Investigations into fentanyl precursors method classification by handheld Fourier transform infrared and Raman spectroscopy combined with multivariate statistical analysis

被引:4
|
作者
McKeown, Hugh E. [1 ,2 ]
Rook, Trevor J. [1 ]
Pearson, James R. [3 ]
Jones, Oliver A. H. [2 ]
机构
[1] RMIT Univ, Sch Sci, Appl Chem & Environm Sci, La Trobe St, Melbourne, Vic 3001, Australia
[2] RMIT Univ, Australian Ctr Res Separat Sci ACROSS, Sch Sci, Plenty Rd, Bundoora, Vic 3083, Australia
[3] Victoria Police Forens Serv Dept, Off Chief Forens Scientist, Macleod, Vic 3085, Australia
关键词
Fourier transform infrared spectroscopy; Raman spectroscopy; Multivariate data analysis; Data fusion; Fentanyl precursors; ATTRIBUTION;
D O I
10.1016/j.forc.2023.100476
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
A goal of narcotic chemical attribution is to exploit a substance of interest for chemical forensic information and evidence. This could include determining the synthetic method used to make it and if that substance is foren-sically linked to any others. In most cases narcotic chemical attribution is profiling the impurities that are present, which give the substance a chemical fingerprint. One narcotic of significant concern to law enforcement and emergency responders is fentanyl due to the health risk it poses from very small amounts and its increasing prevalence in illicit drug markets. Portable handheld spectroscopic instruments have scope to become useful tools for substance identification in the field to ensure safety and to uncover possible investigative leads; how-ever, they have limitations with interpretation of substances that have very small proportions of other compo-nents including impurities. In this study, two spectroscopic techniques, Fourier transform infrared (FTIR) and Raman spectroscopy, were applied to determine the synthetic method employed for the fentanyl precursors N-phenethyl-4-piperidone (NPP) and 4-anilino-N-phenethylpiperidine (ANPP). Principal Component Analysis (PCA) with k-nearest neighbours (k-NN) and Orthogonal Partial Least Squares -Discriminant Analysis (OPLS-DA) were used to establish classification models. The use of low-level and mid-level data fusion strategies were employed to integrate the data from the different handheld spectroscopic instruments, which allowed suitable classification of validation samples by their respective synthetic method. These results demonstrate the versa-tility of handheld spectroscopic instruments, with results easily being exported for data fusion analysis and the possibility for future instrument library enhancements.
引用
收藏
页数:10
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