Diffusion of Water in Zeolites NaX and NaY ... - ACS Publications

Jun 11, 2009 - tetrahedra (in which the T-sites are occupied by either silicon .... Figure 1. (Color online) A pictorial view of the structure of hydr...
0 downloads 0 Views 5MB Size
Download PDF
J. Phys. Chem. C 2009, 113, 12373–12379

12373

Diffusion of Water in Zeolites NaX and NaY Studied by Quasi-Elastic Neutron Scattering and Computer Simulation Pierfranco Demontis,† Herve´ Jobic,§ Miguel A. Gonzalez,‡ and Giuseppe B. Suffritti†,* Dipartimento di Chimica, UniVersita` degli studi di Sassari, and Consorzio InteruniVersitario Nazionale per la Scienza e Tecnologia dei Materiali (INSTM), Unita` di ricerca di Sassari, Via Vienna, 2, 07100 Sassari (Italy), IRCELYON, Institut de Recherches sur la Catalyse et l’EnVironnement de Lyon, CNRS, UniVersite´ de Lyon, UMR5256, 2, AV. A. Einstein, 69629 Villeurbanne (France), Institut Laue-LangeVin, BP 156, 38042 Grenoble (France) ReceiVed: February 20, 2009; ReVised Manuscript ReceiVed: May 22, 2009

The diffusion of water in zeolites NaX and Y was investigated by quasi-elastic neutron scattering (QENS) and by a series of molecular dynamics simulations at different temperatures for different water loadings. The largest measured values of the diffusion coefficients are 1 order of magnitude smaller than in bulk water and are slightly lower in zeolite X than in zeolite Y. The dependence of the calculated diffusion coefficients versus the water content is very low at low loadings, diffusivity grows and reaches a maximum at intermediate loadings, and finally decays to smaller values when the loading approaches saturation. The reproduction of the experimental diffusion coefficient and activation energies by molecular dynamics simulations are discussed. In spite of the use of empirical potential models and classical mechanics equations, the computed activation energies are close to the experiment and the diffusion coefficients follow the same trend as the experimental ones, are of the same order of magnitude, but are overestimated, in particular in zeolite Y. Nevertheless, from these results some suggestions about the details of the diffusion mechanism may be inferred. 1. Introduction The behavior of water in restricted geometries has recently received a renewed interest, both from experimental and theoretical viewpoints. The confining media may be of biological nature, like cellular membranes or enzyme channels, as well as inorganic, such as carbon nanotubes, porous silica glasses, and zeolites or molecular sieves, which are important for their industrial and environmental applications. There is much experimental and theoretical evidence indicating that the properties of water, when confined in nanopores are different from those of common bulk water.1 For instance, the behavior of water in nanotubes has been investigated extensively.1-5 Among the materials characterized by nanopores and nanocavities able to adsorb water, zeolites play a special role. Zeolites are natural or synthetic crystalline compounds usually containing silicon, aluminum, oxygen, and exchangeable cations.6-8 The aluminosilicate framework is built up by corner sharing TO4 tetrahedra (in which the T-sites are occupied by either silicon or aluminum), giving rise to a rather complex but precisely repetitive atomic network with regular nanometric cavities connected by channels or windows, where guest molecules of appropriate size can be adsorbed. These void interior spaces are studded with cations, which compensate for the charge deficit due to the substitution of silicon by aluminum and can admit water, many simple gases, and larger molecules. The adsorption and the diffusion of water in zeolites is a subject of great scientific and technological interest, due to the broad spectrum * To whom correspondence should be addressed. Fax: +39-079-229559. Tel: +39-079-229552. E-mail: [email protected]. † Universita` di Sassari and Consorzio Interuniversitario Nazionale per la Scienza e Tecnologia dei Materiali (INSTM). § Institut de Recherches sur la Catalyse et l’Environnement de Lyon, CNRS, Universite´ de Lyon, UMR5256. ‡ Institut Laue-Langevin.

of zeolite applications as catalysts, adsorbents, molecular sieves, and ion exchangers.6-8 In the present study, we considered two synthetic zeolites of framework type FAU (characteristic of the natural zeolite Faujasite),9 zeolites X and Y, which are distinguished by the amount of aluminum substituting silicon in the structure. In zeolite X, the Si/Al ratio is in the range 1-1.5, whereas in zeolite Y it is in the range 1.6-3. Zeolites X and Y are of cubic symmetry, and their framework is composed by sodalite units interconnected through sixmembered oxygen bridges (hexagonal prisms). The resulting void space forms supercages with a free diameter of about 11 Å, which are tetrahedrally connected through 12-membered rings windows about 7.4 Å wide and form a diamond-like cubic lattice. Exchangeable cations, which compensate the charge deficit due to the Al/Si substitution, are located in the sodalite cages, in the hexagonal prisms, and on the surface of the supercages. Their distribution has been studied extensively and is still discussed.10-13 In the present article, Na-exchanged zeolites X and Y are considered. Zeolites X and Y contain water both in supercages and in sodalite cages, whose amount depends on the number of the exchangeable cations. In zeolite X, at room temperature, the number of adsorbed water molecules per unit cell (molecules/ u.c.) can exceed 25014 and approximately the same number in zeolite Y. Water can be removed by heating in vacuo or in inert gas flow and the complete removal occurs at temperatures above about 600 K in both zeolites.14 Water confined in zeolites NaX and NaY has been investigated experimentally using various techniques: X-ray diffraction (XRD),15,16 neutron powder diffraction,14 diffuse reflectance infrared Fourier-transform spectroscopy (DRIFT),14 temperatureprogrammed desorption (TPD),14 and, in the present work, quasielastic neutron scattering (QENS). The information, which can

10.1021/jp901587a CCC: $40.75  2009 American Chemical Society Published on Web 06/11/2009

12374

J. Phys. Chem. C, Vol. 113, No. 28, 2009

Demontis et al.

Figure 1. (Color online) A pictorial view of the structure of hydrated zeolite NaX containing 120 water molecules per u.c. Si atoms are red, Al atoms are green, O atoms are light gray, and Na cations are orange. The view is from the main diagonal of the unit cell, showing at the center the zigzag channel formed by the supercages connected by 12-membered rings.

be extracted from experimental techniques suggests that the dynamical behavior of the water molecules adsorbed in zeolites X and Y is not homogeneous, but it is possible to distinguish different kinds or classes of the molecules, depending on their location and on the interactions with the aluminosilicate framework, the Na cations, and the other water molecules. However, an atomistic interpretation of the different behaviors is still incomplete. Among the different approaches to get a microscopic insight of hydrated zeolites, the molecular dynamics (MD) simulation technique is very promising in order to complement the experimental information about structural and dynamical properties of zeolites17-24 and we used this technique to evaluate the hydration energy, the position of the water molecules, the vibrational spectra, the relaxation time of the flip motion of the water molecules around their axes, and the diffusivity. Previous MD simulations in hydrated dealuminated (cation-free) zeolite Y were reported by Fleys et al.,25 who simulated the diffusion of water with a flexible framework and water molecule model at different temperatures in the range 250-600 K with 8 molecules/u.c. and, for the limited range 300-500 K, with a water content between 2 and 20 molecules/u.c. This article is devoted to the diffusion of water adsorbed in zeolites X and Y investigated both experimentally using the QENS technique26 and by MD simulations, using a potential model developed by the research group to be used for extended MD simulations of dynamical processes occurring in hydrated zeolites, including diffusion, cation exchange, and dynamical heterogeneities.17-23 It was recently refined to reproduce better the hydration energies and the diffusivities because some preliminary tests showed that it was unsatisfactory.24 2. Experimental Section The NaX (Si/Al ) 1.23) and NaY (Si/Al ) 2.43) zeolites were activated by heating to 673 K under flowing oxygen. After

cooling, the zeolites were pumped to 10-4 Pa while heating up to 673 K. Several samples were prepared by adsorbing known amounts of water onto the activated zeolites; they correspond to 60, 120, and 200 molecules of water per unit cell. The samples were transferred, inside a glovebox, into aluminum containers of annular geometry. All samples were equilibrated at 423 K during 10 h. Cells containing the dehydrated zeolites were also prepared, and their signal was subtracted from the spectra recorded with the cells containing adsorbed water. The neutron experiment was performed on the backscattering spectrometer IN10 at the Institut Laue-Langevin, Grenoble. The containers were placed in a cryofurnace. The incident neutron energy was 2.08 meV (6.27 Å), using a Si(111) monochromator. Quasi-elastic measurements were performed by applying a Doppler shift to the incident neutrons through a movement of the monochromator. Spectra were recorded at different scattering angles, corresponding to wave vector transfer values, Q, ranging from 0.15 to 1.6 Å-1. The resolution function could not be fitted with a simple analytical function so that numerical convolution was employed. The half-width at half-maximum (HWHM) of the energy resolution is on the order of 0.5 µeV. The energy transfer was analyzed in a window of (11 µeV. The scattered intensity is dominated by the hydrogen atoms’ motions because of the large incoherent cross section of hydrogen. In that case, one can extract the self-diffusivity of water from the QENS spectra.26 3. Model and Calculations The structures of hydrated zeolite X Na88[Al88Si104O384] · nH2O (n < 120) belongs to the cubic symmetry group Fd3j14 and that of zeolite Y, Na56[Al56Si136O384] to the symmetry space group Fd3m.27 They are illustrated in Figures 1 and 2. As shown in Figures 1 and 2, there are different sites that can be occupied by exchangeable Na ions. The problem of the

Diffusion of Water in Zeolites NaX and NaY

J. Phys. Chem. C, Vol. 113, No. 28, 2009 12375

Figure 2. (Color online) A pictorial view of the structure of hydrated zeolite NaY containing 120 water molecules per u.c. Symbols and view as in Figure 1.

distribution of the cations in the available sites in both zeolite X and Y is very difficult to solve, from experimental as well from the theoretical point of view, and it is still the object of a lively debate, as mentioned above.10-13 Indeed, not only the cation distribution should minimize the electrostatic repulsion but also it should be related to the equally almost unknown distribution of Al atoms among the possible T sites in the center of TO4 tetrahedra.28 The cation distribution in zeolite X was determined by starting from the structural data of ref 14 and by minimizing empirically the electrostatic repulsion and the total energy. Many possible distributions yielding similar total energy could be found, so that we choose one of them, by considering that their influence on the diffusive process at large scale should not be relevant, as the determining factor should be the average distance between the cations, yielding the average diffusive jump length of the water molecules. Indeed, water molecules are preferentially coordinated to the cations, as far it is allowed by the steric hindrance of other molecules and of the framework. As for the cation distribution in zeolite Y, we followed the same procedure, starting from the data of ref 27. The MD simulation box corresponded to one cubic crystallographic cell both for zeolites X and Y. The cell side in zeolite X corresponded, when available,14 to the experimental ones depending on the loading. It was a ) 25.1074 Å for the lowest loading (20 mol/u.c.), a ) 25.1044 Å for a loading of 40 mol/ u.c., and a ) 25.0505 Å for the loading equal or larger than 60 mol/u.c. In zeolite Y, the cell side was set equal to the experimental value27 a ) 24.85 Å. As the thermal expansion of zeolites X and Y in the simulated temperature range is very small,29,30 in the simulations at different temperatures the cell side was left unchanged.

The simulation boxes, including 576 framework atoms in both zeolites, differed for the content of Na cations (88 cations in zeolite X14 and 56 ones in zeolite Y27 respectively, whose charges compensated a corresponding number of Al atoms substituted to Si atoms) and for the number of water molecules (20, 40, 60, 120, 150 200, and 250 per unit cell both in zeolites X an Y). Starting water molecule coordinates were derived from experimental structures, when available,14 and, especially at high loading, by a docking procedure ensuring that the distance of the oxygen atom of any added molecule from another oxygen atom (belonging to the framework as well as to a different water molecule) was larger than 3 Å. For each water content (or loading), the simulations were carried out at least at three different temperatures, in the range 330-770 K, to compare the computed diffusion coefficients with the experimental data and to evaluate the activation energies. The simulations, in NVE ensemble, lasted 1.6-18 ns, depending on the loading and temperature. Overall, a simulation was continued until the mean linear displacement (MLD, the square root of the mean square displacement, MSD) overran the cell dimensions and the trend of MSD versus time was unambiguously linear. Actually, MLD range was about 25-80 Å. MLDs larger than the simulation box dimensions can be obtained by computing the coordinates of the particles without reducing them to the original box. If a particle crosses the box wall, its position is ascribed to an adjacent box (ref 17). The time step was 0.5 fs to represent the water molecule vibrations with sufficient accuracy. The details of the simulation features are reported in Tables S2 and S3 of the Supporting Information. To simulate flexible water molecules, a sophisticated electric field-dependent empirical model19 developed in this laboratory

12376

J. Phys. Chem. C, Vol. 113, No. 28, 2009

Demontis et al.

was adopted. The flexibility of water molecules was needed to reproduce the deformation of the water molecule geometry in zeolites and the corresponding changes of the vibrational spectra, which will be discussed in a forthcoming article. To include lattice deformations and vibrations in the simulated system, a flexible zeolite framework model developed in this laboratory as well18,23 has been used. It was further improved to evaluate the behavior of water in zeolite Na A, and the modified model is reported in the supporting information in ref 24. The charges assigned to the framework atoms were: 1.0 e for Na, -1.001 e for O both in zeolite X and Y, and 1.76 e (1.89 e) for Si and 1.288 e (1.274 e) for Al in zeolite X (zeolite Y). The choice of flexible framework and of performing simulations in NVE ensemble is aimed to ensure a correct evaluation of the diffusion coefficients31 but it sometimes entails a drift of the computed temperature due to round-off numerical errors. This drift can reach a few percent at the highest temperatures but in any case the diffusion coefficients can be evaluated at a given temperature through Arrhenius law fitting. The evaluation of the Coulomb energy was performed using the efficient method proposed by Wolf et al.32 and extended in our laboratory to complex systems.33 The cutoff radius was Rc set equal to one-half of side of the simulation box, corresponding to one unit cell and, correspondingly, the damping parameter was R ) 2/Rc. The structural quantities and the diffusion coefficients were evaluated from the MSDs using standard methods17,21 and the activation energies were derived according to the Arrhenius equation. 4. Results and Discussion a. QENS experiments. Some of the QENS spectra obtained in NaX for different water loadings, at 350 K, are shown in Figure 3. The time scale accessible in this work ranges between 1 and 10 ns. Because the correlation times for local motions of water, flips, or rotations, are much shorter, 1-100 ps, any quasielastic broadening due to these motions will look perfectly flat in our narrow energy domain, after Fourier transform.26 The broadenings that are observed are thus only due to the translational motion of water. It appears from Figure 3 that the broadening is the smallest at the lowest concentration, which indicates a lower water mobility. The individual spectra could be fitted with a Lorentzian function, corresponding to the diffusion motion, numerically convoluted with the instrumental resolution. The HWHMs of the Lorentzian functions were then plotted as a function of Q.2 An example is shown in Figure 4 for the same water concentration in the two zeolites, at 300 K. The widths obtained in NaY are larger, which means that water diffusivity is larger. The variation of the HWHMs is characteristic of a jump diffusion process with a distribution of jump lengths.26 All of the spectra obtained at the different Q values could thus be fitted simultaneously with this model. The calculated HWHMs are in good agreement with the broadenings of the individual spectra. It can be noted that, at small Q values, corresponding to length scales larger than the supercage-tosupercage distance, all jump diffusion models coincide so that the water diffusivities are model independent. b. MD simulations. Before performing the extended simulations yielding diffusion coefficients, the structural and vibrational properties of zeolites X and Y at different degrees of hydrations were studied. The detailed results will be reported elsewhere, but, in summary, the computed quantities reproduced satisfactorily the experimental data. In particular, the error bounds of mean coordinates were on the order of 0.1 Å, those of vibrational frequencies were a few percent, and those of adsorption energies

Figure 3. (Color online) Comparison between experimental (crosses) and calculated (solid lines) QENS spectra obtained at the same temperature, 350 K, for various water loadings in NaX: (a) 60, (b) 120, and (c) 200 molecules per u.c. (Q ) 0.27 Å-1).

Figure 4. (Color online) Broadenings derived for a concentration of 120 water molecules per u.c., at 300 K, in the two zeolites: (b) NaY, (9) NaX. The different points correspond to individual fits of the spectra, the solid lines to simultaneous fits with a jump diffusion model.

were within about 10% of the experimental data. However, in the long runs performed to evaluate diffusion coefficients, by checking the distribution functions of the coordinates, we noticed an increasing lack of the original crystal symmetry of the framework for increasing water content and for increasing temperature but without loss of the bond connectivity. This finding is in line with the experimental results reported in ref 14, where it was found that, at room temperature, for a loading of 120 molecules/u.c., the diffraction pattern could not be indexed in the space group Fd3j, which indicates the formation of at least one new phase, entailing a deformation of the

Diffusion of Water in Zeolites NaX and NaY

Figure 5. (Color online) Activation energies for diffusion of water. Filled squares (black): NaX, experimental (QENS); open squares (blue): NaX, calculated; filled diamonds (red): NaY, experimental; open diamonds (olive): NaY, calculated. The lines are guides to the eye.

framework. It is plausible that a similar deformation occurs also in zeolite Y. This problem will be discussed in a separate publication. Na cations were never observed to diffuse at the time scale of the simulations (some nanoseconds), their maximum MSD being on the order of 1 Å, even at the highest temperatures and loadings. As the diffusion of Na cations is an activated process, if the energy barrier for diffusion is so high that no diffusive event occurs during the simulations, it is not possible even to guess the diffusion coefficient order of magnitude. The simulations of the diffusive properties of water at different temperatures and loadings yield the values of the diffusion coefficients, from which the activation energies for diffusion can be derived by applying the Arrhenius law. This law was strictly obeyed in the explored temperature ranges and for all considered loadings, except for the lowest loadings and the highest temperatures (above 600 K). At very low loadings, the energy barriers are high, so that the diffusivity is very low and the statistics of the diffusive jumps are poorer, in spite of the remarkable duration of the trajectories. At high temperature, the diffusion mechanism can be slightly different from that at lower temperatures because the phase space regions accessible to the diffusing molecules may become larger.34 In Figure 5 and in Table S1 of the Supporting Information, the activation energies for diffusion are reported along with the experimental ones. The calculated values are overestimated by about 10% for both zeolites X and Y, a reasonable result, showing that the potential is sufficiently accurate. The activation energies at any loading are higher in zeolite X than in zeolite Y because of the larger number of Na cations interacting with the adsorbed water. In Figure 3, an anomalous peak appears for both zeolites, at 60 molecules/u.c. and another peak, for zeolite X only, at 150 molecules/u.c. Their origin will be discussed below, after considering the trend of the calculated diffusivity. The computed diffusion coefficients, along with the experimental ones are reported in Figures 6, 7, and 8 at three selected temperatures (350, 400, and 450 K, for which experimental data are available) and in Tables S2 and S3 of the Supporting Information at all considered loadings and temperatures. The trend of the calculated diffusion coefficients versus the water content can be assigned to the type IV diffusivity according to the classification proposed by Ka¨rger and Pfeifer.35 The type IV diffusivity is very low at low loadings, grows and reaches a maximum at intermediate loadings, and finally decays to zero when the loading approaches saturation. In Figure 6, it appears that at 350 K the computed diffusion coefficients are close to the experimental ones in both zeolites for a loading of 60 molecules/u.c., whereas for higher loadings

J. Phys. Chem. C, Vol. 113, No. 28, 2009 12377

Figure 6. (Color online) Diffusion coefficients as a function of loading, at 350 K. Symbols as in Figure 5. In adddition: filled circles (wine) NaX, experimental (PFG NMR, ref 35).

Figure 7. (Color online) Diffusion coefficient as a function of loading, at 400 K. Symbols as in Figure 5.

Figure 8. (Color online) Diffusion coefficient as a function of loading, at 450 K. Symbols as in Figure 5.

they remain well reproduced in zeolite X but in zeolite Y the computed diffusion coefficients are approximately twice the experimental ones. In all cases, both experimental and computed diffusivities in zeolite Y are larger than in zeolite X, as it should be expected because of the smaller number of Na cations accessible to water molecules present in zeolite Y, entailing a smaller hydration energy. At 400 K and at 450 K (Figures 7 and 8) similar trends are observed. Pulsed field gradient nuclear magnetic resonance (PFG NMR) experimental data of diffusion coefficients for water in zeolite NaX at 298 K and at different loadings are reported in ref 35. By assuming an activation energy of 20 kJ/mol (Figure 5 or Table S1 of the Supporting Information), the value of the diffusion coefficients at 350 K can be estimated, and as a result they are close to both the QENS and the MD values, as it appears in Figure 6. The nice agreement of the values obtained by the three techniques (PFG NMR, QENS, and MD), so different in nature, is unusual and gratifying. On the contrary, for instance, for the diffusion of water in zeolite Na A there are marked differences between PFG NMR and QENS results.36 The errors of the computed diffusion coefficients correspond to the linear fit errors for the calculations performed at a given temperature and to those derived from the linear fit of the activation energies for the values extrapolated using the Arrhenius law. The last ones are larger, and probably are closer to

12378

J. Phys. Chem. C, Vol. 113, No. 28, 2009

the real statistical errors of the computed values, as it is obtained by series of computed values. Overall, also in view of the estimated errors, the agreement between simulations and experiments is reasonable. At all temperatures, the trend of the diffusion coefficients versus the loading in zeolite Y shows a minimum at 60 molecules/u.c., corresponding to a maximum of the activation energy. Unfortunately, there are no experimental data available below this loading. As this anomaly occurs at different temperatures, it is hardly caused by a numerical error, even if the height of the peak is smaller than the error bar. One can suppose, tentatively, that the activation energy maximum would correspond to the saturation of the available coordination sites of water. Indeed, unless the coordination ability of the cations is exceeded, water molecules remain close to the cations and from time to time jump and coordinate to the adjacent cation because the cation-water interaction energy is much larger than the weak hydrogen bonds with the framework oxygens. In our model of zeolite NaY, there are 32 Na cations accessible to water molecules able to diffuse (some of them are trapped in the smaller cages and do not diffuse at ordinary temperature, as it occurs in zeolite Na A24), with a maximum of two coordinated water molecules each (also ref 24) so that to diffuse a water molecule finds hardly a close coordination site and the activation energy shows a maximum at about 60 molecules/ u.c. At higher loadings, the extra water molecules cannot coordinate to the cations and are hydrogen bonded to other ones or to the framework oxygens, and find a lower energy barrier to diffuse. The diffusivity therefore increases with the loading until the crowding of the water molecules in the supercages begins to hinder the diffusive process. In zeolite X, the phenomenology is more complex. In Figure 5, one observes a maximum of the activation energy at 60 molecules/u.c, corresponding to that found in zeolite Y, but at the same loading no minimum of the diffusivity appears, probably because the absolute value of the diffusion coefficient is very small and the minimum is overwhelmed by the steeply increasing trend of the diffusivity. At 150 molecules/u.c., we found another maximum of the activation energy, entailing a minimum of the diffusivity at 350 K (Figure 6) and a sharp maximum at 450 K (Figure 8). It is probable that it corresponds to a sort of saturation of the adsorption sites, such as the filling of the first layer of water molecules on the cage surface. In zeolite Na A,24 this kind of filling occurs for 152 molecules/u.c. (184 molecules/ u.c. including the molecules adsorbed in sodalite cages), but in the R-cage of zeolite Na A water is adsorbed also near the center of the windows connecting adjacent cages, whereas in zeolites X and Y the windows are larger and this kind of adsorption does not occur. c. General Discussion. The comparison between the results of the simulations and the experimental data can be considered as overall satisfactory, by considering the use of empirical potentials and classical mechanics simulations. In particular, activation energies for the diffusive process are in close agreement with experiment but the small differences entail large discrepancies in the values of the computed diffusion coefficients, which depend exponentially on the activation energies. One could attempt to further optimize the water-cation and water framework interactions but the analytical form of the interactions should be changed. The model used in this work performed reasonably well for describing the behavior of water in zeolite Na A,24 although the computed diffusion coefficients, which will be reported in an article in preparation, are underestimated with respect to the QENS data.36 Nevertheless, the water diffusivities derived from QENS are on the same order

Demontis et al. of magnitude of those reported in the present article, while somewhat smaller, in spite of the slightly lower values of the activation energies: 16 kJ/mol for 5 molecules per cage (40 molecules per u.c.), and 12 kJ/mol for 15 molecules per cage(120 molecules per u.c.). On the other hand, the Arrhenius equation includes a preexponential factor depending on the probability of the process, specifically of the diffusive jumps, which is different in zeolite A and in zeolites X and Y, due to the different structure of the cavities and the different number and configuration of the cations. In other words, the value of the diffusion coefficient depends not only on the activation energy but also on the diffusion mechanism. It is interesting to compare the results obtained in the present work with those derived by previous simulations in dealuminated zeolite Y.25 The considered loading range was 2-20 molecules/ u.c., the highest loading corresponding to the lowest one reported in the present work. For this loading and at 400 K, the computed diffusion coefficient is about 10-8 m2s-1, 2 orders of magnitude larger than the value both measured and computed in the present work for zeolite Y, and in the considered loading range one obtained type I diffusivity according to the classification proposed by Ka¨rger and Pfeifer.35 The type I diffusivity decreases monotonically from a maximum at very low loading to zero at some higher loading. These large discrepancies are not surprising by considering the different nature of the adsorption in ordinary and dealuminated zeolites. Indeed, dealuminated zeolites are essentially hydrophobic, because the water-framework interactions are weaker than the water-water ones, and the diffusivity is much larger than that in ordinary zeolites containing exchangeable cations to which water molecules are coordinated by large electrostatic forces. Moreover, in dealuminated zeolites the diffusivity decreases versus the loading because the water molecules tend to aggregate in clusters, which become more stable and larger as the loading increases. On the contrary, when the cations are present, the water molecules coordinated to the ions are helped by the collisions with the surrounding molecules to overcome the energy barrier for the diffusive jump, and this mechanism is the more efficient as the number of the adjacent molecules is higher, so that the diffusivity increases with the loading until the steric hindrance forces it to decrease. 5. Conclusions QENS and classical MD simulation techniques were used to investigate the diffusion of water contained in the cages of zeolite X and Y. The largest measured values of the diffusion coefficients are 1 order of magnitude smaller than those in bulk water because of the strong interactions of water with the exchangeable cations present near the surface of the zeolite cavities, which hinders the jumps of the molecules from a preferred position to the adjacent ones. For the same reason, the diffusivity is slightly lower in zeolite X than that in zeolite Y, which contains a smaller concentration of cations. The trend of the calculated diffusion coefficients versus the water content can be assigned to the type IV diffusivity according to the classification proposed by Ka¨rger and Pfeifer,35 which is very low at low loadings, grows and reaches a maximum at intermediate loadings, and finally decays to zero when the loading approaches saturation. The MD simulations, in spite of the use of empirical potential models and classical mechanics equations, were able to yield activation energies close to the experiment and diffusion coefficients following the same trend as the experimental ones,

Diffusion of Water in Zeolites NaX and NaY of the same order of magnitude but overestimated, in particular in zeolite Y. In addition, from these results some suggestions about the details of the diffusion mechanism may be inferred. Acknowledgment. The neutron experiments were performed at the Institut Laue-Langevin, Grenoble, France, using the IN10 spectrometer; we thank Dr. L. Van Eijck for his help during the measurements. This research is supported by the Italian Ministero dell’Istruzione, dell’Universita`, e della Ricerca (MIUR), PRIN funding, by Universita` degli studi di Sassari and by Istituto Nazionale per la Scienza e Tecnologia dei Materiali (INSTM), which are acknowledged. This work makes use also of results produced by the Cybersar Project managed by the Consorzio COSMOLAB, a project cofunded by the Italian Ministry of University and Research (MUR) within the Programma Operativo Nazionale 2000-2006 “Ricerca Scientifica, Sviluppo Tecnologico,AltaFormazione”perleRegioniItalianedell’Obiettivo 1 (Campania, Calabria, Puglia, Basilicata, Sicilia, Sardegna) Asse II, Misura II.2 “Societa` dell’Informazione”, Azione a “Sistemi di calcolo e simulazione ad alte prestazioni”. More information is available at http://www.cybersar.it. Supporting Information Available: Complete tables of computed and experimental activation energies and diffusion coefficients. This material is available free of charge via the Internet at http://pubs.acs.org. References and Notes (1) Angell, C. A. Science 2008, 319, 582–587. (2) Nagy, G.; Gordillo, M. C.; Gua`rdia, E.; Martı´, J. J. Phys. Chem. C 2007, 111, 12524–12530. (3) Cicero, G.; Grossman, J. C.; Schwegler, E.; Gygi, F.; Galli, G. J. Am. Chem. Soc. 2008, 130, 1871–1878. (4) Won, C. Y.; Aluru, N. R. J. Phys. Chem. C 2008, 112, 1812–1818. (5) Alexiadis, A.; Kassinos, S. Chem. ReV. 2008, 108, 5014–5034. (6) Breck, D. W. Zeolite Molecular SieVes, Structure, Chemistry, and Use; John Wiley & Son: New York, 1974. (7) Barrer, R. M. Zeolites and Clay Minerals as Sorbents and Molecular SieVes; Academic Press: London, 1978. (8) Introduction to Zeolite Science and Practice. In Stud. Surf. Sci. Catal. van Bekkum, H., Flanigen, E. M., Jacobs, P. A., Jansen, J. C., Eds.; Elsevier: Amsterdam, 2001; Vol. 137. (9) Gottardi, G.; Galli, E. Natural Zeolites; Springer-Verlag: Berlin, 1985.

J. Phys. Chem. C, Vol. 113, No. 28, 2009 12379 (10) Abrioux, C.; Coasne, B.; Maurin, G.; Henn, F.; Boutin, A.; Di Lella, A.; Nieto-Draghi, C.; Fuchs, A. H. Adsorption 2008, 14, 743–754. (11) Gueudre´, L.; Quoineaud, A. A.; Pirngruber, G.; Leflaive, P. J. Phys. Chem. C 2008, 112, 10899–10908. (12) Nicolas, A.; Devautour-Vinot, S.; Maurin, G.; Giuntini, J. C.; Henn, F. Microporous Mesoporous Mater. 2008, 109, 413–419. (13) Frising, T.; Leflaive, P. Microporous Mesoporous Mater. 2008, 114, 27–63. (14) Hunger, J.; Beta, I. A.; Bo¨hlig, H.; Ling, C.; Jobic, H.; Hunger, B. J. Phys. Chem. B 2006, 110, 342–353. (15) Olson, D. H. J. Phys. Chem. 1970, 74, 2758–2764. (16) Calestani, G.; Bacca, G.; Andeetti, G. D. Zeolites 1987, 7, 54–58. (17) Demontis, P.; Suffritti, G. B. Chem. ReV. 1997, 97, 2845–2878. (18) Demontis, P.; Suffritti, G. B.; Bordiga, S.; Buzzoni, R. J. Chem Soc., Faraday Trans. 1995, 91, 525–533. (19) Cicu, P.; Demontis, P.; Spanu, S.; Suffritti, G. B.; Tilocca, A. J. Chem. Phys. 2000, 112, 8267–8278. (20) Demontis, P.; Stara, G.; Suffritti, G. B. J. Phys. Chem. B 2003, 107, 4426–4436. (21) Demontis, P.; Stara, G.; Suffritti, G. B. J. Chem. Phys. 2004, 120, 9233–9244. (22) Demontis, P.; Stara, G.; Suffritti, G. B. Microporous Mesoporous Mater. 2005, 86, 166–175. (23) Demontis, P.; Gulı´n-Gonza´lez, J.; Suffritti, G. B. J. Phys. Chem. B 2006, 110, 7513–7518. (24) Demontis, P.; Gulı´n-Gonza´lez, J.; Jobic, H.; Masia, M.; Sale, R.; Suffritti, G. B. ACS Nano 2008, 2, 1603–1614. (25) Fleys, M.; Thompson, R. W.; MacDonald, J. C. J. Phys. Chem. B 2004, 108, 12197–12203. (26) Jobic, H.; Theodorou, D. N. Microporous Mesoporous Mater. 2007, 102, 21–50. (27) Fitch, A. N.; Jobic, H.; Renouprez, A. J. Phys. Chem. 1996, 90, 1311–1318. (28) van Bokhoven, J. A.; Lee, T.-L.; Drakopoulos, M.; Lamberti, C.; Thieβ, S.; Zegenhagen, J. Nat. Mater. 2008, 7, 551–555. (29) Attfield, M. P.; Sleight, A. W. Chem. Commun. 1998, 601–602. (30) Tucker, M. G.; Dove, M. T.; Keen, D. A. J. Phys.: Condens. Matter 2000, 12, L425-L430. (31) Smit, B.; Maesen, T. L. M. Chem. ReV. 2008, 108, 4125–4184. (32) Wolf, D.; Keblinki, P.; Phillpot, S. R.; Eggebrecht, J. J. Chem. Phys. 1999, 110, 8254–8282. (33) Demontis, P.; Spanu, S.; Suffritti, G. B. J. Chem. Phys. 2001, 112, 8267–8278. (34) Yashonath, S.; Demontis, P.; Suffritti, G. B. J. Phys. Chem. C 2008, 112, 10730–10731. (35) Ka¨rger, J.; Ruthven, J. M. Diffusion in Zeolites and Other Microporous Solids; John Wiley and Sons: New York, 1992. (36) Paoli, H.; Me´thivier, A.; Jobic, H.; Krause, C.; Pfeifer, H.; Stallmach, F.; Ka¨rger, J. Microporous Mesoporous Mater. 2002, 55, 147–158.

JP901587A