MetalâOrganic Frameworks - ACS Publications - American Chemical

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The Journal of Physical Chemistry

Water Structure and Dynamics in Homochiral [Zn(l-L)(X)] Metal-Organic Frameworks Zachary L. Terranova,‡ Matthew M. Agee,‡ Francesco Paesani* Department of Chemistry and Biochemistry, University of California, San Diego 9500 Gilman Drive, La Jolla, CA 92093 KEYWORDS: Metal-organic frameworks, confined water, proton conduction, interfaces

The structural, thermodynamic, and dynamical properties of water adsorbed in two homochiral metal-organic frameworks (MOFs) with general formula [Zn(l-L)(X)], X = Cl and Br, and L = 3methyl-2-(pyridin-4-ylmethylamino)-butanoic acid, are investigated through molecular dynamics simulations. Water molecules establish distinct hydrogen-bonding patterns within the pores of the two MOFs, which directly correlate with the strength of the underlying framework-water interactions. In particular, at low loading, the Zn-Cl groups of [Zn(l-L)(Cl)] effectively provide a templating scaffold for the formation of one-dimensional hydrogen-bonded water chains that propagate along the MOF channels following the helicity of the framework. In contrast, the relatively weaker framework-water interactions in [Zn(l-L)(Br)] lead to less ordered water distributions inside the pores. The simulation results are in agreement with the available experimental data and provide molecular-level insights into specific hydrogen-bonding motifs and spatial arrangements of the water molecules inside the pores, which can be related to the different proton conductivities measured for the two MOFs.

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1. INTRODUCTION The intrinsic chemical diversity and porosity make metal-organic frameworks (MOFs) promising materials for several technological applications, including gas storage (e.g., methane and hydrogen storage),1-11 carbon capture,12-17 hydrocarbon separation,18-20 catalysis,21-27 electrical28-29 and proton30-42 conductivity, magnetism43-48 and luminescence.49 However, despite their versatility, several frameworks display low stability when exposed to moisture, which has limited the use of MOFs in industrial applications thus far.50-51 On the other hand, MOF solubility has been successfully exploited for in vivo medical applications and water-unstable frameworks have been specifically synthesized for drug delivery and imaging applications under physiological conditions.52-55 A detailed understanding of the behavior of water within the MOF pores, including the identification of fundamental water-framework interactions and the characterization of possible degradation mechanisms is crucial to the rational design of new stable structures tailored for large-scale applications. For example, it is known that small amounts of water in the pores can enhance the CO2 adsorption capacity of certain MOFs, including MOF-100,56 HKUST-1,57 and MIL-10158 while, in other cases, water was found to be detrimental to carbon capture in more hydrophilic MOFs, since both H2O and CO2 molecules compete for the same binding sites within the pores.51 The structural properties of MOFs can also be affected by the presence of water. As mentioned above, some frameworks degrade irreversibly under mild conditions while other structures remain highly stable even when completely immersed in boiling water.51 In general, the stability of MOFs exposed to steam with different levels of saturation can be correlated with the estimated dissociation energy of the metal-ligand bonds. It has been shown that some MOFs,


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such as those belonging to the MIL-53 family, can undergo reversible transitions from large- to narrow-pore structures as a function of the amount of water adsorbed in the pores.59-62 More recently it has been demonstrated that water molecules can mediate proton conduction through the MOF pores.37 For example, a significant variation in proton conduction was observed upon water adsorption in a series of isostructural frameworks belonging to the MIL-53 family, with the differences in the measured conductivities being correlated with the acidity of the functional groups of the framework.63 A family of four homochiral MOFs with general formulas [Zn(γ-L)(X)], with γ = l or d, X = Cl and Br, and L = 3-methyl-2-(pyridin-4ylmethylamino)-butanoic acid, was also investigated for proton conduction.64 Although all four MOFs were found to adsorb water, proton conductivity (4.4 x 10-5 S cm-1) was only observed in the two [Zn(γ-L)(Cl)] enantiomeric structures. Proton conduction in MOFs with general formula (NH4)2(adp)[Zn2(ox)3] was also shown to be remarkably dependent on the amount of water adsorbed in the pores.33 A molecular-level understanding of the relationship between water behavior inside the pores and overall MOF properties has only recently started to emerge. Molecular dynamics (MD) simulations with classical force fields suggested that the displacement of the benzene dicarboxylate (BDC) linkers coordinated to the Zn centers in MOF-5 (also known as IRMOF-1) was likely involved in the degradation process upon exposure to moisture.65 However, subsequent simulations performed with an empirically parameterized reactive force field indicated that water hydrolysis promoted by direct interactions of H2O molecules with the Zn centers of the framework was actually responsible for the collapse of the MOF-5 structure.66 Grand canonical Monte Carlo (GCMC) simulations were employed to study the mechanisms of water adsorption in MIL-100(Cr) and MIL-101(Cr).67 The breathing effect of MIL-53(Cr)


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induced by water adsorption was characterized using both MD and GCMC simulations.60, 68 The impact of nuclear quantum effects62 and electronic polarization61, 68 on the properties of water adsorbed in the MIL-53(Cr) pores was investigated through molecular simulations. These studies predicted relatively stronger interactions between water molecules and the µ2-OH groups of the framework as well as a significantly slower water dynamics in the MOF pores compared to liquid water as a result of confinement.68 These predictions were confirmed by subsequent ab initio MD simulations based on density functional theory (DFT).69-70 More recently, MD simulations were used to reveal the microscopic mechanisms associated with water-mediated proton transport in MIL-53 as a function of temperature, water loading, and pore size.34 The structure of the hydrated proton was found to resemble that of a distorted Zundel complex when the MIL-53 framework was in the narrow-pore configuration. A transition to Eigen-like structures was then observed at higher water loading when the pores opened as a result of the breathing effect.34 In this study, MD simulations are used to investigate the structure and dynamics of water in the [Zn(γ-L)(X)] MOFs (with X = Cl and Br) of Ref. 64. As mentioned above, relatively high proton conductivity was observed upon water adsorption in the Cl-substituted framework but not in the Br-substituted isomer.64 The main focus of this study is on characterizing the relationship between framework properties and water behavior as a function of loading as well as on identifying specific hydrogen-bonding motifs and spatial arrangements of the water molecules in the pores, which are directly related to the different proton conductivities measured for [Zn(γL)(Cl)] and [Zn(γ-L)(Br)]. The paper is organized as follows: The computational methodology is presented in Section 2, the structural and dynamical properties of water inside the pores as a


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function of loading are discussed in Section 3, and a brief summary and outlook are given in Section 4. 2. COMPUTATIONAL METHODOLOGY Since the proton conductivities measured in Ref. 64 were found to be dependent on the specific halogen present on the framework and not related to the specific enantiomeric form of the MOF structure, molecular models were developed only for the [Zn(γ-L)(X)] with γ = l. Following our previous studies,47, 71 fully flexible force fields were developed for both [Zn(l-L)(Cl)] and [Zn(lL)(Br)] MOFs, and used in MD simulations aimed at characterizing the behavior of water in the MOF pores as a function of loading. The General Amber Force Field (GAFF) was used to model the intramolecular interactions of the L ligand.72 Specific parameterizations of all relevant Zn-L and Zn-X interactions were derived from fits to ab initio data obtained for the reduced MOF

Figure 1. The molecular model used in the parameterization of the flexible force field for [Zn(lL)(Cl)]. H atoms are in white, C atoms are in grey, N atoms are in blue, O atoms are in red, the Cl atom is in green, and the Zn atom is light violet (center). An analogous model with Br replacing Cl was used for [Zn(l-L)(Br)].


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model shown in Figure 1. All ab initio calculations were carried out with Gaussian 0973 at the DFT level using the M062X functional74 in combination with the cc-pVDZ basis set for H, C, O, and Cl,75 and the ccpVDZ-PP basis set for Zn.76 After performing energy minimizations on both Cl- and Brsubstituted reduced models, potential energy scans along the corresponding normal modes were carried out to map the underlying energy landscape. Fits to the potential energy curves corresponding to normal modes with frequencies below 500 cm-1 were then performed with a genetic algorithm77 to determine the force field parameters associated with the description of all bonds, angles, and dihedrals containing the Zn centers. The threshold of 500 cm-1 (719 K) was specifically chosen to guarantee an accurate description of the low-frequency modes of the framework, which determine the overall flexibility of the MOF structures at ambient conditions. The atomic partial charges were obtained from fits to the electrostatic potential of an extended model (see Supporting Information) calculated using the CHELPG method.78 The water interactions were described by the aSPC/Fw model79 and the force field parameters associated with the nonbonded framework-water interactions were derived from the Lorentz-Berthelot mixing rule.80 Although highly accurate ab initio water potentials have recently become available (e.g., see Refs. 81-88), their integration in MD simulations of MOFs is still prohibitive due to the existing incompatibility with the force fields currently used to describe the frameworks. Research in this area, involving the development of ab initio potentials for both inorganic and organic MOF subunits, is ongoing in our group. On the other hand, besides being computationally expensive give the system size and simulation lengths required for an accurate modeling of MOF properties, popular DFT models commonly used in ab initio molecular dynamics simulations have been shown not to be particularly accurate in describing the


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properties of water (e.g., see Ref. 89 for recent benchmark calculations). Among classical water models, the aSPC/Fw model was specifically chosen because it is the underlying water force field employed in the anharmonic multistate empirical valence bond (aMS-EVB3) model of protonated water,79 which, following Ref. 34, we are currently using to investigate proton conduction in both [Zn(l-L)(Cl)] and [Zn(l-L)(Br)]. Specific details about the fitting procedure along with the complete list of the force field parameters are reported in the Supporting Information. All MD simulations were performed with DL_POLY Classic90 on [Zn(l-L)(X)] structures consisting of 2 x 2 x 2 primitive cells in periodic boundary conditions. The short-range interactions were truncated at an atom-atom distance of 9.0 Å, while the electrostatic interactions were treated using the Ewald method.80 The MD simulations were carried out with a variable number of water molecules per primitive cell. The water molecules were initially distributed uniformly in the MOF pores, and each system was equilibrated for 5 ns through MD simulations carried out in the constant stress and constant temperature (NσT) ensemble. The production runs were then performed in the canonical (NVT) ensemble for 5 ns, which were used to calculate all structural and thermodynamic properties, as well as in the microcanonical (NVE) ensemble for an additional 1 ns, which was used to calculate all dynamical properties.91 The temperature and pressure were maintained via Nosé-Hoover thermostat and barostat with relaxation times of 1 and 5 ps, respectively. The equations of motion were propagated according to the velocity Verlet algorithm with a time step of 0.5 fs.80 The self-diffusion coefficient, D, of the water molecules in the pores of the two [Zn(l-L)(X)] MOFs was obtained from the Einstein relation


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D = lim

rcom ( t ) − rcom ( 0 )

t→∞

where rcom ( t ) − rcom ( 0 )

2

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2

6t

(1)

is the center-of-mass (com) mean square displacement of each water

molecule and the angle bracket indicates an ensemble average over all water molecules. The time scales associated with the orientational dynamics of the water molecules inside the pores were extracted from exponential fits to the corresponding time decays of the orientational time autocorrelation function C 2 ( t ) = P2 e ( 0 ) ⋅ e ( t ) , where P2 e ( 0) ⋅ e ( t ) is the second Legendre polynomial of the angle spanned in time by the unit vector e(t) lying on one OH bond of each H2O molecule, and the brackets indicate an ensemble average over both OH bonds and water molecules. 3. RESULTS AND DISCUSSION 3.1 Thermodynamic and structural properties Typically Zn-based MOFs are susceptible to hydrolysis when exposed to water and become unstable even when exposed to low relative humidity.65-66, 92 In the [Zn(l-L)(X)] MOFs studied here, however, the halogen atoms of the framework have a protecting effect on the Zn centers thus providing H2O molecules with more favorable binding sites, which, in turn, enables the framework to remain intact upon hydration. Analogous to bare ions in solution, the metal-halide groups on the framework are known to be good hydrogen bond acceptors and have the ability to perturb the structure and dynamics of liquid water.93-98 The degree of interaction between the water molecules adsorbed in the MOF pores and the framework itself can be quantified by the heat of adsorption, ∆H, shown in Figure 2. In this study, ∆H = H(0) - H(N), where H(N) is the enthalpy of the MOF at a given water loading, N,


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Figure 2. Differential heat of adsorption for water in [Zn(l-L)(X)] with X = Cl (green) and Br (blue) calculated for N = 2, 4, 6, 8, 10, 12, 18, and 24 H2O molecules per pore. See main text for details.

and H(0) is the enthalpy of the completely dehydrated MOF. Both H(N) and H(0) were calculated from NσT simulations and N corresponds to the number of H2O molecules per pore. For water in [Zn(l-L)(Cl)], ∆H is ~10 kcal/mol at N = 2, increases up to ~12 kcal/mol at N = 6 before dropping significantly at N = 8 and then stabilizing at the approximately constant value of ~9 kcal/mol for N ≥ 10. By contrast the heat of adsorption of water in [Zn(l-L)(Br)] displays a larger variation, starting at ~5 kcal/mol at N = 2, reaching a maximum of ~16 kcal/mol at N = 8, before decreasing to ~1 kcal/mol at N = 24. The variation of ∆H with N can be rationalized by considering the specific Zn—X ⋯ H—OH interactions that exist inside the pores of the two isomeric MOFs, with the Zn—Cl ⋯ H—OH interaction being relatively stronger.96-98 This correlates with the increase of ∆H in [Zn(l-L)(Cl)] up to N = 6, corresponding to the number of Zn—Cl groups within a pore. At higher loading, when all Zn—Cl sites in the pores are saturated,


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the additional water molecules must interact with less favorable binding sites, thus explaining the large drop of ∆H at N = 8. The subsequent increase of ∆H for water in [Zn(l-L)(Cl)] suggests the formation of a stable hydrogen-bond network between the H2O molecules adsorbed within the pores. The presence of weaker framework-water interactions in [Zn(l-L)(Br)] manifests itself in the low value of ∆H for N = 2, when all Br sites on the framework are effectively available for binding. As it will become more evident from the analysis of the spatial distribution of the water molecules inside the pores (Figure 3), the large value of ∆H predicted at N = 8 in [Zn(l-L)(Br)] is indicative of an optimal balance between water packing and water-framework interactions. As N increases, crowding repulsive effects between water molecules confined in the pores dominate and consequently lead to a reduction of the heat of adsorption. The low value of ∆H predicted for N = 24 in [Zn(L)(Br)] indicates a much lower affinity of water for the framework at high loadings. This is in agreement with variable-temperature single-crystal X-ray diffraction measurements that found water evaporating from [Zn(l-L)(Br)] at much lower temperature than from [Zn(l-L)(Cl)].64 Due to weaker framework-water interactions, the spatial arrangement of the H2O molecules in the [Zn(l-L)(Br)] pores is less ordered as demonstrated by the three-dimensional density distributions calculated for the water oxygen which are shown in Figure 3. From the inspection of the front view of the water density at N = 6, 12, 18, and 24, it is immediately apparent that well-defined pockets of dense regions arranged in a hexagonal pattern persist in the vicinity of the Zn—Cl groups at all levels of loading in [Zn(l-L)(Cl)]. The three-dimensional densities also show that, after binding to each of the six Zn—Cl groups within a pore, the water molecules start developing an inner hydrogen-bonded layer that propagates along the MOF channels. The


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templating effect of the [Zn(l-L)(Cl)] framework on the water distribution correlates with the heat of adsorption shown in Figure 2, providing direct evidence of different binding motifs within the pores as a function of N. By contrast, due to weaker framework-water interactions, H2O molecules adsorbed in the [Zn(l-L)(Br)] pores do not remain in stable formations, which thus results in more diffuse spatial distributions. Further insights into the spatial arrangement of the water molecules in the MOF pores are l

l

Figure 3. Three-dimensional density distributions of the water oxygen calculated for [Zn(lL)(Cl)] (first two columns) and [Zn(l-L)(Br)] last two columns as a function of the number of water molecules, N, per pore. The first and third columns show front views while the second and fourth columns show side views of the corresponding MOF channels. The coordinates of the framework atoms were averaged over 5 ns of MD simulation in the NVT ensemble. H atoms are in white, C atoms are in dark grey, N atoms are in blue, O atoms are in red, Cl atoms are in green, Br atoms are in orange, Zn atoms are light violet. The water densities (shown at an isosurface value of 0.16 Å-3) are in light blue. ACS Paragon Plus Environment

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gained from the analysis of the three-dimensional density distributions along the MOF channels. As mentioned above, the water molecules adsorbed in the [Zn(l-L)(Cl)] pores arrange in consecutive layers that are templated by the Zn—Cl groups and propagate along the MOF channels, effectively forming one-dimensional hydrogen-bonded chains that follow the l-helicity of the framework. While a roughly similar spatial arrangement is also found in [Zn(l-L)(Br)], the water molecules in this case fail to maintain a high level of order, resulting in more scattered density distributions. The present MD simulations also predict a higher degree of distortion of the [Zn(l-L)(Br)] framework upon water adsorption due to the intrinsic MOF flexibility as well as to the larger size of the Br atoms which effectively reduces the pore volume available to the water molecules, thus resulting in higher internal pressures for the same water loading. A detailed analysis of the effects of framework flexibility on the properties of MOFs upon water adsorption is currently being investigated by our lab. Quantitative information on the spatial distribution of the water molecules in the two homochiral MOFs can be obtained from the analysis of the radial distribution functions (RDFs) shown in Figure 4, which directly report on unique structural features depending on the Zn—X groups present on the framework. The Ow-Cl RDFs, describing the spatial correlations between the oxygen atoms (Ow) of the H2O molecules and the Cl atoms of the framework, display distinct peaks at ~3.4 Å, ~5.8 Å and ~8.0 Å, arising from the ordered arrangement of the water molecules inside the [Zn(l-L)(Cl)] pores which is templated by the helical periodicity of the M— Cl groups along the MOF channels. In contrast, the analogous Ow-Br RDFs are less structured, displaying a main peak at ~3.4 Å and a smaller peak at ~4.7 Å, which gradually disappears as N increases. The dependence of the two Ow-X RDFs on water loading directly reflects the relative strengths of the underlying framework-water interactions, with the stronger Zn—Cl ⋯ H—OH


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interaction being capable of effectively holding the water molecules at fixed distances from each other. As shown in Figure 3, once all Zn—X sites are hydrated, the additional water molecules are unable of interacting directly with the framework and begin filling the inner region of the MOF channels. As a consequence, the two Ow-X RDFs become more similar at higher loadings. The different hydrogen-bonding patterns that the water molecules establish in the two [Zn(lL)(X)] MOFs as a function of loading clearly emerge from the analysis of the Ow-Ow RDFs. Specifically, a single peak at ~6.2 Å is found at low loadings in [Zn(l-L)(Cl)], corresponding to the shortest distance between water molecules bound to adjacent Zn—Cl groups. In contrast, two

Figure 4. Ow-Cl (panel a), Ow-Br (panel b), and Ow-Ow (panels c and d) radial distribution functions calculated for [Zn(l-L)(Cl)] (left column) and [Zn(l-L)(Br)] (right column) as a function of the number of water molecules, N, per pore. See main text for details.


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peaks are found at ~2.8 Å and ~5.4 Å for the Ow-Ow RDF in [Zn(l-L)(Br)]. These two peaks result from the competition between framework-water and water-water interactions, with the peak at the shortest distance corresponding to water molecules directly hydrogen-bonded to each other. In both MOFs, the first Ow-Ow peak at ~2.8 Å becomes more pronounced as a function of water loading, reflecting the increasing number of H2O molecules that establish hydrogen bonds between each other. This is accompanied by the simultaneous development of a broad peak between 4.0 Å and 5.0 Å, which is associated with hydrogen-bonded water molecules located within different layers inside the pores (see Figure 3). 3.2 Dynamical properties Despite being homochiral MOFs, the presence of different halogen atoms in the framework results in distinct dynamical properties of the water molecules adsorbed in the pores. The variation of the overall water diffusion coefficient (blue), along with the corresponding components, parallel (red) and perpendicular (green) to the MOF channels, is shown in Figure 5

Figure 5. Water diffusion coefficient (D) and its components perpendicular (Dx,y) and parallel (Dz) to the MOF channels calculated in [Zn(l-L)(Cl)] (panel a) and [Zn(l-L)(Br)] (panel b) as a function of number of water molecules, N, per pore. Statistical uncertainties are within the size of the symbols. See main text for details.


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as a function of loading. As a reference, the aSPC/Fw model predicts a self diffusion coefficient of 0.233 Å2 ps-1 for bulk water, in good agreement with the experimental value (0.229 Å2 ps-1).79 The diffusion of water in [Zn(l-L)(Br)] is effectively only contingent upon the amount of water present in the pores and increases as a function of loading (panel a). By contrast, up to N = 6, which corresponds to the minimum number of water molecules necessary to saturate all Zn—Cl groups within a pore, the diffusion coefficient of water in [Zn(l-L)(Cl)] is extremely small, indicating that the water molecules are effectively immobile at low loadings. Once all Zn—Cl groups are saturated, the diffusion coefficient increases incrementally with N as the water molecules begin filling the inner region of the MOF channels where they can move relatively more freely, only impeded by the surrounding hydrogen-bond network. As expected, due to the confining environment provided by the framework, the diffusion of H2O molecules along the MOF channels, Dz, is significantly faster than the diffusion along perpendicular directions, Dx,y. Molecular-level insights into the dynamics of the hydrogen-bond network established inside the MOF pores can be derived from the analysis of the water orientational correlation function,

Figure 6. Orientational correlation functions, C2(t), calculated for water in [Zn(l-L)(Cl)] (panel a) and [Zn(l-L)(Br)] (panel b) as a function of number of H2O molecules, N, per pore. See main text for details.


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C2(t) introduced in Section 2, which is proportional to the experimentally measured orientational anisotropy.99 In particular, the intermediate time scale of orientational relaxation directly reflects the breaking and forming of intermolecular hydrogen bonds, whereas the short and long time decays of C2(t) can be related to librational motions and complete structural randomization, respectively. In this study, the time decay of C2(t), shown in Figure 6 for different water loadings in [Zn(l-L)(Cl)] and [Zn(l-L)(Br)], were fitted to a tri-exponential function

C2 ( t ) = A1e −t τ1 + A 2 e−t τ2 + A 3e−t τ3

(2)

where Ai are the amplitudes and τi are the relaxation time constants associated with each exponential, which are reported in Table 1. After an initial fast drop, C2(t) displays a different time decay as a function of the number of water molecules per pore in the two MOFs. In fact, the different behavior of water in the two MOFs at low loadings can be directly determined from the analysis of the second relaxation time, τ2, associated with the formation and cleavage of hydrogen bonds. At low loadings, water molecules within [Zn(l-L)(Cl)] reorient at much slower rates due to the relatively stronger hydrogen bonds formed with the Zn—Cl groups, with τ2 ranging from 50 to 100 ps when N ≤ 6. This critically retarded hydrogen-bond dynamics persists until addition of more water molecules (N ≥ 8), which, as mentioned above, results in the formation of a second concentric and relatively more mobile water layer extending along the MOF channels. In contrast, as a result of the weaker framework-water interactions, the values of τ2 for the water reorientation within the [Zn(l-L)(Br)] pores display a much smaller variation with N, being always less than 25 ps independently of loading. The calculated τ2 values thus show that, in both MOFs, the formation and cleavage of hydrogen bonds between water molecules occurs on significantly slower time scales than in the liquid phase (τ2 = 2.7 ps for aSPC/Fw water at ambient conditions79). The suppressed water mobility inside the pores thus


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Table 1. Relaxation time constants, τI, obtained from fits to orientational correlation functions calculated for water in [Zn(l-L)(Cl)] and [Zn(l-L)(Br)] as a function of number

of H2O molecules per pore. [Zn(l-L)(Cl)]

[Zn(l-L)(Br)]

N

τ1 (ps)

τ2 (ps)

τ3 (ps)

τ1 (ps)

τ2 (ps)

τ3 (ps)

2

0.06

94

> 1000

< 0.01

22

315

4

0.05

50

300

< 0.01

18

385

6

0.05

100

750

< 0.01

22

480

8

< 0.01

16

180

< 0.01

19

450

10

< 0.01

25

215

< 0.01

15

410

12

< 0.01

14

180

< 0.01

20

390

18

< 0.01

16

210

< 0.01

15

260

24

< 0.01

10

90

< 0.01

10

160

suggests that proton conduction in the two MOFs can mainly occur through proton hopping between adjacent molecules according to the Grotthuss mechanism, which can explain the higher conductivity measured for [Zn(l-L)(Cl)] due to the presence of ordered water chains that extend along the MOF channels. Molecular-level studies of proton conduction in both [Zn(l-L)(Cl)] and [Zn(l-L)(Br)] are currently ongoing in our group. Finally, it is worth noting the large values of τ3, which are consistent with a very slow randomization of the orientation of the water molecules inside the pores due to the extreme confining effects of the frameworks. 4. CONCLUSIONS Understanding the molecular mechanisms that govern water adsorption, structure, and mobility in MOFs is key to the rational design of de novo hydrothermal stable frameworks for large-scale


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applications. Recent experimental measurements have shown that water adsorbed in the pores can efficiently mediate proton conduction in MOFs at relatively low temperature and humidity, although the underlying driving forces are not yet fully understood. In this study, molecular dynamics simulations were employed to characterize the behavior of water in two homochiral MOFs with general formula [Zn(l-L)(X)], X = Cl and Br. A direct correlation was found between the relative strength of the framework-water interactions and the structural and dynamical properties of the H2O molecules adsorbed in the MOF pores. In particular, the water molecules adsorbed in the [Zn(l-L)(Cl)] pores arrange in consecutive layers that are templated by the Zn— Cl groups and propagate along the MOF channels, effectively forming one-dimensional hydrogen-bonded chains that follow the l-helicity of the framework. In contrast, the relatively weaker framework-water interactions in [Zn(l-L)(Br)] were found to lead to less ordered water formations inside the pores. The slow dynamics predicted for water molecules adsorbed in the pores suggests that proton conduction in the two MOFs can mainly occur through proton hopping between adjacent molecules according to the Grotthuss mechanism, which supports the view derived in Ref. 64 based on the experimentally measured conductivities. ASSOCIATED CONTENT Supporting Information. Details of the fitting procedure used in the development of the flexible force fields for the two [Zn(l-L)(X)] MOFs, including a complete list of the force field parameters. This material is available free of charge via the Internet at http://pubs.acs.org. AUTHOR INFORMATION Corresponding Author * [email protected]


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Author Contributions ‡ These authors contributed equally. Funding Sources National Science Foundation, DMR-1305101 and ACI-1053575 U.S. Department of Energy, DE-FG02- 13ER16387 and DE-AC02-05CH11231

ACKNOWLEDGMENTS We wish to thank Mr. Adil Mohd-Salleh for helpful discussion at the early stages of this study. This research was supported by the National Science Foundation (Award Number DMR1305101) and the U.S. Department of Energy, Office of Science, under Award No. DE-FG0213ER16387, and used resources of the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the National Science Foundation Grant Number ACI-1053575 (Allocation TG-CHE110009) as well as of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract DE-AC02-05CH11231.

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