Calculation of the Solubility Parameter by COSMO-RS Methods and Its Influence on Asphaltene–Ionic Liquid Interactions

Imidazolium-based ionic liquids as dispersants to improve the stability of asphaltene in Egyptian heavy crude oil

Deposition of asphaltene aggregates can easily depress the oil production, because it may clog the wellbores, annulus, pipelines, and surface facilities. Moreover, asphaltene molecules have a negative effect on the catalytic reactions in the refinery process. Therefore, in this work, three different ionic liquids (IL-H, IL-CH3, and IL-NO2) were synthesized, and characterized using FT-IR and NMR spectroscopy to evaluate their efficiency as asphaltene dispersants. The thermal gravimetric analysis of the prepared ILs showed that IL-H, IL-NO2, and IL-CH3 were thermally stable up to 280 °C. The ILs showed good dispersion activity of the petroleum asphaltenes, where the asphaltene onset precipitation (AOP) was changed from 7.5 to 10.5, 11, and 13.5 ml added n-heptane after the use of IL-H, IL-NO2, and IL-CH3, respectively. Moreover, the colloidal instability index of crude oil was changed from 0.92 (unstable asphaltene) to 0.69 (stable asphaltene). It is noted during the experiments that the presence of an alkyl chain attached to the ionic liquid moiety increases the efficiency of the dispersant. This may be owing to the formation of π-π* with asphaltene molecules due to the presence of electron donating group. Quantum chemical parameters were calculated for the prepared ILs, and the theoretical data confirmed the experimental results.

New Screening Protocol for Effective Green Solvents Selection of Benzamide, Salicylamide and Ethenzamide

New protocol for screening efficient and environmentally friendly solvents was proposed and experimentally verified. The guidance for solvent selection comes from computed solubility via COSMO-RS approach. Furthermore, solute-solvent affinities computed using advanced quantum chemistry level were used as a rationale for observed solvents ranking. The screening protocol pointed out that 4-formylomorpholine (4FM) is an attractive solubilizer compared to commonly used aprotic solvents such as DMSO and DMF. This was tested experimentally by measuring the solubility of the title compounds in aqueous binary mixtures in the temperature range between 298.15 K and 313.15 K. Additional measurements were also performed for aqueous binary mixtures of DMSO and DMF. It has been found that the solubility of studied aromatic amides is very high and quite similar in all three aprotic solvents. For most aqueous binary mixtures, a significant decrease in solubility with a decrease in the organic fraction is observed, indicating that all systems can be regarded as efficient solvent-anti-solvent pairs. In the case of salicylamide dissolved in aqueous-4FM binary mixtures, a strong synergistic effect has been found leading to the highest solubility for 0.6 mole fraction of 4-FM.

Prediction of small-molecule compound solubility in organic solvents by machine learning algorithms

Rapid solvent selection is of great significance in chemistry. However, solubility prediction remains a crucial challenge. This study aimed to develop machine learning models that can accurately predict compound solubility in organic solvents. A dataset containing 5081 experimental temperature and solubility data of compounds in organic solvents was extracted and standardized. Molecular fingerprints were selected to characterize structural features. lightGBM was compared with deep learning and traditional machine learning (PLS, Ridge regression, kNN, DT, ET, RF, SVM) to develop models for predicting solubility in organic solvents at different temperatures. Compared to other models, lightGBM exhibited significantly better overall generalization (logS  ± 0.20). For unseen solutes, our model gave a prediction accuracy (logS  ± 0.59) close to the expected noise level of experimental solubility data. lightGBM revealed the physicochemical relationship between solubility and structural features. Our method enables rapid solvent screening in chemistry and may be applied to solubility prediction in other solvents.

Simultaneous Extraction of Sulfur and Nitrogen Compounds from Model Diesel Fuel Using Neoteric Green Solvents

Removal of nitrogen and sulfur compounds from diesel fuel is essential to comply with the increasing stringent regulations. The extraction capability of two deep eutectic solvents, namely, tetrabutylphosphoniumbromide/ethylene glycol, TBPBr/EG, with molar ratio 1:2, and tetrabutylammoniumbromide/ethylene glycol, TBABr/EG, with molar ratio 1:2, in simultaneously extracting basic nitrogen, nonbasic nitrogen, and sulfur compounds represented by pyridine, indoline, and dibenzothiophene (DBT) from n-hexadecane, was investigated. Two pseudo-ternary phase diagrams of (TBPBr/EG + (pyridine + indoline + DBT) + n-hexadecane) and (TBABr/EG + (pyridine + indoline + DBT) + n-hexadecane) were predicted via a conductor-like screening model for real solvents (COSMO-RS) and experimentally validated at 298.15 K and 1 atm. Both solvents showed zero cross-contamination, indicating the suitability of all solvents as extraction solvents. The tie lines obtained for both COSMO-RS and experiments were in agreement and had root-mean-square deviation (RMSD) values of less than 5% for both systems. Selectivity and distribution ratio calculated indicates the suitability of both solvents in extracting sulfur and nitrogen compounds from hexadecane. Two new parameters, namely, extraction efficiency, α, and extraction affinity, β, were introduced to ease the performance comparison of both solvents. TBPBr/EG shows a slightly better performance than TBABr/EG. Other than that, the presence of multiple solutes shows low effects on the performance of these solvents.

Multiple approaches for achieving drug solubility: an in silico perspective

Discovering new therapeutically active molecules is the ultimate destination in pharmaceutical research and development. Most drugs discovered are lipophilic and, hence, exhibit poor aqueous solubility, resulting in low bioavailability. Thus, there is a need to use various solubility enhancement techniques. Computational approaches enable the analysis of drug-carrier interactions or the numerous conformational changes in the carrier matrix that might establish an appropriate balance between cohesive and adhesive stability in a formulation. In this review, we discuss research approaches that provided molecular insight into drugs and their modifiers to unravel their solubility, stability, and bioavailability.

MoDoop: An Automated Computational Approach for COSMO-RS Prediction of Biopolymer Solubilities in Ionic Liquids

An automated computational framework (MoDoop) was developed to predict the biopolymer solubilities in ionic liquids (ILs) on the basis of conductor-like screening model for real solvents calculations of two thermodynamic properties: logarithmic activity coefficient (ln γ) at infinite dilution and excess enthalpy (H ^E) of mixture. The calculation was based on the optimized two-dimensional structures of biopolymer models and ILs by searching the lowest-energy conformer and optimizing molecular geometry. Three lignin models together with one IL dataset were used to evaluate the prediction ability of the developed method. The evaluation results show that ln γ is a more reliable property to predict lignin solubilities in ILs and the p-coumaryl alcohol model is considered as the best model to represent lignin molecules. The developed MoDoop approach is efficient for rapid in silico screening of suitable ionic liquids to dissolve biopolymers.

Experimental and Theoretical Study on Supramolecular Ionic Liquid (IL)-Asphaltene Complex Interactions and Their Effects on the Flow Properties of Heavy Crude Oils

A combined study for understanding the molecular interactions of asphaltenes with molecular species such as ionic liquids (ILs) comprised experimental measurements and computational numerical simulation calculations, using density-functional theory (DFT) with dispersion corrections, molecular dynamics (MD) calculations, and experimental rheological characterization of the heavy crude oils (HCOs), before and after doping with ILs, respectively. The main results show that ILs influence the asphaltenic dimer association by forming supramolecular complexes that modify the properties of crude oils such as viscosity and interfacial tension. The IL-cation and asphaltene-π ligand molecular interactions seem to dominate the interactions between ionic liquids and asphaltenes, where ILs' high aromaticity index induces a strong interaction with the aromatic hard core of asphaltenes.

Quantifying intermolecular interactions of ionic liquids using cohesive energy densities

For ionic liquids (ILs), both the large number of possible cation + anion combinations and their ionic nature provide a unique challenge for understanding intermolecular interactions. Cohesive energy density, ced, is used to quantify the strength of intermolecular interactions for molecular liquids, and is determined using the enthalpy of vaporization. A critical analysis of the experimental challenges and data to obtain ced for ILs is provided. For ILs there are two methods to judge the strength of intermolecular interactions, due to the presence of multiple constituents in the vapour phase of ILs. Firstly, ced_IP, where the ionic vapour constituent is neutral ion pairs, the major constituent of the IL vapour. Secondly, ced_C+A, where the ionic vapour constituents are isolated ions. A ced_IP dataset is presented for 64 ILs. For the first time an experimental ced_C+A, a measure of the strength of the total intermolecular interaction for an IL, is presented. ced_C+A is significantly larger for ILs than ced for most molecular liquids, reflecting the need to break all of the relatively strong electrostatic interactions present in ILs. However, the van der Waals interactions contribute significantly to IL volatility due to the very strong electrostatic interaction in the neutral ion pair ionic vapour. An excellent linear correlation is found between ced_IP and the inverse of the molecular volume. A good linear correlation is found between IL ced_IP and IL Gordon parameter (which are dependent primarily on surface tension). ced values obtained through indirect methods gave similar magnitude values to ced_IP. These findings show that ced_IP is very important for understanding IL intermolecular interactions, in spite of ced_IP not being a measure of the total intermolecular interactions of an IL. In the outlook section, remaining challenges for understanding IL intermolecular interactions are outlined.