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Database and new models based on a group contribution method to predict the refractive index of ionic liquids
Wang, Xinxin1; Lu, Xingmei1,2; Zhou, Qing1,2; Zhao, Yongsheng1,2; Li, Xiaoqian1,2; Zhang, Suojiang1,2
2017-08-14
Source PublicationPHYSICAL CHEMISTRY CHEMICAL PHYSICS
ISSN1463-9076
Volume19Issue:30Pages:19967-19974
Abstract

Refractive index is one of the important physical properties, which is widely used in separation and purification. In this study, the refractive index data of ILs were collected to establish a comprehensive database, which included about 2138 pieces of data from 1996 to 2014. The Group Contribution-Artificial Neural Network (GC-ANN) model and Group Contribution (GC) method were employed to predict the refractive index of ILs at different temperatures from 283.15 K to 368.15 K. Average absolute relative deviations (AARD) of the GC-ANN model and the GC method were 0.179% and 0.628%, respectively. The results showed that a GC-ANN model provided an effective way to estimate the refractive index of ILs, whereas the GC method was simple and extensive. In summary, both of the models were accurate and efficient approaches for estimating refractive indices of ILs.

SubtypeArticle
WOS HeadingsScience & Technology ; Physical Sciences
DOI10.1039/c7cp03214e
Indexed BySCI
Language英语
WOS KeywordArtificial Neural-network ; S-sigma-profile ; Physical-properties ; Organic-compounds ; Multilayer Perceptron ; Thermal-conductivity ; Energy Applications ; Density Prediction ; Surface-tension ; Pure Compounds
WOS Research AreaChemistry ; Physics
WOS SubjectChemistry, Physical ; Physics, Atomic, Molecular & Chemical
Funding OrganizationNational Natural Scientific Fund of China(21376242 ; Key Program of National Natural Science Foundation of China(91434203) ; 21336002 ; 21476234)
WOS IDWOS:000407053000048
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ipe.ac.cn/handle/122111/23179
Collection多相复杂系统国家重点实验室
Affiliation1.Chinese Acad Sci, Inst Proc Engn, Key Lab Green Proc & Engn, Beijing Key Lab Ionic Liquids Clean Proc, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Coll Chem & Chem Engn, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Wang, Xinxin,Lu, Xingmei,Zhou, Qing,et al. Database and new models based on a group contribution method to predict the refractive index of ionic liquids[J]. PHYSICAL CHEMISTRY CHEMICAL PHYSICS,2017,19(30):19967-19974.
APA Wang, Xinxin,Lu, Xingmei,Zhou, Qing,Zhao, Yongsheng,Li, Xiaoqian,&Zhang, Suojiang.(2017).Database and new models based on a group contribution method to predict the refractive index of ionic liquids.PHYSICAL CHEMISTRY CHEMICAL PHYSICS,19(30),19967-19974.
MLA Wang, Xinxin,et al."Database and new models based on a group contribution method to predict the refractive index of ionic liquids".PHYSICAL CHEMISTRY CHEMICAL PHYSICS 19.30(2017):19967-19974.
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