves of hazardous chemicals. The results showed that the four hazardous chemicals, sulfur, red phosphorus, potassium permanganate, and corn starch had bright colors, distinct spectral curve characteristics, and obvious changes in reflectivity, which were easy to identify. Moreover, the matching degree of their spectral curves was positively correlated with their reflectivity. However, the spectral characteristics of carbon powder, strontium nitrate, wheat starch, and magnesium–aluminum alloy powder were not obvious, with no obvious characteristic peaks or trends of change in reflectivity. Except for the reflectivity and the matching degree of the carbon powder being maintained at a low level, the reflectivity of the remaining three samples was relatively close, so that it was difficult to identify with the spectral curves alone, and color information should be considered for further identification.

Nondestructive discrimination of red silk single fibers using total reflection X-ray fluorescence spectrometry and synchrotron radiation X-ray fluorescence spectrometry

In a strangulation case, when a necktie is used as a murder weapon, the dyed silk single fiber becomes an important evidence sample to solve the crime. Dyed silk single fibers contain elements, such as Cr and Co, which are obtained from dyeing using metal mordants. Currently, there are no nondestructive and sufficiently sensitive elementary analytical methods for the forensic analysis of single fibers. Therefore, in this study, eight commercially available red silk samples were collected and used for total reflection X-ray fluorescence (TXRF) and synchrotron radiation X-ray fluorescence (SR-XRF) spectrometry. Benchtop TXRF detected both S in the silk protein and Cl and Ca, which are elements absorbed from the environment by silkworms, but also Cr, which is a dyeing derivative for metal mordants. The presence of Cr and Zn, in addition to the Zn/Cr signal intensity ratios, was reported to be particularly useful identifiers. In SR-XRF, the presence of Cr, Co, Zn, and Br and the Zn/Cr signal intensity ratios were reported to be useful discriminating indicators. In this study, the nondestructive discrimination capabilities of TXRF and SR-XRF measurements for the samples were found to be 85.7% and 100%, respectively. Therefore, we propose a combination of TXRF and SR-XRF as a new nondestructive single fiber identification method for forensic science. Moreover, if partial destruction of a single fiber is allowed, the observation of the cross section and micro-Fourier-transform infrared spectroscopy measurements is useful for identifying red silk fibers.

Identification and analysis of organic explosives from post-blast debris by nuclear magnetic resonance

The growing threat of terrorism has triggered an urgent need to find effective ways to improve the analysis of explosives. This will aid forensic scientists in analysing the post-blast debris, which in turn helps the law enforcement agencies to frame suitable regulations. Analysis of post-blast debris is challenging as it hosts a massive amount of complexity. There are various techniques reported till date such as mass spectrometry, gas chromatography, high-performance liquid chromatography, Fourier transform infrared spectroscopy, and Raman spectroscopy for the analysis of post-blast residues. However, none of them has been able to identify the structural composition of the explosives. The current research study focuses on identifying the structural composition of the explosives from the post-blast debris using the nuclear magnetic resonance (NMR) technology. The post-blast analytes were extracted from soil samples, cleaned by the solid phase extraction (SPE) method and were rapidly analysed by the nuclear magnetic resonance spectrometer. This paper reports the identification of nitro organic explosives such as pentaerythritol tetranitrate (PETN), trinitrotoluene (TNT) and 2,4,6-trinitrophenylmethylnitramine (tetryl) in post-blast debris by 400 MHz nuclear magnetic resonance spectrometer.