Computational Screening of Bimetal-Functionalized Zr6O8 MOF

Department of Chemistry, Michigan Technical University, Michigan 49331, United States. Inorg. Chem. , 2017, 56 (15), pp 8739–8743. DOI: 10.1021/acs...
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Computational Screening of Bimetal-Functionalized Zr6O8 MOF Nodes for Methane C−H Bond Activation Dale R. Pahls,†,§ Manuel A. Ortuño,†,§ Peter H. Winegar,†,‡ Christopher J. Cramer,*,† and Laura Gagliardi*,† †

Department of Chemistry, Chemical Theory Center, and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455, United States ‡ Department of Chemistry, Michigan Technical University, Michigan 49331, United States S Supporting Information *

ABSTRACT: Zr-based metal−organic frameworks (MOFs) are promising supports for copper-based catalysts able to activate methane. Homo- and heterobimetalfunctionalized NU-1000 MOF nodes were selected to computationally screen the effect of ancillary metals for C−H bond activation, allowing us to correlate activation free energies with chemical descriptors.

F

ossil fuels are depleting, but reserves of light hydrocarbons such as methane are abundant in natural gas reservoirs.1,2 Despite vast literature on homo-3 and heterogeneous catalysts,4 zeolites,5 and enzymes,6 the efficient and selective functionalization of such inert C−H bonds is still a challenge. Here, we focus on metal−organic frameworks (MOFs),7 a versatile family of mesoporous materials, as platforms to address this challenge. Concerning light hydrocarbons, only a few examples of MOF-mediated C−H bond functionalization are available. Yaghi and co-workers reported the oxidation of methane to acetic acid using the V-based MIL-47 and MOF-48 as catalysts.8 More recently, Long and co-workers converted ethane to ethanol via Fe−oxo moieties in the magnesiumdiluted Fe0.1Mg1.9(dobdc) MOF-74.9,10 Zr-based MOFs appear as promising catalyst supports due to their excellent thermal and chemical stability.11 In particular, we focus on the MOF NU-1000, comprised of [Zr6(μ3-O)4(μ3-OH)4(OH)4(OH2)4]8+ nodes and tetratopic 1,3,6,8-tetrakis(p-benzoate)pyrene linkers (Figure 1a).12,13 The presence of terminal hydroxo and aquo ligands at the node (Figure 1b) allows postsynthetic functionalization14 with a wide variety of metals, such as Fe,15 Co,16 Ni,17 Cu,18 and Zn,19 among others,20 including heterobimetallic Co−Al systems.21 Metal-functionalized NU1000 nodes have been shown to be active catalysts for hydrogenation,17 oxidation,16,21 and epoxidation22 reactions. Indeed, Cu-functionalized NU-1000 nodes exhibit methane to methanol conversion and stand out as proof-of-concept MOF materials for this kind of reactivity.23 We note that other Zr6O8 MOFs, such as defect sites in the UiO series,24 PCN-700, and MOF-808, present the same supporting functionality as that found in NU-1000 and such sites have also been employed for the deposition of potentially catalytic metals,20,25 so results presented here are likely to be relevant to those systems as well. In the present contribution, we employ computational models to explore further the potential activity of metal© 2017 American Chemical Society

Figure 1. NU-1000 MOF (a), NU-1000 node (b), and bimetallic systems used in this study (c).

functionalized NU-1000 nodes toward C−H bond activation. Inspired by recent studies on Cu-NU-1000 catalysts for methane to methanol reactivity,23 we designed a series of Cubased NU-1000 nodes as shown in Figure 1c, bearing Cu and a second metal, namely Fe(II), Co(II), Ni(II), Cu(II), and Zn(II).26 This approach allows us to screen metals to determine which would be an optimal dopant for methane activation.27 Since common deposition techniques use water as a coreactant,12 hydroxo ligands complete the coordination in the precatalytic systems. One of our goals is through systematic study of the effect of the ancillary metal to obtain predictive chemical descriptors of possibly more general utility.28 All calculations were performed at the density functional theory (DFT) level using the M06-L density functional (see SI for details). From the periodic structure of NU-1000, we extract a neutral cluster model,13,29 where the pyrene-based linkers are simplified to benzoate and kept fixed to mimic the rigidity of the framework (see SI for details). All Cu-M species were found to have high-spin ground states. We report free energies in kcal mol−1 in the gas phase at 298 K and 1 atm. Received: May 25, 2017 Published: July 25, 2017 8739

DOI: 10.1021/acs.inorgchem.7b01334 Inorg. Chem. 2017, 56, 8739−8743

Communication

Inorganic Chemistry

have endergonic reaction free energies, as expected given the formation of a product methyl radical. Radical rebound (not studied here) has been shown to drive the reaction downhill for other Cu-oxo systems.31 Comparing 2-Cu to other copper-based systems that activate the C−H bond in methane, 2-Cu has an activation free energy (ΔG‡ = 25.2 kcal mol−1) comparable to those of [Cu2O]2+ catalysts deposited onto ZSM-5 (reported barrier of 21 kcal mol−1).32 Such barriers are somewhat higher than those associated with ligated terminal Cu-oxo and dicopper-oxo complexes31a,d (ΔG‡ ∼ 16−18 kcal mol−1), as well as zeolitesupported [Cu3O3]2+ systems (13−15 kcal mol−1).5a With computed activation free energies for all bimetallic species in hand, we next correlate these values with chemical descriptors. The activity of metal-oxo clusters for methane activation is known to be sensitive to the development of hole character on the coordinated oxyl ligand;33 so the spin density at one or more oxygen atoms might serve as a predictive descriptor. Figure 3 plots the activation free energies against the

A formal C−H bond abstraction reaction coordinate at a bimetallic NU-1000 node is shown in Figure 2. As the original

Figure 2. Methane C−H bond abstraction via bimetallic species for isomers 1-M (a) and 3-M (b). M = Fe, Co, Ni, Cu, Zn.

μ3O and μ3OH positions (Figure 1c) on which the metals are supported are inequivalent even after deprotonation of the μ3OH group, two isomers must be considered for all heterobimetallic species: one where Cu(II) is bound to the μ3O position (1-M, Figure 2a) and one where Cu(II) is bound to the former μ3OH position (now μ3O−, 3-M, Figure 2b). To promote C−H bond activation, the initial Cu(II)-M(II) species 1-M and 3-M must be activated by oxidation to form a Cu(II)− oxyl moiety. Our model complexes were oxidized by removal of a hydrogen atom from the bridging OH group, leading to 2-M and 4-M, which were more thermodynamically stable than analogous oxidation of the nonbridging OH groups. Subsequent transition states TS2-M and TS4-M produce the corresponding methyl radicals and regenerate 1-M and 3-M. Activation (ΔG‡) and reaction (ΔGr) free energies (298 K) associated with the processes shown in Figure 2 are collected in Table 1. Comparing site isomers, Fe, Co, and Ni species are Table 1. Free Energies in kcal mol−1 (2-M + CH4 as Zero)

a

M

ΔG‡ (TS2−2)

ΔGr (1−2)

Fe Co Ni Cua Zn

47.2 42.4 32.7 25.2 19.6

36.4 32.2 20.8 13.0 5.5

ΔG‡ (TS4−4)

ΔGr (3−4)

4.2 4.9 6.2

44.6 35.0 27.8

37.4 24.8 14.3

−3.2

23.9

9.7

4

Figure 3. Plots of ΔG‡ vs ρ(O) (a) and Σρ(O) (b) for 2-M. Regression lines in red.

spin density of the reacting oxyl atom (ρ(O), Figure 3a) and the sum of spin densities of all six oxygen atoms bound to Cu and M (Σρ(O), Figure 3b) for isomer 2-M. ρ(O) correlates to ΔG‡ for all metals, with larger spin densities (i.e., more oxyl character) associated with lower activation free energies (R2 = 0.929). Σρ(O) only exhibits a linear correlation if the redoxinnocent metal Zn is considered as an outlier (R2 = 0.992). For isomer 4-M, however, while the linear correlation with Σρ(O) is still found to hold, no similar trend is observed for ρ(O) (Figure S1). Thus, ρ(O) and Σρ(O) are not general descriptors for these particular systems. CM5 partial atomic charges were examined, but no clear correlations to ΔG‡ were found. We turned next to an analysis of the different transition state structures. By the Hammond postulate,34 a more reactive oxyl should have a transition-state (TS) structure that more closely resembles reactants, that is, a shorter C−H bond and a longer O−H bond. We indeed found good linear correlations between C−H bond lengths and ΔG‡ for TS2-M and TS4-M (R2 = 0.837 and 0.983, Figure 4), with shorter C−H bonds associated with lower activation free energies. Similar correlations were

There is only a single structure for the homobimetallic.

more active with isomer 4, while the more active Zn derivative is isomer 2. We assume no interconversion between 2 and 4, so activation energies via TS2 and TS4 are reported relative to their corresponding isomers 2 and 4, respectively. The relative activation free energies for both isomers behave similarly: the Lewis acidic metal Zn gives the lowest activation free energy, whereas the values for transition-metal Cu, Ni, Co, and Fe derivatives increase with decreasing atomic number. The moderate activation free energy for the homobimetallic Cu system, 25.2 kcal mol−1, is in line with previously reported reactivity.23 We also highlight the still lower activation free energies of 19.6 and 23.9 kcal mol−1 for the two Cu−Zn isomers, consistent with the Cu−ZnO synergy already shown for Cu/ZnO/Al2O3 catalysts.30 All of the bimetallic systems 8740

DOI: 10.1021/acs.inorgchem.7b01334 Inorg. Chem. 2017, 56, 8739−8743

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Inorganic Chemistry

b) environments. For Ca derivatives, the computed ΔGr(1−2) and ΔGr(3−4) are 7.3 and 9.8 kcal mol−1. According to the regression equation from Figure 5, the predicted relative activation free energies would be 21.4 and 23.4 kcal mol−1. The actual computed activation energies via TS2-Ca and TS4-Ca were found to be 20.7 and 24.1 kcal mol−1, in good agreement with the predicted values. Similarly, for isomer a of the Al analogues, the computed ΔGr(1−2) and ΔGr(3−4) of 8.6 and 16.9 kcal mol−1 predict ΔG‡ of 22.4 and 29.3 kcal mol−1, respectively, which are again in line with the computed values of 23.2 and 29.8 kcal mol−1. Similar results were found for isomer b, where the ΔGr(1−2) and ΔGr(3−4) of 8.5 and 16.9 kcal mol−1 predict ΔG‡ of 22.4 and 29.3 kcal mol−1, respectively, in agreement with the computed values of 22.1 and 29.7 kcal mol−1. A plot of ΔG‡ vs ΔGr for all species can be found in the SI. Illustrating the broad applicability of the BEP principle, this correlation continues to hold when other systems are added as well, e.g., the Cu complexes31 and Cu-exchanged zeolites38 mentioned above (Table S1). To conclude, we have computationally evaluated methane C−H bond activation using bimetal-functionalized NU-1000 nodes. While spin density is a qualitatively informative descriptor, transition state C···H (and O···H) bond lengths and predicted reaction free energies show high correlations with computed activation free energies. Our calculations suggest that materials combining Cu and Lewis-acidic metals might enhance C−H bond activation processes. Such computational modeling can guide efforts toward the postsynthetic functionalization of MOF nodes for catalyst design.

Figure 4. Plots of ΔG‡ vs d(C···H) for TS2-M (a) and TS4-M (b). Regression lines in red.

determined for O−H bond lengths, with now longer bonds being associated with lower activation free energies for TS2-M and TS4-M (R2 = 0.876 and 0.999, respectively, Figure S2). In contrast to the spin densities discussed above, these correlations involving distances work well for all metals in both isomers. Of course, if one’s goal is to avoid having to compute TS structures, these correlations are of limited utility. The observed bond distance trends do suggest, however, that moving from the qualitative Hammond postulate to the predictive Bell−Evans−Polanyi (BEP) principle35 might generate a descriptor. By this principle, there should be a direct relationship between the thermodynamics and kinetics of reactions of the same family. Indeed, plots of ΔG‡ vs ΔGr show excellent linear correlations for 2-M (R2 = 0.995) and 4-M (R2 = 0.995) with less endoergic reactions having lower activation free energies. More importantly, the combined data sets still retain excellent linear correlation (R2 = 0.990, Figure 5), showing that ΔGr is a robust descriptor.



ASSOCIATED CONTENT

* Supporting Information S

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.inorgchem.7b01334. Cartesian coordinates for all optimized species (XYZ) Computational details, additional correlation plots, and energies for all optimized species (PDF)



AUTHOR INFORMATION

Corresponding Authors

* E-mail: [email protected], Twitter: @ChemProfCramer. *E-mail: [email protected]. ORCID

Manuel A. Ortuño: 0000-0002-6175-3941 Christopher J. Cramer: 0000-0001-5048-1859 Laura Gagliardi: 0000-0001-5227-1396 Author Contributions §

These authors contributed equally.

Notes

The authors declare no competing financial interest.



Figure 5. Plots of ΔG‡ vs ΔGr and for both 2-M and 4-M species. Regression line in red.

ACKNOWLEDGMENTS This work was supported as part of the Inorganometallic Catalyst Design Center, an Energy Frontier Research Center funded by the U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES), under Award DESC0012702. The authors acknowledge the Minnesota Supercomputing Institute (MSI) for providing resources that contributed to the research results reported within this paper.

We tested the predictive power of ΔGr as a descriptor with the Lewis acidic metals Ca(II)36 and Al(III).37 Due to the increased oxidation state of Al(III), we removed an additional proton from the metal-oxo cluster to maintain charge balance, which then creates two potential oxyl sites: oxyls bound to either Zr−OH2 (isomer a, as in Figure 2) or Zr−OH (isomer 8741

DOI: 10.1021/acs.inorgchem.7b01334 Inorg. Chem. 2017, 56, 8739−8743

Communication

Inorganic Chemistry



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DOI: 10.1021/acs.inorgchem.7b01334 Inorg. Chem. 2017, 56, 8739−8743

Communication

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DOI: 10.1021/acs.inorgchem.7b01334 Inorg. Chem. 2017, 56, 8739−8743