Silvia Cirstea

Dec 19, 2024 | mdpi.com | Silvia Cirstea

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Jun 14, 2024 | mdpi.com | Yanita Yankova Yankova |Silvia Cirstea |Michael Cole |John Warren

1. IntroductionFire investigation is considered one of the most challenging forensic science disciplines. Current gas chromatographic and spectroscopic analytical methods in fire investigation cannot discriminate or individualize petrol sources based on class compounds within the petrol samples from the fire scene to give an indication of the country of origin, refinery (source), natural weathering/age or fire exposure.

May 1, 2024 | preprints.org | Yanita Yankova Yankova |Silvia Cirstea |Michael Cole |John Warren

Preprint Article Version 1 This version is not peer-reviewed Version 1 : Received: 30 April 2024 / Approved: 30 April 2024 / Online: 1 May 2024 (07:38:51 CEST) Yankova, Y.Y.; Cirstea, S.; Cole, M.; Warren, J. Identification and Discrimination of Petrol Sources by Nuclear Magnetic Resonance Spectroscopy and Machine Learning in Fire Debris Analysis. Preprints 2024, 2024050031. https://doi.org/10.20944/preprints202405.0031.v1 Yankova, Y.Y.; Cirstea, S.; Cole, M.; Warren, J.