A PLS regression model using flame spectroscopy emission for determination of octane numbers in gasoline

Predicting Octane Number Using Nuclear Magnetic Resonance Spectroscopy and Artificial Neural Networks

“…Several correlations and methods have been reported in the literature to predict ON of pure hydrocarbons [3][4][5][6], PRFs [7,8], toluene primary reference fuels (TPRFs) [8][9][10][11], gasoline compounds [12], naphtha [13,14], gasolines [15][16][17][18][19][20][21][22], gasoline with ethanol [7,[23][24][25][26][27] and petroleum fractions [16]. The inputs for these models have been generated by utilizing different analytical techniques such as Fourier transform infra-red (FT-IR) spectroscopy [5,13,28,29], flame emission spectroscopy [30], nuclear magnetic resonance (NMR) spectroscopy [23,31,32], dispersive fiber-optic Raman spectroscopy [19], dielectric spectroscopy [18], gas chromatography [17], distillation curves [15], thermal wave interferometry [21] and ignition delay time (IDT) measured in an ignition quality tester (IQT) [22]. The data from these techniques have been analysed by a number of statistical and theoretical methods like multiple linear regression (MLR)…”

1H NMR application in characterizing the refinery products of gasoline

“…However, the measurement of the RON takes time and requires a relatively large amount of gasoline samples, and it normally is performed only for the purpose of quality inspections. In order to circumvent the drawbacks of the RON method, several other techniques have been proposed, such as the gas chromatography, fluorescent indicator adsorption, dielectric spectroscopy, phononic crystal sensing, flame spectroscopy emission, near infrared spectroscopy, 1 H and 13 C nuclear magnetic resonance (NMR) spectroscopy, etc. Among these techniques, 1 H NMR spectroscopy has been shown to successfully determine the ON for the product gasoline .…”

Artificial neural networks (ANNS) versus partial least squares (PLS) for spectral interference correction for taking part of the lab to the sample types of applications: an experimental study

“…In the last few years, PLS has been described in books and in tutorials [25][26][27][28][29][30][31][32]. Currently, PLS is receiving increased attention in the literature, for instance, during the last year or so, several papers describing the application of PLS to chemical problems have been published [33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49].…”