Nitrogen Compound Characterization in Fuels by Multidimensional Gas Chromatography.

Certain nitrogen-containing compounds can contribute to fuel instability during storage. Hence, detection and characterization of these compounds is crucial. There are significant challenges to overcome when measuring trace compounds in a complex matrix such as fuels. Background interferences and matrix effects can create limitations to routine analytical instrumentation, such as GC-MS. In order to facilitate specific and quantitative measurements of trace nitrogen compounds in fuels, a nitrogen-specific detector is ideal. In this method, a nitrogen chemiluminescence detector (NCD) is used to detect nitrogen compounds in fuels. NCD utilizes a nitrogen-specific reaction that does not involve the hydrocarbon background. Two-dimensional (GCxGC) gas chromatography is a powerful characterization technique as it provides superior separation capabilities to one-dimensional gas chromatography methods. When GCxGC is paired with a NCD, the problematic nitrogen compounds found in fuels can be extensively characterized without background interference. The method presented in this manuscript details the process for measuring different nitrogen-containing compound classes in fuels with little sample preparation. Overall, this GCxGC-NCD method has been shown to be a valuable tool to enhance the understanding of the chemical composition of nitrogen-containing compounds in fuels and their impact on fuel stability. The % RSD for this method is <5% for intraday and <10% for interday analyses; the LOD is 1.7 ppm and the LOQ is 5.5 ppm.

Evolving window factor analysis-multivariate curve resolution with automated library matching for enhanced peak deconvolution in gas chromatography-mass spectrometry fuel data.

Fuel chromatography is inherently limited by the high complexity of petroleum fuel compositions. In practice, almost no fuel components are fully resolved in gas chromatography. This is due to both insufficient peak capacity for the large number of individual components within time and chromatographic efficiency constraints, and insufficient resolving power of the stationary phase in the gas chromatography column relative to the many structurally similar isomers or homologs present in petrochemical fuels. Multidimensional approaches, longer columns and slower heating rates can offer some benefits but will not necessarily fully resolve co-eluting fuel compounds, especially within reasonable analysis times. The following work details how deconvolved mass spectral loadings, combined with library matching, provide a quality metric against which to automatically evaluate results obtained from an experimental evolving window factor analysis-multivariate curve resolution deconvolution algorithm applied to gas chromatography-mass spectrometry data. This algorithm was evaluated in the context of trace component detection in synthetic fuel data sets, dodecane and tetradecane detection in petrochemical fuels, and the detection of natural products unlikely to be present in petrochemical fuels. In the case of the trace component detection challenge, the experimental algorithm outperformed a control algorithm that utilized a singular value-based quality metric. Meanwhile, when detecting dodecane, tetradecane, and natural products in petrochemical fuels, the experimental algorithm allowed for higher-quality compound identification results than could be obtained without peak deconvolution, thus reliably improving fuel component resolution in an automated fashion.

Capillary electrophoresis of heparin and other glycosaminoglycans using a polyamine running electrolyte.

This study involves the use of polyamines as potential resolving agents for the capillary electrophoresis (CE) of glycosaminoglycans (GAGs), specifically heparin, dermatan sulfate, chondroitin sulfate, over-sulfated chondroitin sulfate (OSCS), and hyaluronan. All of the compounds can be separated from each other with the exception of chondroitin sulfate and hyaluronan. Using optimization software, the final run conditions are found to be 200 mM ethylenediamine and 45.5 mM phosphate as the electrolyte with -14 V applied across a 50 µm ID×24.5 cm fused silica capillary at 15°C. The ion migration order, with OSCS as the last instead of the first peak, is in contrast to previous reports using either a high molarity TRIS or lithium phosphate run buffer with narrower bore capillaries. Total analysis time is 12. 5 min and the relative standard deviation of the heparin migration time is about 2.5% (n=5). The interaction mechanism between selected polyamines and heparin is explored using conductivity measurements in addition to CE experiments to show that an ion-pairing mechanism is likely.

Capillary electrophoresis methods for the determination of covalent polyphenol-protein complexes.

The bioactivities and bioavailability of plant polyphenols including proanthocyanidins and other catechin derivatives may be affected by covalent reaction between polyphenol and proteins. Both processing conditions and gastrointestinal conditions may promote formation of covalent complexes for polyphenol-rich foods and beverages such as wine. Little is known about covalent reactions between proteins and tannin, because suitable methods for quantitating covalent complexes have not been developed. We established capillary electrophoresis methods that can be used to distinguish free protein from covalently bound protein-polyphenol complexes and to monitor polyphenol oxidation products. The methods are developed using the model protein bovine serum albumin and the representative polyphenol (-)epigallocatechin gallate. By pairing capillaries with different diameters with appropriate alkaline borate buffers, we are able to optimize resolution of either the protein-polyphenol complexes or the polyphenol oxidation products. This analytical method, coupled with purification of the covalent complexes by diethylaminoethyl cellulose chromatography, should facilitate characterization of covalent complexes in polyphenol-rich foods and beverages such as wine.