A quantitative prediction of the viscosity of ionic liquids using S sigma-profile molecular descriptors | |
Zhao, Y. S. ; Huang, Y. ; Zhang, X. P. ; Zhang, S. J. | |
刊名 | Physical Chemistry Chemical Physics |
2015 | |
期号 | 5页码:3761-3767 |
关键词 | ARTIFICIAL NEURAL-NETWORK STRUCTURE-PROPERTY RELATIONSHIPS COSMO-RS MELTING-POINTS PHYSICAL-PROPERTIES SURFACE TENSIONS QSPR CORRELATION TEMPERATURE MODEL DESIGN |
其他题名 | Phys. Chem. Chem. Phys. |
中文摘要 | In this study, two novel QSPR models have been developed to predict the viscosity of ionic liquids (ILs) using multiple linear regression (MLR) and support vector machine (SVM) algorithms based on Conductorlike Screening Model for Real Solvents (COSMO-RS) molecular descriptors (S sigma-profile). A total data set of 1502 experimental viscosity data points under a wide range of temperatures and pressures for 89 ILs, is employed to train and verify the models. The Average Absolute Relative Deviation (AARD) values of the total data set of the MLR and SVM are 10.68% and 6.58%, respectively. The results show that both the MLR and SVM models can predict the viscosity of ILs, and the performance of the nonlinear model developed using the SVM is superior to the linear model (MLR). Furthermore, the derived models also can throw some light onto structural characteristics that are related to the viscosity of ILs. |
收录类别 | SCI |
原文出处 | |
语种 | 英语 |
WOS记录号 | WOS:000348203200090 |
公开日期 | 2015-04-01 |
内容类型 | 期刊论文 |
源URL | [http://ir.ipe.ac.cn/handle/122111/11903] |
专题 | 过程工程研究所_研究所(批量导入) |
推荐引用方式 GB/T 7714 | Zhao, Y. S.,Huang, Y.,Zhang, X. P.,et al. A quantitative prediction of the viscosity of ionic liquids using S sigma-profile molecular descriptors[J]. Physical Chemistry Chemical Physics,2015(5):3761-3767. |
APA | Zhao, Y. S.,Huang, Y.,Zhang, X. P.,&Zhang, S. J..(2015).A quantitative prediction of the viscosity of ionic liquids using S sigma-profile molecular descriptors.Physical Chemistry Chemical Physics(5),3761-3767. |
MLA | Zhao, Y. S.,et al."A quantitative prediction of the viscosity of ionic liquids using S sigma-profile molecular descriptors".Physical Chemistry Chemical Physics .5(2015):3761-3767. |
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