Prediction of Azeotropic Temperature and Composition of Binary Azeotrope Containing Water Based on Quantitative Structure-Property Relationship

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Abstract Several prediction models based on quantitative structure-property relationship, which was performed for estimating azeotropic temperature and composition of 125 binary azeotropes containing water at 101.325 kPa, were established. First of all, the three-dimensional molecular structure of each pure component was plotted by HyperChem 8.0 software, meanwhile the pre-optimization and further optimization of the molecular structure were implemented by the molecular mechanics method and the quantum mechanics semi-empirical method, respectively. Besides, the stable structures with minimum energy were imported into Material Studio 8.0 software to calculate descriptors. Moreover, the feature descriptors which were most associated with azeotropic temperature or composition were selected by genetic algorithm. Then, the azeotropic temperature and composition prediction models were built by using multiple linear regression methods. In the last place, the established optimal model was internally validated, externally validated, applied domain analyzed, compared with similar models in the literature and UNIFAC group contribution method. The results show that the optimal azeotropic temperature and composition prediction model that was made up of 8/5 feature descriptors, which multiple correlation coefficient, adjusted multiple correlation coefficient, root mean square errors, mean absolute deviation, leave-one-out cross-validation coefficient and external validation coefficient were 0.960 6/0.997 0, 0.957 2/0.996 9, 2.94/0.016 1, 1.89/0.010 4, 0.947 5/0.995 7 and 0.943 9/0.997 6,respectively, and the established optimal models were provided with more excellent stability, favorable generalization and fantastic predictive than the similar models.

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	Articles by authors
	Zeng Xingyan
	Zhu Lin
	Lü Liping
	Li Bing

Keywords： quantitative structure-property relationship (QSPR)； azeotropic temperature； azeotropic composition； prediction； a binary azeotrope containing water

Received 2019-07-02;

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Zeng Xingyan, Zhu Lin, Lü Liping, Li Bing.Prediction of Azeotropic Temperature and Composition of Binary Azeotrope Containing Water Based on Quantitative Structure-Property Relationship[J] Chemcial Industry and Engineering, 2020,V37(4): 30-39

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