Ternary Mixtures Of Ionic Liquids Research Articles

Phase Separation and Ion Diffusion in Ionic Liquid, Organic Solvent, and Lithium Salt Electrolyte Mixtures.

The highly desirable characteristics of ternary mixtures of ionic liquids, organic solvents, and metal salts make them a promising candidate for use in various electrothermal energy storage and conversion systems. In this study, using large-scale classical molecular dynamics simulations, we looked into 10 different ternary electrolyte mixtures using combinations of [EMIM]+, [BMIM]+, and [OMIM]+ cations with [NO3]-, [BF4]-, [PF6]-, [ClO4]-, [TFO]-, and [NTf2]- anions, tetraglyme, and Li salt to study the effect of ionic liquid composition on the phase behavior of ternary electrolyte mixtures. We uncovered that in these electrolytes, phase separation is mainly a function of pairwise binding energy of the constituents of the mixture. To corroborate this theory, several simulations are performed at various temperatures ranging from 260 to 500 K for each mixture, followed by calculating the binding energy of ionic liquid pairs using density functional theory. Our results verify that the transition temperature for the phase separation of each system is indeed a function of the pairwise binding energy of its ionic liquid pairs. It is also found that in some cases, the diffusion coefficient of the Li+ ions decreased even with the increase in the temperature, an effect that is attributed to the presence of condensed ionic domains in the electrolyte. This study provides a new insight for the design of multicomponent electrolyte mixtures for a wide range of energy applications.

Multicomponent Phase Separation in Ternary Mixture Ionic Liquid Electrolytes.

We investigate the phase behavior of ternary mixtures of ionic liquid, organic solvent, and lithium salt by molecular dynamics simulations. We find that at room temperature, the electrolyte separates into distinct phases with specific compositions; an ion-rich domain that contains a fraction of solvent molecules and a second domain of pure solvent. The phase separation is shown to be entropy-driven and is independent of lithium salt concentration. Phase separation is only observed at microsecond time scales and greatly affects the transport properties of the electrolyte.

Density Prediction of Ionic Liquids at Different Temperatures Using the Average Free Volume Model.

In this work, based on the average free volume model, the correlation between the molar volume and the van der Waals volume Vw for the ionic liquids (ILs) was derived. With this model, the density of pure ILs and binary and ternary mixtures of ILs over a wide range of temperature (278–473.15 K) can be calculated with good accuracy only with the information of the chemical components. A total number of 1859 data points of 41 pure ILs and IL mixtures based on imidazolium, pyridinium, pyrrolidinium, phosphonium, and ammonium cations were used to verify the model. For pure ILs and IL mixtures, the average absolute relative deviations (ARDs) are 1.04 and 1.19%, respectively. The overall discrepancies are less than 4%.

A theoretical study for isopiestic equilibrium mixtures of ionic liquid 1 + ionic liquid 2 + water systems

In the present study, molecular dynamics simulation studies have been carried out on some ternary mixtures of ionic liquid 1 + ionic liquid 2 + water systems which are in isopiestic equilibrium to describe the microstructure and dynamic properties of the investigated isopiestic systems. [C4MIM]Br + [C4MIM]Cl + H2O and [C4MIM]Cl + [C4MIM]I + H2O systems along with their corresponding binary aqueous solutions were selected to investigate the effect of anion on the behavior of the systems and in order to investigate the effect of cation, [C2MIM]Br + [C6MIM]Br + H2O system and their corresponding binary aqueous solutions were selected. It was found that, the densities calculated by the simulation method are well-agreed with the experimental data. Moreover, the radial distribution functions, combined distribution functions and spatial distribution functions were also calculated and the obtained results showed that the soluting-effect in the investigated solutions as well as the degree of hydrophobicity of ionic liquids were in agreement with those obtained experimentally. Finally, the hydrogen bond strength and interactions of various parts of the ionic liquids with each other and with water molecules were investigated and discussed in details.

Application of gene expression programming for predicting density of binary and ternary mixtures of ionic liquids and molecular solvents

Ionic Liquids (ILs) have received increased attention across a number of disciplines in recent years. This noticeable importance of ILs is attributed to their attractive proprieties. Precise evaluation of the thermophysical properties of ionic liquids and their mixtures with molecular solvents is essential for distinct multidisciplinary applications. In this study, a rigorous white-box intelligent technique, viz. gene expression programming (GEP) was implemented for establishing new correlations for accurate prediction of density of binary and ternary mixtures of ILs and molecular solvents. The newly suggested correlations were developed using a comprehensive experimental database with 1985 real measurements under a variety of operational conditions. The obtained results revealed that the newly established GEP-based correlations can predict the density of binary and ternary mixtures of ILs and molecular solvents with a high degree of integrity. The GEP-based correlations exhibited overall average absolute relative error (AARE) values of 0.5621% and 0.2128% for binary and ternary cases, respectively. Besides, it was found that our proposed explicit correlations followed the expected tendency with respect to the considered variables. Furthermore, the superiority and the reliability of the GEP-based correlations was testified against the best-existing approaches in the literature. Finally, the leverage approach was performed and the statistical validity of the correlations and the experimental data was testified.

Modeling the acentric factor of binary and ternary mixtures of ionic liquids using advanced intelligent systems

Ionic liquids (ILs) have found application in wide range of areas including petroleum industry, extractive distillation, raw material processing, additives for lubricants, functional materials, and catalyst for organic processes. Despite their applications in various fields of science, the use of ILs has been of questionable existence due to their induced toxic effects. To study the phase behavior of these ILs, various methods of obtaining data have been proposed. Notably, the main source of data comes from the laboratory experiments. Despite the existence of experimental methods to quantify the vapor-liquid equilibrium behavior of a fluid – IL system, it is necessary to build a model that can predict the behavior of the system at various states such as, changing temperature, pressure, and volume. Notwithstanding the huge cost and time required during experiments, thermodynamic model has found increasing use for modeling complex mixtures and/or compounds. One of the key parameters of the various thermodynamic models is the acentric factor, which dictates the level of sphericity of a molecule. In this study, the authors explored two different intelligent systems to estimate this key property for binary and ternary mixtures. The algorithm considered in this study include the least square support vector machine and artificial neural network. The input parameters considered include the critical temperature and volume, mole fraction of the solvent(s) and ionic liquid, molecular weight, density of the mixture, and temperature of the fluid. The comparison between the best model and experimental data point indicates very low root mean square error of 0.0164 and 0.0005 for the binary and ternary mixtures respectively. Similarly, the best model produced a very high correlation coefficient of 0.9826 and 1.0000 for the binary and ternary mixtures respectively.

Ternary mixtures of ionic liquids for better salt solubility, conductivity and cation transference number improvement.

We hereby present the new class of ionic liquid systems in which lithium salt is introduced into the solution as a lithium cation−glyme solvate. This modification leads to the reorganisation of solution structure, which entails release of free mobile lithium cation solvate and hence leads to the significant enhancement of ionic conductivity and lithium cation transference numbers. This new approach in composing electrolytes also enables even three-fold increase of salt concentration in ionic liquids.

Phase Equilibrium Study of Binary and Ternary Mixtures of Ionic Liquids + Acetone + Methanol

The vapor–liquid equilibrium (VLE) data for binary systems of acetone + 1-ethyl-3-methylimidazolebromine ([EMIM][Br]), methanol + 1-ethyl-3-methylimidazolebromine ([EMIM][Br]), acetone + 1-butyl-3-methylimidazolebromine ([BMIM][Br]), methanol + 1-butyl-3-methylimidazolebromine ([BMIM][Br]), and ternary VLE data for systems of acetone + methanol + 1-ethyl-3-methylimidazolebromine ([EMIM][Br]), acetone + methanol + 1-ethyl-3-butylimidazolebromine ([BMIM][Br]) were detected at 101.3 kPa in an all-glass dynamic recirculating still. With the addition of bromine–based ionic liquids, the relative volatility of acetone to methanol was enhanced and the azeotropy was eventually eliminated. As for the separating effect, [EMIM][Br] is better than [BMIM][Br]. The measured binary and ternary VLE data were correlated with the nonrandom two-liquid activity coefficient model, and the results demonstrated that the experimental data and the correlated data were in good agreement.

Effect of N,N′-bis(2-pyridylmethylidene)-1,2-diiminoethane Schiff base (BPIE) on the thermodynamic properties of the ionic liquid 1-hexyl-3-methylimidazolium chloride in N,N-dimethylacetamide solvent at T = 298.15 K

Densities, viscosities, and refractive indices of ternary mixtures of ionic liquid 1-hexyl-3-methylimidazolium chloride ([HMIm]Cl)+Schiff base, N,N′-bis(2-pyridylmethylidene)-1,2-diiminoethane (BPIE), a mixture of cis- and trans-isomers, + N,N-dimethylacetamide (DMA) were measured at T=298.15K. From the obtained data, apparent molar volumes (Vϕ), corresponding experimental slopes (Sv), standard partial molar volumes (Vϕ0), transfer volumes (ΔtVϕ0), viscosity B-coefficients, solvation numbers (Sn), and molar refractions (RD) were calculated and discussed on the basis of (solute+solvent), and (solute+cosolute) interactions. As stated by cosphere overlap model (Yan et al., 2009), the negative transfer volumes obtained here show the dominance of (polar+nonpolar) interactions between the polar group of BPIE and the nonpolar alkyl chain of [HMIm]Cl and (nonpolar+nonpolar) interactions between the nonpolar groups of BPIE and the alkyl chain of [HMIm]Cl. The values of solvation numbers (Sn) were obtained as Sn>2.5 and decrease as the concentration of BPIE in the mixtures increases. The Sn>2.5 means that the IL is solvated in the mixtures, but the decreasing the Sn values indicates that the solvation of the ions of the ionic liquid decreases at higher concentrations of the Schiff base.

Density Prediction of Mixtures of Ionic Liquids and Molecular Solvents Using Two New Generalized Models

Engineers often demand generalized models without sophisticated and long-time computations. To date, such models are still lacking for the density prediction of ionic liquid (IL) mixtures. In this paper, corresponding states principle combining with new mixing rules is employed to develop two new generalized models for density prediction of IL mixtures, including an extended Riedel (ER) model and an artificial neural network (ANN) model. A total of 1985 data points of binary and ternary mixtures of IL with molecular solvents, such as water, alcohols, ketones, ethers, hydrocarbons, esters, and acetonitrile, are used to verify the models. Average absolute relative deviations of the ER model and the ANN model are 0.92% and 0.37%, respectively, which indicates both the developed models can achieve a universal and accurate density prediction of IL mixtures. Moreover, the ER model does not contain any fitted parameters and thus provides a real predictive method.

Density, viscosity and refractive index prediction of binary and ternary mixtures systems of ionic liquid

Different artificial neural networks architectures were developed to predict the density, viscosity and refractive index of binary and ternary mixtures of ionic liquids using their individual properties. All neural network implemented were evaluated using the root mean square error (RMSE) and the average percentage deviations (APD) for the training and validation phase. The individual models implemented show great values of R2 (greater than 9.995∙10-01) and low errors in terms of RMSE, that corresponds with an APD less than 7.766∙10-02 %, with the exception of the model for the prediction of viscosity where the error raised to 3.338 %. The results show that the different individual artificial neural networks implemented are a useful tool to predict the density, viscosity and refractive index of binary and ternary mixtures of ionic liquids and with reasonably accuracy. Â

Phase equilibria of mixtures of mutually immiscible ionic liquids

In the last decade, the scientific community has witnessed a burgeoning research in ionic liquids. Numerous and diverse applications for them have been pointed out in the literature, with some processes based on ionic liquid technology already working in real plants. Among the possible fields of application, that of solvent extraction involving ionic liquids as solvents holds an important position. The opportunities of ionic liquids as alternative solvents for these kind of processes could be improved by the recent discovery of mutually immiscible ionic liquids. The use of ionic liquids presenting mutual immiscibility can generate stable multi-layer solvent systems, which, combined with the typical advantages offered by ionic liquids (good solvation properties, task-specific tuned structures, etc.), can mean a powerful medium for multi-component separations. To get a deeper knowledge of the behaviour of mutually immiscible ionic liquids, the phase equilibria of binary and ternary mixtures of ionic liquids were investigated. Specifically, hydrophobic ionic liquids with the common anion bis{(trifluoromethyl)sulfonyl}amide were selected. Pairs of ionic liquids with largely different cations were chosen, looking for the existence of mutual immiscibility between them. It was found that ionic liquids with a tetraalkylphosphonium cation are largely immiscible at ambient temperature with some other ionic liquids including 1,3-dialkylimidazolium or 1-alkylpyridinium cations. The miscibility of such pairs of ionic liquids was temperature dependent, following an upper critical solution temperature (UCST) behaviour. It was also found that small changes in the structure of an ionic liquid can drastically affect the mutual solubility with another ionic liquid. The liquid–liquid equlibrium (LLE) data of these systems were acceptably correlated by means of the classical non-random two-liquid (NRTL) equation.