Ionic liquids (ILs) are promising fluidic materials due to their unique physicochemical properties, driving extensive research for diverse applications. Key properties, including thermodynamic properties (e.g., density and solubility) and transport properties (e.g., viscosity and self-diffusion coefficient (SDC)), play a crucial role in developing IL-based technologies. These properties are typically characterized through experiments and theoretical modeling. However, given the time-consuming and costly nature of experiments, developing accurate theoretical models is essential for optimizing IL-based applications.

Thermodynamic models for various fluids, including ILs, are well-established, with the ion-specific electrolyte perturbed-chain statistical associating fluid theory (ePC-SAFT) effectively modeling the thermodynamic properties of ILs. In contrast, transport property models depend largely on experimental data, leading to separate modeling of viscosity and SDC. For viscosity, ePC-SAFT has coupled with free volume theory (ePC-SAFT-FVT), but inconsistencies arise between ion- and molecular-based frameworks in the two models. Meanwhile, theoretical SDC models are scarce and have yet to be applied to ILs. Traditionally, thermodynamic and transport property models use distinct molecular parameters, though, in principle, these parameters should be independent of specific properties. This suggests the feasibility of a universal approach to determining transport properties based on molecular parameters of thermodynamic models. Additionally, as both viscosity and SDC characterize molecular motion, it remains unclear whether they can be simultaneously modeled for ILs.

This thesis aimed to propose a universal approach to modeling thermodynamic and transport properties of ILs, where a predictive SDC model and an ion-specific ePC-SAFT-FVT for viscosity were developed, and the Einstein relation was employed to explore the simultaneous modeling of viscosity and SDC.

• In the first part, the SDC model for LJ fluids was extended to chain-like fluids using a correction function, with viscosity calculated via the Stokes-Einstein equation. By fitting SDC and viscosity data for 19 n-alkanes using molecular parameters from ePC-SAFT, a universal parameter set was obtained, achieving AARDs of 8.4% for SDC and 7.2% for viscosity. These parameters were used to predict the SDC and viscosity of long n-alkanes, branched alkanes, and cyclic compounds, with higher deviations for the latter two. The model was then extended to ILs, yielding AARDs of 39.4% for SDC and 30.1% for viscosity, with the performance considered acceptable due to using only three universal parameters.
• In the second part, an ion-specific ePC-SAFT-FVT model was developed to describe the viscosities of 72 ILs. The ion-based approach achieves an AARD of 8.7%, comparable to the molecular-based approach (AARD = 6.1%), while significantly reducing the number of adjustable parameters from 216 to 81. This enhances flexibility by enabling cation-anion parameter combinations for predictions. The model was extended to 19 IL mixtures, yielding an AARD of 9.1%, outperforming the molecular-based approach (AARD = 12.7%). These results show the ion-specific ePC-SAFT-FVT model effectively represents the viscosity of pure ILs and their mixtures.
• In the third part, the Einstein relation was combined with the ePC-SAFT-FVT model to describe the SDCs of ILs. Viscosity-derived FVT parameters were used to calculate the sum of ionic SDCs, requiring only one adjustable parameter. This parameter was either fitted for each IL (AARD = 8.1%) or predicted from the van der Waals volume (AARD = 10.3%). The predictive approach was also applied to calculate cationic and anionic SDCs using the total SDC and cationic transference number, yielding AARDs of 10.8% and 10.2%, respectively. These results show that, by utilizing viscosity-derived parameters, the ePC-SAFT-FVT model combined with Einstein relation effectively predicts the SDCs of ILs.