Issue 30, 2017

Database and new models based on a group contribution method to predict the refractive index of ionic liquids

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.

Graphical abstract: Database and new models based on a group contribution method to predict the refractive index of ionic liquids

Supplementary files

Article information

Article type
Paper
Submitted
15 May 2017
Accepted
03 Jul 2017
First published
03 Jul 2017

Phys. Chem. Chem. Phys., 2017,19, 19967-19974

Database and new models based on a group contribution method to predict the refractive index of ionic liquids

X. Wang, X. Lu, Q. Zhou, Y. Zhao, X. Li and S. Zhang, Phys. Chem. Chem. Phys., 2017, 19, 19967 DOI: 10.1039/C7CP03214E

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