Analysis of middle distillate fuels by midband infrared spectroscopy

Review on the Relationship Between Liquid Aerospace Fuel Composition and Their Physicochemical Properties

“…Shi et al [55] determined the aviation fuel composition through GC × GC-MS/FID and correlated the gravimetric NHOC with the detailed composition by different statistical algorithms. In addition, PLS regression models combined with FT-IR spectra were used for the prediction of the gravimetric NHOC of hydrocarbon fuels [73]. As discussed, the gravimetric NHOC of aviation hydrocarbon fuels is closely related to their hydrogen content.…”

“…Many studies attempted to estimate viscosity on the basis of molecular structure [56,57,73,79]. Cai et al [79] (8)…”

In-Depth Interpretation of Mid-Infrared Spectra of Various Synthetic Fuels for the Chemometric Prediction of Aviation Fuel Blend Properties

“…Chemometric analysis of Fourier transform infrared (FTIR) spectra of fossil fuels, especially in the near-infrared (NIR) region, has proven to be a powerful tool to predict, e.g., physicochemical properties from conveniently obtainable spectroscopic data. , Beyond that, it has been shown that it is possible to predict whether a fossil fuel contains synthetic components or not. , However, it is not self-evident that infrared (IR) spectroscopy is the method of choice to differentiate between hydrocarbons of fossil and synthetic origin, because the latter chemically correspond very well to those present in fossil fuels . Also, more sophisticated techniques, such as comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (GC × GC–TOFMS), can be used to reliably predict properties of fossil fuels. , …”

Feasibility of quality process control of a naphtha fractioning unit based on near-infrared spectroscopic prediction of physical and chemical properties of medium naphtha streams

“…Near-infrared (NIR) spectroscopy has proved to be quite suitable for such applications, providing the basis for predicting several chemical and physical properties from a single sample's spectrum [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. By means of powerful multivariate techniques like partial least-squares regression (PLS), each property of interest can be regressed on the NIR absorption spectra, resulting in a calibration model that can be used to predict that property's value for a given test sample.…”