Study of consumer fireworks post-blast residues by ATR-FTIR

Machine Learning Enhanced Optical Spectroscopy for Disease Detection

Optical spectroscopy plays an important role in disease detection. Improving the sensitivity and specificity of spectral detection has great importance in the development of accurate diagnosis. The development of artificial intelligence technology provides a great opportunity to improve the detection accuracy through machine learning methods. In this Perspective, we focus on the combination of machine learning methods with the optical spectroscopy methods widely used for disease detection, including absorbance, fluorescence, scattering, FTIR, terahertz, etc. By comparing the spectral analysis with different machine learning methods, we illustrate that the support vector machine and convolutional neural network are most effective, which have potential to further improve the classification accuracy to distinguish disease subtypes if these machine learning methods are used. This Perspective broadens the scope of optical spectroscopy enhanced by machine learning and will be useful for the development of disease detection.

Are fireworks a significant episodic source of brown carbon?

We hypothesize that firework events involving the combustion of charcoal fuel, organic binders, metal salts, and cellulose-based wrapping material could be significant transient sources of aerosol brown carbon (BrC). To test this, we couple high time-resolution (1 min) measurements of black carbon (BC) and BrC absorption from a 7-wavelength aethalometer with time-integrated (12-24 h) measurements of filter extracts, i.e., UV-visible, fluorescence, and Fourier-transformed infrared (FT-IR) signatures of BrC, total and water-soluble organic carbon (OC and WSOC), ionic species, and firework tracer metals during a sampling campaign covering the Diwali fireworks episode in India. In sharp contrast to BC, BrC absorption shows a distinct and considerable rise of 2-4 times during the Diwali period, especially during the hours of peak firework activity, as compared to the background. Fluorescence profiles suggest enrichment of humic-like substances (HULIS) in the firework plume, while the enhancement of BrC absorption in the 400-500 nm range suggests the presence of nitroaromatic compounds (NACs). Considerable contributions of WSOC and secondary organics to OC (44.1% and 31.2%, respectively) and of the water-soluble fraction of BrC to total BrC absorption (71.0%) during the Diwali period point toward an atmospherically processed, polar signature of firework-related BrC, which is further confirmed by FT-IR profiles. This aqueous BrC exerts a short-lived but strong effect on atmospheric forcing (12.0% vis-à-vis BC in the UV spectrum), which could affect tropospheric chemistry via UV attenuation and lead to a stabilization of the post-Diwali atmosphere, resulting in enhanced pollutant build-up and exposure.

Introducing ATR-FTIR Spectroscopy through Analysis of Acetaminophen Drugs: Practical Lessons for Interdisciplinary and Progressive Learning for Undergraduate Students

Infrared (IR) spectroscopy is a vibrational spectroscopic technique useful in chemical, pharmaceutical, and forensic sciences. It is essential to identify chemicals for reasons spanning from scientific research and academic practices to quality control in companies. However, in some university degrees, graduate students do not get the proficiency to optimize the experimental parameters to obtain the best IR spectra; to correlate the IR spectral bands with the molecular vibrations (chemical elucidation); to have some criteria for any substance identification (especially relevant in quality control to recognize counterfeit); and to apply chemometrics for comparing, visualizing, and classifying the IR spectra. This work presents an experimental laboratory practice for an introductory teaching of the IR instrumental conditions in the identification of substances based on visual spectra comparison and statistical analysis and matching. Then, the selected IR conditions are applied to different commercial drugs, in the solid state or in solution, mostly composed of acetaminophen. Finally, the students apply chemometrics analysis to the IR data. This practice was designed for the training in a chemistry subject for undergraduate students of the chemistry, pharmacy, or forensics degrees, among others related to science, medical, food, or technological sciences.

Chemometrics in forensic science: approaches and applications

Forensic investigations are often reliant on physical evidence to reconstruct events surrounding a crime. However, there remains a need for more objective approaches to evidential interpretation, along with rigorously validated procedures for handling, storage and analysis. Chemometrics has been recognised as a powerful tool within forensic science for interpretation and optimisation of analytical procedures. However, careful consideration must be given to factors such as sampling, validation and underpinning study design. This tutorial review aims to provide an accessible overview of chemometric methods within the context of forensic science. The review begins with an overview of selected chemometric techniques, followed by a broad review of studies demonstrating the utility of chemometrics across various forensic disciplines. The tutorial review ends with the discussion of the challenges and emerging trends in this rapidly growing field.

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.

Investigations into the source attribution of party sparklers using trace elemental analysis and chemometrics

In Australia, party sparklers are commonly used to initiate or prepare inorganic based homemade explosives (HMEs) as they are the most easily accessible and inexpensive pyrotechnic available on the market. As sparkler residue would be encountered in cases involving these types of devices, the characterisation and source determination of the residue would be beneficial within a forensic investigation. The aim of this study is to demonstrate the potential of using trace elemental profiling coupled with chemometric and other statistical techniques to link a variety of different sparklers to their origin. Inductively coupled plasma-mass spectrometry (ICP-MS) was used to determine the concentration of 50 elements in 48 pre-blast sparkler samples from eight sparkler brands/classes available in Australia. Extracting ground-up sparkler residue in 10% nitric acid for 24 hours was found to give the most reliable quantification. The collected data were analysed using Principal Component Analysis (PCA) to visualise the distribution of the sample data and explore whether the sparkler samples could be classified into their respective brands. ANOVA based feature selection was used to remove elements that did not largely contribute to the separation between classes. This resulted in the development of a 7-elemental profile, consisting of V, Co, Ni, Sr, Sn, Sb, W, which could be used to correctly classify the samples into eight distinct groups. Linear Discriminant Analysis (LDA) was subsequently used to construct a discriminant model using four out of six samples from each class. The model successfully classified 100% of the samples to their correct sparkler brand. The model also correctly matched 100% of the remaining samples to the correct class. This demonstrates the potential of using trace elemental analysis and chemometrics to correctly identify and discriminate between party sparklers.

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.

Identification of inorganic oxidizing salts in homemade explosives using Fourier transform infrared spectroscopy

Recently, inorganic low explosives, such as pyrotechnic composition, black powder, and ammonium nitrate, are commonly used in improvised explosive devices (IEDs) by the rioter or terrorists since these energetic materials can be obtained easily and legally from civilian markets. Identification of inorganic oxidizing salts in these homemade explosives, including nitrates, chlorates, and perchlorates, is a necessary procedure for forensic investigators to provide criminal evidences. In this article, Fourier transform infrared (FTIR) spectroscopy was used to discriminate NO₃^-, CO₃^2-, ClO₃^-, ClO₄^-, SO₄^2-, and NH₄⁺, whose characteristic absorption bands were explained by vibration modes of the covalent bonds. Then the spectral absorption features of nitrate salts with monovalent or divalent cations were discussed. Furthermore, it was studied whether nitrates or perchlorates can be unequivocally distinguished with the presence of carbonate and sulfate impurities through FTIR technique. Finally, the feasibility of this method was verified through an analytical case of homemade explosives.

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.