Narcotics were dispersed in solid dilutants of different concentrations by weight. In this study cocaine, heroin, and MDMA were analyzed using near-IR (785 nm excitation) micro-Raman spectroscopy. Raman spectroscopy offers the potential for the identification of illegal narcotics in seconds by inelastic scattering of light from molecular vibrations. These measurements demonstrate the feasibility of using near-IR Raman spectroscopy for rapid quantitative characterization of illegal narcotics. Caffeine and glucose concentrations were estimated with RMSEPs of 5.2 and 6.6%, respectively. Quantitative calibration models were generated using partial least-squares algorithms which predicted the concentration of cocaine in the solid mixtures containing caffeine and glucose from the Raman spectrum with a root mean standard error of prediction (RMSEP) of 4.1%. Discrimination on the basis of caffeine and glucose concentrations was also possible. Analysis of the score and loadings plots for these components showed that the samples can be clearly classified on the basis of cocaine concentration.
It was found that 98% of the spectral variation was accounted for by three principal components.
Principal component analysis of the data was employed to ascertain what factors influenced the spectral variation across the concentration range.
Near-infrared (785 nm) excitation was used to obtain Raman spectra from a series of 33 solid mixtures containing cocaine, caffeine and glucose (9.8-80.6% by weight cocaine), which were then analysed using chemometric methods.
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