Abstract
With respect to the emerging role of forensic science for arson investigation, a low cost and promising onsite detection method for ignitable liquids is desirable. Gas chromatography-differential mobility spectrometry (GC-DMS) was investigated as a tool for analysis of ignitable liquids from fire debris. Headspace solid-phase microextraction (SPME) was applied as the preconcentration and sampling method. The combined information afforded by gas chromatography and differential mobility spectrometry provided unique two-way patterns for each sample of ignitable liquid. Two-way GC-DMS data were classified into one of seven ignitable liquids using a fuzzy rule-building expert system (FuRES). The performance of the classifier was validated using bootstrap Latin partitions (BLPs) and also compared to optimized partial least-squares (PLS) classifiers. Better prediction results can be obtained by using two-way GC-DMS data than only using one-way total ion chromatograms or integrated differential mobility spectra. FuRES models constructed with the neat ignitable liquids identified the spiked samples from simulated fire debris with 99.07 +/- 0.04% accuracy.
TY - JOUR
T1 - Forensic application of gas chromatography-differential mobility spectrometry with two-way classification of ignitable liquids from fire debris.
AU - Lu,Yao,
AU - Harrington,Peter B,
Y1 - 2007/08/08/
PY - 2007/8/9/pubmed
PY - 2007/8/9/medline
PY - 2007/8/9/entrez
SP - 6752
EP - 9
JF - Analytical chemistry
JO - Anal Chem
VL - 79
IS - 17
N2 - With respect to the emerging role of forensic science for arson investigation, a low cost and promising onsite detection method for ignitable liquids is desirable. Gas chromatography-differential mobility spectrometry (GC-DMS) was investigated as a tool for analysis of ignitable liquids from fire debris. Headspace solid-phase microextraction (SPME) was applied as the preconcentration and sampling method. The combined information afforded by gas chromatography and differential mobility spectrometry provided unique two-way patterns for each sample of ignitable liquid. Two-way GC-DMS data were classified into one of seven ignitable liquids using a fuzzy rule-building expert system (FuRES). The performance of the classifier was validated using bootstrap Latin partitions (BLPs) and also compared to optimized partial least-squares (PLS) classifiers. Better prediction results can be obtained by using two-way GC-DMS data than only using one-way total ion chromatograms or integrated differential mobility spectra. FuRES models constructed with the neat ignitable liquids identified the spiked samples from simulated fire debris with 99.07 +/- 0.04% accuracy.
SN - 0003-2700
UR - https://www.unboundmedicine.com/medline/citation/17683164/Forensic_application_of_gas_chromatography_differential_mobility_spectrometry_with_two_way_classification_of_ignitable_liquids_from_fire_debris_
L2 - https://doi.org/10.1021/ac0707028
DB - PRIME
DP - Unbound Medicine
ER -