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Predicting H2S solubility in ionic liquids by the quantitative structure-property relationship method using S sigma-profile molecular descriptors
Zhao, Yongsheng1,2; Gao, Jubao1; Huang, Ying3; Afzal, Raja Muhammad1; Zhang, Xiangping1; Zhang, Suojiang1
2016
Source PublicationRSC ADVANCES
ISSN2046-2069
Volume6Issue:74Pages:70405-70413
Abstract

Predicting hydrogen sulfide (H2S) solubility in ionic liquids (ILs) is vital for industrial gas desulphurization. In this work, the qualitative analysis of the influence of cations and anions on the H2S solubility in ILs has been conducted. The results indicate that anions play an important role in determining the H2S solubility in ILs. Subsequently, two novel quantitative structure-property relationship (QSPR) models are developed based on charge distribution area (S sigma-profile) descriptors and an extreme learning machine (ELM) algorithm. To develop the QSPR models, a total of 1282 pieces of data belonging to 27 ILs are employed to validate the models. The average absolute relative deviation (AARD%) and coefficient of determination (R-2) of the two QSPR models of the entire data set are 3.73% and 0.998, as well as 3.80% and 0.997, respectively. These results suggest that the proposed QSPR models can be useful for the prediction of H2S solubility in ILs.

SubtypeArticle
WOS HeadingsScience & Technology ; Physical Sciences
DOI10.1039/c6ra15429h
Indexed BySCI
Language英语
WOS KeywordCOSMO-RS ; HYDROGEN-SULFIDE ; CO2 ; BIS(TRIFLUOROMETHYL)SULFONYLIMIDE ; HEXAFLUOROPHOSPHATE ; ABSORPTION ; SEPARATION ; DIFFUSION ; MIXTURES ; SOLVENTS
WOS Research AreaChemistry
WOS SubjectChemistry, Multidisciplinary
Funding OrganizationNational Basic Research Program of China(2015CB251403) ; National Natural Science Fund for Distinguished Young Scholars(21425625) ; key program of Beijing Municipal Natural Science Foundation(2141003) ; National Natural Science Foundation of China(21506219)
WOS IDWOS:000381512800088
Citation statistics
Cited Times:11[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ipe.ac.cn/handle/122111/21455
Collection多相复杂系统国家重点实验室
Affiliation1.Chinese Acad Sci, Beijing Key Lab Ion Liquids Clean Proc, Inst Proc Engn, State Key Lab Multiphase Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Chem & Chem Engn, Beijing 100049, Peoples R China
3.China HuanQiu Contracting & Engn Corp, Proc Simulat Technol Dept, Beijing 100012, Peoples R China
Recommended Citation
GB/T 7714
Zhao, Yongsheng,Gao, Jubao,Huang, Ying,et al. Predicting H2S solubility in ionic liquids by the quantitative structure-property relationship method using S sigma-profile molecular descriptors[J]. RSC ADVANCES,2016,6(74):70405-70413.
APA Zhao, Yongsheng,Gao, Jubao,Huang, Ying,Afzal, Raja Muhammad,Zhang, Xiangping,&Zhang, Suojiang.(2016).Predicting H2S solubility in ionic liquids by the quantitative structure-property relationship method using S sigma-profile molecular descriptors.RSC ADVANCES,6(74),70405-70413.
MLA Zhao, Yongsheng,et al."Predicting H2S solubility in ionic liquids by the quantitative structure-property relationship method using S sigma-profile molecular descriptors".RSC ADVANCES 6.74(2016):70405-70413.
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