Accurate Prediction of the Surface Tensions of Ionic Liquids–Amines–Water Mixtures Regarding CO2 Recovery and Sequestration Processes

Abstract

A support vector machine (SVM) model is presented concerning accurate prediction of the surface tension of the complex mixtures of ionic liquids (ILs)–amines–water using the most important types of amines employed in the gas sweetening plants, such as monoethanolamine, diethanolamine, and methyldiethanolamine. Different ILs, such as [bmim] [BF4], [bmim] [DCA], [mmim] [dmp], [emim] [dep], [bmim] [BF4], [bmim] [Br], [bmim] [BF4], and [bmim] [Br], are considered in the presented model. The effects of most important influencing parameters, such as temperature and mass fraction of amines and ILs, on the surface tension of the aqueous mixtures of ILs and amines are well represented. A comparison of the presented model and the most important models reveals that the suggested SVM model has better performance in terms of accuracy and generalizability. The percentage average absolute deviation between the predicted and experimental surface tensions is about 0.44% suggesting the superiority of the presented model over wide ranges of temperatures and species concentrations.