Advances in Fire Debris Analysis

Sigman, Michael E.; Williams, Mary R.

doi:10.3390/separations6010013

Cited by 7 publications

(2 citation statements)

References 9 publications

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“…The current gold standard method for analyzing fire debris to determine if an accelerant is present is gas chromatography-mass spectrometry (GC-MS) [5] [6].…”

Section: Introductionmentioning

confidence: 99%

Rapid Detection of Accelerants in Fire Debris Using a Field Portable Mid-Infrared Quantum Cascade Laser Based Analyzer

Huang,

Zhang,

Dai

et al. 2023

OJAppS

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Arson presents a challenging crime scene for fire investigators worldwide. Key to the investigation of suspected arson cases is the analysis of fire debris for the presence of accelerants or ignitable liquids. This study has investigated the application and method development of vapor phase mid-Infrared (mid-IR) spectroscopy using a field portable quantum cascade laser (QCL) based system for the detection and identification of accelerant residues such as gasoline, diesel, and ethanol in fire debris. A searchable spectral library of various ignitable fluids and fuel components measured in the vapor phase was constructed that allowed for real-time identification of accelerants present in samples using software developed in-house. Measurement of vapors collected from paper material that had been doused with an accelerant followed by controlled burning and then extinguished with water showed that positive identification could be achieved for gasoline, diesel, and ethanol. This vapor phase mid-IR QCL method is rapid, easy to use, and has the sensitivity and discrimination capability that make it well suited for non-destructive crime scene sample analysis. Sampling and measurement can be performed in minutes with this 7.5 kg instrument. This vibrational spectroscopic method required no time-consuming sample pretreatment or complicated solvent extraction procedure. The results of this initial feasibility study demonstrate that this portable fire debris analyzer would greatly benefit arson investigators performing analysis on-site.

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“…The current gold standard method for analyzing fire debris to determine if an accelerant is present is gas chromatography-mass spectrometry (GC-MS) [5] [6].…”

Section: Introductionmentioning

confidence: 99%

Rapid Detection of Accelerants in Fire Debris Using a Field Portable Mid-Infrared Quantum Cascade Laser Based Analyzer

Huang,

Zhang,

Dai

et al. 2023

OJAppS

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“…For this reason, a strategy needs to be developed to successfully compare weathered and unweathered samples. Different approaches have been proposed to overcome this complication 3 . Researchers have tried to tackle the problem without using an explicit evaporation model, for instance by using statistical methods such as principal component analysis (PCA) [4][5][6] , linear discriminant analysis (LDA) 4,6 , canonical variate analysis (CVA) 6 , hierarchical cluster analysis (HCA) 5 or by covariance mapping 7 .…”

mentioning

confidence: 99%

Artificial intelligence and thermodynamics help solving arson cases

Korver

Schouten

Moultos

et al. 2020

Sci Rep

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In arson cases, evidence such as DNA or fingerprints is often destroyed. One of the most important evidence modalities left is relating fire accelerants to a suspect. When gasoline is used as accelerant, the aim is to find a strong indication that a gasoline sample from a fire scene is related to a sample of a suspect. Gasoline samples from a fire scene are weathered, which prohibits a straightforward comparison. We combine machine learning, thermodynamic modeling, and quantum mechanics to predict the composition of unweathered gasoline samples starting from weathered ones. Our approach predicts the initial (unweathered) composition of the sixty main components in a weathered gasoline sample, with error bars of ca. 4% when weathered up to 80% w/w. This shows that machine learning is a valuable tool for predicting the initial composition of a weathered gasoline, and thereby relating samples to suspects.

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