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Solubility data is one of the essential basic data for CO2 capture by ionic liquids. A selective ensemble modeling method, proposed to overcome the shortcomings of current methods, was developed and applied to the prediction of the solubility of CO2 in imidazolium ionic liquids. Firstly, multiple different sub–models were established based on the diversities of data, structural, and parameter design philosophy. Secondly, the fuzzy C–means algorithm was used to cluster the sub–models, and the collinearity detection method was adopted to eliminate the sub–models with high collinearity. Finally, the information entropy method integrated the sub–models into the selective ensemble model. The validation of the CO2 solubility predictions against experimental data showed that the proposed ensemble model had better performance than its previous alternative, because more effective information was extracted from different angles, and the diversity and accuracy among the sub–models were fully integrated. This work not only provided an effective modeling method for the prediction of the solubility of CO2 in ionic liquids, but also provided an effective method for the discrimination of ionic liquids for CO2 capture.

Prediction of the Solubility of CO2 in Imidazolium Ionic Liquids Based on Selective Ensemble Modeling Method