Machine learning methods for the detection of explosives, drugs and precursor chemicals gathered using a colorimetric sniffer sensor

Biothiols, characterized by thiol groups, exhibit remarkable affinity for certain metals, playing pivotal roles in intracellular and extracellular biological processes. Fluctuations in their levels profoundly impact overall physiological health. Despite the development of various probes for biothiol detection and quantification, their inability to monitor thiol-to-disulfide state transitions persists as a limitation. Given their association with pathologies, early detection remains imperative. Gold nanorod (AuNR)-based colorimetric probes have garnered attention for their utility in visual diagnostic assays. Herein, we present a costeffective, and sensitive multicolor ratio measuring probe enabling on-site simultaneous identification, discrimination, and quantification of essential biothiols�cysteine (CYS), glutathione (GSH), cystine (CYSS), and glutathione disulfide (GSSG)�while also quantifying thiol-to-disulfide ratios. Our investigation clarifies the probe's functionality, elucidating etching and antietching mechanisms based on sulfhydryl group coordination with Hg 2+ . This coordination impedes gold amalgam formation, facilitating discriminative detection via AuNR size and aspect ratio modulation, validated by transmission electron microscopy. Notably, distinct rainbow-like fingerprint patterns were discernible both visually and spectroscopically for the aforementioned biothiols and their respective thiol-to-disulfide ratios. Subsequent qualitative and quantitative analyses via linear discriminant analysis (LDA) and partial least squares regression revealed linear correlations over broad concentration ranges (

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

Otłowski,

Zalas,

Gierczyk

2024

Sci Rep

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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.

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Machine learning methods for the detection of explosives, drugs and precursor chemicals gathered using a colorimetric sniffer sensor

Abstract: Colorimetric sensing technology for the detection of explosives, drugs, and their precursor chemicals is an important and effective approach. In this work, we use various machine learning models to detect...

Cited by 4 publications

References 37 publications

Ensuring food safety by artificial intelligence-enhanced nanosensor arrays

Ensuring food safety by artificial intelligence-enhanced nanosensor arrays

Gold Nanorod Amalgamation: Machine Learning Empowered Discrimination of Biothiol and Thiol Ratios

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

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