Estimating solubility of supercritical H2S in ionic liquids through a hybrid LSSVM chemical structure model

doi:10.1016/j.cjche.2018.08.026

中国化学工程学报 ›› 2019, Vol. 27 ›› Issue (3): 620-627.DOI: 10.1016/j.cjche.2018.08.026

• Chemical Engineering Thermodynamics • 上一篇下一篇

Estimating solubility of supercritical H₂S in ionic liquids through a hybrid LSSVM chemical structure model

Alireza Baghban¹, Jafar Sasanipour², Sajjad Habibzadeh^1,3, Zhi'en Zhang⁴

1 Chemical Engineering Department, Amirkabir University of Technology, Mahshahr Campus, Mahshahr, Iran;
2 Gas Engineering Department, Petroleum University of Technology, Ahwaz, Iran;
3 Chemical Engineering Department, Amirkabir University of Technology, Tehran, Iran;
4 Key Laboratory of Low-grade Energy Utilization Technologies and Systems, Ministry of Education of China, Chongqing University, Chongqing 400044, China

收稿日期:2018-03-28 修回日期:2018-08-01 出版日期:2019-03-28 发布日期:2019-04-25
通讯作者: Alireza Baghban,E-mail addresses:Alireza_baghban@alumni.ut.ac.ir;Zhi'en Zhang,E-mail addresses:zhienzhang@hotmail.com

Estimating solubility of supercritical H₂S in ionic liquids through a hybrid LSSVM chemical structure model

Alireza Baghban¹, Jafar Sasanipour², Sajjad Habibzadeh^1,3, Zhi'en Zhang⁴

1 Chemical Engineering Department, Amirkabir University of Technology, Mahshahr Campus, Mahshahr, Iran;
2 Gas Engineering Department, Petroleum University of Technology, Ahwaz, Iran;
3 Chemical Engineering Department, Amirkabir University of Technology, Tehran, Iran;
4 Key Laboratory of Low-grade Energy Utilization Technologies and Systems, Ministry of Education of China, Chongqing University, Chongqing 400044, China

Received:2018-03-28 Revised:2018-08-01 Online:2019-03-28 Published:2019-04-25
Contact: Alireza Baghban,E-mail addresses:Alireza_baghban@alumni.ut.ac.ir;Zhi'en Zhang,E-mail addresses:zhienzhang@hotmail.com

摘要/Abstract

摘要： Development of a predictive tool for H₂S solubility estimation can be very helpful in gas sweetening industry. Experimental databases on H₂S solubility were rarely available, so as reliable predictive models. Thus, in this study the H₂S solubility database was established, and then a Least-Squares Support Vector Machine (LSSVM) approach based on the established database is proposed. Group contribution method was also applied to eliminate the model's dependence on experimental data. Accordingly, our proposed LSSVM model can predict H₂S solubility as a function of temperature, pressure, and 15 different chemical structures of Ionic liquids (ILs). Root Mean Square Error (RMSE) and coefficient of determination (R²) are 0.0122 and 0.9941, respectively. Moreover, comparison of our model with other existing models showed its reliability for H₂S solubility in ILs. This can be very useful for engineers dealing with gas sweetening process in different applications of analysis, simulation, and designation.

关键词: Ionic liquid, Hydrogen sulfide, LSSVM, Group contribution method

Abstract: Development of a predictive tool for H₂S solubility estimation can be very helpful in gas sweetening industry. Experimental databases on H₂S solubility were rarely available, so as reliable predictive models. Thus, in this study the H₂S solubility database was established, and then a Least-Squares Support Vector Machine (LSSVM) approach based on the established database is proposed. Group contribution method was also applied to eliminate the model's dependence on experimental data. Accordingly, our proposed LSSVM model can predict H₂S solubility as a function of temperature, pressure, and 15 different chemical structures of Ionic liquids (ILs). Root Mean Square Error (RMSE) and coefficient of determination (R²) are 0.0122 and 0.9941, respectively. Moreover, comparison of our model with other existing models showed its reliability for H₂S solubility in ILs. This can be very useful for engineers dealing with gas sweetening process in different applications of analysis, simulation, and designation.

Key words: Ionic liquid, Hydrogen sulfide, LSSVM, Group contribution method

Alireza Baghban, Jafar Sasanipour, Sajjad Habibzadeh, Zhi'en Zhang. Estimating solubility of supercritical H₂S in ionic liquids through a hybrid LSSVM chemical structure model[J]. 中国化学工程学报, 2019, 27(3): 620-627.

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Estimating solubility of supercritical H₂S in ionic liquids through a hybrid LSSVM chemical structure model

Estimating solubility of supercritical H₂S in ionic liquids through a hybrid LSSVM chemical structure model

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