Experiments, Modeling, and Simulation of CO2 Dehydration by Ionic

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Separations

Experiments, Modeling, and Simulation of CO2 Dehydration by Ionic Liquid, Triethylene Glycol, and Their Binary Mixtures Yifan Jiang, Mohsen Taheri, Gangqiang Yu, Jiqin Zhu, and Zhigang Lei Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.9b02540 • Publication Date (Web): 05 Aug 2019 Downloaded from pubs.acs.org on August 6, 2019

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Industrial & Engineering Chemistry Research

Experiments, Modeling, and Simulation of CO2 Dehydration by Ionic Liquid, Triethylene Glycol, and Their Binary Mixtures

Yifan Jiang, Mohsen Taheri, Gangqiang Yu, Jiqin Zhu,* and Zhigang Lei* State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing 100029, China

ABSTRACT: Ionic liquids (ILs) as a new class of gas dehydration solvents, in combination with the traditional triethylene glycol (TEG) solvent were first proposed for carbon dioxide (CO2) dehydration. Among 210 preliminary ILs, the hydrophilic [BMIM]+[BF4]- was selected based on the COSMO-RS model-involved IL screening methodology. Solubility of CO2 in pure TEG, pure [BMIM]+[BF4]-, binary mixture of TEG + [BMIM]+[BF4]-, and ternary mixture of TEG + [BMIM]+[BF4]- + H2O were measured experimentally. Two new binary interaction parameters (BIPs) were introduced by correlating a series of experimental data with the UNIFAC-Lei model. The COSMO-RS model along with the reduced density gradient (RDG) method was applied to interpret the nature of interaction between molecules. The CO2 dehydration experiment was conducted in a laboratory-scale absorption tower. The process simulation indicates that, in comparison with pure TEG, the use of IL purely or mixed with TEG improves both separation performance and process energy penalty.

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1. INTRODUCTION With the rapid development of industrialization, emissions of greenhouse gases have caused severe environmental problems. Among the primary greenhouse gases, carbon dioxide (CO2) has the greatest impact on the global warming owning to the large volume of its constant anthropogenic emissions.1 The first solution for global warming is to control and reduce CO2 emissions. However, the current scientific and technological endeavours are not sufficient to change the inherent energy demand structure of the globe. Thus, separation and recovery of CO2 from industrial processes become the key point to the alleviation of destructive effect of this long-lived greenhouse gas. At present, the recovered CO2 is mainly utilized in two types of processes: one is to use it as an industrial raw material for processing and synthesis;2 the other is to seal it in the underground geological formation.3 In both applications, CO2 needs to be transported through pipelines. Pipeline transportation has certain requirement for moisture content. To avoid the corrosion and blockage of pipelines, dehydration must be carried out prior to the gas transportation. The triethylene glycol (TEG) dehydration method is widely applied in industry for CO2 dehydration, since TEG has the advantages of high moisture absorption and easy regeneration.4 However, there are some problems associated with the TEG dehydration process: (1) the reboiler temperature needs to be strictly controlled, because an excessive temperature will lead to the solvent decomposition;5 and (2) CO2 promotes the degradation process of TEG, thus reducing the solvent replacement time and increasing the operating cost.6 Over the last several years, the applications of ionic liquids (ILs) in separation and purification processes,7-10 organic synthesis and catalysis,11 electrochemistry,12 and material

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chemistry13 have been studied by many researchers. In separation processes, the high stability of ILs makes them easy to regenerate, the low vapor pressure of ILs reduces atmospheric pollution, and the designability of ILs brings about the possibility of selection of a suitable IL for a given process.14 Therefore, in this work the usage of IL-TEG hybrid solvents in CO2 dehydration processes was investigated. IL and TEG mixed as the hybrid solvents can benefit from the advantages of each other, which can subsequently increase the separation efficiency of CO2 dehydration process. The aim of this work is divided into the following sections: (1) the most suitable IL for CO2 dehydration experiment was selected from 210 preliminary IL candidates, using a COSMO-RS-based IL solvent screening method and taking into account the Henry’s constants (Hi) of CO2 and H2O, the selectivity of CO2 to H2O (S = HCO2/HH2O), and other physical properties such as IL stability; (2) experimental measurements were performed to obtain the solubility of CO2 in pure TEG, pure IL, binary mixture of TEG + IL, and ternary mixture of TEG + IL + H2O, and the predicted values by UNIFAC-Lei model were compared with experimental data; (3) the CO2 dehydration experiment using IL-TEG as absorbent in an absorption tower was carried out at the laboratory-scale; (4) an in-depth analysis on CO2 dehydration mechanism by the reduced density gradient (RDG) method and COSMO-RS model was made; and (5) the CO2 gas dehydration process simulation was conducted within the ASPEN PLUS framework. 2. EXPERIMENTAL SECTION 2.1. Materials The chemical materials used in this study including CO2, TEG, and IL were purchased

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from chemical markets. Detailed information on these chemicals can be found in Supporting Information (SI) Table S1. 2.2. Apparatus and Procedure 2.2.1. CO2 Solubility Measurement The solubility data of CO2 in pure IL, pure TEG, binary mixture of IL + TEG, and ternary mixture of IL + TEG + H2O were measured over a wide temperature (from 273.15 to 353.15 K) and pressure (from 0.5 to 3.5 MPa) range using a gas-liquid equilibrium (GLE) apparatus. Ethanol and silicone oil as the medium for cooling and heating, respectively, were used in the experimental apparatus to achieve the required low and high temperatures. Details on the structure and operating procedure of experimental apparatus have been given elsewhere.14 Fluctuations of the pressure gauge and temperature sensor used in the experiments were ± 0.001 MPa and ± 0.1 K, respectively. 2.2.2. Gas drying experiment The CO2 drying experiment was carried out in an absorption tower (Φ30 mm × 1 m). A scheme of gas drying experimental setup is presented in Figure S1. The gas from a CO2 cylinder passes through a regulator, a gas flow regulator, and a buffer tank containing H2O. The saturated H2O gas enters from the bottom of absorption tower. The solvent passes through the advection pump from the top of absorption tower so that the two streams are in countercurrent contact. The H2O content in the feeding CO2 gas was measured on-line by a dew point meter (the type RHD-601), around 20000 ppm (molar fraction basis) at 298.2 K and atmospheric pressure. The flow rate of the feeding CO2 gas was kept at 800 mL·min-1.

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3. MODELING SECTION 3.1. UNIFAC-Lei Model The UNIFAC-Lei model, an efficient activity coefficient-based group contribution predictive model, has been extensively applied by many researchers.7,15-17 It extends the original UNIFAC model to IL systems, and is written as ln  i  ln  iC  ln  iR

(1)

where ln  Ci is directly related to the shape and size of groups, which contains the group area and volume parameters Rk and Qk (see SI Table S2 ); and ln  iR is only related to the areas and interactions of groups, which contains a pair of binary interaction parameters (BIPs)

amn and anm . Information on BIPs correlation is available in our previous work.18,19 In this work, six UNIFAC-Lei structural groups (CH2, CO2, OH, CH2O, H2O, and

 MIMBF4  )

are concerned, which are listed in Table 1.18,20,21 The BIPs ( amn and anm )

between CO2 and CH2O, as well as those between CH2O and

 MIMBF4  ,

are unknown.

Thus, they were acquired using the CO2 solubility data measured in this work as well as those collected from the literature.22 The objective function (OF) was used to acquire the unknown

amn and anm :  1 OF  min   N

N

 1

xcal  xexp   xexp 

(2)

where x is the solubility of CO2 (in mole fraction) in liquid phase; and N is the number of data points. For the BIPs acquired in this work, a three-fold cross validation method was used to verify the predictive capability of UNIFAC-Lei model. The solubility data of CO2 in TEG and in the mixture of TEG and IL are randomly divided into three groups of the same type. The BIPs were correlated with the two sets of data, and verified with the left one. Therefore, 5



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three models (Model 1/3, Model 2/3, and Model 3/3) were set up in this procedure, and each model had 1/3 of the data. The average relative deviation (ARD) was applied to select the best values of BIPs. Table 2 lists the BIPs between CO2 and CH2O and between [MIM][BF4] and CH2O ( amn and anm ), along with the ARD values. It can be seen that ARD is less than 0.08 in most of the cases, indicating the validity of UNIFAC-Lei model. Gas-liquid equilibrium (GLE) for the CO2 + solvent systems can be written as

i yi P   i xi Pi s

(3)

where xi and yi are the mole fractions of CO2 in the liquid and gas phases, respectively; P and Pi S

are the system pressure and the saturated vapor pressure of CO2 at a certain

temperature;23 i is the gas phase fugacity coefficient of CO2;24 and γi is the CO2 activity coefficient calculated by the UNIFAC-Lei model. 3.2. COSMO-RS Model Screening a suitable IL by means of predictive thermodynamic models can save time and cost of the experiments. Herein, among 210 preliminary ILs, the statistical thermodynamic-based COSMO-RS model was utilized to explore a matching IL for gas dehydration experiments. The two-dimensional structures, names, and abbreviations of ILs used in this study are given in SI Table S3. Figure S2a shows the influence of cation and anion types on the COSMO-RS predicted HCO2 in ILs. Moreover, for most of the anions (e.g., [ClO4]-, [AC]-, and [TF2N]-), the longer the cationic alkyl chain length in ILs, the higher the solubility of CO2 in ILs. Therefore, [BMIM]+ with a shorter alkyl chain is selected as the cationic moiety. As shown in Figures S2b and S2c, anions play the dominant roles in determining the HH2O and selectivity of CO2 to H2O (S). Although S is the largest in the ILs

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with the anion [AC]-, the [AC]- is not a thermally stable anion.25 Moreover, it exhibits chemical absorption for CO2, which is clearly not conducive to the dehydration process.26 In addition, H2O has a higher solubility in ILs in which the anion is halogen; however, their melting points are high, that is, they are solid at room temperature.27,28 Therefore, the hydrophilic-IL [BMIM]+[BF4]- was selected as a suitable CO2 dehydration IL. In addition to the low melting temperature and good chemical stability, [BMIM]+[BF4]- is completely miscible with H2O at room temperature.25,29,30 Although the hydrolysis of BF4-based ILs may occur under certain conditions, the H2O content in feeding gas is relatively small and thus hydrolysis effect is not considered in this work. The COSMO-RS model is a powerful and efficient tool which allows to estimate the excess enthalpies for the binary or ternary mixture systems including ILs.31-33 In the calculation, the excess enthalpy is the sum of three specific interactions, i.e., electrostatic-misfit interaction (HMF), hydrogen bonding interaction (HHB), and van der Waals interaction (HvdW):

H m  H MF  H HB  H vdw

(4)

3.3. RDG Analysis RDG analysis is used for the interpretation of intermolecular and intramolecular weak interactions.34 Weak interactions mainly include hydrogen bonding (HB), van der Waals (vdW), and steric interactions. Herein, Multiwfn35 software was used for RDG calculation, and VMD36software was used for the display of weak interactions. Compared to the COSMO-RS model, RDG analysis further sheds light on the interaction mechanism between CO2/H2O molecule and the solvent molecule.

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4. PROCESS SIMULATION The CO2 dehydration process simulation was conducted within the ASPEN PLUS framework, the rigorous equilibrium stage (EQ-stage) model being adopted. The employed IL ([BMIM]+[BF4]-) was added manually into the ASPEN program, while TEG, H2O, and CO2 were added from the ASPEN PLUS (V7.2) database. The newly obtained parameters along with the previously available UNIFAC-Lei BIPs were imported into the UNIFAC property model so that the processes can be simulated accurately based on the experimentally-derived parameters. 5. RESULTS AND DISCUSSION 5.1. Solubility of CO2 in Solvents Figures 1 and 2 show the solubility of CO2 (1) in pure TEG (2), [BMIM]+[BF4]- (3), the binary mixture of TEG (2) + [BMIM]+[BF4]- (3) at different contents (x2 = 0.2, 0.5, 0.8), and the ternary mixture of TEG (2) + [BMIM]+[BF4]- (3) + H2O (4) at different contents (x2 = 0.14, 0.35, 0.56), along with the UNIFAC-Lei predicted values. It can be observed that the results follows the general trend. Under the same temperature and pressure, the solubility of CO2 in mixed solvents increases with the increase of [BMIM]+[BF4]- content in the mixture. Furthermore, the UNIFAC-Lei model shows the reliable predictive power for the solubility of CO2 in either single (TEG or [BMIM]+[BF4]-) or mixed solvents. Comparison of the UNIFAC-Lei predicted values versus experimental data is given in SI Table S4. As a whole, the ARDs are less than 10%, thus, UNIFAC-Lei model is suitable for predicting the CO2 solubility in the hybrid TEG-IL solvents. As shown in Figure 2 and Figure S3, the presence of H2O in solvents reduces the CO2 solubility, which facilitates the acquisition of more CO2

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product in the gas dehydration processes. The detailed CO2 solubility data are listed in SI Tables S5 and S6. The Henry’s constant is also an important thermodynamic property, which is calculated by37

H 1 (T,P)  lim

x1  0

f1L P (T , P, y1 )  lim 1 x1 x1 0 x1

(5)

where H 1 (T,P) is the Henry’s constant of CO2 (1) in TEG, [BMIM]+[BF4]-, or TEG + [BMIM]+[BF4]- (expressed in mole fraction); f1L is the fugacity of CO2 in liquid phase; and

1 (T , P, y1 ) is the fugacity coefficient of pure CO2 in gas phase.24 The Henry’s constants of CO2 in pure and mixed solvents by linear regression at temperatures (273.15, 293.15, 313.15, 333.15, and 353.15 K) are given in Table 3, together with the calculated values by UNIFAC-Lei model. Obviously, [BMIM]+[BF4]- has the lower Henry's constants than other solvents, that is, CO2 is more soluble in [BMIM]+[BF4]- than in other solvents investigated in this work. Moreover, the Henry’s constants predicted by UNIFAC-Lei model were compared with those obtained experimentally. It is clear from Table 3 that both agree well. 5.2. CO2 Dehydration Process Experiment Using TEG-IL as Absorbent The solvent used in the CO2 dehydration process experiment at temperature of 298.2 K and atmospheric pressure was TEG (x2 = 0.5) + [BMIM]+[BF4]- (x3 = 0.5). The main reason for choosing this proportion of mixed solvents is based on the dehydration effect of mixed hydrophilic solvents at the same molar ratio. Evidently, the solvent flow rate has a significant effect on separation performance. Figure 3a shows that the H2O content in outlet gas is related to solvent flow rate. As the solvent flow rate increases, the H2O content in outlet gas first drops rapidly, and then becomes stable. Meanwhile, the H2O content in solvent itself 9



also greatly affects the H2O content in outlet gas. As shown in Figure 3b, at a given flow rate, the H2O content in outlet gas has a linear relationship with the H2O content in solvent. Thus, in practice these two factors should be taken into account together. The detailed gas dehydration experimental data are given in SI Table S7. 5.3. Excess Enthalpy for CO2-Liquid Systems The excess enthalpies of one ternary mixture (CO2 + TEG (x2=0.5) + [BMIM]+[BF4](x3=0.5)) and two binary mixtures (CO2 + TEG and CO2 + [BMIM]+[BF4]-) at 298.15 K are presented in Figure 4. At low CO2 concentration region, the negative excess enthalpy of CO2-TEG system indicates that the van der Waals interaction (HvdW) is dominant, bringing out the exothermicity as depicted in Figure 4a. However, when the mole fraction of CO2 exceeds 0.8, the contribution of hydrogen bonding interaction (HHB) to excess enthalpy is more than HvdW, while the electrostatic-misfit interaction (HMF) can almost be ignored. For the CO2-[BMIM]+[BF4]- system, Figure 4b presents the predicted excess enthalpies. Unlike the CO2-TEG system, the excess enthalpy of CO2 + [BMIM]+[BF4]- is negative in the whole concentration range, indicating the exothermic process. Moreover, the absolute value of excess enthalpy of CO2 + [BMIM]+[BF4]- is much greater than that of CO2 + TGE, indicating a stronger interaction between CO2 and [BMIM]+[BF4]-, which makes the solubility of CO2 in ILs much greater than in TEG. To understand the solubility mechanism of CO2 in binary mixtures, the excess enthalpies of CO2 + TEG (x2=0.5) + [BMIM]+[BF4]- (x3=0.5) are shown in Figure 4c. The Hm, HHB, HvdW, and HMF in ternary system seem to lie between those in binary systems. More specially, the solubility of CO2 in binary mixtures is also between those in pure TEG and IL, which means that excess enthalpy also reflects the change in solubility

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in some degree. Similarly, the trend of excess enthalpies of CO2 + TEG (x2=0.2) + [BMIM]+[BF4]- (x3=0.8) and CO2 + TEG (x2=0.8) + [BMIM]+[BF4]- (x3=0.2) is also related to the solubility. Their excess enthalpies are shown in SI Figure S4. The excess enthalpies (Hm, HHB, HvdW, and HMF) of binary and ternary mixtures at 298.15 K are depicted in Figure 5. It was found that both Hm and HvdW become more negative with the increase of [BMIM]+[BF4]- content in solution, exhibiting the strong exothermicity. However, the strong exothermicity of the mixture is favorable for improving the solubility of CO2 in IL.38 Moreover, HvdW makes the largest contribution to excess enthalpy, indicating that the difference in CO2 interactions with TEG and [BMIM]+[BF4]- mainly results from van der Waals force. As for HHB and HMF, with the increase of [BMIM]+[BF4]- content, HHB becomes smaller, whereas HMF becomes higher, but still lower than HHB. Thus, HvdW and HHB have a more significant contribution to excess enthalpy. Figure 6a shows the Hm of equimolar CO2-solvent mixtures calculated by COSMO-RS model versus the Henry’s constants calculated by UNIFAC-Lei model at 298.15 K. As the solubility of CO2 in solvent increases (corresponding to the small Henry’s constants), exothermic effect of the mixture becomes stronger (corresponding to the reduced Hm ). Figure 6b further analyzes the effect of HHB, HvdW, and HMF on the solubility of CO2 in solvent. As the solubility of CO2 in solvent increases, HvdW and HMF also increase, while HHB shows an opposite trend. The detailed Henry’s constants and excess enthalpies are given in SI Table S8. Figure 7 shows the comparison between the excess enthalpy of H2O + TEG + [BMIM]+[BF4]- and that of CO2 + TEG + [BMIM]+[BF4]-. Under the same molar

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composition, the excess enthalpies of CO2 and solvent are negative, in contrast to the positive excess enthalpies of H2O and solvent (see Figure 7a). In addition, Figure 7b further reveals that under the same molar composition, HHB plays the key role in the excess enthalpy of H2O and solvent, while HvdW does in the excess enthalpy of CO2 and solvent. This indicates that the main interaction between H2O and solvent is hydrogen bond formed to remove the moisture from gas mixture. 5.4. RDG Analysis for the CO2/H2O + TEG + IL Systems Figure 8a shows a large green iso-surface between TEG and [BMIM]+[BF4]-, indicating that the two compounds are bound together by vdW interaction. Furthermore, inside the [BMIM]+[BF4]-, the hydrogen atom on the imidazole ring forms a strong HB with the fluorine atom. The red region inside the imidazole ring indicates a strong steric effect. For the TEG + [BMIM]+[BF4]- + CO2 system (see Figure 8b), the green region between CO2 and TEG indicates vdW interaction, while the yellow-green region represents a weak spatial steric effect. For the TEG + [BMIM]+[BF4]- + H2O system (see Figure 8c), the dark blue region indicates that the hydrogen atoms in H2O molecule form a strong HB with the fluorine atoms in [BF4]-. In addition, there is a green region between the oxygen atoms in H2O molecule and the hydrogen atoms in the methylene group of TEG, indicating the formation of a weak HB. It can be inferred that the formation of HB plays the key role in the removal of H2O molecules from gas mixture, which is consistent with the excess enthalpy analysis aforementioned. The molecular structures optimized by Gaussian 09 software are shown in SI Figure S5. 5.5. Process Simulation on CO2 Gas Dehydration with TEG, IL, and the Mixed TEG +

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IL as Absorbents Figure 3 shows that the simulated values by the EQ-stage model with the UNIFAC property model agree well with the experimental data, thus verifying the reliability of UNIFAC-Lei model for CO2 dehydration using the mixed TEG + IL solvent as absorbent. Figure 9 shows the CO2 dehydration process flowsheet using three different absorbents (pure IL, pure TEG, and 50 wt% TEG + 50 wt% IL). As shown in Figure 9a, the pure IL contacts countercurrent with the moisture-containing CO2 gas in absorption column, in which the product gas is discharged at the top, while the IL rich in moisture passes through a heat exchanger and then enters the flash tank. The recycled absorbent passes through the condenser and enters the absorber. Since TEG is more volatile than IL, for the dehydration process using TEG or TEG + IL as absorbent, a distillation column is used instead of flash tank for solvent recovery (see Figure 9b). The following specifications are considered in process simulation: (1) maintaining the same specification of gas feed and solvent, and (2) the molar fraction of H2O in product gas doesn’t exceed 600 ppm. Optimized specifications of the three processes are given in SI Tables S9. As given in Table 4, the pure IL process achieves the best separation performance and the lowest energy consumption under the same gas feed (1000 kg/h, 2% mole fraction in water content) and absorbent doses (3500 kg/h). However, for pure TEG process, both separation performance and energy consumption are the worst. In addition, compared to the pure TEG process, both separation performance and energy consumption of the TEG + IL process are improved due to the addition of IL. Therefore, the application of TEG + IL process can not only reduce the cost of pure IL in some degree, but also achieve a better separation performance.

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6. CONCLUSIONS In this work, the mixed IL and TEG was first proposed as absorbent for gas dehydration. The hydrophilic IL ([BMIM]+[BF4]-) was selected after considering such factors as solubility and chemical stability. Moreover, the COSMO-RS model and reduced density gradient (RDG) method were used together to reveal the different types of interactions. It was proven that the strong hydrogen bond (HB) formed by H2O molecule and the anion ([BF4]-) plays a key role in gas dehydration. The solubility data of CO2 in pure TEG, pure [BMIM]+[BF4]-, binary mixture of TEG + [BMIM]+[BF4]-, and ternary mixture of TEG + [BMIM]+[BF4]- + H2O were measured. The UNIFAC-Lei predicted values show a good consistency with experimental data. The binary mixture of TEG and [BMIM]+[BF4]- as absorbent exhibits an excellent CO2 dehydration performance. Furthermore, the process simulation on CO2 dehydration was conducted within the ASPEN PLUS framework. In comparison with the benchmark pure TEG solvent, pure IL or a combination of IL-TEG solvent can improve both separation performance and energy consumption. In the end, it is noting that no extra streams and equipments are needed to add based on the original TEG process, when using the TEG + IL solvent as absorbent.

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

ASSOCIATED CONTENT

Supporting Information The Supporting Information is available free of charge on the ACS Publications website. Detailed experimental solubility data and predicted values by the UNIFAC-Lei model, the flowsheet of gas dehydration experiment, and the optimized process parameters can be found in the online version (xls).  AUTHOR INFORMATION Corresponding Author *Phone:

+86-10-64433695; E-mail: [email protected] (J. Zhu).

E-mail: [email protected] (Z. Lei). ORCID Jiqin Zhu: 0000-0003-1187-0522 Zhigang Lei: 0000-0001-7838-7207 Yifan Jiang: 0000-0003-4855-9340 Gangqiang Yu: 0000-0002-3595-6972 Notes The authors declare no competing financial interest.  ACKNOWLEDGMENTS This work is financially supported by the National Key R&D Plan of China (No. 2018YFB0604702) and the National Natural Science Foundation of China under Grant (No. U1862103).

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 REFERENCES (1) Work, S. N. Kinetics of core material dissolution in the presence of inhibitors for application in geologic carbon sequestration. Rice University, 2010. (2) Ramachandriya, K. D.; Kundiyana, D. K.; Wilkins, M. R.; Terrill, J. B.; Atiyeh, H. K.; Huhnke, R. L. Carbon dioxide conversion to fuels and chemicals using a hybrid green process. Appl. Energy 2013, 112, 289-299. (3) Murai, S.; Fujioka, Y. Challenges to the Carbon Dioxide Capture and Storage (CCS) Technology. IEEJ Trans. Electr. Electron. Eng. 2010, 3, 37-42. (4) Kemper, J.; Sutherland, L.; Watt, J.; Santos, S. Evaluation and Analysis of the Performance of Dehydration Units for CO2 Capture. Energy Procedia 2014, 63, 7568-7584. (5) Netusil, M.; Ditl, P. Comparison of three methods for natural gas dehydration. J. Nat. Gas Chem. 2011, 20, 471-476. (6) Bahadori, A.; Vuthaluru, H. B.; Mokhatab, S. Analyzing solubility of acid gas and light alkanes in triethylene glycol. J. Nat. Gas Chem. 2008, 17, 51-58. (7) Taheri, M.; Dai, C.; Lei, Z. CO2 capture by methanol, ionic liquid, and their binary mixtures: Experiments, modeling, and process simulation. AIChE J. 2018, 64, 2168-2180. (8) Zhu, Z.; Hu, J.; Geng, X.; Qin, B.; Ma, K.; Wang, Y.; Gao, J. Process design of carbon dioxide and ethane separation using ionic liquid by extractive distillation. J. Chem. Technol. Biotechnol. 2018, 93, 887-896. (9) Hu, Y.; Su, Y.; Jin, S.; Chien, I. L.; Shen, W. Systematic approach for screening organic and ionic liquid solvents in homogeneous extractive distillation exemplified by the tert-butanol dehydration. Sep. Purif. Technol. 2019, 211, 723-737. (10) Zhu, Z.; Ri, Y.; Li, M.; Jia, H.; Wang, Y.; Wang, Y. Extractive distillation for ethanol dehydration using imidazolium-based ionic liquids as solvents. Chem. Eng. Process. 2016, 109, 190-198. (11) Weishi, M.; Tak Hang, C. Ionic-liquid-supported synthesis: a novel liquid-phase strategy for organic synthesis. Acc. Chem. Res. 2006, 39, 897-908. (12) Shen, Y.; Zhang, Y.; Qiu, X.; Guo, H.; Li, N.; Ivaska, A. Polyelectrolyte-functionalized ionic liquid for electrochemistry in supporting electrolyte-free aqueous solutions and application in amperometric flow injection analysis. Green Chem. 2007, 9, 746-753.

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(13) Brandt, A.; Hallett, J. P.; Leak, D. J.; Murphy, R. J.; Welton, T. The effect of the ionic liquid anion in the pretreatment of pine wood chips. Green Chem. 2010, 12, 672-679. (14) Lei, Z.; Chen, B.; Koo, Y. M.; MacFarlane, D. R. Introduction: Ionic Liquids. Chem. Rev. 2017, 117, 6633-6635. (15) Kamgar, A.; Esmaeilzadeh, F. Prediction of H2S solubility in [hmim][Pf6], [hmim][Bf4] and [hmim][Tf N] using UNIQUAC, NRTL and COSMO-RS. J. Mol. Liq. 2016, 220, 631-634. (16) Akbari, A.; Rahimpour, M. R. Prediction of the solubility of carbon dioxide in imidazolium based ionic liquids using the modified scaled particle theory. J. Mol. Liq. 2018, 255, 135-147. (17) Yu, G.; Dai, C.; Lei, Z. Modified UNIFAC-Lei Model for Ionic Liquid–CH4 Systems. Ind. Eng. Chem. Res. 2018, 57, 7064-7076. (18) Lei, Z.; Zhang, J.; Li, Q.; Chen, B. UNIFAC model for ionic liquids. Ind. Eng. Chem. Res. 2014, 48, 2697-2704. (19) Lei, Z.; Dai, C.; Liu, X.; Xiao, L.; Chen, B. Extension of the UNIFAC Model for Ionic Liquids. Ind. Eng. Chem. Res. 2012, 51, 12135-12144. (20) Skjoldjorgensen, S.; Kolbe, B.; Gmehling, J.; Rasmussen, P. Vapor-Liquid Equilibria by UNIFAC Group Contribution. Revision and Extension. Ind. Eng. Chem. Process Des. Dev. 1979, 18, 2352-2355. (21) Dai, C.; Wei, W.; Lei, Z.; Li, C.; Chen, B. Absorption of CO2 with methanol and ionic liquid mixture at low temperatures. Fluid Phase Equilib. 2015, 391, 9-17. (22) Wise, M.; Chapoy, A. Carbon dioxide solubility in triethylene glycol and aqueous solutions. Fluid Phase Equilib. 2016, 419, 39-49. (23) Shiflett, M. B.; Yokozeki, A. Solubility and diffusivity of hydrofluorocarbons in room‐temperature ionic liquids. AIChE J. 2010, 52, 1205-1219. (24) Span, R.; Wagner, W. A New Equation of State for Carbon Dioxide Covering the Fluid Region from the Triple㏄oint Temperature to 1100 K at Pressures up to 800 MPa. J. Phys. Chem. Ref. Data 1996, 25, 1509-1596. (25) Cao, Y.; Mu, T. Comprehensive Investigation on the Thermal Stability of 66 Ionic Liquids by Thermogravimetric Analysis. Ind. Eng. Chem. Res. 2014, 53, 8651–8664. (26) Gomez-Coma, L.; Garea, A.; Irabien, A. Carbon dioxide capture by [emim][Ac] ionic liquid in a polysulfone hollow fiber membrane contactor. Int. J. Greenhouse Gas Control 2016, 52, 401-409. (27) Ngo, H. L.; Lecompte, K.; Hargens, L.; Mcewen, A. B. Thermal properties of imidazolium ionic 17



liquids. Thermochim. Acta 2000, 357, 97-102. (28) Brünig, T.; Krekić, K.; Bruhn, C.; Pietschnig, R. Calorimetric Studies and Structural Aspects of Ionic Liquids in Designing Sorption Materials for Thermal Energy Storage. Chem-Eur J. 2016, 22, 16200-16212. (29) Suarez, P. A. Z.; Einloft, S.; Dullius, J. E. L.; Souza, R. F. D.; Dupont, J. Synthesis and physical-chemical properties of ionic liquids based on 1-n-butyl-3-methylimidazolium cation. J. Chim. Phys. Phys.-Chim. Biol. 1998, 95, 1626-1639. (30) Maiti, A.; Kumar, A.; Rogers, R. D. Water-clustering in hygroscopic ionic liquids-an implicit solvent analysis. Phys. Chem. Chem. Phys. 2012, 14, 5139-5146. (31) Kurnia, K. A.; Coutinho, J. A. P. Overview of the Excess Enthalpies of the Binary Mixtures Composed of Molecular Solvents and Ionic Liquids and Their Modeling Using COSMO-RS. Ind. Eng. Chem. Res. 2013, 52, 13862-13874. (32) Klamt, A. The COSMO and COSMO-RS solvation models. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2011, 1, 699-709. (33) Mokrushina, L.; Buggert, M.; Smirnova, I.; Arlt, W.; Schomäcker, R. COSMO-RS and UNIFAC in Prediction of Micelle/Water Partition Coefficients. Ind. Eng. Chem. Res. 2007, 46, 6501-6509. (34) Johnson, E. R.; Keinan, S.; Morisánchez, P.; Contrerasgarcía, J.; Cohen, A. J.; Yang, W. Revealing noncovalent interactions. J. Am. Chem. Soc. 2010, 132, 6498. (35) Lu, T.; Chen, F. Multiwfn: a multifunctional wavefunction analyzer. J. Comput. Chem. 2012, 33, 580-592. (36) Humphrey, W.; Dalke, A.; Schulten, K. VMD: Visual molecular dynamics. J. Mol. Graphics 1996, 14, 33-38. (37) Lee, B.-C.; Outcalt, S. L., Solubilities of gases in the ionic liquid 1-n-butyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide. J. Chem. Eng. Data 2006, 51, 892-897. (38) Palomar, J.; Gonzalezmiquel, M.; Polo, A.; Rodriguez, F. Understanding the Physical Absorption of CO2 in Ionic Liquids Using the COSMO-RS Method. Ind. Eng. Chem. Res. 2011, 50, 3452-3463.

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Page 18 of 36

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Table Captions Table 1. Group Binary Interaction Parameters (amn and anm) in the UNIFAC-Lei Model

Table 2. Three-fold Cross Validation Results

Table 3. Henry’s Constants of CO2 in Solvents Obtained Experimentally (Hexp) and Predicted by UNIFAC-Lei Model (Hpred) at Different Temperatures

Table 4. Comparison of the Simulation Results among the Three CO2 Dehydration Processes

19



Page 20 of 36

Table 1. Group Binary Interaction Parameters (amn and anm) in the UNIFAC-Lei Model

a

m

n

amn

anm

CH2 CH2 CH2 CH2 CH2 CO2 CO2 CO2 CO2 [MIM][BF4] [MIM][BF4] [MIM][BF4] OH OH CH2O

CO2 [MIM][BF4] OH CH2O H2O [MIM][BF4] OH CH2O H2O OH CH2O H2O CH2O H2O H2O

107.7 1108.51 986.5 251.5 1318 -14.4413 794.9 137.1718a 497 131.24 -42.2773a -408 28.06 353.5 -314.7

6339 588.74 156.4 83.36 300 430.7991 65.65 748.9029a 386.91 -13.77 -152.6024a 242.88 237.7 -229.1 540.5

Group binary interaction parameters obtained in this work; others from refs.18,20,21

20


Page 21 of 36 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46


Table 2. Three-fold Cross Validation Results

m

CO2 CO2 CO2 [MIM][BF4] [MIM][BF4] [MIM][BF4]

n

Models

No. of data points in training set

No. of data points in validation set

CH2O Model 1/3 44 CH2O Model 2/3 45 CH2O Model 3/3 45 best values for interaction parameters CH2O Model 1/3 78 CH2O Model 2/3 78 CH2O Model 3/3 78 best values for interaction parameters

23 22 22 39 39 39

amn

anm

195.6120 137.1718 137.0440 137.1718 -42.2773 -36.7135 -38.8464 -42.2773

569.1142 748.9029 749.5391 748.9029 -152.6024 -153.6099 -142.1957 -152.6024

21


ARDs for validation set

ARDs for all data

0.0779 0.0732 0.0824

0.0772 0.0768 0.0769

0.0389 0.0461 0.0437

0.0427 0.0427 0.0427


Page 22 of 36

Table 3. Henry’s Constants of CO2 in Solvents Obtained Experimentally (Hexp) and Predicted by UNIFAC-Lei Model (Hpred) at Different Temperatures Solvents

T (K)

Hexp(MPa)

Hpred(MPa)

RDs

TEG

273.15 293.15 313.15 333.15 353.15

7.61 11.13 17.05 23.37 32.61

7.00 10.97 16.55 24.12 34.13

0.0804 0.0148 0.0293 0.0321 0.0468

[BMIM]+[BF4]-

273.15

4.05

3.63

0.1023

293.15 313.15 333.15 353.15 273.15 293.15 313.15 333.15 353.15 273.15 293.15 313.15 333.15 353.15 273.15 293.15 313.15 333.15 353.15

6.67 9.66 13.49 16.82 4.84 7.03 10.12 14.74 20.02 5.65 8.51 12.20 16.37 22.00 6.48 10.48 15.93 18.89 27.63

5.64 8.46 12.28 17.34 4.19 6.49 9.71 14.07 19.82 5.06 7.86 11.76 17.03 23.99 6.09 9.50 14.28 20.75 29.28

0.1538 0.1249 0.0901 0.0304 0.1335 0.0768 0.0405 0.0455 0.0099 0.1035 0.0764 0.0361 0.0406 0.0901 0.0606 0.0929 0.1036 0.0985 0.0595

TEG(x2=0.2) + ILs(x3=0.8)

TEG(x2=0.5) + ILs(x3=0.5)

TEG(x2=0.8) + ILs(x3=0.2)

22


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Table 4. Comparison of the Simulation Results among the Three CO2 Dehydration Processes Contents

Absorbents

Product stream

Streams

Solvent

Pure IL

Pure TEG

TEG + IL

Temperature (℃)

25

25

25

Mass flowrate (kg·h-1)

974

980

978

H2O content of the CO2 product (molar fraction)

101 ppm

563 ppm

393 ppm

CO2 loss (kg·h-1)

17.72

11.72

13.72

Mass flowrate (kg·h-1)

3500

3500

3500

CO2 content in the recycled solvent (molar fraction)

384ppm

2000ppm

2282ppm

0.147

-0.008 0.16 0.16

-0.0035 0.152 0.152

1.201

1.362

1.385

Flash drum Heat duty (GJ/h) Condenser (GJ/h) Desorption column Reboiler (GJ/h) Total heating duty (GJ/h) Heat Heat duty (GJ/h) exchanger

Heat dutya

0.147

Cooler1

Heat duty (GJ/h)

-0.146

-0.195

-0.161

Cooler2

Heat duty (GJ/h)

-0.024

-0.0008

-0.0001

-0.17 0.184 3.56

-0.2038 0.214

-0.1646 0.209

Total cooling duty (GJ/h) PSEP (GJ/kg)b Energy consumption of vacuum pump (kW) aCO

2

dehydration process with IL: total heating duty = energy consumption of flash drum, total cooling

duty = energy consumption of cooler 1 + energy consumption of cooler 2; CO2 dehydration process with pure TEG or TEG + IL: total heating duty = energy consumption of reboiler, total cooling duty = energy consumption of cooler 1 + energy consumption of cooler 2 + energy consumption of condenser. bPSEP

=

energy

demand

/

flow

rate

of

23


captured

H2O

(GJ/kg).


Figure Captions Figure 1. Solubility of CO2 (1) in TEG, [BMIM]+[BF4]-, and their mixtures at 273.15 K (a), 293.15 K (b), 313.15 K (c), 333.15 K (d), and 353.15 K (e). Lines, results predicted by the UNIFAC-Lei model; scattered points, experimental data. (●) and (—), TEG; (□) and (– –), TEG (x2=0.8) + [BMIM]+[BF4]- (x3=0.2); (△) and (– –), TEG (x2=0.5) + [BMIM]+[BF4](x3=0.5); (○) and (– –), TEG (x2=0.2) + [BMIM]+[BF4]- (x3=0.8); (▲) and (—), [BMIM]+[BF4]-.

Figure 2. Solubility of CO2 (1) in the binary mixtures (TEG + [BMIM]+[BF4]-) and in the ternary mixtures (TEG + [BMIM]+[BF4]- + H2O) at 293.15 K (a, d), 313.15 K (b), and 333.15 K (c). Lines, results predicted by the UNIFAC-Lei model; scattered points, experimental data. (●) and (—), TEG (x2=0.14) + [BMIM]+[BF4]- (x3=0.56) + H2O (x4=0.3); (▲) and (—), TEG (x2=0.35) + [BMIM]+[BF4](x3=0.35) + H2O (x4=0.3); (■) and (—), TEG (x2=0.56) + [BMIM]+[BF4]- (x3=0.14) + H2O (x4=0.3); (★) and (—), TEG (x2=0.5) + [BMIM]+[BF4]- (x3=0.5).

Figure 3. (a) The effect of solvent volume flowrate (VS) on the H2O content (mole fraction) in outlet gas (y1) when the WH2O in the feeding solvent is 500 ppm (●), 1000ppm (▲), 2000ppm (■) , respectively; and (b) the effect of the H2O content WH2O (mass fraction) in solvent on the H2O content (mole fraction) in outlet gas (y1) when VS is 5 ml/min. Lines, predicted values by the EQ stage model; scattered points, experimental data.

24


Page 24 of 36

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Figure 4. Excess enthalpies calculated by the COSMO-RS model at 298.15 K. CO2 (1) + TEG (2) (a); CO2 (1) + [BMIM]+[BF4]- (2) (b); and CO2 (1) + TEG (x2=0.5) + [BMIM]+[BF4]- (x3=0.5) (c).

Figure 5. The intermolecular interactions Hm (a), HvdW (b), HHB (c), and HMF (d) for the excess enthalpies of binary and ternary mixtures at 298.15 K. (▲) [BMIM]+[BF4]-; (□) TEG (x2=0.2) + [BMIM]+[BF4]- (x3=0.8); ( △ ) TEG (x2=0.5) + [BMIM]+[BF4]- (x3=0.5); (○) TEG (x2=0.8) + [BMIM]+[BF4]- (x3=0.2); (●) TEG.

Figure 6. Excess enthalpies (Hm) of equimolar CO2-solvent mixtures calculated by COSMO-RS model versus the Henry’s constants (H) calculated by UNIFAC-Lei model at 298.15 K (a) and the effect of HvdW, HHB, and HMF on CO2 solubility at 298.15 K (b). (▲) [BMIM]+[BF4]-; (□) TEG (x2=0.2) + [BMIM]+[BF4]- (x3=0.8); ( △ ) TEG (x2=0.5) + [BMIM]+[BF4]- (x3=0.5); (○) TEG (x2=0.8) + [BMIM]+[BF4]- (x3=0.2); (●) TEG.

Figure 7. Excess enthalpies of the ternary mixtures: (a) solid lines, H2O + TEG + [BMIM]+[BF4]-; dotted lines, CO2 + TEG + [BMIM]+[BF4]-; black lines, TEG (x2=0.2) + [BMIM]+[BF4]- (x3=0.8); red lines, TEG (x2=0.5) + [BMIM]+[BF4]- (x3=0.5); blue lines, TEG (x2=0.8) + [BMIM]+[BF4]- (x3=0.2). (b) H2O (x1=0.3) + TEG (x2=0.35) + [BMIM]+[BF4](x3=0.35) and CO2 (x1=0.3) + TEG (x2=0.35) + [BMIM]+[BF4]- (x3=0.35).

25



Figure 8. Color-filled reduced density gradient (RDG) maps. Isovalue of RDG is set to 0.5, and the value of sign (λ2)ρ on the surfaces is represented by filling color ranging from -0.03 to 0.02 au. Blue means the strong attractive interactions, and red means the strong nonbonded overlap.

Figure 9. The CO2 dehydration processes with pure IL (a) and pure TEG or TEG + IL (b) as absorbents.

26


Page 26 of 36

2.5

3.0

2.0

2.5 2.0

P (MPa)

1.5 1.0

1.5 1.0

0.5

0.5

(a) 0.0 0.0

0.1

0.2

4.0

x1

0.3

0.4

0.5

0.0 0.0 4.0

3.5

3.5

3.0

3.0

2.5

2.5

2.0

0.1

0.2

x1

0.3

0.4

2.0

1.5

1.5

1.0

1.0

0.5 0.0 0.0

(b)

P (MPa)

P (MPa)

0.5

(c) 0.1

x1

0.2 4.0

0.0 0.0

0.3

(d) 0.1

x1

0.2

3.5 3.0 2.5

P (MPa)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


P (MPa)

Page 27 of 36

2.0 1.5 1.0 0.5

(e)

0.0 0.0

0.1 x1

0.2

Figure 1. Solubility of CO2 (1) in TEG, [BMIM]+[BF4]-, and their mixtures at 273.15 K (a), 293.15 K (b), 313.15 K (c), 333.15 K (d), and 353.15 K (e). Lines, results predicted by the UNIFAC-Lei model; scattered points, experimental data. (●) and (—), TEG; (□) and (– –), TEG (x2=0.8) + [BMIM]+[BF4]- (x3=0.2); (△) and (– –), TEG (x2=0.5) + [BMIM]+[BF4](x3=0.5); (○) and (– –), TEG (x2=0.2) + [BMIM]+[BF4]- (x3=0.8); (▲) and (—), [BMIM]+[BF4]-.

27



4.0

5.0

3.0 P (MPa)

P (MPa)

4.0 3.0 2.0

2.0 1.0

1.0

(b)

(a)

0.0 0.0

0.1

0.2 x1

0.3

0.0 0.0

0.4

5.0

5.0

4.0

4.0

3.0

3.0

P (MPa)

P (MPa)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 28 of 36

2.0 1.0 0.0 0.0

x1

0.2

2.0 1.0

(c)

0.1 x1

0.1

(d)

0.2

0.0 0.0

0.1

x1

0.2

0.3

Figure 2. Solubility of CO2 (1) in the binary mixtures (TEG + [BMIM]+[BF4]-) and in the ternary mixtures (TEG + [BMIM]+[BF4]- + H2O) at 293.15 K (a, d), 313.15 K (b), and 333.15 K (c). Lines, results predicted by the UNIFAC-Lei model; scattered points, experimental data. (●) and (—), TEG (x2=0.14) + [BMIM]+[BF4]- (x3=0.56) + H2O (x4=0.3); (▲) and (—), TEG (x2=0.35) + [BMIM]+[BF4](x3=0.35) + H2O (x4=0.3); (■) and (—), TEG (x2=0.56) + [BMIM]+[BF4]- (x3=0.14) + H2O (x4=0.3); (★) and (—), TEG (x2=0.5) + [BMIM]+[BF4]- (x3=0.5).

28


Page 29 of 36

700

700 (a)

600

600

500

500 y1 (ppm)

y1 (ppm)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


400 300

400 300

200

200

100

100

0

0

5

10

VS (ml/min)

0

15

(b)

0

1000

2000

3000

4000

WH2O (ppm)

Figure 3. (a) Effect of solvent volume flowrate (VS) on the H2O content (mole fraction) in outlet gas (y1) when the WH2O in the feeding solvent is 500 ppm (●), 1000ppm (▲), 2000ppm (■) , respectively; and (b) effect of the H2O content WH2O (mass fraction) in solvent on the H2O content (mole fraction) in outlet gas (y1) when VS is 5 ml/min. Lines, predicted values by the EQ stage model; scattered points, experimental data.

29



1500

1000

HCO2-IL(J·mol-1)

HHB

1000 HCO2-TEG(J·mol-1)

500 HMF

0

-500

Hm

-1000

HvdW

-1500 0.0

0.2

0.4

0.6

x1

0.8

500

HHB

0

HMF

-500 Hm

-1000 -1500 -2000

HvdW

-2500

(a)

-3000 0.0

1.0

0.2

0.4

x1

0.6

(b) 0.8 1.0

1000 HCO2-IL+TEG (J·mol-1)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 30 of 36

HHB

500 0

HMF

-500 Hm

-1000 -1500 -2000

HvdW

-2500 0.0

0.2

0.4

x1

0.6

(c)

0.8

1.0

Figure 4. Excess enthalpies calculated by the COSMO-RS model at 298.15 K. CO2 (1) + TEG (2) (a); CO2 (1) + [BMIM]+[BF4]- (2) (b); and CO2 (1) + TEG (x2=0.5) + [BMIM]+[BF4]- (x3=0.5) (c).

30


Page 31 of 36

500

0 -500

Hm (J·mol-1)

HvdW (J·mol-1)

0

-1000

-500

-1500

-1000

-2000

(b)

(a) -1500 0.0

0.2

0.4

x1

0.6

0.8

-2500 0.0

1.0

1400 1200

0.4

0.2

0.4

x1

0.6

0.8

1.0

0.6

0.8

1.0

(d)

(c) 400

HMF (J·mol-1)

800 600 400

300 200 100

200 0 0.0

0.2

500

1000

HHB (J·mol-1)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


0.2

0.4

x1

0.6

0.8

1.0

0 0.0

x1

Figure 5. The intermolecular interactions Hm (a), HvdW (b), HHB (c), and HMF (d) for the excess enthalpies of binary and ternary mixtures at 298.15 K. (▲) [BMIM]+[BF4]-; (□) TEG (x2=0.2) + [BMIM]+[BF4]- (x3=0.8); ( △ ) TEG (x2=0.5) + [BMIM]+[BF4]- (x3=0.5); (○) TEG (x2=0.8) + [BMIM]+[BF4]- (x3=0.2); (●) TEG.

31



(a)

0

Hm (J·mol-1)

-200 -400 -600 -800

-1000 -1200

6

8

10

12

14

IL

0.2TEG+0.8IL

0.5TEG+0.5IL

1200 900 600 300 0 -300 -600 -900 -1200 -1500 -1800

0.8TEG+0.2IL

(b)

TEG

H (MPa)

Hm (J·mol-1)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 32 of 36

■ HMF ■ HHB ■ HvdW

12.20

10.91

8.72

7.20

6.26

H (MPa)

Figure 6. Excess enthalpies (Hm) of equimolar CO2-solvent mixtures calculated by COSMO-RS model versus the Henry’s constants (H) calculated by UNIFAC-Lei model at 298.15 K (a) and the effect of HvdW, HHB, and HMF on CO2 solubility at 298.15 K (b). (▲) [BMIM]+[BF4]-; (□) TEG (x2=0.2) + [BMIM]+[BF4]- (x3=0.8); ( △ ) TEG (x2=0.5) + [BMIM]+[BF4]- (x3=0.5); (○) TEG (x2=0.8) + [BMIM]+[BF4]- (x3=0.2); (●) TEG.

32


Page 33 of 36

2000

Hm (J·mol-1)

1500 (a) 1000 500 0 -500

-1000 -1500 -2000 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 xCO2 (xH2O)

1200 800 Hm (J·mol-1)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


■ HMF

(b)

■ HHB ■ HvdW

400 0

-400 -800

-1200 CO2

H2O

Figure 7. Excess enthalpies of the ternary mixtures: (a) solid lines, H2O + TEG + [BMIM]+[BF4]-; dotted lines, CO2 + TEG + [BMIM]+[BF4]-; black lines, TEG (x2=0.2) + [BMIM]+[BF4]- (x3=0.8); red lines, TEG (x2=0.5) + [BMIM]+[BF4]- (x3=0.5); blue lines, TEG (x2=0.8) + [BMIM]+[BF4]- (x3=0.2). (b) H2O (x1=0.3) + TEG (x2=0.35) + [BMIM]+[BF4](x3=0.35) and CO2 (x1=0.3) + TEG (x2=0.35) + [BMIM]+[BF4]- (x3=0.35).

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(b) TEG + [BMIM]+[BF4]- + CO2

(a) TEG + [BMIM]+[BF4]-

(c) TEG + [BMIM]+[BF4]- + H2O -0.02

-0.03

H-bond

vdW

Steric

Figure 8. Color-filled reduced density gradient (RDG) maps. Isovalue of RDG is set to 0.5, and the value of sign (λ2)ρ on the surfaces is represented by filling color ranging from -0.03 to 0.02 au. Blue means the strong attractive interactions, and red means the strong nonbonded overlap. 34


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H2O CO2 product gas IL

Cooler 2 Cooler 1

Heat exchanger Flash

Feed

Pump

(a) Offgas TEG or TEG+IL H2O

CO2 product gas Cooler 2 Cooler 1

Desorption column

Heat exchanger Reboiler

Feed

Pump

(b) Figure 9. The CO2 dehydration processes with pure IL (a) and pure TEG or TEG + IL (b) as absorbents. 35



Table of Content (TOC) Graphic

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Experiments, Modeling, and Simulation of CO2 Dehydration by Ionic

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