LAPSE:2021.0370
Published Article
LAPSE:2021.0370
Prediction of the Solubility of CO2 in Imidazolium Ionic Liquids Based on Selective Ensemble Modeling Method
Luyue Xia, Shanshan Liu, Haitian Pan
May 17, 2021
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.
Keywords
Carbon Dioxide, fuzzy C–means, ionic liquids, Modelling, prediction, selective ensemble, solubility
Suggested Citation
Xia L, Liu S, Pan H. Prediction of the Solubility of CO2 in Imidazolium Ionic Liquids Based on Selective Ensemble Modeling Method. (2021). LAPSE:2021.0370
Author Affiliations
Xia L: College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, Zhejiang, China; Zhejiang Province Key Laboratory of Biomass Fuel, Hangzhou 310014, Zhejiang, China [ORCID]
Liu S: College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, Zhejiang, China
Pan H: College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, Zhejiang, China; Zhejiang Province Key Laboratory of Biomass Fuel, Hangzhou 310014, Zhejiang, China
Journal Name
Processes
Volume
8
Issue
11
Article Number
E1369
Year
2020
Publication Date
2020-10-28
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr8111369, Publication Type: Journal Article
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LAPSE:2021.0370
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doi:10.3390/pr8111369
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May 17, 2021
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May 17, 2021
 
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Calvin Tsay
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