Functionalizing Porous Aromatic Frameworks with Polar Organic

Functionalizing Porous Aromatic Frameworks with Polar Organic Groups for High-Capacity and Selective CO2 Separation: A Molecular Simulation Study. Rav...
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Functionalizing Porous Aromatic Frameworks with Polar Organic Groups for High-Capacity and Selective CO2 Separation: A Molecular Simulation Study Ravichandar Babarao,† Sheng Dai,†,‡ and De-en Jiang*,† † ‡

Chemical Science Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States Department of Chemistry, University of Tennessee, Knoxville, Tennessee 37966, United States

bS Supporting Information ABSTRACT: Porous aromatic frameworks (PAFs) were recently synthesized with the highest surface area to date; one such PAF (PAF-1) has diamond-like structure with biphenyl building blocks and exhibits exceptional thermal and hydrothermal stabilities. Herein, we computationally design new PAFs by introducing polar organic groups to the biphenyl unit and then investigate their separating power toward CO2 by using grand-canonical Monte Carlo (GCMC) simulations. Among these functional PAFs, we found that tetrahydrofuranlike ether-functionalized PAF-1 shows higher adsorption capacity for CO2 at 1 bar and 298 K (10 mol per kilogram of adsorbent) and also much higher selectivities for CO2/CH4, CO2/N2, and CO2/H2 mixtures when compared with the amine functionality. The electrostatic interactions are found to play a dominant role in the high CO2 selectivities of functional PAFs, as switching off atomic charges would decrease the selectivity by an order of magnitude. This work suggests that functionalizing porous frameworks with tetrahydrofuran-like ether groups is a promising way to increase CO2 adsorption capacity and selectivity, especially at ambient pressures.

’ INTRODUCTION CO2 capture and sequestration (CCS) is becoming increasingly important in addressing climate change. One of the main challenges in CCS is the development of energy-efficient separation of CO2 from other gas mixtures such as flue gas of coal-fired power plants (the so-called post-combustion carbon capture). In this respect, separation via adsorption has attracted many researchers to explore porous materials with a wide variety of topology, pore-size, and functionality for CO2 capture. For example, conventional zeolite materials such as 13X and NaY have been studied for CO2 separation which shows exceptionally high CO2 selectivity.1,2 With the development of reticular chemistry, novel porous materials with high surface area and porosity have been extensively explored, including metalorganic frameworks (MOFs), covalent-organic frameworks (COFs), and zeolitic imidazolate frameworks (ZIFs).3 Moreover, several strategies have been employed to enhance CO2 selectivity, such as the presence of constricted pore size, open metal-sites, postsynthetic modification, and functional groups.4 In addition, the presence of extra-framework ions shows high adsorption selectivity as predicted recently in a charged zeolitelike metal-organic framework (ZMOF).5 However, the presence of even a small amount of H2O in the gas mixture reduces the selectivity drastically by almost one-order of magnitude.6 r 2011 American Chemical Society

Adding functional groups to the organic linkers, particularly the amine group has been widely studied for CO2 capture. For instance, Arstad et al. characterized three MOFs as adsorbents for CO2 with and without uncoordinated amine functionalities and found the amine functionalized adsorbents exhibit high CO2 adsorption capacities.7 High uptake of CO2 reaching a maximum of 6 mmol/g at 1 bar was observed in a cobalt-adeninate MOF named as bio-MOF-11.8 Triazolate-bridged MOF functionalized with ethylenediamine shows the highest binding energy to date for CO2 adsorption in a MOF and an uptake of 3.24 mmol/g at 1 bar and 298 K.9 Effect of pore size on CO2 adsorption capacity was systematically studied in an anionic bio-MOF-1 by replacing smaller dimethylammonium cations with larger cations.10 Couck et al. demonstrated that functionalizing MIL-53(Al) with the amino group together with the presence of -OH group enhances the selectivity of CO2/CH4 by orders of magnitude at low pressures when compared to nonfunctionalized MIL-53(Al).11 Recently, Torrisi et al. predicted CO2/CH4 selectivity by adding different functional groups such as -OH, -COOH, -NH2, and -CH3 in MIL-53(lp) and found -COOH and -OH substituted ligands shows the best selectivity when compared to original Received: September 13, 2010 Revised: January 31, 2011 Published: February 25, 2011 3451

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Langmuir MIL-53(lp).12 In addition, several studies have reported the strength of interaction of CO2 with various functional linkers using ab initio methods.13-15 One of the major drawbacks of most porous MOFs and COFs is their limited physicochemical stability. Most recently, Ben et al.16 developed a new class of stable porous materials, porous aromatic frameworks (PAFs), with diamond-like structure in which the single bond between two sp3 carbon atoms is replaced by single or multiple phenyl groups. One such PAF (named as PAF-1) is synthesized and exhibits unprecedented surface area (BET surface area, 5640 m2/g) to date. Unlike most MOFs, PAF-1 shows exceptionally high thermal and hydrothermal stability and also high uptakes of CO2 and H2 gas.16 The predicted experimental isotherm for N2 matches well with the simulation results based on the crystalline PAF-1 structure constructed from the diamond structure. Trewin and Cooper17 highlighted in their study that the powder X-ray diffraction pattern of PAF-1 in Ben et al.’s work showed a very broad peak, suggesting that the PAF-1 is amorphous. They constructed a pore model based on amorphous silica with predicted density slightly lower than but surface area similar to the crystalline PAF-1 model.17 Despite the issue with the crystallinity of the newly discovered PAF, one hopes that further improvements in the synthesis technique could yield larger crystals. In the mean time, it is worthwhile to explore this framework for its novel porous structure and as a scaffold for taskspecific functionalization from molecular simulations. For example, Lan et al. simulated the hydrogen adsorption capacity in several PAF structures by replacing the C-C bond in the diamond structure with multiple phenyl rings.18 More recently, Sun et al. proposed a new PAF with the lithium tetrazolide linkers and predicted its hydrogen storage capacity using GCMC simulations.19 Both the two simulation studies are based on the crystalline PAF model, namely, the diamond-like structure. PAF’s potential for CO2 adsorption and separation, however, have not been explored; neither have the neutral polar organic functional groups. Hence, in this work we considered the crystalline PAF-1 as a perfect scaffold for us to build up polar organic groups on the biphenyl units and explore their effects on CO2 selectivity. For comparison, we also constructed an amorphous model for the PAF-1 structure to predict the adsorption isotherm and selectivity. Beyond the functional groups often considered in the literature such as -NH2, -OH, and -COOH for CO2 adsorption, we ask the question if there exist more selective ones for CO2 that can be used to functionalize novel porous materials such as PAFs. To this end, we are inspired by a recent study relating the molecular structure to its CO2 solubility.20 We reason that a high solubility may point to a stronger interaction with CO2 and hence high selectivity. So we guide our molecular simulations by quantum mechanical calculations of interaction energies between CO2 and small molecules containing different functional groups which are shown to have high CO2 solubility as solvents. We then choose promising functional groups to add on the biphenyl building blocks of PAF-1 to design new functional PAFs and then investigate their separation efficacies of CO2/N2, CO2/ CH4 and CO2/H2 mixtures using grand-canonical Monte Carlo (GCMC) simulation.

’ METHODS Turbomole V5.10 was used to compute the interaction energy between CO2 and various molecular functional groups at the MP2 level

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with triple-ζ valence basis sets with polarization (def2-TZVP).21 As no experimental crystallographic data are available for PAF-1, we constructed the structure by replacing the C-C bond in the diamond structure with the biphenyl group and optimized the structure using the Forcite module of the Material Studio suite of programs.22 We call the resultant structure the crystalline model. We then designed several hypothetical PAFs in a similar manner by using a functionalized biphenyl unit. Amorphous model for PAF-1 was also constructed using the procedure employed previously.23 In this model, a tetrahedral carbon connected to biphenyl ring was combined in a stepwise manner to form a larger cluster. Using the amorphous cell module in Material Studio, a threedimensional amorphous cell was constructed using six of these larger clusters. The target density for the simulation was set to 0.315 g/cm3 as calculated from experimental data. The models were fully relaxed using the Discover molecular mechanics and dynamics simulation module with the COMPASS force field.24 The calculated elemental composition for this amorphous model (C, 94.52; H, 5.48) is comparable with the experimental composition of PAF-1.16 The simulated powder X-ray diffraction pattern for the proposed amorphous PAF-1 structure is shown in Figure S1 in the Supporting Information (SI) and will be discussed below together adsorption results. Using a similar approach as mentioned above, functionalized amorphous PAF-1 was also constructed. For gas adsorption in various PAFs, the interactions of gas-adsorbent and gas-gas were modeled as a combination of pairwise site-site Lennard-Jones (LJ) and Coulombic potentials 8 9 2 !12 !6 3 < = σ σ q q R Rβ Rβ β 5þ 4εRβ 4 ð1Þ uij ðrÞ ¼ Σ : rRβ rRβ 4πε0 rRβ ; R∈i β∈j where ε0= 8.8542  10-12 C2 N-1 m-2 is the permittivity of the vacuum and σRβ and εRβ are the collision diameter and well depth, respectively. The LJ potential parameters of the framework atoms are adopted from Dreiding force field.25 A number of simulation studies have revealed that Dreiding force field can accurately predict gas adsorption in porous materials such as MOFs and COFs.26 Atomic partial charges are calculated based on fragmental cluster using density functional theory (DFT) as implemented in DMol3.22 Because of the large number of atoms in a unit cell, the DFT calculations were performed on a cluster model cleaved from the unit cell as shown in Figure S2 in the Supporting Information. To maintain the original hybridization, the cleaved bonds of the cluster were saturated by methyl groups. The PW91 functional along with the Double-ξ numerical polarization (DNP) basis set was used in the DFT calculations, which is comparable to 6-31G(d,p) Gaussian-type basis set. DNP basis set incorporates p-type polarization into hydrogen atoms and d-type polarization into heavier atoms. From the DFT calculations, the atomic charges were evaluated by fitting to the electrostatic potential using the Merz-Kollman (MK) scheme.27 Figure S2 in Supporting Information shows the estimated atomic charges. The adsorbates CO2 and N2 were mimicked as three-site model to account for the quadrupole moment, whereas a two-site model for H2 and a united-atom model for CH4 were employed. The C-O bond length in CO2 was 1.18 Å and the bond angle — OCO was 180. The charges on C and O atoms were þ0.576e and -0.288e (e = 1.6022  10-19 C the elementary charge), respectively, resulting in a quadrupole moment of -1.29  10-39 C 3 m2. The model reproduced the isosteric heat and isotherm of CO2 adsorption in slilicate. N2 had N-N bond length of 1.10 Å, a charge of -0.482e on N atom, and a charge of þ0.964e at the center-of-mass, which were fitted to the experimental bulk properties of N2. On the basis of this model, the quadrupole moment of N2 was -4.67  10-40 C 3 m2. H2 was mimicked by a two-site model with the LJ potential parameters fitted to the isosteric heat of H2 adsorption on a graphite surface. For H2 adsorption, quantum effects are included using 3452

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Feynman-Hibbs (FH)28 effective potential as it is important at cryogenic temperature. CH4 was represented by a united-atom model interacting with the LJ potential. The potential parameters were adopted from the TraPPE force field, which was developed to reproduce the critical parameters and liquid densities of alkanes. H2O was represented by TIP3P (three-point transferable interaction potential) model. CO was represented as a two-site model with the LJ potential parameters fitted to the heat of CO adsorption on exfoliated graphite (grafoil). The force-field parameters for CO2, CH4, N2, H2, CO, and H2O are taken from earlier work.5,29 Table S1 (Supporting Information) lists the LJ parameters and atomic charges of the adsorbates. The cross LJ parameters were evaluated by the Lorentz-Berthelot combining rules. The adsorption of pure CO2, H2, N2 and binary mixture CO2/CH4, CO2/H2, and CO2/N2 was simulated by the grand canonical Monte Carlo (GCMC) method, which has been widely used for the simulation of adsorption. Both CO2/H2 and CO2/N2 mixtures were assumed to have a bulk composition of 15:85, and for CO2/CH4 a bulk composition of 50:50 was considered. In order to study the effect of H2O on selectivity, a small trace of H2O (0.1 wt %) was added to the binary mixture. The framework atoms are kept frozen during simulation because adsorption involves low-energy equilibrium configurations and the flexibility of framework has a marginal effect, particularly on the adsorption of small gases. The LJ interactions were evaluated with a spherical cutoff equal to half of the simulation box with long-range corrections added; the Coulombic interactions were calculated using the Ewald sum method. The number of trial moves in a typical GCMC simulation was 2  107, though additional trial moves were used at high loadings. The first 107 moves were used for equilibration and the subsequent 107 moves for ensemble averages. Six types of trial moves were attempted in GCMC simulation, namely, displacement, rotation, and partial regrowth at a neighboring position, entire regrowth at a new position, swap with reservoir, and exchange of molecular identity. Unless otherwise mentioned, the statistical uncertainty was generally smaller than the symbol sizes presented in the figures. Canonical ensemble (NVT) simulation is performed to estimate the isosteric heat of adsorption at infinite dilution. A single adsorbate molecule is subjected to three types of trial moves employed in the NVT simulation, namely, translation, rotation and regrowth. The isosteric heat at infinite dilution is calculated from 0 0 - Uintra Þ q0st ¼ RT - ðUtotal

ð2Þ

where U0total is the total adsorption energy of a single molecule with adsorbent and U0intra is the intramolecular interaction of a single gas molecule in bulk phase. The experimental adsorption isotherm is usually reported in the excess amount Nex, while simulation gives the absolute amount Nab. To convert from Nab to Nex, we use Nex ¼ Nab - Fb Vf ree

ð3Þ

where Fb is the density of bulk adsorbate, Vfree is the free volume in adsorbent available for adsorption and is estimated from Z ð4Þ Vf ree ¼ exp½-uHe ad ðrÞ=kB T dr V

uHe ad

where is the interaction between Helium and adsorbent, in which σHe = 2.58 Å and εHe/kB = 10.22 K.30 Note that the free volume detected by helium is temperature dependent, and usually the room temperature is chosen. The ratio of free volume Vfree to the occupied volume Vtotal gives the porosity φ of adsorbent. The Henry constant KH was evaluated by Z ð5Þ KH ¼ β exp½ - βua ðr, ϖÞ dr dϖ

where β = kBT and kB is the Boltzmann constant. The integral yields the excess chemical potential of a single gas molecule upon adsorption. From the regrowth move, which is equivalent to the test-particle insertion method,31 the excess chemical potential was evaluated. To validate the force field parameters used in this study, we compared our simulation results with the available experimental data for the adsorption of CO2, H2 and N2 in PAF-1. (Figure S3 in Supporting Information). A reasonably good agreement is obtained between the predicted isotherm of CO2, H2 and N2 in crystalline model for PAF-1 and the experimental data.

’ RESULTS AND DISCUSSION CO2 Interaction with Model Functional Groups. To guide our molecular simulations, we first computed the binding energies of CO2 with various model functional groups at the MP2/TZVP level of theory which is capable of capturing the dispersion interaction. Several N-containing and O-containing groups were considered.20 We explored different geometries of CO2 approaching and interacting with the functional groups and show the most stable complexes in Figure 1. We found that CO2 interacts with these small molecules mainly through its electropositive C atom with the electronegative O or N atom of the functional groups. The closest contact ranges from 2.7 to 3.5 Å and the binding energy from -11 to -19 kJ/mol, in the regime of nonbonded interactions. Interestingly, we found that CO2 interacts most strongly with ether O atoms (Figure 1, parts f and h), especially as in tetrahydrofuran (THF) shown in Figure 1h. Besides electrostatic interactions between the partial positive charge of C and the partial negative charge of O, additional interactions exist between H atoms (next to the ether O) and the O atoms of CO2 with a distance of ∼2.8-2.9 Å. This causes an increase of CO2 binding energy especially in THF (BE = -19.2 kJ/ mol) than the other groups including -NH2 (BE= -16.6 kJ/mol). The constrained ring structure of THF seems to provide stronger H 3 3 3 O bonding in the CO2-THF complex than in the CO2-DME complex (BE= -16.3 kJ/mol), as evidenced by the shorter H 3 3 3 O bonds in the former (Figure 1h). A typical electrostatic-potential map is shown for THF in Figure S4 in the Supporting Information, which shows positive potential on the H atoms and negative on the O atom. The CO2-DME complex has been experimentally and computationally examined previously,32,33 and our results for the CO2-DME complex agree with those reports in terms of binding energy and geometry, suggesting that the CO2-THF complex may also be observed experimentally. Design of Functional PAFs. The above study of CO2 interaction with molecular functional groups shows that the ether O groups especially as in THF should be our first choice and the amino group is the next. So we chose -OCH3, -NH2, and -CH2OCH2- as in THF to functionalize PAF-1, and the constructed functional PAFs are named as NH2_PAF-1 (for -NH2), MO_PAF-1 (for -OCH3) and DHF_PAF-1 (for -CH2OCH2-; here DHF means dihydrofuran, which is a better chemical description of the functional biphenyl unit). Figure S5 in the Supporting Information shows the optimized unit cell of different functional PAFs together with their linkers. To characterize the adsorbent structure, the framework densityFf, free volume Vfree, and porosity φ of each PAF are calculated and listed in Table 1. The channel morphologies and the radius of the channel are calculated using the HOLE program34 and shown in Figure 2. There exists a zigzag channel in all the PAFs 3453

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Figure 1. Optimized conformations and binding energies (BE, defined as the energy of the complex minus the energy sum of CO2 and the functional group) of CO2 with model functional groups (a) acetonitrile, (b) acetone, (c) methanol, (d) methyl acetate, (e) dimethylformamide, (f) dimethyl ether, (g) ethylamine, and (h) tetrahydrofuran, calculated at the MP2/TZVP level of theory. The bond lengths are in units of angstroms. Key: C, gray; O, red; N, blue; H, white.

Table 1. Framework Density Gf, Free Volume Vfree, and Porosity O Calculated from This Work.a Ff (g/cm3)

Vfree (cm3/g)

φ

PAF-1

0.31

2.66

0.84

NH2_PAF-1

0.43

1.60

0.69

MO_PAF-1

0.55

1.09

0.60

DHF_PAF-1

0.69

0.89

0.62

a

See Figure S5 in the Supporting Information for the structure and building unit of the four PAFs.

and the radius of the channel is ∼6.6 Å in PAF-1, which is close to those predicted by Lan et al.18 The channel radius decreases to ∼5.5 Å in NH2_PAF-1, ∼ 4.4 Å in MO_PAF-1, and ∼4.6 Å in DHF_PAF-1. Adsorption properties at infinite dilution. Table 2 lists the isosteric heat q0st and Henry’s constant KH for CO2, CH4, N2, and H2 adsorption at infinite dilution. The extent of adsorption in the Henry regime depends primarily on the interaction strength between CO2 and adsorbent, which is reflected in q0st and KH. The predicted q0st and KH in all the PAFs considered follows the order CO2 > CH4 > N2 > H2, implying the strong interaction of CO2 with the framework. With the addition of functional group to the linker, the framework densityFf decreases in the order of PAF-1 > NH2_PAF-1 > MO_PAF-1 > DHF_PAF-1 which is opposite to the free volume Vfree. The KH for CO2 predicted from simulation increases in the order PAF-1 < NH2_PAF-1 < MO_PAF-1 < DHF_PAF-1. Isosteric heat at infinite dilution q0st predicted from simulation follows the order MO_PAF-1 > DHF_PAF-1 > NH2_PAF-1 > PAF-1, in slight disagreement with the binding energies of CO2 with model functional group which follow the order tetrahydrofuran > ethylamine > dimethylether (Figure 1). This is due to that the CO2 molecule interacts with two neighboring -OCH3 groups in MO_PAF-1 but interacts with just one O atom in DHF_PAF-1, resulting in a slightly increased q0st in the former. In addition, the KH and q0st does not follow the similar trend for the adsorbates as shown in Table 2. The reason is that q0st primarily depends on the adsorption energy, whereas KH depends on both energetic and entropic effect.

CO2 Adsorption Isotherms. Figure 3 shows the adsorption isotherms of CO2 in PAF-1 and the three different functional PAFs at 298 K in the low-pressure and medium-to-high-pressure regimes. CO2 adsorption capacity at low pressure (Figure 3a) follows the order DHF_PAF-1 > MO_PAF-1 > NH2_PAF-1 > PAF-1 which is consistent with KH predicted in Table 1. However, at high pressures (>1000 kPa) the order is reversed (Figure 3b) as the adsorption capacity is now primarily determined by the free volume. At 100 kPa, CO2 adsorption in DHF_PAF-1 reaches approximately 10 mmol/g (44 wt %) which is almost two times greater than in traditional adsorbent, zeolite NaX and NaY.35,36 However, the CO2 capacity is still lesser than those observed in MgMOF-74 at pressures below 100 kPa, whereas the reverse is true at above 100 kPa. The reason is due to strong coordination of CO2 with the unsaturated metal cation present in MgMOF-74 at very low pressure, while the less energetic sites are adsorbed at high pressure.37 In addition, the predicted CO2 adsorption in DHF_PAF-1 is also greater than in most amine-functionalized MOFs such as Zn-aminotriazolatooxalate MOF (3.78 mmol/g),7 bio-MOF-11 (4.1 mmol/g),8 bioMOF-1 (4.46 mmol/g at 273 K),10 triazolate-bridged MOF (3.24 mmol/g)9 and charged rht-MOF (3 mmol/g).29 Adsorption of Binary Mixture. Next we simulated the adsorption isotherms of the CO2/N2 mixture (bulk composition 15:85 as roughly in the flue gas) in PAF-1 and the three functional PAFs at 298 K (Figure 4). Both CO2 and N2 exhibit a linear isotherm with increasing pressure in PAF-1 and NH2_PAF-1 as a result of the substantially higher pore volume compared to that in MO_PAF-1 and DHF_PAF-1. However, at high pressure both CO2 and N2 approaches saturation in NH2_PAF-1, MO_PAF-1 and DHF_PAF-1, except for CO2 in PAF-1. The adsorption amount of N2 in PAF-1 is larger than CO2 at low to moderate pressures due to the higher molar ratio of N2 to CO2 in the bulk CO2/N2 mixture. At high pressures (say above 5 MPa), the adsorption amount of CO2 is greater than N2 due to the increased cooperative interactions of CO2 molecules. (We found that when the bulk composition of CO2/N2 mixture is higher than 20:80, more CO2 is adsorbed than N2 in PAF-1; see Figure S6 in the Supporting Information). In the three functional PAFs and especially DHF_PAF-1, more CO2 is 3454

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Figure 2. Channel morphologies and radius of the channel along the XY plane in crystalline model: (a) PAF-1, (b) NH2_PAF-1, (c) MO_PAF-1, and (d) DHF_PAF-1.

adsorbed than N2 due to the increase in electrostatic interaction in addition to dispersion interactions. Moreover, a steep increase in CO2 adsorption is found in MO_PAF-1 and DHF_PAF-1 (Figure 4c and 4d), due to the enhanced electrostatic interaction between the negative oxygen of the functional group present in

the framework and positive carbon atom of CO2. To explore the structural information for CO2 in these functional PAFs, the radial distribution functions g(r) between CO2 and N atom in NH2_PAF-1 and O atom in MO_PAF-1 and DHF_PAF-1 are shown in Figure 5. A pronounced peak in g(r) for CO2 and N 3455

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atom is observed at r = ∼ 3.8 Å in NH2_PAF-1. In MO_PAF-1, there exist a peak at r = ∼ 4.0 Å and second peak at r = ∼ 8.6 Å. Interestingly, in DHF_PAF-1, two distinct peaks are present at r = ∼ 2.9 and 4.1 Å indicating a stronger electrostatic interaction Table 2. Isosteric Heat q0st and Henry’s Constant KH Calculated from This Work q0st (kJ/mol) CO2 CH4 PAF-1

N2

KH (mmol/g/kPa) H2

CO2

CH4

N2

H2

12.76 9.25 7.44 6.59 0.01204 0.00640 0.00353 0.00142

NH2_PAF-1 21.05 9.63 8.14 6.83 0.01759 0.00392 0.00216 0.00087 MO_PAF-1 33.68 15.52 12.76 7.79 0.15248 0.00771 0.00304 0.00068 DHF_PAF-1 30.19 12.90 12.20 7.47 0.32987 0.00658 0.00359 0.00057

between CO2 and O atom of THF-like ether group present in the framework. The second peak refers to the interaction of CO2 with the O atom of a neighboring ligand, confirming multiple interactions. Adsorption isotherms of the CO2/CH4 and CO2/H2 mixtures were also simulated in the four PAFs and showed in Figure S7 and S8 in the Supporting Information. Similar to the CO2/N2 mixture adsorption discussed above, CO2 is more preferentially adsorbed than CH4 and H2 especially in MO_PAF-1 and DHF_PAF-1. The separation of CO2/CH4, CO2/N2, and CO2/H2 mixture is quantified by selectivity Si/j = (xi/xj)(yj/yi), where xi and yi are the mole fractions of component i in adsorbed and bulk phases, respectively. Figure 6 shows the adsorption selectivity for CO2/CH4, CO2/N2, and CO2/H2 mixture for different PAFs. The selectivity shows a different trend in each PAF for all the three mixtures. For

Figure 3. CO2 adsorption isotherms at 298 K in PAF-1 and the three functionalized PAF-1 at (a) low and (b) moderate pressure based on crystalline model.

Figure 4. (a) Adsorption isotherms for 15:85 CO2/N2 mixture in (a) PAF-1, (b) NH2_PAF-1, (c) MO_PAF-1, and (d) DHF_PAF-1 at 298 K based on crystalline model. Symbols: upward triangle, CO2; downward triangle, N2. The inset graph refers to the linear scale. 3456

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Figure 5. Radial distribution functions of CO2 around (a) N in NH2_PAF-1, (b) O in MO_PAF-1, and (c) O in DHF_PAF-1 for CO2/N2 mixture based on crystalline model at 0.01 MPa.

Figure 6. Adsorption selectivity for (a) CO2/CH4, (b) CO2/N2, and (c) CO2/H2 mixtures based on crystalline model.

CO2/CH4 mixture, the selectivity in PAF-1 remains nearly constant at low pressure and increases slightly with pressure and finally approaches saturation at high pressure. Similar behavior is observed for NH2_PAF-1, with the selectivity higher than in PAF-1 due to the increased interaction of CO2 with the NH2_PAF-1 structure. The predicted selectivity in NH2_PAF-1 is ∼5 which is similar to those observed in amino-substituted MOF, IRMOF-1(NH2)4 where the selectivity ranges from 5 to 6.38 The selectivity in MO_PAF-1 decreases monotonically with increasing pressure as consequence of two factors. First, the more energetically favorable sites are occupied initially (that is, the CO2 molecules are located near the partial negative oxygen atom of -OCH3 group) and then the less favorable sites at high pressures. The second reason is the significant reduction in the electrostatic interactions between CO2 and MO_PAF-1 with increased loading. The selectivity in DHF_PAF-1 is much higher than that in the other three PAFs and shows less variation with the pressure. Overall, the selectivity follows the order DHF_PAF-1 > MO_PAF-1 > NH2_PAF-1 > PAF-1 in all the three mixtures, particularly at low to moderate pressures. To probe the role of the electrostatic interaction in the highly selective adsorption of CO2 in DHF_PAF-1, we performed additional simulations by setting all atomic charges on the framework to zero; the predicted selectivities decrease by 1 order of magnitude, particularly in MO_PAF-1 and DHF_PAF-1 (Figure S9 in the Supporting Information). This clearly demonstrates the important role of electrostatic interactions in the selective adsorption of CO2 over other gases such as CH4, N2, and H2 in DHF_PAF-1. In addition, in the absence of electrostatic interactions, the selectivity of all three mixtures follow the order MO_PAF-1 > DHF_PAF-1 > NH2_PAF-1 >

PAF-1 at low to moderate pressures (0.1-1.0 MPa), which is consistent with the increasing pore radius (see Figure 2). Therefore, the pore-size decrease due to the functionalization also increases the CO2 selectivity, but the magnitude of the enhancement is much less than that due to the electrostatic interaction. Effect of H2O on Adsorption Selectivity. Power-plant flue gas is saturated with water vapor, so it is desirable of a CO2 adsorbent to be water-resistant. We examined the effect of H2O on adsorption selectivity and found the selectivity remains more or less the same in all the functionalized PAF-1, except DHF_PAF-1. This is due to the weak interaction of H2O with the highly hydrophobic PAF-1 structures. Surprisingly, in DHF_PAF-1, the effect of H2O on adsorption selectivity is more pronounced. Figure 7 shows the adsorption selectivity for CO2/ CH4, CO2/N2 and CO2/H2 mixtures in the absence and presence of 0.1 wt % H2O in DHF_PAF-1. The presence of H2O reduces the selectivity in all the three mixtures, because H2O, a highly polar molecule, interacts with the THF-like etheroxygen present in the framework more strongly than CO2. This causes a decrease in the adsorption amount of CO2 and subsequently the selectivity. The decrease in selectivity is similar to the effect of H2O on the adsorption of CO2/CH4 in rho-ZMOF.6 However, the percentage decrease in selectivity in the presence of H2O in rho-ZMOF is higher (varying from 75 to 95% at low to moderate pressure), while it ranges from 50 to 80% in DHF_PAF-1. This is because H2O exhibit strong electrostatic interaction with the extra-framework cations present in rhoZMOF, when compared to ether-oxygen present in DHF_PAF-1. We note that even in the presence of H2O, 3457

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Figure 7. Adsorption selectivity for (a) CO2/CH4, (b) CO2/N2, and (c) CO2/H2 mixtures in the absence (closed symbols) and presence (open symbols) of 0.1 wt % H2O in crystalline DHF_PAF-1 model.

Figure 8. (a) Adsorption isotherms of CO2 and (b) selectivity for CO2/N2 mixture in PAF-1 and DHF_PAF-1 based on crystalline and amorphous model. The closed (open) symbols are based on crystalline (amorphous) models. Legend: circle, PAF-1; square, DHF_PAF-1.

DHF_PAF-1's selectivity for CO2 is still about twice that of NH2_PAF-1 and five times that of PAF-1. Adsorption Isotherm and Selectivity in Amorphous PAF-1 Structure. Because of the relatively amorphous nature of synthesized PAF-1,27 one wonders if the crystalline model derived from the diamond structure is a realistic representation of the synthesized material. For comparison, we also constructed an amorphous model for PAF-1 and DHF_PAF-1. A Connolly surface area of 4930 m2/g and a solvent-accessible surface area of 5680 m2/g were calculated for the amorphous PAF-1, based on a probe radius of 1.82 Å. The predicted solvent-accessible surface area matches closely with the experimental BET surface area (5600 m2/g).16 A similar comparison has been made for MOF materials by D€uren et al., who found the accessible surface area to be in good agreement with the experimental BET surface area.39 We also simulated the powder X-ray diffraction pattern for the proposed amorphous PAF-1 structure (Figure S1 in the Supporting Information). It can be seen that no peaks were observed, indicating the amorphous nature of the constructed PAF-1 model. Next we predicted CO2 adsorption isotherm (Figure S10 in the Supporting Information) in the proposed amorphous PAF-1 model (with the Lennard-Jones parameters taken from DREIDING force field) and compared with experiment and the predicted isotherms based on crystalline PAF-1 model. We found that the simulated isotherm in amorphous PAF-1 model over predicts the experimental results more than the crystalline model, even though both models show a linear behavior within the pressure range

considered in this study. The reason for this overprediction of adsorption in the amorphous model may be due to the increase in cooperative interactions between CO2 and the amorphous framework. We also predicted the adsorption capacity of CO2 and selectivity for CO2/N2 mixture in amorphous DHF_PAF-1 (Figure 8). Much higher adsorption capacity and selectivity are predicted in the amorphous model when compared to the crystalline one. So the role of the furan functional group in enhancing CO2 selectivity is found in both crystalline and amorphous models, though it is more pronounced in the amorphous one. From comparison with available experimental adsorption data, the crystalline model seems to be better than the amorphous one we have constructed. With more sophisticated amorphous models, better agreement with experiment may be achieved, but we believe that our conclusions regarding the role of the functional groups will still be valid. Comparison of CO2/CH4, CO2/N2 and CO2/H2 Selectivity with Previous Work. Now we compare our predicted selectivity based on crystalline model with the literature data. The selectivity for CO2/CH4 in DHF_PAF-1 at infinite dilution is KH(CO2)/ KH(CH4) ≈ 50 and reduces to 18 at ambient condition. The predicted selectivity in DHF_PAF-1 is higher than those found in -COOH substituted MIL-53(lp), where the selectivity is ∼17 at 0.1 bar.12 The selectivity for CO2/N2 mixture in DHF_PAF-1 is KH(CO2)/KH(N2) ≈ 92 at infinite dilution and reduces to 54 at 1 atm. Similarly the selectivity for CO2/H2 mixture in DHF_PAF-1 is KH(CO2)/KH(H2) ≈ 580 at infinite dilution 3458

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Langmuir and reduces to 340 at 1 atm. These selectivities are higher than those reported in most MOFs, COFs, ZIFs and zeolites, but still lesser than those reported in NaX, NaY, MgMOF-74 and MOFs with extraframework ions as shown in Table S2 (Supporting Information). However, CO2 adsorption capacity in NaX, NaY, MgMOF-74, and MOFs with extraframework ions is lower than in DHF_PAF-1 at ambient conditions, as discussed earlier. Moreover, the presence of water vapor is expected to dramatically reduce NaX and NaY’s selectivity for CO2 due to strong interaction between water and extra-framework cations; after all, conventional zeolites are often used as desiccants. But the quantitative extent of the reduction has not been reported in the literature of molecular simulations. Delta loading or working capacity is a very important parameter for adsorbent selection,40 which is defined as the difference of adsorbed amounts of one component in a mixture between high (production step) and low (regeneration step) pressure in a pressure-swing adsorption process. The delta loadings of CO2 between 1.0 and 0.1 MPa for CO2/CH4 (50:50), CO2/N2 (15:85), and CO2/H2 (15:85) mixture in DHF_PAF-1 are predicted to be around 10.04, 8.92, and 9.77 mmol/g, respectively. For a CO2CO-CH4 mixture of bulk composition 70:15:15, the working capacity is around 9.60 mmol/g at the same condition, higher than those calculated in BPL activated carbon (3.43 mmol/g), NaX (1.44 mmol/g), and Cu-BTC (7.37 mmol/g).40 As stated in the Introduction, this study was motivated by the need to capture CO2 from power-plant flue gas which is usually emitted at ambient pressures. Hence, the most relevant results from the present work are those for CO2/N2 mixtures at low to moderate pressures (around 1 bar). In this regime, we have shown that tetrahydrofuran-like ether-functionalized PAF-1 boasts of high adsorption capacity than many other porous materials and also higher selectivity than the aminefunctionalized PAF-1.

’ CONCLUSIONS We designed porous aromatic frameworks (PAFs) with polar organic functional groups for CO2 separation, guided by quantum chemical calculations, and used GCMC simulation to predict CO2/CH4, CO2/N2, and CO2/H2 mixture selectivity. A reasonably good agreement was obtained between the simulation results and experimental data for the adsorption isotherms of CO2, H2, and N2 in crystalline PAF-1 model. Among the three functional PAFs considered, PAF-1 functionalized with tetrahydrofuran-like ether groups shows high adsorption capacity for CO2 (10 mol per kilogram of adsorbent at 1 bar and 298 K) and high selectivity for CO2/CH4, CO2/N2 and CO2/H2 mixtures at ambient conditions, in agreement with the strongest binding found between CO2 and THF among numerous molecular functional groups considered. This study reveals that adding THF-like ether groups to a porous framework yields much higher CO2 selectivity over CH4, H2, and N2 than the amine functionality. It is expected that incorporation of this kind of functional group into other porous materials such as MOFs and ZIFs via functional building units or postsynthetic modification may also lead to more selective CO2 separation. ’ ASSOCIATED CONTENT

bS Supporting Information. Force field parameters for adsorbates, simulated powder-XRD pattern for the proposed

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amorphous PAF-1 structure, electrostatic potential of tetrahydrofuran, selectivity comparison table, cluster for atomic partial charge calculation, adsorption isotherms for CO2, H2, and N2, and mixture isotherms. This material is available free of charge via the Internet at http://pubs.acs.org.

’ AUTHOR INFORMATION Corresponding Author

*E-mail: [email protected].

’ ACKNOWLEDGMENT This work was supported by the Division of Chemical Sciences, Geosciences, and Biosciences, Office of Basic Energy Sciences, U.S. Department of Energy. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC0205CH11231. ’ REFERENCES (1) Krishna, R. J. Phys. Chem. C 2009, 113, 19756. (2) Krishna, R.; van Baten, J. M. J. Membr. Sci. 2010, 360, 323. (3) Janiak, C.; Vieth, J. K. New J. Chem. 2010, 34, 2366. (4) D’Alessandro, D. M.; Smit, B.; Long, J. R. Ang. Chem. Int. Ed. 2010, 49, 6058. (5) Babarao, R.; Jiang, J. W. J. Am. Chem. Soc. 2009, 131, 11417. (6) Babarao, R.; Jiang, J. W. Energy Environ. Sci. 2009, 2, 1088. (7) Arstad, B.; Fjellvag, H.; Kongshaug, K. O.; Swang, O.; Blom, R. Adsorption 2008, 14, 755. (8) An, J.; Geib, S. J.; Rosi, N. L. J. Am. Chem. Soc. 2010, 132, 38. (9) Demessence, A.; D’Alessandro, D. M.; Foo, M. L.; Long, J. R. J. Am. Chem. Soc. 2009, 131, 8784. (10) An, J.; Rosi, N. L. J. Am. Chem. Soc. 2010, 132, 5578. (11) Couck, S.; Denayer, J. F. M.; Baron, G. V.; Remy, T.; Gascon, J.; Kapteijn, F. J. Am. Chem. Soc. 2009, 131, 6326. (12) Torrisi, A.; Bell, R. G.; Mellot-Draznieks, C. Cryst. Growth Des. 2010, 10, 2839. (13) Torrisi, A.; Mellot-Draznieks, C.; Bell, R. G. J. Chem. Phys. 2009, 130. (14) Vogiatzis, K. D.; Mavrandonakis, A.; Klopper, W.; Froudakis, G. E. Chemphyschem 2009, 10, 374. (15) Torrisi, A.; Mellot-Draznieks, C.; Bell, R. G. J. Chem. Phys. 2010, 132. (16) Ben, T.; Ren, H.; Ma, S. Q.; Cao, D. P.; Lan, J. H.; Jing, X. F.; Wang, W. C.; Xu, J.; Deng, F.; Simmons, J. M.; Qiu, S. L.; Zhu, G. S. Angew. Chem., Int. Ed. 2009, 48, 9457. (17) Trewin, A.; Cooper, A. I. Angew. Chem., Int. Ed. 2010, 49, 1533. (18) Lan, J. H.; Cao, D. P.; Wang, W. C.; Ben, T.; Zhu, G. S. J. Phys. Chem. Lett. 2010, 1, 978. (19) Sun, Y. X.; Ben, T.; Wang, L.; Qiu, S. L.; Sun, H. J. Phys. Chem. Lett. 2010, 1, 2753. (20) Lin, H. Q.; Freeman, B. D. J. Mol. Struct. 2005, 739, 57. (21) Ahlrichs, R.; Bar, M.; Haser, M.; Horn, H.; Kolmel, C. Chem. Phys. Lett. 1989, 162, 165. (22) Materials Studio 4.3; Accelrys: San Diego, CA, 2008. (23) Jiang, J. X.; Trewin, A.; Su, F. B.; Wood, C. D.; Niu, H. J.; Jones, J. T. A.; Khimyak, Y. Z.; Cooper, A. I. Macromolecules 2009, 42, 2658. (24) Sun, H. J. Phys. Chem. B 1998, 102, 7338. (25) Mayo, S. L.; Olafson, B. D.; Goddard, W. A. J. Phys. Chem. 1990, 94, 8897. (26) D€uren, T.; Bae, Y. S.; Snurr, R. Q. Chem. Soc. Rev. 2009, 38, 1237. (27) Besler, B. H.; Merz, K. M.; Kollman, P. A. J. Comput. Chem. 1990, 11, 431. 3459

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