Publication Date: 2025
Thermochimica Acta (00406031)749
Deep Eutectic Solvents (DESs) are often categorized as novel green solvents. Knowledge of the thermal conductivity of a solvent in an industrial process is vital for the optimization of energy utilization. Considering the vast number of DESs introduced to date, it is practically impossible to measure all their thermal conductivities. Thus, it is vital to have predictive models that can predict the thermal conductivities of various DESs, and at different temperatures. For this purpose, a large data bank was collected, including 338 data points from 56 DESs of various natures. The data were used to develop a group contribution (GC) model and an atomic contribution (AC) model to predict the thermal conductivities of DESs. The calculated AARD% values of 7.62 % and 9.52 % for the proposed GC and AC models, respectively, indicated reliable performance and promising predictions for both models. The models were also compared to well-known literature models. © 2025 Elsevier B.V.
Publication Date: 2025
Thermochimica Acta (00406031)754
Deep eutectic solvents (DESs) are gaining attention as sustainable alternatives to conventional solvents due to their tunable properties and environmental advantages. Yet, predicting their physical behavior, particularly acoustic properties like the speed of sound, remains limited, especially in approaches that consider chemical structure. This study introduces a hybrid machine learning framework that incorporates molecular-level information to predict the speed of sound in DES systems with high accuracy and interpretability. A dataset of 1001 experimental data points, collected from 92 distinct DESs under atmospheric pressure and varying temperatures, was used to train and evaluate the models. Instead of relying solely on bulk experimental parameters, the models integrate structural descriptors based on group and atomic contributions, capturing detailed chemical features of both hydrogen bond donors and acceptors. These structure-based inputs were embedded into machine learning algorithms to develop robust and generalizable predictive tools. The resulting models demonstrated excellent performance, achieving average absolute relative deviations below 1 %. In addition to strong predictive power, the framework allows for interpretation of how specific molecular characteristics influence acoustic behavior, offering a transparent view into the structure–property relationship. This work advances the application of machine learning in solvent science by uniting chemical intuition with data-driven modeling. The hybrid approach not only enhances predictive capability but also provides mechanistic insight, making it a valuable tool for the rational design and selection of DESs in green chemistry, materials processing, and related fields. © 2025 Elsevier B.V.
Halder, A.K.,
Haghbakhsh, R.,
Ferreira, E.S.,
Duarte, A.R.C.,
Cordeiro, M.N.D. Publication Date: 2025
Journal of Molecular Liquids (18733166)418
Heat capacity, a crucial physical property for chemical processes, is often understudied in Deep Eutectic Solvents (DESs), which in turn are promising green alternatives to environmentally hazardous conventional solvents. This work addresses this gap by developing a machine learning model to predict DES heat capacity and identify key structural features influencing it. We employed a dataset of 530 DESs with corresponding experimental heat capacity values. Quantum-chemical COSMO-RS-based descriptors, capturing detailed information about DES structures, were calculated for each data point. Various machine learning algorithms, namely k-Nearest Neighbours (kNN), Random Forests (RF), Neural Network Multilayer Perceptron (MLP), and Support Vector Machines (SVM) were explored alongside a linear model (Multiple Linear Regression, MLR). Hyperparameter optimisation ensured all models were fine-tuned for optimal performance. The most successful model, based on the MLP technique, achieved remarkably low Average Absolute Relative Deviation (AARD) values of 0.500 % and 3.999 % for the training and test sets, respectively. This signifies a significant improvement in prediction accuracy compared to traditional methods. Furthermore, by applying a SHapley Additive exPlanations (SHAP) analysis, we identified the most crucial structural factors within DES components that govern their heat capacity. This comprehensive investigation offers valuable insights that can pave the way for an efficient design of novel DESs in the future. © 2024 The Author(s)
Rasekh M.R.E.,
Sharifi F.M.,
Alavi S.,
Janatyan, N.,
Javadi M.H.M.,
Rajabi, A.,
Karvar, H.,
Haghbakhsh, R.,
Foruzan, M.,
Goshadrou, A. Publication Date: 2025
e-Prime - Advances in Electrical Engineering, Electronics and Energy (27726711)pp. 2091-2096
This paper aims to introduce a model of the solar plant electricity supply chain, encompassing mixed power plants, transmission lines, and consumers, with a focus on optimization and consideration of uncertainties. Within this article, the supply chain of solar power plants is delineated based on various parameters. The quantities of power plants and solar panels are determined by different priorities, such as investment levels, pollution mitigation, and reduction of gas consumption by conventional power plants, utilizing the particle swarm algorithm for optimal outcomes. The proposed model addresses uncertainties related to electricity demand, solar radiation levels, and consequently, the power production of solar panels, through the application of type 2 fuzzy logic. The optimization of the model is done keeping in mind various constraints including the supply of electricity and the maximum allowed use of solar cells. The innovation of this article is in the design of the supply chain model from the point of view of the uncertainty of electric power production and the amount of consumer demand and the optimal selection of solar panels for solar power plants to minimize the electricity consumption of the gas power plant and the amount of pollution caused by it. Based on the results obtained from the simulation of this article, it has been shown that considering the maximum investment capacity, up to 76 % of the electric energy can be supplied by building five solar power plants at certain distances from the electric substations around the case study. Considering the maximum weight coefficients for CO2 plant emissions and gas consumption, five solar power plants are the optimal number that is achieved by proposed algorithm. The power capacity of five solar power plants is optimized 4.100,4.222,3.920,4.375and 3.991MW, respectively. To evaluation of the proposed model, PSO algorithm is compared to GA and the results show that cost function and convergence time in PSO is less than GA in the various weight coefficients scenarios. This optimal mode leads to the maximum reduction of gas consumption in the gas power plant, and on the other hand, the amount of pollution is minimized. The prediction of this number of power plants with different priorities is presented in this article and different policies can be considered strategically for this model of the supply chain. © 2025
Publication Date: 2025
Industrial and Engineering Chemistry Research (15205045)64(1)pp. 823-832
Deep eutectic solvents (DESs) are novel green solvents. Potential applications of DESs require a knowledge of their physical and thermodynamic properties. This study is devoted to the DES heat capacity. Since the potential number of DESs to be prepared in the future is innumerable, it is vital to have predictive models. In this study, two machine learning models, namely, the multilayer perceptron artificial neural network (MLPANN) and the least square support vector machine (LSSVM) were coupled with the group contribution (GC) and atomic contribution (AC) approaches. In the contribution methods, each structural fragment of the compounds is considered as input to the machine learning models, significantly enhancing predictive capability. A comprehensive database was collected, including 640 data points from 51 different DESs at various temperatures. The MLPANN-GC and LSSVM-GC models resulted in AARD% values of 1.74 and 1.73%, respectively, while the corresponding values were 2.90 and 2.64% for the MLPANN-AC and LSSVM-AC models. © 2024 American Chemical Society.
Publication Date: 2025
European Journal of Pharmaceutics and Biopharmaceutics (18733441)211
The pharmaceutical sector is aware of supercritical CO2 (SC-CO2) as a possible replacement for problematic organic solvents. Using a novel artificial intelligence (AI) strategy to predict drug solubility using the SC-CO2 system mathematically has been deemed an intriguing approach. In this work, the atomic contribution (AC) method and machine learning (ML) models are combined to develop hybrid machine learning models to compute the solubility of several drugs, including anticoagulants, anti-cancers, calcium channel blockers, immunosuppressives, antihistamines, and others. The novelty of the approach lies in using the AC concept to capture molecular details at the atomic level. This enables the model to account for the specific contributions of individual atoms and to provide more precise input features for machine learning. The integration of these molecular insights with ML techniques results in significantly improved predictive performance over traditional ML methods. Throughout the modeling procedure, temperature, pressure, the density of SC-CO2, and the effect of constituent atoms of the drugs are the input variables, while the solubility of drugs is the output. This study looks into predicting the solubility of these drugs in SC-CO2 using the least square support vector machine (LSSVM) with radial basis function kernel (RBF) and multilayer perceptron artificial neural network (MLPANN). These models were developed using a database including 2358 experimental solubility data points from 86 solid drugs. The solubility of solid drugs in supercritical CO2 spans a remarkably wide range in this study, from as high as 3.9 × 10-2 to as low as 1 × 10-7. The results demonstrated that this innovative approach could estimate solid drug solubility in SC-CO2 with AARD% and R2 values of 7.20 and 0.99, respectively, under different pressure and temperature conditions. The ability of the models to capture a wide range of solubilities in SC-CO2 showcases their effectiveness in dealing with both highly and poorly soluble compounds. The developed models, considering their global prediction, accuracy, and being user-friendly, are the best options to be used by researchers for incorporating into software for enabling more efficient design of supercritical extraction processes and reducing the need for trial-and-error experimentation in manufacturing. © 2025 Elsevier B.V.
Given the common challenge of low solubility of many drugs in water, it is vital to implement novel methods to improve it. One method that is widely used across various applications is the use of co-solvents. In particular, Deep Eutectic Solvents have been recognized for their potential in the pharmaceutical industries. This potential is due to their environmental compatibility, cost-effectiveness, and desirable properties. Due to the large number and variety of deep eutectic solvents, it is not possible to perform experimental studies to determine the effect of Deep Eutectic Solvents on the solubility of drugs in water. Thus, it is vital to have thermodynamic models, to help researchers to estimate how the co-solvents enhance the solubility of drugs. This research investigates the performance of five relevant thermodynamic models. The investigated models are all empirical and require regression on the experimental data of each system to be used, which makes them non-predictive. Therefore, to overcome this issue, for the first time, the Khayam-Rajabi-Haghbakhsh model (KRH) has been developed as the first comprehensive and accurate predictive model for estimating the solubility of various drugs in water considering Deep Eutectic Solvents as co-solvents. For the development of this model, a comprehensive data bank including 1489 experimental data points for 13 different drugs and 17 Deep Eutectic Solvents has been used. The AARD% of this model has been calculated to be 13.00, indicating a high level of accuracy. Statistical analysis demonstrates acceptable and unbiased performance across all Deep Eutectic Solvents and drugs investigated. This model is widely utilized for various drug systems, water, and Deep Eutectic Solvents as co-solvents due to its comprehensiveness, accuracy, and capability to estimate drug solubility without needing experimental data. © 2025 Semnan University.
Publication Date: 2025
Separation and Purification Technology (13835866)354
Hydrogen sulfide (H2S) is one of the most dangerous impurities of natural gas which cause human and environmental issues. Thus, the main process of gas sweetening plants is H2S removal from natural gas. Amine solutions are the commonly used solvents for gas-sweetening processes in petroleum industries. However, amin solutions are not safe and cause many environmental issues especially in the post-process treatment of used amine. Thus, the issue of proposing green sustainable solvents for gas sweetening is vital for petroleum industries. Deep Eutectic Solvents (DESs) are the most recently introduced green solvents which have shown good capability for H2S absorption. Thus, DESs are one of the most possible candidates for green solvents to replace amine solutions. Experimental studies to choose suitable solvents is a tough challenge because working with H2S is very dangerous and requires expensive facilities. Therefore, an accurate and global thermodynamic model is necessary to predict the solubilities of H2S in DESs without the requirement of experimental data. This study for the first time in open literature, proposes two accurate and global thermodynamic models of group contribution (GC) and atomic contribution (AC) for predicting the H2S solubilities in various nature DESs. The largest and most updated data bank for H2S solubility in DESs was developed from open literature, including 415 solubility data of 37 different nature DESs. The proposed GC and AC models were developed according to the gathered data bank and their results were analyzed by statistical parameters. Both GC and AC models show normal behavior and promising results concerning experimental data by the calculated AARD% of 9.64, and 12.86, respectively. © 2024 Elsevier B.V.
Publication Date: 2025
Journal of Hazardous Materials (18733336)490
Sulfur dioxide (SO2) is one of the hazardous gases during coal or hydrogen sulfide combustion in petrochemical and coal-related industries. Unfortunately, SO2 is released into the atmosphere in most SO2-involved industries. The high concentration of SO2 in the atmosphere leads to acid rain, which leads to various damage and destruction of the environment. Therefore, preventing SO2 emissions into the atmosphere is vital. Considering environmental guidelines, Deep Eutectic Solvents (DESs), as the recent category of green solvents because of their eco-friendly characteristics are interesting. Considering the huge number of introduced DESs and also the costly and time-consuming process for experimental measurement of SO2 absorption by DESs, it is vital to have predictive thermodynamic models for predicting SO2 solubilities in DESs. In this study, for the first time in open literature, two general, accurate, and predictive models of atomic and group contributions were developed for SO2 absorption by various nature DESs based on a comprehensive data bank over wide ranges of temperatures and pressures. The gathered data bank includes 997 SO2 absorption data points for 65 various nature DESs. Both developed GC and AC models showed reliable and predictive performances by presenting the AARD% values of 10.3 and 11.7, respectively. © 2025 Elsevier B.V.
Publication Date: 2025
Journal of Molecular Liquids (18733166)428
Most of the recent studies have been praising the peculiar ability of deep eutectic systems (DES), especially the natural-based ones (designated by NADES), in dissolving a wide variety of compounds. Despite their remarkable physicochemical properties, it is still true that little is known about the factors that would help to comprehend their interesting behaviour when they are used as solvents. Hence, it is important to gather as many tools as possible that can be useful for understanding it. First, the affinity degrees between the two selected compounds (Ibuprofen and Xylitol) and the various NADES, were analysed using Hansen Solubility Parameters (HSPs), which confirmed to be a good tool for screening good and bad NADES for solubilising Ibuprofen and Xylitol. Although, in general, the empirical models (EM) such as the one proposed by Hoftyzer-Van Krevelen and Fedors (HKF) and Yamamoto (Ymt) performed better than the semi-empirical models (SEM), when it came to assessing affinity, it was found that this actually depends on the type of assessment carried out, i.e., if it is in 1- or 2-dimension. Furthermore, it was also found that, except for the dispersive parameter (δd), all the others play a significant role in the interaction between the two compounds and NADES, especially the total solubility parameter (δt). Finally, the correlations between a set of physiochemical properties of NADES and the solubility data were evaluated in this work where it was possible to conclude that surface tension, density and molar volume are those that present the highest contribution for the variations in the solubility. © 2025 The Authors
Publication Date: 2024
Chemosphere (00456535)366
Sulfur dioxide (SO2), produced mainly from the combustion of coal, is the most important cause of acidic rain, skin diseases, and environmental issues. To overcome the environmental problems, SO2 must be captured on an industrial scale before it is released into the air. In chemical industries, organic solvents are used for partial absorption of SO2. However, those organic solvents have negative environmental effects. Thus, proposing environmentally friendly and green solvents for SO2 absorption is vital for industries. Recently, increased attention has been paid to capturing SO2 using Deep Eutectic Solvents (DESs) as the most recently introduced category of green solvents. This study performed a comprehensive screening study on the investigation of the performance of various simple and complicated models for SO2 solubilities in a wide range of different nature DESs. For this purpose, the most updated and largest SO2 solubility data bank in DESs involving 976 data points for 63 different nature DESs over wide temperature and pressure ranges has been gathered from open literature. For model screening, for the physical absorption models, the performances of SRK and CPA as the simple cubic and complicated sophisticated equations of state, NRTL and UNIQUAC as the well-known activity coefficient models, and for the chemical absorption models, RETM were investigated and compared. For physical absorption models, coupling an equation of state with the UNIQUAC activity coefficient model i.e. CPA-UNIQUAC, SRK-UNIQUAC, and also using simple SRK-SRK models led to the best performances. Compared to all investigated models, RETM as the chemical absorption model showed the best performance with the AARD% value of 12.95. This shows the importance of considering the chemical absorption mechanism for SO2 absorption by DESs. Finally, general guidelines for using different modeling approaches were proposed to be considered by the researchers. © 2024 Elsevier Ltd
Publication Date: 2024
Journal of Molecular Liquids (18733166)399
The Deep Eutectic Solvents (DESs), considering their favorable features, such as low vapor pressure, environmental sustainability, and biodegradability, have gained much attention in the last two decades. However, further development of DESs requires knowledge of their physical and critical properties. Since most DESs thermally decompose before reaching their critical point, their critical properties cannot be measured experimentally. Therefore, theoretical predictive methods, such as group contribution (GC) models are applied. However, up to now, no GC models have been developed specifically for the estimation of DES critical properties. To deal with this issue, almost all of the researchers have applied the modified Lydersen Joback-Reid method developed for Ionic Liquids (ILs), proposed by the group of Valderamma. Since ILs are basically different compounds than DESs, the question remains as to why a model aimed specifically at ILs should be used for DESs. Furthermore, the reliability and extent of accuracy of their application to DESs are unknown. A third question in this area is whether other GC models could be applied to DESs. To investigate these issues, in the present study, six different GC models, namely the Lydersen, Ambrose, Klincewicz-Reid, Joback-Reid, Valderamma-Alvarez and Valderamma-Robles models, were studied for the estimation of the critical properties and acentric factors of a wide variety of DESs. To evaluate the reliability of the investigated GC models, since actual experimental data are not available for these properties, an indirect approach was taken in which the predicted critical properties and acentric factors were used to estimate densities and surface tensions (one volume based and one energy-based parameter), whose experimental data are available for DESs. The results indicated that the Ambrose model, followed by the Valderamma-Alvarez and Valderamma- Robles models, by considering their better performances and the larger variety of DESs that they can handle, are the most globally applicable among all six investigated GC models. Regarding accuracy alone, the model of Ambrose has an edge over the others and is suggested as the most accurate GC model for the estimation of the critical properties and acentric factors of DESs. The Valderamma-Alvarez and Valderamma-Robles models seem to be the next best accurate models. Therefore, the overall results of this study point out that the common approach taken up to this point by almost all researchers to estimate these properties needs to be reconsidered. © 2024 Elsevier B.V.
Publication Date: 2023
Journal of Chemical Thermodynamics (10963626)178
In this study, carbon dioxide solubilities were measured experimentally in the DES composed of 1 NaBr + 6 ethylene glycol at temperatures ranging from 293.2 to 323.2 K and pressures up to 37 bars. The minimum and maximum measured CO2 solubilities (in mole fraction) within the investigated temperature and pressure ranges were 0.0013 and 0.0526, respectively. The measured data were then used to optimize the values of fitting parameters of the Cubic Plus Association, and the Soave–Redlich–Kwong EoSs equations of state. The AARD% values of 3.37 % and 2.52 % for SRK and CPA EoSs, respectively, showed reliable results for both models. However, the SRK EoS could estimate accurate carbon dioxide solubilities only by much larger binary interaction parameters, as compared to the CPA EoS. Also, using the measured data, the values of Henry's constant, standard enthalpy, standard entropy, and standard Gibbs free energy of dissolution were calculated according to thermodynamic relations. The stronger interactions in the mixture of carbon dioxide with DES by the establishment of new intermolecular bonds (as compared to the pure DES), leads to the liberating of energy upon dissolution. This also results in less disorder and chaos as indicated by analyzing the above-mentioned thermodynamic properties. © 2022
Publication Date: 2023
Journal of Molecular Liquids (18733166)388
In this study, hybrid machine learning nonlinear models were developed to predict the viscosity of DESs by combining the group contribution (GC) concept with the multilayer perceptron, a well-known feedforward artificial neural network, and the Least Squares Support Vector Machine (LSSVM) algorithm. Deep Eutectic Solvents (DESs) have come to the forefront in recent years as appealing substitutes for conventional solvents. It is imperative to have a thorough grasp of the essential properties of DESs to expand the employment of these compounds in new procedures. Most frequently, one of the crucial physical properties of a DES that must be precisely determined is its viscosity. To develop the models, a dataset of 2533 viscosity data points for 305 DESs at various temperatures (from 277.15 to 373.15 K) was gathered to build the models. By using temperature, molar ratios, and functional groups as inputs, the results indicate that the suggested models can determine the viscosity of DESs with high accuracy. The models yield average absolute relative deviations below 10% and squared correlation coefficients higher than 0.98. © 2023 The Author(s)
Publication Date: 2023
Molecules (14203049)28(16)
Publication Date: 2023
Journal of Molecular Liquids (18733166)384
The classification of Natural Deep Eutectic Systems (NADES) as promising alternative solvents for the 21st century has been reported. Although this is mainly due to their very interesting characteristics that have attracted the attention of the scientific community, there is, however, a lack of information regarding many physicochemical properties of these compounds. Therefore, the main objective of this work was to characterize and relate the properties, both of hydrophilic and hydrophilic NADES, regarding their water content, density, viscosity, refractive index, dielectric constant, dipole moment, surface tension, as well solvatochromic parameters. Comparatively to the set of organic solvents also explored, it was observed that for these parameters studied, the values of hydrophilic systems are mostly higher than those of organic solvents, which in turn tend to be higher than those of hydrophobic systems. Moreover, the analysis of solvatochromic parameters (polarity and Kamlet-Taft parameters) provided new evidence for the usefulness of NADES as potential substitute solvents for sustainable development. Finally, regarding the general list of compounds, it was proved with statistical parameters (Pearson correlation coefficient and p-value) that most of the studied properties are strong and significantly correlated with each other. © 2023 The Author(s)
Publication Date: 2023
Fluid Phase Equilibria (03783812)565
Deep Eutectic Solvents (DESs) are a recently introduced class of green solvents with unique and favorable characteristics. Despite their recent debut, the scientific community has begun to place greater emphasis on them as alternatives to ionic liquids (ILs). Knowledge of the various physical properties of DESs is essential for various applications in the chemical industries and related fields. In this study, a comprehensive database including 1410 density data points, from 166 different DESs at various temperatures and atmospheric pressure, were retrieved from open literature to develop models to increase the accuracy of density predictions. The densities of DESs were used to develop two commonly used machine learning models, namely Multilayer Perceptron Artificial Neural Network (MLPANN) and Least Square Support Vector Machine (LSSVM), in conjunction with the group contribution (GC) method. Based on the GC method, each fragment of a compound contributes a specific amount to the physical property's value. By considering this, the prediction ability was improved by applying the GC method in the model development procedure. Both models predict the DES densities by taking into account the effect of 35 functional groups, the temperature, and the HBA/HBD molar ratios. The optimum MLPANN model structure consists of a single hidden layer with five neurons and a logarithmic sigmoid transfer function. By employing this MLPANN-GC model, the values of the squared correlation coefficient, R2, and absolute average relative deviation percent, AARD%, were 0.99 and 0.61%, respectively, while for the LSSVM-GC model (with the radial basis function (RBF) kernel), they were 0.99 and 0.56%, respectively. Also, K-fold cross-validation was used to assess the performance of the LSSVM-GC model. The presented machine learning models in this study were found to perform more accurately than those obtained using the best current correlations and GC models for DES densities in the open literature. The more accurate results, in addition to the enhanced predictability behavior of the developed models, give these models a preference for use in industrial and academic applications. © 2022
Publication Date: 2023
European Journal of Pharmaceutics and Biopharmaceutics (18733441)193pp. 1-15
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. © 2023 Elsevier B.V.
Publication Date: 2023
European Journal of Pharmaceutics and Biopharmaceutics (18733441)193pp. 308-309
Publication Date: 2022
Fluid Phase Equilibria (03783812)561
In this study, the performance of a novel DES, consisting of butane-1,2-diol as the hydrogen bond donor (HBD) and choline chloride as the hydrogen bond acceptor (HBA), was investigated thermodynamically for carbon dioxide absorption. The molar ratio of choline chloride to butane-1,2-diol was 1:4. Carbon dioxide solubilities in this DES were measured experimentally in a high-pressure equilibrium cell. The solubility measurements were carried out in a temperature range of 303.2 to 333.2 K, and pressures up to almost 3.4 MPa. The P-x isotherms showed an almost linear increase of solubility with increasing pressure. Based on the measured experimental data, the values of Henry's constants at very dilute concentrations were calculated, as well as the standard enthalpies, entropies, and Gibbs free energies of dissolution. By analyzing the calculated parameters, it was concluded that the dissolution process is exothermic, and that stronger interactions prevail in the mixture of carbon dioxide and the investigated DES, as compared to the interactions within the neat components. Finally, the Cubic Plus Association (CPA) and Soave-Redlich-Kwong (SRK) equations of state (EoSs) were used to model the experimental solubility data. Absolute average relative deviation percent (AARD%) values of 3.78% and 5.48% for the CPA and SRK EoSs, respectively, indicated good agreement with experimental values for both models. However, the CPA EoS achieved higher accuracy, and with much smaller values of binary interactions parameters, thus indicating the importance of considering association interactions for the accurate modeling of carbon dioxide solubilities in DESs. © 2022
Publication Date: 2022
Fluid Phase Equilibria (03783812)553
In this study, the aqueous mixture viscosities of two phenolic DESs, consisting of (1 ChCl: 3 phenol) and (1 ChCl: 4 phenol), were measured at atmospheric pressure over the temperature range of 293.15–333.15 K. According to the measured data, the values of viscosity deviations for the investigated aqueous systems were calculated to indicate deviating viscosity behavior with respect to ideality. Both aqueous systems showed negative viscosity deviations over the entire composition range and at all of the investigated temperatures. The Redlich-Kister model was applied to estimate the viscosity deviations of both aqueous systems at different compositions and temperatures, while the viscosity behavior, itself, was modeled by different literature models, consisting of the Grunberg-Nissan, Jouyban-Acree, McAllister, Preferential Solvation, and an Arrhenius-like viscosity model. All of the models presented satisfactory agreement, however the Preferential Solvation and the Jouyban-Acree models succeeded to achieve more reliable results as compared to the others. In addition to the mixture viscosity estimation models, the Jones-Dole viscosity model was applied to both of the aqueous systems to suggest the interactions in the mixture. By calculating and analyzing the values of the B-coefficients of this model, possibly stronger interactions among the DESs and water molecules in the mixture were suggested, as compared to the self-species interactions. © 2021
Publication Date: 2022
Molecules (14203049)27(4)
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. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Publication Date: 2022
Frontiers in Chemistry (22962646)10
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. Copyright © 2022 Parvaneh, Haghbakhsh, Duarte and Raeissi.
Halder, A.K.,
Haghbakhsh, R.,
Voroshylova, I.V.,
Duarte, A.R.C.,
Cordeiro, M.N.D. Publication Date: 2022
Molecules (14203049)27(15)
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. © 2022 by the authors.
Halder, A.K.,
Haghbakhsh, R.,
Voroshylova, I.V.,
Duarte, A.R.C.,
Cordeiro, M.N.D. Publication Date: 2021
Molecules (14203049)26(19)
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. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Publication Date: 2021
Journal of Molecular Liquids (18733166)342
When this article was published online, Eqs. (7) and (A13) had typing errors when they appeared as follows: [Formula presented] [Formula presented] The corrected equations are: [Formula presented] [Formula presented] © 2021
Fernandes, C.C.,
Haghbakhsh, R.,
Marques, R.,
Paiva, A.,
Carlyle, L.,
Duarte, A.R.C. Publication Date: 2021
ACS Sustainable Chemistry and Engineering (21680485)9(46)pp. 15451-15460
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. © 2021 The Authors. Published by American Chemical Society.
Publication Date: 2021
Journal of Molecular Liquids (18733166)330
CO2 solubilities in the deep eutectic solvent (1 choline chloride +3 triethylene glycol) were measured at the four temperatures of 303.15, 313.15, 323.15 and 333.15 K and pressures up to 30 bars. Measurements were carried out in a newly designed, built and validated high pressure solubility apparatus. The measured data were modeled by the cubic plus association (CPA) and the Soave-Redlich-Kwong (SRK) equations of state, with AARD% values of 5.52% and 7.30% for the CPA and SRK EoSs, respectively, showing the good correlative ability of both models. Furthermore, by calculating the standard Gibbs free energies of dissolution, standard enthalpies of dissolution and standard entropies of dissolution at infinite dilution, we found that the dissolution process is nonspontaneous and exothermic, with the CO2 - DES interactions being the stronger interactions. The solution becomes less chaotic and reaches a higher degree of order in the liquid phase after dissolution of CO2. © 2021
Publication Date: 2021
Scientific Reports (20452322)11(1)
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. © 2021, The Author(s).
Publication Date: 2021
Molecules (14203049)26(18)
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. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Publication Date: 2021
Journal of Chemical Thermodynamics (10963626)158
In this study, the densities of the pseudo-binary systems of water and the deep eutectic solvent, 1 choline chloride + 4 phenol were measured and reported for the first time in literature, and a comprehensive investigation on the various volumetric properties was carried out. Nine mixtures, with different compositions of water, were prepared. The densities of the prepared mixtures, as well as pure water and pure deep eutectic solvent (DES) were measured within a temperature range of 293.15–333.15 K at atmospheric pressure. Various volumetric properties, such as excess molar volumes and isobaric volume expansions, partial molar volumes and excess partial molar volumes were calculated for the investigated compositions. Furthermore, partial molar volumes and excess partial molar volumes at infinite dilution were estimated for water and the DES. By analysing the calculated properties, the interstitial accommodation effect was suggested for the investigated mixtures. The stronger tendency of water to be solvated in the mixture, as compared to the DES, was observed for all investigated temperatures. This suggests that, most probably, hydrogen bonds in the investigated mixtures are established in a manner in which water molecules are located at central positions, surrounded by the DES pseudo-molecules. © 2021 Elsevier Ltd
Publication Date: 2020
Journal of Molecular Liquids (18733166)307
Deep eutectic solvents (DESs) are a recently introduced class of sustainable solvents, being studied by many researchers in various fields. Because of the vast potential applications of DESs, it is necessary to have their physical properties available. Surface tension is an important physical property which has significant effects on permeability and bubbling, and hence in the design of processes. Up to date, there is no general model available in open literature for estimating the surface tension of DESs. In this study, for the first time, a general, simple, easy-to-use, and accurate correlation is proposed for the estimation of the surface tension of DESs at different temperatures. The correlation was developed based on a large data bank, including 553 data points, from 112 DESs having different natures. The model results were investigated by different statistical analyses and it was found that the correlation is not biased and shows normal behavior. The value of calculated overall AARD% of the model is 8.8%. The proposed model was compared to three general surface tension models in the literature and the comparison showed greater reliability and better agreement of the proposed model with respect to other literature models. © 2020 Elsevier B.V.
Publication Date: 2020
Molecules (14203049)25(7)
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. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Publication Date: 2020
Fluid Phase Equilibria (03783812)507
The goal of this study was to propose, a general, yet simple and accurate model for the estimation of the standard molar chemical exergies of various organic compounds, often used in the industries. With this goal in mind, for the first time in literature, the atomic contribution approach was considered, and the feasibility of adopting such a simple method to calculate chemical exergies was investigated. A large data bank, consisting of 4129 organic compounds from wide ranges of families, was gathered from the literature, and divided into training and test datasets. Upon investigating various functionalities, and optimizing using the training databank, two atomic contribution models were proposed to calculate the standard enthalpy and entropy of formation, from which, the standard molar chemical exergy of a compound is calculated. The AARD% value for estimating the standard molar chemical exergy of the entire database, consisting of both the training and testing datasets, was 0.64%, which shows not only the feasibility of applying the atomic contribution approach for the calculation of this property, but also high accuracy as compared to more tedious literature models. Since the proposed models require knowledge of only the chemical formula and the normal boiling point of the desired compound, it is indeed in line with our purpose of simplicity and generality, and can easily be incorporated into computer codes. Considering that it is also global and quite accurate, this model even has great potential to be used in energy and chemical-related software. © 2019 Elsevier B.V.
Publication Date: 2020
Fluid Phase Equilibria (03783812)521
Deep eutectic solvents have aroused a great level of interest in recent years. In this regard, a simple model is presented for the calculation of viscosities of a wide range of deep eutectic solvents. Based on a databank covering 156 deep eutectic solvents of different natures, a straightforward, simple, accurate, and global correlation is proposed. This model, which covers wide ranges of temperatures, requires the critical pressure, critical temperature, and one reference viscosity data as its input parameters. Since the model has one set of global constants, it can be used for any DES. Apart from this correlation, a second approach was also taken in this study, which was to obtain the constants of the Vogel-Fulcher-Tamman (VFT) model for all of the investigated DESs. With this approach, the constants are individually fit to each DES, therefore, no physical properties are required as input. The average absolute relative deviation errors of 10.4% and 1.7% for the proposed model and the VFT model, respectively, are compared to literature models. The results indicate that the proposed correlation, in addition to its acceptable accuracy and simplicity, is a general model for the estimation of the viscosities of different-natured deep eutectic solvents. © 2020
Publication Date: 2020
Journal of Chemical Thermodynamics (10963626)150
In the present study, the volumetric behaviour of mixtures of (Ethaline + ethanol) was investigated for the first time. Ethaline, which is the mixture of choline chloride and ethylene glycol at a molar ratio of 1:2, is among the most well-known Deep Eutectic Solvents (DESs). Because of its rather low viscosities as compared to many DESs, it has gained the interest of researchers for use in different applications. In this work, isobaric densities of the mixtures of Ethaline + ethanol were measured and presented over the entire mixture concentration range within the temperature range of (293.15–333.15) K. Using the measured data, excess molar volumes of the mixtures were calculated and analysed. The negative values of excess molar volumes suggested the stronger interactions of hydrogen bonds in the mixture with respect to the pure states of its constituents. Additionally, partial molar volumes and excess partial molar volumes, as well as the corresponding values at infinite dilution, were calculated and analysed. It was found that both Ethaline and ethanol have the tendency to be solvated by the mutual unlike-molecule in the mixture, and this tendency is stronger for Ethaline. It is also suggested that within the established hydrogen bond networks in the mixture, the Ethaline pseudo-molecules are probably located at central positions, being mostly surrounded by ethanol molecules. © 2020 Elsevier Ltd
Haghbakhsh, R.,
Peyrovedin, H.,
Raeissi, S.,
Duarte, A.R.C.,
Shariati, A. Publication Date: 2020
Entropy (10994300)22(4)
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. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
Publication Date: 2020
Journal of Molecular Liquids (18733166)307
Nowadays, Deep Eutectic Solvents (DESs) are considered as green solvents in many research fields. Knowledge of the physical properties of DESs can pave the way to their useful utilization. One of the important properties of a DES is its heat capacity. Besides experimental measurements, which are expensive and time consuming, it is vital to have models for the estimation of heat capacities. A generalized model is presented to estimate the heat capacities of DESs. In this regards, 505 isobaric heat capacity data points, over the wide temperature range of 278.15 to 363.15 K, from 28 DESs of different natures were used to develop the model. Up to date, this is the largest data bank investigated for isobaric heat capacities of DESs in the open literature. Based on this database, a simple, straightforward, yet precise correlation was developed to estimate the heat capacities of DESs as a function of temperature, molecular weight, critical pressure, and acentric factor. The absolute average relative deviation (AARD%) of the proposed correlation for all of the investigated data points is 4.7%, which shows that the calculated results are quite promising for such complicated systems. To the best of our knowledge, up to now, there are no generalized models for estimating the heat capacities of deep eutectic solvents, and this is the first model in the literature, therefore, it can be of great value to researchers in the field. The model has even further significance when considering that it is actually needless of any experimental data as input. This is because the physical properties used in the correlation to identify the substance are themselves obtained by group contribution methods. In practice, the only required information to use this simple and predictive model is the chemical structure. © 2018
Publication Date: 2020
Journal of Chemical Thermodynamics (10963626)147
In this study, a comprehensive investigation on the volumetric properties of mixtures of a deep eutectic solvent (DES) and an alcohol was carried out. Ethaline (1 choline chloride + 2 ethylene glycol), which is one of the more common DESs, and methanol were chosen to make the desired mixtures. Nine different mixture compositions of Ethaline + methanol, over the full range of concentrations, were prepared. Densities of pure Ethaline and methanol, and also nine mixture samples, were measured at five temperatures from 283.15 to 323.15 K and atmospheric pressure. The excess volumes of the investigated mixtures were calculated and modeled with the Redlich-Kister model. All of the calculated values of excess volumes were negative, which probably shows stronger hydrogen bond contributions and better interstitial accommodations in the mixtures with respect to the pure states. Furthermore, other volumetric properties, such as partial molar volumes and excess partial molar volumes at each composition and at infinite dilution were calculated. By analyzing the calculated volumetric properties, the greater tendency of Ethaline for solvation in the mixture was observed as compared to methanol. Therefore, it is suggested that probably the hydrogen bond networks in the mixture are created in a pattern in which mostly Ethaline occupies central positions, being surrounded largely by methanol molecules. © 2020 Elsevier Ltd
Publication Date: 2020
Journal of Chemical and Engineering Data (00219568)65(8)pp. 3965-3976
Reports on deep eutectic solvents (DESs), as a new category of green media following ionic liquids (ILs), are increasingly emerging in the literature. Because of the dramatically large number of DESs that will be introduced in the future, it would require much time and expense to experimentally measure their refractive indices. Therefore, proposing a global model that has the ability to estimate the refractive indices of various types of DESs is vital. In this study, it was the goal to develop an accurate, global, simple, and easy-to-use model for estimating the refractive indices of large numbers of DESs having different natures. With this idea in mind, a large up-to-date data bank for DESs was collected, consisting of 1203 data points from 153 different DESs, to develop the model. The proposed model requires critical pressure, molecular weight, and acentric factor as the input parameters. These parameters are calculated by suggested procedures. Therefore, in essence, to be used, the refractive index model does not need any experimental data. The overall absolute average relative deviation, AARD%, of the proposed model for all of the investigated DESs is 1.03%, which indicates high accuracy, as well as generality, for the estimation of the refractive indices of DESs. Copyright © 2020 American Chemical Society.
Haghbakhsh, R.,
Peyrovedin, H.,
Raeissi, S.,
Duarte, A.R.C.,
Shariati, A. Publication Date: 2020
International Journal of Refrigeration (01407007)113pp. 174-186
Energy shortage and environmental pollution are among the most serious challenges facing mankind. The utilization of efficient and green solvents has great urgency, if true action is to be taken to alleviate these issues. The Deep Eutectic Solvents (DESs) were recently introduced as sustainable solvents with special characteristics. These novel solvents have very low vapor pressures and can be “designed” for desired properties through the engineered selection of appropriate hydrogen-bond donors and acceptors. Research is necessary to investigate the feasibility of applying DESs in various industrial applications, including absorption refrigeration systems. Since the coefficient of performance (COP) and the exergetic coefficient of performance (ECOP) of an absorption refrigeration system depend highly on the properties of the absorbent and refrigerant, selecting a proper DES with particular attention to its physical properties, can dramatically affect its efficiency. In this study, three DESs were investigated as potential absorbents, consisting of Reline (1 Choline chloride + 2 urea), Ethaline (1 Choline chloride + 2 ethylene glycol) and Glyceline (1 Choline chloride + 2 glycerol), with ammonia as the refrigerant. A modified SRK-NRTL model was used to estimate the physical and thermodynamic properties of the DESs and their mixtures with ammonia. The COPs and ECOPs of the absorption refrigeration cycles were calculated within wide ranges of absorber and regenerator temperatures. The results were compared to literature systems, including ammonia/water and ammonia/ionic liquids cycles. The performances based on energy and exergy analyses showed that ammonia/DES working fluids have the potential to be used in such cycles. © 2020
Publication Date: 2020
Fluid Phase Equilibria (03783812)503
Ionic Liquids (ILs) are designer solvents with very unique properties, resulting in the exponential growth of publications in the field. Speed of sound can be considered as one of the important thermodynamic properties of compounds, since many other thermophysical properties can be determined using the speed of sound, including density, isentropic compressibility, isothermal compressibility, thermal conductivity, heat capacity, Joule-Thomson coefficient, and bulk modulus. Since ILs are designer solvents, much of their properties are unknown, hence, knowledge of their speeds of sound can be quite valuable. Two new straightforward models, with totally different approaches and input parameters, are proposed to estimate the speed of sound in ILs: an atomic contribution model, which only considers the atoms as building blocks to create the molecule and estimate its speed of sound; and a novel correlation. The atomic contribution model is the first which requires knowledge of only the chemical formula of the IL, making it needless of, not only any physical properties, but also the molecular structure which group contribution methods do require. This is considerable progress, as it will cover the majority of future ILs, which have not even been synthesized, and it does not have the ambiguities and difficulties of conventional group contribution (GC) methods for such complex structures. The further notable progress is its easy incorporation into computer programs, which is a serious setback with GC models. However, while being very straightforward and easy-to-use, it is more global than literature models. In addition to the atomic contribution method, a novel empirical correlation is proposed, with a new perspective. Both proposed models are quite reliable, while being very simple, and general. © 2019
Publication Date: 2019
Journal of Environmental Chemical Engineering (22133437)7(6)
Nowadays, environmental issues and the energy crisis are among the most important challenges to researchers. The necessity of increasing the energy efficiency of industrial processes is vital. If this efficiency increase is additionally done by using sustainable components, environmental issues are also alleviated. Deep eutectic solvents (DESs) are a new generation of green solvents with unique properties. This has led to the exponential growth of research in the field, oriented towards green chemistry and green processing. This study investigates the feasibility of utilizing DESs in the petroleum industries by considering the case study of capturing CO2 from natural gas, resulting in a purified gas with greater heating value. The idea is to utilize the DES as an absorbent, in place of the conventional Selexol. The pressure swing absorption process was simulated for two different DES, namely Reline and Glyceline. The purity of the methane stream was 89.1% when using Selexol, and 90.1% and 79.6% for Reline and Glyceline, respectively. The carbon dioxide stream showed even greater purity differences when DESs were used (98.3%, 98.4% and 94.9% CO2 when using Reline, Glyceline, and Selexol, respectively). Furthermore, energy and exergy analyses were carried out on the proposed plants. While the overall duties were less for the plants using DESs (-51.27, -11.13, and 15.17 and kW for Reline, Glyceline, and Selexol, respectively), the exergy destructions were not (146.78, 165.64, 96.54 kW for Reline, Glyceline, and Selexol, respectively). The results indicated the feasibility of using DESs as potential physical solvents in such industries. © 2019 Elsevier Ltd.
Publication Date: 2019
Physics and Chemistry of Liquids (10290451)57(3)pp. 401-421
In this study, a new correlation is proposed for estimating 1-alkyl-3-methylimidazolium ionic liquid (IL) viscosities at different temperatures and atmospheric pressure. Since ILs are rather novel, many of their physical properties are still unavailable. Because of this limitation, the aim of this work was to propose a correlation with a new insight and approach, which requires a minimum number of physical properties as input parameters. In addition to minimal dependency on physical properties, further goals in the development of the model were generality, ease-of-use, simplicity and high accuracy. A total of 2073 literature viscosity datapoints at different temperatures for 38 different ILs were used and a correlation was developed which satisfied the above-mentioned goals. The IL viscosity models of Lazzús and Pulgar-Villarroel, and Gardas and Coutinho were compared to the proposed correlation. More reliable results were obtained by the proposed relation in comparison to literature models. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
Publication Date: 2019
Journal of Chemical and Engineering Data (00219568)64(9)pp. 3811-3820
In this work, the selective separation of toluene from mixtures of toluene + heptane or toluene + hexane was investigated using the newly emerging family of solvents, namely, deep eutectic solvents (DESs), as the extracting agent. The liquid-liquid equilibria (LLE) of these systems were measured at a temperature of 303.2 K and a pressure of 85 kPa. The DESs considered were made of choline chloride as the hydrogen bond acceptor (HBA) and phenol as the hydrogen bond donor (HBD), at the two different HBA-HBD molar ratios of 1:3 and 1:4. The experimental liquid-liquid equilibrium data, along with the selectivities and distribution coefficients, were reported for each set of equilibrium data and also compared with other ternary systems in the literature containing toluene + heptane or toluene + hexane and various solvents. The experimental results revealed that the studied DESs in this work have the potential to be utilized in the separation of toluene from either hexane or heptane at low concentrations of toluene. The experimental LLE data was also modeled using the nonrandom two-liquid (NRTL) model. The values of the root-mean-square deviations of the NRTL results with respect to experimental values indicated acceptable agreement, suggesting NRTL as a potential model for such systems. © 2019 American Chemical Society.
Haghbakhsh, R.,
Bardool, R.,
Bakhtyari, A.,
Duarte, A.R.C.,
Raeissi, S. Publication Date: 2019
Journal of Molecular Liquids (18733166)296
Deep eutectic solvents (DESs) mostly comply with the principles of green chemistry. Therefore, they are being widely investigated due to their great potential for a variety of applications in the industries. However, it is necessary to have accurate (thermo)-physical property information on any solvent before it can pave its way into the industries. Among such properties, density as a function of temperature is one of the most important. In this study, a simple, accurate and global correlation is proposed to estimate the densities of a large number of DESs of different natures. The proposed model is a function of the critical temperature, critical volume and acentric factor of the DES, as well as the temperature of the system. In this way, the model is capable of accurately predicting the densities of DESs without the need for any reference temperature density data, in contrast to most of the literature models that do require a reference data point. The average relative error for 149 DESs of different natures was estimated to be 3.12% by the proposed model, indicating its accuracy compared to previous models. © 2019 Elsevier B.V.
Publication Date: 2018
Fluid Phase Equilibria (03783812)470pp. 193-202
Deep eutectic solvents (DESs) make up a most-recent category of ‘green’ solvents with a potentially promising future. Insignificant vapor pressure, biodegradability, low cost, task-specific engineering, and high absorption for gases such as CO2 are the most important characteristics of most DESs. To apply DESs in various industries, knowledge of their physical properties is vital. Since the viscosity of a DES is a strong function of temperature, as well as the ratio of the hydrogen bond donating and accepting components, to estimate the viscosity behavior, a model based on sound theory is proposed in this study, i.e., the free volume theory. Since DESs are strongly associating components, this theory is enriched by using associating equations of state, namely CPA and PC-SAFT. In this study, a large density and viscosity databank of 27 DESs of different nature, also with varying molar ratios of the hydrogen bond donor and acceptor, were used to propose the model. In this way, a global model is presented for the first time to estimate the viscosities of DESs. The pseudo-component approach, with a 2B association scheme, was considered for the DESs. Both the CPA and the PC-SAFT EoSs, coupled with the free volume theory, showed reliable results, with average AARD% values in viscosity for all of the investigated DESs equal to 2.7% and 2.7%, respectively. Furthermore, both models reliably showed the trend of nearly logarithmic increase in DES viscosity with decreasing temperature. Also, both models accurately estimated the viscosity behavior of the DESs by not only changing the molecular nature of the hydrogen bond donor with a fixed hydrogen bond acceptor, but also at all of the various molar ratios investigated. © 2017 Elsevier B.V.
Publication Date: 2018
Journal of Chemical Thermodynamics (10963626)124pp. 10-20
Deep Eutectic Solvents (DESs) have been introduced recently as a new generation of green solvents. DESs have great potential to be used in different fields and applications, and so, it is important to have information on the properties of DESs and their mixtures. Up to now, the volumetric properties of only aqueous mixtures of DESs have been investigated. In this study, we measured the densities of pseudo-binary mixtures of methanol and choline chloride + urea (1:2) (reline) at atmospheric pressure over the temperature range of 293.15-323.15 K. Based on the measured density data, excess molar volumes of the mixtures were calculated. All of the excess molar volumes had negative values, which show the stronger solvation interactions of the mixture molecules compared to the interactions within pure reline or methanol. Furthermore, the volumetric properties of partial molar volume, excess partial molar volume, partial molar volume at infinite dilution, excess partial molar volume at infinite dilution, and isobaric volume expansion were calculated. By comparing the excess partial molar volumes at infinite dilution of reline and methanol, it is concluded that each prefers to be surrounded by the other, and this tendency is stronger for reline molecules. © 2018
Publication Date: 2018
Journal of Molecular Liquids (18733166)272pp. 731-737
Deep Eutectic Solvents are complex solvents whose properties are challenging to understand and to model. In this study, the Prigogine–Flory–Patterson (PFP) theory was used, for the first time in literature, to estimate excess molar volumes of different systems consisting of Deep Eutectic Solvents (DESs). Twelve different systems, consisting of Ethaline + DMSO, Ethaline + water, Reline + water, Reline + methanol, Reline + ethanol, Glycine + water, Glycine + methanol, Glycine + ethanol, Glycine + isopropanol, Maline + water, Tegaline + water, and Glucoline + water were investigated in the full range of concentrations and within wide ranges of temperature, at atmospheric pressure. Excess molar volume is a complicated thermodynamic property because it depends not only on the shape, size, and chemical nature of each pure component in the mixture, but also on all of the binary and higher order interactions of the components in the mixture. The Prigogine–Flory–Patterson theory is one of the very few theoretical models for estimating excess molar volume. Because of the thermodynamic background of the PFP theory, which divides the excess molar volume into three different molecular interaction contributions, the results of this model in mixtures involving DESs can be valuable for a rough interpretation of the molecular interactions of such complex mixtures at a microscopic scale. In order to avoid the correlative aspect of the PFP theory, a generalized relation was proposed for the interaction parameter of the theory covering all temperatures. The resulting model, with a total AARD% of 14.6% and agreement between the predicted trends and the corresponding experimental trends, indicated the capability and suitability of the PFP theory in estimating excess molar volumes of such complex and non-ideal mixtures consisting of DESs. © 2018
Publication Date: 2018
Fluid Phase Equilibria (03783812)472pp. 39-47
In this study, the deep eutectic solvent of choline chloride/urea, also known as Reline, was synthesized. Mixtures of Reline with ethanol were prepared covering the entire concentration range, and their densities were determined experimentally. Together with pure Reline and pure ethanol, this made a total of eleven systems, whose densities were measured over the temperature range of 293.15–333.15 K at pressure of 100 kPa. The volumetric properties of interest in the calculation of other derivative thermodynamic properties were determined for all of the investigated mixtures and temperatures. This included the correlation of density to temperature, as well as the excess molar volumes, partial molar volumes, partial molar volumes at infinite dilution, excess partial molar volumes, excess partial molar volumes at infinite dilution, and isobaric volume expansions. The excess molar volumes had negative values at all concentrations and temperatures. This led us to propose a possible molecular arrangement of the hydrogen bond network, placing Reline mainly in central positions, with the preference to be surrounded by ethanol molecules. © 2018 Elsevier B.V.
Publication Date: 2018
Journal of Chemical and Engineering Data (00219568)63(4)pp. 897-906
The thermodynamic modeling of a new generation of solvents, deep eutectic solvents (DESs) is investigated. Because hydrogen bonding is a dominant molecular interaction, the cubic plus association (CPA) equation of state (EoS) was chosen for modeling. This is the first study to model DES density and carbon dioxide solubility using CPA. Fifteen different DESs were chosen which have density data, as well as CO2 solubility data, available in the literature over wide temperature and pressure ranges. To date, this is the most extended and global databank of DESs which has been employed in relation to a complex EoS. The density data were used to optimize the CPA parameters. The CPA EoS proved to be capable of accurately modeling pure DES densities. The validity of the optimized CPA parameters was further validated with literature density data of mixtures of DES + water, which were estimated successfully by a purely predictive procedure. To calculate CO2 solubility in DES, all the possible association schemes of CO2 were investigated. It was concluded that the inert (no-association) scheme for CO2 was the most accurate (AARD% = 6.2), while at the same time being the simplest with fewer fitting parameters. The induced association (solvation) scheme (AARD% = 7.1) is also suitable. © 2017 American Chemical Society.
Publication Date: 2018
Journal of Molecular Liquids (18733166)250pp. 259-268
In this study, the thermodynamic modeling of SO2 solubilities in 14 Deep Eutectic Solvents (DESs) of different nature was investigated for the first time in literature. This is a challenging mixture to model. The thermodynamic modeling approach of γ − ϕ for vapor-liquid equilibria was used. The Cubic Plus Association Equation of State (CPA EoS) was used to represent the vapor phase and the NRTL and UNIQUAC models were both investigated for the liquid phase. The DESs were considered as pseudo-components and their physical properties calculated. Both the CPA-UNIQUAC and CPA-NRTL models showed good agreement with experimental values, with total AARD% of 2.9% and 3.1%, respectively. CPA-UNIQUAC shows slightly better results, while CPA-NRTL is a simpler model. In addition to the γ − ϕ approach, the ϕ − ϕ approach was investigated for all of the systems. However, the results were not reliable, even when incorporating binary interaction parameters as adjustable parameters in the model. © 2017 Elsevier B.V.
Publication Date: 2018
Chemical Engineering Communications (00986445)205(7)pp. 914-928
In this study, the goal was to derive a new purely predictive model to obtain binary interaction parameters based on intermolecular theories. The Lorentz–Berthelot and Halgren HHG molecular combining rules were coupled with the vdw1 mixing rule to derive the new equations for binary interaction parameters. These equations were used with the PR and ER EoSs to calculate the vapor–liquid equilibria of 14 binary mixtures of nitrogen with either methane, ethane, propane, iso-butane, n-butane, iso-pentane, n-pentane, n-hexane, n-heptane, n-octane, n-nonae, n-decane, n-dodecane, or n-tetradecane over wide ranges of temperature and pressure. To increase the accuracy for all of the investigated systems, we have additionally suggested a new correlative mode for the proposed equations. For some of the systems, the proposed predictive equations enhance the accuracy of vapor–liquid equilibria predictions up to three times in comparison to the case where binary interaction parameters are set to zero. © 2018, © 2018 Taylor & Francis.
Publication Date: 2018
Journal of Molecular Liquids (18733166)249pp. 554-561
Deep Eutectic Solvents (DESs), as recently introduced green solvents, are interesting for different fields and applications. Most of the known DESs have high viscosities, which change dramatically with temperature. Therefore, the viscosity of a DES is most often one of the vital physical properties which must be known accurately. Because of the strong non-ideal interactions between the constituents, as well as the dramatic changes of DES viscosity with temperature, modeling and predicting the viscosities of DESs over wide ranges of temperatures is very challenging. In this study, a viscosity approach is used and implemented into two advanced association equations of state for different families of deep eutectic solvents. The cubic plus association (CPA) and the perturbed chain-statistical associating fluid theory (PC-SAFT) equations of state (EoSs), which are two powerful models to handle associating compounds, have been coupled with the friction theory, which is itself among the successful theoretical viscosity models of literature. Twenty-seven different types of DESs, for which density and viscosity data are available in open literature, were considered. A large density databank, consisting of 590 density data over wide ranges of temperatures and pressures, together with a large viscosity databank covering 253 viscosity data over wide ranges of temperatures at atmospheric pressure were collected. The resulting friction theory models with the CPA and PC-SAFT EoSs were checked against experimental data and their deviations were found to be the same and equal to 4.4%. Such accuracy showed the promising capability of both models. By changing the hydrogen bond donor types for a fixed hydrogen bond acceptor, the accuracies of the models were also shown to be good with respect to experimental values. In addition, both models perfectly followed the trends of changing ratios of hydrogen bond donors to hydrogen bond acceptors. The viscosity-temperature trend of the different DESs was also successfully modeled. © 2017
Publication Date: 2017
Journal of Molecular Liquids (18733166)236pp. 214-219
In this study, a new simple, general, accurate and easy-to-use correlation has been developed for estimating the thermal conductivities of pure ionic liquids (ILs) over a wide range of temperatures at atmospheric pressure. In addition to the abilities mentioned, a further goal of this work was to develop a thermal conductivity correlation which does not require, as input parameters, any other physical properties, once a single thermal conductivity data point is available. This can be a valuable advantage, especially in the field of ILs for which many physical properties are unavailable. The new correlation has been proposed based on 378 thermal conductivity temperature data points from 44 different IL types. The proposed correlation, in comparison to two well-known and commonly used group contribution models and one literature correlation, shows much higher accuracy with respect to experimental values. Calculations covering all of the investigated ILs in this work resulted in AARD% values of 1.0%, for the proposed model. It is also more widely applicable, as indeed, it can estimate IL thermal conductivities with a very simple formula and without the need for other physical properties, even molecular weight and molecular structure. © 2017
Publication Date: 2017
Industrial and Engineering Chemistry Research (15205045)56(8)pp. 2247-2258
In this study, the behaviors of viscosities of nine ionic liquids (ILs) over wide ranges of pressures and temperatures were determined. The investigated ILs belonged to the three imidazolium-based families of tetrafluoroborate, hexafluorophosphate, and bis[(trifluoromethyl)sulfonyl]imide. The two well-known cubic equations of state (EoS's) of Peng-Robinson (PR) and the Soave-Redlich-Kwong (SRK), as well as the two more-sophisticated EoS's of cubic plus association (CPA), and perturbed-chain statistical associating fluid theory (PC-SAFT), were each coupled with two well-known theoretical viscosity models, namely the friction theory and the free volume theory. Calculated results showed that the free volume model, coupled with PC-SAFT, has superior results in comparison to the free volume model with the CPA EoS. For the viscosity model of free volume, the studied cubic EoS's did not give accurate results. When the friction model was used, the PC-SAFT EoS once more showed better accuracy than the CPA EoS; however, the CPA results in this model were quite close to that of the PC-SAFT, while the differences were great with the free volume model. One of the remarkable conclusions for the friction theory model was the unexpectedly reliable results that it gave with the cubic EoS's. This suggests that when highly accurate results are not crucial, this combination can be the best choice because of the significantly greater simplicity of a cubic EoS over an association EoS. © 2017 American Chemical Society.
Publication Date: 2016
Journal of the Taiwan Institute of Chemical Engineers (18761070)58pp. 57-70
In this study, viscosity of nine members of alcohol group as the polar compounds in a wide range of pressure and temperature based on total number of 1090 viscosity set data have been investigated. Theoretical viscosity estimation models, such as free volume, Eyring's and friction theory were studied by coupling with common used and simple EoSs such as PR and SRK and also complicated and specific EoSs for polar and associating compounds such as CPA and PC-SAFT. In general using from CPA and PC-SAFT decrease the values of error for all of the viscosity models, but the effect of these equations of state is more impressive for the friction theory and can decrease the AARD% value about 3.8 times. In the free volume and Eyring's theories although decreasing the errors can be seen by CPA and PC-SAFT but this decreasing is not impressive like friction theory. All of the viscosity theories coupled with all of the equations of state investigated here can estimate with a good agreement viscosity-temperature Arrhenius like behavior of alcohols at constant pressure, but the EoSs have a great effect on the viscosity-pressure near to linear behavior of alcohols at constant temperature. © 2015 Taiwan Institute of Chemical Engineers.
Publication Date: 2016
Journal of Natural Gas Science and Engineering (18755100)32pp. 185-197
Owing to concerns associated with energy consumption and energy intensive methods in the chemical industries, the present study aims to investigate production of some downstream products of natural gas in a recuperative configuration. Accordingly, simultaneous production of dimethyl ether from methanol and syngas and also methyl formate from methanol is investigated in a catalytic heat-exchanger reactor assisted with water perm-selective membranes. Dimethyl ether synthesis from methanol and syngas are exothermic reactions supplying required energy for the methanol dehydrogenation reaction. Produced waters in both exothermic sides are eliminated from reaction media by permeation through the perm-selective membranes equipped on the inner and outer surfaces of the reactor. A feasibility study is implemented through a mathematical model based on mass and energy balance. Genetic algorithm as a powerful method in nonlinear optimization problems is applied to obtain optimum operating conditions. 97% methanol conversion to dimethyl ether, 66% methanol conversion to methyl formate and 17% hydrogen conversion are the advancements of the proposed thermally double-coupled double-membrane reactor working under optimum conditions. © 2016.
Publication Date: 2015
AIChE Journal (00011541)61(9)pp. 3094-3103
A new model, named the crossover-UNIQUAC model, has been proposed based on the crossover procedure for predicting constant-pressure liquid-liquid equilibria (LLE). In this manner, critical fluctuations were incorporated into the classical UNIQUAC equation. Coexistence curves were estimated for systems having a diverse range of asymmetries. These systems included the LLE of five different mixtures, composed of nitrobenzene with one of the members of the alkane homologous family (either pentane, octane, decane, dodecane, or tetradecane), as well as an extra system having a different chemical nature, namely the mixture of n-perfluorohexane and hexane, to further check the validity of the proposed approach. Using these nonideal mixtures, the validity of the new model was investigated within wide ranges, covering near-critical to regions falling far away from the critical point. The graphical trends, as well as the quantitative comparison with experimental data indicated the good agreement of the proposed model results with the experimental data. A maximum AARD% value of 3.97% was obtained in calculating molar compositions by the proposed model for such challenging systems covering noncritical, as well as critical regions. In addition, to show the strength of the proposed crossover approach to describe properties other than LLE, molar heat capacities were investigated for the system of nitrobenzene+dodecane. © 2015 American Institute of Chemical Engineers.
Publication Date: 2015
Fluid Phase Equilibria (03783812)403pp. 95-103
The heat capacities of pure ionic liquids (ILs) are among the thermophysical properties that are required for certain engineering calculations and designs. In this study, a simple correlation is presented for the prediction of the heat capacities of pure ionic liquids. This correlation is a temperature-dependent relation that uses temperature, molecular weight and the number of atoms (such as carbon, hydrogen, oxygen, nitrogen, etc.) in the structure of the IL as input parameters. A dataset of approximately 128 different ILs, consisting of 4822 data points, was used to develop and validate this general correlation, covering a temperature range from 190 to 663. K. Nearly three-quarters of the data were used for optimization and a quarter for validation. The resulting correlation gives good estimations for heat capacities, while having a number of advantages over previous literatures methods. These advantages include (a) being very simple; (b) not requiring any experimental data as input parameters; (c) being more global than previous literature models by having been constructed over a larger databank of ionic liquids; (d) being accurate. The average absolute relative deviation (AARD%) was calculated to be 5.8% for the optimization dataset, and 5.6% for the validation dataset. This is smaller than what is obtained for the literature atomic-contribution methods proposed by Farahani et al. and Sattari et al., with AARD% values of 14.2% and 6.6%, respectively, based on the validation dataset of this study. © 2015 Elsevier B.V..
Publication Date: 2015
Journal of Natural Gas Science and Engineering (18755100)22pp. 377-394
The paraffin group has a major role in the surface properties of hydrocarbon reservoirs. Because of its importance, this work reports new experimental density data for binary mixtures of heptane+hexadecane at temperatures and pressures ranging from 313.15 to 393.15K, and 0.34 to 44.47MPa, respectively. Five compositions were investigated, consisting of pure heptane, pure hexadecane, and their binary mixtures at heptane mole fractions of 0.4296, 0.6932, and 0.8748. An Anton Paar vibrating-tube densimeter was used to measure the densities. The resulting density data were fit to a Tait-type equation, showing deviations of less than 0.12% in AAD%. Excess volumes were calculated from the experimental data and fit to the Redlich-Kister equation. In addition, partial molar volumes of the components at infinite dilution and excess partial molar volumes of the components at infinite dilution were calculated. The isobaric expansion and the isothermal compressibility were also driven from the Tait-type equation. © 2014 Elsevier B.V.
Publication Date: 2015
Journal of Solution Chemistry (00959782)44(8)pp. 1555-1567
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. © 2015 The Author(s).
Publication Date: 2015
Journal of Molecular Liquids (18733166)211pp. 948-956
Haghbakhsh, R.,
Konttorp, M.,
Raeissi, S.,
Peters, C.J.,
O'connell, J.P. Publication Date: 2014
Journal of Physical Chemistry B (15205207)118(49)pp. 14397-14409
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. © 2014 American Chemical Society.
Publication Date: 2014
Journal of Supercritical Fluids (08968446)92pp. 60-69
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. © 2014 Elsevier B.V.
Publication Date: 2014
Journal of the Taiwan Institute of Chemical Engineers (18761070)45(6)pp. 2888-2898
The already numerous industrial applications of alcohols is continuously growing to even higher significance. Accurate estimations of the physical properties of various alcohols within wide ranges of pressures and temperatures are necessary in the design and optimum operation of such processes. In this study, high-pressure liquid densities of the first six members of the normal alkanol family were predicted as a function of temperature and pressure. This was done using two different approaches: The computer method of support vector machine (SVM) and the thermodynamic model of Cubic Plus Association Equation of State (CPA EoS). A total of 2979 experimental data on alcohol density, also covering high pressure and high temperature conditions, were obtained from literature. The results of the calculations show that the value of AARD% for all of the 2979 data was 0.06% for the SVM computer model and 1.36% for the thermodynamic CPA model. © 2014 Taiwan Institute of Chemical Engineers.
Publication Date: 2013
Journal of Supercritical Fluids (08968446)77pp. 158-166
Engineers often demand the availability of easy correlations without difficult and time-consuming calculations. Up till now, there has been a lack of such correlations for mixtures of CO2 + ionic liquids. This work proposes a correlation to predict CO2 solubility in 27 common ionic liquids. The main advantages are its simplicity and minimal input data, namely temperature and pressure. The ionic liquids investigated ranged within a variety of families, having various anions and cations. Compared with the popular engineering models of Peng-Robinson (PR) and Soave-Redlich-Kwong (SRK), the present correlation is much easier to use, yet it is also more accurate (PR, SRK and the proposed model had AARD% values of 43.5%, 44.3% and 4.9%, respectively for a total of 3073 data), even when binary interaction coefficients of PR and SRK are optimized to experimental data (AARD% values of 17.2%, 16.9% and 4.9% for PR, SRK and the proposed model, respectively). © 2013 Elsevier B.V.
Publication Date: 2013
Fluid Phase Equilibria (03783812)342pp. 31-41
Nowadays due to wide applications of supercritical fluids (SCFs) technology in different industrial fields, solubility estimation of solid species in SCF is so important. In this work, two new correlations for the prediction of supercritical carbon dioxide (SC-CO2) density and solubility of 31 well known industrial compounds in the SC-CO2 are proposed. These correlations have been developed based on the sensitivity analysis and mathematically regression using 1240 SC-CO2 density data and 1012 solubility data of 31 solid compounds for the temperature range of 308-523K and pressure between 75 and 468bar. The proposed density and solubility models have been compared with the literature experimental data and also different models. The proposed SC-CO2 density correlation has better performance (lower AARD%) and higher density prediction ability at wider range of temperature and pressure respect to Jouyban et al. and Bahadori et al. density models. Also, more precisely prediction results of proposed solubility model respect to K-J and Chrastil models showed that the proposed model can be used as a reliable solubility model in industrial applications. © 2013 Elsevier B.V.
Publication Date: 2013
Thermochimica Acta (00406031)551pp. 124-130
In this study, a new approach for the prediction of density of pure hydrocarbons such as n-pentane, n-octane, n-decane, and toluene has been suggested. The available experimental data in the literature have been selected at high pressure (∼500 MPa) and high temperature (∼400 °C) conditions. The data are analyzed accurately using artificial neural networks and have been compared with different results obtained by various EOSs such as, PC-SAFT, SAFT, Peng-Robinson and SRK equations. The values of "Average Absolute Deviation Percent" for the densities of each material are calculated using artificial neural networks. These are 0.2 for n-pentane, 0.11 for n-octane, 0.66 for n-decane and 0.51 for toluene, which are substantially more accurate than those obtained with various EOSs. Finally, it has been shown that artificial neural network as an applicable and feasible instrument can be proposed to predict the density data for such materials with high accuracy. © 2012 Elsevier B.V. All rights reserved.
Adib, H.,
Haghbakhsh, R.,
Saidi, M.,
Takassi, M.A.,
Sharifi, F.,
Koolivand, M.,
Rahimpour, M.R.,
Keshtkari, S. Publication Date: 2013
Journal of Natural Gas Science and Engineering (18755100)10pp. 14-24
Fischer-Tropsch synthesis is a collection of chemical reactions that converts a mixture of carbon monoxide and hydrogen into hydrocarbons. In this study, application of FTS is studied in a wide range of synthesis gas conversions. Artificial neural networks (ANN) were used to predict the molar percentage of CH4, CO2 and CO in the Fischer-Tropsch process of natural gas and also genetic algorithm (GA) was applied to obtain the optimum values of operational parameters. The input parameters consist of a 3-dimensions vector which includes the reaction time, operating pressure and temperature and also the output was molar percentage of CH4, CO2 and CO. Topology and decision parameters have been calculated by trial and error and acceptable correlation coefficients (R2 = 0.94 for CH4, R2 = 0.93 for CO2 and R2 = 0.96 for CO) were obtained. Also the results obtained by sensitivity analysis represent that operation time has significant influence on molar percentage of CH4 as desired product with respect to other operational parameters. Finally the results justify that GA-ANN could be effectively used for FTS as a powerful estimation technique. © 2012 Elsevier B.V.
Keshtkari, S.,
Haghbakhsh, R.,
Raeissi, S.,
Florusse, L.J.,
Peters, C.J. Publication Date: 2013
Journal of Supercritical Fluids (08968446)84pp. 182-189
The high pressure vapor-liquid equilibria of binary mixtures of propylene and isopropyl alcohol were measured experimentally within a temperature range of 315-440 K and pressures up to 6 MPa, using a synthetic method. The experimental data were modeled using the cubic plus association (CPA) equation of state (EoS) by once considering and once not considering solvation between the inert and polar molecules in the mixture. Results indicated that taking solvation into account did not make a huge improvement in the accuracy of CPA for this particular system. In addition, the Soave-Redlich-Kwong (SRK) EoS, representing the widely-used engineering EoS family, was also compared to the CPA. Results showed that both the CPA and SRK perform well for this system in the pressure and temperature range investigated, however, the values of binary interaction coefficients required by SRK to approach the experimental data are much greater than for CPA. © 2013 Elsevier B.V. All rights reserved.
