Facilitated transport membrane with functionalized ionic liquid carriers for CO2/N2, CO2/O2, and CO2/air separations

Yun-Yang Lee a, Nalinda P. Wickramasinghe b, Ruth Dikki a, Darrell L. Jan c and Burcu Gurkan *a
aDepartment of Chemical and Biomolecular Engineering, Case Western Reserve University, Cleveland, OH 44106, USA. E-mail: yxl2286@case.edu; beg23@case.edu; rcd82@case.edu
bNortheast Ohio High Field NMR Facility, Case Western Reserve University, Cleveland, OH 44106, USA. E-mail: npw8@case.edu
cAmes Research Center, National Aeronautics and Space Administration, Moffett Field, CA 94043, USA. E-mail: darrell.l.jan@nasa.gov

Received 10th June 2022 , Accepted 23rd August 2022

First published on 23rd August 2022


Abstract

CO2 separations from cabin air and the atmospheric air are challenged by the very low partial pressures of CO2. In this study, a facilitated transport membrane (FTM) is developed to separate CO2 from air using functionalized ionic liquid (IL) and poly(ionic liquid) (PIL) carriers. A highly permeable bicontinuous structured poly(ethersulfone)/poly(ethylene terephthalate) (bPES/PET) substrate is used to support the PIL–IL impregnated graphene oxide thin film. The CO2 separation performance was tested under a mixture feed of CO2/N2/O2/H2O. Under 410 ppm of CO2 at 1 atm feed gas, CO2 permanence of 3923 GPU, and CO2/N2 and CO2/O2 selectivities of 1200 and 300, respectively, are achieved with helium sweeping on the permeate side. For increased transmembrane pressure (>0 atm), a thicker PIL–IL/GO layer was shown to provide mechanical strength and prevent leaching of the mobile carrier. CO2 binding to the carriers, ion diffusivities, and the glass transition temperature of the PIL–IL gels were examined to determine the membrane composition and rationalize the superior separation performance obtained. This report represents the first FTM study with PIL–IL carriers for CO2 separation from air.


Introduction

Removal of metabolically generated carbon dioxide (CO2) from cabin air in spacecraft (2500 ppm CO2)1 is accomplished by sorbents like zeolites1,2 which have high CO2 capacities. However, zeolites, similar to most common metal organic frameworks,3 are not selective to CO2 especially in the presence of moisture and their generation requires significant thermal energy. Furthermore, the temperature swing between room temperature and 300–350 °C creates cracks in the zeolite pellets and dusting.4 The dusting is problematic because it can migrate to small passages, where it can lodge and cause clogging. This is of particular concern in spacecraft since the dust migration in microgravity will be different from what can be observed in ground tests. Therefore, it is desired to develop new sorbents and less energy demanding separation technologies. Similarly, CO2 capture from the atmospheric air, referred as direct air capture (DAC), relies on the selective capture of CO2 from a very dilute concentration (410 ppm CO2) and sequestration of the captured CO2 in order to achieve negative emissions. While carbon capture and sequestration is more efficient to implement at point sources of CO2 emissions, such as power plants, petroleum refinery, and chemical plants where CO2 concentration is higher, there is still a considerable amount of CO2 being emitted from discrete sources that are difficult to decarbonize such as transportation (29%), commercial and residential buildings (13%), and agricultural activities (10%) that total up to 52% of the overall CO2 emissions.5 Therefore, carbon negative technologies such as DAC are essential to stay below the projected 1.5 °C temperature rise globally.6

Simple thermodynamical calculations (see ESI) suggest that the theoretical minimum work for DAC, where CO2 is 410–420 ppm, is almost four times greater than that from post-combustion CO2 capture (PCCC) where the CO2 is about 20%. Accounting for the fluid transportation, compression, heating, and thermal exchange, the overall energy demand for CO2 separation from dilute stream (e.g., 410–2500 ppm) is much greater than the theoretical work. The estimated energy requirement for DAC (410 ppm) and space cabin air (2500 ppm) is in the range of 200 to 400 kJ per mol CO2,7–10 whereas the energy for PCCC is roughly half of that.10 The state-of-the-art DAC technologies, with a few demonstrations in pilot scale,11 rely on either the solid adsorption or liquid absorption of CO2. Liquid systems pass air through solutions like aqueous amines12 or alkali metal hydroxides.13,14 Solid systems utilize supported amine sorbents15–17 and humidity-swing quaternary ammonium based anion-exchange resins.18,19 However, these sorption techniques are energy-intensive processes, since the strong binding of amine and CO2 (C–N bond, about −80 kJ mol−1)20 requires a temperature of around 120 °C to cleave off CO2 for sorbent regeneration. Similarly, the calcination temperature of above 700 °C for alkali/alkaline earth carbonates21 results in a high energy demand.

In contrast to absorption and adsorption technologies, membrane separation is a non-equilibrium process that operates by mass control22 and under isothermal conditions with typically higher energy efficiency. It is also a promising technology for its high modularity, process simplicity, and lower operational cost.23 Conventional solution–diffusion (S–D) gas separation membranes rely on the difference in solubility and diffusivity of the target gas over other gas components for separation.24 Recent progresses on the S–D membranes focused on increasing (1) the solubility selectivity toward CO2 over other gases by the incorporation of highly polar or ionic components;25–29 and (2) the diffusivity selectivity for CO2 sieving by rigid polymeric backbones with high free volume.30–34 There is usually a tradeoff between gas permeance and selectivity of a membrane, as described by the Robeson upper-bound.35–37 The S–D type membranes are often implemented as multi-stage membrane systems to achieve the desired separation, which inevitably drives up the energy consumption. Facilitated transport membranes (FTMs) utilize CO2-philic carriers such as amines that chemically bind with CO2, thus enabling CO2 transport by both (1) vehicular motions (CO2 transport in the form of CO2-carrier complexes) and (2) hopping motions (CO2 transport via hopping along a number of CO2-philic sites) of the carriers, along with (3) CO2 diffusion, following the direction of transmembrane CO2 gradient.38 Therefore, the CO2 permeation is significantly improved even under reduced CO2 partial pressures while maintaining a high selectivity.39 Therefore, FTMs perform above the Robeson upper-bound. Amine functionalized polymers are the most common FTMs that are referred as having fixed site carriers. FTMs that incorporate amine-based salts and ionic liquids (ILs) as mobile carriers40–47 are shown to further enhance CO2 transport.48

While FTMs have been studied for CO2 separation from post-combustion flue gas, there are only a few reports that we are aware of discussing their utility relevant for DAC and for CO2 removal from cabin air.49–51 Under DAC and cabin air conditions, there is very small driving force for CO2 transport owing to low concentration, temperature, and humidity; hence, it is extremely challenging to concentrate the CO2 on the effluent side. There has been two reports assessing membrane-based DAC processes by simulations based on (1) a hypothetical non-FTM52 with ultra-high permeance (40[thin space (1/6-em)]000 GPU) and low CO2/N2 selectivity (70); and (2) a hypothetical FTM53 with high permeance (2500 GPU) and high CO2/N2 selectivity (680). In 2022, Sandru et al. fabricated a three-layered composite membrane with an ultrathin surface-grown amine-rich top layer (10 nm) and a thin mid-layer of highly permeable amorphous polytetrafluoroethylene, PTFE, (1 μm) coated over a porous membrane support as the bottom layer (50 μm).54 The fabricated membrane achieved a CO2 permeability of 1000 Barrer (equivalent to 50[thin space (1/6-em)]000 GPU; calculated based on the reported overall membrane thickness of 50 μm) and a CO2/N2 selectivity greater than 1000, with a CO2/N2 feed (10/90, v/v; RH = 100%) at 25 °C. The authors observed no diffusion limitations, unlike the previously reported thicker polyallylamine FTM (1 μm in thickness; 300 GPU and selectivity of 23).55 While this membrane was not tested under conditions relevant to DAC or cabin air, it demonstrates the importance of a thin selective layer and a highly permeable substrate to overcome the selectivity–permeability trade-off.

Lee and Gurkan reported a poly(ionic liquid)–ionic liquid/graphene oxide (PIL–IL/GO) composite membrane in 2021 as the first representative FTM specifically designed for CO2/N2 separation relevant to DAC and CO2 removal from cabin air.56 The PIL–IL carriers were nanoconfined within the GO nano framework (GONF) resulting in a 900 nm-thick CO2 selective layer on an ultrafiltration (UF) membrane substrate. The choice of the mobile carrier, 1-methyl-3-ethylimidazolium 2-cyanopyrrolide, [EMIM][2-CNpyr], enabled the reactivity–mobility balance of CO2 by synergizing the IL's high affinity to CO2 and low viscosity (in comparisons to other reactive ILs). A high CO2 permeance of 3090 GPU coupled with a high CO2/N2 selectivity of 1180 was demonstrated by the PIL–IL/GO FTM under 410 ppm CO2 feed at 25 °C and 40% RH. This performance is superior to other known polyvinylamine and PIL ionomer based FTMs under similar conditions.40,47 Here, we extend this work and report a thin PIL–IL/GO selective layer on a bPES/PET substrate with well-interconnected pores as highly permeable FTM that demonstrates high performance of CO2 separation from CO2/N2/O2/H2O mixture at extremely low CO2 partial pressures. The impacts of oxygen and water on CO2 capacity and the diffusivity of the carrier were examined by 13C-NMR and 1H-DOSY NMR. The specific interactions between the GONF and the PIL–IL gel was characterized by HSBC NMR and FTIR. This study reports on the CO2/O2 selectivity and tunability of the CO2/(N2 + O2) separation ratio, and the mechanical strength against a transmembrane pressure for PIL–IL/GO type FTMs through the modifications of the PIL–IL composition and GONF layer thickness.

Experimental section

Materials

The IL precursor, 1-ethyl-3-methylimidazolium iodide ([EMIM][I], >98%) was purchased from TCI America. The ACS grade reagent methanol, isopropanol, and acetone were purchased from Alfa Aesar via Thermo Scientific. Anion precursor pyrrole-2-carbonitrile (99%) and Amberlite® IRN-78 anion exchange resin (AER) in [OH] form were purchased from Thermo Scientific. The poly(ionic liquid) (PIL) precursor, poly(diallydimethylammonium chloride) (P[DADMA][Cl], Mw 400–500 kDa, ∼20 wt% aqueous solution) and paramagnetic compound chromium acetylacetonate (Cr(ACAC)3, 97%) were purchased from Millipore-Sigma. The AER was washed with methanol for at least three times and vacuum dried at room temperature before use. Solid P[DADMA][Cl] was acquired by directly pulling vacuum on the aqueous solution at 40 °C for three days and 80 °C for a day. The deuterated solvent DMSO-d6 (25 ml, 99.8%) was purchased from Thermo Scientific. The NMR tubes (5 mm OD; 7′′ L; wall thickness: 0.38 mm) with coded closed caps were purchased from Bruker. The NMR coaxial tube set (inner cell: NE-5-CIC; outer cell: NE-UPE-7) were purchased from New Era Enterprises, Inc.

The ultrafiltration (UF) substrate membrane (LY; nominal cutoff of 100 kDa) with poly(ethersulfone) (PES) skin layer and poly(ethylene terephthalate) (PET) nonwoven substrate was purchased from Synder Filtration. The bPES/PET was prepared following the procedure as described by Pang et al.57 Briefly, the highly gas permeable substrates with bicontinuous structured skin layer (with pore size of 30–40 nm) were fabricated by water-vapor induced phase separation, followed with water immersion. This highly permeable membrane is abbreviated as bPES/PET to make a distinction from the commercial UF substrate. Single-layer graphene oxide (GO) dispersion (5 mg ml−1) was purchased from ACS Material (synthesized by modified Hummers’ method and have an average width and thickness of 0.3 μm and 0.8 nm, respectively).

Tank gases of nitrogen (N2; Ultra High Purity (UHP)), argon (Ar; UHP), helium (He; UHP), carbon dioxide (CO2; bone dry), hydrogen (H2; UHP), and synthetic air (synthetic blend of N2 (80%) and O2 (20%), with less than 1 ppm of CO2) were purchased from Airgas.

Methods

Synthesis of [EMIM][2-CNpyr] (IL) and P[DADMA][2-CNpyr] (PIL). The synthesis of IL and PIL started with the anion exchange step of the precursor materials of [EMIM][I] (10 g in 100 ml methanol) and P[DADMA][Cl] (10 g in 100 ml methanol), respectively, into OH intermediates. The use of AER to precursor was monitored to be around 5 mg AER per mmole precursor. The residual halide content in the intermediate solution was tested by 0.1 N silver nitrate (AgNO3) solution and confirmed to be low (<1000 ppm) from the lack of visual white precipitates of silver halides. The halide contents were further determined to be lower than 0.25% (detection limit) by combustion ion chromatography. The intermediate solutions of IL and PIL in [OH] form were separately mixed with the anion precursor pyrrole 2-carbonitrile (with cation to anion precursor molar ratio of 1[thin space (1/6-em)]:[thin space (1/6-em)]1.02 mol) for acid–base neutralization reaction to complete overnight. The excess solvent was removed from the resulting solutions by rotary evaporation at 60 °C. Samples were then vacuum dried at 80 °C for overnight to remove residual water. The molecular structure of the synthesized PIL and IL were characterized and confirmed by 1H-NMR and heteronuclear single quantum coherence (HSQC), heteronuclear multiple bond correlation (HMBC) on a Bruker 500 MHz (Fig. S1 and S2).

Fabrication of PIL–IL/GO composite membrane

Both UF and bPES/PET membrane substrates were rinsed with methanol/DI water (1[thin space (1/6-em)]:[thin space (1/6-em)]1, v/v) for at least three times to remove residual salt crystals from the substrate. This step is important as these contaminants can change the surface charge of GO flakes in the suspension in the next step, causing coagulation and failure of the GONF layer deposition. The membranes were dried in vacuum at 40 °C overnight prior to use. The GO in water dispersion (0.2 mg ml−1 and 2 mg ml−1) were prepared by diluting the purchased GO solution (5 mg ml−1) with DI water and sonication. The GONF layer was deposited over the substrates by vacuum filtering the GO suspension on top of the membrane substrate (with level accuracy checked) for roughly 5–10 min. To ensure even coverage and a final GONFL layer with homogenous thickness, the leveling of the membrane was confirmed to be perfectly horizontal. The deposited GONF layer was then impregnated by the PIL–IL gel by drop casting. The PIL–IL casting solution was prepared by mixing 0.2 mg ml−1 of PIL and 20 mg ml−1 of IL in methanol. The fabricated PIL–IL/GO on bPES/PET membranes were allowed to dry under ambient air and were kept under vacuum at ambient temperature before use.

Materials characterization

The Fourier-Transformed Infrared (FTIR) spectra of the IL, PIL, and membranes were taken on Nicolet iS50 (Thermo Scientific) using a diamond crystal attenuated total reflectance (ATR) unit. Water content of the ILs were confirmed to be <1000 ppm by a coulometric Karl Fischer titrator (Metrohm; 889D). Viscosity of the IL was measured with a viscometer (RheoSense; microVisc) equipped with microchannel chips (Rheosense A05, A10, and B20). The phase transition of PIL–IL gels was performed with a DSC (Mettler Toledo DSC3), where the PIL–IL gels (∼15 mg) were pre-loaded into Al pans and sealed in Ar atmosphere glovebox (VTI; H2O and O2 < 0.1 ppm). The sample pans were first held at 80 °C (5 min), then cooled to −90 °C and held for 50 min, and finally heated back to 80 °C with a rate of 10 °C min−1 under N2 for three cycles. No differences were observed among the cycles and therefore only the glass transition temperature (Tg) of the third cycle is reported. The surface morphology and cross-sectional topography of the membranes were taken by field emission scanning electron microscopy (FESEM; ThermoFisher Apreo 2S). All membrane samples were sputtered with about 5 nm Pd prior to analysis for high conductivity and better image resolution.

CO2 binding capacity

The CO2/N2/O2 gas mixture was prepared by mixing the CO2 with the as-purchased synthetic air (N2/O2) by mass flow controllers (MFCs; Brooks 5850i) with Labview® via data acquisition units (DAQ; National Instrument 782604-01). The humidity control was achieved by a water bubbler. For the precise control of temperature, the gas lines, including the water bubbler, was kept inside an incubator (HettCube 400R; Across International LLC). The mixing of the gases for the desired compositions of 410, 1000, 2500, 5000, 10[thin space (1/6-em)]000, and 20[thin space (1/6-em)]000 ppm of CO2 at 22 °C and 40% relative humidity level (40% RH at 22 °C refers to 7.9 Torr or 10.6 mbar) was done in a 300 mL metal chamber (Swagelok) within the incubator. The gas flow rate was measured by ADM 2000 Flowmeter (J&W Scientific Inc., acquired by Agilent). A CO2 analyzer (SBA-5, PPSystems Inc.) with a detection range of 0 to 20[thin space (1/6-em)]000 ppm was used to confirm the CO2 concentration in the prepared gas mixtures. To determine the CO2 absorption capacity of the IL, the gas mixture with the set CO2 content (200 ml min−1) was contacted with the IL (1 g) under 60 rpm agitation in a glass vial (20 ml) for at least 6 h at 22 °C for equilibrium. The equilibrium for CO2 saturation was reached within 2–3 h, whereas the equilibrium for the set relative humidity took longer. Therefore, a wait time of 6 h was allowed to ensure the system reached thermodynamic equilibrium. The binding capacity between CO2 and IL carrier was studied by quantitative 13C-NMR. Following CO2 absorption, 20 mg of the IL was sampled into 0.6 ml of 0.1 M Cr(ACAC)3 DMSO-d6 solvent and quantification of the CO2–IL complex followed the previously reported method.58 The identified products were identical to our previous report;58 briefly the peaks at 146, 154, and 158 ppm were assigned to carbamate, carboxylate, and bicarbonate complexes, respectively.

Self-ion diffusivities

Self-diffusion coefficient of the IL was measured by Diffusion-Ordered Spectroscopy (DOSY) on the same 500 MHz NMR. About 0.3 ml of DMSO-d6 was loaded into the inner cell and the top was flame sealed (or sealed with epoxy resin). About 1.5 ml of the CO2-saturated IL (at 410, 1000, 2500, 5000, 10[thin space (1/6-em)]000, and 20[thin space (1/6-em)]000 ppm CO2 under 40% RH) was transferred into the outer cell and the atmosphere in the headspace was purged with the same atmosphere used for CO2 absorption. The inner cell was then inserted into the outer cell and sealed with coded close cap and parafilm to ensure a gas tight environment. The samples were measured using bipolar gradient pulse sequence (ledbpg2s) and the Z-gradient diffusion probe (Fig. S3a). The diffusion times (Δ) and gradient pulse duration (δ) were optimized in subsequent experiments according to practical needs, until full exponential decay pattern of magnetization was observed within 16 pulse gradient strengths (from 2% to 98%) (Fig. S3b and S4a). The isotopic self-diffusivity (D) of ions was calculated using eqn (1)via MestReNova.
 
image file: d2nr03214g-t1.tif(1)
where γ is the gyromagnetic ratio, g is the magnitude of the gradient pulse, δ is the duration of the gradient pulse, and Δ is the interval (drifting or diffusion time) between two gradient pulses in the opposite direction. M0 is the strength of magnetization without pulse field gradient applied, whereas M(g) is the measured magnetization that exponentially decay as a function of applied pulse field gradient strength. An example of the calculated 1H-DOSY is shown in Fig. S4b.

Membrane tests

The gas separation performance of the PIL–IL/GO composite membrane was tested under both sweep and vacuum modes. The membrane was placed in between two aluminum foils and fastened in a stainless-steel permeation cell (Advantec). The membrane module along with the bubbler and gas mixing chamber were kept within the temperature and humidity-controlled incubator (HettCube 400R; Across International LLC). Simulated CO2/N2/O2/H2O feed gas of 410, 1000, 2500, 5000, and 10[thin space (1/6-em)]000 ppm CO2 with various humidity level were prepared by fine tuning the gas flow rate of the anhydrous CO2, anhydrous synthetic air (N2/O2 = 80/20), and moisture saturation by passing the specific gas streams through the water bubbler. The CO2/N2/H2O feed gas were prepared by mixing anhydrous CO2, anhydrous N2, and moisture saturated N2. Fig. 1 shows the schematic of the membrane testing setup. The permeate side of the membrane module has both the helium sweep (0 Torr gauge pressure; single solid line) and the vacuum (−760 Torr gauge pressure; double solid line) capability for testing of different transmembrane pressures. The flow rate of feed gas and sweep gas were kept constant as 200 cm3 min−1. For tests under the sweeping mode (labeled with pathway ① in Fig. 1), the permeate gas was carried by the He sweep directly to a gas chromatography, GC (Agilent 7890B) with a micro-packed column and thermal conductivity detector (TCD) with He mobile phase for quantitative compositional analysis. For tests under vacuum operation (labeled with pathway ② in Fig. 1), the permeate was first collected by a pump (Agilent; IDP-7 dry scroll pump) under vacuum and then mixed with the He sweep, as shown, for GC analysis. The specific testing conditions are listed in Table 1.
image file: d2nr03214g-f1.tif
Fig. 1 Schematics of the membrane test unit. Permeate gas was collected and sent to gas chromatogram (GC) either by He sweep (path ①) or by vacuum (path ②) for a transmembrane pressure of 0 or 1 atm, respectively. The balance gas of CO2 is either synthetic air (N2/O2 = 80/20) or N2 for the CO2/N2/O2/H2O or CO2/N2/H2O mixtures, respectively.
Table 1 Fabricated FTM specifications and the membrane testing conditions
Membrane substrate
Membrane # i ii iii iv v
Substrate UF bPES/PET
Membrane area 5 cm2
Selective layer
PIL–IL/GO (mg–mg/mg) 0.2–20/0.2 0.4–40/0.4 0.5–50/0.5 1.25–3.75/1
Thickness (μm) 0.9 1.4 1.6 2.0
Membrane testing condition
Feed; sweep 200 cm3 min−1; 200 cm3/min
CO2 in feed (ppm) 410, 2500, and 10[thin space (1/6-em)]000 (1%), CO2 balanced with N2 or synthetic air (N2/O2 = 80/20) at 760 Torr
Transmembrane pressure (ΔP; Torr) 0 760
Temperature (K) 295 and 313 K
Relative humidity (% RH) 0, 40, and 80 40


The gas separation performance was calculated in gas permeance unit (GPU; 1 GPU = 3.348 × 10−10 mol m−2 s−1 Pa−1) by eqn (2).

 
Pi = 106(Qi/(A·Δpi))(2)
where Qi is the permeating rate of component i (cm3 s−1), A is the membrane area (5.06 cm2), and Δpi is the transmembrane partial pressure gradient for component i (cmHg). The uncertainty in permeance (Pi) was determined from the propagation of error analysis using the respective uncertainties in A (±0.11 cm2 based on the measured membrane coupon radius of ±0.2 mm), Δpi (±0.01 cmHg based on the measured concentrations by GC) and the standard deviation in the repeated measurements for Qi (varied for each of the conditions in the range of 0.0001–0.0003 cm3 s−1 for 5 measurements).

The selectivity of CO2 over N2 (αCO2/N2) and CO2 over O2 (αCO2/O2) are calculated using eqn (3) and (4), respectively. The separation ratio (αCO2/(N2+O2)), which is the permeance ratio of CO2 over the sum of N2 and O2, is a parameter that better describes the performance of gas separation in ternary gas mixtures, and it is calculated using eqn (5).

 
image file: d2nr03214g-t2.tif(3)
 
image file: d2nr03214g-t3.tif(4)
 
image file: d2nr03214g-t4.tif(5)

The dependence of CO2 permeance on the CO2 partial pressure of the feed is described by a homogenous reactive diffusion model given in eqn (6).39,47

 
image file: d2nr03214g-t5.tif(6)
where l is the thickness of the membrane, PCO2/l is the measured CO2 permeance, image file: d2nr03214g-t6.tif is a fit parameter that represent the CO2 permeance (GPU) at saturation of carriers (corresponding to the CO2 permeance from S–D pathway), ηCO2 is the efficacy of the facilitated transport pathway, image file: d2nr03214g-t7.tif is the partial pressure of CO2 in the feed when the carriers are saturated with CO2, and image file: d2nr03214g-t8.tif is the set CO2 partial pressure in the feed.

Results and discussion

We first present the results from the characterization of the CO2 carrier, namely the [EMIM][2-CNpyr], in terms of its CO2 binding capacity in the presence of N2 and O2, measurement of ion self-diffusivities, and the thermal behavior of the IL when gelled with PIL. The fabricated membranes with the PIL–IL gel is then described through their topological and cross-sectional features as determined by SEM as well as the specific interactions among the PIL, IL, and GO components examined by FTIR and NMR methods. Finally, the CO2 separation performance of the FTMs under synthetic air feed and at varying temperature and humidity conditions are presented.

CO2 binding and transport

CO2 binding to the IL and the ion diffusivities in the presence of O2 (16–20%) is studied at 22 °C and 40% RH (10.6 mbar). The CO2 absorption by [EMIM][2-CNpyr] has been previously shown56,58 to form carbamate (CO2 binding to the pyrrole anion), carboxylate (CO2 binding to the imidazolium cation), and bicarbonate (CO2 binding to the co-absorbed water) species in both pure CO2 and CO2/N2 mixture gas. The distribution of these products was found to be different at low CO2 partial pressures in CO2/N2 compared to pure CO2. Fig. 2a shows the breakdown of the measured CO2 binding capacities, calculated from the 13C-NMR peak integration of carbamate at 146 ppm (–N–COO), carboxylate at 154 ppm, and bicarbonate (HO–COO) with (red bordered) and without O2 presence (black bordered). At 410 ppm, 40% of the total capacity under pure CO2 is achieved in both cases of with and without O2, showing the strong interactions between the IL and CO2. The capacity at 2500 ppm of CO2 is about 60% of the total capacity under pure CO2 (4.3 mole CO2 per kg sorbent). Within the gas compositions studied, there is no significant influence of O2 on the measured solubility of CO2. The physisorbed of CO2 within the entropic voids of the [EMIM][2-CNpyr] is expected to be less than 3% of the overall CO2 solubility.59 The physiosorbed O2 is expected to be at least a factor lower60 than that of physiosorbed CO2 in ILs in general. This is due to the high polarizability of the quadrupolar CO2 within ionic environments, in contrast to nonpolar O2. The measured bulk viscosity of the IL is also not influenced much with O2 (Fig. S5a). However, as seen in Fig. 2b, the measured ideal diffusivities of the imidazolium cation (filled symbols) and the pyrrolide anion(hollow symbols) demonstrate a weak dependence on O2 (3–5% difference between gray and red symbols) and a strong dependence on CO2.
image file: d2nr03214g-f2.tif
Fig. 2 (a) Measured CO2 capacity of [EMIM][2-CNpyr] at 22 °C and 40% RH (10.6 mbar) by quantitative 13C-NMR with and without (red bordered bars) O2 in the synthetic air feed. The O2 concentration in the gas mixtures was maintained at about 20% with the exception of 200[thin space (1/6-em)]000 ppm CO2 where O2 concentration was 16%. The uncertainty in the reported capacities is calculated from the signal to noise ratio and found to be less than 0.05 mole CO2 per kg sorbent. (b) The dependence of self-diffusivities of [EMIM]+ (filled symbol) and [2-CNpyr] (hollowed symbol) on the CO2 concentration in the absorbed feed gas with (red) and without (gray) O2.

The ion self-diffusivities were measured by 1H-DOSY NMR (Fig. S4). The diffusivity of imidazolium (D+) is higher than the pyrrolide (D) despite the smaller size of the pyrrolide anion. Previous studies61,62 on various ILs reported similar observations and attributed this trend to the hydrogen bonding associated mostly with the anions. The diffusivity of [EMIM], [2-CNpyr], and their CO2-complexes are around 10−7 cm2 s−1 at 22 °C, which is an order of magnitude higher than the reported ion diffusivities for a similar CO2 reactive IL 1-methyl-3-ethylimidazolium acetate (∼10−8 cm2 s−1 with a viscosity of 2700 cP).63 The CO2-complexed ions could not be resolved effectively from their parent ions as they appeared as single peak for both the imidazolium and the pyrrolide. This is attributed to the strong H-bonding58 between the CO2 complexed and un-complexed ions and the fast exchange of proton between these species. The strong dependence of the ideal diffusivity of both the cation (D+) and the anion (D) on the quantity of CO2 within the IL is also indicative of the increased intermolecular hydrogen bonding that leads to slower diffusion. It should be noted that the direct deconvolution of different transport mechanism of CO2 (diffusion, hoping, and vehicular motion) is not possible at this point by 1H-DOSY since CO2 itself is not proton-bearing. Therefore, the measured diffusivities of ions reflect the overall transport of carrier-CO2 complex. The (D+/D) ratio remained in the range of 1.18–1.23 for all of the conditions studied, suggesting no major changes in the solvation environment when O2 is present in the carrier liquid.

The incorporation of PIL into IL provides mechanical reinforcement by forming a non-crosslinked gel. In turn, the IL component acts as the plasticizer for mobility enhancement of the CO2 carrier. Fig. 3 shows the phase-transition of PIL–IL gels in the bulk as characterized by DSC. The plotted red squares are the glass transition temperatures (Tg) of the PIL–IL gels, as determined from the midpoint of the transition region of the DSC curves. The Tg decreases as the amount of PIL decreases. In order to have a mobile carrier within the membrane at cabin or atmospheric temperatures, it is more desirable to have a viscous gel than a glassy one. Therefore, optimization of the PIL–IL content is necessary for a targeted permeance. Too high of a PIL content would increase the membrane resistance while too high of an IL content may not demonstrate sufficient mechanical stability against large transmembrane pressures. We tested the PIL[thin space (1/6-em)]:[thin space (1/6-em)]IL composition of 1:100, similar to our previous work,56 to allow for high carrier mobility, for the sweeping mode of operation and the 1[thin space (1/6-em)]:[thin space (1/6-em)]3 PIL[thin space (1/6-em)]:[thin space (1/6-em)]IL composition to improve stability of the carrier within the membrane architecture against vacuum mode of operation on the permeate side.


image file: d2nr03214g-f3.tif
Fig. 3 The phase diagram of PIL[thin space (1/6-em)]:[thin space (1/6-em)]IL mixture (in molar ratio) measured by DSC, with a scanning rate of 10 °C min−1 under N2. The glass transition (Tg) points are connected with red dashed line as the hypothetical trend of phase-transition of the gel from the glassy state to elastomeric state. The plot of DSC curve from which Tg was obtained is given in Fig. S6.

Characterization of PIL–IL/GO membrane

In comparison to the commercial UF membrane substrate (Fig. 4a), the schematics and the SEM images of bPES/PET substrate are shown in Fig. 4b. The bPES skin layer has an interconnected porous structure with a pore size of roughly 30–40 nm64 (Fig. 4b, right panel) whereas the UF substrate has a semi-dense PES skin layer (Fig. 4a, right panel). The fabrication of GONF on the bPES/PET substrate was done by vacuum filtering where the GO nanosheets (each with about 0.3 μm width) were deposited homogeneously to give a wrinkled top surface (Fig. 4c, right panel). The deposited GONF is estimated to consist of about 250 to 260 GO layers, based on the individual sheet thickness of 0.8 nm and spacing of 1 nm in between the GO layers.56 The impregnation of the PIL–IL gel into the GONF layer caused swelling and change in surface morphology with a final PIL–IL/GO selective layer thickness of about 850 nm (Fig. 4d) in comparison to GONF thickness of about 450 nm (Fig. 4c).
image file: d2nr03214g-f4.tif
Fig. 4 Schematics and the cross-sectional SEM images of UF substrate (a), the fabricated bPES/PET substrate (b), GONF on bPES/PET substrate (c), and PIL–IL/GO selective layer on bPES/PET substrate (d). The zoomed-in images on the right for (a) and (b) panels show the difference in porosity of the PES skin layer. The surface morphology shown on the right of panels (c) and (d) represent the GONF top surface before and after impregnation with PIL–IL gel, respectively. The surface morphology of the unmodified UF and bPES/PET substrates are shown in Fig. S7a.

The specific interactions between GO and PIL–IL gel were probed by FTIR and NMR methods. Fig. 5 shows the FTIR spectra of PIL–IL/GO on bPES/PET substrate (ii in Table 1), where the characteristic features of PIL–IL (νaromatic-CH 3100 cm−1, νalkyl-CH 2900 cm−1, and νC[triple bond, length as m-dash]N 2220 cm−1) and GO (νOH 3430 cm−1, νC–(C[double bond, length as m-dash]O) 1720 cm−1, and νC[double bond, length as m-dash]C 1570 cm−1) were confirmed. The observation of the red-shifted GO peaks (νOH 3430 cm−1 and νC–(C[double bond, length as m-dash]O) 1720 cm−1; highlighted with red arrows) and the blue-shifted PIL–IL peaks (νaromatic-CH 3100 cm−1, νalkyl-CH 2900 cm−1, and νC[triple bond, length as m-dash]N 2220 cm−1; highlighted with blue arrows) suggest the molecular interactions between the PIL, IL, and GO components.65 Fig. S7b compares the peak shifts of the PIL–IL/GO on UF and bPES/PET substrate, in which we don't see much difference in the featured characteristic peaks. Therefore, we concluded that the nano-confinement of PIL–IL in GONF is effective, and the PIL–IL gel is not leached out into the substrate even when the pore size increase from UF (3–4 nm) to bPPES/PET (30–40 nm). The photo images of the PIL–IL/GO and GONF on UF and bPES/PET substrates are in Fig. S7a.


image file: d2nr03214g-f5.tif
Fig. 5 FTIR spectra of PIL, IL, PIL–IL, PIL–IL/GO on bPES/PET, GONF on bPES/PET, and bPES/PET substrate. The vertical dashed lines mark the resonance peak of νOH 3430 cm−1 (GONF), νaromatic-CH 3100 cm−1 (IL), νalkyl-CH 2900 cm−1 (PIL), νC[triple bond, length as m-dash]N 2220 cm−1 (PIL and IL), νC–(C[double bond, length as m-dash]O) 1720 cm−1 (GONF), νC[double bond, length as m-dash]C 1570 cm−1 (GONF). The arrows indicate the red and blue shift-direction of each vibration in the PIL–IL/GO, due to molecular interactions among the constituents.

The HMBC NMR (Fig. 6a) further provided support to the interactions between the PIL–IL and GO by FTIR by specifically probing the correlated 1H and 13C within the selective layer components. In order to remove the interference from the majority component, which is the substrate, the PIL–IL/GO flakes (Fig. 6a, inset) were scraped from the membrane surface and re-dissolved in DMSO-d6 for HMBC. The correlations between the imidazolium ring (g, i, and k) and GO were highlighted in yellow at the intersections of the dashed lines (Fig. 6a). This interaction between [EMIM]+ and GO is ascribed to both the π–π and electrostatic interactions.65–67 Moreover, 1H-NMR of PIL–IL/GO also suggests the interaction between PIL–IL and GONF. Fig. 6b compares the 1H-NMR of PIL–IL/GO and PIL–IL gel. With a molar ratio of PIL[thin space (1/6-em)]:[thin space (1/6-em)]IL = 1[thin space (1/6-em)]:[thin space (1/6-em)]100, we observed the spectra to be almost the same as IL (Fig. S1a) since the proton signal of PIL is diminished due to its low concentration (Fig. 6b, bottom). With the confinement of PIL–IL within the GONF, the characteristic peaks of [EMIM]+ cation “a, b, c, g, i, and k” broaden68 due to the relatively slow movement of the ions within the NMR time scale (Fig. 6b, top). Such broadening effect was observed only in the IL constituent and was not observed on the line width of the d-solvent (DMSO-d6 at 2.58 ppm, labeled with *). The OH moiety of GO component is also downshifted to 4.7 ppm (Fig. 6b, top) from 3.4 ppm that is seen in pure GO sample without the presence of PIL or IL (Fig. S8). This shift further supports the existence of interactions between the PIL–IL and GO.


image file: d2nr03214g-f6.tif
Fig. 6 (a) HMBC spectra showing the molecular interactions between PIL, IL, and GO components. Inset shows the images of PIL–IL/GO material collected by scraping off the top selective layer from the PIL–IL/GO on bPES/PET to redisperse in DMSO-d6 for HMBC NMR. (b) 1H-NMR of the PIL–IL/GO and PIL–IL gel. The GO peaks, from high field to down field, are likely due to the native alkyl-CH (∼3 ppm), OH (4.7 ppm), aromatic-CH (∼7 ppm) functionalities that are captured due to their interaction with the IL. The NMR of pure GO is shown in Fig. S8.

CO2 separation

The CO2 permeance and CO2 selectivity against N2 and O2 with the PIL–IL/GO FTMs were measured by membrane testing according to the conditions summarized in Table 1. Fig. 7 shows the performance of PIL–IL/GO on bPES/PET substrate (ii in Table 1); both with (hollowed symbols) and without O2 (filled symbols). CO2 permeance of 3900 GPU (Fig. 7a) and CO2/N2 selectivity of 1200 (Fig. 7b) were measured under 410 ppm CO2 with CO2/N2/H2O mixture feed at 40% RH and 22 °C. Under 2500 ppm CO2 (cabin air), the performance was 1360 GPU with a CO2/N2 selectivity of 650. The exponential decrease in CO2 permeance with increased CO2 concentration in feed is a characteristic trait of facilitated transport (F-T) mechanism. The permeances for the non-reactive O2 and N2 stay constant around 6 GPU for O2 and 1 GPU for N2. The F-T pathway dominates over S–D mechanism for CO2 transport at these low partial pressure conditions. While the CO2/N2 selectivity of the FTM with bPES/PET substrate (ii in Table 1) was about the same as the one with the UF substrate (i in Table 1; Fig. S9b), PIL–IL/GO on bPES/PET presented 10% higher CO2 permeance under both DAC and cabin air conditions with CO2/N2/H2O mixture feed (Fig. S9a). Following the resistance-in-series model, this increase in permeance is ascribed to the thinner bPES skin layer with larger pore size (30–40 nm) that is interconnected as opposed to the semi-dense PES layer (pore size 3–4 nm) of the commercial UF substrate.57,64,69 The CO2 permeance decreased by about 45% in the presence of O2 to 2100 GPU at 410 ppm of CO2 (Fig. 7a). This was observed irrespective of the substrate used (Fig. S9a). Recalling that the solubility of CO2 in IL is barely changed with and without the presence of O2 presence (Fig. 2a), we suggest that the decrease in CO2 permeance is related with the slower diffusion of CO2 and CO2-complexes within the membrane (Fig. 2b). The CO2/O2 selectivity (265 at 410 ppm CO2) is lower than that of CO2/N2 selectivity (1100) since O2 (∼5 GPU) is in general more permeable than N2 (∼1.5 GPU), mainly due to their difference in molecular size (O2: 3.46 Å vs. N2: 3.64 Å). Fig. 7c shows the separation ratio of PIL–IL/GO on bPES/PET with and without O2. The PIL–IL/GO on bPES/PET was observed to have lower separation ratio due to the higher permeance of O2 than N2.
image file: d2nr03214g-f7.tif
Fig. 7 (a) Permeance of PIL–IL/GO on bPES/PET (i in Table 1) under CO2/N2/H2O (filled circle) and CO2/N2/O2/H2O (hollowed circle). (b) CO2/N2 and CO2/O2 selectivities. (c) CO2/(N2 + O2) separation ratio. Notice that for CO2/N2/H2O feed, the CO2/(N2 + O2) separation ratio is the same as CO2/N2 selectivity. The feed gas had a humidity level of 40% RH at 22 °C; 10.6 mbar moisture.

The experimental data presented in Fig. 7a was fitted to the facilitated transport model (eqn (6)) to extract parameters of image file: d2nr03214g-t9.tif and image file: d2nr03214g-t10.tif (Fig. S10). The image file: d2nr03214g-t11.tif parameter (in units of GPU) corresponds to the CO2 permeance of FTMs at complete carrier saturation and therefore represents the S–D portion of the overall CO2 permeance. The fitted values of image file: d2nr03214g-t12.tif are magnitudes lower than the overall measured CO2 permeance image file: d2nr03214g-t13.tif; consistent with FTM behavior where CO2 permeance decreases with increasing CO2 concentration since the membrane starts to behave more like S–D membrane or even as a membrane absorber at high CO2 partial pressures. The extracted CO2 permeance at carrier saturation of the PIL–IL/GO on UF under CO2/N2 is 32.6 GPU, which is in the vicinity of the previously reported CO2 permeance of 19 GPU at higher CO2 concentration of 15% at 22 °C.56 Further comparing the extracted value of image file: d2nr03214g-t14.tif (Fig. S10 inset table) under the condition with and without O2, CO2 saturation of carriers within the membrane seems more likely to happen when there is O2 present, regardless of the membrane substrate used. The slower ion-self diffusivity in the presence of O2 as seen in Fig. 2b also supports this observation.

Factors like humidity70 and temperature39 are known to influence the transport behavior in FTMs. Under high humidity, water is co-absorbed with CO2. The presence of water is known to decrease the viscosity of ILs and it also increases the CO2 capacity due to the reaction between CO2 and water that forms bicarbonate.56 On the other hand, increase in temperature not only increases chain mobility in PIL (hence faster CO2 transport) but also encourages the dissociation of IL–CO2 complex (hence faster CO2 release) due to the exothermic nature of CO2 absorption. Therefore, CO2 separation from air for PIL–IL/GO on bPES/PET was evaluated at different humidity levels and temperatures as shown in Fig. 8a and b, respectively. The CO2 permeance, CO2/N2 selectivity, and separation ratio all increase with increased humidity and temperature, primarily owing to the faster transport of the CO2. (See ESI for more detailed discuss on the temperature effect on FTM performance.) A higher CO2 transport was achieved with higher moisture content, since humidity not only increases the binding of CO2 to IL carrier (via greater extent of bicarbonate formation) but also increases the diffusivity of the carriers due to lubrication effect from water co-absorption (Fig. S11). With increased temperature, CO2 and IL–CO2 complex diffusivities are expected to increase, so does the dissociation rate of IL–CO2 complex. There is much discussion in the field71 on whether it is the increase of the carrier mobility49 or the CO2 dissociation rate47 that dominates for higher CO2 separation performance with increased temperature. A recent study on high performance FTMs at room temperature suggest the rate determining step is the diffusion.54 Therefore, not surprisingly the separation performance decayed with increased thickness of selective layer (from ii to iv in Table 1) as seen in Fig. 8c due to the increased film resistance to diffusion. Fig. 8d further demonstrates the stability of PIL–IL/GO on bPES/PET over the course of 7 days under continuous feed of 410 ppm CO2 at 40% RH and 295 K. We believe that the nano-confinement of PIL–IL within GONF (through (1) π–π interaction and (2) electrostatic interactions) played a pivotal role for this stability.56


image file: d2nr03214g-f8.tif
Fig. 8 The change in CO2 separation performance with humidity (a), temperature (b), membrane thickness (c), and time (d). Membrane ii (in Table 1) is used in panel (a), (b), and (d); and membrane ii, iii, and iv are used in panel (c).

We further tested PIL–IL/GO on bPES/PET under vacuum operation with 760 Torr transmembrane pressure. Membranes ii, iii, and iv (in Table 1) leaked. We noticed the transmembrane pressure gradient could not be maintained and the permeate composition was almost the same as the feed, suggesting the need of further mechanical reinforcement on the selective PIL–IL/GO layer. Table S1 shows our efforts of changing the PIL–IL/GO composition by gradually increasing the PIL and GO loading of the selective layer. The increase of PIL and GO components increased the mechanical stability of the PIL–IL/GO; however, this was accompanied with significant reductions in CO2 binding capacity and transport. The high content of PIL also led to a relative brittle film (see Fig. 3) where cracks could form even under the plasticization by moisture at 40% RH (i.e., samples 3 and 7 in Table S1). However, it was demonstrated that a PIL–IL/GO of 1.27–3.75/1 (v in Table 1; sample 21 in Table S1) withstands the pressure gradient. Fig. 9 shows CO2 separation performance at 295 and 313 K for the FTM sample v. At 295 K, the F-T pathway appears to be more hindered due to the higher PIL content, which is less reactive to CO2 without the imidazolium moiety in the ionomer structure, and the thicker selective layer. The performance resembles an S–D membrane, where a CO2 permeance of 31 GPU and separation ratio of 6.2 were measured. At 313 K, the F-T mechanism was enhanced due to improved diffusivity with increased temperature, the CO2 permeance increased by 15-fold along with an increase in CO2/N2 selectivity. However, the CO2/O2 selectivity remains about the same, possibly due to the enhanced O2 diffusion. These results demonstrate that even a relatively small increase in the thickness of the selective layer for mechanical stability results in dramatic reduction in the FTM performance, thus identifying the mass transport resistance as the most critical factor. Therefore, our recommendation for future research direction for PIL–IL type of FTMs is chemical modifications of the selective layer so that the carriers can be covalently bonded in order to achieve both the superior separation performance and the durability in particular for transmembrane pressures larger than zero.


image file: d2nr03214g-f9.tif
Fig. 9 Performance of vacuum operation of PIL–IL/GO on bPES/PET (v in Table 1) under 410 ppm CO2 with mixture feed of CO2/N2/O2 at 22 and 40 °C; both with 40% RH.

Conclusions

An FTM with PIL–IL/GO selective layer was fabricated using a highly permeable bicontinuous structured bPES/PET substrate. The nanoconfinement of PIL–IL within the GONF layer through ionic interactions between the carriers and the GO flakes and π–π interactions between the aromatic moieties was effective in maintaining the membrane stability under zero transmembrane pressure. The presence of O2 in the feed did not affect the carrier-CO2 binding capacity under the tested conditions, however it resulted in slightly slower CO2 transport. The fabricated FTM with PIL–IL/GO selective layer and the bPES/PET substrate presented a CO2 permeance of 2100 GPU and high selectivities of CO2/N2 (1100) and CO2/O2 (265) under conditions relevant to DAC (410 ppm CO2, 40% RH, 295 K). Under 2500 ppm of CO2, conditions relevant to cabin air, the permeance decreases to 430 GPU while the CO2/N2 selectivity and CO2/O2 selectivity dropped to 150 and 67, respectively. These results demonstrate a superior performance, especially the CO2/O2 selectivity, among the known FTMs reported to date. Further, this study represents the first FTM for CO2 separation from air. To improve the membrane stability and to prevent leaching of the carrier for operations under a positive transmembrane pressure, the selective layer thickness was increased. The thicker membranes presented significant resistance thus resulting in lower separation performance. In order to further tune the membrane stability without increasing the thickness and resistance, covalent interactions between the PIL–IL and GO within a thin selective layer are determined to be necessary.

Author contributions

Y. Y. L. synthesized the IL and PIL, and fabricated, characterized, and tested the membranes. N. P. W. assisted in performing the DOSY and HMBC NMR measurements. R. D. measured CO2 capacities. D. L. J. contributed to the experimental plans and the discussions on the CO2 removal from cabin air. B. G. oversaw the experiments and analysis. All authors contributed to the writing of the manuscript.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

This work was supported by an Early Career Faculty grant from NASA's Space Technology Research Grants Program under Award No. 80NSSC18K1505. The characterization of IL–CO2 binding and self-diffusivity under DAC relevant conditions were supported by the U.S. Department of Energy, Office of Science, Basic Energy Science under award Number DE-SC0022214. The authors would like to thank Dr Ruizhi Pang and Dr W. S. Winston Ho for providing the bPES/PET substrate. The authors acknowledge the Northeast Ohio High Field NMR Facility, Swagelok Center for Surface Analysis of Materials (SCSAM) for the access to SEM, and the Soft Matter Characterization Laboratory for the access to TGA at Case Western Reserve University.

References

  1. J. C. Knox, 47th Int. Conf. Environ. Syst., 2017, ICES-2017-209.
  2. R. Huang, J. T.-M. Richardson, G. Belancik and D. Jan, 47th Int. Conf. Environ. Syst., 2017, ICES-2017-116.
  3. D. G. Madden, H. S. Scott, A. Kumar, K. Chen, R. Sanii, A. Bajpai, M. Lusi, T. Curtin, J. J. Perry, M. J. Zaworotko and T. Curtin, Philos. Trans. R. Soc., A, 2017, 375, 2084–2094 CrossRef PubMed.
  4. J. C. Knox, 48th Int. Conf. Environ. Syst., 2018, ICES-2018-215.
  5. Overview of Greenhouse Gases, https://www.epa.gov/ghgemissions/overview-greenhouse-gases.
  6. National Academies, Negative Emissions Technologies and Reliable Sequestration: A Research Agenda, 2019 Search PubMed.
  7. K. Z. House, A. C. Baclig, M. Ranjan, E. A. Van Nierop, J. Wilcox and H. J. Herzog, Proc. Natl. Acad. Sci. U. S. A., 2011, 108, 20428–20433 CrossRef CAS PubMed.
  8. R. P. Lively and M. J. Realff, AIChE J., 2016, 62, 3699–3705 CrossRef CAS.
  9. M. V. Paragano and J. Kolmas, 45th Int. Conf. Environ. Syst., 2015, ICES-2015-112.
  10. F. Zeman, Environ. Sci. Technol., 2007, 41, 7558–7563 CrossRef CAS PubMed.
  11. M. Erans, E. S. Sanz-Pérez, D. P. Hanak, Z. Clulow, D. M. Reiner and G. A. Mutch, Energy Environ. Sci., 2022, 15, 1360–1405 RSC.
  12. R. Custelcean, N. J. Williams, K. A. Garrabrant, P. Agullo, F. M. Brethomé, H. J. Martin and M. K. Kidder, Ind. Eng. Chem. Res., 2019, 58, 23338–23346 CrossRef CAS.
  13. J. K. Stolaroff, D. W. Keith and G. V. Lowry, Environ. Sci. Technol., 2008, 42, 2728–2735 CrossRef CAS PubMed.
  14. K. Lackner, H.-J. Ziock and P. Grimes, in Conference: 24th Annual Technical Conference on Coal Utilization and Fuel Systems, Clearwater, FL (US), Clearwater, Florida, 1999.
  15. A. Holewinski, M. A. Sakwa-Novak and C. W. Jones, J. Am. Chem. Soc., 2015, 137, 11749–11759 CrossRef CAS PubMed.
  16. A. R. Sujan, S. H. Pang, G. Zhu, C. W. Jones and R. P. Lively, ACS Sustainable Chem. Eng., 2019, 7, 5264–5273 CrossRef CAS.
  17. S. Bali, M. A. Sakwa-Novak and C. W. Jones, Colloids Surf., A, 2015, 486, 78–85 CrossRef CAS.
  18. T. Wang, K. S. Lackner and A. Wright, Environ. Sci. Technol., 2011, 45, 6670–6675 CrossRef CAS PubMed.
  19. X. Shi, H. Xiao, H. Azarabadi, J. Song, X. Wu, X. Chen and K. S. Lackner, Angew. Chem., Int. Ed., 2020, 59, 6984–7006 CrossRef CAS PubMed.
  20. E. A. Van Nierop, S. Hormoz, K. Z. House and M. J. Aziz, Energy Procedia, 2011, 4, 1783–1790 CrossRef CAS.
  21. Y. Duan and D. C. Sorescu, J. Chem. Phys., 2010, 133, 1–11 Search PubMed.
  22. S. T. Hwang, AIChE J., 2004, 50, 862–870 CrossRef CAS.
  23. H. B. Park, J. Kamcev, L. M. Robeson, M. Elimelech and B. D. Freeman, Science, 2017, 356, 1138–1148 CrossRef PubMed.
  24. W. J. Koros and C. Zhang, Nat. Mater., 2017, 16, 289–297 CrossRef CAS PubMed.
  25. I. Kammakakam, K. E. O’Harra, E. M. Jackson and J. E. Bara, Polymer, 2021, 214, 123239 CrossRef CAS.
  26. A. R. Nabais, R. O. Francisco, V. D. Alves, L. A. Neves and L. C. Tomé, Membranes, 2021, 11, 1–19 CrossRef PubMed.
  27. I. Kammakakam, J. E. Bara, E. M. Jackson, J. Lertxundi, D. Mecerreyes and L. C. Tomé, ACS Sustainable Chem. Eng., 2020, 8, 5954–5965 CrossRef CAS.
  28. J. Liu, S. Zhang, D. e. Jiang, C. M. Doherty, A. J. Hill, C. Cheng, H. B. Park and H. Lin, Joule, 2019, 3, 1881–1894 CrossRef CAS.
  29. S. Tachibana, K. Hashimoto, H. Mizuno, K. Ueno and M. Watanabe, Polymer, 2022, 241, 124533 CrossRef CAS.
  30. Z. Huang, C. Yin, T. Corrado, S. Li, Q. Zhang and R. Guo, Chem. Mater., 2022, 34, 2730–2742 CrossRef CAS.
  31. T. J. Corrado, Z. Huang, D. Huang, N. Wamble, T. Luo and R. Guo, Proc. Natl. Acad. Sci. U. S. A., 2021, 118, 1–7 CrossRef PubMed.
  32. J. G. Seong, W. H. Lee, J. Lee, S. Y. Lee, Y. S. Do, J. Y. Bae, S. J. Moon, C. H. Park, H. J. Jo, J. S. Kim, K. R. Lee, W. S. Hung, J. Y. Lai, Y. Ren, C. J. Roos, R. P. Lively and Y. M. Lee, Sci. Adv., 2021, 7, 1–11 Search PubMed.
  33. I. Rose, C. G. Bezzu, M. Carta, B. Comesanã-Gándara, E. Lasseuguette, M. C. Ferrari, P. Bernardo, G. Clarizia, A. Fuoco, J. C. Jansen, K. E. Hart, T. P. Liyana-Arachchi, C. M. Colina and N. B. McKeown, Nat. Mater., 2017, 16, 932–937 CrossRef CAS PubMed.
  34. L. Hu, V. T. Bui, A. Krishnamurthy, S. Fan, W. Guo, S. Pal, X. Chen, G. Zhang, Y. Ding, R. P. Singh, M. Lupion and H. Lin, Sci. Adv., 2022, 8, 27–29 Search PubMed.
  35. B. Comesaña-Gándara, J. Chen, C. G. Bezzu, M. Carta, I. Rose, M. C. Ferrari, E. Esposito, A. Fuoco, J. C. Jansen and N. B. McKeown, Energy Environ. Sci., 2019, 12, 2733–2740 RSC.
  36. B. W. Rowe, L. M. Robeson, B. D. Freeman and D. R. Paul, J. Membr. Sci., 2010, 360, 58–69 CrossRef CAS.
  37. L. M. Robeson, J. Membr. Sci., 2008, 320, 390–400 CrossRef CAS.
  38. A. Klemm, Y. Y. Lee, H. Mao and B. Gurkan, Front. Chem., 2020, 8, 1–8 CrossRef.
  39. Y. Han and W. S. W. Ho, Ind. Eng. Chem. Res., 2020, 59, 5340–5350 CrossRef CAS.
  40. E. Kamio, M. Tanaka, Y. Shirono, Y. Keun, F. Moghadam, T. Yoshioka, K. Nakagawa and H. Matsuyama, Ind. Eng. Chem. Res., 2020, 59, 2083–2092 CrossRef CAS.
  41. Y. Han, D. Wu and W. S. W. Ho, J. Membr. Sci., 2018, 567, 261–271 CrossRef CAS.
  42. S. Zhang, H. Li, H. Li, B. Sengupta, S. Zha, S. Li and M. Yu, Adv. Funct. Mater., 2020, 30, 2002804 CrossRef CAS.
  43. S. Janakiram, F. Santinelli, R. Costi, A. Lindbråthen, G. M. Nardelli, K. Milkowski, L. Ansaloni and L. Deng, Chem. Eng. J., 2021, 413, 127405 CrossRef CAS.
  44. S. Janakiram, J. L. Martín Espejo, X. Yu, L. Ansaloni and L. Deng, J. Membr. Sci., 2020, 616, 118626 CrossRef CAS.
  45. J. Zhang, E. Kamio, A. Matsuoka, K. Nakagawa, T. Yoshioka and H. Matsuyama, Ind. Eng. Chem. Res., 2021, 60, 12640–12649 CrossRef CAS.
  46. J. Zhang, E. Kamio, M. Kinoshita, A. Matsuoka, K. Nakagawa, T. Yoshioka and H. Matsuyama, Ind. Eng. Chem. Res., 2021, 60, 12698–12708 CrossRef CAS.
  47. Y. Han and W. S. W. Ho, J. Membr. Sci. Lett., 2022, 2, 100014 CrossRef.
  48. X. Deng, C. Zou, Y. Han, L.-C. Lin and W. S. W. Ho, J. Phys. Chem. C, 2020, 124, 25322–25330 CrossRef CAS.
  49. A. Matsuoka, S. Taniguchi, E. Kamio and H. Matsuyama, Ind. Eng. Chem. Res., 2021, 60, 7397–7405 CrossRef CAS.
  50. D. T. Wickham, K. J. Gleason, J. R. Engel, S. W. Cowley and C. Chullen, 43th Int. Conf. Environ. Syst., 2013, 1–18 Search PubMed.
  51. D. T. Wickham, J. A. Nabity, J. McCarty and R. Aaron, 49th Int. Conf. Environ. Syst., 2019, ICES-2019-187 Search PubMed.
  52. S. Fujikawa, R. Selyanchyn and T. Kunitake, Polym. J., 2021, 53, 111–119 CrossRef CAS.
  53. C. Castel, R. Bounaceur and E. Favre, Front. Chem. Eng., 2021, 3, 1–15 Search PubMed.
  54. M. Sandru, E. M. Sandru, W. F. Ingram, J. Deng, P. M. Stenstad, L. Deng and R. J. Spontak, Science, 2022, 376, 90–94 CrossRef CAS PubMed.
  55. B. Belaissaoui, E. Lasseuguette, S. Janakiram, L. Deng and M. C. Ferrari, Membranes, 2020, 10, 1–23 CrossRef PubMed.
  56. Y. Y. Lee and B. Gurkan, J. Membr. Sci., 2021, 638, 119652 CrossRef CAS.
  57. R. Pang, K. K. Chen, Y. Han and W. S. W. Ho, J. Membr. Sci., 2020, 612, 118443 CrossRef CAS.
  58. Y. Y. Lee, D. Penley, A. Klemm, W. Dean and B. Gurkan, ACS Sustainable Chem. Eng., 2021, 9, 1090–1098 CrossRef CAS.
  59. Y. Y. Lee, K. Edgehouse, A. Klemm, H. Mao, E. Pentzer and B. Gurkan, ACS Appl. Mater. Interfaces, 2020, 12, 19184–19193 CrossRef CAS PubMed.
  60. N. A. Ramli, N. A. Hashim and M. K. Aroua, Chem. Eng. Commun., 2018, 205, 295–310 CrossRef CAS.
  61. H. Tokuda, K. Hayamizu, K. Ishii, M. A. B. H. Susan and M. Watanabe, J. Phys. Chem. B, 2004, 108, 16593–16600 CrossRef CAS.
  62. S. M. Green, M. E. Ries, J. Moffat and T. Budtova, Sci. Rep., 2017, 7, 1–12 CrossRef CAS PubMed.
  63. A. Radhi, K. A. Le, M. E. Ries and T. Budtova, J. Phys. Chem. B, 2015, 119, 1633–1640 CrossRef CAS PubMed.
  64. R. Pang, Y. Yang, Y. Han, K. K. Chen and W. S. W. Ho, J. Membr. Sci., 2022, 654, 120547 CrossRef CAS.
  65. W. Ying, J. Cai, K. Zhou, D. Chen, Y. Ying, Y. Guo, X. Kong, Z. Xu and X. Peng, ACS Nano, 2018, 12, 5385–5393 CrossRef CAS PubMed.
  66. X. Wan, K. Zhang, T. Wan, Y. Yan, Z. Ye and X. Peng, J. Membr. Sci., 2022, 652, 120475 CrossRef CAS.
  67. M. Dong, K. Zhang, X. Wan, S. Wang, S. Fan, Z. Ye, Y. Wang, Y. Yan and X. Peng, Small, 2022, 18, 2108026 CrossRef CAS PubMed.
  68. M. Dong, K. Zhang, X. Wan, Z. Fang, Y. Hu, Z. Ye, Y. Wang, Z. Li and X. Peng, Appl. Mater. Today, 2022, 27, 101458 CrossRef.
  69. R. Pang, Y. Han, K. K. Chen, Y. Yang and W. S. W. Ho, Appl. Energy, 2022, 311, 118624 CrossRef CAS.
  70. X. Deng, Y. Han, L. C. Lin and W. S. W. Ho, J. Phys. Chem. C, 2022, 126, 3661–3670 CrossRef CAS.
  71. A. Matsuoka, A. Otani, E. Kamio and H. Matsuyama, Sep. Purif. Technol., 2022, 280, 119847 CrossRef CAS.

Footnote

Electronic supplementary information (ESI) available: NMR characterization of IL, PIL, and GO; pulse sequence and the spectra recoded for 1H-DOSY NMR; viscosity and water content of IL as a function of CO2 concentration and humidity; FTIR, SEM, and photo images of the membranes; details of the transport model fit; membrane specifications for the tested vacuum operation. See DOI: https://doi.org/10.1039/d2nr03214g

This journal is © The Royal Society of Chemistry 2022