Bridging Zirconia Nodes within a MetalâOrganic Framework via

Article pubs.acs.org/JACS

Bridging Zirconia Nodes within a Metal−Organic Framework via Catalytic Ni-Hydroxo Clusters to Form Heterobimetallic Nanowires Ana E. Platero-Prats,† Aaron B. League,‡ Varinia Bernales,‡ Jingyun Ye,‡ Leighanne C. Gallington,† Aleksei Vjunov,§ Neil M. Schweitzer,∥ Zhanyong Li,⊥ Jian Zheng,§ B. Layla Mehdi,# Andrew J. Stevens,§ Alice Dohnalkova,△ Mahalingam Balasubramanian,† Omar K. Farha,⊥,□ Joseph T. Hupp,⊥ Nigel D. Browning,#,¶ John L. Fulton,§ Donald M. Camaioni,§ Johannes A. Lercher,§,▽ Donald G. Truhlar,‡ Laura Gagliardi,‡ Christopher J. Cramer,‡ and Karena W. Chapman*,† †

X-ray Science Division, Advanced Photon Source, Argonne National Laboratory, Argonne, Illinois 60439, United States Department of Chemistry, Minnesota Supercomputing Institute, and Chemical Theory Center, University of Minnesota, Minneapolis, Minnesota 55455, United States § Institute for Integrated Catalysis, #Physical and Computational Science Directorate, and △Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States ∥ Department of Chemical and Biological Engineering and ⊥Department of Chemistry, Northwestern University, Evanston, Illinois 60208, United States ¶ Materials Science and Engineering, University of Washington, Seattle, Washington 98195, United States □ Department of Chemistry, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia ▽ Department of Chemistry and Catalysis Research Institute, Technische Universität München, 85748 Garching, Germany ‡

S Supporting Information *

ABSTRACT: Metal−organic frameworks (MOFs), with their well-ordered pore networks and tunable surface chemistries, offer a versatile platform for preparing well-defined nanostructures wherein functionality such as catalysis can be incorporated. Notably, atomic layer deposition (ALD) in MOFs has recently emerged as a versatile approach to functionalize MOF surfaces with a wide variety of catalytic metal-oxo species. Understanding the structure of newly deposited species and how they are tethered within the MOF is critical to understanding how these components couple to govern the active material properties. By combining local and long-range structure probes, including X-ray absorption spectroscopy, pair distribution function analysis, and difference envelope density analysis, with electron microscopy imaging and computational modeling, we resolve the precise atomic structure of metal-oxo species deposited in the MOF NU1000 through ALD. These analyses demonstrate that deposition of NiOxHy clusters occurs selectively within the smallest pores of NU-1000, between the zirconia nodes, serving to connect these nodes along the c-direction to yield heterobimetallic metal-oxo nanowires. This bridging motif perturbs the NU-1000 framework structure, drawing the zirconia nodes closer together, and also underlies the sintering resistance of these clusters during the hydrogenation of light olefins.

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INTRODUCTION

explore the interplay between nanocatalyst and support in well-defined systems. NU-1000 is a large-pore zirconium-based MOF that shows promise as a catalyst support (Figure 1).2−5 In NU-1000, strong ZrIV−O bonds within Zr6(O)8 nodes impart high chemical and thermal stability,6 thus allowing the framework to tolerate more extreme catalytic reaction conditions, while

The activity of nanocatalysts depends not only on the characteristics of the catalytic particle (e.g., structure, size, and chemical state) but also on the nature of its interaction with and distribution within a support. Metal−organic frameworks (MOFs), with high internal surface area, have recently been explored as catalysts and nanocatalyst supports.1 The structural uniformity of MOFs, with regular pore geometry and surface functionalization, offers new opportunities to © 2017 American Chemical Society

Received: May 15, 2017 Published: July 11, 2017 10410

DOI: 10.1021/jacs.7b04997 J. Am. Chem. Soc. 2017, 139, 10410−10418

Article

Journal of the American Chemical Society

support interactions, this observation motivates a more detailed investigation of the catalytic oxo-Ni species in NU-1000. Here, we combine experimental probes of local and long-range atomic structure with computational modeling to develop a consistent structural model for the Ni-based catalyst deposited via ALD on NU-1000, referred to as Ni-AIM. Through difference envelope density (DED) analysis of powder diffraction data and electron microscopy imaging, the distribution of the deposited species and the lattice perturbation induced by the Ni-oxo clusters are explored. Combining Ni and Zr K-edge X-ray absorption spectroscopies (XAS) and differential pair distribution function (PDF) analysis with models derived from density functional calculations, a model for the atomic structure of the oxo-Ni catalyst was identified.

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Figure 1. Representations of the NU-1000 structure showing (a) the Zr6-based nodes, (b) the hexagonal and triangular channels viewed perpendicular to the c-axis, and (c) the 8 Å pores viewed parallel to the c-axis. Hydroxyl groups, available for reaction with ALD reagents, are shown in red.

METHODS

Synthesis. NU-1000 and Ni-AIM were prepared as described previously.2,5 Samples were prepared with 1, 2, and 3 ALD cycles, where each ALD cycle is composed of multiple pulses of the Ni precursor followed by multiple pulses of water vapor. This protocol was established to ensure the self-limiting ALD half-cycle goes to completion, fully saturating available reaction sites and favoring a uniform deposition. The Ni concentration in Ni-AIM, determined by inductively coupled plasma−atomic emission spectroscopy (ICPAES), was 4.1 ± 0.4, 8.3 ± 0.3, and 12.6 ± 0.5 Ni atoms per Zr6 node after 1, 2, and 3 ALD cycles, respectively. This corresponds to estimated formulas of Zr6O12Hx(TBAPy)2·[Ni(OH)y]n for n ≈ 4, 8, and 12; TBAPy = 1,3,6,8-tetrakis(p-benzoic acid)pyrene. Synchrotron X-ray Scattering (XRD and PDF). Powder X-ray diffraction (XRD) data and total scattering data suitable for PDF analysis were collected at beamlines 17-BM and 11-ID-B, respectively, at the Advanced Photon Source at Argonne National Laboratory using 17.0 keV (0.72768 Å) and 58.6 keV (0.2114 Å) X-rays, respectively. Data were collected using amorphous silicon-based area detectors. Geometric corrections and reduction to one-dimensional data used GSAS-II13 and FIT2D.14 To simulate activation conditions, powder samples were loaded into borosilicate capillaries and assembled into a flow cell that enables controlled temperature and atmosphere studies.15 Samples were heated from 50 to 200 °C at 2.5 °C min−1 under H2 (3.5% in He) and then held at 200 °C for 2 h. The activated samples were cooled to 50 °C under H2, and data was collected. Lattice parameters and peak intensities were quantified based on the diffraction data via Le Bail whole-pattern fitting16,17 based on the reported structural model for NU-1000 (csq topology, P6/mmm, a ≈ 40 Å, c ≈ 17 Å).2 Lattice and pseudo-Voigt profile parameters were refined over a 0.5−10° 2θ range. Structure envelopes were generated using the intensities of low-index Bragg reflections.18,19 DEDs were then obtained via subtraction of the structure envelope for pristine NU-1000 from the envelope for ALD-modified NU-1000.20 Additional DEDs considered the difference between the envelopes for fresh and activated Ni-AIM. PDFs were obtained from the data within PDFgetX221 to a Qmax = 22 Å−1. Differential PDFs were calculated and correlations of interest were quantified by fitting Gaussian functions within Fityk.22 PDFs for structural models were simulated in PDFgui.23 X-ray Absorption Spectroscopy (XANES and EXAFS). Transmission geometry XAS measurements were performed at 10-ID and 20-BM at the Advanced Photon Source at Argonne National Laboratory. Ni K-edge XAS spectra were acquired from 8100 to 9488 eV, resulting in a k-range up to 15.3 Å−1. Zr K-edge XAFS spectra were acquired from 17 750 to 18 700 eV, resulting in a k-range up to 13 Å−1. At MR-CAT (sector 10-ID),24 in situ XAS measurements were performed under flow conditions using a high-temperature cell described previously.25 The data analysis and background removal were performed within ATHENA and ARTEMIS.26 The Fourier transform of the k-space EXAFS data were fitted to theoretical models derived using the FEFF9 code.27

flexibility of the framework allows local distortions to be accommodated, including a distortion of the Zr6-based nodes following dehydration at elevated temperature.7 The chemistry of its pore surface, with the Zr6-based nodes decorated by −OHx groups [Zr6(μ3-O)4(μ3-OH)4(OH)4(OH2)4]8+],8 can be functionalized through reaction at the surface hydroxyl species by using atomic-layer deposition (ALD). In the two-step ALD process, an organometallic reagent first reacts at OHx groups on the pore surface in a self-limiting reaction. Subsequently, exposure to water vapor liberates the remaining organic species coordinated to the deposited metal while regenerating surface −OHx groups for subsequent ALD modification. Through AIM (ALD In MOFs), a wide variety of highly dispersed metal oxide species, with catalytic activity, have been deposited within NU1000, with the self-limiting nature of the ALD process favoring a more uniform deposition within the high aspect ratio pores.2,5,9−11 In NU-1000, ALD of transition metals such as Ni produces a highly dispersed catalyst that demonstrates appreciable turnover frequency for light alkene hydrogenation reactions with remarkable resistance to catalyst sintering.5 This activity is attained following activation at 200 °C in H2. Initial models proposed to understand and interpret the mechanism of catalysis by this material assumed uniform ALD of Ni species over available −OHx reaction sites; with a maximal of 4 Ni deposited per node and 8 −OHx available for reaction around each node, each Ni atom was proposed to be coordinated to pairs of −OHx species on separate node faces.5 However, we have recently discovered that the pore geometry of the NU-1000 support has a greater influence on the distribution of transition metal species deposited through AIM than does the initial distribution of the available −OHx reaction sites.12 Deposition occurs preferentially at sites within the NU-1000 pores where adsorption of the ALD reagent molecules is most favorable. For Zn-ALD in NU-1000, deposition occurs at only half of the original −OHx sites with selective ALD in the smallest pores of the NU-1000 framework and not in the intermediate triangular or large hexagonal channels.12 Given that the catalytic behavior of supported nanocatalysts can be strongly influenced by their atomic and electronic structure, their distribution on a support, and the catalyst− 10411


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Journal of the American Chemical Society Density Functional Calculations. The calculations were performed using the mix-node topology of NU-1000,8 with the M06-L density functional in Gaussian 09.28,29 An automatic densityfitting set generated by the Gaussian program was used to reduce the cost of calculations. Calculations were performed on a single Zr6 node with linkers truncated to benzoate groups. During geometry optimization, the carbon and hydrogen atoms of the truncated linkers were fixed to simulate the structural rigidity of the framework, while all other atoms were allowed to relax. The 6-31G(d) basis set30 was employed for H, C, and O atoms during geometry optimization, along with the SDD basis set and pseudopotential31 for Ni and Zr atoms. Zero-point energies and thermal contributions to enthalpies and Gibbs free energies were derived from vibrational frequency calculations performed at the same level of theory. The nature of all stationary points was verified by analytical computation of vibrational frequencies. Periodic DFT Calculations. The cell optimizations of NU-1000 and nNi4-NU-1000 were carried out using the CP2K code.32 The PBE functional33 with Grimme et al.’s D3 dispersion corrections34 was used to calculate the exchange−correlation energy. The DZVP-MOLOPT basis set was used with Geodecker et al.’s pseudopotentials35 with a plane wave cutoff energy of 360 Ry. The convergence criteria are the same as in the previous work.36 Scanning Transmission Electron Microscopy (STEM). The samples were infiltrated in LR White acrylic resin (Electron Microscopy Sciences, Hatfield, PA, USA) and polymerized at 60 °C for 24 h. The embedded material was sectioned to a 50 nm thickness on a Leica ultramicrotome (Ultracut E) using a Diatome diamond knife. The microtomed samples were placed on 200-mesh laceycarbon-coated Cu-grids (Ted Pella) and imaged with an aberrationcorrected FEI Titan 80-300S operating at 300 keV. The high angle annular dark field (HAADF) collection inner angle was ∼75 mrad, and the nominal probe size was ∼0.1 nm.

Figure 2. DEDs corresponding to the location of Ni species in Ni-AIM (green surface) and the regions that increase (blue mesh) and decrease (red mesh) in electron density during activation viewed perpendicular (top) and parallel (bottom) to the c-axis.

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RESULTS AND DISCUSSION The diffraction data for Ni-AIM are broadened relative to pristine NU-1000, indicating increased disorder in the framework following ALD (see the SI). DED analysis of the differences in relative peak intensities of the powder X-ray diffraction data provides a low-resolution map of the electron density deposited within the NU-1000 pores following ALD. This analysis is based on the intensity of the low-angle peaks in the powder diffraction data, which can be well quantified despite the broadening of the diffraction data. The DED analysis indicates that the NiOxHy species in Ni-AIM are not distributed around the node faces as initially proposed.5 Instead, the new electron density following ALD is localized in the small pores of the NU-1000 lattice (Figure 2). Reaction of ALD precursors in the small pores is favored by dispersion interactions.12 The electron density distribution remains largely unchanged during activation, although a slight expansion of the electron density toward the hexagonal channel is evident (Figure 2). Following multiple ALD cycles, the electron density also expands in the ab plane toward the hexagonal channel. The new electron density corresponding to the deposited NiOxHy species indicates that these exist predominately as clusters within the small pores bounded by pairs of Zr6O8 nodes. Compositional analysis suggests that these clusters contain an average of 4 Ni atoms following a single ALD cycle and that they grow by a further ∼4 Ni with each subsequent ALD cycle. Accordingly, a cluster-based model for the catalytic oxo-Ni species is proposed here to better understand and interpret the catalytic performance and sintering resistance of Ni-AIM. Inspection of Ni K-edge XANES data (Figure 3) indicates that the average Ni is approximately six-coordinated Ni(II) with

Figure 3. k2-weighted (a) χ(r) and (b) Im g[χ(r)] Ni-EXAFS spectra of Ni-AIM following 1, 2, and 3 ALD cycles and 1 ALD cycle activation. The normalized Ni-XANES data (inset) suggest an octahedral NiO6 geometry with the pre-edge feature (inset) indicating distortion of these octahedra.

an octahedral geometry.37 A pre-edge peak at ∼8333 eV, attributed to a 1s−3d electronic transition, suggests a slight distortion of these NiO6 octahedra.37 The increase in the preedge peak intensity following activation suggests increasing distortion of the NiO6 or increasing population of undercoordinated Ni. The Ni K-edge EXAFS data for Ni-AIM have features in between those for the bulk reference compounds α-Ni(OH)2 and NiO, with layered and three-dimensional structures, 10412


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be separated in the d-PDF. For the Zr K-edge EXAFS analysis, the distances and DWF for the initial Zr···Zr (3.517 Å) and Zr−O correlations (2.14 Å, 2.28 Å) were fixed to the values refined for pristine NU-1000. The relative proportion of the shorter Zr−O distance and a new Zr···Zr distance at ∼3.39 Å was refined; these increased nearly linearly with the number of ALD cycles. The d-PDFs were adjusted to eliminate the contribution from these changes to the Zr geometries; to simulate the changes in the Zr coordination, Gaussian functions were added to the differential at the original Zr···Zr distance and subtracted from the differential at the new, shorter Zr···Zr distance with the relative intensity of the added/subtracted functions based on the relative proportion of original and short correlations in the EXAFS. The distortion-corrected d-PDFs include only the new atom−atom correlations associated with the NiOxHy clusters (Figure 4b). A peak in the d-PDF at ∼2.03 Å is associated with Ni−O, and a peak at ∼3.03 Å is associated with Ni···Ni and O···O in edge-shared NiO6 octahedra. These closely match the correlations from the EXAFS analysis. A further peak at 3.26 Å can be attributed to Ni···M for polyhedra in a corner-shared arrangement. This may include contributions from cornershared Ni···Zr or Ni···Ni, although due to the stronger scattering power of Zr, the former is likely the dominant contribution. During activation, the most significant change in the d-PDF is an increased intensity (by 30%) of the peak at 3.03 Å corresponding to Ni···Ni in edge-shared octahedra, with a commensurate decrease in the intensity of the feature at 3.26 Å. The increased intensity of this Ni···Ni correlation, which is consistent with the EXAFS analysis, is compatible with the densification of the cluster during activation through conversion of any corner-shared Ni···Ni to the edge-shared configuration or an increasingly nonplanar (i.e., NiO-like) arrangement. With increasing number of ALD cycles, the number of Ni··· Ni correlations at 3.03 Å increases, suggesting an increase in the average cluster size. This is evident in both the EXAFS and dPDF data, although, the coordination numbers from the EXAFS analysis are offset to larger values. For both cases, the increase is larger than would be expected if the additional NiOx species were added in a planar fashion, thus suggesting that the clusters may adopt increasing NiO character (with a maximal Ni···Ni coordination number of 12 for bulk NiO, cf. 6 for a strictly layered structure). A series of Ni4OxHy cluster models (Figure 5) were investigated computationally and evaluated against the experimental data to identify atomic structure models for the catalytic species for 1-cycle Ni-AIM. An initial cubic cluster model (model A) built from previous work,5 where two Ni atoms were assumed to deposit on a node face, one each on the μ3-O and μ3-OH, and with additional layers directly depositing on top of these, was considered. However, the experimental data suggest that the Ni···Ni distances in Ni-AIM are longer than in this cubic model (∼2.84 Å, cf. 3.03 Å). Subsequent cluster models were bound to the node (via the −OH) through one Ni atom. These included cluster models having atomic arrangements related to NiO (model B) and α-Ni(OH)2 (model C), with nonplanar and planar NiO6 octahedra, respectively. The energies, enthalpies, and free energies calculated for model systems A, B, and C are shown in Table 1. The relative enthalpy values for the model systems show a trend where

respectively (see the SI). Fitting the EXAFS data for 1-cycle NiAIM yields an average first-shell Ni−O coordination number of 5.4(2) at a distance of 2.046(2) Å. While features beyond this first-shell distance have low amplitude and were not fit in an earlier EXAFS analysis,37 a second-shell Ni···Ni distance could be refined at 3.035(9) Å with a coordination number of 2.9(8) and a large Debye−Waller factor (DWF, a factor of ∼2 larger than for Ni−O). The large uncertainty in the coordination number and large DWF suggest several distinct Ni···Ni correlations exist. Following activation, the Ni−O and Ni···Ni distances contract to 2.033(2) and 2.997(10) Å, respectively, with the coordination numbers decreasing for Ni−O (by ∼10%) and increasing for Ni···Ni (by 25%), although the changes in coordination number are comparable to the uncertainty in the values. As EXAFS features for higher-order shells have lower amplitude and can overlap with multiplescattering features, there is greater uncertainty in the analysis at longer distances. For example, fits to the EXAFS data do not change substantially upon inclusion of Ni···Zr paths. To further probe the atomic structure of the NiOxHy clusters beyond the first coordination shell, we applied PDF analysis, which can provide longer-range local structural insights than EXAFS. Differential analysis of the PDF data highlights new and modified atom−atom distances following ALD; by subtracting the PDF for unmodified NU-1000, new atom− atom distances associated with the deposited NiOxHy species and changes to the NU-1000 local structure during ALD are isolated. The differential PDFs (d-PDFs) obtained by subtraction of the PDF for pristine NU-1000 from Ni-AIM include a negative feature at ∼3.5 Å (Figure 4a), below the

Figure 4. Differential PDFs (a) obtained by subtraction of the PDF for pristine NU-1000 showing a feature at ∼3.5 Å below the −4πρr baseline, indicating distortion of the Zr6-based nodes and (b) corrected for the node distortion quantified through fits to the Zr K-edge EXAFS.

−4πρr baseline. This is characteristic of distortion of the symmetric Zr6-based nodes in pristine NU-1000;7 during this distortion the number of original Zr···Zr correlations at 3.5 Å decreases (such that this feature is oversubtracted in the differential), while new Zr···Zr correlations are observed at shorter and longer distance. This indicates that the ALD process is associated with a degree of node distortion, with the degree of distortion increasing during catalyst activation. Changes to the Zr coordination geometry characteristic of this node distortion were also observed in the Zr K-edge EXAFS data. Fitting of the Zr EXAFS data (see SI) quantified the changes to the Zr−O and Zr−Zr bond length distributions, thus allowing the contribution from the Zr6 node distortion to 10413


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Figure 5. Proposed models of a Ni4 cluster attached to a MOF Zr6 node and a comparison of the corresponding simulated Ni K-edge EXAFS (left) and PDFs (right, Ni−Ni, Ni−O, and O−O correlations) to the experimental data (black). For both EXAFS and PDF, model C provides the best match to the experimental data [C: light gray, O: red, Ni: green, Zr: gray].

Table 1. Relative Energies Calculated at 298 K for Ni4OxHy Cluster Modelsa energy [kcal/mol] b

number of H2O ΔErel° ΔHrel° ΔGrel°

A

B

C

12 −212 −199 −107

15 −259 −232 −117

13 −238 −216 −123

a

Energies relative to bare NU-1000 node, free water molecules, and free Ni precursor. bMolecules needed to form the Ni cluster. Note that because the AIM process is performed under a flow of gas, it is ambiguous what phase to use for the standard states of the free nickel precursors and water molecules. For the free energies reported here we used a gas-phase standard state of 22.4 L mol−1 for all species.

Figure 6. (a) DFT-optimized Ni4OxHy cluster that best matches the experimental data. The distribution of related Ni4-based clusters within NU-1000 from periodic density functional calculations viewed (b) parallel and (c) perpendicular to the c-axis. (d) Bimetallic metal oxide chains formed along the c-direction due to bridging of the Zr6-based nodes by the Ni4-based clusters [C: light gray, O: red, Ni: green, Zr: gray].

increasing the number of Ni atoms or coordinating O atoms (indicated by the number of water molecules needed to form each cluster) results in increased stability. This result is in agreement with the expectation that the factor that should most limit cluster growth is the greater entropy that water molecules enjoy when free in solution, rather than trapped in a cluster, a factor not accounted for by the enthalpy values. Therefore, on the basis of these energies alone, none of the cluster models can confidently be identified as being more stable than the others; correspondence to the experimental structural data is the best measure of which model is closest to reality. The optimized model C locally resembles a unit containing four Ni atoms within an α-Ni(OH)2-like layer (Figure 5, Figure 6a), and it provides the best correspondence to the experimental Ni K-edge EXAFS data and differential PDF data.38 This model offers a better match to the observed peak positions and intensities. Because these models do not reflect

distortion of the nodes, the correspondence of the Ni··· Zr(node) correlations at ∼3.3 Å was not considered. The best cluster model (C), with an approximately planar array of four edge-sharing NiO6 octahedra, has an average Ni− O coordination number of 5.75, with the node-bound Ni being five-coordinate with the others being six-coordinate. The average edge-sharing Ni···Ni distance is 3.018 Å. The multiple Ni environments, with some two-coordinate Ni···Ni and some three-coordinate Ni···Ni, are likely reflected in the large estimated standard deviations (esd) in the refined EXAFS parameters. The span of this cluster (O···O) is ∼7.5−8 Å. This is close to, but slightly less than, the O···O separation between Zr6-based nodes on opposite sides of the small pore of NU10414


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change in c-lattice parameter, and blurs the line between supported nanocatalyst and nanocatalyst support. The orientation of the Ni4-based clusters in the periodic density functional calculations (Figure 6), with the edges of the Ni4 planar cluster oriented toward the large hexagonal channels, matches the shape of the electron density seen in the DED, which is elongated toward these channels. The plane of the Ni4based clusters is tilted relative to the c-crystallographic axis and also relative to the line between the Zr6-based nodes. Disordered arrangement of the cluster tilt, which may also be coupled to tilting or displacement of the connected nodes, in combination with a disordered orientation of the node distortions,7 likely contributes to the increased disorder and peak broadening seen for NU-1000 following ALD. The lattice changes and reduced crystallinity following AIM are evident in both the diffraction data and high-angle annular dark field (i.e., Z-contrast) STEM imaging (Figure 7). The

1000 (∼8.5 Å), such that bridging of the nodes through the NiOxHy clusters may be possible. The observed contraction of the NU-1000 lattice along the c dimension following ALD (by ∼0.5 Å), with commensurate expansion along the a dimension, suggests such a bridging motif, whereby a cluster may draw the bridged Zr6-based nodes closer together. Undercoordination of some Ni atoms and tension applied to the cluster along the caxis by the connected NU-1000 framework may contribute to the octahedral distortion suggested by the XANES pre-edge peak. For comparison with the experimental data, periodic density functional calculations for a bridging Ni4 hydroxo cluster (Ni4(OH)6(OH2)6) tethered in the small pore of NU-1000 were undertaken to assess the direction and magnitude of the NU-1000 lattice changes. The periodic DFT calculations were performed for one NU-1000 unit cell, which has three Zr nodes. This allowed us to screen three cases, 1Ni4-, 2Ni4-, and 3Ni4-NU-1000, to study the trend of the lattice constant variation of Ni-AIM. The lattice parameters for optimized pristine NU-1000 and with progressively increasing proportions of bridging Ni clusters are shown in Table 2. For pristine NUTable 2. Lattice Dimensions Obtained from Diffraction Analyses and Periodic DFT Calculations for NU-1000 and Ni-AIM. method

material

PXRD

NU-1000 cycle 1 cycle 2 cycle 3 NU-1000 1Ni4 2Ni4 3Ni4

DFT

na

Ni/Zr6b

a (Å)

c (Å)

0 1 2 3

0 4.1 8.3 12.6 0 4/3 8/3 4

39.543 40.159 39.86 41.61 39.897 40.056 40.538 40.842

16.655 16.184 16.039 17.42 16.635 16.510 16.101 15.859

a

n is the number of Ni4 clusters per unit cell. bNi/Zr6 is the average number of Ni atoms per Zr6-based node.

1000, the lattice parameters optimized by DFT are in good agreement with the experimental data, especially for the cparameter (a = 39.897 Å, c = 16.635 Å, cf. a = 39.543 Å, c = 16.655 Å). Table 2 shows that the calculated c parameter of NU-1000 decreases monotonically and the a parameter increases monotonically when the Ni4-based cluster loading increases from one to three per unit cell. This trend is in a good agreement with the experimentally observed change in lattice parameters (see Table 2), and this agreement is consistent with the Ni4-hydroxo moieties being the dominant bridging motif in the Ni-AIM sample. The bridging of Zr6 nodes by Ni4 clusters along the cdirection can be considered to form one-dimensional heterobimetallic metal-oxo chains within the framework (Figure 6d) with alternating Zr-oxo and Ni-oxo moieties. These are aligned along the c-axis linked via the ligands, which serve as a porous organic matrix. Just as the Zr6-based nodes within NU1000 behave as ultrasmall nanoparticles of ZrO2,7 the Zr6−Ni4 chains can be considered as heterobimetallic metal-oxo nanowires. The formal linkage of the Ni4 clusters to the nodes effectively changes the framework topology from csq for pristine NU-1000 to more closely approximate kag for NiAIM.39 The integration of the Ni4 clusters within the NU-1000 framework couples their structures, as evidenced by the large

Figure 7. STEM images acquired for (a) NU-1000 (black curve) and (b) Ni-AIM following 1 cycle (green curve) in the ab plane. The respective FFTs are in the inset. (c) Distribution of the node separation from the radial sum of the FFT and (d) the apparent size of the nodes (looking down the c-axis). The scale bar in the STEM images corresponds to 20 nm.

sensitivity of HAADF to high-Z elements shows how the position and distribution of the Zr6-based nodes are modified by the ALD treatment. Fast Fourier transform based image processing shows a ring for Ni-AIM at the same spatial frequency as the crystalline NU-1000 lattice, suggesting the framework disordered in Ni-AIM involves displacement of the nodes from the ideal lattice sites, which may be needed to accommodate bridging of the nodes by the tilted NiOxHy clusters. Down a single column, displacement of the Zr6-based nodes in different directions increases the apparent node size (a projection) from 10 Å in NU-1000 to 14 Å in Ni-AIM. The similarities between images from both samples suggest that the Ni-oxo clusters are deposited throughout the crystal rather than just in selected areas (e.g., the outer surface). The changes to the local Ni cluster structure during activation are coupled to complex changes in the NU-1000 10415


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by low-scattering H without perturbing the octahedral geometry),5 in light of the present model of Ni4-based clusters, this change in coordination number must be re-evaluated. Although of similar magnitude to the uncertainty in the values, the change in average Ni coordination number could be interpreted as a change from predominately NiO6 to mixed NiO6−NiO5, which may be expected due to loss of water coordinated to Ni. The change could be attributed in part to an increased distortion of the Ni octahedra due to local changes to the Zr6 node following water removal. Accordingly, we propose that during activation, the observed local changes to the Ni4-based clusters are driven by removal of water to form undercoordinated and/or more distorted Ni(II) sites. This is consistent with the decreased first-shell Ni−O coordination number, the decreased Ni−O to Ni···Ni peak ratio, and the contraction of the Ni−O and Ni···Ni distances. Deactivation of the catalyst upon exposure to atmospheric conditions can be mainly attributed to coordination of species (e.g., water) at the unsaturated Ni(II) sites.

lattice parameters (Figure 8). The different lattice evolutions for unmodified NU-1000 and Ni-AIM demonstrate the

Figure 8. Evolution in the a (red) and c (blue) lattice dimensions of pristine NU-1000 (open symbols) and Ni-AIM (closed symbols).

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cooperative interactions of the Ni clusters within the framework. During activation, the NU-1000 lattice parameters change anisotropically; qualitatively different behaviors are observed for unmodified and Ni-deposited NU-1000. For unmodified NU-1000, the lattice dimensions change monotonically. For Ni-AIM, more complex changes are observed. Initially, the lattice parameters mirror those of unmodified NU-1000 with contraction along the a-axis and expansion along the c-axis. These trends then reverse with expansion along the a-axis and contraction along the c-axis. Finally, both the a-axis and c-axis contract. Upon cooling to room temperature following activation, both axes expand, a negative thermal expansion behavior. The 6% increase in volume corresponds to a coefficient of thermal expansion of α = −325 × 10−6 K−1, which is in the “colossal” range for thermal expansion.40 Anomalous thermal expansion behavior has been documented in other Zr6-based MOFS albeit of much lower magnitude.41 The linearity of this behavior and the underlying atomic mechanism require further detailed investigation, but is beyond the scope of the present study. Considering the local structure changes during activation of Ni-AIM, the d-PDF peak at 3.01 Å, corresponding to edgesharing NiO6 octahedra, increases in intensity (Figure 4). This is not reversed upon conditions that lead to catalyst deactivation (i.e., exposure to air and moisture). The persistent increase in the contribution from edge-sharing Ni···Ni correlations in the PDF may be explained if not all Ni ions adopt an edge-sharing configuration immediately following ALD treatment and if during the activation any corner-sharing Ni···Ni restructure to the edge-sharing configuration is evident in model C (see the SI). Alternatively, a fraction of Ni clusters may adopt NiO-like structures during activation, e.g., model C → model B. During activation, small changes are evident in the XAS data. As seen previously,5 Ni remains in the divalent state, the preedge peak increases slightly, indicating a more distorted Ni environment, and the refined value for the coordination number decreases slightly (by 0.5 (0.3) from 5.4(2) to 4.9(2)). While this reduction in average coordination number was previously postulated to arise from a change from six- to five-coordination in isolated Ni sites (or substitution of a ligand

CONCLUSIONS

In summary, while the Ni loading achieved through one ALD cycle averages one Ni per pair of −OHx ligands, the present analysis reveals a local structure picture that is very different from this average. Instead of being dispersed around the equators of the nodes, over the −OHx sides available for ALD reaction, the deposited oxo-Ni(II) species exist as clusters preferentially located on node faces in the small pores but not the large hexagonal channel. This is supported by the low contribution from Ni···Zr paths to the XAS data, which is indicative of Ni clustering rather than their presence as isolated Ni sites. The EXAFS and PDF analyses suggest that the local structure of these oxo-Ni(II) clusters contains edge-sharing NiO6 octahedra, and a DFT-optimized cluster model related to α-Ni(OH)2 provides the best correspondence to the experimental data. During activation, the most significant changes are associated with a conformational change of the Ni sites (i.e., from corner- to edge-sharing octahedra) accompanied by the removal of water. The c-axis length of the oxo-Ni(II) clusters (7.5−8 Å O···O) optimized via DFT matches the distance between nodes across the small cavity. The internode distance decreases from ∼8.5 Å in pristine NU-1000 to 8 Å in Ni-AIM (O···O). We propose that the large contraction along the c-axis during ALD is due to bridging of the adjacent nodes by the Ni species, which pulls bridged nodes closer together, coupling the structures of the supported nanocatalyst and nanocatalyst support. This has important implications for the catalytic activity, wherein bridging and strain exerted on the Ni cluster by the MOF lattice may contribute to the observed distortion of the Ni environment. Strain and distortion can be important to the catalytic activity.42 This bridging structure motif, whereby clusters are well separated, may further mitigate sintering and catalyst deactivation. The one-dimensional bimetallic metal-oxo chains formed within the NU-1000 through bridging of the Zr6 nodes by Ni4 clusters suggests that AIM could provide a novel approach to preparing nanowires of controlled compositional heterogeneity. Indeed, under appropriate treatment with displacement of the bridging pyrene tetracarboxylate ligands, it may be possible to decouple and isolate these linear chains. 10416


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(2) 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. J. Am. Chem. Soc. 2013, 135, 10294. (3) Mondloch, J. E.; Katz, M. J.; Isley, W. C.; 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. Nat. Mater. 2015, 14, 512. (4) Li, Z.; Peters, A. W.; Bernales, V.; Ortuño, M. A.; Schweitzer, N. M.; DeStefano, M. R.; Gallington, L. C.; Platero-Prats, A. E.; Chapman, K. W.; Cramer, C. J.; Gagliardi, L.; Hupp, J. T.; Farha, O. K. ACS Cent. Sci. 2017, 3, 31. (5) Li, Z.; Schweitzer, N. M.; League, A. B.; Bernales, V.; Peters, A. W.; Getsoian, A. B.; Wang, T. C.; Miller, J. T.; Vjunov, A.; Fulton, J. L.; Lercher, J. A.; Cramer, C. J.; Gagliardi, L.; Hupp, J. T.; Farha, O. K. J. Am. Chem. Soc. 2016, 138, 1977. (6) Howarth, A. J.; Liu, Y.; Li, P.; Li, Z.; Wang, T. C.; Hupp, J. T.; Farha, O. K. Nat. Rev. Mater. 2016, 1, 15018. (7) Platero-Prats, A. E.; Mavrandonakis, A.; Gallington, L. C.; Liu, Y.; Hupp, J. T.; Farha, O. K.; Cramer, C. J.; Chapman, K. W. J. Am. Chem. Soc. 2016, 138, 4178. (8) Planas, N.; Mondloch, J. E.; Tussupbayev, S.; Borycz, J.; Gagliardi, L.; Hupp, J. T.; Farha, O. K.; Cramer, C. J. J. Phys. Chem. Lett. 2014, 5, 3716. (9) Kim, I. S.; Borycz, J.; Platero-Prats, A. E.; Tussupbayev, S.; Wang, T. C.; Farha, O. K.; Hupp, J. T.; Gagliardi, L.; Chapman, K. W.; Cramer, C. J.; Martinson, A. B. F. Chem. Mater. 2015, 27, 4772. (10) Peters, A. W.; Li, Z.; Farha, O. K.; Hupp, J. T. ACS Nano 2015, 9, 8484. (11) Klet, R. C.; Wang, T. C.; Fernandez, L. E.; Truhlar, D. G.; Hupp, J. T.; Farha, O. K. Chem. Mater. 2016, 28, 1213. (12) Gallington, L. C.; Kim, I. S.; Liu, W.-G.; Yakovenko, A. A.; Platero-Prats, A. E.; Li, Z.; Wang, T. C.; Hupp, J. T.; Farha, O. K.; Truhlar, D. G.; Martinson, A. B. F.; Chapman, K. W. J. Am. Chem. Soc. 2016, 138, 13513. (13) Toby, B. H.; Von Dreele, R. B. J. Appl. Crystallogr. 2013, 46, 544. (14) Hammersley, A. P.; Svensson, S. O.; Hanfland, M.; Fitch, A. N.; Hausermann, D. High Pressure Res. 1996, 14, 235. (15) Chupas, P. J.; Chapman, K. W.; Kurtz, C.; Hanson, J. C.; Lee, P. L.; Grey, C. P. J. Appl. Crystallogr. 2008, 41, 822. (16) Le Bail, A. J. Non-Cryst. Solids 1995, 183, 39. (17) Petříček, V.; Dušek, M.; Palatinus, L. Z. Kristallogr. - Cryst. Mater. 2014, 229, 345. (18) Yakovenko, A. A.; Reibenspies, J. H.; Bhuvanesh, N.; Zhou, H.C. J. Appl. Crystallogr. 2013, 46, 346. (19) McCusker, L. B.; Baerlocher, C. Chem. Commun. 2009, 1439. (20) Yakovenko, A. A.; Wei, Z.; Wriedt, M.; Li, J.-R.; Halder, G. J.; Zhou, H.-C. Cryst. Growth Des. 2014, 14, 5397. (21) Qiu, X.; Thompson, J. W.; Billinge, S. J. L. J. Appl. Crystallogr. 2004, 37, 678. (22) Wojdyr, M. J. Appl. Crystallogr. 2010, 43, 1126. (23) Farrow, C. L.; Juhas, P.; Liu, J. W.; Bryndin, D.; Bozin, E. S.; Bloch, J.; Proffen, T.; Billinge, S. J. L. J. Phys.: Condens. Matter 2007, 19, 7. (24) Segre, C. U.; Leyarovska, N. E.; Chapman, L. D.; Lavender, W. M.; Plag, P. W.; King, A. S.; Kropf, A. J.; Bunker, B. A.; Kemner, K. M.; Dutta, P.; Duran, R. S.; Kaduk, J. AIP Conf. Proc. 1999, 521, 419. (25) Setthapun, W.; Williams, W. D.; Kim, S. M.; Feng, H.; Elam, J. W.; Rabuffetti, F. A.; Poeppelmeier, K. R.; Stair, P. C.; Stach, E. A.; Ribeiro, F. H.; Miller, J. T.; Marshall, C. L. J. Phys. Chem. C 2010, 114, 9758. (26) Ravel, B.; Newville, M. J. Synchrotron Radiat. 2005, 12, 537. (27) Rehr, J. J.; Kas, J. J.; Vila, F. D.; Prange, M. P.; Jorissen, K. Phys. Chem. Chem. Phys. 2010, 12, 5503. (28) 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.;

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/jacs.7b04997. Details of the material synthesis, N2 adsorption isotherms, computation, X-ray scattering, and spectroscopy analysis (PDF)

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AUTHOR INFORMATION

Corresponding Author

*[email protected] ORCID

Ana E. Platero-Prats: 0000-0002-2248-2739 Leighanne C. Gallington: 0000-0002-0383-7522 Zhanyong Li: 0000-0002-3230-5955 Jian Zheng: 0000-0003-2054-9482 Omar K. Farha: 0000-0002-9904-9845 Joseph T. Hupp: 0000-0003-3982-9812 Johannes A. Lercher: 0000-0002-2495-1404 Donald G. Truhlar: 0000-0002-7742-7294 Laura Gagliardi: 0000-0001-5227-1396 Christopher J. Cramer: 0000-0001-5048-1859 Karena W. Chapman: 0000-0002-8725-5633 Notes

The authors declare the following competing financial interest(s): J.T.H. and O.K.F. have a financial interest in the start-up company NuMat Technologies, which is seeking to commercialize metalorganic frameworks.

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ACKNOWLEDGMENTS This work was supported as part of the Inorganometallic Catalysis Design Center, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, under Award No. DE-SC0012702. Work done at Argonne was performed using the Advanced Photon Source, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC0206CH11357. XAS measurements at 20-BM were further supported by the Canadian Light Source. We thank Dr. A. B. F. Martinson and Dr. I. S. Kim for preparing the Ni-AIM sample used for variable-temperature diffraction analysis of the lattice dimensions. A.E.P.P. acknowledges a Beatriu de Pinós fellowship (BP-DGR 2014) from the Ministry of Economy and Knowledge from the Catalan Government. STEM experiments were supported by the Chemical Imaging Initiative (CII) Laboratory Directed Research and Development (LDRD) Program at Pacific Northwest National Laboratory (PNNL). PNNL is a multiprogram national laboratory operated by Battelle for the U.S. DOE under Contract DE-AC0576RL01830. The STEM work was performed using the Environmental Molecular Sciences Laboratory (EMSL), a national scientific user facility sponsored by the Department of Energy’s Office of Biological and Environmental Research and located at PNNL. MRCAT operations are supported by the Department of Energy and the MRCAT member institutions.

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REFERENCES

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