Browsing by Author "Hardy, Iona"

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    Development of a Smart Sniffer Device for the Detection of Illicit Drugs, Homemade Explosives, and their Precursor Chemicals
    (Cranfield University, 2020-11-30 13:29) Hardy, Iona
    The controlled drug market in the UK alone is worth £9.4 billion a year (£19 billion a year cost to society) and is used to finance other crimes, including terrorism with enormous social-economical costs. The threat continues to change and exploitation of the latest scientific and technical advances to enhance operation capabilities for an early detection of terrorist and criminal activities, is at the core of Law Enforcement Agencies (LEAs) operational requirements. Among the detection technologies currently used/explored by UK and International market, a portable sniffer device that can detect multiple illicit substances, in a non-destructive, rapid, and accurate manner, would offer a valid alternative to LEAs.The CRIM-TRACK sniffer device was developed by Cranfield and Danish Technical University (EU FP7 project) and is currently at TRL 4. See attached file for the full abstract.
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    Getting a Whiff of Crime: The Chemistry Behind Detection of Illicit Substances by a New Sniffer Dog
    (Cranfield University, 2022-01-13T17:45:13Z) Hardy, Iona
    To combat the constantly shifting threat related to the trafficking of illicit drugs and terrorism and meet Law Enforcement Agencies (LEAs) operational requirements, the exploitation of the latest scientific and technical advances is key. A valid alternative to the detection technologies currently used/explored by UK and International markets, is the CRIM-TRACK sniffer device, which allows detection of multiple illicit substances in a non-destructive, rapid, and accurate manner. The CRIM-TRACK sniffer includes a colourimetric sensor system (Microchip, Figure 1) consisting of chromic dyes reacting to vapour traces of illicit substances (Analytes).The aim of this PhD project is to further develop the CRIM-TRACK sniffer device’s colourimetric sensor through chemical analysis of the interaction between analyte and dye molecules. Responsive (Colour changing) and non-responsive dyes from the current colourimetric microchip for the analyte of interest are determined through detection experiments using the CRIM-TRACK sniffer. The detection mechanisms of four analytes – a selection of chemical precursors and controlled drugs – with two families of dyes, diazobenzenes and sulfonephthaleins, have been ascertained. This is achieved by applying analytical techniques such as Nuclear Magnetic Resonance and UV-Vis Spectrophotometry and comparing the data produced by analyte:dye mixtures and their single components. Evaluation of these mixtures is aided by comparison of experimental data against modelling data produced by colleagues at Sheffield Hallam University. Understanding the detection mechanisms allows the identification and selection of other responsive dyes for improvement of the current microchip and the design of scenario specific microchips.
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    Machine learning methods for the detection of explosives, drugs and precursor chemicals gathered using a colorimetric sniffer sensor
    (Royal Society of Chemistry, 2023-04-18) Francis, Deena P.; Laustsen, Milan; Dossi, Eleftheria; Treiberg, Tuule; Hardy, Iona; Shiv, Shai Hvid; Hansen, Bo Svarrer; Mogensen, Jesper; Jakobsen, Mogens H.; Alstrøm, Tommy S.
    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 these substances from colorimetric sensing experiments conducted in controlled environments. The detection experiments based on the response of a colorimetric chip containing 26 chemo-responsive dyes indicate that homemade explosives (HMEs) such as hexamethylene triperoxide diamine (HMTD), triacetone triperoxide (TATP), and methyl ethyl ketone peroxide (MEKP) used in improvised explosives devices are detected with true positive rate (TPR) of 70–75%, 73–90% and 60–82% respectively. Time series classifiers such as Convolutional Neural Networks (CNN) are explored, and the results indicate that improvements can be achieved with the use of kinetics of the chemical responses. The use of CNNs is limited, however, to scenarios where a large number of measurements, typically in the range of a few hundred, of each analyte are available. Feature selection of important dyes using the Group Lasso (GPLASSO) algorithm indicated that certain dyes are more important in discrimination of an analyte from ambient air. This information could be used for optimizing the colorimetric sensor and extend the detection to more analytes.
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    Until Sniffer Dogs Can Talk: CRIM-TRACK
    (Cranfield University, 2022-11-22T14:39:37Z) Hardy, Iona
    This image is a digitally drawn short comic highlighting the CRIM-TRACK sniffer, a device that utilises a colourimetric sensor system to detect illicit compounds by their vapour at sensitivity rivalling a sniffer dog, but with better discrimination. Both detection methods can detect multiple substances, but sniffer dogs cannot signal which substance they have found, whilst the CRIM-TRACK sniffer can. The research aims to contribute to developing the CRIM-TRACK sniffer device, specifically the disposable colourimetric microchips used. This is being carried out by investigating the colour change mechanisms of select dyes when they encounter illicit compounds such as illicit drugs, homemade explosives, and their precursor chemicals using common analytical techniques. This data will allow future generations of the microchip to be tuned via dye selection for specific scenarios.
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    Validation of data from an artificial sniffer dog by common analytical techniques
    (SETCOR, 2021-10-22) Hardy, Iona; Jakobsen, Mogens Havsteen; Treiberg, Tuule; Gotfredsen, Charlotte Held; Dossi, Eleftheria
    CRIM-TRACK, an artificial sniffer dog, employs a colourimetric sensor system to monitor the colour change of chromic dyes when in contact with the vapours of illicit molecules (analytes) for detection and identification of substances. Within, the interaction of illicit chemicals and chromic dyes have been studied in solution using Proton Nuclear Magnetic Resonance ( 1 H NMR) spectroscopy and Ultraviolet-Visible (UV-Vis) spectrophotometry, to validate data generated from detection experiments using CRIM-TRACK sniffer. 1 H-NMR revealed the colour change mechanism induced by benzyl methyl ketone (BMK), a precursor chemical of methamphetamines, was hydrogen bonding between the BMK and specific dye molecules. It also revealed that hexamine (HEX), an explosives precursor, induced a colour change by formation of ion pairs with the specific dye molecules. The colour changes detected by CRIM-TRACK were confirmed by UV-Vis where a shift in absorption wavelength and/or a change in absorbance occurred.