Natural Gas Dehydration with Ionic Liquids - Energy & Fuels (ACS

The technology of natural gas dehydration with ionic liquids (ILs) as a promising method was proposed and systematically investigated in this work. Th...
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Natural Gas Dehydration with Ionic Liquids Gangqiang Yu, Chengna Dai, Liang Wu, and Zhigang Lei Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b02920 • Publication Date (Web): 11 Jan 2017 Downloaded from http://pubs.acs.org on January 23, 2017

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Natural Gas Dehydration with Ionic Liquids Gangqiang Yu, Chengna Dai, Liang Wu, and Zhigang Lei∗ State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Box 266, Beijing 100029, China

ABSTRACT: The technology of natural gas dehydration with ionic liquids (ILs) as a promising method was proposed and systematically investigated in this work. The IL [EMIM][Tf2N] was screened out as an appropriate absorbent from 252 ILs candidates for natural gas dehydration process by means of COSMO-RS model. The σ-profiles and σ-potentials of CH4-H2O-IL system were analyzed at the molecular level to explain the possibility of CH4 dehydration using [EMIM][Tf2N] as absorbent. The experiment data of CH4 solubility in pure IL and in the mixture of IL + H2O were measured, and compared with the predicted results by UNIFAC-Lei model. Moreover, the CH4 dehydration experiment was carried out, and the gas product with a low water content (down to 350 ppm in mole fraction) can be obtained. Finally, the conceptual dehydration process was simulated and optimized using the rigorous equilibrium (EQ) stage model, into which the UNIFAC-Lei model parameters were input. It was found that the CH4 dehydration process with [EMIM][Tf2N] demonstrates the better separation performance, i.e., no solvent loss, plant miniaturization, and saving energy consumption, when compared to the benchmark triethylene glycol (TEG) process. Thus, ILs can be taken on as a type of promising alternative absorbents to conventional solvents in the field of gas dehydration. Keywords: Natural gas dehydration, Ionic liquids (ILs), UNIFAC-Lei model, COSMO-RS

∗ Corresponding author. Tel: +86 10 64433695. E-mail address: [email protected] (Z. Lei).

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model, Process simulation 1. INTRODUCTION Natural gas has been widely applied in various fields such as chemical industry, energy sources, and daily life. The extracted raw natural gas is often saturated by water vapor, and even may carry a certain amount of liquid water.1 The presence of water in natural gas can cause many serious disasters. For example, the presence of water vapor in natural gas containing CO2 and H2S can form acid, leading to the corrosion of pipelines and equipments2,3 In some cases it can form gas hydrate blocking valves, pipelines and process equipment,4 decreasing the pipeline transmission capacity, causing too much power consumption, and thus increasing the additional economic losses. To meet the need of pipeline specifications, before delivering to the pipeline all natural gas is required to remove water. Thus, natural gas dehydration is necessary, which is beneficial to the effective development and utilization of natural gas. Nowadays the main methods for natural gas dehydration are: absorption with conventional solvents,5 adsorption with solid desiccants,6 condensation, membrane separation,7 and supersonic separation.8 Among others, the method of absorption with conventional solvents has been widely used in industrial production. Moreover, triethylene glycol (TEG) is often used.9,10 The dehydration process with TEG consists of two major steps: absorption of water in wet gas through absorption column, and desorption of water from the water-loaded solvent in regenerator (distiller). The regeneration of TEG is a very significant step in the whole process because water content in the recycled TEG would straightly affect the quality of gas product.9,10 The operating parameters such as regeneration temperature and

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pressure can cause some certain influence on the quality of regenerated TEG. The purity of regenerated TEG will increase with the increasing regeneration temperature, and decrease with the increasing regeneration pressure. Thus, the optimal operating conditions are at high temperature and low pressure. However, the regeneration temperature has to be controlled to around 208 ℃,5 above which TEG starts to decompose. Although TEG has a relatively low saturated vapor pressure, there are still a large number of losses through vaporization, which can not be avoided during regeneration process. The high energy consumption and relatively high loss of TEG result in high operating cost. In addition, foaming phenomenon often exists in TEG dehydration process, especially in the presence of hydrocarbons, wax, sand, drilling mud and other impurities, which can cause severe foaming, flooding, higher glycol losses and poor efficiency and increase maintenance cost in the absorption column. To eliminate the drawbacks, it is necessary to explore a more suitable, efficient and alternative absorbent to replace TEG for the dehydration of natural gas. In recent years, ionic liquids (ILs) have received increasingly significant attention as novel green solvents due to their distinctive physicochemical properties, such as high thermal and chemical stability, inflammability, tunable properties, low-melting points, and almost negligible vapor pressure around room temperature; and so far there has been no literature reported on the foaming problems of ILs. These good characteristics have made them become promising green candidates to replace traditional organic solvents in many chemical engineering processes, e.g., gas drying,11 extractive distillation,12 and homogeneous two-phase catalytic reactions.13 It is known that many ILs are highly hygroscopic and possess a high solubility for water, so that the affinity of ILs for water vapor is even higher than that

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of TEG. Moreover, the superiority of negligible vapor pressure can make the ILs regeneration process simplified, and almost pure ILs can be obtained simply by a flash tank. Meanwhile, the volatilization loss of solvents can be avoided. In principle, ILs can be used as a kind of promising gas dehydration agents and alternative absorbents to TEG. For these reasons, several researchers proposed the potential use of ILs for gas dehydration. Heym et al.11 reported the application of two types of ethyl sulfate based ILs for natural gas dehydration; however, the proposed ILs may hydrolyze in case of CO2 and H2S existing in feeding gas. Nevertheless, the open literature on the dehydration of natural gas with ILs is still rare, let alone the rigorous mathematical model for process simulation and optimization. However, the first step is to screen out the best suited IL used for natural gas dehydration from a tremendous number of potential candidates of ILs. The conductor-like screening model for real solvents (COSMO-RS) model independent on the experimental data is an efficient and priori predictive method,14 showing a very strong predictive power for various properties of ILs solutions. For more details on the COSMO-RS model for ILs, please see the website at https://www.scm.com/doc/Tutorials/COSMO-RS/Ionic_Liquids.html, which was provided by our group. The Henry’s law constants of water and CH4, as well as the selectivity of CH4/H2O, in a great amount of ILs were calculated by the COSMO-RS model in this work to screen out the suitable IL. The σ-profiles and σ-potentials derived by the COSMO-RS model were used to analyze the intermolecular interactions for CH4-IL-H2O system at the molecular level. On the other hand, the accuracy of COSMO-RS model for describing the phase equilibrium of gas-IL systems is often less than that of UNIFAC-Lei model.15 In this case, the popular UNIFAC-Lei model has to be used for the rigorous process simulation of

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natural gas dehydration with ILs. This is the first work to extend our UNIFAC-Lei model to the CH4-IL-H2O system. The content of this work is organized according to the following several aspects: 1) selection of suitable IL and analysis on separation mechanism at the molecular scale by COSMO-RS model; 2) measurement of CH4 solubility in pure IL and in the mixture of IL + H2O, and extension of UNIFAC-Lei model to the CH4-IL-H2O system; 3) experimental validation on CH4 dehydration process with IL; and 4) process simulation and optimization using the EQ stage model. 2. PREDICTIVE THERMODYNAMIC MODELS 2.1. COSMO-RS Model The COSMO-RS model, which combines quantum chemical calculation with statistical thermodynamics, has been used to predict the thermodynamic properties of liquid mixture, such as activity coefficient, Henry’s law constant, solubility, and vapor pressure.16,17 The details on the parameterization of COSMO-RS model can be found in previous publications.18,19 The COSMOthermX software (version C30_1301, COSMOlogic GmbH & CO. KG, Leverkusen, Germany), which is programmed especially for the COSMO-RS model, was used for IL screening and the analysis of σ-profiles and σ-potentials. In the calculation the IL was treated as one cation and one anion mixture, as adopted by most of the authors. When the structures on cation/anion species are available in COSMObase library, they were directly used. In case of cation/anion species not available, the continuum solvation COSMO files of electronic density and molecular geometry were developed with TURBOMOLE (version 6.4) using the triple zeta valence potential (TZVP) basis set. The structures and

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meanings of abbreviations for all anions and cations of the ILs involved in this work are listed in Table S1 in Supporting Information. 2.2. UNIFAC-Lei Model The UNIFAC-Lei model developed by us has been widely applied by many authors for the systems containing ILs. In this work, the UNIFAC-Lei model was also adopted to describe the phase equilibrium, in which the skeleton of cation and anion is treated as a whole functional group as in previous works.20,21 In this model, the activity coefficient of component i ( γ i ) is expressed as ln γ i = ln γ iC + ln γ iR

(1)

where ln γ iC and ln γ iR represents the combinatorial contribution and the residual contribution, respectively. The ln γ iC term contains two group parameters Rk and Qk for each functional group; ln γ iR term is caused by energetic interaction between functional groups, and is a function of group interaction parameters amn and anm. The details on the calculation can be found in our previous publications.20,21 For the binary system of CH4 (1) + IL (2), the gas-liquid equilibrium at low and medium pressures can be represented by the following equation y1 P1φ1 (T , P, y1 ) = x1γ 1P1S

(2)

where y1 and x1 are the mole fractions of CH4 in gas and liquid phases, respectively;

φ1 (T , P, y1 ) is the fugacity coefficient of CH4 in gas phase calculated by the Peng-Robinson (PR) equation of state at a certain temperature and pressure; P and T are the system pressure and temperature, respectively; P1s is the saturated vapor pressure of CH4 calculated by Antoine equation, the model parameters of which come from Fogg and Gerrard;22 and γ1 is

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the activity coefficient of CH4 in liquid phase calculated by the UNIFAC-Lei model. In this work, the interaction parameters (amn and anm) between CH4 and IL, together with those between CH3 and H2O functional groups, were obtained by correlating a large amount of experimental CH4 solubility data published in literature.23-33 The average relative deviation (ARD) minimized was adopted as objective function (OF):

OF =

1 N xcal - xexp N∑ xexp 1

(3)

where xexp and xcal are the solubility of CH4 in liquid phase obtained from experimental data and predicted by the UNIFAC-Lei model, respectively; and N is the number of data points. The new obtained binary group interaction parameters as well as the available parameters20,34,35 concerned in this work are listed in Table 1. The comparison between experimental and predicted solubility of CH4 in IL and in H2O is listed in Table 2. The details on CH4 solubility data in ILs and in H2O, along with experimental methods and the corresponding cited literatures, are shown in Tables S2 and S3 in Supporting Information, respectively. 3. EXPERIMENTAL SECTION 3.1. Materials In this work, the IL [EMIM][Tf2N] (molecular mass 391.31 g·mol-1, purity > 99%, and water content < 2000 ppm in mass fraction) was purchased from Shanghai ChengJie Chemical Co. LTD. CH4 (purity > 99.95wt %, and the pressure 13 MPa) was purchased from Beijing Beiwen Special Gases Factory. Before starting the experiment, the IL must be purified to remove traces of water and volatile impurities at 353 K for 12 h by a rotary evaporator instrument (RE-52AA, Shanghai Yarong Biochemical Instrument Plant) to ensure 7

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the water content below 400 ppm as determined by the Karl Fischer titration (KLS701). 3.2. Apparatus and Procedure 3.2.1. CH4 Solubility Measurement The CH4 solubility data in pure [EMIM][Tf2N] and in the mixture of 98 wt% [EMIM][Tf2N] + 2 wt% H2O were measured at temperatures of (313.2, 333.2 and 353.2) K and pressures up to 7.0 MPa using a high-pressure view-cell apparatus by the drainage gas-collecting method. The low water content in the IL mixture was selected because the feeding gas to be dried in the actual process normally contains a small amount of water vapor (< 2 wt%). The details on this apparatus were described in our previous publications.36,37 The accuracies of temperature and pressure of the apparatus are 0.1 K and 0.001 MPa, respectively. In order to ensure the accuracy of experimental data, each data point was measured at least three times. Notably, it was assumed that no IL appeared in the gas phase. For the measurement of CH4 solubility in the IL + H2O mixture, the volatilization of water was also ignored since the water content in gas phase was very small under the experimental condition. That is to say, the composition of CH4 in gas phase was assumed to equal to unity. 3.2.2. Natural Gas Drying with IL The natural gas drying experiment was conducted in a packed stainless steel column with a height of 1 m and a diameter of 30 mm, in which θ ring packings (4×4×0.6 mm) were randomly loaded. 38 The flow diagram of experimental apparatus is shown in Figure 1. In the beginning, IL at a certain volume flowrate was pumped from the storage tank into the top of gas drying column (i.e., absorption column) by a constant-flux pump to fully wet the packings. The CH4 feeding gas was taken from the cylinder by a pressure reducing valve and

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a pressure and flow regulator, and flowed into a water storage tank to be satured. Then, the CH4 gas with saturated water entered into the bottom of absorption column. The saturated water content in CH4 gas is about 12000 ppm in mole fraction as measured by a gas moisture meter (type RHD-601, rang 0-30000 ppm, accuracy 30 ppm). In this way, CH4 gas and IL contacted countercurrent along the absorption column. It is noted that during the dehydration process IL did not bring about foaming problem. The water content in gas product could gradually reduce until it reached a stable value with a fluctuation of ± 0.1 ppm as measured by a gas moisture meter installed at the top of absorption column. The water-loaded IL at the bottom of absorption column was collected and regenerated by a rotary evaporator instrument (RE-52AA). 4. RESULTS AND DISCUSSION 4.1. Screening of ILs for CH4 Dehydration It is important to choose the suitable IL for CH4 dehydration from 252 kinds of ILs (i.e., different combinations of 14 cations and 18 anions) in terms of solubility selectivity ( S CH 4 /H 2O =

H CH 4 H H 2O

) of CH4 to H2O and the solubility of H2O (HH2O, MPa), both of which are

predicted by the COSMO-RS model. As shown in Figure 2, the selectivity of H2O/CH4 and the solubility of H2O in ILs are mainly affected by the anion, while the cation plays a secondary role. The trends determined by anions on the selectivity and Henry’s law constant of H2O in ILs are almost consistent. That is to say, the ILs with a high selectivity may also have a high solubility of water. Meanwhile, the solubility of CH4 in ILs is dependent on both cation and anion. For most ILs based on the same anion, the solubility of CH4 increases with the increasing alkyl chain length on cations. Moreover, it seems that the fluorination on anion 9

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with the same cation is unfavorable for increasing the CH4/H2O selectivity. For example, the selectivity with [CF3SO3]- is smaller than that with [CH3SO3]-. The ILs with hydrophilic anions like [Ac]-, [DEPO4]-, and [Cl]- exhibit the highest selectivity (over 105) among all the ILs investigated. However, it is known that the thermal stabilities of these ILs are not stable.39,40 The decomposition temperature of ILs with different anions shows the order of [Ac]– < Cl− < BF4− ≈ PF6− < [Tf2N]−. However, it can be seen from Figure 2(a) that the CH4/H2O selectivity in [EMIM][Tf2N] is more than 1000, which suffices for separating water from natural gas. Moreover, it is easy to purchase [EMIM][Tf2N] from chemical markets with a relatively cheap price. Thus, based on a comprehensive consideration, the IL [EMIM][Tf2N] was selected in this work as the suitable absorbent for CH4 dehydration process due to its good thermal stability (over 400 ℃), low viscosity (38.6 mPa·s at 20 ℃), and resistance to hydrolysis.41 4.2. Analysis of the σ-Profiles and σ-Potentials The σ-profiles and σ-potentials generated by the COSMO-RS model were used to analyze the separation mechanism relevant to CH4-H2O-IL system at the molecular level. The σ-profiles reveal the charge distribution on the surface of molecule and indicate the relative amount of surface with polar screening charge density (σ) for a molecule, while the σ-potentials represent the affinity of the molecule for surface of polarity σ. The entire σ range is divided into three regions, namely the nonpolar region (-0.009 e/Å2 < σ < 0.009 e/Å2), the hydrogen bond donor region (σ < -0.009 e/Å2), and the hydrogen bond acceptor region (σ > 0.009 e/Å2). As shown in Figure 3(a), the σ-profile of H2O has a wide range, and exhibits two strong peaks, i.e., one appearing at -0.018 e/Å2 in the hydrogen bond donor region acting as a

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hydrogen bond donor, and the other at 0.018 e/Å2 in the hydrogen bond acceptor region acting as a hydrogen bond acceptor. Thus, water is either a strong hydrogen bond acceptor or a strong hydrogen bond donor. For the CH4 σ-profile, almost all of the peaks appear in the nonpolar region. The σ-profile of [EMIM]+ ranges from -0.017 to 0.003 e/Å2 with a weak peak around -0.009 e/Å2, but most parts are in the nonpolar region. Thus, [EMIM]+ has the weak ability to act as a hydrogen bond donor. However, the anion [Tf2N]- can act as a strong hydrogen bond acceptor, because of the strong peak at 0.011 e/Å2. Therefore, the hydrogen bond interaction between H2O and IL is much stronger than that between CH4 and IL, and the anion plays a more important role than the cation. As shown in Figure 3(b), an almost straight line is observed for the σ-potential of H2O in the nonpolar region, demonstrating its high molecular polarity. The strongly negative σ-potential appears in the hydrogen bond donor region as well as in the hydrogen bond acceptor region, indicating that H2O has a strong affinity with other hydrogen bond donor or acceptor molecules. The negative σ-potential of [EMIM][Tf2N] in the hydrogen bond acceptor region indicates the strong hydrogen bond acceptor capability, further confirming that the interaction between [EMIM][Tf2N] and H2O is much stronger than that between [EMIM][Tf2N] and CH4, because of the formation of strong hydrogen bond between [Tf2N]- (as a strong hydrogen bond acceptor) and H2O (as a strong hydrogen bond donor). Thus, this work explains the possibility of CH4 dehydration with ILs at the molecular scale.

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4.3. Vapor Pressure of Water in [EMIM][Tf2N] The vapor pressure for the binary mixture of [EMIM][Tf2N] and H2O was measured in the temperature range from 293.15 to 353.15 K with a modified equilibrium still, and predicted by the UNIFAC-Lei model. For more details, please see Supporting Information The total average relative deviation (ARD) between experimental data and predicted values is 5.25%, validating the applicability of UNIFAC-Lei model for describing the VLE for the IL-H2O system (see Table S5 in Supporting Information). As shown in Figure 4, H2O absorption isotherms in ILs are not linear. However, the absorption isotherms exhibit nearly linear behavior at a low content of water. Thus, in this low content, the linear relation between vapor pressure and water mole fraction agrees well with the Henry’s law. When increasing the mole fraction of water, the vapor pressure first increases and then almost levels off approaching to the saturated vapor pressure of pure H2O at the same temperature, which is mainly due to the partial miscibility between water and [EMIM][Tf2N] leading to the demixing of IL and H2O at high H2O content. 4.4. CH4 Solubility in Pure [EMIM][Tf2N] and in the Mixture of [EMIM][Tf2N] + H2O The measured CH4 solubility data in pure [EMIM][Tf2N] and in the mixture of [EMIM][Tf2N] and H2O (98 wt% [EMIM][Tf2N] + 2 wt% H2O), along with the predicted results by the UNIFAC-Lei model are shown in Figure 5. It can be seen that experimental data and predicted values agree well, with the ARD 7.92%, validating the reliability of UNIFAC-Lei model toward CH4-H2O-IL system. The detailed data are listed in Table S4 in Supporting Information. It is obvious that CH4 solubility in pure [EMIM][Tf2N] is higher than that in the mixture of [EMIM][Tf2N] + H2O under the same operating conditions. This

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conforms to the so-called lever rule, in which gas solubility in binary mixture can be accounted based on the mole fraction average of individual solvents in the mixture.37,42 On the other hand, the addition of water into IL enhances the CH4 recovery ratio, leading to more gas product being released from the solution into the gas product at the top of absorption column. 4.5. CH4 Dehydration Experiment The CH4 dehydration experiment with [EMIM][Tf2N] as absorbent was carried out at temperature of 20 ℃ and ambient pressure. In the experiment, the flow rate of water-rich CH4 gas (water content around 12000 ppm in mass fraction) was kept at 500 mL·min-1 at normal temperature and pressure (NTP). The influence of IL flow rate on the outlet gas product was first investigated with the water mass fraction (wH2O, IL) in the inlet IL (after evaporation) 250 ppm. As shown in Figure 6(a), with the increase of IL amount, the water content in the outlet gas product first decreases sharply, and then almost levels off. When the IL volume flow rate is over 25 mL·min-1 (NTP), the water content (mole fraction) in the outlet gas product can be reduced to less than 350 ppm, which is completely enough to meet the needs of industrial water content in CH4 product. We also went a further step to investigate the effect of water content in the inlet IL on the outlet gas product at the IL flow rate of 25 mL·min-1 (NTP). As shown in Figure 6(b), with the increase of water content in the inlet IL, the water content in the outlet gas product increases as well. During the experiments, the water-loaded IL at the bottom of absorption column was regenerated by evaporating for a few hours in a rotary evaporator at 80 ℃ and 0.05 atm. 4.6. CH4 Dehydration Process Simulation

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4.6.1. Model Description and Validation The process simulation of CH4 dehydration with IL was carried out by Aspen Plus software (version 7.2). The UNIFAC model was used as the property method for process simulation, and the model parameters given in Table 1 were used. The EQ stage model for gas dehydration process was established. The number of theoretical stages was calculated by the HETP (height equivalent to a theoretical plate) method. The calculated HETP value is 0.544 m using the empirical correlation formula as proposed by Strigle,43 thus, the corresponding number of theoretical stages for the packing height of one meter is around 2. The simulated results by the EQ stage model, into which the UNIFAC property model was embedded, are shown in Figure 6. It is obvious that the simulated values and experimental data are in a good agreement with the ARD only 4.41%, indicating the validation of EQ stage model for process simulation and optimization. 4.6.2. Process Simulation and Optimization The continuous dehydration process with IL was conceptually designed, which mainly consists of a gas drying column and a flash drum for IL regeneration. The flowchart is illustrated in Figure 7(a). The feed gas with the water content of 12000 ppm (mole fraction) enters into the gas drying column at the bottom, and the IL with the water content of 250 ppm (mass fraction) is added at the top. The regeneration of IL is performed in a flash drum. The influence of design parameter (e.g., the number of theoretical stage of gas drying column Nt) •

and the operating parameters (e.g., the mass flow rate of the inlet IL ( m IL ), operating temperature of gas drying column (T1), regeneration temperature (T2) and pressure (P2) of flash drum) on the separation performance (i.e., water content in the outlet gas product) was

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investigated by process simulation using the EQ stage model. The water content in the outlet •

gas product as functions of the mass flow rate ( m IL ) and the number of theoretical stages (Nt) is shown in Figure 8(a). It can be seen that with the increase of IL flow rate, the water content in the outlet gas product decreases, and then tends to be constant. When the number of theoretical stage Nt is over 5, the influence of theoretical stage on the water content in the outlet gas product is not predominant. For example, when the number of theoretical stage •

increases from 3 to 5 at m IL = 4000 kg·h-1, an obvious improvement for the water content in the outlet gas product can be obtained (y1 decreases from 1246 to 597 ppm). But when Nt increases from 7 to 11, the water content in the outlet gas product only decreases from 490 to 439 ppm. Consequently, the optimal Nt was chosen at 5. It can be seen from Figure 8(b), when increasing the operating temperature of gas drying column (T1), the water content in the outlet gas product increases gradually. That is, a low operating temperature is favorable for gas dehydration. As shown in Figures 8(c) and 8(d), a high temperature (T2) and a low pressure (P2) of flash drum are desirable to achieve a better dehydration effect. In summary, to ensure the water content in the outlet gas product less than 600 ppm and the CH4 recovery ratio more than 99.5%, the optimal operating conditions are listed as follows: T1 = 20 ℃, P1 •

= 0.1 MPa, m IL = 4000 kg·h-1, T2 = 140 ℃, and P2 = 0.05 atm. In this case, the water content in the outlet gas product can be reduced to 597 ppm, and the CH4 recovery ratio can achieve as high as 99.8%. 4.6.3. Comparison between IL and TEG The dehydration process with TEG as the benchmark solvent was also simulated under the same operating conditions as those with IL except that the regeneration equipment of

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TEG is a distillation column instead of a flash drum (see Figure 7(b)). The operating parameters for CH4 dehydration process with respective [EMIM][Tf2N] and TEG as absorbents are listed in Table 3. The simulated results by the EQ stage model are given in Table 4. It can be seen that under the same production capacity of CH4 gas (CH4 recovery ratio ≥ 99.5%), the water contents in the gas product for [EMIM][Tf2N] and TEG are 597 and 1587 ppm, respectively. However, when achieving the same water content (1587 ppm) in CH4 gas product using the two processes, the flow rates of [EMIM][Tf2N] and TEG are 2600 and 4000 kg·h-1, respectively. Moreover, the recovery ratio of solvent for IL is 100%, whereas it is only 99.89% for TEG. The TEG process has the volatile TEG loss at the top of both gas drying column and desorption column, but the IL process has not. In particular, the space volume of flash drum (1.16 m3) in the IL process is reduced by 65.98%, when compared with that of the desorption column (3.41 m3) in the TEG process which consists of 1 condenser, 3 theoretical stages and 1 reboiler. This indicates that the use of IL for CH4 dehydration process can save a lot of space volume. Furthermore, the energy consumptions between [EMIM][Tf2N] and TEG were also compared. The thermophysical properties used in the energy analysis are given in Supporting Information. In the [EMIM][Tf2N] process the heating duty required for the regeneration system is 39.38 kW, while it is 60.74 kW in the TEG process. The total cooling duties in the [EMIM][Tf2N] and TEG processes including the energy consumed in cooler 1, cooler 2, and regeneration system (condenser) are -47.55 and -65.96 kW, respectively. In addition, in the [EMIM][Tf2N] process there is an extra 0.12 kW electric energy consumption of vacuum pump for flash drum. In total, the total heating and cooling duties can be decreased 34.97%

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and 27.91% in the IL process, respectively, when compared to those in the TEG process. Meanwhile, the exergy consumption (10.96 kW) in the IL process can be saved as much as 51.91% compared with that (22.79 kW) in the TEG process, which was obtained using the calculation method as proposed by Kotas.44 Moreover, to obtain the products with the same water content (1587 ppm), the costs for energy consumption and equipment in the IL process can be reduced by 2.01 × 105 RMB /year and 2.42 × 105 RMB, respectively, lower than in the TEG process. Thus, the payback period for the IL process is about 2.3 years. Anyway, the IL process demonstrates more excellent separation performances than the conventional TEG process, i.e., no solvent loss, plant miniaturization, and saving energy consumption. 5. CONCLUSIONS In this work, the CH4 gas dehydration with IL as absorbent was systematically investigated from the viewpoint of chemical engineering. The COSMO-RS model was used not only for screening out the suitable IL, but also for deriving the σ-profiles and σ-potentials of CH4-H2O-IL system to explore the separation mechanism at the molecular scale. The IL [EMIM][Tf2N] was selected after considering such factors as solubility, selectivity, thermal stability, viscosity, hydrolysis, source, and so on. The solubility of CH4 in pure IL and in the mixture of IL + H2O was measured, and the popular UNIFAC-Lei model was adopted to describe the gas-liquid equilibrium. On this basis, the rigorous EQ stage model, into which the UNIFAC-Lei model parameters were input, was established to simulate and optimize the whole CH4 dehydration process. When compared to the benchmark TEG process, CH4 gas dehydration with IL is indeed a typical process intensification (PI) technology because it meets the following three main characteristics as defined by PI technology: miniaturization,

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saving energy, and reducing waste generation. For more details on PI technology, please see the

website

http://www.rvo.nl/sites/default/files/bijlagen/European_Roadmap_Process_Intensification.pdf.

at So this

work ranges from molecular level to industrial scale. In the end, it should be mentioned that the proposed CH4 gas dehydration process with IL is easily implemented in practice in a similar manner as the conventional TEG process in that the original desorption column is replaced by a simpler flash drum. The gas dehydration technology with IL as proposed in this work is not limited to CH4 gas, and may be extended to the dehydration of other gases or removing other volatile organic compounds from gas mixtures. ■ AUTHOR INFORMATION Corresponding Author *Tel.: +86-1064433695. E-mail: [email protected].

Notes The authors declare no competing financial interest.

■ ACKNOWLEDGMENTS This work was financially supported by the National Natural Science Foundation of China under Grants (Nos. 21476009, 21406007, and U1462104).

Supporting Information Available: The abbreviations, names, and structures of ILs used throughout the paper, the detailed CH4 solubility data in ILs and H2O from literature used for the correlation of group interaction parameters in UNIFAC-Lei model, and the detailed experimental solubility data measured in this work and the predicted values by UNIFAC-Lei model.

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■ REFERENCES (1) Baker, R.W.; Lokhandwala, K. Natural gas processing with membranes: An overview. Ind. Eng. Chem. Res. 2008, 47, 2109-2121. (2) Gonfaa, G.; Bustama, A. M.; Sharifa, A. M.; Mohamadb, N.; Ullah, S. Tuning ionic liquids for natural gas dehydration using COSMO-RS methodology. J. Nat. Gas Sci. Eng. 2015, 27, 1141-1148. (3) Shi, L.; Wang, C.; Zou, C. Corrosion failure analysis of L485 natural gas pipeline in CO2 environment. Eng. Failure Anal. 2014, 36, 372-378. (4) Caputo, F.; Cascetta, F.; Lamanna, G.; Rotondo, G.; Soprano, A. Estimation of the damage in a natural gas flow line caused by the motion of methane hydrates. J. Nat. Gas Sci. Eng. 2015, 26, 1222-1231. (5) Netusil, M.; Ditl, P. Comparison of three methods for natural gas dehydration. J. Nat. Gas Chem. 2011, 20, 471-476. (6) Tagliabue, M.; Farrusseng, D.; Valencia, S.; Aguado, S.; Ravon, U.; Rizzo, C.; Corma, A.; Mirodatos, C. Natural gas treating by selective adsorption: material science and chemical engineering interplay. Chem. Eng. J. 2009, 155, 553-566. (7) Bernardo, P.; Drioli, E.; Golemme, G. Membrane gas separation: A review/state of the art. Ind. Eng. Chem. Res. 2009, 48, 4638-4663. (8) Yang, Y.; Wen, C.; Wang, S.; Feng, Y.; Witt, P. The swirling flow structure in supersonic separators for natural gas dehydration. Rsc Adv. 2014, 4, 52967-52972. (9) Bahadori, A.; Vuthaluru, H. B. Simple methodology for sizing of absorbers for TEG (triethylene glycol) gas dehydration systems. Energy. 2009, 34, 1910-1916. (10) Bahadori, A.; Vuthaluru, H. B. Rapid estimation of equilibrium water dew point of natural gas in TEG dehydration systems. J. Nat. Gas. Sci. Eng. 2009, 1, 68-71. (11) Heym, F.; Haber, J.; Korth, W.; Etzold, B.J.; Jess, A. Vapor pressure of water in mixtures with hydrophilic ionic liquids-A contribution to the design of processes for drying of gases by absorption in ionic liquids. Chem. Eng. Technol. 2010, 33, 1625-1634. (12) Lei, Z.; Li, C.; Chen, B. Extractive distillation: A review. Sep. Purif. Rev. 2003, 32, 121-213. (13) Wasserscheid, P.; Keim, W. Ionic liquids-new “solutions” for transition metal catalysis. Angew. Chem. Int. Ed. 2000, 39, 3772-3789. (14) Eckert, F.; Klamt, A. Fast solvent screening via quantum chemistry: COSMO-RS approach. AIChE J. 2002, 48, 369-385. 19

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(15) Lei, Z.; Chen, B.; Li, C.; Liu, H. Predictive molecular thermodynamic models for liquid solvents, solid salts, polymers, and ionic liquids. Chem. Rev. 2008, 108, 1419-1455. (16) Diedenhofen, M.; Klamt, A. COSMO-RS as a tool for property prediction of IL mixtures-A review. Fluid Phase Equilib. 2010, 294, 31-38. (17) Klamt, A. Conductor-like screening model for real solvents: A new approach to the quantitative calculation of solvation phenomena. J. Phys. Chem. 1995, 99, 2224-2235. (18) Grensemann. H.; Gmehling, J. Performance of a conductor-like screening model for real solvents model in comparison to classical group contribution methods. Ind. Eng. Chem. Res. 2005, 44, 1610-1624. (19) Klamt, A.; Jonas, V.; Bürger, T.; Lohrenz, J. C. W. Refinement and parametrization of COSMO-RS. J. Phys. Chem. A. 1998, 102, 5074-5085. (20) Lei, Z.; Zhang, J.; Li, Q.; Chen, B. UNIFAC model for ionic liquids. Ind. Eng. Chem. Res. 2009, 48, 2697-2704. (21) 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. (22) Fogg, P. G. T.; Gerrard, W. Solubility of Gases in Liquids: A Critical Evaluation of Gas/Liquid Systems in Theory and Practice; John Wiley &Sons: New York, 1991. (23) Campos, C. E. P. S.; Penello, J. R.; Pessoa, F. L. P.; Uller, A. M. C. Experimental measurement and thermodynamic modeling for the solubility of methane in water and hexadecane. J. Chem. Eng. Data. 2010, 55, 2576-2580. (24) Chapoy, A.; Coquelet, C.; Richon, D. Solubility measurement and modeling of water in the gas phase of the methane/water binary system at temperatures from 283.08 to 318.12 K and pressures up to 34.5 MPa. Fluid Phase Equilib. 2003, 214, 101-117. (25) Chapoy, A.; Mohammadi, A. H.; Richon, D.; Tohidi, B. Gas solubility measurement and modeling for methane-water and methane-ethane-butane-water systems at low temperature conditions. Fluid Phase Equilib. 2004, 220, 111-119. (26) Kim, Y. S.; Ryu, S. K.; Yang, S. O.; Lee, C. S. Liquid water-hydrate equilibrium measurements and unified predictions of hydrate-containing phase equilibria for methane, ethane, propane, and their mixtures. Ind. Eng. Chem. Res. 2003, 42, 2409-2414. (27) Kumełan, J.; Kamps, Á. P. S.; Tuma, D.; Maurer, G. Solubility of the single gases methane and xenon 20

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in the ionic liquid [hmim][Tf2N]. Ind. Eng. Chem. Res. 2007, 46, 8236-8240. (28) Liu, X.; Afzal, W.; Prausnitz, J. M. Solubilities of small hydrocarbons in tetrabutylphosphonium bis(2,4,4-trimethylpentyl)

phosphinate

and

in

1-ethyl-3-methylimidazolium

bis(trifluoromethylsulfonyl) imide. Ind. Eng. Chem. Res. 2013, 52, 14975-14978. (29) Ou, W.; Geng, L.; Lu, W.; Guo, H.; Qu, K.; Mao, P. Cover image quantitative Raman spectroscopic investigation of geo-fluids high-pressure phase equilibria: Part II. Accurate determination of CH4 solubility in water from 273 to 603 K and from 5 to 140 MPa and refining the parameters of the thermodynamic model. Fluid Phase Equilib. 2015, 391, 18-30. (30) Raeissi, S.; Peters C. J. High pressure phase behaviour of methane in 1-butyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide. Fluid Phase Equilib. 2010, 294, 67-71. (31) Serra, M. C. C.; Pessoa. F. L. P.; Palavra, A. M. F. Solubility of methane in water and in a medium for the cultivation of methanotrophs bacteria. J. Chem. Thermodyn. 2006, 38, 629-1633. (32) Wang, Y.; Han, B.; Yan, H.; Liu, R. Solubility of CH4 in the mixed solvent t-butyl alcohol and water. Thermochim. Acta. 1995, 253, 327-334. (33) Yang, S. O.; Cho, S. H.; Lee, H.; Lee, C. S. Measurement and prediction of phase equilibria for water + methane in hydrate forming conditions. Fluid Phase Equilib. 2001, 185, 53-63. (34) Gmehling, J.; Rasmussen, P.; Fredenslund, A. Vapor-liquid equilibria by UNIFAC group contribution. 2. Revision and extension. Ind. Eng. Chem. Proc. Des. Dev. 1982, 21, 118-127. (35) Nocon, G.; Weidlich, U.; Gmehling, J.; Onken, U. Prediction of gas solubilities by a modified UNIFAC-equation. Ber. Bunsen-Ges. Phys. Chem. 1983, 13, 381-392. (36) Lei, Z.; Yuan, J.; Zhu, J.; Solubility of CO2 in propanone, 1-ethyl-3-methylimidazolium tetrafluoroborate, and their mixtures. J. Chem. Eng. Data. 2010, 55, 4190-4194. (37) Lei, Z.; Dai, C.; Yang, Q.; Zhu. J.; Chen, B. UNIFAC model for ionic liquid-CO (H2) systems: An 120experimental and modeling study on gas solubility. AIChE J. 2014, 60, 4222-4231. (38) Li, H.; Fu, Y.; Li, X.; Gao, X. State-of-the-art of advanced distillation technologies in China. Chem.. Eng. Technol. 2016, 39, 815-833. (39) Meine, N.; Benedito, F.; Rinaldi, R. Thermal stability of ionic liquids assessed by potentiometric titration. Green Chem. 2010, 12, 1711-1714. (40) Wendler, F.; Todi, L.N.; Meister, F. Thermostability of imidazolium ionic liquids as direct solvents for cellulose. Thermochim. Acta. 2012, 528, 76-84. 21

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(41) Huddleston, J. G.; Visser, A. E.; Reichert, W. M.; Willauer, H. D.; Broker, G. A.; Rogers, R. D. Characterization and comparison of hydrophilic and hydrophobic room temperature ionic liquids incorporating the imidazolium cation. Green Chem. 2001, 3, 156-164. (42) Shiflett, M. B.; Yokozeki, A. Phase behavior of carbon dioxide in ionic liquids: [emim][Acetate], [emim][Trifluoroacetate], and [emim][Acetate] + [emim][Trifluoroacetate] Mixtures. J. Chem. Eng. Data. 2009, 54, 108-114. (43) Strigle, R.F. Packed Tower Design and Applications: Random and Structured Packing, second ed.; Gulf Publishing Company: Houston, 1994. (44) Kotas, T. J. The exergy method of thermal plant analysis; Krieger Publishing Company: Malabar, FL, 1995.

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Table Captions

Table 1. The Group Interaction Parameters (amn and anm) among CH4, IL, and H2O for the UNIFAC-Lei Model

Table 2. Comparison of CH4 Solubility Between Experimental Data and Predicted Results by UNIFAC-Lei Model

Table 3. Optimum Operating Conditions for CH4 Dehydration Processes with [EMIM][Tf2N] and TEG

Table 4. Comparison of Process Simulation Results Between [EMIM][Tf2N] and TEG

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Figure Captions Figure 1. The flow chart of experimental apparatus for CH4 dehydration. (1) gas drying column; (2) gas moisture meter; (3) pressure and flow regulators; (4) water storage tank; (5) constant-flux pump; (6) IL storage tank; (7) CH4 cylinder; (8) valve.

Figure 2. The common logarithm ( lgS CH 4 /H 2O ) of CH4/H2O selectivity (a) and Henry’s law constants ( lgH H 2O ) of H2O (b) in 252 ILs at 298.15 K calculated by the COSMO-RS model.

Figure 3. σ-Profiles of CH4, H2O, [EMIM]+, and [Tf2N]-(a) and σ-potentials of CH4, H2O, and [EMIM][Tf2N] (b).

Figure 4. Vapor pressures for the H2O + [EMIM][Tf2N] system at different temperatures. ●, 353 K; ◆, 343 K;▼, 333 K; ▲, 313 K; ■, 293 K; dash lines, vapor pressure of pure H2O; solid lines, predicted values by the UNIFAC-Lei model.

Figure 5. Solubility of CH4 in [EMIM][Tf2N] and in the [EMIM][Tf2N] + H2O mixture at 313.2 K (a), 333.2 K (b), and 353.2 K (c). Solid lines, predicted by the UNIFAC-Lei model; scattered points, experimental data. ■, [EMIM][Tf2N]; ●, 98 wt% [EMIM][Tf2N] + 2 wt% H2O.

Figure 6. Influence of the volume flow rate VIL (NTP) (a) and the water content (mass fraction) wH2O,IL in the inlet IL (b) on the water content (mole fraction) y1 in the outlet gas product. Solid lines, calculated values by the EQ stage model; scattered points, experimental data.

Figure 7. CH4 dehydration processes with the IL [EMIM][Tf2N] (a) and TEG (b).

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Figure 8. Influence of mass flow rate mIL , number of theoretical stages Nt (a), absorber temperature T1 (b), flash drum temperature T2 (c), and flash drum pressure P2 (d) on the water content y1 (mole fraction) in the outlet gas product. The dotted line in the Y-axis direction, selected operation parameters; the dotted line in the X-axis direction, targeted water content. •

(a) T1 = 20 ℃, P1 = 0.1 MPa, T2 = 140 ℃, P2 = 0.05 atm; (b) P1 = 0.1 MPa, Nt = 5, mIL = 4000 kg·h-1, •

T2 = 140 ℃, P2 = 0.05 atm; (c) T1 = 20 ℃, P1 = 0.1 MPa, Nt = 5, mIL = 4000 kg·h-1, P2 = 0.05 atm; (d) •

T1 = 20 ℃, P1 = 0.1 MPa, Nt = 5, mIL = 4000 kg·h-1, T2 = 140 ℃.

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Table 1. The Group Interaction Parameters (amn and anm) among CH4, IL, and H2O for the UNIFAC-Lei Model m

n

αmn

αnm

CH4

[MIM][Tf2N]

2588.07a

434.02a

CH4

H2O

509.89a

999.81a

CH4

CH2

-399.5

1161

H2 O

[MIM][Tf2N]

-60.36

392.98

CH2

[MIM][Tf2N]

400.89

145.8

CH2

H2O

1318

300

a

Group binary interaction parameters obtained in this work; others are from references.20,34,35

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Table 2. Comparison of CH4 Solubility Between Experimental Data and Predicted Results by UNIFAC-Lei Model Solvents

T range (K)

P range (bar)

[EMIM][Tf2N]

299.00-334.00

10.43-39.53

[HMIM][Tf2N]

333.15-413.25

[BMIM][Tf2N]

ARD

No. of data points

Refs.

15.31

20

(28)

14.40-93.00

13.03

18

(27)

300.31-453.15

15.01-161.05

16.93

82

(30)

H2O

283.13-313.11

9.77-179.98

23.31

12

(25)

H2O

276.20-298.15

23.00-166.00

17.44

18

(26)

H2O

273.10-298.20

23.30-126.80

15.00

26

(33)

H2O

303.20-323.20

1.12-6.38

23.50

9

(23)

H2O

293.15-323.15

1.01

14.25

13

(31)

H2O

288.15-298.15

11.73-50.87

24.07

15

(32)

H2O

283.08-318.12

9.92-251.50

19.11

30

(24)

H2O

273.15-313.15

50.00-400.00

23.09

22

(29)

(%)

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Table 3. Optimum Operating Conditions for CH4 Dehydration Processes with [EMIM][Tf2N] and TEG Absorbents

Contents Columns

Streams

Absorption column Temperature (℃) Pressure (atm) Total stages Flash drum /Desorption column Temperature (℃) Pressure (atm) Total stages Moles reflux ratio Distillate rate (kmol·h-1) Feed stream Temperature (℃) Pressure (atm) Component flowrate (kg·h-1) CH4 H2O Solvent stream Temperature (℃) Pressure (atm) Component flowrate (kg·h-1) [EMIM][Tf2N] H2O TEG

[EMIM][Tf2N]

TEG

20 1.0 5

20 1.0 5

140 0.05 -

204 1 3 0.6 0.71

20 1.0

20 1.0

986.54 13.46

986.54 13.46

20 1.0

20 1.0

3998.88 1.12 -

26.52 3973.48

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Table 4. Comparison of Process Simulation Results Between [EMIM][Tf2N] and TEG Contents Streams

Absorbents Product stream

Bottom stream in gas drying column

Top stream of flash drum / desorption column

Recycled stream

Heat duty

solvent

Flash drum

[EMIM][Tf2N]

TEG

Temperature (℃)

20

20

Mass flow rate (kg·h-1) Water content (mole fraction) Temperature (℃) Composition (mass fraction) CH4 H2O [EMIM][Tf2N] TEG Temperature (℃) Mass flowrate (kg·h-1) Composition (mass fraction) CH4 H2O [EMIM][Tf2N] TEG Temperature (℃) Mass flowrate (kg·h-1) Composition (mass fraction) CH4 H2O [EMIM][Tf2N] TEG Heat duty (kW)

985.21 597 ppm 25

987.29 1587 ppm 24

610 ppm 0.003 0.996 140 15.19

253 ppm 0.010 0.991 97 14.16

0.161 0.839 140 4000.00

0.072 0.813 0.115 204 3998.55

995 ppb 256 ppm 1 39.38

15 ppb 6224 ppm 0.993 -

Desorption column Condenser (kW) Heat exchanger

Cooler 1

Cooler 2

-

-8.18

Reboiler (kW)

-

60.74

Cool stream inlet temperature (℃)

25

24

Cool stream outlet temperature (℃)

120

186

Heat duty (kW)

152.27

433.99

Inlet temperature (℃)

45

45

Outlet temperature (℃)

20

20

Heat duty (kW)

-37.94

-57.48

Temperature of outlet (℃)

20

20

Heat duty (kW)

-9.61

-0.29

-47.55 10.96 0.12 1.16 m3 -

-65.96 22.79 3.41 m3

a

Total cooling duty (kW) Exergy consumption (kW) Energy consumption of vacuum pump (kW) Flash drum volume (m3) Desorption column volume (m3) a

The total cooling duty with IL and TEG refers to the cooling energy consumed in cooler 1, cooler 2, and the solvent regeneration system (condenser). 29

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2 8 7

6

4

water-loaded IL

3

5

Figure 1. The flow chart of experimental apparatus for CH4 dehydration. (1) gas drying column; (2) gas moisture meter; (3) pressure and flow regulators; (4) water storage tank; (5) constant-flux pump; (6) IL storage tank; (7) CH4 cylinder; (8) valve.

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(a)

P666,14 5-6 4-5 3-4 2-3 1-2 0-1

P4444 BMPYR

102

OMIM BMPY HMIM

103

BPY

104

BMIM C3MIM

Cation

N4111

EPY

105

EMIM HEMIM

bFAP

SbF6

eFAP

PF6

TCB

Tf2N

BF4

CF3SO3

SCN

CH3SO4

NO3

DCA

TFA

TOS

CH3SO3

CL

DEPO4

Ac

MMIM

Anion

10

-1

10-2

10-3 10-4

Anion

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P666,14 P4444 BMPYR OMIM BMPY HMIM N4111 BPY BMIM C3MIM EPY EMIM MMIM HEMIM

-1-0 -2--1 -3--2 -4--3 -5--4

Cation

(b)

bFAP eFAP SbF6 PF6 Tf2N TCB BF4 CF3SO3 SCN CH3SO4 DCA NO3 TOS TFA CH3SO3 CL DEPO4 Ac

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

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Energy & Fuels

(c) P666,14

10

BMPYR

2-2.5

P4444

1.5-2

OMIM

1-1.5

BMPY

0.5-1

HMIM

N4111

101.5

BPY

Cation

BMIM

C3MIM EMIM EPY 2

SbF6

PF6

MMIM BF4

SCN

TCB

DCA

NO3

CF3SO3

CH3SO4

TFA

TOS

Tf2N

CH3SO3

Ac

DEPO4

CL

eFAP

10 bFAP

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

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HEMIM

Anion

Figure 2. The common logarithm ( lgS CH 4 /H 2O ) of CH4/H2O selectivity (a), Henry’s law constants (MPa) ( lgH H 2 O ) of H2O (b) and Henry’s law constants ( lgH H 2 O ) of CH4 (c) in 252 ILs at 298.15 K calculated by the COSMO-RS model.

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35 +

[EMIM] [Tf2N] CH4 H2O

30 25

p (σ)

20 15 10 5 (a)

0 -0.03

-0.02

-0.01

0.00

0.01

0.02

0.03

σ (e/Å2)

0.8

0.4

Decreasing interaction

H2O CH4 [EMIM][Tf2N]

0.6

0.2 0.0 -0.2

Increasing interaction

µ(σ) [kcal/(mol·Å2)]

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

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-0.4 -0.6

(b)

-0.8 -0.03

-0.02

-0.01

0.00

0.01

0.02

0.03

σ (e/Å2)

Figure 3. σ-Profiles of CH4, H2O, [EMIM]+, and [Tf2N]-(a) and σ-potentials of CH4, H2O, and [EMIM][Tf2N] (b).

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55 50 45 40 35

P /kPa

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

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30 25 20 15 10 5 0 0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

x1

Figure 4. Vapor pressures for the H2O + [EMIM][Tf2N] system at different temperatures. ●, 353 K; ◆, 343 K;▼, 333 K; ▲, 313 K; ■, 293 K; dash lines, vapor pressure of pure H2O; solid lines, predicted values by the UNIFAC-Lei model.

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0.09 0.08

(a)

0.07 0.06

x1

0.05 0.04 0.03 0.02 0.01 0.00

0

1

2

3

4

5

6

6

7

7

P/MPa

0.08 0.07

(b)

0.06 0.05

x1

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

Energy & Fuels

0.04 0.03 0.02 0.01 0.00

0

1

2

3

4

5

P/MPa

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8

Energy & Fuels

0.08 0.07

(c)

0.06 0.05

x1

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

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0.04 0.03 0.02 0.01 0.00

0

1

2

3

4

5

6

7

8

P/MPa

Figure 5. Solubility of CH4 in [EMIM][Tf2N] and in the [EMIM][Tf2N] + H2O mixture at 313.2 K (a), 333.2 K (b), and 353.2 K (c). Solid lines, predicted by the UNIFAC-Lei model; scattered points, experimental data. ■, [EMIM][Tf2N]; ●, 98 wt% [EMIM][Tf2N] + 2 wt% H2O.

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1050

(a)

900

y1 (ppm)

750 600 450 300 0

5

10

15

20

25

30

VIL (mL·min-1)

1400 1200 1000 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

Energy & Fuels

800 600 400 (b)

200 0

200

400

600

800

wH2O, IL (ppm)

Figure 6. Influence of the volume flow rate VIL (NTP) (a) and the water content (mass fraction) wH2O,IL in the inlet IL (b) on the water content (mole fraction) y1 in the outlet gas product. Solid lines, calculated values by the EQ stage model; scattered points, experimental data.

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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

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CH4 product IL

Cooler 2 Gas drying column

Feed

H2O Flash

Heat exchanger

Pump 1

Pump 2

(a)

Cooler 1

H2O

CH4 product TEG

Cooler 2 Desorption column Gas drying column

Reboiler

Feed Heat exchanger

Pump 1

Cooler 1

(b)

Figure 7. CH4 dehydration processes with the IL [EMIM][Tf2N] (a) and TEG (b).

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7000 Nt=3 Nt=5 Nt=7 Nt=9 Nt=11

6000

y1 (ppm)

5000 4000 3000 2000

(a)

1000 0

1000

2000

3000

4000

5000

6000

7000



mIL (kg·h-1)

5400 4800

y1 (ppm)

4200 3600 3000 2400 1800 1200

(b)

600 0

0

10

20

30

40

T1 (℃) 2200 2000

(c)

1800 1600

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

Energy & Fuels

1400 1200 1000 800 600 400 90

100

110

120

130

140

150

160

T2 (℃)

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170

180

Energy & Fuels

1600 1400 1200

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

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1000 800 600 400

(d)

200 0 0.00

0.05

0.10

0.15

P2 (atm)



Figure 8. Influence of mass flow rate mIL (a), number of theoretical stages Nt (a), absorber temperature T1 (b), flash drum temperature T2 (c), and flash drum pressure P2 (d) on the water content y1 (mole fraction) in the outlet gas product. The dotted line in the Y-axis direction, selected operation parameters; the dotted line in the X-axis direction, targeted water content. •

(a) T1 = 20 ℃, P1 = 0.1 MPa, T2 = 140 ℃, P2 = 0.05 atm; (b) P1 = 0.1 MPa, Nt = 5, mIL = 4000 kg·h-1, •

T2 = 140 ℃, P2 = 0.05 atm; (c) T1 = 20 ℃, P1 = 0.1 MPa, Nt = 5, mIL = 4000 kg·h-1, P2 = 0.05 atm; (d) •

T1 = 20 ℃, P1 = 0.1 MPa, Nt = 5, mIL = 4000 kg·h-1, T2 = 140 ℃.

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