ABSTRACT
A baseline correction method that uses basis set projection to estimate spectral backgrounds has been developed and applied to gas chromatography/mass spectrometry (GC/MS) data. An orthogonal basis was constructed using singular value decomposition (SVD) for each GC/MS two-way data object from a set of baseline mass spectra. A novel aspect of this baseline correction method is the regularization parameter that prevents overfitting that may produce negative peaks in the corrected mass spectra or ion chromatograms. The number of components in the basis, the regularization parameter, and the mass spectral range from which the spectra were sampled to construct the basis were optimized so that the projected difference resolution (PDR) or signal-to-noise ratio (SNR) was maximized. PDR is a metric similar to chromatographic resolution that indicates the separation of classes in a multivariate data space. This new baseline correction method was evaluated with two synthetic data sets and a real GC/MS data set. The prediction accuracies obtained by using the fuzzy rule-building expert system (FuRES) and partial least-squares-discriminant analysis (PLS-DA) as classifiers were compared and validated through bootstrapped Latin partition (BLP) between data before and after baseline correction. The results indicate that baseline correction of the two-way GC/MS data using the proposed methods resulted in a significant increase in average PDR values and prediction accuracies.
ABSTRACT
Monitoring the changes of jet fuel physical properties is important because fuel used in high-performance aircraft must meet rigorous specifications. Near-infrared (NIR) spectroscopy is a fast method to characterize fuels. Because of the complexity of NIR spectral data, chemometric techniques are used to extract relevant information from spectral data to accurately classify physical properties of complex fuel samples. In this work, discrimination of fuel types and classification of flash point, freezing point, boiling point (10%, v/v), boiling point (50%, v/v), and boiling point (90%, v/v) of jet fuels (JP-5, JP-8, Jet A, and Jet A1) were investigated. Each physical property was divided into three classes, low, medium, and high ranges, using two evaluations with different class boundary definitions. The class boundaries function as the threshold to alarm when the fuel properties change. Optimal partial least squares discriminant analysis (oPLS-DA), fuzzy rule-building expert system (FuRES), and support vector machines (SVM) were used to build the calibration models between the NIR spectra and classes of physical property of jet fuels. OPLS-DA, FuRES, and SVM were compared with respect to prediction accuracy. The validation of the calibration model was conducted by applying bootstrap Latin partition (BLP), which gives a measure of precision. Prediction accuracy of 97 ± 2% of the flash point, 94 ± 2% of freezing point, 99 ± 1% of the boiling point (10%, v/v), 98 ± 2% of the boiling point (50%, v/v), and 96 ± 1% of the boiling point (90%, v/v) were obtained by FuRES in one boundaries definition. Both FuRES and SVM obtained statistically better prediction accuracy over those obtained by oPLS-DA. The results indicate that combined with chemometric classifiers NIR spectroscopy could be a fast method to monitor the changes of jet fuel physical properties.
ABSTRACT
Triolein, a triglyceride containing oleic acid as the only acid moiety in the glyceride molecules has been isothermally treated at 280, 300, and 325 degrees C in glass vials under nitrogen atmosphere. The products formed during the thermal treatment at each temperature have been analysed both by infrared spectrometry and GC-MS. The GC-MS analysis was performed after derivatisation of the fatty acids into their methyl esters (FAMEs). Chemometric tools were used in determining the concentrations of the main products namely triolein and trieaidin in the thermally treated mixtures. The concentration profiles of the trielaidin formed during thermal treatment at the above three temperatures were used in determining activation energy for the cis-trans isomerisation of triolein. The combined analysis reveals that the thermal treatment induces not only cis-trans isomerisation but also fission and fusion in the molecules. Furthermore, migration of the double bond in oleic and elaidic acids forming cis and trans isomers of the 18:1 acid was also observed. The heat-induced isomerisation in triolein follows a zeroth order reaction with an activation energy 41+/-5 kcal/mol.
