Modelling phase equilibria of pure ionic liquids from a new equation of state

Alavianmehr, Mohammad Mehdi; Akbari, Falamarz; Behjatmanesh–Ardakani, Reza

doi:10.1007/s11581-016-1769-z

Cited by 5 publications

(9 citation statements)

References 53 publications

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“…In turn, comparing molar volume ( v = M /ρ), where M stands for molecular weight, of different ILs is an important piece of information when studying molecular interactions, in particular packing effects. For all these reasons, a significant amount of effort has been devoted to studying QSPRs for ρ of ILs since the pioneering papers of Slattery et al, Ye and Shreeve, Gardas and Coutinho, and others. − In particular, in 2012, I coauthored a paper presenting a state-of-the-art method for predicting p –ρ– T of data ILs in terms of group contributions (GCs) . In those days, this method was marked as the best one in the review paper of Coutinho et al Recently, the model has been used as reference method for evaluation of new experimental data, − as well as utilized as a supporting tool in CAMD of ILs for separations .…”

Section: Introductionmentioning

confidence: 99%

“…The number of building blocks defined previously was 177 (including 45 cationic, 69 anionic, and 63 substituted functional groups), which is quite high and allows one to estimate ρ values of a virtually infinite number of structures. This approach emerged as the most promising one in terms of accuracy and predictive capacity compared to other models reported in those days. − Since then, a number of new contributions to the field of GC methods for density have been reported. − In general, they can be divided into two classes: (1) purely empirical models based on either linear or nonlinear regression of experimental data; − (2) the models adopting thermodynamics (EoSs). − In further text, I provide a brief, but critical, review of these contributions (the former ones − have been summarized previously).…”

Section: Introductionmentioning

confidence: 99%

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Extensive Databases and Group Contribution QSPRs of Ionic Liquids Properties. 1. Density

Paduszyński

2019

Ind. Eng. Chem. Res.

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A new group contribution (GC) quantitative structure-property relationship (QSPR) for estimating density (ρ) of pure ionic liquids (ILs) as a function of temperature (T) and pressure (p) is developed on the basis of the most comprehensive collection of volumetric data reported so far (in total 41 250 data points, deposited for 2267 ILs from diverse chemical families). The model was established based on a carefully revised, evaluated, and reduced data set, whereas the adopted GC methodology follows the approach proposed previously [Ind. Eng. Chem. Res.201251591604]. However, a novel approach is proposed to model both temperature and pressure dependence. The idea consist of an independent representation of reference density ρ0 at T 0 = 298.15 K and ρ0 = 0.1 MPa and dimensionless correction f(T, P)  ρ(T, p)/ρ0 for other conditions of temperature and pressure. Three common machine learning algorithms are employed to represent the quantitative structure–property relationship between the studied property end points, GCs, T, and p, namely, multiple linear regression, feed-forward artificial neural network, and least-squares support vector machine. On the basis of detailed statistical analysis of the resulting models, including both internal and external stability checks by means of common statistical procedures such as cross-validation, y-scrambling, and “hold-out” testing, the final model is selected and recommended. An impact of type of cation and anion of the accuracy of calculations is highlighted and discussed. Performance of the new model is finally demonstrated by comparing it with similar methods published recently in the literature.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Extensive Databases and Group Contribution QSPRs of Ionic Liquids Properties. 1. Density

Paduszyński

2019

Ind. Eng. Chem. Res.

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“…Diedrichs et al 46 calculated the liquid C p for 33 pure compounds including associating fluids through a group contribution VTPR (Volume Translated Peng−Robinson) EoS, and different parametrization strategies were considered for comparison. Using the PHTC (Perturbed Hard-Trimer-Chain) EoS, Alavianmehr et al 47 predicted the C p of several fatty acid ethyl esters (FAEEs) at pressures up to 100 MPa, and the results were compared with the calculated data from literature.…”

Section: Introductionmentioning

confidence: 99%

“…For example, the temperatures of water in their work are from 273 to 373 K, corresponding to a reduced temperature range of 0.42−0.58. Alavianmehr et al 47 calculated the properties of fatty acid ethyl esters (FAEEs) with the perturbed hard-trimer-chain (PHTC) EoS, for which the parameters were only fitted to the compressed ρ. A satisfactory accuracy of ρ, C p , and u can be observed in their study.…”

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confidence: 99%

Heat Capacities of Fluids: The Performance of Various Equations of State

Zhu

Liu

et al. 2020

J. Chem. Eng. Data

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Heat capacities are fundamental properties of fluids for heat transfer applications.Accurate data can be generally obtained by experimental methods, which are usually expensive, difficult and time-consuming. In terms of the calculations of heat capacities, many models have been proposed in literature. Equations of state represent one of the most promising methods, but their performance has not been systematically studied and extensively reviewed. In this work, calculations and performance of various equations of state for heat capacities are reviewed, and the different contributions to heat capacities are also discussed. The accuracy of the calculated heat capacities, as presented in literature, is also compared for some specific compounds, and the effects of different parametrization strategies as well as association schemes are analyzed. Finally, calculations for both associating and non-associating compounds are performed using two association models, Cubic Plus Association and Perturbed-Chain Statistical Associating Fluid Theory equations of state, for a wide range of compounds for which the heat capacity results from literature are available.

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“…The proposed model was employed to predict the volumetric properties of polymers. In our previous work [16], we examined the predictive power of this EOS for the prediction of the liquid density, isothermal compressibilities, and thermal expansion coefficients as well as the heat capacities and vapor pressure of pure ILs. For this purpose, 39 ILs with various anions were chosen.…”

Section: Introductionmentioning

confidence: 99%

Thermophysical properties of ionic liquids and their mixtures from a new equation of state

Akbari

Alavianmehr

Ardakani

et al. 2017

Ionics

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In our previous work, a perturbed hard-trimersphere equation of state (PHTS EOS) was developed for modeling the phase equilibria of pure ionic liquids (ILs) (M.M. Alavianmehr et al., Ionics 22 (2016) 2447-2459. In this work, we have successfully extended the model to the mixtures of IL + IL and IL + solvent. Two temperaturedependent parameters appearing in the EOS are correlated with two microscopic scaling constants σ, the effective hardsphere diameter, and ε, the non-bonded interaction energy. The overall average absolute deviation (AAD) of the estimated densities from the literature data using the proposed model with and without non-additivity parameter (λ ij ) was found to be 0.44 and 0.79%, respectively. A modified Enskog equation and rough hard-sphere (RHS) theory are combined with our proposed equation of state to calculate the viscosity coefficient of ionic liquids and their mixtures. Finally, from the results obtained, a linear relation between logarithm of surface tension and viscosity property of ionic liquid was developed.

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Modelling phase equilibria of pure ionic liquids from a new equation of state

Cited by 5 publications

References 53 publications

Extensive Databases and Group Contribution QSPRs of Ionic Liquids Properties. 1. Density

Extensive Databases and Group Contribution QSPRs of Ionic Liquids Properties. 1. Density

Heat Capacities of Fluids: The Performance of Various Equations of State

Thermophysical properties of ionic liquids and their mixtures from a new equation of state

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