Study of Spectral Modifications in Acidified Ignitable Liquids by Attenuated Total Reflection Fourier Transform Infrared Spectroscopy
Identifiers
Permanent link (URI): http://hdl.handle.net/10017/50061DOI: 10.1177/0003702815626681
ISSN: 0003-7028
Date
2016-03Affiliation
Universidad de Alcalá. Departamento de Química Analítica, Química Física e Ingeniería QuímicaBibliographic citation
Applied Spectroscopy, 2016, v. 70, n. 3, p. 520-530
Keywords
Attenuated total reflection Fourier transform infrared spectroscopy
ATR FT-IR
Acidified ignitable liquid
Chemical ignition, Molotov cocktail
Chemometrics
Fire debris
Gasoline.
Document type
info:eu-repo/semantics/article
Version
info:eu-repo/semantics/publishedVersion
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
© SAGE, 2016
Access rights
info:eu-repo/semantics/openAccess
Abstract
In this work, the spectral characteristics of two types of acidified gasoline and acidified diesel fuel are discussed. Neat and acidified ignitable liquids (ILs) infrared absorption spectra obtained by attenuated total reflection Fourier transform infrared spectroscopy were compared in order to identify the modifications produced by the reaction of the ILs with sulfuric acid. Several bands crucial for gasoline identification were modified, and new bands appeared over the reaction time. In the case of acidified diesel fuel, no significant modifications were observed. Additionally, the neat and acidified ILs spectra were used to perform a principal components analysis in order to confirm objectively the results. The complete discrimination among samples was successfully achieved, including the complete differentiation among gasoline types. Taking into account the results obtained in this work, it is possible to propose spectral fingerprints for the identification of non-burned acidified ILs in forensic investigations related with arson or the use of improvised incendiary devices (IIDs).
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Study_Martin_AppSpectros_2016.pdf | 700.0Kb |
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Files | Size | Format |
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Study_Martin_AppSpectros_2016.pdf | 700.0Kb |
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