|Department:||Chemistry and Biochemistry (Arts and Sciences)|
|Keywords:||Analytical Chemistry; Forensic analysis; DMS; GC/MS; IMS; chemometrics|
|Full text PDF:||http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1267816777|
Rapid, practical, and low-cost analytical methods are always desirable in forensic analysis. Using proper sample preparation techniques with the application of gas chromatography/mass spectrometry (GC/MS), gas chromatography-differential mobility spectrometry (GC-DMS) and ion mobility spectrometry (IMS) with chemometric analysis, analytical methods were developed for fast and practical identification and classification of analytes in complicated matrices. GC-DMS was investigated as a tool for analysis of ignitable liquids from fire debris. The combined information afforded by gas chromatography and differential mobility spectrometry provided unique two-way patterns for each sample of ignitable liquid. Fuzzy rule-building expert system (FuRES) models constructed with the neat ignitable liquids identified the spiked samples from simulated fire debris with 99.07±0.04% accuracy. The performances of DMS as gas chromatographic detector was also compared with mass spectrometry (MS) using a chemometric tool, projected difference resolutions (PDRs). The PDR results show that one-way mass spectra data exhibit higher resolution than DMS data, while total ion chromatograms from GC-DMS show higher resolution than that from GC/MS for differentiating seven kinds of ignitable liquids. Direct methylation and solid phase microextraction (SPME) were used as a sample preparation technique for classification of bacteria based on fatty acid methyl esters (FAMEs) profiles. Compared with traditional chemical derivatization and liquid-liquid extraction (LLE), the method presented in this work avoids using inorganic and organic solvents and greatly decrease sample preparation time as well. The difference between Gram-positive and Gram-negative bacteria was clearly observed with the application of principal component analysis (PCA) of GC/MS data of bacterial FAMEs. The cross-validation study using ten bootstrap Latin partition (BLP) and fuzzy rule building expert system (FuRES) presented an 87±3% correct classification rate. A comparatively rapid and reliable screening method for detection of cocaine and its metabolites, benzoylecgonine and cocaethylene in urine was demonstrated using solid phase extraction (SPE) coupled with IMS. Data analysis with alternating least squares (ALS) was used to model the IMS spectral datasets and separate the reactant ion peak from the product ion peaks. This method provides forensic chemists a viable approach for fast and simple drug screening.