Prediction of properties of biodiesel-diesel blends using spectrofluorimetry and multivariate calibration

Abstract

© Versita Sp. z o.o. Received 21 February 2012; Accepted 19 April 2012 Keywords: Concentration • Specific gravity • Viscosity • Spectrofluorimetry • Multivariate calibrationRegressions based on fluorescence spectroscopy were developed to provide relatively inexpensive and rapid measurements of the concentration, viscosity, and specific gravity of biodiesel-diesel blends. The methods involved obtaining a mathematical model from spectrofluorimetric data and data from a given property (concentration, dynamic viscosity, or specific gravity) using partial least squares (PLS) regression, which was then applied as a model for predicting properties of interest. The predicted concentrations, dynamic viscosities, and specific gravities of the biodiesel-diesel blends were compared with actual values and agreed reasonably well with the obtained results. The models showed high correlation between real and predicted values. The R-square values near 1 indicated excellent model accuracy for predicting concentrations, specific gravities, and dynamic viscosities of biodiesel-diesel blends. The residual distribution did not follow a trend with respect to the predicted variables, indicating an excellent fit to the data.

Identificação de substâncias puras ou em formulações através de análise espectral e quimiometria

“…5) Avaliam a degradação do papel isolante em transformadores de alta potência 74 . 6) Permitem a predição das propriedades de blendas de biodiesel em diesel inclusive de massa específica e viscosidade por métodos óticos 6,29,75 . 7) Fazem a identificação de adulteração de biocombustível por adição de óleo residual ao diesel por espectrofluorimetria total 3D e análise das componentes principais 3 .…”

Prediction of Kinematic Viscosity and Density of Biodiesel Using Electrospray Ionization Mass Spectrometry by Multivariate Statistical Models

“…In the literature there are models to predict some biodiesel properties: Meira et al (2012) 5 used fluorescence spectroscopy to predict the kinematic viscosity and density of biodiesel/diesel blends by using the PLSR. Meng et al (2014) 6 applied artificial neural network (ANN) to predict the kinematic viscosity of biodiesel with the data collected from the literature, using mass fractions of methyl esters.…”

Environmentally Friendly Determination of Quality Parameters of Biodiesel/Diesel Blends Using Fourier Transform Infrared Spectra

“…Biodiesel is traditionally obtained by the transesterification reaction of a fat or oil with short chain alcohols in the presence of a catalyst [1]. The most attractive features of this biofuel are the possibility of production from vegetable oils and recycled fats, its high miscibility with petrochemical diesel, its biodegradability, and its low or null content of sulfur derivatives, sulfur being the major cause of atmospheric pollution [2].…”