Modeling Of Length Tunable Selectivity For Gas Chromatography

Author : Roman Jaramillo
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (119 download)

DOWNLOAD NOW!

Download or read book Thermodynamic Modeling of Comprehensive Two-Dimensional Gas Chromatography Separations written by Roman Jaramillo and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive two-dimensional gas chromatography (GCxGC) has emerged as a powerful analytical technique. Coupling two chromatographic columns greatly expands the number of compounds which can be detected, allowing for a more robust characterization of complex solutions, such as petrochemical samples and environmental waters. Through thermodynamic modeling of analyte retention times, GC method parameters, i.e., column dimensions, temperature program, etc., can rapidly be altered and evaluated without performing physical experiments. Chromatographers can determine the conditions which optimize the GC separation, producing shorter method runtimes while maintaining analyte resolution. Thermodynamic modeling is well understood in one-dimensional GC separations. However, significant second dimension modeling errors have consistently been observed when modeling GCxGC separations. A deeper understanding of the GCxGC separations process is required. A GCxGC modeling script was written which accounts for the various thermal zones present in a thermally modulated GCxGC system, a feature which past modeling scripts have consistently simplified, introducing sources of modeling errors. The modeling script can also model several GCxGC parameters which past modeling scripts have omitted, despite being frequently used by chromatographers, most notably the constant flow setting. Additionally, the modeling script is available for use in a web based graphical user interface, making it more accessible to chromatographers who don't have coding backgrounds. The GCxGC modeling script accuracy was evaluated using several hydrocarbon standards typically used in petrochemical applications. Modeling evaluations were performed on three LECO GCxGC systems. On two systems minimal retention time modeling errors were observed. On the third system, increased modeling errors were initially observed. However, the modeling script was modified to characterize and account for the unique separation mechanisms of the instrument, resulting in a third instance of accurate retention time modeling. The utility of the GCxGC modeling script was expanded by determining the thermodynamic indices of 50 polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) on two GC columns, allowing for their retention time modeling. The modeling script was used to develop and optimize a GCxGC separation of PCDD/Fs in fish tissue matrix. Successful modeling of PCDD/F congener elution orders and patterns was achieved, demonstrating the thermodynamic indices' use as a congener identification mechanism. Finally, GCxGC modeling was applied to model alkane isovolatility curves, providing a method for performing second-dimension Kovats retention indices analyte identification. This technique provides a secondary analyte identification mechanism to supplement a mass spectral library search, supporting proper solution qualification. Thermodynamically modeling the isovolatility curves removes the prohibitive GCxGC instrument and method modifications which similar techniques require.