Structural Characterization of Pristine and ... - ACS Publications

Article Cite This: Chem. Mater. 2018, 30, 4432−4439

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Structural Characterization of Pristine and Defective [Zr12(μ3‑O)8(μ3‑OH)8(μ2‑OH)6]18+ Double-Node Metal−Organic Framework and Predicted Applications for Single-Site Catalytic Hydrolysis of Sarin Mohammad R. Momeni* and Christopher J. Cramer

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Department of Chemistry, Minnesota Supercomputing Institute, and Chemical Theory Center, University of Minnesota, Minneapolis, Minnesota 55455, United States S Supporting Information *

ABSTRACT: Periodic PBE-D3 and M06-L calculations predict the lowest-energy proton topology of a [Zr6(μ3O)4(μ3-OH)4(μ2-OH)3]2 ZrIV−MOF (J. Am. Chem. Soc. 2017, 139, 7004−7011), which has a unique double-node structure, to be 73.4 and 64.2 kcal/mol more stable than that originally proposed. Mono- and bidefective Zr12 secondary building units derived from this topology and built by removing one and two bridging terphenyldicarboxylate linkers and saturating the remaining open ZrIV metal sites with hydroxyl and aqua groups, are predicted to exhibit higher reactivity for the hydrolysis of sarin nerve agent than other coordinatively unsaturated Zr6-based MOFs reported to date.

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INTRODUCTION Metal−organic frameworks (MOFs) are highly porous materials with repeating metal−oxide nodes interconnected by organic linkers which are known to be excellent supports and/or catalysts for a wide variety of applications.1−12 Zirconium(IV) MOFs including coordinatively saturated/ unsaturated cubic Zr-terephthalate UiO-6613,14 and coordinatively unsaturated NU-100015,16 with, respectively, [Zr6(μ3O)4(μ3-OH)4]12+ and [Zr6(μ3-O)4(μ3-OH)4(OH)4(OH2)4]8+ metal−oxide nodes, are at the center of attention owing to their exceptional thermal, chemical, and mechanical stabilities.17−26 Recently, Lin and co-workers reported the synthesis of a new “double-node” ZrIV−MOF (Zr12−Pristine) from solvothermal reaction of ZrCl4 and H2TPDC (4,4′-terphenyldicarboxylic acid) in DMF and water at 90 °C using acetic acid as modulator.27 The structure of this MOF was determined from X-ray diffraction data to be comprised of secondary building units, each combining two Zr6 metal−oxide nodes having the overall formula [Zr 6 (μ 3 -O) 4 (μ 3 -OH) 4 (μ 2 OH)3]218+, interconnected by 18 bridging TPDC linkers (Figure 1). The unit cell of Zr12−Pristine includes two Zr12 nodes and belongs to the P3̅1c space group. There are 744 atoms (including H atoms) in the unit cell with the distance between the two bridging μ2-OH groups in the neighboring Zr12 nodes being 2.8 nm (Figure 1c).27 Through X-ray absorption fine structure (EXAFS) measurements, Lin and co-workers inferred that the double-node derives from two Zr6 metal−oxide nodes, having open faces capped by one water molecule and one hydroxyl group each, © 2018 American Chemical Society

Figure 1. Structure of the Zr12−Pristine MOF. (a) The TPDC ditopic linker, (b) the Zr12 metal−oxide node, and the (c) as-synthesized unit cell along the crystallographic “a” axis. Hydrogen atoms are omitted for clarity. In a−c, gray, red, and green spheres represent C, O, and Zr atoms, respectively.

losing three adjacent water molecules from each node and using the remaining six hydroxyl groups to bridge the two nodes while simultaneously forming three hydrogen bonds between the adjacent bridging hydroxyl groups (see Figure 2).27 Lin and co-workers went on to demonstrate that decoration of Zr12−Pristine with CoII led to an active catalyst for the hydrogenative reduction of nitroarenes, nitriles, and isocyanides to their corresponding amines.27 The unique topological features of this new Zr12 doublenode MOF inspired us to employ periodic and extended cluster-based density functional theory (DFT) to study in Received: May 8, 2018 Revised: June 13, 2018 Published: June 14, 2018 4432

DOI: 10.1021/acs.chemmater.8b01913 Chem. Mater. 2018, 30, 4432−4439

Article

Chemistry of Materials

Fock/Kohn−Sham matrix is diagonalized (see SI Section S1 for discussions regarding the effects of different shrinking factors on total energies of different Zr12 isomers).53 Tolerances for coulomb and exchange sums were set to 7 7 7 7 14. Vibrational frequency calculations were performed by numerical differentiation of the analytic first derivative of the energy at the Γ point (i.e., at the center of the first Brillouin zone in reciprocal space). A fragment comprised of the metal−oxide node was used in all frequency calculations with tolerance on convergence of the total energy set to 10−11 a.u. Periodic Calculations with CP2K. Periodic calculations were performed using the PBE58 density functional with damped D3 dispersion correction59 in CP2K version 2.6.1.60 The double-zeta valence with polarization DZVP-MOLOPT basis sets and core− electron pseudopotentials according to the Geodecker−Teter−Hutter formulation61 were employed. For locating first-order saddle points along the reaction path of interest, the climbing-image nudged elastic band (CI-NEB) method62 was used. The plane-wave cutoff of the finest grid and REL_CUTOFF were set to 360 RY and 60 RY. MAX_FORCE (hartree/bohr), RMS_FORCE, MAX_DR (bohr), and RMS_DR were set to 0.0030, 0.0050, 0.0020, and 0.0050, respectively. Vibrational frequency calculations were performed numerically at the Γ point on a fragment comprised of the metal− oxide node (without the linkers) and the organophosphorus nerve agent. Extended and Truncated Cluster Calculations. Cluster models were cut from the M06-L optimized periodic unit cells of different Zr-based MOFs. To obtain these cluster models, the organic linkers around the metal−oxide node were truncated to either benzoate or formate groups with the carbon atoms of the carboxylate linkers fixed to keep the rigidity of the MOF. Geometries were then minimized in the gas phase using the M06-L density functional. The Def2-SVP63,64 basis set for organic type elements along with the SDD basis set and its associated effective core potential56 for ZrIV atoms were used. All basis sets were obtained from the basis set exchange database.65 The grid used for numerical integration in DFT was set to “ultrafine,” i.e., a pruned grid of 99 radial shells and 590 angular points per shell. The natures of all stationary points were determined by calculation of analytic vibrational frequencies, which were also used to compute molecular partition functions (298 K, 1 atm) using the conventional particle-in-a-box, rigid-rotator, quantum mechanical harmonic oscillator approximation,66 except that all vibrational frequencies below 50 cm−1 were replaced with values of 50 cm−1 (the quasi-harmonic-oscillator approximation).66 Zero-point vibrational energies and thermal contributions to enthalpy were determined from these partition functions. For transition-state structures, the presence of a single imaginary frequency corresponding to the reaction path of interest was confirmed. As we are interested in 1 M standard-state free energies in aqueous solution, a factor of RT ln(24.5), which is 1.9 kcal/mol at 298 K, was added to the free energy of all chemical species other than water in order to correct for the 1 atm to 1 M standard state concentration change. Water itself is adjusted by a factor of RT ln(55.56), which is 2.38 kcal/mol, in light of its bulk liquid state concentration.66 Electronic energies were further refined by performing single point calculations with the M06-2X67,68 meta-GGA hybrid density functional on gas phase optimized geometries with the larger Def2TZVP63,64 basis set on light elements as well as SDD on Zr atoms using the SMD continuum solvation model69 with parameters for water (ε = 78.355). Default convergence criteria for geometry optimizations and single point energy calculations were used. All reported extended and truncated cluster free energies and enthalpies are computed by combining M06-2X(SMD) single point energies with thermochemical contributions obtained at the M06-L(gas phase) level. All cluster computations for the proton topology of Zr12 and for mechanistic studies were carried out with Gaussian 0970 and Gaussian 16.71

Figure 2. Schematic of different isotopomers considered for proton topology of Zr12−Pristine. For clarity, the TPDC linkers are not shown and hydrogen bonds between the bridging μ2-OH groups are indicated with dashed lines. Relative electronic energies are given in Table 1.

additional detail the structure of its pristine, mono-, and bidefective forms. We also assessed the reactivity of the Zr12−bidefective framework for the hydrolysis of sarin nerve agent in order to compare to other coordinatively unsaturated Zr6− MOFs, including MOF-808, NU-1000, and defective UiO-66, all of which have previously been demonstrated to be effective catalysts for this process,28−49 with mechanistic details being the subject of prior theoretical studies.46−49 We note that results reported in this work could potentially be applied to other experimentally reported double-node type Zr1250 and Hf1251 MOFs in the literature.

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COMPUTATIONAL DETAILS

Periodic Calculations with CRYSTAL. Periodic M06-L metaGGA density functional52 calculations made use of the CRYSTAL 14 and 17 codes.53,54 For these calculations, we employed all-electron pob-TZVP55 Gaussian basis sets for nonmetal elements, with one added shell of d polarization functions on atoms other than H. For Zr, the Stuttgart/Cologne basis set and its associated 28-electron pseudopotential (ECP28MWB)56 was employed. Both atomic coordinates and cell parameters of all studied Zr−MOFs were fully relaxed. Exponents below 0.15 were removed from basis sets to improve convergence of the self-consistent field (SCF) procedure. Default convergence criteria of the gradients and displacements were used in geometry optimizations. Given the known sensitivity of the meta-GGA Minnesota density functionals to the size of the integration grid, the largest possible grid, i.e., the “extra extra large grid” in both CRYSTAL 14 and 17, was employed. A shrinking factor of 2 in the reciprocal space was used which according to the Pack− Monkhorst method57 determines the number of k points at which the 4433


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RESULTS AND DISCUSSION Proton Topology of Zr12−Pristine Double-Node MOF. Precise determination of the proton topology of MOFs has many implications to their chemical stability and reactivity, acid−base chemistry, their role as supports in deposition of different transition metal catalysts, conductivity, and catalysis. However, different proton topologies can be challenging to distinguish from the experimental point of view, which highlights the importance of computational approaches. We first consider the proton topology of Zr12−Pristine, noting that the topology originally assigned by Lin and co-workers was for the most part speculative.27 We examined nine different proton topologies, each optimized starting from the experimentally reported crystal structure for the heavy atoms. We note that 20 isotopomers were initially built from the experimental crystal structure however only nine of them converged to unique local minima, while the rest were either too unstable to converge or converged to one of the other nine topologies. In addition, cluster calculations were performed on benzoate-capped cluster models constructed from each periodic optimized crystal structure. The different topologies are illustrated in Figure 2, their corresponding relative energies are given in Table 1.

developed Repeating Electrostatic Potential Extracted ATomic (REPEAT) method,72 especially developed and benchmarked for porous crystalline solids such as MOFs, was used (see SI Figure S1). The computed M06-L/pob-TZVP Mulliken atomic charges show that the μ3-O groups of the Original and Zr12−I isomers are on average −0.218 au and −0.226 au, respectively, more negatively charged than corresponding μ3OH groups. Lack of separation of these highly negatively charged μ3-O moieties in the Original isomer leads to an electrostatic charge disparity with accumulation of electronic charge density in between the metal−oxide nodes, as further illustrated from computed electrostatic potential maps of the Original vs Zr12−I isomers; negative charge density accumulates at the center of the metal−oxide node of the former but is perfectly dispersed throughout the node in the latter (SI Figure S1). This finding also agrees with our energy rankings of different isotopomers: at both the M06-L/pob-TZVP and PBE-D3/DZVP-MOLOPT levels of theory predict that transferring a proton to the middle of the node stabilizes Zr12−II compared to its Zr12−VIII analogue by 23.3 and 27.3 kcal/mol, respectively, placing Zr12−II next to the most-stable Zr12−I isomer. The six bridging μ2-OH groups in all isomers interconnect by three hydrogen bonds, which have distances of 1.911−1.915 Å in the optimal Zr12−I isomer. The simulated infrared (IR) spectrum of Zr12−I in the high frequency region (blue spectrum, computed using a scaling factor of 0.956)73,74 is shown in Figure 3 (individual frequencies are listed in SI Table S3 and the full spectrum is given in SI Figure S2).

Table 1. Computed Gas Phase Periodic and BenzoateCapped Cluster Relative Electronic Energies (kcal/mol) for Different Structural Isotopomers (Figure 2) Considered for [Zr12(μ3-O)8(μ3-OH)8(μ2-OH)6]18+ Double-Node MOF

Zr12−I Zr12−II Zr12−III Zr12−IV Zr12−V Zr12−VI Zr12−VII Zr12−VIII Original

PBE-D3/ DZVPMOLOPT (Periodic)a

M06-L/ pob-TZVP (Periodic)a

M06-L/ Def2-SVP (Cluster)

M06-2X/Def2TZVP//M06-L/ Def2-SVP (Cluster)

0.0 +11.1 +27.0 +11.6 +36.7 +21.7 +39.1 +38.4 +73.4

0.0 +4.4 +11.4 +14.6 +21.9 +22.9 +25.2 +27.7 +64.2

0.0 +13.1 +6.4 +23.3 +30.4 +32.2 +35.4 +61.2 +103.1

0.0 +1.6 +2.9 +10.6 +18.8 +20.4 +24.0 +48.0 +89.8

a Normalized to the number of Zr12 metal−oxide nodes in the unit cell.

Figure 3. Simulated (scaling factor = 0.956) periodic M06-L/pobTZVP infrared spectra of the most-stable Zr12−I (blue) and its bidefective (red) counterpart. A Gaussian line shape is adopted for the raw absorbance spectra with damping factors set to 5. See SI Table S3 for assignments and SI Figure S2 for the full spectra.

The unit cell parameters are predicted to be essentially insensitive to the proton topology, varying by less than 2% over all 9 isomers (Supporting Information (SI) Table S2). The predicted energetics using fully optimized periodic M06-L/ pob-TZVP and PBE-D3/DZVP-MOLOPT methods (and a benzoate-capped cluster model at the M06-2X/Def2-TZVP// M06-L/Def2-SVP level), by contrast, span 64.2 and 73.4 (89.8) kcal/mol, respectively, with the highest energy being that originally proposed by Lin and co-workers, and the lowest being one in which μ3-O and μ3-OH groups are distributed in tetrahedral fashions within each of the two nodes (Figure 2 and Table 1), an arrangement precisely analogous to that previously established for the single nodes of NU-100016. To rationalize the computed large stability difference between the least- and most-stable Original and Zr12−I isomers, we examined changes in the electronic structure of these systems through analysis of Mulliken and Restrained Electrostatic Potential (RESP) charges. For the latter, the recently

Introducing Defects into Zr12−Pristine Double-Node MOF. Considering next catalysis, when functioning as Lewis acids, MOFs generally exploit one or more coordinatively unsaturated open metal sites to which one or more educts bind prior to reacting.1−12 We thus introduced one or two defects into crystal structures begun from the Zr12−I topology and capped the resulting ZrIV open metal sites with OH and OH2 groups, as found for open faces of NU-100016 and defective UiO-66.14 Periodic M06-L/pob-TZVP optimized crystal structures of the pristine, mono- and bi-defective Zr12 MOFs are shown in Figure 4 below (see SI Table S2 for their computed unit cell parameters). 4434


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optimized structures and unit cell parameters). The computed periodic M06-L/pob-TZVP relative electronic energies of these isomers compared to the Zr12−bi-defective isomer shown in the bottom of Figure 4 above are +1.2 kcal/mol and +1.8 kcal/mol, respectively. This confirms the relative insensitivity of the Zr12−I double-node MOF to the location of defects (all optimized periodic CIF structures are provided in the SI). The predicted IR spectrum of Zr12−bi-defective shows two additional intense peaks at 2661.1 and 2685.6 cm−1 for the stretching of the OH bonds involved in hydrogen bonds from the capping OH2 to the capping OH group, such bonds being absent in the pristine precursors (Figure 3 and SI Table S3). Following the thermodynamic cycle proposed by Walsh and co-workers,77 defect formation energies (Edef) were computed for Zr12−mono-defective and Zr12−bi-defective (see SI Figure S4). Per-defect Edef values for mono- and bi-defective Zr12 frameworks are 112.8 and 114.3 kcal/mol, respectively. The corresponding values computed for UiO-66 are 21.2 and 20.4 kcal/mol. We note that Vandichel et al.78 predicted a higher value of 57.4 kcal/mol for the equivalent defect formation in UiO-66, albeit using a thermodynamic cycle that did not include physisorbed water at the nonhydroxyl capped Zr sites. Irrespective of the precise model employed to quantify the energy of defect formation, it is clear that in Zr12−Pristine it is more energetically costly than in UiO-66. We nevertheless imagine that traditional methods such as using HCl or larger monotopic carboxylic acids as modulators and/or postsynthetic treatment with acid should permit the introduction of defects into the Zr12 framework (which will also have defects at crystallite surfaces, of course). Single-Site Heterogeneous Catalytic Hydrolysis of Sarin CWA on Zr12−Bi-defective Double-Node MOF. Coordinatively unsaturated ZrIV−MOFs with Lewis acidic open metal sites have been shown to be highly effective heterogeneous catalysts for the detoxification of organophosphorus-based chemical warfare agents (CWAs).28−49 Such CWAs are highly volatile chemicals that irreversibly bind to the active site of the acetylcholinesterase enzyme which is responsible for inactivating the neurotransmitter acetylcholine.79,80 Hydrolytic mechanisms for both sarin and its simulant dimethyl methyl-phosphonate have been characterized by both theory46−49 and experiment.32 The following mechanistic scheme is general for this catalytic reaction in the presence of water (Scheme 1): First, sarin binds via the phosphonate

Figure 4. M06-L/pob-TZVP optimized crystal structures of (a) pristine Zr12−I (18 linkers), (b) Zr12−mono-defective (17 linkers), and (c) Zr12−bi-defective (16 linkers) MOFs. Generated empty pores after TPDC linker removals are highlighted. In a−c, gray, white, red, and green represent C, H, O, and Zr atoms, respectively.

The most-stable proton topology found in Zr12−I isomer is assumed in all of our calculations involving both mono- and bidefective Zr12. We note two separate theoretical studies performed on defective75 and pristine76 UiO-66 MOF. Through a series of ab initio static and molecular dynamics (AIMD) simulations, Ling and Slater showed that defective UiO-66 exhibits strong dynamic behavior involving proton transfers between the terminal hydroxyl group that caps/ charge-balances open ZrIV metal sites and physiosorbed water molecules at adjacent sites.75 In another very recent AIMD study performed on this same MOF by Van Speybroeck and co-workers, it was shown that at elevated temperatures even pristine UiO-66, having no defects and in the absence of any protic solvent molecules, exhibits dynamic behavior involving decoordination and recoordination of its organic linkers with the metal−oxide node keeping its original morphology.76 We may expect similar behavior to occur in these new double-node Zr12 MOFs, although a molecular dynamics study is outside the scope of this work. Removing first one and then a symmetrically related two linkers creates rhomboid pores with apex to apex distances of ∼15 and ∼28 Å (Figure 4). To explore the sensitivity of the Zr12−I to the location of the removed linkers, we chose to study two other bi-defective isomers in which TPDC linkers were removed from two nearby Zr sites (Zr12−bi-defective−gem) and from top and bottom sides of the Zr12 double-node framework (Zr12−bidefective−μ2) (see SI Figure S3 and Table S2 for their

Scheme 1. Mechanistic Scheme for Hydrolysis of Sarin on Uncapped Faces of ZrIV−MOFs

oxygen to an open ZrIV metal site. This activates the nerve agent with respect to nucleophilic attack at phosphorus by an external water molecule, the nucleophilicity of which is enhanced by concomitant proton transfer to an adjacent hydroxyl capping group. Remediation is complete upon subsequent P−F bond heterolysis (likely facilitated by solvent water acting as a general acid stabilizing the departing fluoride anion). 4435


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Chemistry of Materials Using cluster models extracted from the periodic Zr12−bidefective structure (see Computational Details sections for details), the energetics of the reaction coordinate for the hydrolysis of sarin were computed at the M06-2X//M06-L levels, including the effects of aqueous solvation with the continuum SMD solvation model. Results for Zr12−bidefective are compared in Figure 5 to corresponding data for MOF-808, NU-1000, and trans bi-defective UiO-66 having 10 linkers (UiO-66-10).49

activation free energy than is predicted for water displacement for this MOF. The computed overall activation free energies for MOF-808, NU-1000 (c pore), NU-1000 (large pore), UiO-66-10, and Zr12−bi-defective MOFs are respectively, 16.2, 18.1, 19.2, 17.9, and 15.3 kcal/mol (Figure 5). Optimized H2O displacement and nucleophilic addition TS structures are shown in Figure 6 for Zr12−bi-defective (analogues for the other MOFs may be found in the SI).

Figure 6. Key bond lengths (Å, M06-L/Def2-SVP) in Zr12−bidefective benzoate-capped cluster-model TS structures for water displacement (left) and nucleophilic addition (right). For the formate-capped analogues see SI Figure S6. Gray, white, red, blue, purple, and green represent C, H, O, F, P, and Zr atoms, respectively.

Taking both the displacement and the addition steps into account, the computed reactivity trend for the different MOFs is Zr12−bi-defective > MOF-808 > UiO-66-10 > NU-1000 (c pore) > NU-1000 (large pore), suggesting that testing of experimentally defective Zr12 should be undertaken. While absolute DFT free energies of activation for any given reaction are generally not accurate to within only 1 kcal/mol, cancellation of errors typically makes much higher the reliability of trends in activation free energies in closely related systems, increasing our confidence in our prediction. Modeling Sarin Hydrolysis with Different Cluster vs Periodic Models. Turning to the modeling issue of using benzoate-capped vs formate-capped cluster models to study this reaction coordinate, comparison of the data in Figures 5 and S1 indicates that the more realistic benzoate ligands interact significantly with the reacting species along the reaction coordinate, with variations in activation free energies for any given step differing from 0.0 to 5.4 kcal/mol. In principle, the larger benzoate group can stabilize some species with favorable van der Waals interactions (such as in NU-1000 (c pore)), or destabilize them when interatomic distances become too short and lead to steric repulsion (such as in UiO66-10 and MOF-808). This emphasizes the importance of a suitable model-cluster when studying reactions taking place at MOF faces that effectively reside in “pockets”.28 To further investigate the effects on computed reactivity of different linker-analogue carboxylates in cluster models, we compared results for both formate- and benzoate-capped cluster models of MOF-808 and UiO-66-10 to corresponding full periodic models, keeping the exchange-correlation functional (M06-L) and basis set (pob-TZVP) identical (see SI Table S4 for results). While formate-capped cluster models are not particularly reliable, reaction profiles for benzoate-capped cluster models are in good agreement with periodic results. This comparison validates the likely utility of benzoate-capped models in Zr-based MOFs with larger unit cells, especially when one considers that the disposition of sarin when reacting at a MOF face in the Zr12-bi-defective MOF leaves it quite far

Figure 5. M06-2X/Def2-TZVP//M06-L/Def2-SVP 298 K free energies and enthalpies for hydrolysis of sarin along different cluster-model benzoate-capped reaction coordinates relative to separated reactants. Subsequent loss of HF and recycling of the catalyst is predicted to be exergonic (and nonturnover limiting).48 The corresponding data using formate as a model linker ligand are provided in SI Figure S5.

Considering the chirality of sarin and the topologically different faces of the MOFs, many local minima were located for each stationary point. In addition, the metal−oxide node of NU-1000 has two different faces orienting into different voids (named here as the large pore and the c pore), and we compare to both here. Cartesian coordinates for all lowestenergy species are provided in SI Sections S3−S5. For all of the systems compared in Figure 5, the organic linkers in the cluster models were truncated to benzoate. However, given the very large size of the Zr12−bi-defective model (282 atoms), we also examined the hydrolysis reaction coordinate using formate as a model linker (122 atoms in cluster; see SI Figure S5). As shown in Figure 5, hydrolysis starts with H2O displacement by the nerve agent sarin, and this step is computed to be turnoverlimiting for all of the studied Zr−MOFs except MOF-808. These data offer possible insights into experimental observations that catalytic activity increases with decreasing pH,29 which is contrary to what is observed for homogeneous aqueous hydrolysis of nerve agents in the presence of strong Brønsted acids or bases. We note that at lower pH values more OH groups will be converted to OH2, which based on our mechanistic scheme will translate to an increase in the effective concentration of displaceable sites. This also agrees with the experimental observation that, for NU-1000, prior dehydration of the metal−oxide node accelerates the hydrolysis reaction in aqueous solution,28 which is consistent with our prediction that the step following sarin coordination has a lower 4436


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for providing resources that contributed to the research results reported within this paper. M.R.M. is grateful for helpful discussions with Manuel Ortuño, Omar Farha, and Timur Islamoglu.

from any atom of the terphenyl central ring: the nearest distance between an atom of sarin and the central linker ring for any optimized structure along the sarin reaction coordinate docked into the periodic Zr12-bi-defective structure is 5.486 Å, suggesting that recourse to larger biphenylcarboxylate model linkers is unnecessary. Although it is perilous to attempt to interpret energy differences on the order of 1 kcal/mol, we speculate that the trends in reactivity predicted for the various MOFs may be associated with the degree of accessibility to the defect faces. The large pores present in Zr12-bi-defective offer such access, and this may also explain the higher hydrogenative reduction reactivities observed experimentally for CoII−H@Zr12−Pristine compared to other Zr6 MOFs.27 However, this is not the only consideration, as NU-1000 has a very large pore as well, but water displacement is not facile, suggesting that other electronic structure effects, or geometric effects associated with specific orientations of the benzoate rings (which are fixed to crystal structure geometries in cluster optimizations) play some role as well. Work to identify general descriptors that rationalize (or correlate with) observed trends in reactivity for different MOFs continues in our laboratories.

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(1) Ferey, G. Hybrid Porous Solids: Past, Present, Future. Chem. Soc. Rev. 2008, 37, 191−214. (2) Furukawa, H.; Cordova, K. E.; O'Keeffe, O.; Yaghi, O. M. The Chemistry and Applications of Metal-Organic Frameworks. Science 2013, 341, 1230444. (3) Corma, A.; García, H.; Llabrés i Xamena, i. Engineering Metal Organic Frameworks for Heterogeneous Catalysis. Chem. Rev. 2010, 110, 4606−4655. (4) Ma, L.; Abney, C.; Lin, W. Enantioselective Catalysis with Homochiral Metal−Organic Frameworks. Chem. Soc. Rev. 2009, 38, 1248−1256. (5) Yoon, M.; Srirambalaji, R.; Kim, K. Homochiral Metal−Organic Frameworks for Asymmetric Heterogeneous Catalysis. Chem. Chem. Rev. 2012, 112, 1196−1231. (6) Odoh, S.; Cramer, C. J.; Truhlar, D.; Gagliardi, L. QuantumChemical Characterization of the Properties and Reactivities of Metal−Organic Frameworks. Chem. Chem. Rev. 2015, 115, 6051− 6111. (7) Lee, J.; Farha, O. K.; Roberts, J.; Scheidt, K. A.; Nguyen, S. T.; Hupp, J. T. Metal-Organic Framework Materials as Catalysts. Chem. Soc. Rev. 2009, 38, 1450−1459. (8) Valvekens, P.; Vermoortele, F.; De Vos, D. Metal−Organic Frameworks as Catalysts: The Role of Metal Active Sites. Catal. Sci. Technol. 2013, 3, 1435−1445. (9) Cui, Y.; Li, B.; He, H.; Zhou, W.; Chen, B.; Qian, G. Metal− Organic Frameworks as Platforms for Functional Materials. Acc. Chem. Res. 2016, 49, 483−493. (10) Farha, O. K.; Hupp, J. T. Rational Design, Synthesis, Purification, and Activation of Metal−Organic Framework Materials. Acc. Chem. Res. 2010, 43, 1166−1175. (11) Rogge, S. M. J.; Bavykina, A.; Hajek, J.; Garcia, H.; OlivosSuarez, A. I.; Sepulveda-Escribano, A.; Vimont, A.; Clet, G.; Bazin, P.; Kapteijn, F.; Daturi, M.; Ramos-Fernandez, E. V.; Llabres i Xamena, F. X.; Van Speybroeck, V.; Gascon, J. Metal-Organic and Covalent Organic Frameworks as Single-Site Catalysts. Chem. Soc. Rev. 2017, 46, 3134−3184. (12) Zhu, L.; Liu, X.-Q.; Jiang, H.-L.; Sun, L.-B. Metal-Organic Frameworks for Heterogeneous Basic Catalysis. Chem. Rev. 2017, 117, 8129−8176. (13) Cavka, J. H.; Jakobsen, S.; Olsbye, U.; Guillou, N.; Lamberti, C.; Bordiga, S.; Lillerud, C. P. A New Zirconium Inorganic Building Brick Forming Metal Organic Frameworks with Exceptional Stability. J. Am. Chem. Soc. 2008, 130, 13850−13851. (14) Bennett, T. D.; Cheetham, A. K.; Fuchs, A. H.; Coudert, F. X. Interplay Between Defects, Disorder and Flexibility in Metal-Organic Frameworks. Nat. Chem. 2017, 9, 11−16. (15) Mondloch, J. E.; Bury, W.; Fairen-Jimenez, D.; Kwon, S.; DeMarco, E. J.; Weston, M. H.; Sarjeant, A. A.; Nguyen, S. T.; Stair, P. C.; Snurr, R. Q.; Farha, O. K.; Hupp, J. T. Vapor-Phase Metalation by Atomic Layer Deposition in a Metal−Organic Framework. J. Am. Chem. Soc. 2013, 135, 10294−10297. (16) Planas, N.; Mondloch, J. E.; Tussupbayev, S.; Borycz, J.; Gagliardi, L.; Hupp, J. T.; Farha, O. K.; Cramer, C. J. Defining the Proton Topology of the Zr6-Based Metal−Organic Framework NU1000. J. Phys. Chem. Lett. 2014, 5, 3716−3723. (17) Schoenecker, P. M.; Belancik, G. A.; Grabicka, B. E.; Walton, K. S. Kinetics Study and Crystallization Process Design for Scale-Up of UiO-66-NH2 Synthesis. AIChE J. 2013, 59, 1255−1262. (18) Biswas, S.; Van Der Voort, P. A General Strategy for the Synthesis of Functionalised UiO-66 Frameworks: Characterisation, Stability and CO2 Adsorption Properties. Eur. J. Inorg. Chem. 2013, 2013, 2154−2160.

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CONCLUSION In summary, we have assigned the proton topology of Zr12− Pristine from both periodic and extended cluster density functional calculations and predicted structures of mono- and bi-defective versions of this double-node MOF. Intriguingly, we predict the reactivity of the Zr12−bi-defective system for the hydrolysis of sarin nerve agent to be greater than for all other Zr6 MOFs tested for this reaction to date, suggesting that experimental testing of this prediction is warranted. Finally, from a technical standpoint, we have illustrated the importance, when using cluster models, of using a sufficiently large (realistic) cluster to adequately capture key interactions that may be taking place relatively far from the reacting centers.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.chemmater.8b01913. Details of the computations (PDF) All optimized CIF structures (ZIP) Coordinates (XYZ)

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REFERENCES

AUTHOR INFORMATION

Corresponding Author

*(M.R.M.) E-mail: [email protected]. ORCID

Mohammad R. Momeni: 0000-0002-7731-5823 Christopher J. Cramer: 0000-0001-5048-1859 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported as part of the Nanoporous Materials Genome Center, funded by the U.S. DOE, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences (Award DE-FG02-17ER16362). The authors acknowledge the Minnesota Supercomputing Institute (MSI) 4437


Article

Chemistry of Materials (19) DeCoste, J. B.; Peterson, G. W.; Jasuja, H.; Glover, T. G.; Huang, Y.-G.; Walton, K. S. Stability and Degradation Mechanisms of Metal−Organic Frameworks Containing the Zr6O4(OH)4 Secondary Building Unit. J. Mater. Chem. A 2013, 1, 5642−5650. (20) Kandiah, M.; Nilsen, M. H.; Usseglio, S.; Jakobsen, S.; Olsbye, U.; Tilset, M.; Larabi, C.; Quadrelli, E. A.; Bonino, F.; Lillerud, K. P. Synthesis and Stability of Tagged UiO-66 Zr-MOFs. Chem. Mater. 2010, 22, 6632−6640. (21) Wu, H.; Yildirim, T.; Zhou, W. Exceptional Mechanical Stability of Highly Porous Zirconium Metal−Organic Framework UiO-66 and Its Important Implications. J. Phys. Chem. Lett. 2013, 4, 925−930. (22) Schaate, A.; Roy, P.; Godt, A.; Lippke, J.; Waltz, F.; Wiebcke, M.; Behrens, P. Modulated Synthesis of Zr-Based Metal−Organic Frameworks: From Nano to Single Crystals. Chem. - Eur. J. 2011, 17, 6643−6651. (23) Guillerm, V.; Ragon, F.; Dan-Hardi, M.; Devic, T.; Vishnuvarthan, M.; Campo, B.; Vimont, A.; Clet, G.; Yang, Q.; Maurin, G.; Férey, G.; Vittadini, A.; Gross, S.; Serre, C. A Series of Isoreticular, Highly Stable, Porous Zirconium Oxide Based Metal− Organic Frameworks. Angew. Chem., Int. Ed. 2012, 51, 9267−9271. (24) Huang, Y.; Qin, W.; Li, Z.; Li, Y. Enhanced Stability and CO2 Affinity of a UiO-66 Type Metal−Organic Framework Decorated with Dimethyl Groups. Dalton Trans. 2012, 41, 9283−9285. (25) Wu, H.; Yildirim, T.; Zhou, W. Exceptional Mechanical Stability of Highly Porous Zirconium Metal-Organic Frameworks UiO-66 and Its Important Implications. J. Phys. Chem. Lett. 2013, 4, 925−930. (26) Rogge, S. M. J.; Waroquier, M.; Van Speybroeck, V. Reliably Modeling the Mechanical Stability of Rigid and Flexible MetalOrganic Frameworks. Acc. Chem. Res. 2018, 51, 138−148. (27) Ji, P.; Manna, K.; Lin, Z.; Feng, X.; Urban, A.; Song, Y.; Lin, W. Single-Site Cobalt Catalysts at New Zr12(μ3-O)8(μ3-OH)8(μ2-OH)6 Metal−Organic Framework Nodes for Highly Active Hydrogenation of Nitroarenes, Nitriles, and Isocyanides. J. Am. Chem. Soc. 2017, 139, 7004−7011. (28) Mondloch, J. E.; Katz, M. J.; Isley, W. C., III; Ghosh, P.; Liao, P.; Bury, W.; Wagner, G. W.; Hall, M. G.; DeCoste, J. B.; Peterson, G. W.; Snurr, R. Q.; Cramer, C. J.; Hupp, J. T.; Farha, O. K. Destruction of Chemical Warfare Agents Using Metal−Organic Frameworks. Nat. Mater. 2015, 14, 512−516. (29) Katz, M. J.; Klet, R. C.; Moon, S.-Y.; Mondloch, J. E.; Hupp, J. T.; Farha, O. K. One Step Backward Is Two Steps Forward: Enhancing the Hydrolysis Rate of UiO-66 by Decreasing [OH−]. ACS Catal. 2015, 5, 4637−4642. (30) Moon, S.-Y.; Liu, Y.; Hupp, J. T.; Farha, O. K. Instantaneous Hydrolysis of Nerve-Agent Simulants with a Six-Connected Zirconium-Based Metal−Organic Framework. Angew. Chem., Int. Ed. 2015, 54, 6795−6799. (31) Mondal, S. S.; Holdt, H.-J. Breaking Down Chemical Weapons by Metal−Organic Frameworks. Angew. Chem., Int. Ed. 2016, 55, 42− 44. (32) Plonka, A. M.; Wang, Q.; Gordon, W. O.; Balboa, A.; Troya, D.; Guo, W.; Sharp, C. H.; Senanayake, S. D.; Morris, J. R.; Hill, C. L.; Frenkel, A. I. Situ Probes of Capture and Decomposition of Chemical Warfare Agent Simulants by Zr-Based Metal Organic Frameworks. J. Am. Chem. Soc. 2017, 139, 599−602. (33) Islamoglu, T.; Atilgan, A.; Moon, S.-Y.; Peterson, G. W.; DeCoste, J. B.; Hall, M.; Hupp, J. T.; Farha, O. K. Cerium(IV) vs Zirconium(IV) Based Metal−Organic Frameworks for Detoxification of a Nerve Agent. Chem. Mater. 2017, 29, 2672−2675. (34) Peterson, G. W.; Moon, S.-Y.; Wagner, G. W.; Hall, M. G.; DeCoste, J. B.; Hupp, J. T.; Farha, O. K. Tailoring the Pore Size and Functionality of UiO-Type Metal−Organic Frameworks for Optimal Nerve Agent Destruction. Inorg. Chem. 2015, 54, 9684−9686. (35) Bobbitt, N. S.; Mendonca, M. L.; Howarth, A. J.; Islamoglu, T.; Hupp, J. T.; Farha, O. K.; Snurr, R. Q. Metal−Organic Frameworks for the Removal of Toxic Industrial Chemicals and Chemical Warfare Agents. Chem. Soc. Rev. 2017, 46, 3357−3385.

(36) DeCoste, J. B.; Peterson, G. W. Metal−Organic Frameworks for Air Purification of Toxic Chemicals. Chem. Rev. 2014, 114, 5695− 5727. (37) Katz, M. J.; Mondloch, J. E.; Totten, R. K.; Park, J. K.; Nguyen, S. T.; Farha, O. K.; Hupp, J. T. Simple and Compelling Biomimetic Metal−Organic Framework Catalyst for the Degradation of Nerve Agent Simulants. Angew. Chem., Int. Ed. 2014, 53, 497−501. (38) Katz, M. J.; Moon, S.-Y.; Mondloch, J. E.; Beyzavi, M. H.; Stephenson, C. J.; Hupp, J. T.; Farha, O. K. Exploiting Parameter Space in MOFs: A 20-Fold Enhancement of Phosphate-Ester Hydrolysis with UiO-66-NH2. Chem. Sci. 2015, 6, 2286−2291. (39) Liu, Y.; Moon, S.-Y.; Hupp, J. T.; Farha, O. K. Dual-Function Metal−Organic Framework as a Versatile Catalyst for Detoxifying Chemical Warfare Agent Simulants. ACS Nano 2015, 9, 12358− 12364. (40) Moon, S. Y.; Wagner, G. W.; Mondloch, J. E.; Peterson, G. W.; DeCoste, J. B.; Hupp, J. T.; Farha, O. K. Effective, Facile, and Selective Hydrolysis of the Chemical Warfare Agent VX Using Zr6Based Metal−Organic Frameworks. Inorg. Chem. 2015, 54, 10829− 10833. (41) López-Maya, E.; Montoro, C.; Rodríguez-Albelo, L. M.; Aznar Cervantes, S. D.; Lozano-Pérez, A. A.; Cenís, J. L.; Barea, E.; Navarro, J. A. R. Textile/Metal−Organic-Framework Composites as SelfDetoxifying Filters for Chemical-Warfare Agents. Angew. Chem., Int. Ed. 2015, 54, 6790−6794. (42) de Koning, M. C.; Van Grol, M.; Breijaert, T. Degradation of Paraoxon and the Chemical Warfare Agents VX, Tabun, and Soman by the Metal−Organic Frameworks UiO-66-NH2, MOF-808, NU1000, and PCN-777. Inorg. Chem. 2017, 56, 11804−11809. (43) Liu, Y.; Howarth, A. J.; Vermeulen, N. A.; Moon, S.-Y.; Hupp, J. T.; Farha, O. K. Catalytic Degradation of Chemical Warfare Agents and Their Simulants By Metal-Organic Frameworks. Coord. Chem. Rev. 2017, 346, 101−111. (44) Li, P.; Klet, R. C.; Moon, S.-Y.; Wang, T. C.; Deria, P.; Peters, A. W.; Klahr, B. M.; Park, H.-J.; Al-Juaid, S. S.; Hupp, J. T.; Farha, O. K. Synthesis of Nanocrystals of Zr-Based Metal−Organic Frameworks with csq-Net: Significant Enhancement in the Degradation of a Nerve Agent Simulant. Chem. Commun. 2015, 51, 10925−10928. (45) Gil-San-Millan, R.; López-Maya, E.; Hall, M.; Padial, N. M.; Peterson, G. W.; DeCoste, J. B.; Rodríguez-Albelo, L. M.; Oltra, J. E.; Barea, E.; Navarro, J. A. R. Chemical Warfare Agents Detoxification Properties of Zirconium Metal−Organic Frameworks by Synergistic Incorporation of Nucleophilic and Basic Sites. ACS Appl. Mater. Interfaces 2017, 9, 23967−23973. (46) Islamoglu, T.; Ortuño, M. A.; Proussaloglou, E.; Howarth, A. J.; Vermeulen, N. A.; Atilgan, A.; Cramer, C. J.; Farha, O. K.; Asiri, A. M. Presence versus Proximity: The Role of Pendant Amines in the Catalytic Hydrolysis of a Nerve Agent Simulant. Angew. Chem. 2018, 130, 1967−1971. (47) Troya, D. Reaction Mechanism of Nerve-Agent Decomposition with Zr-Based Metal Organic Frameworks. J. Phys. Chem. C 2016, 120, 29312−29323. (48) Wang, G.; Sharp, C.; Plonka, A. M.; Wang, Q.; Frenkel, A. I.; Guo, W.; Hill, C.; Smith, C.; Kollar, J.; Troya, D.; Morris, J. R. Mechanism and Kinetics for Reaction of the Chemical Warfare Agent Simulant, DMMP(g), with Zirconium(IV) MOFs: An UltrahighVacuum and DFT Study. J. Phys. Chem. C 2017, 121, 11261−11272. (49) Momeni, M. R.; Cramer, C. J. Dual Role of Water in Heterogeneous Catalytic Hydrolysis of Sarin by Zirconium-Based Metal−Organic Frameworks. ACS Appl. Mater. Interfaces 2018, 10, 18435−18439. (50) Waitschat, S.; Reinsch, H.; Stock, N. Water-Based Synthesis and Characterization of a New Zr-MOF With a Unique Inorganic Building Unit. Chem. Commun. 2016, 52, 12698−12701. (51) Cliffe, M. J.; Castillo-Martínez, E.; Wu, Y.; Lee, J.; Forse, A. C.; Firth, F. C. N.; Moghadam, P. Z.; Fairen-Jimenez, D.; Gaultois, M. W.; Hill, J. A.; Magdysyuk, O. V.; Slater, B.; Goodwin, A. L.; Grey, C. P. Metal−Organic Nanosheets Formed via Defect-Mediated Trans4438


Article

Chemistry of Materials formation of a Hafnium Metal−Organic Framework. J. Am. Chem. Soc. 2017, 139, 5397−5404. (52) Zhao, Y.; Truhlar, D. G. A New Local Density Functional for Main-Group Thermochemistry, Transition Metal Bonding, Thermochemical Kinetics, and Noncovalent Interactions. J. Chem. Phys. 2006, 125, 194101. (53) Dovesi, R.; Saunders, V. R.; Roetti, C.; Orlando, R.; ZicovichWilson, C. M.; Pascale, F.; Civalleri, B.; Doll, K.; Harrison, N. M.; Bush, I. J.; D’Arco, P.; Llunell, M.; Causà, M.; Noël, Y.CRYSTAL14 User’s Manual; University of Torino: Torino, 2014. (54) Dovesi, R.; Saunders, V. R.; Roetti, C.; Orlando, R.; ZicovichWilson, C. M.; Pascale, F.; Civalleri, B.; Doll, K.; Harrison, N. M.; Bush, I. J.; D’Arco, P.; Llunell, M.; Causà, M.; Noël, Y.; Maschio, L.; Erba, A.; Rerat, M.; Casassa, S. CRYSTAL17 User’s Manual; University of Torino: Torino, 2017. (55) Peintinger, M. F.; Oliveira, D. V.; Bredow, T. Consistent Gaussian Basis Sets of Triple-Zeta Valence with Polarization Quality for Solid-State Calculations. J. Comput. Chem. 2013, 34, 451−459. (56) Andrae, D.; Haüßermann, U.; Dolg, U.; Stoll, H.; Preuß, H. Energy-Adjusted Ab Initio Pseudopotentials for the Second and Third Row Transition Elements. Theor. Chim. Acta 1990, 77, 123−141. (57) Monkhorst, H. J.; Pack, J. D. Special Points for Brillouin-Zone Integrations. Phys. Rev. B 1976, 13, 5188−5192. (58) Perdew, J.; Burke, K.; Ernzerhof, M. Generalized Gradient Approximation Made Simple [Phys. Rev. Lett. 77, 3865 (1996)]. Phys. Rev. Lett. 1997, 78, 1396. (59) Grimme, S.; Antony, J.; Ehrlich, S.; Krieg, H. J. Chem. Phys. 2010, 132, 154104. (60) Hutter, J.; Iannuzzi, M.; Schiffmann, F.; VandeVondele, J. cp2k: atomistic simulations of condensed matter systems, Wiley Interdiscip. Rev. Comput. Mol. Sci. 2014, 4, 15−25. (61) Goedecker, S.; Teter, M.; Hutter, J. Phys. Rev. B: Condens. Matter Mater. Phys. 1996, 54, 1703−1710. (62) Henkelman, G.; Uberuaga, B. P.; Jónsson, H. J. Chem. Phys. 2000, 113, 9901−9904. (63) Weigend, F. Accurate Coulomb-Fitting Basis Sets for H to Rn. Phys. Chem. Chem. Phys. 2006, 8, 1057−1065. (64) Weigend, F.; Ahlrichs, R. Balanced Basis Sets of Split Valence, Triple Zeta Valence and Quadruple Zeta Valence Quality for H to Rn: Design and Assessment of Accuracy. Phys. Chem. Chem. Phys. 2005, 7, 3297−3305. (65) https://bse.pnl.gov/bse/portal. (66) Cramer, C. J. Essentials of Computational Chemistry: Theories and Models, 2nd ed.; John Wiley & Sons: Chichester, 2004. (67) Zhao, Y.; Truhlar, D. G. The M06 Suite of Density Functionals for Main Group Thermochemistry, Thermochemical Kinetics, Noncovalent Interactions, Excited States, and Transition Elements: Two New Functionals and Systematic Testing of Four M06-Class Functionals and 12 Other Functionals. Theor. Chem. Acc. 2008, 120, 215−241. (68) Zhao, Y.; Truhlar, D. G. Density Functionals with Broad Applicability in Chemistry. Acc. Chem. Res. 2008, 41, 157−167. (69) Marenich, A. V.; Cramer, C. J.; Truhlar, D. G. Universal Solvation Model Based on Solute Electron Density and on a Continuum Model of the Solvent Defined by the Bulk Dielectric Constant and Atomic Surface Tensions. J. Phys. Chem. B 2009, 113, 6378−6396. (70) Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A.; Nakatsuji, H.; Caricato, M.; Li, X.; Hratchian, H. P.; Izmaylov, A. F.; Bloino, J.; Zheng, G.; Sonnenberg, J. L.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Montgomery, J. A., Jr.; Peralta, J. E.; Ogliaro, F.; Bearpark, M.; Heyd, J. J.; Brothers, E.; Kudin, K. N.; Staroverov, V. N.; Keith, T.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Rega, N.; Millam, J. M.; Klene, M.; Knox, J. E.; Cross, J. B.; Bakken, V.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R. E.; Yazyev, O.; Austin, A. J.; Cammi,

R.; Pomelli, C.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Zakrzewski, V. G.; Voth, G. A.; Salvador, P.; Dannenberg, J. J.; Dapprich, S.; Daniels, A. D.; Farkas, O.; Foresman, J. B.; Ortiz, J. V.; Cioslowski, J.; Fox, D. J. Gaussian09; Gaussian, Inc.: Wallingford, CT, 2013. (71) Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Petersson, G. A.; Nakatsuji, H.; Li, X.; Caricato, M.; Marenich, A. V.; Bloino, J.; Janesko, B. G.; Gomperts, R.; Mennucci, B.; Hratchian, H. P.; Ortiz, J. V.; Izmaylov, A. F.; Sonnenberg, J. L.; Williams-Young, D.; Ding, F.; Lipparini, F.; Egidi, F.; Goings, J.; Peng, B.; Petrone, A.; Henderson, T.; Ranasinghe, D.; Zakrzewski, V. G.; Gao, J.; Rega, N.; Zheng, G.; Liang, W.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Throssell, K.; Montgomery, J. A., Jr.; Peralta, J. E.; Ogliaro, F.; Bearpark, M. J.; Heyd, J. J.; Brothers, E. N.; Kudin, K. N.; Staroverov, V. N.; Keith, T. A.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A. P.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Millam, J. M.; Klene, M.; Adamo, C.; Cammi, R.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Farkas, O.; Foresman, J. B.; Fox, D. J. Gaussian16; Gaussian, Inc.: Wallingford, CT, 2016. (72) Campaná, C.; Mussard, B.; Woo, T. K. Electrostatic Potential Derived Atomic Charges for Periodic Systems Using a Modified Error Functional. J. Chem. Theory Comput. 2009, 5, 2866−2878. (73) Alecu, I. M.; Zheng, J.; Zhao, Y.; Truhlar, D. G. Computational Thermochemistry: Scale Factor Databases and Scale Factors for Vibrational Frequencies Obtained from Electronic Model Chemistries. J. Chem. Theory Comput. 2010, 6, 2872−2887. (74) Yang, Y.; Momeni, M. R.; Demir, H.; Pahls, D. R.; Rimoldi, M.; Wang, T. C.; Farha, O. K.; Hupp, J. T.; Cramer, C. J.; Gates, B. C.; Gagliardi, L. Tuning the Properties of Metal-Organic Framework Nodes as Supports of Single-Site Iridium Catalysts: Node Modification by Atomic Layer Deposition of Aluminium. Faraday Discuss. 2017, 201, 195−206. (75) Ling, S.; Slater, B. Dynamic Acidity in Defective UiO-66. Chem. Sci. 2016, 7, 4706−4712. (76) Hajek, J.; Caratelli, C.; Demuynck, R.; De Wispelaere, K.; Vanduyfhuys, L.; Waroquier, M.; Van Speybroeck, V. On the Intrinsic Dynamic Nature of the Rigid UiO-66 Metal−Organic Framework. Chem. Sci. 2018, 9, 2723−2732. (77) Bristow, J. K.; Svane, K. L.; Tiana, D.; Skelton, J. M.; Gale, J. D.; Walsh, A. Free Energy of Ligand Removal in the Metal−Organic Framework UiO-66. J. Phys. Chem. C 2016, 120, 9276−9281. (78) Vandichel, M.; Hajek, J.; Vermoortele, F.; Waroquier, M.; De Vos, D. E.; Van Speybroeck, V. Active site engineering in UiO-66 type metal−organic frameworks by intentional creation of defects: a theoretical rationalization. CrystEngComm 2015, 17, 395−406. (79) Watson, A.; Opresko, D.; Young, R.; Hauschild, V.; King, J.; Bakshi, K. Organophosphate Nerve Agents. In Handbook of Toxicology of Chemical Warfare Agents; Gupta, R. C., Ed.; Academic Press: San Diego, 2009; Chapter 6, pp 43−67. (80) Chambers, J. E.; Oppenheimer, S. F. Organophosphates, Serine Esterase Inhibition, and Modeling of Organophosphate Toxicity. Toxicol. Sci. 2004, 77, 185−187.

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