Surface Tension Prediction of Ionic Liquid Binary Solutions

Lemraski, Ensieh Ghasemian; pouyanfar, Zohre

doi:10.1021/je500479f

Cited by 4 publications

(3 citation statements)

References 31 publications

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“…However, there are a vast number of IL formulations, making experimental density determination exhaustive and expensive . For this reason, computational method development is mandatory to support density data knowledge . Among the methods available in the literature, group contribution methods are widely used.…”

Section: Introductionmentioning

confidence: 99%

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Density of Three Bis(trifluoromethylsulfonyl) Imide Anion-Based Ionic Liquids. High-Pressure Measurement and Estimation Using Group Contribution Methods

Medeiros

Alves

et al. 2023

J. Chem. Eng. Data

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Although physicochemical properties are essential to developing new industrial ionic liquid (IL) applications, experimental data must be obtained, especially under high-pressure operational conditions. Therefore, density data were measured for three commercial ILs: methyltrioctylammonium bis(trifluoromethylsulfonyl) imide [(C8)3C1N][NTf2]; 1-methyl-1-propylpiperidinium bis(trifluoromethylsulfonyl) imide [C3C1Pip][NTf2]; and 1-butylpyridinium bis(trifluoromethylsulfonyl) imide [C5Py][NTf2] at high-pressure and wide temperature ranges [P = (0.2 to 100.0) MPa and T = (298.15 to 398.15) K] by the intermediate of a tube vibrating method. The operational range was chosen because it could cover many industrial applications. The structural interaction between the IL cation and the anion is significant in volumetric behavior. It was observed that the density increases in the following order: [C5Py][NTf2] > [C3C1Pip][NTf2] > [(C8)3C1N][NTf2]. The Tammann–Tait equation was used to evaluate the influence of pressure and temperature on density, showing an average absolute relative deviation (%AARD) of less than 0.032% compared to experimental data. From these data, the isothermal compressibility (κT), isobaric expansivity (αp), thermal pressure coefficient (γv), and internal pressure (P i) were calculated. Additionally, IL density was estimated using five different group contribution methods reported in the literature, with better results obtained for Gardas and Coutinho and Paduszyński and Domańska.

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Section: Introductionmentioning

confidence: 99%

“…24 For this reason, computational method develop- ment is mandatory to support density data knowledge. 25 Among the methods available in the literature, group contribution methods are widely used.…”

Section: Introductionmentioning

confidence: 99%

Density of Three Bis(trifluoromethylsulfonyl) Imide Anion-Based Ionic Liquids. High-Pressure Measurement and Estimation Using Group Contribution Methods

Medeiros

Alves

et al. 2023

J. Chem. Eng. Data

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“…Rilo et al 32 developed a theoretical equation based on the Bahe-Varela pseudo-lattice model. Recently, Ghasemian Lemraski et al 33 predicted the surface tensions of IL mixtures based on the CSGC model (corresponding-states group-contribution method), HSEG model (extended Guggenheim's ideal solution model) and parachor model, and the AARD values were all higher than 5%.…”

Section: Introductionmentioning

confidence: 99%

New models for predicting thermophysical properties of ionic liquid mixtures

Zhang

Zhao

et al. 2015

Phys. Chem. Chem. Phys.

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Potential applications of ILs require the knowledge of the physicochemical properties of ionic liquid (IL) mixtures. In this work, a series of semi-empirical models were developed to predict the density, surface tension, heat capacity and thermal conductivity of IL mixtures. Each semi-empirical model only contains one new characteristic parameter, which can be determined using one experimental data point. In addition, as another effective tool, artificial neural network (ANN) models were also established. The two kinds of models were verified by a total of 2304 experimental data points for binary mixtures of ILs and molecular compounds. The overall average absolute deviations (AARDs) of both the semi-empirical and ANN models are less than 2%. Compared to previously reported models, these new semi-empirical models require fewer adjustable parameters and can be applied in a wider range of applications.

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