Modeling the thermodynamic properties of imidazolium ionic liquids in water, methanol, and ethanol using SAFT-VRE Mie and eSAFT-VR Mie equations of state

• Ion-specific SAFT parameters were derived exclusively from pure-IL densities, with ion-solvent and ion-ion interactions modeled using a simplified Hudson-McCoubrey rule. • Six static permittivity approaches were evaluated within both SAFT-VRE Mie and eSAFT-VR Mie frameworks. • A novel Born size interpretation was introduced, explicitly accounting for hydrogen-bonding in ILs, showing direct correlation with SAFT parameters. • Incorporation of ionic effects improves the accuracy of SAFT-VR Mie in predicting densities of IL + water/methanol/ethanol mixtures. We evaluate the performance of two electrolyte variants of the Statistical Associating Fluid Theory for Variable Range interactions (SAFT-VR) in the generic Mie form, the SAFT-VRE Mie and eSAFT-VR Mie equations of state, in predicting liquid-phase densities and the speed of sound for imidazolium-based ionic liquids (ILs) and their mixtures with water, methanol, and ethanol. A strictly predictive modeling strategy was employed: only pure-component IL densities were used to derive ion-specific molecular parameters (segment length, size, and energy) for imidazolium-based cations and anions, while solvent parameters were taken from the literature. Ion-solvent and ion-ion pair interactions were calculated via a simplified Hudson-McCoubrey combining rule, assuming equal ionization potentials and avoiding any binary parameter fitting. Six formulations of the relative static permittivity (constant, temperature‐dependent, linear in composition, and a volumetric‐composition model) were evaluated within both the SAFT-VRE Mie and eSAFT-VR Mie frameworks. We introduce a novel Born size interpretation that explicitly accounts for hydrogen‐bonding in IL ions, yielding improved agreement with experimental data. Furthermore, we identify quantitative correlations between these Born size and the underlying SAFT parameters, enabling predictive parametrization of related IL systems. The electrolyte models enhance performance over the SAFT-VR Mie, particularly in mixed‐solvent regions, though further refinement is needed near the pure‐IL limit. All calculations were conducted using the open‐source Clapeyron.jl toolkit, ensuring full reproducibility and extensibility.