Overview and thermodynamic modelling of deep eutectic solvents as co-solvents to enhance drug solubilities in water.

The poor water solubility of active pharmaceutical ingredients (APIs) is a major challenge in the pharmaceutical industry. Co-solvents are sometimes added to enhance drug dissolution. A novel group of co-solvents, the Deep Eutectic Solvents (DES), have gained interest in the pharmaceutical field due to their good solvent power, biodegradability, sustainability, non-toxicity, and low cost. In this study, we first provide an overview of all the literature solubility studies involving a drug or API + water + DES, which can be a valuable list to some researchers. Then, we analyze these systems with focus on each individual drug/API and provide statistical information on each. A similar analysis is carried out with focus on the individual DESs. An investigation of the numeric values of the water-solubility enhancement by the different DESs for various drugs indicates that DESs are indeed effective co-solvents, with varying degrees of solubility enhancement, even up to 15-fold. This is strongly encouraging, indicating the need for further studies to find the most promising DESs for solubility enhancement. However, time-consuming and costly trial and error should be prevented by first screening, using theoretical-based or thermodynamic-based models. Based on this conclusion, the second part of the study is concerned with investigating and suggesting accurate thermodynamic approaches to tackle the phase equilibrium modeling of such systems. For this purpose, a large data bank was collected, consisting of 2009 solubility data of 25 different drugs/APIs mixed with water and 31 different DESs as co-solvents at various DES concentrations, over wide ranges of temperatures at atmospheric pressure. This data bank includes 107 DES + water + drug/API systems in total. The solubility data were then modeled according to the solid-liquid equilibrium framework, using the local composition activity coefficient models of NRTL, and UNIQUAC. The results showed acceptable behavior with respect to the experimental values and trends for all of the investigated systems, with AARD% values of 9.65 % and 14.08 % for the NRTL and UNIQUAC models, respectively. In general, the lower errors of NRTL, as well as its simpler calculation process and the requirement of fewer component parameters, suggest the priority of NRTL over UNIQUAC for use in this field.

Editorial for Special Issue: "Recent Advances in Green Solvents".

Today, environmental conservation is one of the most urgent targets [...].

Predicting the Surface Tension of Deep Eutectic Solvents: A Step Forward in the Use of Greener Solvents.

Deep eutectic solvents (DES) are an important class of green solvents that have been developed as an alternative to toxic solvents. However, the large-scale industrial application of DESs requires fine-tuning their physicochemical properties. Among others, surface tension is one of such properties that have to be considered while designing novel DESs. In this work, we present the results of a detailed evaluation of Quantitative Structure-Property Relationships (QSPR) modeling efforts designed to predict the surface tension of DESs, following the Organization for Economic Co-operation and Development (OECD) guidelines. The data set used comprises a large number of structurally diverse binary DESs and the models were built systematically through rigorous validation methods, including 'mixtures-out'- and 'compounds-out'-based data splitting. The most predictive individual QSPR model found is shown to be statistically robust, besides providing valuable information about the structural and physicochemical features responsible for the surface tension of DESs. Furthermore, the intelligent consensus prediction strategy applied to multiple predictive models led to consensus models with similar statistical robustness to the individual QSPR model. The benefits of the present work stand out also from its reproducibility since it relies on fully specified computational procedures and on publicly available tools. Finally, our results not only guide the future design and screening of novel DESs with a desirable surface tension but also lays out strategies for efficiently setting up silico-based models for binary mixtures.

Investigation of carbon dioxide solubility in various families of deep eutectic solvents by the PC-SAFT EoS.

Having been introduced in 2003, Deep Eutectic Solvents (DESs) make up a most recent category of green solvents. Due to their unique characteristics, and also their tunable physical properties, DESs have shown high potentials for use in various applications. One of the investigated applications is CO2 absorption. The thermodynamic modeling of CO2 solubility in DESs has been pursued by a number of researchers to estimate the capacity and capability of DESs for such tasks. Among the advanced equations of state (EoSs), the Perturbed Chain-Statistical Associating Fluid Theory (PC-SAFT) is a well-known EoS. In this study, the performance of the PC-SAFT EoS for estimating CO2 solubility in various DESs, within wide ranges of temperatures and pressures, was investigated. A large data bank, including 2542 CO2 solubility data in 109 various-natured DESs was developed and used for this study. This is currently the most comprehensive study in the open literature on CO2 solubility in DESs using an EoS. For modeling, the DES was considered as a pseudo-component with a 2B association scheme. CO2 was considered as both an inert and a 2B-component and the results of each association scheme were compared. Considering the very challenging task of modeling a complex hydrogen bonding mixture with gases, the results of AARD% being lower than 10% for both of the investigated association schemes of CO2, showed that PC-SAFT is a suitable model for estimating CO2 solubilities in various DESs. Also, by proposing generalized correlations to predict the PC-SAFT parameters, covering different families of DESs, the developed model provides a global technique to estimate CO2 solubilities in new and upcoming DESs, avoiding the necessity of further experimental work. This can be most valuable for screening and feasibility studies to select potential DESs from the innumerable options available.

Deep Eutectic Solvents as Phase Change Materials in Solar Thermal Power Plants: Energy and Exergy Analyses.

Nowadays, producing energy from solar thermal power plants based on organic Rankine cycles coupled with phase change material has attracted the attention of researchers. Obviously, in such solar plants, the physical properties of the utilized phase change material (PCM) play important roles in the amounts of generated power and the efficiencies of the plant. Therefore, to choose the best PCM, various factors must be taken into account. In addition, considering the physical properties of the candidate PCM, the issue of environmental sustainability should also be considered when making the selection. Deep eutectic solvents (DESs) are novel green solvents, which, in addition to having various favorable characteristics, are environmentally sustainable. Accordingly, in this work, the feasibility of using seven different deep eutectic solvents as the PCMs of solar thermal power plants with organic Rankine cycles was investigated. By applying exergy and energy analyses, the performances of each were compared to paraffin, which is a conventional PCM. According to the achieved results, most of the investigated "DES cycles" produce more power than the conventional cycle using paraffin as its PCM. Furthermore, lower amounts of the PCM are required when paraffin is replaced by a DES at the same operational conditions.

Evaluation of Deep Eutectic Systems as an Alternative to Solvents in Painting Conservation.

Natural deep eutectic solvents (NADESs) are considered as green solvents, and due to their promising sustainability, they have been applied in many research fields. In this study, the main goal is to use various NADES systems to replace the traditional solvents used in conservation and restoration to remove varnish layers in a painting. The toxicity of traditional solvents, such as toluene or acetone, is well known in the chemistry field. To replace them, it is important to understand the intrinsic physicochemical properties of a solvent that may act as a substitute. Polarity and solubility are proposed as the best parameters required for this study. The Nile red probe was used to confirm the similarity between the polarity of deep eutectic systems (DESs) and traditional solvents. According to their polarities and Hansen solubility parameters, it is possible to predict the best solvents to solubilize the natural resin varnishes. Besides this, some arithmetic models can also be applied to estimate the critical or thermodynamic properties, which are useful tools to predict the behavior of these solvents. We have further proven the possibility of dissolving natural varnishes such as dammar or mastic in hydrophobic DESs, such as menthol + lauric acid, menthol + decanoic acid, or menthol + thymol.

Density of Deep Eutectic Solvents: The Path Forward Cheminformatics-Driven Reliable Predictions for Mixtures.

Deep eutectic solvents (DES) are often regarded as greener sustainable alternative solvents and are currently employed in many industrial applications on a large scale. Bearing in mind the industrial importance of DES-and because the vast majority of DES has yet to be synthesized-the development of cheminformatic models and tools efficiently profiling their density becomes essential. In this work, after rigorous validation, quantitative structure-property relationship (QSPR) models were proposed for use in estimating the density of a wide variety of DES. These models were based on a modelling dataset previously employed for constructing thermodynamic models for the same endpoint. The best QSPR models were robust and sound, performing well on an external validation set (set up with recently reported experimental density data of DES). Furthermore, the results revealed structural features that could play crucial roles in ruling DES density. Then, intelligent consensus prediction was employed to develop a consensus model with improved predictive accuracy. All models were derived using publicly available tools to facilitate easy reproducibility of the proposed methodology. Future work may involve setting up reliable, interpretable cheminformatic models for other thermodynamic properties of DES and guiding the design of these solvents for applications.

Viscosity Investigations on the Binary Systems of (1 ChCl:2 Ethylene Glycol) DES and Methanol or Ethanol.

In this study, the viscosity behavior of two mixtures of Ethaline (1 ChCl:2 ethylene glycol) with either methanol or ethanol were investigated over the temperature range of 283.15-333.15 K at atmospheric pressure. The measured viscosities of neat Ethaline, methanol, and ethanol showed reliable agreement with the corresponding reported literature values. The mixture viscosities were modeled by an Arrhenius-like model to determine the behavior of viscosity with respect to temperature. The data were also modeled by the four well-known mixture viscosity models of Grunberg-Nissan, Jouyban-Acree, McAllister, and Preferential Solvation. All of the model results were reliable, with the Jouyban-Acree and Preferential Solvation models showing the most accurate agreement with the experimental measurements. The Jones-Dole viscosity model was also investigated for the measured viscosities, and by analyzing the results of this model, strong interactions among Ethaline and the alcohol molecules were proposed for both systems. As a final analysis, viscosity deviations of the investigated systems were calculated to study the deviations of the viscosity behaviors with respect to ideal behavior. Both systems showed negative viscosity deviations at all of the investigated temperatures, with the negative values tending towards zero, and hence more ideal behavior, with increasing temperatures. Moreover, in order to correlate the calculated viscosity deviations, the Redlich-Kister model was successfully used for both systems and at each investigated temperature.

Group contribution and atomic contribution models for the prediction of various physical properties of deep eutectic solvents.

The urgency of advancing green chemistry from labs and computers into the industries is well-known. The Deep Eutectic Solvents (DESs) are a promising category of novel green solvents which simultaneously have the best advantages of liquids and solids. Furthermore, they can be designed or engineered to have the characteristics desired for a given application. However, since they are rather new, there are no general models available to predict the properties of DESs without requiring other properties as input. This is particularly a setback when screening is required for feasibility studies, since a vast number of DESs are envisioned. For the first time, this study presents five group contribution (GC) and five atomic contribution (AC) models for densities, refractive indices, heat capacities, speeds of sound, and surface tensions of DESs. The models, developed using the most up-to-date databank of various types of DESs, simply decompose the molecular structure into a number of predefined groups or atoms. The resulting AARD% of densities, refractive indices, heat capacities, speeds of sound and surface tensions were, respectively, 1.44, 0.37, 3.26, 1.62, and 7.59% for the GC models, and 2.49, 1.03, 9.93, 4.52 and 7.80% for the AC models. Perhaps, even more importantly for designer solvents, is the predictive capability of the models, which was also shown to be highly reliable. Accordingly, very simple, yet highly accurate models are provided that are global for DESs and needless of any physical property information, making them useful predictive tools for a category of green solvents, which is only starting to show its potentials in green technology.

Energy Conservation in Absorption Refrigeration Cycles Using DES as a New Generation of Green Absorbents.

Deep eutectic solvents (DESs) are emerging green solvents with very unique characteristics. Their contribution to atmospheric pollution is negligible, and they can be "designed" for desired properties. In this study, the feasibility of applying DESs (Reline, Ethaline, or Glyceline) as absorbents in absorption refrigeration cycles was investigated. The sophisticated cubic-plus-association (CPA) equation of state, considering the strong intermolecular interactions of such complex systems, was used to estimate the thermodynamic properties. At a fixed set of base case operating conditions, the coefficients of performance were calculated to be 0.705, 0.713, and 0.716 for Reline/water, Ethaline/water, and Glyceline/water systems, respectively, while the corresponding mass flow rate ratios were 33.73, 11.53, and 16.06, respectively. Furthermore, the optimum operating conditions of each system were estimated. To verify the feasibility, results were compared to literature systems, including LiBr/water and various ionic liquid/water systems. The results indicate that DES/water working fluids have the potential to be used in such cycles. Since DESs have the characteristic to be tuned (designed) to desired properties, including their solvent power and their enthalpies of absorption, much further research needs to be done to propose new DESs with higher energy efficiencies.

A Global Model for the Estimation of Speeds of Sound in Deep Eutectic Solvents.

Deep eutectic solvents (DESs) are newly introduced green solvents that have attracted much attention regarding fundamentals and applications. Of the problems along the way of replacing a common solvent by a DES, is the lack of information on the thermophysical properties of DESs. This is even more accentuated by considering the dramatically growing number of DESs, being made by the combination of vast numbers of the constituting substances, and at their various molar ratios. The speed of sound is among the properties that can be used to estimate other important thermodynamic properties. In this work, a global and accurate model is proposed and used to estimate the speed of sound in 39 different DESs. This is the first general speed of sound model for DESs. The model does not require any thermodynamic properties other than the critical properties of the DESs, which are themselves calculated by group contribution methods, and in doing so, make the proposed method entirely independent of any experimental data as input. The results indicated that the average absolute relative deviation percentages (AARD%) of this model for 420 experimental data is only 5.4%. Accordingly, based on the achieved results, the proposed model can be used to predict the speeds of sound of DESs.

Solubility of Carbon Dioxide in Secondary Butyl Alcohol at High Pressures: Experimental and Modeling with CPA.

Mixtures of carbon dioxide and secondary butyl alcohol at high pressures are interesting for a range of industrial applications. Therefore, it is important to have trustworthy experimental data on the high-pressure phase behavior of this mixture over a wide range of temperatures. In addition, an accurate thermodynamic model is necessary for the optimal design and operation of processes. In this study, bubble points of binary mixtures of CO2 + secondary butyl alcohol were measured using a synthetic method. Measurements covered a CO2 molar concentration range of (0.10-0.57) % and temperatures from (293 to 370) K, with pressures reaching up to 11 MPa. The experimental data were modelled by the cubic plus association (CPA) equation of state (EoS), as well as the more simple Soave-Redlich-Kwong (SRK) EoS. Predictive and correlative modes were considered for both models. In the predictive mode, the CPA performs better than the SRK because it also considers associations.

Derivative properties from high-precision equations of state.

In this study, the behavior of derivative properties estimated by equations of state, including isochoric heat capacity, isobaric heat capacity, speed of sound, and the Joule-Thomson coefficient for pure compounds and a mixture, has been investigated. The Schmidt-Wagner and Jacobsen-Stewart equations of state were used for predictions of derivative properties of 10 different pure compounds from various nonpolar hydrocarbons, nonpolar cyclic hydrocarbons, polar compounds, and refrigerants. The estimations were compared to experimental data. To evaluate the behavior of mixtures, the extended corresponding states principle (ECS) was studied. Analytical relationships were derived for isochoric heat capacity, isobaric heat capacity, the Joule-Thomson coefficient, and the speed of sound. The ECS calculations were compared to the reference surface data of methane + ethane. The ECS principle was found to generate data of high quality.