Predicting Physical Properties (Viscosity, Density, And Refractive Index) Of Ternary Systems Containing 1-Octyl-3-Methyl-Imidazolium Bis(Trifluoromethylsulfonyl)Imide, Esters And Alcohols At 298.15 K And Atmospheric Pressure, Using Rigorous Classification Techniques

Keywords

1-Octyl-3-methyl-imidazolium bis(trifluoromethylsulfonyl)imide; Artificial neural network (ANN); Azeotrope breaker; Gene expression programming (GEP); Methanol; Methyl acetate; Physical properties

Abstract

The idea of using ILs as azeotrope breaker instead of conventional organic solvents in extractive and azeotropic distillation seems very promising due to their extraordinary properties. Nevertheless, any attempt to investigate or designing such processes requires a wide range of data on the physiochemical properties of the mixtures involved. In this study the idea of using 1-octyl-3-methylimidazolium bis[(trifluoromethyl)sulfonyl]imide, as an azeotrope breaker or entrainer for separation of ester/alcohol mixtures of ethyl acetate/ethanol, methyl acetate/methanol, and isopropyl acetate/isopropanol is used to predict physical properties (viscosity, density, and refractive index) of ternary systems involved in this process. With the use of artificial neural networks (ANNs) and gene expression programming (GEP), 362 experimental data of 3 ternary [C8mim][NTf2], ester and alcohol mixtures were mathematically modeled. The ANNs provided a robust multi-target network, suited to use as a part of a computer program, which predicted viscosity, density, and refractive index of the ternary mixtures simultaneously. The GEP models provided five separate correlations, suited to use for hand calculations, to predict viscosity, density, and refractive index separately. A comprehensive error analysis was performed on the proposed models to guarantee their accuracy. To assure quality of the experimental data used in developing the model an outlier detection was conducted using Leverage approach. At the end, by using a sensitivity analysis, the effect of each input parameter was investigated.

Publication Date

1-1-2017

Publication Title

Journal of Molecular Liquids

Volume

225

Number of Pages

778-787

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.molliq.2016.11.004

Socpus ID

85006489597 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85006489597

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