Analysis and discrimination of adhesive species using ATR-FTIR combined with Raman, and HS-GC-IMS together with multivariate statistical analysis.

Autor: Ma J; Characteristic Laboratory of Forensic Science in Universities of Shandong Province, Shandong University of Political Science and Law, Jinan 250014, Shandong Province, China., Qi Y; Characteristic Laboratory of Forensic Science in Universities of Shandong Province, Shandong University of Political Science and Law, Jinan 250014, Shandong Province, China. Electronic address: yinghuaqi@sdupsl.edu.cn., Lei M; Characteristic Laboratory of Forensic Science in Universities of Shandong Province, Shandong University of Political Science and Law, Jinan 250014, Shandong Province, China., Xuan H; Shandong Electric Power Engineering Consulting Institute Corp., Ltd, China., Li X; Characteristic Laboratory of Forensic Science in Universities of Shandong Province, Shandong University of Political Science and Law, Jinan 250014, Shandong Province, China., Lu W; Characteristic Laboratory of Forensic Science in Universities of Shandong Province, Shandong University of Political Science and Law, Jinan 250014, Shandong Province, China., Guo J; Characteristic Laboratory of Forensic Science in Universities of Shandong Province, Shandong University of Political Science and Law, Jinan 250014, Shandong Province, China., Chen H; College of Chemistry and Chemical Engineering, Huanggang Normal University, Huanggang 438000, China. Electronic address: chenhuan@hgnu.edu.cn.
Jazyk: angličtina
Zdroj: Journal of chromatography. A [J Chromatogr A] 2024 Nov 08; Vol. 1736, pp. 465402. Date of Electronic Publication: 2024 Sep 26.
DOI: 10.1016/j.chroma.2024.465402
Abstrakt: Identifying the species and origin of adhesives in criminal investigations aids in narrowing inquiry scope and supporting case detection. This study introduces two advanced combined analytical techniques for distinguishing adhesive species, including attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) combined with Raman spectroscopy, and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) together with multivariate statistical analysis. ATR-FTIR categorized seven adhesives into three groups based on the base materials, with further differentiation achieved via Raman spectra. Analysis of volatile components identified 79 volatile organic compounds (VOCs), with esters being the most concentrated. The fingerprint profile clearly illustrated the characteristic fingerprint sequence and unique marker compounds of each adhesive, effectively enabling their differentiation. Multivariate statistical analysis methods, including principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), heatmap, and hierarchical cluster analysis (HCA), were utilized to visually interpret the classification of adhesives. This integrated analytical approach provides a comprehensive analysis of adhesive compositions, facilitating the diversification and precision of adhesive species identification, and broadening the scope for detecting and analyzing trace evidence in forensic science.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024. Published by Elsevier B.V.)
Databáze: MEDLINE
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