The superior properties of specific ionic liquids (ILs), such as negligible volatility, high thermal stability, flexible designability, and their affinity to capture CO2, make them an attractive alternative to chemical and physical solvents that are currently used in CO2 capture processes. However, a limitation to use ILs for industrial CO2 capture is their high viscosity compared to conventional solvents, which leads to a lower CO2 capture rate and higher pumping cost. The viscosity of ILs can be reduced by adding a co-solvent, such as water or methanol. In this work, solubility, vapor–liquid equilibria (VLE), and liquid–liquid equilibria (LLE) for binary and ternary mixtures involving CO2, ILs, water, and methanol have been systematically investigated by employing perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state with two different strategies. ILs were considered as self-associating chain molecules with two association sites in the first strategy. As a comparison, they were regarded as strong electrolytes that dissociate into anions and cations in the second strategy. It was found that both strategies provide accurate correlations in modeling CO2 solubilities in ILs and LLE of binary ILs/water systems. Four ternary systems were selected to verify the predictive capability of the two strategies. For water-containing systems, both strategies performed excellently when binary interaction parameters (BIPs) can be obtained by fitting to experimental data, while they performed poorly for system with few experimental data. For cases where methanol acted as a co-solvent, accurate predictions were obtained with both strategies, even without any BIPs. PC-SAFT was found to be a potential practical tool to develop CO2 capture processes with new alternative solvents when there are sufficient experimental data for binary mixtures.
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