Predicting the solubility of CO₂ and N₂ in ionic liquids based on COSMO-RS and machine learning.

ABSTRACT: As ionic liquids (ILs) continue to be prepared, there is a growing need to develop theoretical methods for predicting the properties of ILs, such as gas solubility. In this work, different strategies were employed to obtain the solubility of CO₂ and N₂, where a conductor-like screening model for real solvents (COSMO-RS) was used as the basis. First, experimental data on the solubility of CO₂ and N₂ in ILs were collected. Then, the solubility of CO₂ and N₂ in ILs was predicted using COSMO-RS based on the structures of cations, anions, and gases. To further improve the performance of COSMO-RS, two options were used, i.e., the polynomial expression to correct the COSMO-RS results and the combination of COSMO-RS and machine lear

SUBMITTER: Qin H 

PROVIDER: S-EPMC11560425 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature