Towards fuel composition and properties from Two-dimensional gas chromatography with flame ionization and vacuum ultraviolet spectroscopy

Abstract

Already low volume (<1mL) test methods facilitate the development of sustainable aviation fuel platforms and higher fidelity computational methods. Here a novel technique with two-dimensional gas chromatography (GCxGC) and Vacuum Ultraviolet (VUV) identification is used to characterize fuel composition and determine properties compared to previous work. Ten properties are predicted, including the temperature dependence of density, viscosity, thermal conductivity, and heat capacity. Property predictions incorporate uncertainty quantification (UQ) from analyte quantification (UQ1), root property uncertainty (UQ2), and the uncertainty associated with isomeric variance (UQ3), when an analyte is not identified via VUV. Comparisons to a previous method illustrate the ability of VUV identification to increase the fidelity of property predictions and decrease uncertainties. This method is applied to a surrogate intended to mimic the first-order properties and composition of a representative Jet A/A-1. In addition to nominal and temperature-dependent properties, the derived cetane number (DCN) of the surrogate is calculated for the distillation fraction evolved. The DCN there is shown to vary across the fraction of fuel distilled. Collectively, this method documents a process to prescreen novel sustainable aviation fuel candidates, facilitate the development of chemical process models, and automate property determinations for computational fluid dynamics.