Abstract
Reducing the emissions of greenhouse gas is a worldwide problem that needs to be solved urgently for sustainable development in the future. The solubility of CO2 in ionic liquids is one of the important basic data for capturing CO2. Considering the disadvantages of experimental measurements, e.g., time-consuming and expensive, the complex parameters of mechanism modeling and the poor stability of single data-driven modeling, a multi-model fusion modeling method is proposed in order to predict the solubility of CO2 in ionic liquids. The multiple sub-models are built by the training set. The sub-models with better performance are selected through the validation set. Then, linear fusion models are established by minimizing the sum of squares of the error and information entropy method respectively. Finally, the performance of the fusion model is verified by the test set. The results showed that the prediction effect of the linear fusion models is better than that of the other three optimal sub-models. The prediction effect of the linear fusion model based on information entropy method is better than that of the least square error method. Through the research work, an effective and feasible modeling method is provided for accurately predicting the solubility of CO2 in ionic liquids. It can provide important basic conditions for evaluating and screening higher selective ionic liquids.
Highlights
Nowadays, energy crises and environmental issues are frontier problems that arouse great concern.Reducing the emissions of CO2 is one of the crucial challenges for sustainable development in the future
544 sets of samples from nine ionic liquids (ILs) were collected from the literature, and divided into a training set, validation set and test set according to a certain proportion
A fusion modeling method was proposed for predicting the solubility of neural
Summary
Energy crises and environmental issues are frontier problems that arouse great concern.Reducing the emissions of CO2 is one of the crucial challenges for sustainable development in the future. The ionic liquids (ILs) have some properties of low volatility, high solubility and high selectivity, which make them increasingly interesting in capturing CO2. These advantages make the ILs considered as a relatively novel type of solvents [1,2,3,4]. E.g., the non-ideal behavior of the research system, the complexity of ionic liquid system, the limited measurement conditions, the time-consuming and high costs on the measurement of ILs, it is impossible to obtain the solubility by the experimental measurement method for practical applications [7,8]. The modeling methods mainly consist of mechanism modeling and data-driven modeling
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