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

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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

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Publication details

The article was received on 15 May 2017, accepted on 03 Jul 2017 and first published on 03 Jul 2017


Article type: Paper
DOI: 10.1039/C7CP03214E
Citation: Phys. Chem. Chem. Phys., 2017, Advance Article
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    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, Advance Article , DOI: 10.1039/C7CP03214E

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