Rigorous correlations for predicting the solubility of H2S in methylimidazolium-based ionic liquids

Two general and simple models, a group contribution correlation (model I) and an empirical relation (model II), were proposed to predict the solubility of H₂S in methylimidazolium based ionic liquids (ILs) over wide range of temperatures (303.15-363.15 K) and pressures (60.8-2016.8 kPa). The constants of the suggested functionality relations were found via the Nelder-Mead simplex algorithm. Both correlations were trained with 407 data points of H₂S solubility in 9 methylimidazolium based ILs and tested through 121 H₂S solubility data points of 3 different methylimidazolium based ILs to ensure generality. A comprehensive statistical evaluation showed that both suggested correlations are vigorous and have satisfactory error trends. The dataset was subjected to a statistical outlier diagnostic test and the validity of the database was confirmed. In addition, the sensitivity analysis revealed that the experimental data and both models have the same responses toward pressure and temperature, which indicates the reliability of the proposed correlations.     

Estimating hydrogen sulfide solubility in ionic liquids using a machine learning approach

For the design and development of new processes of gas sweetening using ionic liquids (ILs), as promising candidates for amine solutions, an amazing model to predict the solubility of acid gases is of great importance. In this direction, in the current study, the capability of artificial neural networks (ANNs) trained with back propagation (BP) and particle swarm optimization (PSO), to correlate the solubility of H₂S in 11different ILs have been investigated. Different structures of three-layer feed forward neural network using acentric factor (ω), critical temperature (T_c), critical pressure (P_c) of ILs accompanied by pressure (P) and temperature (T), as input parameters, were examined and an optimized architecture has been proposed as 5–9–1.Implementation of these models for 465 experimental data points collected from the literature shows coefficient of determination (R²) of 0.99218 and mean squared error (MSE) of 0.00025 from experimental values for PSO-ANN predicted solubilities while the values of R² = 0.95151 and MSE = 0.00335 were obtained for BP-ANN model. Therefore, through PSO training algorithm we are able to attain significantly better results than with BP training procedure based on the statistical criteria.     

Photoinitiated polymerization in ionic liquids: Kinetics and viscosity effects

The photo-induced polymerization of poly(ethylene glycol) dimethacrylate and poly(ethylene glycol) monomethacrylate (crosslinking and linear, resp.) in four imidazolium-based ionic liquids (ILs) containing the same cation or the same anion in pairs is reported. The kinetic studies were accompanied by detailed viscosity measurements, which showed the occurrence of an interesting phenomenon - a viscosity synergism in monomer/IL mixtures (i.e. the viscosity of the mixture is higher than the simple additive combination of viscosities of the two components). Viscosity synergism, very important for kinetic considerations, is especially strong for ILs of low viscosity and its magnitude depends on the monomer structure. The polymerization conducted in ILs was considerably faster than in a reference solvent. The propagation rate coefficients were influenced mainly by the anion structure whereas the termination rate coefficients by viscosity of the initial monomer/IL mixture (taking into account the synergistic effect). FTIR studies showed the existence of specific interactions between the carbonyl group in the monomer and C₂-H of the imidazolium ring; the polymerization rates were directly related to the magnitude of the monomer/IL interaction.     

Random forest model for removal of bromophenol blue using activated carbon obtained from Astragalus bisulcatus tree

In this research, activated carbon (AC) simply was prepared from a local, abundant tree in south of Iran. The AC with low cost and toxicity is a good candidate for bromophenol blue (BPB) removal from aqueous media. The AC with nano scale pore diameter is applicable for this dye removal following optimization of the influence of various parameters including contact time, pH, initial dye concentration and amount of adsorbent. Subsequently, experimental data was analyzed by four kinetic models including pseudo first and second-order, Elovich and the intraparticle diffusion equations and subsequently their respective parameters such as rate constants, equilibrium adsorption capacities and correlation coefficients was investigated and based on well known criterion their applicability was judged. The result shows that adsorption of BPB onto proposed adsorbent at all conditions such as versatile adsorbent dosages and initial BPB concentrations sufficiently described by the combination of the pseudo second-order equation and interparticle diffusion model. It was found that equilibrium rate of the BPB adsorption at various adsorbent dosage well fitted by Langmuir. Investigation of experimental result by two approaches (multiple linear regressions (MLR) and random forest (RF)) models show that RF is a powerful tool for prediction of BPB adsorption by activated carbon obtained from Astragalus bisulcatus tree. The optimal tuning parameters for RF model are obtained based on the n_tree = 100, m_try = 2. For the training data set, the MSE values of 0.0006 and the coefficient of determination (R²) values of 0.9895 for RF model and the MSE value of 0.0104 and the R² value of 0.823 for MLR model are obtained.     

Prediction of critical temperature,critical pressure and acentric factor of some ionic liquids using Patel-Teja equation of state based on genetic algorithm

Critical properties and acentric factor (ω) of 31 ionic liquids (ILs) were obtained by using vapor-liquid equilibrium data of solvent+IL consisting of P-T and P-x experimental data, based on three-parameter Patel-Teja equation of state and genetic algorithm. Optimized P _c , T _c and ω of ILs with Peng-Robinson equation of state (PR EoS) were used to model the behavior of phase equilibria of solvent+IL. Due to lack of experimental data for optimized properties, the validation was done by comparing them to the results in the literature. In each comparison the average absolute percent deviation (AAPD) for optimized properties was based on P-T experimental data, with PR EoS was minimum. For more confidence in the correctness of optimized properties, the behavior of phase equilibria of two new mixtures (i.e., water+emimDMP and methanol+emimDMP), the density and vapor pressure of some pure ILs were predicted by PR EoS, which the prediction of this EoS was satisfactory.     

Electropolymerization of poly(3-methylthiophene) in pyrrolidinium-based ionic liquids for hybrid supercapacitors

The ionic liquids (ILs) N-butyl-N-methyl-pyrrolidinium trifluoromethanesulfonate (PYR₁₄Tf) and N-methyl-N-propyl-pyrrolidinium bis(fluorosulfonyl)imide (PYR₁₃FSI) are investigated as electropolymerization media for poly(3-methylthiophene) (pMeT) in view of their use in carbon/IL/pMeT hybrid supercapacitors. Data on the viscosity, solvent polarity, conductivity and electrochemical stability of PYR₁₄Tf and PYR₁₃FSI as well as the effect of their properties on the electropolymerization and electrochemical performance of pMeT, which features >200 Fg⁻¹ at 60 °C when prepared and tested in such ILs, are reported and discussed; the results of the electrochemical characterization in N-butyl-N-methyl-pyrrolidinium bis(trifluoromethanesulfonyl)imide of the so-obtained pMeT are also given, for comparison.     

Modeling of CO2 Solubility in Selected Imidazolium-Based Ionic Liquids

This study explores the use of COSMO-RS model and Peng-Robinson (PR) equation of state (EoS) to predict the solubility of carbon dioxide (CO₂) in specific ionic liquids (ILs). COSMO-RS was employed to estimate of CO₂ solubility at atmospheric pressure in eight imidazolium-based ILs resulting from the combination of ethyl, butyl, hexyl, and octyl-imidazolium cations with two anions: bis(trifluoromethylsulfonyl)imide ([Tf₂N]) and Trifluoromethanesulfonate ([TFO]). The results indicated relatively acceptable qualitative consistency between the experimental and predicted values. The PR EoS was employed at high pressure by tuning the interaction parameters to fit the experimental data reported in the literature. The model demonstrated excellent accuracy in predicting the solubility of CO₂ at pressure values less than the critical pressure of CO₂; however, at higher pressures, the calculated solubility diverged from the experimental values. Furthermore, the type of anion and cation used in the IL affected the performance of the PR EoS.     

Estimation of H2S solubility in ionic liquids using a rigorous method

Prediction of acid gases solubilities in ionic liquids (ILs), have recently emerged as promising mediums for refining of natural gas, using powerful paradigms is of great importance from technical and economical point of view. In this respect, this study aims at appraising the effectiveness of one of the new generation soft computing methodologies called gene-expression programming (GEP) for estimating the hydrogen sulfide (H₂S) solubility in ionic liquids (ILs). A total data set of 465 experimental data belonging to 11 ionic liquids, which gathered from literatures, were used to develop a general correlation. The temperature and pressure accompanied with acentric factors and critical temperature and pressure of ILs were used as independent input variables, while H₂S solubility as dependent output variables. The modeling results showed the coefficient of determination (R²) of 0.9902 and 0.0438% mean absolute relative error (MARE) for the predicted solubilities from the corresponding experimental values. Therefore, the model is comprehensive and accurate enough to be used to predict the H₂S solubility in various ILs. In addition, the GEP-model predictions were compared with the outputs of two well-known engineering approaches named Soave–Redlich–Kwong (SRK) and Peng–Robinson (PR). Results showed that the proposed evolutionary-based method was more accurate than the widely used aforementioned thermodynamic models.     

Structure-Activity Relationship Modeling and Experimental Validation of the Imidazolium and Pyridinium Based Ionic Liquids as Potential Antibacterials of MDR Acinetobacter baumannii and Staphylococcus aureus

Online Chemical Modeling Environment (OCHEM) was used for QSAR analysis of a set of ionic liquids (ILs) tested against multi-drug resistant (MDR) clinical isolate Acinetobacter baumannii and Staphylococcus aureus strains. The predictive accuracy of regression models has coefficient of determination q² = 0.66 − 0.79 with cross-validation and independent test sets. The models were used to screen a virtual chemical library of ILs, which was designed with targeted activity against MDR Acinetobacter baumannii and Staphylococcus aureus strains. Seven most promising ILs were selected, synthesized, and tested. Three ILs showed high activity against both these MDR clinical isolates.     

Rheological studies of hyaluronan solutions based on the scaling law and constitutive models

We have investigated the scaling relationship between rheological behavior and concentration for both salt-free and saline solutions of hyaluronan (HA), and adopted three viscoelastic constitutive models to predict the linear/non-linear viscoelastic behavior of these aqueous solutions of HA with different molecular weights at different concentrations up to 20 mg/ml. A series of concentration equations are obtained to describe the influence of HA concentration on solution viscosity. Corresponding to dilute and semi-dilute concentration region, salt-free HA solutions have scaling relationship between specific viscosity and HA concentration as η_sp ∼ c^1.0 and η_sp ∼ c^3.5, respectively, while for 0.15 M NaCl HA solutions, the scaling exponents are 1.5 and 4.2, respectively. Simulation results indicate that these constitutive models have good applicability to describe quantitatively the rheological properties of HA entangled solutions under either dynamic or steady shear flow. In addition, the plateau modulus scaling of HA solutions can be well described by the concentration-dependent length scale.     

Effect of 1-Ethyl-3-methylimidazolium Tetrafluoroborate and Acetate Ionic Liquids on Stability and Amyloid Aggregation of Lysozyme

Amyloid fibrils draw attention as potential novel biomaterials due to their high stability, strength, elasticity or resistance against degradation. Therefore, the controlled and fast fibrillization process is of great interest, which raises the demand for effective tools capable of regulating amyloid fibrillization. Ionic liquids (ILs) were identified as effective modulators of amyloid aggregation. The present work is focused on the study of the effect of 1-ethyl-3-methyl imidazolium-based ILs with kosmotropic anion acetate (EMIM-ac) and chaotropic cation tetrafluoroborate (EMIM-BF₄) on the kinetics of lysozyme amyloid aggregation and morphology of formed fibrils using fluorescence and CD spectroscopy, differential scanning calorimetry, AFM with statistical image analysis and docking calculations. We have found that both ILs decrease the thermal stability of lysozyme and significantly accelerate amyloid fibrillization in a dose-dependent manner at concentrations of 0.5%, 1% and 5% (v/v) in conditions and time-frames when no fibrils are formed in ILs-free solvent. The effect of EMIM-BF₄ is more prominent than EMIM-ac due to the different specific interactions of the anionic part with the protein surface. Although both ILs induced formation of amyloid fibrils with typical needle-like morphology, a higher variability of fibril morphology consisting of a different number of intertwining protofilaments was identified for EMIM-BF_4.     

Prediction of CO2/O2 absorption selectivity using supported ionic liquid membranes (SILMs) for gas–liquid membrane contactor

Given their unique and tunable properties as solvents, ionic liquids (ILs) have become a favorable solvent option in separation processes, particularly for capturing carbon dioxide (CO₂). In this work, a simple method that can be used to screen the suitable IL candidates was implemented in our modified gas–liquid membrane contactor system. Solubilities, selectivities of CO₂, nitrogen (N₂), and oxygen (O₂) gases in imidazolium-based ILs and its activity coefficients in water and monoethanolamine (MEA) were predicted using conductor-like screening model for real solvent (COSMO-RS) method over a wide range of temperature (298.15–348.15?K). Results from the analysis revealed that [emim] [NTf₂] IL is a good candidate for further absorption process attributed to its good hydrophobicity and CO₂/O₂ selectivity characteristics. While their miscibility with pure MEA was somehow higher, utilizing the aqueous phase of MEA would be beneficial in this stage. Data on absorption performances and selectivity of CO₂/O₂ are scarce especially in gas–liquid membrane contactor system. Therefore, considering [emim] [NTf₂] IL as a supporting material in supported ionic liquid membranes (SILMs), using aqueous phase of MEA as an absorbent would result in a great membrane-solvent combination system in furthering our gas–liquid membrane contactor process. In conclusion, COSMO-RS is a potentially great predictive utility to screen ILs for specified separation applications. In addition, this work provides useful results for the [emim] [NTf₂]-SILMs to be extensively applied in the field of CO₂ capture and selective O₂ removal.     

Heats of Combustion of Fatty Acids and Fatty Acid Esters

The military uses JP-8, a kerosene type hydrocarbon, to fuel most of its vehicles and is seeking a renewable alternative fuel that meets strict JP-8 specifications. Biodiesel is typically a mixture of different alkyl esters produced from the transesterification of triglycerides readily available in plant oils and used cooking oil. To date, no traditional biodiesel meets the requirements for heat of combustion, freezing point, viscosity and oxidative stability to be a stand-alone replacement for JP-8. This work is a fundamental survey of the heat of combustion of single fatty acid esters and a predictive model for estimating the heat of combustion given a known molecular structure. The gross heat of combustion of various C6–C18 fatty acids and the methyl, propyl and isopropyl esters of these fatty acids was measured. This study sought to relate the effect of chain length, degree of unsaturation and branching to the critical fuel property of the gross heat of combustion (H _c). It was found that H _c (kJ/g) increased with chain length. A nearly linear relationship was found between wt% carbon and hydrogen, and H _c. Group contribution models previously published for hydrocarbons and polymers were modified to more accurately predict the heat of combustion of the fatty acids and esters. Modification of the molar heat values of carboxylic acid, methyl, and methylene groups improved correlation of the model with the experimental results.     

Least square-support vector (LS-SVM) method for modeling of methylene blue dye adsorption using copper oxide loaded on activated carbon: Kinetic and isotherm study

A multiple linear regression (MLR) model and least square support vector regression (LS-SVM) model with principal component analysis (PCA) was used for preprocessing to predict the efficiency of methylene blue adsorption onto copper oxide nanoparticle loaded on activated carbon (CuO-NP-AC) based on experimental data set achieved in batch study. The PCA-LSSVM model indicated higher predictive capability than linear method with coefficient of determination (R²) of 0.97 and 0.92 for the training and testing data set, respectively. Firstly, the novel nanoparticles including copper oxide as low cost, non-toxic, safe and reusable adsorbent was synthesized in our laboratory with a simple and routine procedure. Subsequently, this new material properties such as surface functional group, homogeneity and pore size distribution was identified by FT-IR, SEM and BET analysis. The methylene blue (MB) removal and adsorption onto the CuO-NP-AC was investigated and the influence of variables such as initial pH and MB concentration, contact time, amount of adsorbent and pH, and temperature was investigated. The results of examination of the time on experimental adsorption data and fitting the data to conventional kinetic model show the suitability of pseudo-second order and intraparticle diffusion model. Evaluation of the experimental equilibrium data by Langmuir, Tempkin, Freundlich and Dubinin Radushkevich (D-R) isotherm explore that Langmuir is superior to other model for fitting the experimental data in term of higher correlation coefficient and lower error analysis.     

Inhibiting Effect of Ionic Liquids on the Corrosion of Mild Steel in H2S and HCl Solution

Four imidazolium-based ionic liquids (ILs) were selected to investigate the inhibiting effect of ILs with various alkyl chain lengths on the corrosion of mild steel in H₂S and HCl solution using electrochemical experiments, weight loss and surface analyses, and quantum chemical study. The results demonstrated that these ILs acted as mixed-type inhibitors and efficiently inhibited the corrosion of mild steel in H₂S and HCl solution. Their excellent corrosion inhibition ability was due to their adsorption process on the metal surface, which followed the Langmuir adsorption isotherm. Furthermore, extending the alkyl chain length in the ILs could improve their inhibition performance.     

Estimating solubility of supercritical H2S in ionic liquids through a hybrid LSSVM chemical structure model

Development of a predictive tool for H₂S solubility estimation can be very helpful in gas sweetening industry. Experimental databases on H₂S solubility were rarely available, so as reliable predictive models. Thus, in this study the H₂S solubility database was established, and then a Least-Squares Support Vector Machine (LSSVM) approach based on the established database is proposed. Group contribution method was also applied to eliminate the model's dependence on experimental data. Accordingly, our proposed LSSVM model can predict H₂S solubility as a function of temperature, pressure, and 15 different chemical structures of Ionic liquids (ILs). Root Mean Square Error (RMSE) and coefficient of determination (R²) are 0.0122 and 0.9941, respectively. Moreover, comparison of our model with other existing models showed its reliability for H₂S solubility in ILs. This can be very useful for engineers dealing with gas sweetening process in different applications of analysis, simulation, and designation.