Computational Screening of Functionalized UiO-66 Materials for

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Computational Screening of Functionalized UiO-66 Materials for Selective Contaminant Removal from Air Hakan Demir, Krista S. Walton, and David S. Sholl J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.7b07079 • Publication Date (Web): 29 Aug 2017 Downloaded from http://pubs.acs.org on September 6, 2017

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The Journal of Physical Chemistry

Computational Screening of Functionalized UiO-66 Materials for Selective Contaminant Removal from Air Hakan Demir, Krista S. Walton and David S. Sholl1* School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, 311 Ferst Drive NW, Atlanta, Georgia 30332-0100 Abstract Metal-organic frameworks (MOFs) have potential applications for efficient filtration of toxic gases from ambient air. We have used computational methods to examine the efficacy of functionalized UiO-66 with a wide range of functional groups to identify materials suitable for selective adsorption of NH3, H2S, or CO2 under humid conditions. To this end, adsorption energies at various favorable positions in the structures are obtained from both cluster-based and periodic models. Our cluster calculations show that DFT calculations using the PBE-D2 functional can reliably predict the ranking of materials obtained at the MP2 level. Performing PBE-D2 calculations using periodic models gives rankings of materials that are significantly different than from cluster calculations, showing that confinement effects are important in these materials. On the basis of these calculations, recommendations for high performing materials are made using PBE-D2 calculations from periodic models that use the full structure of each MOF.

1

*

Corresponding author email: [email protected] 1 ACS Paragon Plus Environment


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Introduction Filtration of harmful gases from ambient air has always been an important research area due to pollution caused by human activities. There are two broad strategies for improving air quality, namely capturing the gases at the source before they are released to the atmosphere and removing them from ambient air.1 For both purposes, adsorbent based solutions have received a great deal of interest. Although activated carbon can have high interactions for organic species they are not very effective for capturing high vapor pressure molecules and polar adsorbates.2 The commercial adsorbents such as zeolites are not as effective in humid conditions and better materials are being sought.3 Gases that are of great interest for capture in industrial settings include NH3 and H2S since they are toxic and can emerge during manufacturing processes.4–6 Metal-organic frameworks (MOFs) are attractive candidates for air filtration due to their favorable properties such as high surface area, pore volume, tunable pore size and chemistry.7–9 They are composed of organic linkers connected with metal nodes and used in many areas such as gas storage/separation10–19, catalysis20–24, sensing25–29, drug delivery.30–34 As opposed to conventional adsorbents, MOF affinities for a particular adsorbate can be tailored by grafting functional groups with different polarities, sizes, and affinities.35–38 However, with respect to zeolites, many MOFs have limited humidity, low thermal, hydrothermal and chemical stability.39–41 One of the problems that should be addressed during air purification is coadsorption of water from ambient air, which can degrade the adsorbent. An ideal adsorbent should have both high affinity for a toxic gas and high selectivity towards that gas over water vapor while being stable in humid air.7 Owing to the different chemical properties of toxic gas in the air, it is useful to develop adsorbents that can be functionalized to adjust their affinities towards specific species.42 Among MOFs, UiO-66 has been extensively studied not only because it is functionalizable but also it has high thermal43,44, mechanical45,46, water42,43,47, chemical48–50 stability and ease of regeneration47,51. The thermal and chemical stability of the UiO-66 structure is ascribed to Zr inorganic blocks, their high coordination number, strong bonds between inorganic blocks and the linker and strong Zr-O bonds.39,44,45,52–58 UiO-66 stability is preserved even after it is treated in very acidic (pH=1) or basic (pH=14) environments.59 Functionalities including amino, azide, nitro, halogen, methyl, hydroxyl, and carboxylic acid30,39,60–72 can be experimentally introduced to UiO-66 through isoreticular synthesis. Garibay et al.64 synthesized -NO2, -NH2, –Br and naphthalene functionalized UiO-66 and found similar thermal stability compared to parent UiO-66 for the last two functional groups while the first two functionalized structures had lower stabilities. Jasuja et al.73 studied ammonia adsorption on UiO-66-R (R = -OH, -(OH)2, -NO2, -NH2, -SO3H, and -(COOH)2) and found UiO-66-SO3H and UiO-66-(COOH)2 to have lower ammonia capacities than UiO-66-OH and UiO-66-NH2. This was linked to considerable decrease in porosities due to bulkier functional groups. Inferred from high stability of the UiO-66 framework and shape of the breakthrough curves, it was suggested that it be unlikely for ammonia to react chemically.

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Hu et al.74 experimentally studied several functionalized UiO-66 materials for CO2 adsorption and found UiO-66-(COOH)2 had high CO2 working capacity but also considerable water uptake at low pressures. Cmarik et al.75 measured CO2 and H2O adsorption on UiO-66, UiO-66-NH2, UiO-66-NO2, UiO-66-Naphyl, UiO-66-(OCH3)2 and identified UiO-66-NH2 as the most promising material for vacuum swing adsorption in dry conditions. Nik et al.76 demonstrated increased CO2 adsorption at 35°C on amine functionalized UiO-66 compared to parent UiO-66. Huang et al.’s work77 revealed that –NO2, -NH2, and –(CH3)2 functionalized UiO-66 structures had higher CO2 loading compared to bare UiO-66. Jasuja et al.78 determined that functionalizing UiO-66 with –CH3 group improved CO2 affinity while reducing water adsorption at low pressure. Jasuja et al.’s experimental work79 have indicated that –(CH3)2 functionalization diminished water adsorption by ~50% with respect to the parent UiO-66 and enhanced CO2 interactions. Biswas et al.35 demonstrated UiO-66-X (X=NO2, NH2, OH, CH3, (CH3)2) had higher CO2 loading than bare UiO-66. In Lin Foo et al.’s work it was demonstrated that incorporation of sulphonic acid into UiO-66 enhanced CO2 adsorption.63 Schoenecker et al.80 observed that amine functionalized UiO-66 had higher water affinity compared to the parent material. Kim et al.56 measured water adsorption of UiO-66, UiO-66-NH2, UiO-66-OH, UiO-66(OH)2 and illustrated increased water uptake at low relative humidity for functionalized UiO-66 materials. The body of work described above indicates that UiO-66 can be functionalized with a wide variety of functional groups, and that the resulting family of materials may be interesting in applications requiring selective adsorption. It is therefore interesting to understand which specific functionalized materials may be best suited to particular applications. This motivated Kim et al.8 to use computational methods to examine a wide range of functional groups for selective adsorption of ammonia in UiO-66. Specifically, quantum chemistry calculations were performed using clusters chosen to mimic ammonia adsorption in dry and humid conditions UiO-66 for 21 functional groups including halogens, metal carboxylates, hydroxyls, and amines. These calculations predicted metal carboxylates (-COOCu, -COOAg) to be most promising functional groups in humid conditions, with –COOCu showing the highest affinity for ammonia. A potential disadvantage of cluster-based calculations of this type is that they cannot account for effects due to confinement in the nanopores of UiO-66. In related work partially addressing this issue, Yu et al.81 parameterized force fields for ammonia adsorption in four MOFs (MIL-47, IRMOF-1, IRMOF-10, and IRMOF-16) having –OH, -C=O, -Cl and –COOH functional groups at the MP2 level. The resulting force fields were then used to predict ammonia adsorption isotherms with grand canonical Monte Carlo (GCMC) simulations. Although methods to develop accurate classical force fields for molecular adsorption in nanoporous materials from electronic structure calculations have developed rapidly in recent years82–89, they still require extensive calculations for each specific adsorbent of interest. It is therefore challenging to adopt this approach for multiple adsorbing species in a diverse collection of functionalized materials such as the UiO-66 family we examine in this paper. As a result, we focus in this work on using results from electronic structure calculations directly to give guidance into the choice of functional groups in UiO-66 for selective adsorption.



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We have functionalized UiO-66 to investigate the effect of functional groups on NH3, H2S, CO2 and H2O affinities and identify materials that are selective for these gases in humid conditions. Computational Methods Electronic structure calculations were performed using both cluster and periodic models to assess the effect of confinement on molecular adsorption. For the cluster models used below, calculations were performed using at the Møller–Plesset second-order perturbation (MP2) level and with Density Functional Theory (DFT). For the fully periodic models, only DFT calculations were feasible. We show below that the rankings of functional groups in cluster calculations at the MP2 and DFT levels are highly correlated, which implies that results at the DFT level from periodic systems give reliable results. Similar to the work of Kim et al.8, the cluster models are composed of functional groups attached to C6H5 or C6H4 (for bifunctional groups such as –F2). We considered the 36 functional group shown in Table 1; this list includes many examples not considered in the work by Kim et al.8 We found that for a number of the bulkier functional groups indicated in Table 1 in italics, optimization of periodic models of the functionalized UiO-66 variants is problematic, so results for these functional groups are not discussed below for periodic systems (i.e. -COOAg, -COOCu etc.). Binding energies were defined by = − −

(1)

where Ebinding, Eadsorption complex, Eadsorbate and Eadsorbent are binding energy, total energy of adsorption complex, total energy of isolated adsorbate and total energy of isolated adsorbent, respectively.

Table 1. Functional Groups Investigated (Adsorption energies for those in italics are not available in periodic models) -(CF3)2 -(CH3)2 -(COOH)2 -(NH2)2 -(OCH3)2 -(OH)2 -Br -(Br)2 -C=O -CF3 -CH2-F -CH2-NH2

-CH3 -Cl -(Cl)2 -CN -CHO -COOAg -COOCu -COOH -COOK -COOLi -COONa -F

-F2 -I -I2 -NCO -NH2 -NO2 -NO3 -OCH3 -OH -OOH -SO3H -(NO2)2


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For bifunctional groups, the functional groups were incorporated on the ring in para position with respect to each other. Cluster calculations are done for all adsorbates except CO2. The initial positions of adsorbates with respect to the UiO-66 models are selected in a way that hydrogen bonding and/or Lewis acid-base interactions are possible.8 Starting from those positions, all atoms of the cluster and periodic models were relaxed to an energy minimum. The cluster optimizations are done using GAUSSIAN 0990 at the MP2 level and separately using the M062X and PBE-D2 DFT functionals. For the silver atom, the LanL2DZ eﬀective core potential was used, while for all other atoms a 6-31+G(d,p) basis set was used. Basis set superposition errors (BSSE)91 are incorporated in the binding energy calculations using the counterpoise method. For calculations with periodic materials, the parent UiO-66 structure was taken from Jasuja et al.78 and hydrogen(s) were replaced in the benzene ring with the functional groups of interest. These calculations used 1(1(1 unit cells with lattice parameters of ~14-15 Å in each direction, The Vienna Ab-initio Simulation Package (VASP)92 was used at the PBE-D293 level with a 400 eV kinetic energy cutoff and one Г-centered k-point. For structural optimization, the total energy and ionic force convergence criteria were 1 ) 10+, -. and 3 ) 10+0 -.⁄1, respectively. UiO-66 has a 3D cubic framework composed of Zr6O4(OH)4 nodes linked with 1,4-benzenedicarboxylate linkers (BDC).30 It has centric octahedral cages (11 Å) connected to eight tetrahedral cages (8 Å) with triangular windows (6 Å) (Figure 1).94

Figure 1. UiO-66 Structure along the a axis (H, C, O and Zr are shown in white, gray, red and cyan, respectively)

Dispersion energies are derived from PBE-D2 calculations using the second term of the DFT+D2 approach93 345+3 = 67+345 8

(2)

where F +K

GH = −9: ∑IK

GH ∑F DIJK

?

? A BCD E @=>


(3)


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Here, 9: is the scaling factor, L is the number of atoms, A is the damping factor, CD is the interatomic distance between atom pair i and j, MD: is the dispersion coefficient. Another quantity that is important for gas adsorption processes in terms of energy cost is the isosteric heat of adsorption, N75 , which can be defined using the Clausius-Clapeyron equation75 OPQ @5 R

= −S

TU V T5 O

(4)

To heuristically evaluate the selective adsorption of an adsorbate in humid conditions, the binding energy differences between the adsorbate of interest and water was calculated. For example, to identify functional groups that may be selective for NH3 over H2O, ∆ = BENH3 – BEH2O was assessed. Values of ∆ that are negative imply the potential to be selective towards NH3 over H2O. This simple approach clearly neglects potential synergistic interactions between adsorbates, but it provides a useful method for an initial comparison. In particular, any materials that show a strongly positive ∆ are unlikely to be favorable for capture of the targeted molecules (ammonia in the example above) in a humid environment. Although structure stability is not investigated in this computational study, it should be noted that in the experiments the incorporated functionalities may not always preserve the thermal stability of the parent UiO-66 structure as it was reported by Garibay et al.64 for UiO-66-NH2 and UiO-66-NO2. The reduced thermal stability of UiO-66-NH2 was also indicated by DeCoste et al.41 Results & Discussion Comparison of MP2 and DFT results for clusters Because our cluster calculations can be performed at the MP2 level, they can be used to determine whether lower level DFT calculations can reliably describe the binding of small molecules with functional groups in UiO-66. If DFT calculations can be shown to give useful information in this context, then they can also be used to assess confinement effects in fully periodic structures. The binding energies for NH3, H2S, and H2O were calculated for the [-(CF3)2, -(CH3)2, (COOH)2, -(NH2)2, -(OCH3)2, -(OH)2, -Br, -(Br)2, -C=O, -CF3, -CH2-F, -CH2-NH2, -CH3, -Cl, (Cl)2, -CN, -CHO, -COOAg, -COOCu, -COOH, -COOK, -COOLi, -COONa, -F, -F2, -I, -I2, NCO, -NH2, -NO2, -NO3, -OCH3, -OH, -OOH, and -SO3H] functionalized and unfunctionalized phenyl species using MP2 and separately with DFT using the PBE-D2 and M06-2X functionals. Figure 2 compares the DFT results for the full set of phenyl species to the MP2 results. In each case, only the most favorable binding configuration obtained in our calculation is reported. The binding energies shown in Figure 2 are also listed in Tables S1-3. The PBE-D2 and MP2 results are strongly correlated; the linear fits shown in the figure have R2 = 0.98, 0.97 and 0.98 for NH3, H2S, and H2O, respectively. The correlation between the M06-2X results and MP2 are slightly weaker on average; R2 = 0.95, 0.93 and 0.94 for NH3, H2S, and H2O, respectively. Overall, these observations imply that if DFT is used to order the relative binding energy among a set of functionalized UiO-66 materials that PBE-D2 is slightly preferable to M06-2X, although both 6 ACS Paragon Plus Environment

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give meaningful results. We also performed calculations for a subset of materials at the PBED3(BJ) level of theory; these binding energies are very highly correlated with the binding energies from the PBE-D2 level, as shown in Figure S2. Although the PBE-D2 results are useful for ordering the binding energies of the various functional groups, there is a small but systematic discrepancy between the DFT and MP2 results. One way to characterize this discrepancy is the slopes of the linear fits shown in Figure 2, which for PBE-D2 are 1.10, 1.22, and 1.11 for NH3, H2S, and H2O, respectively. That is, PBE-D2 tends to give a slightly larger difference in binding energy between any two functionalized species than is found with MP2. Another way to characterize this discrepancy is with the mean absolute deviation (MAD) between MP2 and the DFT results. The MAD for NH3, H2S, and H2O is 10.7, 10.7, and 10.2 kJ/mol respectively when using PBE-D2. Thus, while DFT results can be expected to perform well for ranking the relative binding strength of functional groups, some quantitative discrepancies between binding energies at the DFT and MP2 levels exist.

Figure 2. Comparison of binding energies of NH3 (blue), H2S (green), and H2O (red) for functionalized clusters computed using MP2 and DFT. DFT results are shown from PBE-D2 calculations (left) and M06-2X calculations (right). Lines indicate linear regression fits to the data. Comparison of cluster and periodic calculations: effect of confinement We now turn to the question of whether cluster calculations can be used to reliably rank functionalized MOFs in terms of their adsorption affinity for fully periodic materials. To this end, we used periodic PBE-D2 calculations to characterize adsorption in the functionalized UiO66 materials listed in Table 1 (except for the materials listed in italics, as noted above). Figure 3 and Tables S4-6 compare the most favorable binding energies for NH3, H2S, and H2O from periodic calculations with PBE-D2 results from clusters. A somewhat surprising conclusion from this comparison is that the correlation between the periodic systems and clusters is poor. The R2 values for the linear fits in Fig. 3 are 0.492, 0.098, and 0.353 for NH3, H2S, and H2O, respectively. Very similar results are obtained if PBE-D3(BJ) is used for the periodic calculations (see Figure S3). For all three molecules, the cluster calculations fail to correctly predict the adsorbent that has the strongest adsorption in the periodic materials. For NH3, for 7 ACS Paragon Plus Environment


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example, the material predicted by our periodic calculations to bind NH3 most strongly (UiO-66OOH) is the third most strongly binding material when ranked using cluster calculations. It is of course not surprising the binding energies in periodic and cluster models differ. Cluster models do not account, for example, for long range dispersion effects. To estimate the importance of dispersion interactions in the periodic models, we determined the dispersion contribution to Ebind for molecules in the approximate center of the functionalized UiO-66 pore. In many examples we examined, the dispersion energy comprises as much as 50% of the overall adsorption energy for NH3, H2S, or CO2 (see Table S7). This would not prevent cluster calculations from being used to rank materials, however, if the dispersion contributions for all materials are similar. The results from our calculations are summarized in Fig. 4. A key observation from Fig. 4 is that the dispersion energy varies strongly among this set of materials. For H2S, for example, this variation spans ~20 kJ/mol. Critically, this variation in dispersion interactions among materials is poorly reproduced by cluster calculations (data not shown). In the remainder of this paper, we rely on PBE-D2 calculations from fully periodic crystals to assess the binding of species of interest in functionalized UiO-66 materials. The results discussed to this point indicate that this approach is considerably more reliable than similar calculations based on cluster models and also that the rankings of materials derived from these calculations are highly correlated with what would be obtained if MP2 calculations could be performed for the same materials.


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Figure 3. Comparison of lowest binding energies for NH3 (top left), H2S (top right) and H2O (bottom) in cluster and periodic models of 30 functionalized and bare UiO-66 materials.

Figure 4. Dispersion energy at pore centers of UiO-66 variants from periodic PBE-D2 calculations.

Identifying materials for selective adsorption Characterizing the binding energy of single molecules in a set of MOFs is not sufficient to consider materials for adsorption in many practical applications. In almost all cases, toxic species such as NH3 and H2S are present in environments with other molecules that can also potentially adsorb strongly, particularly H2O. It is therefore important to understand whether adsorption in 9 ACS Paragon Plus Environment


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these kinds of mixtures can be selective. To assess the potential for functionalized UiO-66 to selectively adsorb NH3, H2S, or CO2, we compared the relative binding energies of these molecules to the binding energies of H2O. This is a useful quantity to consider situations where the bulk phase concentration of both adsorbing species is low, since our calculations have focused on individual binding sites for adsorbed molecules. As noted above, this heuristic approach neglects possible synergistic effects between coadsorbed species. Figure 5 shows the relative binding energy of NH3 and H2O in the UiO-66 materials we have considered, with all results coming from periodic PBE-D2 calculations. The materials to the left of this figure have the strongest preferential binding for NH3. A number of materials bind NH3 more strongly than H2O by up to 60 kJ/mol. The –(Cl)2 and –F2 functionalized materials show the strongest preferential affinity for NH3. There are also two materials that bind H2O over 20 kJ/mol more strongly than NH3; the –(OCH3)2 and –CH2-NH2 functionalized materials bind H2O 21.7 and 37.1 kJ/mol more strongly than NH3. It is useful to note that there is not a strong correlation between the strength of NH3 binding and the possibility of preferentially binding NH3 relative to H2O. The -OOH functionalized material shows the strongest overall binding for NH3, but the H2O binding energy in this material is roughly the same as NH3. There are several examples, however, that bind NH3 strongly (i.e. have binding energies of more than 100 kJ/mol) and also bind NH3 preferentially relative to H2O.

Figure 5. Relative binding energy for NH3 compared to H2O (red) and net NH3 binding energy (blue) in functionalized UiO-66 materials determined from periodic PBE-D2 calculations.

Figure 6 shows the relative binding energy of H2S and H2O in the UiO-66 materials. In all but eight of the materials we examined, H2O binds more strongly than H2S. For three materials, the binding energy of H2O is more than 30 kJ/mol more favorable than for H2S. Similar to the situation for NH3 and H2O, there is no apparent correlation between the H2S binding energy and 10 ACS Paragon Plus Environment

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the relative binding energy of H2S and H2O. Similar data for CO2 and H2O is shown in Fig. 7. In the majority of the materials, H2O binds more favorably than CO2. The –F2 functionalized material, however, has a CO2 binding energy that is more than 25 kJ/mol stronger than H2O.

Figure 6. Relative binding energy for H2S compared to H2O (red) and net H2S binding energy (blue) in functionalized UiO-66 materials determined from periodic PBE-D2 calculations.

Figure 7. Relative binding energy for CO2 compared to H2O (red) and net CO2 binding energy (blue) in functionalized UiO-66 materials determined from periodic PBE-D2 calculations.



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Table 2. LCD and PLD of UiO-66 variants.

-(CF3)2 -(OCH3)2 -(COOH)2 -I2 -NCO -(Br)2 -SO3H -(NO2)2 -CH2-NH2 -(CH3)2 -NO3 -(Cl)2 -(NH2)2 -NO2 -(OH)2 -OCH3

LCD (Å)

PLD(Å)

5.1 5.8 5.9 6.5 7.4 7.0 6.8 5.4 7.5 7.0 6.4 7.0 7.3 6.3 7.6 7.0

2.1 2.2 2.2 2.2 2.4 2.8 2.8 2.9 2.9 2.9 3.0 3.0 3.0 3.0 3.1 3.2

-CF3 -COOH -OOH -C=O -CHO -I -CH2-F -CN -F2 -Br -Cl -CH3 -NH2 -OH Bare UiO-66 -F

LCD (Å) 7.2 6.3 7.5 9.8 7.0 7.6 7.6 7.2 7.6 7.6 7.6 7.6 7.6 7.6 8.6 7.6

PLD(Å) 3.2 3.2 3.3 3.3 3.3 3.4 3.5 3.5 3.6 3.6 3.7 3.8 3.8 3.9 4.0 4.0

These computational results can also be compared with experimental data. Although calculated binding energies and experimental heats of adsorption are not precisely the same quantities95, they can be qualitatively compared to examine ranking of functionalized UiO-66 variants. Jeremias et al.96 reported a loading averaged heat of adsorption for water (using the ClausiusClapeyron equation at 25°C and 40°C) in UiO-66 and UiO-66-NH2 of 41.3 and 89.5 kJ/mol, respectively. In our calculations, the most favorable water binding energies for those two structures were 36.5 and 69.4 kJ/mol. This shows qualitative agreement between computation and experiment, although it is unclear how much the loading averaged experimental result should differ from the binding energy of the most favorable sites in these materials. Cmarik et al.75 reported a heat of adsorption (using the Clausius-Clapeyron equation at 298, 308 and 318 K) of CO2 in UiO-66-NH2 and UiO-66-NO2 at infinite dilution as -28 and -32 kJ/mol, respectively. The most favorable states observed in our calculations for these two materials were -29.9 and 33.0 kJ/mol, respectively. Although the computational and experimental results apparently agree very well for these two materials, it should be noted that Fang et al.95 showed that the heat of adsorption of CO2 in zeolites is typically ~7-8 kJ/mol less favorable than the binding energies associated with the strongest binding sites. It is therefore reasonable to conclude that the difference in binding energies seen in experiment and calculation are very similar, although the calculated results appear to underestimate the strength of CO2 binding. Although our ability to


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compare results with experimental data is limited, it appears that our periodic PBE-D2 results are consistent with experiment. The relative binding energies discussed above are sufficient to describe mixture adsorption from low concentration bulk phase mixtures if adsorption occurs via a purely competitive mechanism. For many mixtures, particularly those involving H2O, synergistic phenomena can occur that causes adsorbed mixtures to deviate strongly from this simple description97. Adsorption of CO2 in amine-containing adsorbents is considerably enhanced, for example, by the presence of H2O.98,99 Similarly, uptake of NH3 in MOFs including UiO-66 derivatives is reduced by coadsorption with water73,100. Despite the complications associated with these synergistic effects, considering relative binding energies as we have above is likely to be more useful for selecting materials for more detailed study that simply focus on materials with the strongest overall binding energies. When UiO-66 is functionalized with bulky groups, the possibility exists that diffusion limitations may strongly limit the access of adsorbing species to the material’s pores. One initial way to estimate whether these effects may be important is to characterize the largest cavity diameter (LCD) and pore limiting diameter (PLD)101 for each material. We computed these quantities for the energy minimized adsorbate-free periodic unit cells used in our DFT calculations using zeo++102. Any quantitative description of molecular diffusion in tightly confining pores should include the effects of pore flexibility103–105, but the results from these initial calculations with rigid structures can still be useful in assessing whether diffusion limitations might exist. The LCD and PLD for each UiO-66 variant we considered is listed in Table 2, ordered from smallest to largest PLD. A number of the materials have PLD’s that smaller than 3 Å, suggesting that diffusion may be slow for larger adsorbates such as H2S. Exploring this topic further is beyond the scope of our present work, but this issue may warrant further study for materials of particular interest for specific applications.

Summary We have used computational methods to assess the ability of a large number of functionalized UiO-66 materials to competitively adsorb NH3, H2S, CO2, and H2O. We first used cluster models of UiO-66 to compare molecular binding energies at several levels of theory. This showed that a strong correlation exists between binding energies calculated with DFT and with more precise MP2 calculations. This observation is useful because it implies that DFT calculations can be used to reliably rank materials at a similar accuracy to the much more computationally demanding MP2 calculations. We next compared calculations of molecular binding energies from cluster models of UiO-66 and fully periodic crystal structures. All of these calculations were performed with DFT because of the impracticality of using MP2 calculations for fully periodic systems. An important conclusion from this comparison is that cluster calculations cannot be used to reliably rank the binding energies of molecules in the periodic crystals. That is, the impact of confinement on the binding energies that exist in the periodic crystals is strong and cannot be represented in a simple 13 ACS Paragon Plus Environment


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way (e.g. a constant energy correction) among a diverse range of functionalized materials. Although we have only examined this issue for UiO-66 variants, it appears likely that a similar conclusion will apply to other nanoporous materials with small and medium pores. Finally, we used DFT calculations of periodic materials to assess the competitive binding of water with NH3, H2S, and CO2. Our description was based on a simple heuristic approach that compared the binding energies if individual molecules, therefore neglecting any synergistic binding effects. Based on this description, for NH3, H2S and CO2 adsorption in humid air, [-(Cl)2, -F2,-SO3H, -I, -Br, -F, -(CF3)2, -(Br)2, -Cl, -CH3, -(NO2)2, -NO2, -I2, -OCH3, -(OH)2, -C=O, (COOH)2, -(CH3)2, -COOH, and -NCO], [-NO3, -OCH3, -F2, -CH3, -I, -(Cl)2 and -NCO] and [-F2, -(Cl)2, -CH3 and -NCO] functionalized materials are predicted to be the best performing materials, respectively, in terms of preferentially capturing the non-water species. Although many of the functionalized materials we studied preferentially bind NH3 relative to water, only a small number of materials preferentially bind CO2 or H2S relative to water. The approach we have used in this paper provides a useful framework for considering a large number of functionalized UiO-66 materials for selective adsorption at a level that is useful for focusing experimental efforts. There are clearly further issues that could be explored in depth for individual materials of interest, such as the impact of intrinsic and extrinsic defects106,107, coadsorption and the possible impact of functionalization on diffusive transport in the material’s pores. Nevertheless, given the level of effort that would be required to synthesize, characterize, and test that large number of materials we have considered experimentally, we feel that the level of detail we have explored in the calculations reported here is reliable enough to provide actionable insight for the future experimental study of these materials. Supporting Information Calculated lowest binding energies for NH3, H2S, and H2O in cluster and periodic models; calculated lowest binding energies for CO2 in periodic model; PBE-D2 dispersion energies for NH3, H2S, and CO2 calculated at the octahedral pore center in periodic model; lowest binding energy differences of all adsorbates in periodic models; comparison of interaction energies in periodic models with respect to summation of interaction energies in clusters and dispersion energies at the octahedral pore center of periodic models for NH3 and H2S; PBE-D3 (BJ) binding energies for a subset of functionalized UiO-66 materials for cluster and periodic models; .cif files for periodic models. Acknowledgements This material is based upon work supported by the Defense Threat Reduction Agency Contract #HDTRA1-13-C-0090. References (1)

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Computational Screening of Functionalized UiO-66 Materials for

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