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Individualization of petrol sources by high field nuclear magnetic resonance spectroscopy.
Yankova, Yanita; Cole, Michael D; Cirstea, Silvia; Warren, John.
  • Yankova Y; Eurofins Forensic Services, 1 Dukes Green Avenue, Feltham TW14 0LR, United Kingdom. Electronic address: yanita.yankova@forensicsuk.eurofins.com.
  • Cole MD; School of Life Sciences, Anglia Ruskin University, East Road, Cambridge CB1 1PT, United Kingdom.
  • Cirstea S; School of Computing and Information Sciences, Anglia Ruskin University, East Road, Cambridge CB1 1PT, United Kingdom.
  • Warren J; Jazz Pharma, Unit 840 Broadoak Rd, Sittingbourne ME9 8AG, United Kingdom.
Forensic Sci Int ; 361: 112103, 2024 Aug.
Article en En | MEDLINE | ID: mdl-38901059
ABSTRACT
In the forensic science context petrol is considered the most common fire accelerant. However, the identification and classification of petrol sources through the years has been proven to be a challenge in the investigation of fire related incidents. This research explored the possibility of identification and classification of petrol sources using high field NMR spectroscopy. In this study, 1H NMR profiling, using specific pulse sequences to analyse neat aliquot petrol samples of different brands collected at different times across the UK and Ireland is shown, for the first time, to provide a diagnostic 'fingerprint' with specific chemical compounds that can be used for identification and classification of petrol samples. This enables linkage of unknown petrol samples to a source and in addition provides a tool which allows exclusion of potential petrol sources. A new, innovative method using 1H selTOCSY is described for the individualization and classification of petrol samples through the identification of olefinic markers in the samples. Those markers were identified as (i) 3-methyl-1-butene, (ii) a mixture of 1-pentene and 3-methyl-1-butene, (iii) 2-methyl-2-butene and (iv) a mixture of cis and trans-2-pentene.
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Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article