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Journal Articles Infrared Physics and Technology Year : 2022

Prediction of diesel fuel quality indicators using FT-MIR spectroscopy and chemometrics

Abstract

Diesel control by routine methods involves the use of heavy techniques that are generally costly and hazardous. Moreover, these techniques require using several reagents that are harmful for the environment. Methods for rapid and accurate characterization of petroleum derivatives properties are needed to ensure the quality of these essential products. Herein, we tested the application of Fourier transform medium infrared spectroscopy (FT- MIR) for the rapid characterization of key performance-related diesel properties. The proposed methodology, based on the use of Partial Least Square Regression (PLSR), led to accurate predictions of ten properties of in- terest, namely, the viscosity, density, color, flash point, conductivity, cetane number, cold filter plugging point, pour point, 40% of the distillation fraction and water content. The prediction models yield high correlation coefficients between the observed and the predicted responses (around 0.90) and satisfactory cross-validation and prediction error (RMSEP and RMSECV) values. Therefore, the proposed approach that uses the medium infrared spectroscopy (MIR) for quality indicators estimation can be highly recommended as an accurate, eco- friendly, rapid, and reliable solution.
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Dates and versions

hal-03639259 , version 1 (12-04-2022)

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Issam Barra, Mohammed Alaoui Mansouri, Tarik El Moatassem, Mourad Kharbach, Hicham Abou Oualid, et al.. Prediction of diesel fuel quality indicators using FT-MIR spectroscopy and chemometrics. Infrared Physics and Technology, 2022, 122, pp.104096. ⟨10.1016/j.infrared.2022.104096⟩. ⟨hal-03639259⟩
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