Optimizing Open Iron Sites in Metal–Organic Frameworks for Ethane

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Optimizing Open Iron Sites in Metal−Organic Frameworks for Ethane Oxidation: A First-Principles Study Peilin Liao,†,‡ Rachel B. Getman,§ and Randall Q. Snurr*,† †

Department of Chemical & Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States School of Materials Engineering, Purdue University, West Lafayette, Indiana 47907, United States § Department of Chemical and Biomolecular Engineering, Clemson University, Clemson, South Carolina 29634, United States ‡

S Supporting Information *

ABSTRACT: Activation of the C−H bonds in ethane to form ethanol is a highly desirable, yet challenging, reaction. Metal− organic frameworks (MOFs) with open Fe sites are promising candidates for catalyzing this reaction. One advantage of MOFs is their modular construction from inorganic nodes and organic linkers, allowing for flexible design and detailed control of properties. In this work, we studied a series of single-metal atom Fe model systems with ligands that are commonly used as MOF linkers and tried to understand how one can design an optimal Fe catalyst. We found linear relationships between the binding enthalpy of oxygen to the Fe sites and common descriptors for catalytic reactions, such as the Fe 3d energy levels in different reaction intermediates. We further analyzed the three highest-barrier steps in the ethane oxidation cycle (including desorption of the product) with the Fe 3d energy levels. Volcano relationships are revealed with peaks toward higher Fe 3d energy and stronger electron-donating group functionalization of linkers. Furthermore, we found that the Fe 3d energy levels positively correlate with the electron-donating strength of functional groups on the linkers. Finally, we validated our hypotheses on larger models of MOF-74 iron sites. Compared with MOF-74, functionalizing the MOF-74 linkers with NH2 groups lowers the enthalpic barrier for the most endothermic step in the reaction cycle. Our findings provide insight for catalyst optimization and point out directions for future experimental efforts. KEYWORDS: metal−organic frameworks, DFT, catalyst screening, ethane, ethanol, nitrous oxide complex,12−14 which can convert methane to methyl bisulfate (CH3OSO3H) with good yield. The methyl bisulfate can then be reacted with water to form methanol. Challenges for this chemistry include the need to recover the SO2 byproduct and corrosion. Inspired by enzymes containing iron or copper in the active sites,15,16 another direction of active research is to introduce active sites containing transition metal elements to zeolites, such as Fe-ZSM-5,17,18 Cu-ZSM-5,19,20 and Co-ZSM5,21,22 as well as to investigate various iron-oxo structures23,24 and tricopper clusters.25,26 Some remaining challenges for these

1. INTRODUCTION Methane is the major component in natural gas (>84 vol %).1 It is highly desirable to develop efficient chemical processes that convert methane to industrially useful products, by functionalizing methane or forming longer chain organic molecules.2−7 However, activating the C−H bond in methane is very difficult because the C−H bond has a high bond dissociation energy of 431 kJ/mol.8 Compared to methane, the C−H bond in ethane is weaker (410 kJ/mol),8 and ethane is the second most abundant component (>2 vol %) found in natural gas.1 Thus, many researchers have focused on the slightly less difficult problem of C−H activation in ethane as a stepping stone toward eventual activation of methane. One way to activate the C−H bond in methane or ethane is through oxidation.9−11 One promising class of catalysts with high turnover frequencies for this reaction is the Pt bidiazine © XXXX American Chemical Society

Special Issue: Hupp 60th Birthday Forum Received: February 14, 2017 Accepted: March 31, 2017

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DOI: 10.1021/acsami.7b02195 ACS Appl. Mater. Interfaces XXXX, XXX, XXX−XXX

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Figure 1. (a) Ligand structures with complete and abbreviated names. Dashed lines in structures mark where atoms coordinate to Fe. Functional groups are indexed by numbers, where no prime symbol, a subsequent prime symbol, and a subsequent double prime symbol indicate para, meta, and ortho substitutions, respectively. Only single substitution on the linker is tested; therefore, when no ligand is specified for Rn (n = 1, 2, 3), Rn is the H atom. (b) Top view (looking from the missing ligand position toward the Fe site) for sample five-coordinated pyramidal A structures (see Figure 3) with labels underneath. Without and with a prime symbol after the ligand names correspond to anion ligands opposite to each other within the pyramidal plane (“PP” arrangement) and one of the anion ligands located at the pyramidal top (“PT” arrangement), respectively. Gray dashed circles indicate functional group substitutions. Color scheme: H, white; C, gray; N, blue; O, red; and Fe, purple. Figure S3 shows additional sample structures.

catalysts are difficulty in extracting methanol and the need to reactivate the catalysts, for example, with steam. Recently, Xiao et al.27 reported using two MOFs, Fe2(dobdc) (also known as Fe-MOF-74, dobdc4− = 2,5-dioxido-1,4benzenedicarboxylate) and Fe0.1Mg1.9(dobdc), with open Fe sites to catalyze the conversion of ethane to ethanol with N2O as the oxygen source (C2H6 + N2O → C2H5OH + N2). There are several advantages to using MOFs for catalysis. First, they provide a solid framework for supporting well dispersed catalytic Fe sites. Second, the combination of inorganic nodes and organic linkers enables the modular design of catalysts. Last but not least, specifically for the open Fe sites, Xiao et al. proposed that the MOF-74 framework structure stabilizes the high spin state of Fe, which is the spin state found in Fe enzyme catalysts for methane activation.28,29 Verma et al.30 published a follow-up computational study, where they applied Kohn− Sham density functional theory (KS-DFT) to study reactive intermediates and analyze the full reaction pathway. On the basis of these previous findings, it is promising to look further into open Fe sites in MOFs. Vogiatzis et al.31 searched through a database of MOFs32 to find those with coordinatively unsaturated Fe sites. In their stepwise screening procedure, many of the resulting 46 structures were manually discarded based on criteria such as likely instability. For the remaining 7 structures, DFT calculations were performed to assess the formation energy and stability of the high-spin iron(IV)-oxo intermediate, which is known to play a key role in the reaction mechanism. On the basis of their predictions, one of the materials was synthesized and tested experimentally. In this work, we adopted another, more “bottom-up” approach in which we created structures on the computer using common linkers that could be used to build MOFs and analyzed how the

different linkers affect the reaction energetics as a means to gain physical insights for improving the catalysts.

2. COMPUTATIONAL DETAILS The Gaussian 09 Rev. D.01 program33 was used to perform DFT calculations. Multireference methods may be necessary to provide accurate predictions for Fe with an unfilled 3d shell, ranging from 4 to 6 3d electrons for Fe(IV) to Fe(II). Prior work by Verma et al.30 indicates that KS-DFT with the M06-L exchange-correlation functional34 gives reasonable agreement with the correlated wave function method (multistate complete active space second-order perturbation theory (MS-CASPT2)) for Fe-containing MOFs. So we adopted the computational scheme used by Verma et al. for our DFT calculations, which also enables a direct comparison with their results. We used the M06-L exchange-correlation functional34 and the def2-TZVP35 allelectron basis sets with density fitting for all atoms. An ultrafine grid was employed to evaluate integrals. Previously, Verma et al.30 predicted an overall quintet S = 2 spin state as most stable in the Fe-MOF-74 cluster. We also found the S = 2 spin states to be the most stable for a few representative clusters (see Table S1) and set S = 2 for all structures reported in this forum article. We adopted N2O as the oxidant as in the previous experimental and computational work of Xiao et al.27 and Verma et al.30 Verma et al.30 used two structural models: one with 88 atoms and the other with 26 atoms. The larger 88-atom model, obtained by cutting a segment from MOF-74 with an 8 Å radius around the central Fe ion, contains three metal ions, while the smaller 26-atom model comprises one Fe and the first coordination sphere around it, i.e., methanol, formate, and 3-hydroxyprop-2-enoic acid. The baseline model that we use in this work comprises one Fe cation coordinated with five ligands, which consist of methanol and formate ions. We validated our findings using this model by comparing reaction energetics with those calculated using the same 88-atom model as Verma et al. (see section 3.5). B

DOI: 10.1021/acsami.7b02195 ACS Appl. Mater. Interfaces XXXX, XXX, XXX−XXX

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ACS Applied Materials & Interfaces To explore the effect of different organic linkers, we constructed a series of Fe catalyst structures by coordinating different common MOF linkers32 to the Fe site. The construction started with building what we call “A” structures (see Figures 1 and 3), which are the initial states in the catalytic cycles. The Fe cation in the A structure is in the +2 oxidation state. Therefore, to ensure charge neutrality, building the five-coordinated A structure requires two −1 charged ligands and three neutral ligands. Inspired by the 26-atom model employed by Verma et al.,30 our two simplest structures, labeled Fm and Fm′ (see Figure 1), used methanol as the neutral ligand and formate anion as the ligand with −1 charge. We tested two possible arrangements for the two formate groups: one arrangement with the two groups directly opposite to each other within the plane of the pyramid (“PP” arrangement, see Figure 2) and the other with one of the anion ligands

similar trends when we tested the effects of allowing Fe and its NN atoms to relax (see section 1 and Figure S2 in the Supporting Information). In section 3.5, we calculated the reaction pathway for the functionalized 88-atom MOF-74 model in ref 30. In that case, as in ref 30, the reactive species, the Fe atom, and its NN O atoms were allowed to relax while keeping all other atoms fixed.

3. RESULTS AND DISCUSSION 3.1. Reaction Pathway of Ethane Oxidation. The reaction pathway studied in this work is shown in Figure 3.

Figure 2. Schematic illustration for the PP (“pyramid plane”) and PT (“pyramid top”) arrangements of ligands around an Fe center. located at the top of the pyramid (“PT” arrangement). To differentiate the different arrangements, we append a prime “ ′ ” after the names with the “PT” arrangement (see, for example, Figure 1, where Fm′ denotes the Fm structure with a PT arrangement for the formate groups). Then, we replaced either two of the methanol groups or the two formate groups in Fm and Fm′ with different common linkers. We built the Py series by replacing methanol with pyridine, and the BA and Im series by replacing formate with benzoate or imidazolate anions, respectively (see Figure 1 and Figure S3). We also introduced functional groups with various electron donating/withdrawing strengths to these linkers, to examine the effect of electron donating/withdrawing groups on the electronic structure of Fe and, hence, the reaction energetics. The functional groups tested are listed next to the illustration of linkers in Figure 1. The electron donating groups activate the ortho and para positions of aromatic rings, while the electron withdrawing groups activate the meta position. Accordingly, we placed electron donating groups at the para position and also tested a couple of structures at the ortho positions on the BA linker. One exception is for the COOH group. Even though it is slightly electron withdrawing, it is placed at the para position since it acts as a linking group in many MOFs. The other electron withdrawing group tested is −CN, which is placed at the meta position. For the Im group, we only tested one substituted location for functional groups. The index of the functional groups is ordered such that smaller index numbers label stronger electron donating groups. In MOFs, the linkers are somewhat constrained by the crystal structure. To mimic this in a simple way, we fixed the Fe-nearest neighbor (NN) bond lengths to be 2.06 Å, which is the average Fe−O bond length of the 26-atom MOF-74 model as determined by Verma et al.30 Each Fe-NN bond is set to be perpendicular to all other Fe-NN bonds. This is one simple approximate model. We tested the effects of Fe-NN bond length relaxation. We found that while individual Fe-NN bond distances vary, the average bond distance has a maximal difference of 3%. The relative spin stability is unchanged for the case of Im3 tested. Details can be found in the Supporting Information. After this initial construction of A structures, geometry relaxations were carried out on all atoms except Fe and its NN atoms. In all other structures in the reaction cycle, the optimized A structure is held fixed, allowing only the reactive molecular species on top of the open Fe sites to relax. This optimization scheme was used to provide fast screening and allow comparison across different ligands. We obtained

Figure 3. Catalytic reaction cycle for ethane oxidation with N2O on an open Fe site. The bottom dashed arrow indicates where steps that were included by Verma et al.30 were neglected in this work. Oxygen atoms are shown as nearest neighbor atoms to Fe, although for the Py/ Py′ and Im/Im′ series of structures, some of these O atoms would be changed to N atoms. Structure labels are inside boxes next to each structure.

N2O adsorbs on the Fe site, oxidizes Fe to iron oxo, and desorbs as N2, whereas ethane is oxidized by iron oxo to form ethanol. Figure 4 presents sample enthalpy changes along the reaction pathway (full energetics for all catalysts can be found in Table S2). Initial adsorption of N2O is exothermic (from “A” to “B” in Figure 3). After that, the Fe(II) cation is oxidized to form the iron(IV) oxo (FeO) (from “B” to “C”, via TS1). Desorption of N2 with adsorption of ethane causes very little change in enthalpy (from “C” to “D”, via “A_O” which corresponds to the isolated cluster without adsorption of N2 or ethane). The iron oxo then oxidizes ethane to ethanol (from “D” to “E”, via TS2). The last step is ethanol desorption to regenerate the “A” structure. Compared to the pathway reported by Verma et al.,30 the pathway in Figure 3 skips several steps between “D” and “E” that correspond to the formation of Fe−OH and a ·C2H5 radical, rotation of the OH, and rebound of ·C2H5 to form ethanol. According to Verma et al.,30 the enthalpies of activation and reaction for each of these steps are BA2 and BA3″ > BA3) when we moved the functional group from para to ortho positions (see Figure 8c). Overall, this provides additional support for our conclusion and suggests that we can derive design principles from simple models and extend them to more realistic systems.48



ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsami.7b02195. Discussion of the effects of geometry optimization, energies of different spin states, reaction enthalpies, and additional structures (PDF) G

DOI: 10.1021/acsami.7b02195 ACS Appl. Mater. Interfaces XXXX, XXX, XXX−XXX

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Randall Q. Snurr: 0000-0003-2925-9246 Notes

The authors declare the following competing financial interest(s): R.Q.S. has a financial interest in the start-up company NuMat Technologies, which is seeking to commercialize metal-organic frameworks.



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. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, and the Quest high performance computing facility at Northwestern University.



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