0 Citations
0 Reads
Analysis of 'legal high' substances and common adulterants using handheld spectroscopic techniques
Assi S
Guirguis A
Halsey S
Fergus S
Stair J L
Analytical Methods, 7(2), pp 736-746, 2015
Summary
The identification of 'legal highs' is challenging as they often do not match their label claim and contain a wide range of impurities and/or adulterants. In addition, there is a need for techniques to be on-site, rapid and non-destructive. The feasibility of using the in-built algorithms of handheld near-infrared (NIR), Raman and attenuated total reflectance Fourier transform-infrared (ATR-FT-IR) spectroscopy for the identification of 'legal high' substances was investigated. Spectral libraries were constructed using three substances found in 'legal highs' (i.e., dextromethorphan, 2-aminoindane and lidocaine) and their 50 : 50 mixtures with caffeine. Model dilution mixtures with caffeine (i.e., 5-95% m/m) and seven 'legal high' Internet products were used to test the method. The 'legal high' constituents in most of the model mixtures were identified within a minimum range of 30-60% m/m for NIR, 20-75% m/m for Raman, and 41-85% m/m for ATR-FT-IR. This demonstrates that simple library mixtures could be used to identify test substances when the concentrations are variable. Below and above these levels, the test mixtures often correlated to the component in higher concentration. Collectively, the instruments identified the main constituents in the seven Internet products with varying correlation criteria. The NIR and ATR-FT-IR provided complementary information compared to Raman when carbohydrate cutting agents were added to the product, yet the Raman showed a high fluorescence signal for three products hindering identification. These initial studies indicate the suitability of three complementary techniques for rapid identification of 'legal high' products. Further development of spectral libraries, algorithms, and use of alternative Raman excitation wavelengths is needed to provide adequate tools for in-field analysis by non-experts.
Keywords
--
Institution
--
Select Groups
Select Contacts
swap_vert Order by date
Order by date Order by name