A high correlate and simplified QSPR for viscosity of imidazolium-based ionic liquids

Chen, Bor Kuan; Liang, Ming Jyh; Wu, Tzi Yi; Wang, H. Paul

doi:10.1016/j.fluid.2013.04.009

Cited by 60 publications

(61 citation statements)

References 44 publications

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“…Although the models in the Ref. [6] and [53] present lower overall deviations than the models in this work, their models require more parameters, which will increase the complexity of the models. In addition, most of the reported models can only be used at atmospheric pressure.…”

Section: Results Of Mlr Modelmentioning

confidence: 87%

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A quantitative prediction of the viscosity of ionic liquids using S_σ-profilemolecular descriptors

Zhao

Zhang

et al. 2015

Phys. Chem. Chem. Phys.

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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 Conductor-like Screening Model for Real Solvents (COSMO-RS) molecular descriptors (Sσ-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.

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Section: Results Of Mlr Modelmentioning

confidence: 87%

“…The 6 parameters (x 1 to x n ) comprised in the equation (1) are employed to explain the chemical structure of compounds, and n is the number of the parameters to seek the best model. …”

Section: Viscosity Data Points and S σ-Profile Of Ilsmentioning

confidence: 99%

A quantitative prediction of the viscosity of ionic liquids using S_σ-profilemolecular descriptors

Zhao

Zhang

et al. 2015

Phys. Chem. Chem. Phys.

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“…The lowest viscosities for the studied DESs, DES 30 [23,24]. It was found that the viscosity of the DES 30 is lower.…”

Section: Viscositymentioning

confidence: 88%

Triethylene glycol based deep eutectic solvents and their physical properties

Hayyan

Aissaoui

Hashim

et al. 2015

Journal of the Taiwan Institute of Chemical Engineers

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a b s t r a c tDeep eutectic solvents (DESs) have been recently emerged as new ionic liquids (ILs) analogues. The low vapor pressure, inflammability, biodegradability and positive effect on the environment make DESs more favorable as neoteric solvents. In this study, triethylene glycol (TEG) was selected as a hydrogen bond donor (HBD) to form DESs with five types of phosphonium and ammonium salts, namely methyltriphenylphosphonium bromide (MTPB), benzyltriphenylphosphonium chloride (BTPC), allyltriphenylphosphonium bromide (ATPB), choline chloride (2-hydroxyethyl-trimethylammonium) (ChCl) and N,N-diethylenethanolammonium chloride (DAC). The physical properties of the synthesized DESs were measured such as freezing point, viscosity, electrical conductivity, Walden rule, density, pH and water content. In addition, the Fourier transform infrared spectroscopy (FTIR) was employed to study the functional groups. The experiments were conducted at different temperatures, i.e. 25-80°C. It was found that DESs have suitable properties to be used in industrial processes such as separation, extraction, biochemical, petroleum and gas technology.

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“…For this purpose, they presented a polynomial expansion model based on the type of cation, length of side-chain, and type of anion for the expression of IL properties. Another study, using the QSPR method for correlating viscosities of ionic liquids, was the work of Chen et al [37]. They developed a simplified prediction model for the viscosities of imidazolium-based ILs using QSPR coupled with the descriptors of group contribution, considering temperature, molecular weight, and the number of the branched-chain carbon atoms in the imidazole ring.…”

Section: Introductionmentioning

confidence: 99%

Two simple correlations to predict viscosities of pure and aqueous solutions of ionic liquids

Haghbakhsh

Raeissi

2015

Journal of Molecular Liquids

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A high correlate and simplified QSPR for viscosity of imidazolium-based ionic liquids

Cited by 60 publications

References 44 publications

A quantitative prediction of the viscosity of ionic liquids using S_σ-profilemolecular descriptors

A quantitative prediction of the viscosity of ionic liquids using S_σ-profilemolecular descriptors

Triethylene glycol based deep eutectic solvents and their physical properties

Two simple correlations to predict viscosities of pure and aqueous solutions of ionic liquids

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A high correlate and simplified QSPR for viscosity of imidazolium-based ionic liquids

Cited by 60 publications

References 44 publications

A quantitative prediction of the viscosity of ionic liquids using Sσ-profilemolecular descriptors

A quantitative prediction of the viscosity of ionic liquids using Sσ-profilemolecular descriptors

Triethylene glycol based deep eutectic solvents and their physical properties

Two simple correlations to predict viscosities of pure and aqueous solutions of ionic liquids

Contact Info

Product

Resources

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A quantitative prediction of the viscosity of ionic liquids using S_σ-profilemolecular descriptors

A quantitative prediction of the viscosity of ionic liquids using S_σ-profilemolecular descriptors