Screening Deep Eutectic Solvents for CO2 Capture With COSMO-RS

Abstract

In this work, 502 experimental data for CO 2 solubilities and 132 for Henry's constants of CO 2 in DESs were comprehensively summarized from literatures and used for further verification and development of COSMO-RS. Large systematic deviations of 62. 2, 59.6, 63.0, and 59.1% for the logarithmic CO 2 solubilities in the DESs (1:2, 1:3, 1:4, 1:5), respectively, were observed for the prediction with the original COSMO-RS, while the predicted Henry's constants of CO 2 in the DESs (1:1.5, 1:2, 1:3, 1:4, 1:5) at temperatures ranging of 293.15-333.15 K are more accurate than the predicted CO 2 solubility with the original COSMO-RS. To improve the performance of COSMO-RS, 502 data points of CO 2 solubility in the DESs (1:2, 1:3, 1:4, 1:5) were used for correcting COSMO-RS with a temperature-pressure dependent parameter, and the CO 2 solubility in the DES (1:6) was predicted to further verify the performance of the corrected model. The results indicate that the corrected COSMO-RS can significantly improve the model performance with the ARDs decreasing down to 6.5, 4.8, 6.5, and 4.5% for the DESs (1:2, 1:3, 1:4, and 1:5), respectively, and the corrected COSMO-RS with the universal parameters can be used to predict the CO 2 solubility in DESs with different mole ratios, for example, for the DES (1:6), the corrected COSMO-RS significantly improves the prediction with an ARD of 10.3% that is much lower than 78.2% provided by the original COSMO-RS. Additionally, the result from COSMO-RS shows that the σ-profiles can reflect the strength of molecular interactions between an HBA (or HBD) and CO 2 , determining the CO 2 solubility, and the dominant interactions for CO 2 capture in DESs are the H-bond and Van der Waals force, followed by the misfit based on the analysis of the predicted excess enthalpies.

Predictive molecular thermodynamic models for ionic liquids

“…As a powerful and efficient method, the COSMO‐RS model first proposed by Klamt 29 has been extensively employed to predict the thermophysical properties of neat and mixed liquids containing ILs; it is also treated as an a priori model because it is independent of experimental data 30–33 . The COSMO‐RS model has been applied to predict the VLE, LLE, infinite dilution activity coefficients (IDACs), gas solubility, and so forth of a broad array of systems associated with ILs as well as molecular mechanism identification in chemical separation and reaction processes 34–44 …”

Harnessing the power of machine learning for carbon capture, utilisation, and storage (CCUS) – a state-of-the-art review

“…ML has been used to perform solvent screening for different applications 80,81 . Some studies related to solvent screening for CO 2 absorption have been done using the COSMO-RS thermodynamic model 82,83 . However, it should be noted that the number of studies related to the application of ML in the solvent selection and design for CO 2 absorption is considerably less than the application of ML in other types of studies related to CO 2 absorption, which are reviewed in previous sections.…”

Deep Eutectic Solvents as Active Pharmaceutical Ingredient Delivery Systems in the Treatment of Metabolic Related Diseases

“…The cytotoxicity of N,N-diethylammonium chloride (DAC) based and choline chloride based DES were evaluated by investigating the interaction of DESs and cancer cell lines (HelaS3, AGS, MCF-7 and WRL-68) with the conductor-like screening model for real solvents (Liu et al, 2020;Mbous et al, 2020;Rezaei Motlagh et al, 2020). The results revealed that DAC based DESs (IC50 interval, 37-109 mM) were more toxic than choline chloride based DESs (IC50 interval, 279-1,260 mM), indicating the potential of DAC based DESs as an anticancer agent.…”