Eyring’s absolute rate theory was applied for evaluation of the viscosity of ionic liquids (ILs) containing binary mixtures. Considering the mathematical simplicity of the two-suffix-margules model, the Gibbs energy model was further modified. Furthermore, for viscosity evaluation, the proposed Gibbs energy model was coupled with Eyring’s theory. To validate the accuracy of the proposed model, a large set of data containing the binary mixtures of 122 ILs with a total number of 5512 experimental data points was collected from the literature. Moreover, the average absolute relative deviation (AARD %) was obtained as 2.07 %. Also, the capability of the Eyring–MTSM model was tested for the prediction of viscosity for binary and ternary systems. Additionally, comparison of the proposed model with the Eyring–NRTL model indicated a higher accuracy for our model. Finally, the Eyring–UNIFAC model was also checked, and it was found that this model is not accurate enough in its present form.

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The present study was conducted to develop a predictive type of PC-SAFT EOS by incorporating the COSMO computations. With the proposed model, the physical adjustable inputs to PC-SAFT EOS were determined from the suggested correlations with dependency to COSMO computation results. Afterwards, we tested the reliability of the proposed predictive PC-SAFT EOS by modeling the solubility data of certain pharmaceutical compounds in pure and mixed solvents and their octanol/water partition coefficients. The obtained RMSE based on logarithmic scale for the predictive PC-SAFT EOS was 1.435 for all of the solubility calculations. The reported values (1.435) had a lower value than RMSE for COSMO-SAC model (4.385), which is the same as that for RMSE for COSMO-RS model (1.412). The standard RMSE for octanol/water partition coefficient of the investigated pharmaceutical compounds was estimated to be 1.515.

The objective of this study is to develop a model to determine the thermal conductivity of pure ionic liquids and Ionanofluids. In order to estimate the thermal conductivity of pure ionic liquids, a group method of data handling model is proposed based on 23 ionic liquids corresponding to 216 experimental data points.The average absolute relative deviation for all studied systems was 1.81%, which is a satisfactory degree of accuracy for the proposed model. Furthermore, the Maxwell model is modified to correlate the thermal conductivity of Ionanofluids as a function of temperature and volume fraction of nanoparticles. The average absolute relative deviation for this model is 0.61%. Additionally, Maxwell and modified geometric mean (mGM) models are used to evaluate the models that * Corresponding predict the thermal conductivity of Ionanofluids. The results show that mGM is more accurate for prediction of thermal conductivity of Ionanofluids.