Surface Tension of Binary Mixtures of 1-Alkyl-3-methylimidazolium Bis(trifluoromethylsulfonyl)imide Ionic Liquids: Experimental Measurements and Soft-SAFT Modeling

Structural Properties of HEHN- and HAN-Based Ionic Liquid Mixtures: A Polarizable Molecular Dynamics Study

Molecular dynamics simulations of binary mixtures comprising 2-hydroxyethylhydrazinium nitrate (HEHN) and hydroxylammonium nitrate (HAN) were conducted using the polarizable APPLE&P force field to investigate fundamental properties of multimode propulsion (MMP) propellants. Calculated densities as a function of temperature were in good agreement with experiments and similar simulations. The structural properties of neat HEHN and HAN-HEHN provided insights into their inherent, protic nature. Radial distribution functions (RDFs) identified key hydrogen bonding sites located at N-H···O and O-H···O within a first solvation shell of approximately 2 Å. Angular distribution functions further affirmed the relatively strong nature of the hydrogen bonds with nearly linear directionality. The increased hydroxylammonium cation (HA+) mole fraction shows the influence of competitively strong hydrogen bonds on the overall hydrogen bond network. Dominant spatial motifs via three-dimensional distribution functions along with nearly nanosecond-long hydrogen bond lifetimes highlight the local bonding environment that may precede proton transfer reactions.

Insights into the estimation of surface tensions of mixtures based on designable green materials using an ensemble learning scheme

Precise estimation of the physical properties of both ionic liquids (ILs) and their mixtures is crucial for engineers to successfully design new industrial processes. Among these properties, surface tension is especially important. It's not only necessary to have knowledge of the properties of pure ILs, but also of their mixtures to ensure optimal utilization in a variety of applications. In this regard, this study aimed to evaluate the effectiveness of Stochastic Gradient Boosting (SGB) tree in modeling surface tensions of binary mixtures of various ionic liquids (ILs) using a comprehensive dataset. The dataset comprised 4010 experimental data points from 48 different ILs and 20 non-IL components, covering a surface tension range of 0.0157-0.0727 N m-1 across a temperature range of 278.15-348.15 K. The study found that the estimated values were in good agreement with the reported experimental data, as evidenced by a high correlation coefficient (R) and a low Mean Relative Absolute Error of greater than 0.999 and less than 0.004, respectively. In addition, the results of the used SGB model were compared to the results of SVM, GA-SVM, GA-LSSVM, CSA-LSSVM, GMDH-PNN, three based ANNs, PSO-ANN, GA-ANN, ICA-ANN, TLBO-ANN, ANFIS, ANFIS-ACO, ANFIS-DE, ANFIS-GA, ANFIS-PSO, and MGGP models. In terms of the accuracy, the SGB model is better and provides significantly lower deviations compared to the other techniques. Also, an evaluation was conducted to determine the importance of each variable in predicting surface tension, which revealed that the most influential factor was the mole fraction of IL. In the end, William's plot was utilized to investigate the model's applicability range. As the majority of data points, i.e. 98.5% of the whole dataset, were well within the safety margin, it was concluded that the proposed model had a high applicability domain and its predictions were valid and reliable.

Polar soft-SAFT: theory and comparison with molecular simulations and experimental data of pure polar fluids

The consideration of polar interactions is of vital importance for the development of predictive and accurate thermodynamic models for polar fluids, as they govern most of their thermodynamic properties, making them highly non-ideal fluids.

Insights into the influence of the molecular structures of fluorinated ionic liquids on their thermophysical properties. A soft-SAFT based approach

Development of predictive models for FILs.

Vapor Liquid Equilibria of Binary Mixtures of 1-Butyl-3-methylimidazolium Triflate (C4mimTfO) and Molecular Solvents: n-Alkyl Alcohols and Water

Isobaric vapor liquid equilibria (VLE) of binary mixtures of the ionic liquid (IL) 1-butyl-3-methylimidazolium trifluoromethanesulfonate (C₄mimTfO) with either water or short chained n-alkyl alcohols (methanol, ethanol, propan-1-ol, and butan-1-ol) are described in this study. Two different microebulliometers and a classical VLE apparatus were compared and the VLEs were determined in the composition range 0.4 ≤ x(solvent) ≤ 1 at three different pressure levels ( p = 500 mbar, 700 mbar, and 1000 mbar). The experimental data were modeled using the soft-SAFT equation of state, which was able to accurately describe the nonideal behavior of these mixtures. The combined experimental-modeling results obtained contribute to establish the structure-property relationship between the C₄mimTfO and n-alkyl alcohol molecules and to infer about its influence on the phase behavior of these solvents.

Determining the composition of the vacuum-liquid interface in ionic-liquid mixtures

The vacuum-liquid interfaces of a number of ionic-liquid mixtures have been investigated using the combination of reactive-atom scattering with laser-induced fluorescence detection (RAS-LIF), selected surface tension measurements, and molecular dynamics (MD) simulations. The mixtures are based on the widespread 1-alkyl-3-methylimidazolium ([C_nmim]⁺) cation, including mixed cations which differ in chain length or chemical functionality with a common anion; and different anions for a common cation. RAS-LIF results imply that the surface compositions exhibit a general form of non-stoichiometric behaviour that mimics the well-known Henry's and Raoult's laws at low and high mole fraction, respectively. The extended Langmuir model provides a moderately good single-parameter fit, but higher-order terms are required for an accurate description. The quantitative relationship between RAS-LIF and surface tension, which probes the surface composition only indirectly, is explored for mixtures of [C₂mim]⁺ and [C₁₂mim]⁺ with a common bis(trifluoromethylsulfonyl)imide ([NTf₂]^-) anion. Extended Langmuir model fits to surface tension data are broadly consistent with those to RAS-LIF; however, several other common approaches to extracting surface compositions from measured surface tensions result in much larger discrepancies. MD simulations suggest that RAS-LIF faithfully reports on the alkyl-chain exposure at the surface, which is only subtly modified by composition-dependent structural reorganisation.

Nanosegregation and Structuring in the Bulk and at the Surface of Ionic-Liquid Mixtures

Ionic-liquid (IL) mixtures hold great promise, as they allow liquids with a wide range of properties to be formed by mixing two common components rather than by synthesizing a large array of pure ILs with different chemical structures. In addition, these mixtures can exhibit a range of properties and structural organization that depend on their composition, which opens up new possibilities for the composition-dependent control of IL properties for particular applications. However, the fundamental properties, structure, and dynamics of IL mixtures are currently poorly understood, which limits their more widespread application. This article presents the first comprehensive investigation into the bulk and surface properties of IL mixtures formed from two commonly encountered ILs: 1-ethyl-3-methylimidazolium and 1-dodecyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([C₂mim][Tf₂N] and [C₁₂mim][Tf₂N]). Physical property measurements (viscosity, conductivity, and density) reveal that these IL mixtures are not well described by simple mixing laws, implying that their structure and dynamics are strongly composition dependent. Small-angle X-ray and neutron scattering measurements, alongside molecular dynamics (MD) simulations, show that at low mole fractions of [C₁₂mim][Tf₂N], the bulk of the IL is composed of small aggregates of [C₁₂mim]⁺ ions in a [C₂mim][Tf₂N] matrix, which is driven by nanosegregation of the long alkyl chains and the polar parts of the IL. As the proportion of [C₁₂mim][Tf₂N] in the mixtures increases, the size and number of aggregates increases until the C12 alkyl chains percolate through the system and a bicontinuous network of polar and nonpolar domains is formed. Reactive atom scattering-laser-induced fluorescence experiments, also supported by MD simulations, have been used to probe the surface structure of these mixtures. It is found that the vacuum-IL interface is enriched significantly in C12 alkyl chains, even in mixtures low in the long-chain component. These data show, in contrast to previous suggestions, that the [C₁₂mim]⁺ ion is surface active in this binary IL mixture. However, the surface does not become saturated in C12 chains as its proportion in the mixtures increases and remains unsaturated in pure [C₁₂mim][Tf₂N].

A reciprocal binary mixture of protic/aprotic ionic liquids as a deep eutectic solvent: physicochemical behaviour and application towards agarose processing

Apart from structural tuning, the desired properties of ionic liquids (IL) can be achieved through judicious mixing of two or more ionic liquids.

Imidazolium-based ionic liquids grafted on solid surfaces

Supported ionic liquids (SILs), which refer to ionic liquids (ILs) immobilized on supports, are among the most important derivatives of ILs.

PERCEPTRON ARTIFICIAL NEURAL NETWORK AND PREDICTION OF BUBBLE POINTS OF TERNARY MIXTURES CONTAINING IONIC LIQUIDS

The feasibility of using cascade neural networks to correlate the bubble points of ternary mixtures containing ionic liquids (ILs) and classical solvents was investigated. The systems investigated consisted of the ILs from the alkylimidazolium family with either the chloride, tetrafluoroborate, methylsulfate, or ethyl sulfate anions. The classical solvents investigated included 1-propanol, 2-propanol, ethanol, ethyl ethanoate, and water. A total of 272 bubble points were used in the training (205 data points) and testing (67 data points) stages. The optimized network comprised of nine neurons in the hidden layer and used the tangent-sigmoid and purelin functions as the activation functions in the hidden and output layers, respectively. This proposed network was able to correlate the ternary bubble points of both the training (AARD % = 0.13% and R2 = 0.9921) and the testing (AARD % = 0.15% and R2 = 0.9873) subsets with good accuracy, revealing the good correlative capability of the network. The statistical error analysis of all the data indicated an overall absolute average relative deviation (AARD %), mean square error (MSE) and correlation coefficient (R2) of 0.13%, 0.44% and 0.9909%, respectively.