Effects of Fire Suppression Agents and Weathering in the Analysis of Fire Debris by HS-MS eNose
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Marta Ferreiro-González | Miguel Palma | Carmelo G. Barroso | Carlos Martín-Alberca | Barbara Falatová | Danica Kacíková | Stefan Galla | M. Ferreiro-González | M. Palma | C. Barroso | C. Martín-Alberca | D. Kačíková | Barbara Falatová | Stefan Galla
[1] C. García-Ruiz,et al. Analytical tools for the analysis of fire debris. A review: 2008-2015. , 2016, Analytica chimica acta.
[2] C. García-Ruiz,et al. Study of chemical modifications in acidified ignitable liquids analysed by GC-MS. , 2015, Science & justice : journal of the Forensic Science Society.
[3] J. K. Hardy,et al. Accelerant classification by gas chromatography/mass spectrometry and multivariate pattern recognition , 2000 .
[4] Marta Ferreiro-González,et al. Characterization and Differentiation of Petroleum-Derived Products by E-Nose Fingerprints , 2017, Sensors.
[5] José Luis Pérez Pavón,et al. Strategies for qualitative and quantitative analyses with mass spectrometry-based electronic noses , 2006 .
[6] Eric Stauffer,et al. ASTM standards for fire debris analysis: a review. , 2003, Forensic science international.
[7] Bailey E. Knowlton. The Effects of Using Fire-Fighting Foams: GC-MS Pattern Analysis of Fire Debris , 2012 .
[8] Philip Doble,et al. Classification of premium and regular gasoline by gas chromatography/mass spectrometry, principal component analysis and artificial neural networks. , 2003, Forensic science international.
[10] M. Ferreiro-González,et al. Characterization of petroleum-based products in water samples by HS-MS , 2018, Fuel.
[11] C. Lennard,et al. A GC–MS database of target compound chromatograms for the identification of arson accelerants , 1995 .
[12] E. McGee,et al. A study of the effects of a Micelle Encapsulator Fire Suppression Agent on dynamic headspace analysis of fire debris samples. , 2002, Journal of forensic sciences.
[13] Michael E. Sigman,et al. Ignitable Liquid Classification and Identification Using the Summed-Ion Mass Spectrum , 2008 .
[14] Rosa Baby,et al. Quality control of medicinal plants with an electronic nose , 2005 .
[15] G. Zadora,et al. Application of Head-Space Analysis with Passive Adsorption for Forensic Purposes in the Automated Thermal Desorption-Gas Chromatography-Mass Spectrometry System , 2004 .
[16] Marta Ferreiro-González,et al. Determination of Ignitable Liquids in Fire Debris: Direct Analysis by Electronic Nose , 2016, Sensors.
[17] Mary R. Williams,et al. Combined target factor analysis and Bayesian soft-classification of interference-contaminated samples: forensic fire debris analysis. , 2012, Forensic science international.
[19] M. Ferreiro-González,et al. New Headspace-Mass Spectrometry Method for the Discrimination of Commercial Gasoline Samples with Different Research Octane Numbers , 2014 .
[20] Dehan Luo,et al. Application of ANN with extracted parameters from an electronic nose in cigarette brand identification , 2004 .
[21] E. du Pasquier,et al. Chemical fingerprinting of gasoline. 2. Comparison of unevaporated and evaporated automotive gasoline samples. , 2004, Forensic science international.
[22] M. S. Fernandes,et al. The effect of volatile residues in burnt household items on the detection of fire accelerants , 2002 .
[23] M. Ferreiro-González,et al. Gasoline analysis by headspace mass spectrometry and near infrared spectroscopy , 2015 .
[24] Marta Ferreiro-González,et al. Study of the Weathering Process of Gasoline by eNose , 2018, Sensors.
[25] S. Coulson,et al. The effect of compressed air foam on the detection of hydrocarbon fuels in fire debris samples. , 2000, Science & justice : journal of the Forensic Science Society.
[26] J. Harynuk,et al. Automated optimization and construction of chemometric models based on highly variable raw chromatographic data. , 2011, Analytica chimica acta.
[27] M. H. Mach,et al. Gas Chromatography-Mass Spectrometry of Simulated Arson Residue Using Gasoline as an Accelerant , 1977 .
[28] Roman M. Balabin,et al. Gasoline classification using near infrared (NIR) spectroscopy data: comparison of multivariate techniques. , 2010, Analytica chimica acta.
[29] Mary R. Williams,et al. Progress Toward the Determination of Correct Classification Rates in Fire Debris Analysis II: Utilizing Soft Independent Modeling of Class Analogy (SIMCA) , 2014, Journal of forensic sciences.
[30] Mary R. Williams,et al. Biodegradation of representative ignitable liquid components on soil , 2017 .
[31] Kenneth G. Furton,et al. Characterization of background and pyrolysis products that may interfere with the forensic analysis of fire debris , 2004 .
[32] John D. DeHaan Ph.D. Fabc FSSDip,et al. Kirk's Fire Investigation , 2011 .
[33] M. Ferreiro-González,et al. Validation of an HS-MS method for direct determination and classification of ignitable liquids , 2017 .
[34] Thierry Talou,et al. MOS–MOSFET gas sensors array measurements versus sensory and chemical characterisation of VOC’s emissions from car seat foams , 2003 .
[35] M. Ferreiro-González,et al. Application of an HS-MS for the detection of ignitable liquids from fire debris. , 2015, Talanta.