Liquid Structure and Dynamics of Aqueous Isopropanol over -Alumina

Nov 25, 2009 - of Chemistry and Chemical Engineering, Queen's UniVersity, Belfast, BT9 5AG ... The liquid structures of thin films of aqueous solution...
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Liquid Structure and Dynamics of Aqueous Isopropanol over γ-Alumina T. G. A. Youngs,*,† D. Weber,‡ L. F. Gladden,‡ and C. Hardacre§ School of Mathematics and Physics, Queen’s UniVersity, Belfast, BT7 1NN, Department of Chemical Engineering and Biotechnology, UniVersity of Cambridge, Pembroke Street, Cambridge CB2 3RA, and School of Chemistry and Chemical Engineering, Queen’s UniVersity, Belfast, BT9 5AG ReceiVed: July 15, 2009; ReVised Manuscript ReceiVed: October 24, 2009

The liquid structures of thin films of aqueous solutions of 0, 7, 19, 50, and 100 mol % isopropanol above O/Al-terminated γ-alumina 〈001〉 surfaces have been investigated by means of classical molecular dynamics simulations. The structuring effect of the oxide on the liquid mixtures is strong and heavily dependent on the local structure of the oxide. Two distinct regions are found on the oxide surface characterized by the degree of coordination of Al atoms. Above octahedral Al atoms, water and isopropanol molecules adsorb via the oxygen atoms to maximize the electrostatic interaction, whereas above tetrahedral Al sites the solvent molecules adsorb via hydrogen atoms with the oxygen atoms away from the surface. More mobility is found in the second layer compared with the first; however, its structure is still influenced significantly by the orientation of molecules in the first adsorbed layer. Qualitatively, the displacement of water from the surface by the adsorption of isopropanol occurs with 2.6 water molecules lost for every alcohol molecule present based on the effective surface areas of the two species calculated from the pure simulations. Diffusion in the liquid has been investigated by both molecular dynamics and PFG-NMR studies. Both show that the first adsorbed layer is slower moving than the bulk by several orders of magnitude, as expected, and thereafter the simulations show a gradual increase in diffusivity with increasing distance from the interface, tending toward the bulk value. Experimental diffusion coefficients of isopropanol inside the γ-alumina pore are found to be approximately one-quarter of that found in the bulk liquid. When compared with the simulated values, this suggests that the surface properties probed by the NMR technique encompass the first two layers interacting with the surface. In addition, because of the time scale of the measurements, the largest diffusion coefficient obtained includes the pore tortuosity and, therefore, a reduced experimental value is found compared with that obtained from the simulations. Introduction Understanding the solid-liquid interface is of considerable importance in many biological, physical, and chemical processes, for example in cell adhesion, seeding of crystal growth, and catalysis. To date, much effort has been concentrated on experimental investigations of these systems but such studies are often hampered by the fact that the interfacial region accounts for only a small proportion of the total system size, which is difficult to differentiate from the bulk material. Simulation techniques are able to selectively examine the interfacial region and have been used in the interpretation of experimental data as well as in a purely predictive role. However, depending on the nature of the solid and the liquid, the scope of possible simulations may be restricted. If the interactions between the surface and the liquid molecules result in a physisorbed layer, then molecular dynamics simulations with classical potentials can treat surface areas of up to 100 nm2, with thousands of liquid molecules accounted for over time scales on the order of hundreds of picoseconds. This is often the case when the substrate is an unreactive oxide, where electrostatic forces predominate. Contrastingly, metallic systems cannot, in general, be treated well by classical potentials, forcing * To whom correspondence should be addressed. E-mail: t.youngs@ qub.ac.uk. † School of Mathematics and Physics, Queen’s University. ‡ Department of Chemical Engineering and Biotechnology, University of Cambridge. § School of Chemistry and Chemical Engineering, Queen’s University.

the use of more expensive ab initio methods over much smaller surface areas and numbers of molecules, and the dynamical evolution of systems is often not considered. Whereas these calculations are electronically accurate, they may neglect cooperative effects in the liquid phase, which arise, for example, in fluids where the molecule-molecule interactions are strong, for example hydrogen bonding liquids such as water and alcohols. A significant number of studies focus on the ab initio treatment of single reactant/solvent molecules adsorbed on metallic surfaces1 and have proven extremely useful in the understanding of catalytic processes in terms of the energetics of adsorption, desorption, and the nature of the adsorbed transition state. However, it is not commonplace to include solvent molecules in the calculation owing to the significant increase in computational effort required, and few studies in the literature attempt such calculations.2 In contrast, classical molecular dynamics (MD) techniques allow large bulklike and interfacial systems to be studied but do not describe electronic processes such as bond-making and bond-breaking. Although the ability to properly describe interactions between metals and other species in classical MD is still a relatively young area, several continuous potentials have been derived that perform well, for example those developed for Pt/H2O by Nagy et al.3 and Jhon et al.4 Nevertheless, for oxide systems that can be considered effectively inert, and hence where electrostatic interactions between the surface and the liquid are the predomi-

10.1021/jp906677c  2009 American Chemical Society Published on Web 11/25/2009

Aqueous Isopropanol over γ-Alumina nant force behind the formation of the interfacial layer, classical molecular dynamics provide useful information. In this article, we examine the interfacial region between γ-alumina and aqueous isopropanol mixtures. Of the many different crystalline forms of alumina, γ-alumina is the most widely used in catalysis owing to its low cost, high mechanical strength, and high surface area. By contrast, it is also the leastcommon form studied by classical molecular dynamics, with few examples reported to date. Blonksi and Garofalini5 performed simulations of crystalline R- as well as γ-alumina using a modified Born-Mayer-Huggins potential and found excellent agreement with available X-ray data. Surface energies were also calculated for cuts made through several Miller planes. Alvarez et al. used a Pauling-type potential in studies of the surface structure and rearrangements of γ-alumina.6 The majority of computational and experimental studies have concentrated on the use of single solvent systems interacting with the oxide support; however, recently, reactions performed in mixed water/isopropanol solvents have been shown to enhance the activity of the catalyst for a number of hydrogenations. For example, Hu et al. examined the catalytic hydrogenation of 2-butyne-1,4-diol and found a complex trend in the reaction rate as a function of the ratio of water and propan-2-ol used. This could be rationalized by examining the changes in hydrogen solubility and the average gas bubble size formed as a function of the ratio of the solvent components.7 In addition, the role of water in a mixed water-isopropanol solvent system in the hydrogenation of butanone has been examined using experimental and theoretical techniques. The complex variation of reaction rate with solvent composition has been related to its effect on mass transfer rates, diffusion kinetics, and the mechanism for the hydrogenation.8 Although these studies provide some evidence for the effect of utilizing a mixed solvent system, it is not clear how the mixed solvent interacts with the catalyst surface compared with the pure solvent components. It is widely accepted that, although on the macroscopic scale the mixed propan-1-ol/water mixture may appear homogeneous, on the molecular scale aggregates of water and alcohol are found.9 Although this heterogeneity exists in the liquid state, it is important to examine whether this is found following the interaction with an oxide surface as this will significantly affect reaction mechanisms, rates, and selectivities. For example, recent work in our laboratory has shown that, by pretreating a catalyst with long-chain alcohols, it is possible to produce a significantly more hydrophobic surface, which prevents water adsorption on the catalyst.10 Therefore, an understanding of how mixed solvents interact with the surface is critical in achieving a feasible reaction mechanism in these systems. Herein, the structural influence on thin films of pure water and pure isopropanol of a γ-alumina surface, examining the microscopic orientational order imposed on the liquid in both cases, are reported. For aqueous isopropanol solutions, the influence of the alcohol on the exclusion of water from the interface is studied. Dynamics within the thin films are investigated both through simulation and PFG-NMR spectroscopy to provide cross validation and an understanding of the region that is probed experimentally. Methodology Simulation. Because γ-alumina is a defect spinel there is no well-defined crystal structure and no exact means to directly quantify it. In this respect, Paglia et al. investigated the occupancy of cations in the spinel position by examining 1.47 × 109 candidate structures.11 For the purposes of this work, a

J. Phys. Chem. C, Vol. 113, No. 51, 2009 21343 small-scale approximation was generated as follows. The lattice constant of the cubic subunit has been determined previously by Smrcˇok et al.12 and Zhou and Snyder,13 and this is used as the basic framework for the generation of the crystal. Initially, an oxygen lattice across the desired number of repeat units is generated, typically a 3 × 3 × 2 supercell of the crystal for the main production simulations. Aluminum atoms are added randomly into this framework at both tetrahedral and octahedral vacancies, performing a lattice sitelike Monte Carlo simulation until the desired populations are reached. The overall ratio Al:O is maintained at 2:3; however, the distribution of Al over the tetrahedral and octahedral sites of the crystal is not known exactly. Several computational studies have been reported to quantify the exact ratio Altet:Aloct within γ-alumina.11,14,15 In this work, a ratio of Altet:Aloct of 33:67 (i.e., 1:2) is used which is an average of the ratio of 37:63 reported in the X-ray study of Smrcˇok et al.12 and from NMR studies of 30:70.14 All simulations in this work consider interfaces between the Al/Oterminated 〈001〉 surface and the liquid. Once generated by the above method, the positions of all atoms in the surface are kept fixed for the duration of the simulation. The water model used is the SPC/E model16 because it is known to reproduce the structure well as well as the density of the bulk liquid, and this is our primary focus. Isopropanol was represented by the model of Kahn and Bruice17 based on the OPLS-AA framework. Cross-terms between water and isopropanol were generated using the standard Lorentz-Berthelot combination rules. A suitable potential model for interactions of the liquid components with the oxide was then considered. Given that the strongest interaction with the oxide is through the hydroxyl groups of the liquid components, parametrization focused on this aspect of the potential. Alumina is a relatively inert oxide and, therefore, it can be assumed that its interaction with the OH groups present in the liquid phase is likely to be predominantly electrostatic. Because it is undesirable to modify the charges in the water and alcohol models, modification of the interactions between surface and liquid molecules was restricted to the short-range part of the potential. A number of ab initio studies of the interaction of water with R-alumina have been reported and provide useful guidelines to the potential fitting. It is known that both dissociative and molecular adsorption occurs on the R-alumina surface;18 however, only the molecular case is considered in this study and bond-breaking/ making processes are not examined. This approximation is valid because it is known that a cooperative effect exists for strongly hydrogen-bonding fluids, which stabilizes against dissociative adsorption, as has been shown to be the case for MgO/H2O with water clusters containing four or more molecules.19 However, we note that the surfaces under consideration in the present study should be considered as idealized systems owing to the lack of surface hydroxylation. The oxide-water potential used, herein, is of the Lennard-Jones type, with parameters adjusted to reach a suitable compromise between energy and geometry possible given the limitations of using this particular functional form. First principles calculations of water adsorbed on R-alumina suggest the Al-O distances range between 1.93-2.05 Å and the bond energies range from 110-170 kJ mol-1.20-22 In addition, thermogravimetric analysis suggests an adsorption energy of around 150 kJ mol-1.23 Table 1 summarizes the parameters used in the present case and, using this potential zero-temperature minimizations of a single water molecule over a rigid 4 × 4 × 1 slab of R-alumina results in an Al-O distance of 2.099 Å, with the oxygen positions almost directly above the aluminum atom and one

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TABLE 1: Lennard-Jones Parameters Employed for the Interaction between γ-Alumina and Water/Isopropanola interaction

σ, Å

ε, kJ mol-1

O/H* O/C* Al/O* Al/HC Al/C*

2.8 3.0 2.6778 3.0 3.0

0.650 0.650 0.650 0.650 0.650

a

Oxygen ‘O’ refers to the oxide, whereas ‘O*’ refers to oxygen in water or isopropanol. All other parameters for the liquid molecules are as described in refs 16 and 17.

hydrogen atom tilted slightly along an Al-O vector at an angle θAl-O-H ) 117.15°. The strength of this interaction is 160 kJ mol-1, which is comparable to that determined using TGA and in the upper region of values calculated by ab initio studies. We make the reasonable assumption that the potential so derived is transferable to the γ-alumina system as well as from water to the alcoholic group of isopropanol. Pure water (650 molecules, 0 mol % isopropanol), mixtures of 124/124 water/isopropanol (50 mol % isopropanol) 325/76 water/isopropanol (∼19 mol % isopropanol) and 488/38 water/ isopropanol molecules (∼7 mol % isopropanol), and pure isopropanol (152 molecules, 100 mol % isopropanol) were examined. Slabs (3 × 3 × 2) of γ-alumina were generated with the lattice-site Monte Carlo method described above and random configurations of the various isopropanol solutions using the Aten software were added,24 followed by a region of vacuum to give an overall cell length in the z direction of 100 Å. The oxide dimensions in the x and y directions were fixed at ∼23 Å, which provides a large enough system to investigate the quantities of interest. No additional insight would be gained by consideration of larger oxide surface areas. To prevent vaporisation of the solvent during the simulations and maintain approximately the liquid density, a repulsive potential wall was applied in the z direction at the open end of the liquid. Molecular dynamics simulations were performed with the DL_POLY 2.17 software,25 modified to incorporate the YehBerkowitz correction to account for the presence of overall dipoles in the system and enable the calculation of 2D periodic systems correctly using the standard 3D Ewald technique rather than the computationally demanding 2D variation.26 The shortrange cutoff was set to 11.5 Å, and the Ewald sum was calculated over 16, 16, and 64 k vectors in the x, y, and z directions respectively with R ) 0.313964. Preliminary energy minimizations were conducted at small timesteps (from 1.0 × 10-7 to 1.0 × 10-4 ps) and a preparation run of 200 ps was made at a time step of 1.0 × 10-3 ps which was discarded ahead of the main production runs. Simulations of 6 ns length were generated with a time step of 1.0 × 10-3 ps, and for each concentration of isopropanol three separate simulations are conducted, each from a different starting configuration of both the liquid and the oxide to reduce any bias arising from initial conditions. The NVT ensemble was used throughout with a temperature of 300 K and thermostat relaxation time of 0.1 ps. Experimental Section. γ-Al2O3 3 mm support pellets were obtained from Johnson Matthey (Batch No. DM00102) and dried in an oven for at least 12 h at 120 °C prior to liquid imbibition. Three samples were prepared for pulsed field gradient NMR diffusion measurements: (1) a sample of γ-alumina pellets and pure deionised water (>15 MΩ); (2) a sample of γ-alumina pellets and a mixture of 19 mol % isopropan(ol-d) (C3H7OD, Sigma Aldrich 98% atom purity) in deuteriated water (D2O, 99+ % atom purity); (3) A sample of γ-alumina pellets and

Youngs et al. pure 2-propanol (Sigma Aldrich 99+% purity. Isopropan(ol-d) is used with D2O in sample 2 to ensure that the PFG-NMR measurement is assigned, unambiguously, to 1H resonances from the CH3 groups of the isopropan(ol-d) alone and is not contaminated by residual protonated -OH groups, which may undergo isotopic exchange. Approximately 5 g of pellets were soaked in the respective liquids (1-3) for 12 h prior to the measurement. Prior to any NMR experiments, the excess liquid was removed from the pellet external surface by contacting the pellets with filter paper (Whatman No. 1) presoaked in the respective liquid (to prevent liquid being removed from within the pores of the pellets). The soaked pellets were then transferred to 10 mm NMR tubes (Wilmad Glass Co.). It should be noted that, to investigate the influence of support preparation on the measured pore and surface diffusivities, the support was also used without pretreatment, that is not oven-dried, in the assessment of pore and surface diffusivities for pure isopropanol. No significant differences in the measured diffusivities were observed between these cases. All PFG NMR experiments were conducted at 25 °C and performed on a Bruker Avance DMX 300 spectrometer tuned to a resonance frequency of 300.13 MHz using the 13-interval alternating pulsed field gradient stimulated echo (APGSTE) pulse sequence.27 This approach reduces the effect of background magnetic field gradients by reversing the phase shift generated by them over a time 2τ1 where 2τ1 is the time between application of the first and second 90° pulses and also the third 90° pulse and the echo acquisition. Provided 2τ1 , ∆, the effective diffusion time, the equation describing how the signal attenuation (I/I0) varies as a function of the experimental parameters is written:

I ) exp(-γ2g2δ2(∆ - τ1 /2 - δ/12)D) I0

(1)

where γ is the gyromagnetic ratio of the nucleus of interest (1H), and g and δ are the applied magnetic field gradient strength and the duration of this gradient pulse, respectively. If more than one diffusion coefficient is present, eq 1 is rewritten as:

I ) I0

∑ pi exp (-γ2g2δ2(∆ - τ1/2 - δ/12)Di)

(2)

i

where Di is the diffusion coefficient of population i, and pi is the relative population. For convenience, γ2g2δ2(∆ - τ1/2 δ/12) is defined as parameter b. Thus, for eq 1 if the log of the signal attenuation is plotted as a function of b, then the diffusion coefficient is given by the gradient of the plot. Experimental parameters used in the present study were: effective diffusion time, ∆ ) 10 ms; duration of the gradient pulse, δ ) 1 ms; maximum gradient strength, g ) 1000 G cm-1; and recycle time ) 1 s. The effective diffusion time of 10 ms was chosen to maximize the signal-to-noise ratio in the acquired data sets. The number of scans acquired varied depending on the value of b being studied. For low b values, 128 scans were acquired, whereas at the highest values of b, 4096 scans were acquired. For a complete data set as shown in Figure 1, data acquisition times were on the order of 24 h. Figure 1 shows the log-attenuation plot for the 19 mol % IPA in D2O mixture within γ-Al2O3 pellets. The data demonstrate how different numbers of scans are acquired for different ranges of b values, this being required to give adequate signalto-noise throughout the entire data set. All data sets acquired were of this form. As can be seen from eq 2 as b f 0, the gradient will approach the diffusion coefficient of the fast

Aqueous Isopropanol over γ-Alumina

J. Phys. Chem. C, Vol. 113, No. 51, 2009 21345 TABLE 2: Populations of Molecules (N) in the Observed Liquid Layers of the Pure Water and Pure Isopropanol Systems, as Inferred by the Presence of the Molecule’s Center-of-Geometry within z Limits Defined from the Density Profiles in Figure 2a

Figure 1. Log-attenuation plot for the 19 mol % IPA in D2O mixture in porous γ-alumina pellets. The signal is acquired from the IPA only. At high attenuation, an increased number of scans were acquired to improve signal-to-noise and the data were subsequently scaled by the number of scans before plotting: (•) 128 scans, (×) 512 scans, ([) 1024 scans, and (+) 4096 scans. The two limiting gradients yield measurements of the bulk-pore diffusion (as b f 0) and the diffusion of a strongly surface-influenced spin population (large b).

Figure 2. Un-normalized z-density profiles for water and isopropanol centers-of-geometry in the pure water (a) and pure isopropanol (b) simulations (solid lines). Cumulative molecule populations as a function of z are shown as dotted lines. Forcefield values for the bulk density for both liquids in the absence of a surface are represented by horizontal dashed lines. Different colored lines represent individual simulations beginning from different initial configurations of the liquid.

diffusing species, D1, when p1 . p2. At large values of b, signal from population p1 is heavily attenuated and the gradient tends to the value D2. It therefore follows that the bulk-pore and surface diffusion coefficients are determined from the gradients as b f 0, and large b where the gradient tends to a constant minimum value, respectively. A more detailed discussion of this analysis and extension of the experimental to probe the effect of a range of effective diffusion times can be found elsewhere.28 Results and Discussion Populations of Adsorbed Layers. Figure 2 shows the unnormalized z-density profiles of water and isopropanol in the pure water and pure isopropanol systems and Table 2 lists the integrations of the peaks. In all cases, the z density is calculated relative to the first fixed oxide layer to allow a quantitative comparison between the systems studied. For the pure water case, the density profile displays a sharp initial peak at 2.1 Å

mol % IPA/layer

zlayer,

δz, Å

0/1a 0/1b 0/2 0/3 (not layer) 100/1 100/2 100/3

1.0-2.3 2.3-3.5 3.5-5.9 5.9-8.9 1.0-5.0 5.0-10.0 10.0-14.0

1.3 1.2 2.4 3.0 4.0 5.0 4.0

N 33.6 33.5 48.9 56.2 24.9 21.1 20.0

(1.4) (1.1) (4.7) (1.5) (0.8) (0.3) (0.4)

F, g cm-3

Npure

1.42 (0.01) 47.39 0.99 1.01 1.10 0.74 0.88

(0.03) (0.01) (0.03) (0.01) (0.02)

45.50 56.87 17.85 22.31 17.85

a The number of molecules expected for the same volume in an isotropic system of the pure liquid (Npure) at normal densities is given for comparison (F ) 1.000 and 0.785 for water and isopropanol, respectively). Standard deviations are given in brackets.

and a smaller peak at 2.4 Å, both of which arise from the strongly adsorbed first layer in direct contact with the surface, as has been observed for many other water/oxide systems.29 Integration of the curves shows an average population of 67 water molecules, equating to a surface area of 8.46 Å2 molecule-1 (or a coverage of 0.118 molecules Å-2). In the second of the three separate runs, a minor prepeak is found at 1.7 Å (red curve in Figure 2), which is absent in the other two. This feature is related to surface defects in the form of adjacent Aloct vacancies, allowing some water molecules to approach the surface closer than might be expected. A further consequence of this is the appearance of a small peak at 5.0 Å in the z-density profile, suggesting liquid structuring at greater distances than was observed for the surfaces used in the other simulations. Clearly, even small differences in the character of the surface are able to promote significant changes in the structure of the adjacent liquid. Assuming that 1.0 < z < 3.5 Å represents the volume accessible to the water near the surface, that is the first minimum in the z-density profile (Figure 2), for the bulk liquid the same volume would hold ∼47 molecules compared with 67 molecules for the surface adsorbed layer indicating a significant concentrating effect of the liquid at the surface. Contrastingly, in the second layer and beyond the densities are close to that of the bulklike regions, indicating that the majority of the influence of the surface in this system is localized to the first layer. Similar features were noted by de Leeuw and Parker for water over MgO.30 Whereas there is considerable orientational order present in the molecules at the surface, this does not significantly affect the density of subsequent layers despite any perturbation of packing in these layers. The pure isopropanol simulations show stronger structuring into the liquid with oscillations visible out to the fourth and fifth layers at 20 Å from the surface. The additional flexibility and sterics of isopropanol compared with water frustrate packing close to the surface and reduce the possible population of molecules in the first adsorbed layer significantly. In this case, integration of the z-density profile leads to ∼25 molecules in the first layer equating to a surface area of 22.69 Å2 molecule-1 (or coverage of 0.044 molecules Å-2), that is approximately three times that for water. As a result of the orientation of the isopropanol molecules (discussed later) providing a hydrophobic surface covering, the subsequent layering of isopropanol is more well-defined than that observed for pure water. Subsequent peaks for the second, third, and fourth layers occur at approximately 5 Å intervals, which is comparable to the bulk liquid whose center-of-geometry radial distribution function contains a doublet

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Youngs et al.

Figure 3. Un-normalized z-density profiles (solid lines) for water (a) and isopropanol (b) centers-of-geometry in the 7 mol % (top panels), 19 mol % (middle panels), and 50 mol % simulations (bottom panels). Cumulative molecule populations as a function of z are shown as dotted lines. Different colored lines represent individual simulations beginning from different initial configurations of the liquid.

main peak at 4.5 and 5.5 Å (Figure S1 of the Supporting Information). These results, along with those for pure water, are consistent with those over a pure metal surface performed by Tarmyshov and Mu¨ller-Plathe.31 They observed that the layering effect imposed on water persisted only to the third layer, whereas for isopropanol up to eight distinct layers were found. Despite the marked differences in the strengths of interactions with the surface, the effect of having an oxide or metal surface is the same - strong orientational order is imposed on the first layer, which imposes some degree of structuring in subsequent layers. However, the effect of the type of surface on the dynamics is more distinct, as will be discussed later. In the examination of the mixtures of isopropanol and water, care must be taken in the literal interpretation of these results because the populations at the surface are more or less directly influenced by the starting configuration of the liquid - in other words the molecules sitting near the interface at the beginning of the simulations are likely to remain there for the duration of the simulation. Nevertheless, the relative change in populations of the two components provides insight on the drying properties of isopropanol, and, more importantly, the influence upon structure and population of species away from the surface may be examined. Figure 3 shows the un-normalized z-density profiles of the centers-of-mass for water and isopropanol in the 7, 19, and 50 mol % isopropanol systems and Table 3 summarizes the calculated populations for water and isopropanol integrated within the first adsorbed layers as defined by the first minimum in the z-density profile. From the surface area coverage per molecule calculated from the pure water and isopropanol systems, it might be expected that the presence of a single isopropanol molecule adsorbed on the surface would

TABLE 3: Populations of Water (Nwater) and Isopropanol (NIPA) in the First Adsorbed Layer for the Mixed Systemsa mol % IPA/run

NIPA

Nwater

Rexpected

Robserved (diff)

7/1 7/2 7/3 19/1 19/2 19/3 50/1 50/2 50/3

1.03 2.70 2.76 6.00 3.98 4.98 11.46 16.99 12.81

65.75 62.95 64.76 51.29 52.78 54.20 45.19 29.01 40.29

2.78 7.23 7.41 16.10 10.67 13.36 30.70 45.58 34.37

1.29 (-1.49) 4.09 (-3.14) 2.29 (-5.12) 15.75 (-0.35) 14.26 (3.59) 12.84 (-0.52) 21.85 (-8.85) 38.03 (-7.55) 26.75 (-7.62)

a Expected number of removed water molecules from the surface layer (Rexpected) are calculated based on number of isopropanol molecules in the adsorbed layer and their equivalent surface coverage determined from 100 mol % simulations, whereas the observed number of remove water molecules (Robserved) is the difference between the average population in the 0 mol % simulations and observed total population in the mixed system (Nwater).

displace three water molecules because the equivalent surface area per molecule for isopropanol is just under three times that for water (22.69 vs 8.46 Å2). Taking into consideration the influence of the starting configuration in these simulations and the associated error in the calculated populations, we may consider that the 7 and 19 mol % simulations follow more or less this prediction. However, for the 50 mol % simulations it seems more certain that there are more water molecules present at the interface than would be expected for the observed number of isopropanol molecules. Microscopic Structure of Adsorbed Layers. Figure 4 illustrates the average distribution of water molecules and their orientation as a function of position over the surface in the first

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Figure 4. Microscopic structure of the interfacial region in the pure water systems, showing the structure of the topmost oxide surface layers (a) and the averaged value of pz for water molecules in the first (b) and second (c) layers as a function of position over the surface. For (b) and (c), solid red indicates the water oxygen pointing toward the surface (pz f +1), solid blue indicates water oxygen pointing away from the surface (pz f -1), and white regions indicate no water molecules observed at this position. The areas highlighted correspond to octahedral (1) and tetrahedral (2) surface aluminum atoms.

and second layers. Part a of Figure 4 shows the two oxide layers closest to the liquid, which may be thought of as alternating rows of octahedral and tetrahedral Al running in the 〈110〉 direction, as shown in Figure 5. Two regions are marked in part a of Figure 4 to illustrate this; (1) in which there exist Aloct at the surface and (2) a channel of Altet. The orientation of a molecule relative to the surface is defined by the vector b p:

b p ) |b V1 + b V 2|

Figure 5. Isolated and unrelaxed 〈001〉 γ-alumina surface illustrating alternating rows of Aloct/Altet atoms at the surface in the 〈110〉 direction.

where b V1 and b V2 are normalized vectors originating from the oxygen atom (because this is the primary interaction site of both V2 are the two O-H water and isopropanol). For water, b V1 and b bond vectors, whereas for isopropanol the O-H and O-C vectors are used. In the latter case, quantifying the orientation

of the molecules over the surface is less well-defined owing to the bulky alkyl chain but the same interpretation of b p can be made. Because the surface is perpendicular to the z axis in the

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simulations, pz ) -1 indicates that the water molecule points with the oxygen away from (and hydrogens closer to) the surface, pz ) +1 indicates that the water molecule points with the hydrogens away from (and oxygen closer to) the surface, and pz ) 0 that the water molecule lays in a plane parallel to the surface, that is it has no orientational preference in the z direction. Part b of Figure 4 shows a contour map of the average value of pz as a function of position over the surface for the first layer of adsorbed water molecules, that is encompassing all molecules up to the position of the first minimum in the z-density profiles in Figure 2. A significant portion of the surface is dry, shown as white areas in the figure, where no water molecules are observed over the course of the simulation. The structuring effect of the oxide is considerable and highly selective, emphasized by the regular structural features of the surface running in the 〈110〉 direction. Where Aloct exist at the surface, as is the case in region 1 in part a of Figure 2, for example, the water molecules are oriented with oxygen atoms facing the surface giving rise to well-defined red spots in part b of Figure 4. These features are, in general, surrounded by an excluded volume over the surface within the same layer other water molecules do not penetrate. Parker et al. noted, on modeling oxide surfaces in water, that the predominant factor influencing bonding at the surface is the cation-water interaction but that this effect is mediated by the physical volume of the water itself.32 Correspondingly, an approximate surface area per associatively adsorbed water molecule of 10 Å2 was deduced, which may be compared with water in ice at 9.7-11.9 Å2. Here, a slightly lower value of 8.46 Å2 is found with a correspondingly higher adsorption energy of -160 kJ mol-1 compared with -99 kJ mol-1. These differences may be due to the composition of the surface oxide in each case or the geometry of the adsorbed species on the alumina versus the Mg2SiO4. Water molecules over isolated Aloct sites (or ones with fewer neighbors of a similar environment) are oriented with a positive pz, ranging from pz ∼ +0.5, where one O-H bond lies parallel to the surface to maximize the favorable electrostatic interactions between the O and Aloct and also H and a neighboring surface oxygen, to pz ) +1 where the hydrogens are furthest away from the surface. Similar features are observed for the adsorption of a single water molecule on R-alumina.18 For an oxide where the lattice oxygen spacing is roughly commensurate with that between molecules in the pure liquid state, as is the case for MgO and water, for example, the orientation and structure of the first adsorbed layer is more strictly defined than in the present case.33 Importantly, on γ-alumina, near-planar adsorption of water is disfavored because the cubic lattice structure at the surface disfavors such geometries owing to the Al-O distance (c.f. MgO). Hence, water molecules prefer to sit in nonplanar orientations and benefit from interaction with the rest of the bulk liquid. The cooperative effect of the bulk liquid alone is presumably not enough to force nonplanar adsorption because for MgO it has been shown that a second layer of liquid above adsorbed water molecules does not perturb significantly the planar arrangement.33 Above tetrahedral Al channels on the surface, for example region 2 in part a of Figure 4, water molecules are found, on average, to have one hydrogen pointing toward the surface. A bifurcated interaction exists between this hydrogen and two surface oxygens, one on either side of the channel, and with O · · · H distances between 2.4 and 2.6 Å. The second hydrogen of the water molecule points along the vector of the channel, approximately parallel to the surface, and may hydrogen bond to an adjacent water molecule in the same

Youngs et al. channel. In this way, chains of hydrogen-bonded water molecules in the same orientation may be found. In the second layer, part c of Figure 4, the orientation of water molecules is strongly coupled to those in the first adsorbed layer. For example, the water molecules in region 1 (part a of Figure 4) in the surface layer are strongly oriented with hydrogens pointing away from the surface, that is pz > +0.5, and this orientation is found to persist into the second layer. The greater mobility of the liquid in the second layer results in the regions being not as well-defined as in part c of Figure 4, but they are, nevertheless, clearly visible. Further increased motion in the third defined layer leads to the structure becoming even less well-defined but some memory of the first adsorbed layer is still present. It is worth discussing the second of the three pure water simulations in more detail because it is clear that the molecules in the adsorbed layer appear to be oriented differently from what is expected from the underlying oxide surface structure. The alternating 〈110〉 rows of Altet and Aloct typically result in an adsorbed water layer with, to a good first approximation, corresponding rows of molecules oriented with pz < -0.5 and pz > +0.5, respectively. The adsorption of pure isopropanol leads to the structure at the interface differing considerably compared with the water adsorption owing to the hydrophobic alkane moiety of the solvent molecules. As can be seen from Figure 6, in contrast to the pure water case, the surface is only partially contacted by the hydroxyl groups of the isopropanol. Again, a strong correlation between the positions of Aloct with the OH group of the liquid molecules is observed; however, not all of the possible interaction sites of this type are occupied (marked areas in part b of Figure 6). Closer inspection of the molecules at the surface shows that, for molecules adsorbed along rows of Aloct, the shortrange van der Waals repulsions serve to orient the alkyl chains roughly perpendicular to the 〈110〉 direction (i.e., looking along z), placing them alternately on opposite sides of the Aloct row to minimize steric repulsions (Figure S4 of the Supporting Information). Correspondingly, the alkane tails shield the neighboring Altet sites from other alcohol molecules - the marked regions in part b of Figure 6 highlight unoccupied Aloct sites arising from the complementary situation where an isopropanol adsorbed on an Altet site obscures the Aloct site from the liquid. These blue regions represent a bifurcated hydrogen bond configuration comparable to that observed for the pure water system. Integration of the O · · · O RDF for pure isopropanol (Figure S2 of the Supporting Information) shows that the coordination number of hydroxyl groups around a central OH group is a little less than 2, suggesting the formation of clusters of three alcohol head groups in the liquid. Adsorption of molecules at the surface necessarily breaks this microscopic structure and, as can be seen from the integrals of the in-layer RDFs of the pure isopropanol simulation (Figure S3 of the Supporting Information). In the adsorbed layer, the bulklike coordination number of 2 is not reached until beyond 4 Å, well past the first minimum in the bulk O · · · O RDF. Molecules are permitted to sit with OH groups at similar distances to the bulk, albeit in smaller proportions, because the distance between neighboring surface Aloct atoms (2.807 Å) is almost identical to the position of the first maximum in the O · · · O RDF. Whereas this may seem likely to enhance the packing of isopropanol on the surface, the significant bulk associated with the alkyl chains must also be considered and the orientation enforced on the OH headgroup. Because the OH group points more or less toward the Aloct site, it cannot hydrogen bond to a neighboring alcohol, in contrast to the liquid

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Figure 6. Microscopic structure of the interfacial region of the pure isopropanol systems, showing the averaged structure of the topmost oxide surface layers (a) and the averaged value of pz for isopropanol molecules in the first (b) and second (c) layers as a function of position over the surface. For (b) and (c) solid red indicates the water oxygen pointing toward the surface (pz f +1), solid blue indicates oxygen pointing away from the surface (pz f -1), and white regions indicate no water molecules observed at this position. Gray highlights in part b indicate some Aloct sites above which isopropanol has not adsorbed.

where O-H · · · O interactions create the local micellar structure. For the second layer the shape of the integral is more bulklike but the first plateau is at 1, approximately half of that seen in the liquid. Thus, the isopropanol trimer is not seen in the second adsorbed layer because the molecules in the adsorbed layer present a hydrophobic face to the remaining liquid, restricting its opportunities to hydrogen bond effectively. A similar conclusion was reached by Tarmyshov and Mu¨ller-Plathe in their studies of isopropanol over Pt(111).31 Within the first adsorbed layer for the 7, 19, and 50 mol % simulations, some clustering of isopropanol molecules is found, which suggests that the individual liquid components are somewhat segregated on the surface (Figures S5-S7 of the Supporting Information). Nevertheless, the clustering of alcohol molecules on the surface appears to be consistent with the presence of the trimer in the

liquid, from which the constituent molecules adsorb at the surface within the same locality. Dynamics of Adsorbed Layers. The center-of-mass velocity autocorrelation function (VACF) and mean-squared displacement (MSD) for specific subsets of molecules have been calculated to examine their short and long-time dynamical behavior. Because there are two distinct interactions of molecules with the surface in the first layer, that is those above Aloct and those above Altet, we consider the VACF and MSD of each type separately. To differentiate between the species, it is assumed that molecules in the first adsorbed layer that have pz > +0.5 contribute to the Aloct function, whereas those with pz < -0.5 contribute to the Altet function. For the second layer and beyond, all molecules within a particular z slice of the simulation defined from the positions of minima in the z-density

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Youngs et al.

TABLE 4: Calculated Diffusion Coefficients Calculated from the Slope of the MSD in the Linear Region 10-20 psa mol % IPA/layer 0/1, pz > 0.5 0/1, pz < -0.5 0/2 0/3 0/4 0/5 0/6 Bulk 100/1 100/2 100/3 100/4 100/5 Bulk

zlayer, Å

Dtot, × 10-5 cm2 s-1

1.0-2.3 2.3-3.5 3.5-5.9 5.9-8.9 8.9-11.9 11.8-14.9 14.9-17.9

0.0006 (0.0003) 0.0008 (0.0007) 0.33 (0.11) 1.04 (0.19) 1.55 (0.05) 1.96 (0.13) 2.16 (0.18) 2.51 0.0013 (0.0003) 0.09 (0.01) 0.25 (0.01) 0.40 (0.01) 0.54 (0.01) 0.75

1.0-5.0 5.0-10.0 10.0-14.0 14.0-18.5 18.5-23.2

a Bulk values for the liquid are those calculated from the forcefield at the experimental density and 300 K.

Figure 7. Velocity autocorrelation functions for pure water (a) and pure isopropanol (b) simulations (taken from a single simulation data from other simulations is comparable), calculated for molecules in specific layers parallel to the surface over 5 × 104 simulation timesteps. Simulated data for bulk systems in the absence of a surface are given for comparison and are generated with the same forcefields used in the main simulations.

profiles in Figure 2, where possible, are considered. This approach reduces the number of molecules that contribute to the functions at any given point and, therefore, to obtain sufficiently accurate statistics the molecules are allowed to make more than one contribution over the course of the simulations, that is if a molecule leaves the z slice of interest but later reenters all velocity and position accumulators for it are reset and a fresh contribution to the function begins. Furthermore, for the MSD only the short-time region is well-defined because the mobility of molecules means that there is an unavoidable upper limit placed on the length of time a particular molecule will stay within the region of interest. Hence, MSD slopes are taken over the short, but statistically accurate, region of 10-20 ps in all cases. Table 4 lists the diffusion coefficients obtained from the slope of the MSDs, whereas Figure 7 shows the VACFs for the molecules in the pure component systems. The definition of the local structure as a function of the distance from the surface is

Figure 8. Contributions to the velocity autocorrelation functions for molecules in the first adsorbed layer from components parallel (solid lines) and perpendicular (dashed lines) to the surface normal in the pure water simulation for interactions proceeding through (a) Aloct and (b) Altet.

strongly correlated with the calculated diffusion coefficients. Strong order is present in the first adsorbed layer and whereas significant structuring is also found in the second and, to a lesser degree, in the third layers and this is reflected by increasing diffusion coefficients. As the distance from the surface increases further the diffusion coefficient tends toward that of the bulk liquid value. The VACFs for the second and third layers suggest bulklike short-time dynamics even if the overall rate of molecular diffusion is lower than the bulk value. For pure water, the molecular diffusion coefficients in the adsorbed layer are effectively zero, regardless of whether the molecule is above a tetrahedral or octahedral site. However, the VACFs calculated for each of these distinct interactions, shows that the subpicosecond dynamics are considerably different depending on the adsorbed site. For a molecule above Aloct with pz ≈ +1, the corresponding VACF has an oscillatory structure related to rapid molecular vibrations along the surface normal that persists up to 0.4 ps. This is clearly visible when considering the individual contributions to the VACF from each of the parallel and perpendicular directions to the surface normal, as shown in Figure 8. This indicates that the oscillations in the function are related solely to movement in the z direction. In contrast, the VACF for molecules above Altet with pz ≈ -1 (part a of Figure 7) shows a behavior more typical of a selfinteracting fluid, with a broad minimum that decays to zero. The individual components above Altet also show some weak fluctuations in the z component, which are much smaller than those above the octahedral sites. Furthermore, the local minima in the x and y functions are less pronounced for interactions with Altet. These differences suggest that interactions with Altet are of comparable strength to those with Aloct but the restrictions on the allowed interaction geometries and their associated vibrations are more limiting in the latter. Moreover, integration of the two separate curves for the adsorbed layer in part a of Figure 7 suggests that the mobility of the two sites are similar in magnitude but with those related to Altet being marginally higher. It is known that the VACF for water displays a minimum while the function is still positive followed by a small peak at approximately 0.12 ps, independent of the quality of the forcefield used in the simulation34 and that this is a result of librational modes caused by strong hydrogen bonding.35 The VACFs presented in part a of Figure 7 (or Figure 8) do not show this feature for the adsorbed layer as a result of the restricted liquid environment, which decreases the number of hydrogen bonds per water molecule and hence reduces the intensity of librational modes and their contribution to the VACF. In the case of pure isopropanol the first adsorbed layer is again effectively static with a very low calculated diffusion

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TABLE 5: Experimental Diffusion Coefficients as Measured by PFG-NMRa D, × 10-5 cm2 s-1 mol % IPA

surface

bulk pore

bulk liquid

0 19 100

0.019 (0.0055) 0.0053 (0.0004) 0.0013 (0.0003)

0.966 (0.017) 0.147 (0.001) 0.163 (0.001)

2.29 (0.01) 0.39 (0.002) 0.61 (0.004)

a Values given are for the isopropanol component of the system, except for the 0 mol % mixture where values for water are presented. Estimated uncertainties are given in parentheses.

coefficient (Table 4), which gradually rises with increasing z, tending toward the bulk liquid value. The VACFs indicate that there are no such strong oscillations parallel to the surface normal as was the case for liquid water, a reflection of the bulkier nature of the molecule and its local environment, potentially coupled with a weaker interaction with the oxide. Whereas the adsorbed layer shows significantly different shorttime behavior than the bulk, it also appears from the VACFs that the second layer is also affected, which is in contrast to that found for the pure water case, and also from simulations of isopropanol over Pt(111).31 One possible explanation is that this is the effect of the hydrophobic covering on the surface, which prevents the liquid forming its preferred trimer structure in the second layer. The third isopropanol layer shows bulk liquidlike VACF behavior. The experimental diffusion coefficients of the three experimental samples (1-3) as determined by PFG-NMR for three different regimes are summarized in Table 5 - bulk liquid refers to measurements conducted in the absence of any surface, bulk pore refers to liquid within the pore, and surface includes the diffusion of surface-influenced molecules. The PFG-NMR technique measures the slowest diffusion coefficient and an average diffusion coefficient for the fastest moving species over the time scale of the measurement. The latter includes a contribution from motion between the pores within the material and, therefore, the tortuosity needs also to be considered.28 The observation that the displacements measured over the effective diffusion time for both bulk-pore and surface contributions correspond to distances greater than a single pore diameter is consistent with molecules remaining within the surfaceinfluenced layer while diffusing over length-scales greater than a single pore. A comparison with diffusion coefficients determined from simulations of similar systems allows an estimation of the spatial regions to which the measured diffusion coefficients may be related. Because the pore width is on the order of tens of nanometres, it is to be expected that toward the center of the pore the liquid diffusion will have a bulklike value. The diffusion coefficients for the bulk-pore regime presented here, being between 21-29% of the bulk liquid value, must still lie within a surface-influenced region. Experimentally the diffusion over the surface is found to be considerably faster by several orders of magnitude than in the simulation. Although this may be due to the lack of hydroxylation in the simulation as well as the absence of any associated microscopic roughness of the alumina surface, this assumes that the PFG-NMR measurements are probing the first adsorbed layer. It is more likely that both the first and second layers are measured as one owing to strong correlations between the two that are found within this region. Taking the same average from the simulated diffusion coefficients results in values closer to those determined experimentally. This interpretation is consistent

Figure 9. Diffusion coefficients calculated from the pure water (top, black lines, dotted line represents second simulation) and pure isopropanol (bottom, red lines) systems for molecules in z slices of ∆z width beginning at the first minimum observed in the z-density profiles in Figure 2 (i.e., starting at the end of the first adsorbed layer). Dashed lines indicate the bulk-pore diffusion coefficients determined by PFGNMR.

with the results of Fripiat et al.36 and Halperin et al.37 where estimates of the surface influenced layer are thought to be between 1-3 monolayers. Figure 9 plots the diffusion coefficients calculated from molecules within z slices of 5-12 Å width (∆z) beyond the first adsorbed layer in the pure water and pure isopropanol simulations. The experimental bulk-pore values are found to cross the calculated lines at ∆z of 6 and 8.5 Å for water and isopropanol, respectively. In the case of the alcohol this z- range corresponds well to the second and third layers of liquid as determined from the z-density profiles in Figure 2. For water the same correlation is more difficult to make since the third layer is less distinct in the z-density profile. It should be noted that this is likely to be the minimum distance beyond which the surface influence is felt. The simulation may provide an underestimation from the simulation as the lack of surface hydroxylation may induce stronger longer range correlations within the liquid and a weaker dependence of the diffusion coefficient with distance from the surface. In addition, if the tortuosity of the pore network is taken into account, this will lead to higher experimental values of the bulk-pore diffusion coefficient.28 The limitations of both the simulation and the experimental methods indicate that the bulk-pore diffusion coefficient will occur for molecules beyond the third layer. Conclusions Strong correlations between the structure and dynamics of the liquid with octahedral surface Al are observed, with the effects of these surface sites permeating 10-15 Å into the liquid. For both isopropanol and (in particular) water, a mixture of molecular orientations is evident in the first adsorbed layer, largely guided by the arrangement of octahedral and tetrahedral Al. For isopropanol, this removal of liquid anisotropy results in a predominantly hydrophobic covering of the surface, with methyl groups exposed to the remainder of the liquid and forming an effective barrier on the surface. In mixed simulations, we observe qualitatively the presence of alcohol- and waterrich regions at the surface, and suggests that the trimeric isopropanol structure within the pure liquid is somewhat maintained in these adsorbed regions, albeit in a 2D fashion. Given the lack of surface hydroxylation in the simulations, coupled with the slight overestimate of bulk isopropanol diffusion by the forcefield, we can infer that the measured PFGNMR surface influenced region corresponds to the first two

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distinct liquid layers. The bulk-pore region encompasses layers above at least the third layer observed by simulation. Acknowledgment. The authors thank the EPSRC and Johnson Matthey for funding this work under the CARMAC project. The authors also express their gratitude to Drs. Mick Mantle and Andy Sederman for enlightening discussions and Miss Tegan Roberts for the NMR experimental preparation and subsequent data analysis. D.W. thanks the Cambridge European Trust and the Studienstiftung des deutschen Volkes for additional funding. T.Y. thanks R. M. Lynden-Bell for useful discussions. Supporting Information Available: Centers of mass figures, radial distribution function figure, and structural views of selected molecules. This material is available free of charge via the Internet at http://pubs.acs.org. References and Notes (1) See, for example, the following reviews and references therein: Lanzani, G.; Martinazzo, R.; Materzanini, G.; Pino, I.; Tantardini, G. F. Theor. Chem. Acc. 2007, 117, 805–825. Taylor, C. D.; Neurock, M. Curr. Opin. Solid St. M. 2005, 9, 49–65. (2) Janik, M. J.; Neurock, M. Electrochim. Acta 2007, 52, 5517–5528. (3) Nagy, G.; Heinzinger, K.; Spohr, E. Faraday Discuss. 1992, 94, 307–315. (4) Jhon, I. Y.; Kim, H. G.; Jhon, M. S. J. Colloid Interface Sci. 2003, 260, 9–18. (5) Blonski, S.; Garofalini, S. H. Surf. Sci. 1993, 295, 263–274. (6) Alvarez, L. J.; Leo´n, L. E.; Sanz, J. F.; Capita´n, M. J.; Odriozola, J. A. Phys. ReV. B 1994, 50, 2561–2565. Alvarez, L. J.; Leo´n, L. E.; Sanz, J. F.; Capita´n, M. J.; Odriozola, J. A. J. Phys. Chem. 1995, 99, 17872– 17876. (7) Hu, B.; Fishwick, R. P.; Pacek, A. W.; Winterbottom, J. M.; Wood, J.; Stitt, E. H.; Nienow, A. W. Chem. Eng. Sci. 2007, 62, 5392–5396. (8) Hindle, K.; Rooney, D. W.; Akpa, B. S.; Gladden, L. F.; Weber, D.; Neurock, M.; Sinha, N,; Stitt, E. H. 19th International Symposium on Chemical Reaction Engineering, Potsdam, Germany, 2006. (9) Dixit, S.; Crain, J.; Poon, W. C. K.; Finney, J. L.; Soper, A. K. Nature 2002, 416, 829–832. (10) Manyar, H. G.; Weber, D.; Daly, H.; Thompson, J. M.; Rooney, D. W.; Gladden, L. F.; Stitt, E. H.; Delgado, J. J.; Bernal, S.; Hardacre, C J. Catal. 2009, 265, 80–88. (11) Paglia, G.; Rohl, A. L.; Buckley, C. E.; Gale, J. D. Phys. ReV. B 2005, 71, 224115. (12) Smrcˇok, L.; Langer, V.; Krˇestan, J. Acta Crystallogr., Sect. C 2006, 62, i83–i84. (13) Zhou, R.-S.; Snyder, R. L. Acta Crystallogr., Sect. B 1991, 47, 617–630.

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