Predicting CO2 Solubility in Aqueous and Organic Electrolyte Solutions with Epc-Saft Advanced

Solvent influence and salt influence on CO2 solubility are essential factors toward the development of processes involving CO2 conversion. In this work, the equation of state (EOS) electrolyte Perturbed-Chain Statistical Associating Fluid Theory (ePC-SAFT advanced) was applied to model the CO2 solubility in single organic solvents (methanol, ethanol, N-methyl-2-pyrrolidone, dimethyl sulfoxide, tetrahydrofuran, dimethylformamide, gamma-valer-olactone, and acetonitrile). Further, CO2 solubility was predicted in aqueous solvent mixtures and in aqueous electrolyte solutions (NaCl, KCl, CsCl, MgCl2, CaCl2, NaNO3, KNO3, Mg(NO3)2, Ca(NO3)2, Na2SO4, K2SO4, MgSO4, NaHCO3, and K2CO3) with water as single solvent as well as in aqueous alcoholic solvent mixtures. CO2 solubility in systems with a lack of data (CsCl) was measured in this work with a high-pressure variable-volume view cell. Broad ranges of temperatures, pressures, and high concentrations of electrolytes were considered, and solvent effects, ion effects, and pH effects were studied. The nature of the considered systems required including dissociation reactions of carbonic acid in the modeling framework, most importantly for the systems containing carbonate salts. The results showed that i) CO2 solubility was the highest in non-polar solvents, ii) all salts caused salting-out effects on the CO2 solubility except carbonates (an apparent salting-in due to a pH shift), and that iii) the strength of salting-out effect was related to the charge density of the ions. The salt influence on CO2 solubility was predicted qualitatively correct with ePC-SAFT advanced; that is, fitting binary interaction parameters be-tween ions and CO2 was not necessary, which is a result found for the first time. Finally, ePC-SAFT advanced allowed predicting the CO2 solubility in multi-component systems containing solvent mixtures, salt mixtures, or a solvent mixture with an additional salt over a broad range of conditions in good agreement with available literature data.