thermodynamic modeling of ionic liquid physical properties

This research focused on investigating the thermophysical characteristics of seven selected ionic liquids (ils), specifically [cn-tea][tfsi], and on developing predictive models for these properties using three different thermodynamic approaches. the pc-saft equation of state (eos) was employed to estimate density, the fvt model was applied to forecast dynamic viscosity, and the mpelofsky model was utilized to compute surface tension. to enhance the accuracy of these models, experimental data from three ils with differing alkyl chain lengths were used. a nonlinear least-squares technique was employed to adjust the model parameters by minimizing the discrepancies between the predicted values and the experimental results. following this, a generalized function was formulated to link the optimized model parameters with the number of carbon atoms in the cationic alkyl chains of the ils. this function allowed for the estimation of model parameters for the remaining four ils. the performance of the models was evaluated using average absolute deviations (aads%). the developed models showed strong predictive capability for the thermo-physical properties of the ils. in the correlation approach, the aads% were 0.0163 for density, 4.5534 for viscosity, and 0.1731 for surface tension. for the prediction approach, the deviations were somewhat higher at 0.0780% for density, 6.1122% for dynamic viscosity, and 1.2821% for surface tension. these findings suggest that the models can effectively predict the properties of other ils within the same chemical family, offering a valuable tool for further studies.