A new group contribution method based on GCVOL model developed by Elbro et al. in 1991 [Elbro, H. S.; Fredenslund, A.; Rasmussen, P. Ind. Chem. Eng. Res. 1991, 30, 2576–2582] is proposed for the estimation of ionic liquids density over a wide range of temperature and pressure. A total of 102 new groups for ionic liquids were introduced to the already 60 existing groups revised and proposed in 2003 by Ihmels and Gmehling [Ihmels, E. C.; Gmehling, J. Ind. Chem. Eng. Res. 2003, 42, 408–412]. These groups were proposed based on a collection of density data from literature. The databank contains data of 864 different ionic liquids, including dicationic and tricationic species, and a total of 21 845 data points, covering a temperature range of 251.62–473.15 K and a pressure range of 0.1–300.0 MPa. An average absolute relative deviation (%AARD) of 0.83% was obtained, indicating that our model is able to predict densities of a great variety of ionic liquids accurately.

This work presents density (ρ) and viscosity (μ) data and correlations of binary and ternary blends containing soybean oil, soybean biodiesel, and petroleum diesel. The data were obtained for different composition ranges, for binary blends data were obtained in a mass fraction (w) in an interval of 0.100 to 0.900. Additionally, ternary data were taken by a random range, at T = (293. 15, 313.15, 333.15, 353.15, and 373.15) K, at atmospheric pressure. The experimental data were compared to predictive models based on group contribution method. Density and viscosity data were correlated by a temperature and composition equation (T and w, as independent variables). A statistical analysis has been designed by using chi-square distribution, which revealed an agreement between experimental and estimated data better than 99.5 %.

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Several models based on the Group Contribution concept and on the Corresponding States Principle were reviewed for the estimation of vapor pressures and enthalpies of vaporization of fatty acid methyl and ethyl esters commonly occurring in biodiesel. The accuracy of each model was tested by comparing its output values to experimental data obtained from the literature. For vapor pressures, the number of occurrences where the methods failed completely have also been analyzed. Efforts were made to identify the best method for the estimation of each property and it was observed that the models' reliability depend on the type of ester and on the operational conditions (pressure and temperature) considered.