The use of portable separation devices for forensic analysis: A review of recent literature

Development and evaluation of portable NIR technology for the identification and quantification of Australian illicit drugs

The efficient and accurate analysis of illicit drugs remains a constant challenge in Australia given the high volume of drugs trafficked into and around the country. Portable drug testing technologies facilitate the decentralisation of the forensic laboratory and enable analytical data to be acted upon more efficiently. Near-infrared (NIR) spectroscopy combined with chemometric modelling (machine learning algorithms) has been highlighted as a portable drug testing technology that is rapid and accurate. However, its effectiveness depends upon a database of chemically relevant specimens that are representative of the market. There are chemical differences between drugs in different countries that need to be incorporated into the database to ensure accurate chemometric model prediction. This study aimed to optimise and assess the implementation of NIR spectroscopy combined with machine learning models to rapidly identify and quantify illicit drugs within an Australian context. The MicroNIR (Viavi Solutions Inc.) was used to scan 608 illicit drug specimens seized by the Australian Federal Police comprising of mainly crystalline methamphetamine hydrochloride (HCl), cocaine HCl, and heroin HCl. A number of other traditional drugs, new psychoactive substances and adulterants were also scanned to assess selectivity. The 3673 NIR scans were compared to the identity and quantification values obtained from a reference laboratory in order to assess the proficiency of the chemometric models. The identification of crystalline methamphetamine HCl, cocaine HCl, and heroin HCl specimens was highly accurate, with accuracy rates of 98.4 %, 97.5 %, and 99.2 %, respectively. The sensitivity of these three drugs was more varied with heroin HCl identification being the least sensitive (methamphetamine = 96.6 %, cocaine = 93.5 % and heroin = 91.3 %). For these three drugs, the NIR technology provided accurate quantification, with 99 % of values falling within the relative uncertainty of ±15 %. The MicroNIR with NIRLAB infrastructure has demonstrated to provide accurate results in real-time with clear operational applications. There is potential to improve informed decision-making, safety, efficiency and effectiveness of frontline and proactive policing within Australia.

Evaluation of handheld Raman spectrometers for the detection of intact explosives

The detection of intact explosives in the field provides a unique challenge for investigators, considering the sensitive and dangerous nature of these samples. Handheld Raman instruments have grown in popularity for the analysis of unknown samples in the field, combining speed of data collection and reliability with a size that allows for the instruments to be field portable. Handheld Raman instruments are used commonly in the field, and yet there is very little research on the detection capabilities of these instruments, specifically for explosive compounds. The present study aimed to evaluate the detection capabilities of two handheld Raman spectrometers, the Rigaku ResQ-CQL and the Field Forensics HandyRam™, using explosives analytical standards, including 2,4,6-trinitrotoluene (TNT), nitromethane (NM), ammonium nitrate (AN) and smokeless powder components such as diphenylamine (DPA), ethyl centralite (EC), and methyl centralite (MC). The spectrometers were evaluated on their sensitivity, the repeatability of the data, and the performance of the internal library when available. In addition, an interference study with glass and plastic containers was also performed. Finally, authentic intact explosive samples, including TNT flakes, a mixture of ammonium nitrate and fuel oil (ANFO), smokeless powder and nitromethane were analyzed to evaluate the developed method and test the detection capabilities of the spectrometers with authentic samples. Spectra were reproducible for all the analytes across both instruments, with regards to the peak location and the intensity. Spectra obtained with the Rigaku ResQ-CQL displayed better resolution for all analytes, including the authentic samples. In addition, its wider scan range allowed for the detection of more detailed peaks below 400 cm-1. Identifying the detection capabilities of these handheld instruments can therefore help guide investigators on how to best utilize them in the field.