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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
发表期刊PHYSICAL CHEMISTRY CHEMICAL PHYSICS
ISSN1463-9076
卷号19期号:30页码:19967-19974
摘要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.
文章类型Article
WOS标题词Science & Technology ; Physical Sciences
DOI10.1039/c7cp03214e
收录类别SCI
语种英语
关键词[WOS]ARTIFICIAL NEURAL-NETWORK ; S-SIGMA-PROFILE ; PHYSICAL-PROPERTIES ; ORGANIC-COMPOUNDS ; MULTILAYER PERCEPTRON ; THERMAL-CONDUCTIVITY ; ENERGY APPLICATIONS ; DENSITY PREDICTION ; SURFACE-TENSION ; PURE COMPOUNDS
WOS研究方向Chemistry ; Physics
WOS类目Chemistry, Physical ; Physics, Atomic, Molecular & Chemical
项目资助者National Natural Scientific Fund of China(21376242 ; Key Program of National Natural Science Foundation of China(91434203) ; 21336002 ; 21476234)
WOS记录号WOS:000407053000048
引用统计
文献类型期刊论文
条目标识符http://ir.ipe.ac.cn/handle/122111/23179
专题多相复杂系统国家重点实验室
作者单位1.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
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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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