New mathematical modeling of temperature-based properties of ionic liquids mixture: Comparison between semi-empirical equation and equation of state

[Display omitted] •Modeling of four temperature-based properties of IL-mixture using semi-empirical correlations.•Determination semi-empirical equation coefficients for each cation-family with novel optimization algorithm.•Investigation accuracy of cubic EoS, non-cubic EoS and semi-empirical correlation on IL-mixture density. Ionic liquids are a significant type of organic salts with attractive and superior physicochemical features for employing in a number of chemical processes. Ionic liquids include one large and asymmetric cationic or anionic functional group. The properties of cationic functional group are almost similar and it is main motivation of this study. In the present investigation, we extended various semi-empirical correlations to predict some temperature-based properties of ionic liquids mixture (IL-mixture). These properties are density, viscosity, surface tension and bubble point pressure. In the case of IL-mixture density, modified Rackett equation and Taylor equation with three scenarios, modified Gardas and Coutinho equation were considered and the obtained results were compared with Peng-Robinson equation of state (EoS), Patel-Teja EoS and perturbed-chain statistical associating fluid theory EoS. In the case of IL-mixture viscosity, two types of activation energy concept models were used and also, Lee-Kesler method and modified Brock and Bird were applied to predict IL-mixture bubble point pressure and IL-mixture surface tension, respectively. A used dataset was collected from reliable literature including 2731 data points of bubble pressure (23 binary system), 4643 data points of density (102 binary system), 1011 data points of viscosity (32 binary system) and 391 data points of surface tension (16 binary system). These data relevant to 12 cation-family and 36 solvents. The all of the data was haphazardly separated in two subsets of train and test with a computer program. The obtained results indicated all used semi-empirical correlations gives the best match with corresponding experimental data and the values of statistical parameters demonstrated this hypothesis.