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New method based on the UNIFAC–VISCO model for the estimation of ionic liquids viscosity using the experimental data recommended by mathematical gnostics
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Zhao, Nan, Oozeerally, Ryan, Degirmenci, Volkan, Wagner, Zdeněk, Bendová, Magdalena and Jacquemin, Johan (2016) New method based on the UNIFAC–VISCO model for the estimation of ionic liquids viscosity using the experimental data recommended by mathematical gnostics. Journal of Chemical & Engineering Data, 61 (11). pp. 3908-3921. doi:10.1021/acs.jced.6b00689 ISSN 0021-9568.
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Official URL: http://dx.doi.org/10.1021/acs.jced.6b00689
Abstract
The viscosity of ionic liquids (ILs) has been modeled as a function of temperature and at atmospheric pressure using a new method based on the UNIFAC–VISCO method. This model extends the calculations previously reported by our group (see Zhao et al. J. Chem. Eng. Data 2016, 61, 2160–2169) which used 154 experimental viscosity data points of 25 ionic liquids for regression of a set of binary interaction parameters and ion Vogel–Fulcher–Tammann (VFT) parameters. Discrepancies in the experimental data of the same IL affect the quality of the correlation and thus the development of the predictive method. In this work, mathematical gnostics was used to analyze the experimental data from different sources and recommend one set of reliable data for each IL. These recommended data (totally 819 data points) for 70 ILs were correlated using this model to obtain an extended set of binary interaction parameters and ion VFT parameters, with a regression accuracy of 1.4%. In addition, 966 experimental viscosity data points for 11 binary mixtures of ILs were collected from literature to establish this model. All the binary data consist of 128 training data points used for the optimization of binary interaction parameters and 838 test data points used for the comparison of the pure evaluated values. The relative average absolute deviation (RAAD) for training and test is 2.9% and 3.9%, respectively.
Item Type: | Journal Article | |||||||||
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Subjects: | Q Science > QD Chemistry | |||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | |||||||||
Library of Congress Subject Headings (LCSH): | Ionic solutions -- Viscosity -- Estimates -- Mathematical models | |||||||||
Journal or Publication Title: | Journal of Chemical & Engineering Data | |||||||||
Publisher: | American Chemical Society | |||||||||
ISSN: | 0021-9568 | |||||||||
Official Date: | 10 October 2016 | |||||||||
Dates: |
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Volume: | 61 | |||||||||
Number: | 11 | |||||||||
Page Range: | pp. 3908-3921 | |||||||||
DOI: | 10.1021/acs.jced.6b00689 | |||||||||
Status: | Peer Reviewed | |||||||||
Publication Status: | Published | |||||||||
Access rights to Published version: | Open Access (Creative Commons) | |||||||||
RIOXX Funder/Project Grant: |
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