The covariance matrix computed from the retention time-ion abundance data matrix from gas chromatography/mass spectrometry analysis of ignitable liquids is shown to be a useful tool for automated identification of ignitable liquids in a database. The absolute value of the element-by-element difference between two normalized covariance matrices is shown to quantitatively differentiate between ignitable liquids composed of complex mixtures of hydrocarbons and is amenable to automated searching of ignitable liquid databases. The covariance mapping method is applied to a matrix-contaminated postburn sample, allowing the determination of a high degree of similarity between the ignitable liquid and a heavily evaporated gasoline.
Principal components analysis (PCA), linear discriminant analysis (LDA), and quadratic discriminant analysis (QDA) were used to develop a multistep classification procedure for determining the presence of ignitable liquid residue in fire debris and assigning any ignitable liquid residue present into the classes defined under the American Society for Testing and Materials (ASTM) E 1618-10 standard method. A multistep classification procedure was tested by cross-validation based on model data sets comprised of the time-averaged mass spectra (also referred to as total ion spectra) of commercial ignitable liquids and pyrolysis products from common building materials and household furnishings (referred to simply as substrates). Fire debris samples from laboratory-scale and field test burns were also used to test the model. The optimal model's true-positive rate was 81.3% for cross-validation samples and 70.9% for fire debris samples. The false-positive rate was 9.9% for cross-validation samples and 8.9% for fire debris samples.
A comparative analysis of the discriminating power of laser-induced breakdown spectroscopy (LIBS) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), each coupled with refractive index (RI) measurements, is presented for a study of 23 samples of automobile float glass. Elemental emission intensity ratios (LIBS) and elemental concentration ratios (LA-ICP-MS) and their associated confidence intervals were calculated for each float glass sample. The ratios and confidence intervals were used to determine the discrimination power of each analytical method. It was possible to discriminate 83% of the glass samples with 99% confidence based on LIBS spectra alone, and 96-99% of the samples could be discriminated based on LIBS spectra taken in conjunction with RI data at the same confidence level. LA-ICP-MS data allowed for 100% discrimination of the samples without the need for RI data. The results provide evidence to support the use of LIBS combined with RI for forensic analysis of float glass in laboratories that do not have access to LA-ICP-MS.
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