Experimental CO2 Solubility Data Research Articles

Deep Eutectic Solvent + Water System in Carbon Dioxide Absorption.

In the present work, deep eutectic solvents (DESs) were synthesized in a one-step process by heating the hydrogen bond acceptors (HBAs) tetrabutylammonium bromide and tetrabutylphosphonium bromide, along with two hydrogen bond donors (HBDs) ethanolamine and N-methyldiethanolamine, which were mixed in certain molar ratios. This mixture was then mixed with water to form a DES + water system. The densities of the prepared DES + water systems were successfully measured using the U-tube oscillation method under atmospheric pressure over a temperature range of 293.15-363.15 K. The CO2 trapping capacity of the DES + water systems was investigated using the isovolumetric saturation technique at pressures ranging from 0.1 MPa to 1 MPa and temperatures ranging from 303.15 K to 323.15 K. A semi-empirical model was employed to fit the experimental CO2 solubility data, and the deviations between the experimental and fitted values were calculated. At a temperature of 303.15 K and a pressure of 100 kPa, the CO2 solubilities in the DES + water systems of TBAB and MEA, with molar ratios of 1:8, 1:9, and 1:10, were measured to be 0.1430 g/g, 0.1479 g/g, and 0.1540 g/g, respectively. Finally, it was concluded that the DES + water systems had a superior CO2 capture capacity compared to the 30% aqueous monoethanolamine solution commonly used in industry, indicating the potential of DES + water systems for CO2 capture.

Assessment of CO2-Oil swelling behavior using molecular dynamics simulation: CO2 utilization and storage implication

CO2 injection into petroleum reservoirs is an effective enhanced oil recovery (EOR) method that can increase the recovery of oil while reducing CO2 emissions into the atmosphere. To ensure successful implementation of CO2 EOR, a detailed understanding of reservoir fluid properties and the phase behavior of CO2-oil mixtures at different scales is required. The extent to which CO2 injection improves the oil recovery factor is heavily dependent on the swelling behavior of CO2-oil mixtures, which can be quantified by swelling factors. In this study, we model a CO2-oil swelling test using molecular dynamics (MD) simulations to calculate the swelling factors over a pressure range of 24.8 to 68 bar at a temperature of 303.15 K for an actual crude oil sample. The multicomponent molecular model of the oil is built using 1000 molecules of six hydrocarbons, based on the compositional analysis of the oil sample. CO2 molecules are then added to the system at several pressure steps, based on experimental CO2 solubility data, and the resulting swelling factors are compared to their corresponding experimental values. The results of this study demonstrate that the MD simulation model can be successfully used to investigate CO2-oil swelling behavior and accurately predict the swelling factors with a minor mean percentage error of 6%. Additionally, analysis of potential energy variations due to interactions between different molecules in the system under increasing pressures and CO2 mole fractions indicates that the swelling process is primarily controlled by changes in intermolecular forces between CO2-oil and oil-oil molecular pairs, while the effect of CO2-CO2 molecular potentials on oil swelling is minimal. This work highlights the ability of the MD simulation technique to model the complex phase behavior of CO2-oil mixtures and provides unique insights into the molecular-scale mechanisms of CO2 dissolution in oil and the resulting swelling phenomenon.

Novel hybrid QSPR-GPR approach for modeling of carbon dioxide capture using deep eutectic solvents.

In recent years, deep eutectic solvents (DESs) have garnered considerable attention for their potential in carbon capture and utilization processes. Predicting the carbon dioxide (CO2) solubility in DES is crucial for optimizing these solvent systems and advancing their application in sustainable technologies. In this study, we presented an evolving hybrid Quantitative Structure-Property Relationship and Gaussian Process Regression (QSPR-GPR) model that enables accurate predictions of CO2 solubility in various DESs. The QSPR-GPR model combined the strengths of both approaches, leveraging molecular descriptors and structural features of DES components to establish a robust and adaptable predictive framework. Through a systematic evolution process, we iteratively refined the model, enhancing its performance and generalization capacity. By incorporating experimental CO2 solubility data in varied DES compositions and temperatures, we trained the model to capture the intricate solubility behaviour precisely. The analytical capability of the evolving hybrid model was validated against an extensive dataset of experimental CO2 solubility values, demonstrating its superiority over individual QSPR and GPR models. The model achieves high accuracy, capturing the complex interactions between CO2 and DES components under varying thermodynamic conditions. The versatility of the evolving hybrid model was highlighted by its ability to accommodate new experimental data and adapt to different DES compositions and temperatures. The proposed QSPR-GPR model presented a powerful tool for predicting CO2 solubility in DES, providing valuable insights for designing and optimizing solvent systems in carbon capture technologies. The model's remarkable performance enhances our understanding of CO2 solubility mechanisms and contributes to sustainable solutions for mitigating greenhouse gas emissions. As research in DESs progresses, the evolving hybrid QSPR-GPR model offers a versatile and accurate means for predicting CO2 solubility, supporting advancements in carbon capture and utilization processes towards a greener and more sustainable future.

Solubility of carbon dioxide in promising methylimidazolium-based ionic liquids

One of the most pressing environmental concerns facing humanity today is the limitation of carbon dioxide emissions. In the field of natural gas sweetening, carbon capture is equally critical. CO2 solubility in three promising ionic liquids {1-Hexyl-3-methylimidazolium bis(trifluoro-methyl-sulfonyl) imide [HMIM][Tf2N], 1-Butyl-3-methylimidazolium dimethyl-phosphate [BMIM][DMP], and 1-Propyl-3-methylimidazolium (trifluoromethylsulfonyl)imide [PMIM][Tf2N]} was measured at (303.15, 323.15 and 343.15) K and pressures up to 1.4 MPa. The densities of the three ionic liquids were determined at atmospheric pressure (98.5 ± 0.8 kPa) and temperatures ranging from (293.15 to 343.15) K.The lowest Henry's Law constant (highest capacity) for CO2 was that of [HMIM][Tf2N] followed by [PMIM][Tf2N] and [BMIM][DMP]. [HMIM][Tf2N] also had a higher absorption capacity than Selexol/Genesorb 1753 and was second best only to 1-Octyl-3-methylimidazolium bis (trifluoro-methane sulfonyl) imide [OMIM][Tf2N] among all ionic liquids, based on solubility data published in the literature. Note that [BMIM][DMP] was also found to be among the best four ionic liquids according to the Henry's Law data collected from the literature.Three distinct mixing rules were used to correlate the experimental CO2 solubility data with the Peng-Robinson equation of state (PR-EoS) using the van der Waals one (vdW1), van der Waals two (vdW2), and the Wong-Sandler mixing rule along with the Non-Random Two-Liquid model (WS-NRTL). The average absolute deviations for vdW1, vdW2, and WS-NRTL mixing rules, when calculated for the three ionic liquid systems at the three temperatures, were 4.89 %, 0.82 %, and 0.84 %, respectively.

Experimental data and modeling of the CO2 solubility in 2-methylimidazole aqueous solution

CO2 capture plays a critical role in reducing carbon emissions. Novel chemical absorption media, such as imidazole aqueous solutions, have been extensively studied as potential candidates. In this work, new experimental data of CO2 solubility in 5–30 wt% 2-methylimidazole (2-MeIm) aqueous solutions at 293.15–313.15 K were measured. The Cubic-Plus-Association equation of state (CPA EoS) with the pseudo chemical reaction approach has been proposed to model the CO2 solubility in the 2-MeIm aqueous solutions. The CPA model can describe well the saturated vapor pressure (1.1%), liquid density (0.5%) and vapor–liquid equilibrium data (14%) of 2-MeIm aqueous solutions. Temperature dependent binary interaction parameters between 2-MeIm and CO2 are needed in order to satisfactorily represent the phase equilibrium data of the 2-MeIm-H2O-CO2 ternary systems (11%) in the temperature range of 293.15–393.15 K, which covers all the decarbonization process operation conditions. With the pseudo chemical reaction approach within CPA EoS, it is possible to distinguish the physical and chemical effects of CO2 solubility in chemical absorbents. This work provides the experimental and model basis for further research and application of the novel imidazole-based separation media for CO2 capture.

CO2 solubility modelling in Non-Precipitating aqueous solutions of potassium lysinate

Modelling of CO2 solubility in aqueous solutions of potassium lysinate (LysK) is mainly hindered by scarcity of experimental vapor–liquid equilibrium data and lack of chemical equilibrium constants associated to the reaction mechanism for the CO2/LysK/H2O system. Therefore, Kent-Eisenberg (KE) correlation stands out from the literature, being among the most used approaches for the description of the equilibrium CO2 partial pressure at different loadings. In this work, a Kent-Eisenberg-like approach has been developed, enhancing the empirical Kent-Eisenberg with Debye-Hückel activity coefficients in order to guide model calibration with reference to selected experimental data for CO2 solubility in 33.1 and 33.5 %w/w aqueous LysK solution; moreover, the KE edition provides an estimation of the missing equilibrium constants. This information has been embedded in a first thermodynamically sound and predictive Deshmukh-Mather (DM) model (average absolute deviation equal to 7 %) validated against additional experimental data in a wide temperature and concentration range.

Enrichment in CO2 Absorption by 2-Methyl Piperazine-Activated Tertiary Amines, Physical Solvents, and Ionic Liquid Systems.

One of the ever-demanding research fields is the development of new solvents with better properties for mitigation of CO2 compared to existing solvents. This work reports the measurement and modeling of CO2 solubility in newly proposed aqueous solvent blends of 2-methyl piperazine with N-methyldiethanolamine (MDEA), sulfolane (TMSO2), and 1-butyl-3-methyl-imidazolium acetate ([bmim] [Ac]). The operating temperature and CO2 partial pressure conditions chosen were 303.2–323.2 K and 2–370 kPa, respectively. Along with this, qualitative 13C NMR and FTIR analysis were also performed to consider the proposed reaction scheme. The experimental vapor–liquid equilibrium data were modeled by a modified Kent–Eisenberg equilibrium model. The equilibrium constants associated with 2-methyl piperazine (2-MPZ) and [bmim] [Ac] deprotonation and carbamate formation reactions were regressed to fit the experimental CO2 solubility data. In addition, the CO2 cyclic capacity and heat of absorption were evaluated for the aq (MDEA + 2-MPZ) blend.

Experimental investigations and the modeling approach for CO2 solubility in aqueous blended amine systems of monoethanolamine, 2-amino-2-methyl-1-propanol, and 2-(butylamino)ethanol.

In this work, new CO2 solubility data on three types of aqueous amine blends were reported to complement existing databases. The experiments were conducted at temperatures of 313K (absorption condition) and 363K (desorption condition). The effect of the MEA concentration on the CO2 solubility in several amine blends at low CO2 partial pressure (8 to 50.65kPa) were studied in this work, including 0.1, 0.3, 0.5mol/L MEA + 2mol/L AMP; 0.1, 0.3, 0.5mol/L MEA + 2mol/L BEA; and 0.1, 0.3, 0.5mol/L MEA + 1, 2mol/L AMP + 1, 2mol/L BEA. Besides, an additional group of equilibrium CO2 solubility data were conducted at 298K in order to estimate the heat of CO2 absorption of the blended solvents at a temperature range from 298 to 313K. A new simplified Kent-Eisenberg model was developed for the predictions of blended solvents, and a multilayer neural network model with Levenberg-Marquardt backpropagation algorithm was developed upon five hundred reliable published experimental data. The predictions from two methods are both in good agreement with the experimental CO2 solubility data.

Prediction of CO2 solubility in potential blends of ionic liquids with Alkanolamines using statistical non-rigorous and ANN based modeling: A comprehensive simulation study for post combustion CO2 capture

Equilibrium CO2 solubility data plays a pivotal role in the process design of the post-combustion CO2 capture Unit. In the current study, statistical non-rigorous models are developed to predict the solubility of carbon dioxide (CO2) in different aqueous blends of ionic liquids (ILs) and blends of ILs with alkanolamines, ethanol, etc. These correlations are utilized to estimate the liquid phase CO2 loading as a function of CO2 partial pressure at different temperature conditions. The correlations can predict CO2 solubility in the liquid phase of different (ILs + alkanolamine + water/ethanol) in the temperature and CO2 partial pressure range of (298–353) K and (50–6200) kPa respectively. The CO2 mole fraction in the liquid phase pertaining to 19 different solvent formulations is considered in the range of (0–0.487). It has been found that there is a good agreement between the results of the proposed models and reported experimental data of CO2 solubility. In addition to this, the predictability of artificial neural network (ANN) for CO2 solubility is also tested for 22 systems of ionic liquid blends with amines. The main advantages associated with these proposed models are their underlying simplicity and minimal input data, namely temperature and pressure.

Experimental Measurements of CO2 Solubility in Aqueous MgCl2 Solution at Temperature between 323.15 and 423.15 K and Pressure up to 20 MPa

Experimental CO2 solubility data in brine at high temperatures and pressures are important for CO2 capture and storage (CCS) applications. Many data have been acquired in single-salt aqueous solutions such as NaCl, CaCl2, and Na2SO4. CO2 solubility data in aqueous solutions containing MgCl2 are extremely scarce. In this work, new experimental data of CO2 solubility in MgCl2 solutions were acquired. Thirty-three experimental points of CO2 solubility have been reported in an original range of pressure (1.5 to 20 MPa), temperature (323.15, 373.15, and 423.15 K), and salinity (1, 3, and 5 mol/kg). Measurements were made using the potentiometric titration method. Results show that the CO2 solubility increases with the evolution of pressure and decreases with the evolution of MgCl2 concentrations. A discussion about the salting-out effect on MgCl2 solutions is made, and a comparison is proposed on the same effect in aqueous systems containing calcium chloride.

Experimental investigations and developing multilayer neural network models for prediction of CO2 solubility in aqueous MDEA/PZ and MEA/MDEA/PZ blends

AbstractIn this research, a new set of experimental data for CO2 solubility in aqueous blended amine solvents were investigated experimentally over the CO2 partial pressure range from 8 to 100 kPa at 40 °C and were compared with the benchmark aqueous 30 wt.% MEA solution. This work developed two multilayer neural network models named models A and B, for predicting the CO2 solubility in various aqueous blended amine solvents including 36 wt.% MDEA + 17 wt.% PZ, 24 wt.% MDEA + 26 wt.% PZ, and 6 wt.% MEA + 25 wt.% MDEA + 17 wt.% PZ. Models A and B were developed by using Levenberg–Marquardt back propagation algorithm with 427 and 301 of reliable experimental data sets gathered from the published data, respectively. The results indicate that the high accuracy prediction of the CO2 solubility in Methyldiethanolamine/Piperazine (MDEA/PZ) blends could be obtained by the network developed by Tan‐sigmoid transfer function with two hidden layers consist of eight and four neurons, while the network developed by Tan‐sigmoid transfer function with three hidden layers consist of 20, 10, and five neurons provided the highest accuracy for predicting the CO2 solubility in MEA/MDEA/PZ blends comparing to other model structures. The comparison results show that the neural network modeling provided more closer predictions to the experimental results than the simulator and other thermodynamic models when predicting the CO2 equilibrium solubility in blended amine solvents. © 2021 Society of Chemical Industry and John Wiley & Sons, Ltd.

CO2-binding organic liquids for high pressure CO2 absorption: Statistical mixture design approach and thermodynamic modeling of CO2 solubility using LJ-Global TPT2 EoS

CO2-binding organic liquids (CO2-BOLs) or switchable ionic liquids (SILs) are switchable polarity solvents (SPS) that can be used as non-aqueous, energy efficient solvents for CO2 absorption. In this study, the three-component CO2-BOLs comprised of a single-component CO2-BOL (tertiary alkanolamine) and a two-component CO2-BOL (superbase/alcohol) are introduced. The most efficient equimolar combination of superbase (1,8-diazabicyclo-[5.4.0]-undec-7-ene (DBU)), alcohol (methanol, n-butanol, sec-butanol, tert-butanol and hexanol) and amine (Dimethylethanolamine (DMEA), Diethylethanolamine (DEEA) and N-methyldiethanolamine (MDEA)) are obtained using screening experiments considering CO2 loading (αeq) and absorption rate (αR). The mixture design technique is employed for modeling of αeq and αR as a function of mole fraction of components at 35.0 °C and initial pressure of 25.0 bar. The DBU/DMEA/n-butanol CO2-BOL represented the best performance for CO2 uptake. The experimental CO2 solubility data in DBU/n-butanol, DBU/DMEA and DBU/DMEA/n-butanol BOLs were obtained in the temperature range of 25.0–45.0 °C and the pressure range of 1.0–45.0 bar. The DBU mole fraction was selected to be 0.1 and 0.2 while the molar ratio of DMEA to n-butanol was kept constant at 2 in the three-component BOL. The simultaneous vapor–liquid and chemical equilibrium calculation algorithm using LJ-Global TPT2 equation of state was used for the thermodynamic modeling of CO2 solubility in BOLs. The average absolute relative deviation error (AAD%) for the calculation of total pressure of DBU/n-butanol, DBU/DMEA and DBU/DMEA/n-butanol BOLs were obtained to be 8.5%, 5.8% and 8.6%, respectively.

Effect of Blending Ratio and Temperature on CO2 Solubility in Blended Aqueous Solution of Monoethanolamine and 2-Amino-2-methyl-propanol: Experimental and Modeling Study Using the Electrolyte Nonrandom Two-Liquid Model.

This paper reports the newly measured experimental data for CO2 solubility in a blended aqueous solution of monoethanolamine (MEA) and 2-amino-2-methyl-propanol (AMP) at different amine mixing ratios (MEA/AMP/H2O = 9:21:70, 15:15:70, and 21:9:70 wt %) and working temperatures (323.15, 373.15, and 383.15 K). The successive substitution method was used for calculating the mole fractions of all molecules (four molecules) and electrolytes (three cations and four anions) from the equilibrium along with the material and charge balance equations (11 equations). The electrolyte nonrandom two-liquid (e-NRTL) model was used to investigate nonideality in the liquid phase. Using the abovementioned thermodynamic models, the partial pressures of CO2 in the gas phase, mole fractions of all components in the liquid phase, pH variations, heats of absorption, and cyclic capacities of CO2 according to the absorption/desorption temperature and the blending ratio of MEA/AMP were estimated.

Measurements and modeling of vapor liquid equilibrium of CO2 in amine activated imidazolium ionic liquid solvents

The mean surface temperature has increased considerably over the past few decades primarily due to the huge contribution of CO2, a greenhouse gas. Hence, the reduction of CO2 majorly from the point sources of emission has been a thrust domain of research. This work reports the measurements and modeling of CO2 solubility in newly proposed aqueous solvent blends of 1-butyl-3-methyl-imidazolium acetate ([bmim] [Ac]) and amine activators. Various amine activators viz. 1-(2-aminoethyl) piperazine (AEP) and bis (3-aminopropyl) amine (APA) have been employed in aqueous [bmim] [Ac] over the wide operating temperature and CO2 partial pressure range of (303.15˗323.15) K and (1–390) kPa, respectively. Along with this, qualitative 13C NMR and FTIR analysis have been also performed to assess the proposed reaction scheme. The experimental vapor liquid equilibrium data (VLE) were modeled by modified Kent-Eisenberg equilibrium model including the gas phase non-ideality and Feed forward neural network model. The equilibrium constants associated with [bmim] [Ac], AEP and APA deprotonation, and carbamate formation reactions are regressed to fit the experimental CO2 solubility data. Various important thermophysical properties such as surface tension, viscosity, sound velocity, refractive index and density have also been measured and correlated using established as well as newly proposed models.

Experimental data, thermodynamic and neural network modeling of CO2 absorption capacity for 2-amino-2-methyl-1-propanol (AMP) + Methanol (MeOH) + H2O system

In this study, new experimental data were reported for CO2 solubility in H2O + 2-amino-2-methyl-1-propanol (AMP) + methanol (MeOH) system by using a static-synthetic apparatus. The experiments were done in the temperature range of 313.15–353.15 K and the CO2 partial pressure range of 1.08–303.7 kPa. The concentrations (wt. %) of mixed AMP + MeOH were 8.2 + 41.2, 16.5 + 32.2, 22.3 + 27.7 and 30.6 + 19.4. Also, the density of the hybrid solvent was measured using a pycnometer similar to concentration and temperature ranges. To correlate the experimental CO2 solubility data, three different models namely modified Kent-Eisenberg, Deshmukh-Mather, and artificial neural network (ANN) were used. The density data were correlated by Redlich-Kister equation. The results showed that the ANN modeling with an average absolute relative deviation (AARD%) and a correlation coefficient (R2) of 1.95 and 0.9981, respectively, were in good agreement with the experimental CO2 loading data in comparison with other models.

Prediction of CO2 solubility in multicomponent electrolyte solutions up to 709 bar: Analogical bridge between hydrophobic solvation and adsorption model

Prediction of CO2 solubility in electrolyte solution is important for the design of various industrial processes using CO2. A large amount of experimental data is needed to predict the solubility accurately, as a consequence of the complex composition of electrolyte solution. 1384 experimental CO2 solubility data in various electrolyte solutions (containing mostly Na+, Ca2+, Mg2+, K+, SO42−, and Cl−) from 30 references were used as training and validation data for developing a solubility model. According to the analogy between the hydrophobic solvation of CO2 and the adsorption phenomena, the novel solubility model with only four parameters (m0, α, k0, and k1) was developed to predict the CO2 solubility in solution with various ions. The model was correlated with the CO2 pressure and system temperature. The effect of dissolved electrolytes on the CO2 solubility was indicated by the concentration of electrostricted water molecule (ha) in the model, which was calculated using the concentration and hydration number of dissolved ions. The developed model with four parameters—obtained from experimental CO2 solubility data in water and single-salt solutions—reproduced the CO2 solubility well in complex electrolyte solutions, including the solutions after CO2–brine–rock reactions. Of the 1384 data, 94% were within a 95% prediction interval of the model. The model parameters can be used to estimate the heat of CO2 solvation, maximum CO2 solubility in water, and decay constant of the CO2 solubility with respect to the ha value. The developed model was further validated with single-salt solutions containing minor ions such as Li+ or Br−.

Efficient estimation of CO2 solubility in aqueous salt solutions

Industrialization and modernization have led to an increasing trend of greenhouse gas emissions entering the atmosphere. Consequently, many countries are imposing strict environmental regulations due to increasing concern on the climate change, and a significant amount of research is being conducted to tackle this problem. Carbon capture and sequestration are one of the major methods, which can remarkably contribute to this issue since a major greenhouse gas in Earth's atmosphere is carbon dioxide (CO2). The general objective of this work was to investigate the significance of potential use of aqueous salt solutions for capturing CO2 by developing an accurate model for estimation of this phenomenon. In particular, 608 experimental data of CO2 solubility in aqueous solutions of salts as a function of temperature, pressure, salt solution concentration (molality), hydrogen bond acceptor count of salts, molecular weight of salts, and complexity value of the salts were collected from the literature. Four state-of-the-art computational methods (LSSVM, ANN, PSO-ANFIS and GA-ANFIS) were employed to examine their predictive capability for the problem. The results reveal that the LSSVM offers the highest accuracy with R2 = 0.9927 and %AARD = 5.37. Although the neural network and fuzzy interface systems are more complex approaches, the superiority of the LSSVM method for the problem under study demonstrates the easy nature of this phenomenon. Thus, the LSSVM model is recommended for estimating the CO2 solubility in aqueous salt solutions because not only it has more accuracy, but also it is easy to apply, has less mathematically complicated and less time-consuming.

Thermodynamic and Kinetic Studies of CO2 Capture by Glycol and Amine-Based Deep Eutectic Solvents

Anthropogenic CO2 emissions into the atmosphere are responsible for the global warming, therefore, it is essential to reduce these emissions at the source. Recently, deep eutectic solvents (DESs) have shown great potential to absorb the CO2. In the current study, 15 different types of amine- and glycol-based deep eutectic solvents were synthesized and investigated for CO2 absorption. In general, amine-based solvents have shown higher CO2 absorption as compared to glycol based solvents. In particular, the highest CO2 absorption was observed for the tetrabutyl ammonium bromide and methyldiethanol amine (TBAB/4MDEA) system having a CO2 solubility of 0.29 (mol CO2/mol solvent) at 1 MPa and 303.15 K. Thermophysical properties of all synthesized DESs were estimated using the modified Lydersen–Joback–Reid method and Lee–Kesler mixing rule. Experimental CO2 solubility data were well fitted using the nonrandom two liquid and the Peng–Robinson thermodynamic models. Apart, CO2 solubility data were correlated with He...

Experimental Study of Carbon Dioxide Solubility in Aqueous N-Methyldiethanolamine Solution with 1-Butylpyridinium Tetrafluoroborate Ionic Liquid

New experimental data for CO2 solubility in the aqueous solutions of N-methyldiethanolamine (MDEA) and 1-butylpyridinium tetrafluoroborate ([Bpy][BF4]) ionic liquid (IL) are reported. The experiments were conducted in a static high pressure equilibrium cell. Solubility measurement of CO2 was performed in various solution compositions of IL and MDEA in a wide temperature range of 298.15–343.15 K and pressures up to 4 MPa. The experimental results revealed that, by increasing the weight percent of IL, the absorption capacity of aqueous mixtures diminishes. It was also observed that the main capacity of CO2 loading in the absorbent solutions belonged to MDEA through chemical absorption, whereas its concentration was more effective than IL in gas solubility. The experimental results are correlated using a semiempirical model with good accuracy.

Carbon dioxide solubilities in tricyanomethanide-based ionic liquids: Measurements and PC-SAFT modeling

This work reports the measurements of the solubility of carbon dioxide (CO2) in three tricyanomethanide based ionic liquids (ILs) constituted by different cations: 1-butyl-3-methylimidazolium, 1-butyl-4-methylpyridinium, 1-butyl-1-methylpyrrolidinium in order to investigate the effect of the cation on the solubility. The solubility of CO2 have been determined using high-pressure variable volume cell in a range of temperature from T = (292.13–367.85) K and pressure up to 121.6 bars. A high solubility of CO2 in the 1-butyl-4-methylpyridinium tricyanomethanide was observed in comparison with the other cation. It was found that the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) may be used to represent with good accuracy the experimental data of CO2 solubility in tricyanomethanide based ionic liquid.