SCI和EI收录∣中国化工学会会刊

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 Habibzadeh1,3, Zhi'en Zhang4   

  1. 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 E-mail:Alireza_baghban@alumni.ut.ac.ir;zhienzhang@hotmail.com

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

Alireza Baghban1, Jafar Sasanipour2, Sajjad Habibzadeh1,3, Zhi'en Zhang4   

  1. 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 E-mail:Alireza_baghban@alumni.ut.ac.ir;zhienzhang@hotmail.com

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