Dependence of Water Dynamics on Molecular Adsorbates near

Mar 26, 2014 - First-principles molecular dynamics simulations are used to gain an atomistic-level insight into how the molecular behavior of interfac...
5 downloads 0 Views 3MB Size
Download PDF
Article pubs.acs.org/JPCC

Dependence of Water Dynamics on Molecular Adsorbates near Hydrophobic Surfaces: First-Principles Molecular Dynamics Study Donghwa Lee,† Eric Schwegler,† and Yosuke Kanai*,†,‡ †

Condensed Matter and Materials Division, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States ‡ Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States S Supporting Information *

ABSTRACT: First-principles molecular dynamics simulations are used to gain an atomistic-level insight into how the molecular behavior of interfacial water is influenced by specific surface adsorbates. Although the overall hydrophobic versus hydrophilic character of a given surface is widely recognized to be important in determining the behavior of interfacial water molecules, we show that subtle molecular details may also play a role in determining the dynamical behavior of water. By comparing water diffusivity at three different nonpolar surfaces, we find that specific surface features can lead to a suppression of hydrogen bond network ring structures by enhancing hexagonal spatial distributions of water molecules near the surface. Such a distinct molecule-dependent behavior of the interfacial water was found to persist well into the liquid, while most structural properties are noticeably influenced in only the first water layer.

■

INTRODUCTION The behaivor of interfacial water is important for numerous applications including corrosion, tribology, reaction chemistry, surface patterning, and environmental and soil science.1,2 The general concept of hydrophobicity is often used to interpret the characteristics of interfacial water on the basis of properties such as the contact (wetting) angle.3 Molecular passivation is a common scheme to modify the hydrophobicity of the material’s surface and control the behavior of water at the interface. Although the overall hydrophobic versus hydrophilic character of a given surface is widely recognized to be important in determining the behavior of interfacial water molecules,4 the role of atomistic details in the dynamical behavior of water has not been well understood at the microscopic molecular level. With a growing interest in nanoscale water interfaces, many different studies have been performed to understand how the structural and dynamical properties of interfacial water are different relative to those of bulk liquid water. Several experimental studies including those based on nuclear magnetic resonance,5 ultrafast IR spectroscopy,6 and atomic force microscopy7 observed that the perturbation of interfacial water remains rather localized although the actual extent of such locality is not clearly distinguished.1,8−10 Similarly, a number of empirical molecular simulation studies have shown © 2014 American Chemical Society

that the perturbation of water molecules occurs primarily in the first water layer and that the bulk properties are quickly recovered farther away.1,8,11 Recently, first-principle density functional theory (DFT)−molecular dynamics (MD) approaches also predicted a short-ranged perturbation of the interfacial water molecules, indicating that the structural variation is limited to the region where water molecules are in direct contact with the surface.12,13 In spite of these numerous investigations, the overall dynamical behavior of interfacial water has remained somewhat controversial. Experimental studies have reported both short and long relaxation times in the dynamics of interfacial water. A slow decay time for interfacial water molecules has been reported by quasi-elastic neutron scattering14 and atomic force microscopy.7 In contrast, magnetic relaxation dispersion studies 15 did not observe any significant slow decay component. Other approaches such as fluorescence spectroscopy16 and solvation dynamics17 indicate a large variation of interfacial water dynamics. Recently, the existence of two separate regions showing different dynamical behavior has been suggested from ultrafast spectroscopy.18 Similarly, several Received: March 21, 2014 Published: March 26, 2014 8508

dx.doi.org/10.1021/jp502850k | J. Phys. Chem. C 2014, 118, 8508−8513

The Journal of Physical Chemistry C

Article

group (COOH). Interactions among all atoms are described using density functional theory (DFT)27 with the generalized gradient approximation of Perdew−Burke−Ernzehof (PBE).28 Ultrasoft pseudopotentials29 are used, and wave functions and charge densities are expanded in plane waves with kinetic energies up to 25 and 180 Ry, respectively. The Car−Parrinello molecular dynamics approach is employed to investigate the dynamical trajectories in an NVT ensemble.30 A time step of 3 au and a fictitious electronic mass of 340 au are used for the dynamics. An elevated temperature of 375 K is used with a Nose−Hoover chain thermostat to describe water behavior at room temperature as done in previous works.31 We run the MD simulation for at least 30 ps to obtain enough statistics of water behavior after the pre-equilibration of 3 ps. The properties of confined water generally depend on the extent of confinement itself as well as the atomistic characteristics of the surface. To investigate how specific molecular adsorbates influence the behavior of confined water at the interface, the effects stemming from differences in the confinement distances need to be separated from those coming from the surface (i.e., from specific molecular adsorbates). To address this, we carried out an extensive set of MD simulations to choose a particular confinement distance for each surface such that the confinement is the same for all four surfaces. Figure 2 shows the density profile of water molecules along the

experimental studies have reported inconsistent dynamics of confined water molecules. Enhanced dynamical behavior has been reported for water confined in a carbon nanotube (CNT).19−21 In contrast, other studies have reported decreased mobility of water confined in a CNT22,23 or between hydrophilic surfaces.24 Simulation studies have also led to inconsistent dynamics of the confined water. DFT13 and classical25 MD simulations have reported enhanced water flow in nanoscale CNT or graphene layers with decreasing confinement distances. On the other hand, another MD simulation26 has reported decreased mobility of water molecules confined by graphene sheets. In this work, the effects of molecular adsorbates on the structural and dynamical behavior of interfacial water at the surface are investigated by employing first-principle DFT−MD approaches. We find that similar adsorbates of a nonpolar characteristic can lead to significantly different dynamical behavior of water molecules at the interface. The physical origin of varying water dynamics associated with the adsorbates was elucidated from the spatial distribution pattern of water molecules at the interface. Our study demonstrates how the corrugation profile of the surface electrostatic potential plays an important role in determining interfacial water dynamics.

■

THEORETICAL METHODS Figure 1 shows a schematic view of the systems we have examined, which involve 108 water molecules confined between two Si(111) surfaces with different surface adsorbates. A four-layered slab with 72 Si atoms is used to model the surface with periodic boundary conditions. Four different surfaces are investigated by changing the molecular adsorbate layer: three nonpolar groups (H, CF3, and CH3) and one polar

Figure 2. Density of water molecules as a function of the distance from the surface.

direction perpendicular to the functionalized Si surface. The observed density oscillations in each of the simulations are typical of a liquid in contact with a flat surface.24,32 As shown in Figure 2, with the confining distances between the surfaces chosen in our MD simulations, the equivalent confinement was prepared for all the surfaces such that the water density shows the identical increase away from the confining surfaces.

■

RESULTS AND DISCUSSION For convenience, we group all water molecules into two distinctive regions: region I represents roughly the first water layer, from the surface to the first minimum of the water density profile (Figure 2), and the rest is considered as region II, which shows relatively small fluctuations in the water density (see Figure 2). A sharp increase of the water density just outside the water depletion region is a common behavior observed for both graphene and hydrogenated diamond surfaces.13 The height of the first peak in the water density depends somewhat on the molecular details at the surface; the peak height varies from 1.49 g/cm3 at the H−Si surface to 1.58

Figure 1. Schematic view of confined water by Si(111) surfaces. The confinement region is split into two regions: surface region (about 4 Å width region from the top of the surface adsorbates) and near-surface region (about 15 Å width region in the middle of the confined water). The blue rectangle represents the simulation box. The right side of the figure shows the top view of four different Si surfaces functionalized by H, CF3, CH3, and COOH in order from top to bottom. 8509

dx.doi.org/10.1021/jp502850k | J. Phys. Chem. C 2014, 118, 8508−8513

The Journal of Physical Chemistry C

Article

Table 1. Comparison of Analytical Results at Four Different Surfacesa region I 3

peak density (g/cm ) no. of HBs (per O atom) diffusivity (10−5 cm2/s) no. of 5-fold HB polygon rings local structure index (Å2)

donor acceptor

region II

H

CH3

CF3

COOH

H

CH3

CF3

COOH

1.49 1.54 1.52 1.86 0.12

1.55 1.58 1.56 0.97 0.80

1.58 1.60 1.57 0.84 0.94

1.77 1.87 (1.39) 1.73 (1.52) 0.62 0.33

1.20 (0.98) 1.81 1.81 1.22 1.25 0.0271

1.33 (0.99) 1.86 1.86 0.58 3.74 0.0301

1.31 (0.99) 1.87 1.88 0.28 7.04 0.0312

1.15 (0.98) 1.83 1.78 0.96 3.42 0.0286

a

Density in region I corresponds to the peak density. The average density in region II is also shown in parentheses. For the COOH surface, the number of HBs formed only among water molecules is shown in parentheses. The local structure index is only obtained for region II.

g/cm3 for the CF3−Si surface among the hydrophobic surfaces, while the COOH−Si surface shows a much higher peak (see Table 1). The small difference among the three hydrophobic surfaces can be understood by considering the ionic character of the adsorbate molecules. The C−F bond has a stronger ionic character relative to the C−H or Si−H bonds, and therefore, the CF3-terminated Si surface exhibits a slightly sharper distribution of water molecules in region I. The average water density in region II is approximately 1 g/cm3 for all the surfaces. Diffusivity near Hydrophobic Surfaces. The mean square displacement (MSD) of the water molecules in the different confined systems is shown in Figure 3a. For

Given that the extended hydrogen bond network in liquid water leads to a coupling between the translational and rotational motion of individual water molecules, 33 an examination of the rotational autocorrelation function (RAF) can be used to provide additional details of the dynamical behavior of water molecules near different surfaces. Figure 3b shows the RAF, Γ = ⟨μ(0)·μ(t)⟩, at the four different surfaces, where μ corresponds to the molecular dipole moment vector of individual water molecules. In this analysis, μ is approximated by simply assigning a point charge to each O and H atom as −2 and +1, respectively. A noticeably different decay rate is evident for the rotational motion of the water molecules near the four different surfaces; faster decay is associated with faster rotational motion of water molecules, resulting in faster diffusion.13 In line with our observation in the MSD, the same trend in the decay time of RAF is also observed for water molecules at different surfaces. In order to gain further insight into the dynamical behavior of the water near the different surfaces, the MSDs of the water molecules in regions I and II (see Figure 4) were computed

Figure 3. (a) Mean square displacement and (b) rotational autocorrelation function of water molecules at Si surfaces passivated with different surface functional groups.

comparison, the MSDs of bulk (unconfined) water and water confined by the hydrophilic COOH−Si surface are also shown. We find that having different surface adsorbates leads to noticeable differences in the diffusivity even for somewhat similar hydrophobic surface adsorbates; the self-diffusivity, as determined by the Einstein diffusion equation, varies from 0.44 to 1.44 (10−5 cm2/s) depending on the adsorbate molecules. We observe that water molecules diffuse much faster at the H− Si surface than at the other Si surfaces. Although the overall hydrophobic/hydrophilic character of a surface is generally considered to strongly influence the dynamical behavior of the interfacial water molecules, the specific atomistic details of the adsorbate molecules appear to have a significant effect as well.

Figure 4. Mean square displacements of water molecules in two different regions from the Si surfaces passivated with different surface functional groups.

separately. Since water molecules can diffuse into and out of each region, we track the spatial location of all water molecules throughout the simulation and separate their contributions depending on in which region they are located. Figure 4 shows the MSDs of water molecules at the H−, CH3−, CF3−, and COOH−Si surfaces in regions I and II. As expected, this analysis clearly shows that the water molecules diffuse faster 8510

dx.doi.org/10.1021/jp502850k | J. Phys. Chem. C 2014, 118, 8508−8513

The Journal of Physical Chemistry C

Article

slightly different from those of the CH3− and CF3−Si surfaces, the qualitative features of the angular distribution are remarkably similar for the three different nonpolar surfaces, which indicates that there is less of a dependence of the orientations on the specific surface adsorbates. We further confirmed this by performing a similar analysis on the molecular orientation of the water molecules (see the Supporting Information for more details). Thus, the angular orientation of OH bonds does not explain the differences in diffusivity of water at the three hydrophobic surfaces. We also note that the orientational behavior of the OH bonds is largely insensitive to the specific confining distance between the silicon surfaces (see Figure S4 in the Supporting Information). Although the different nonpolar surfaces do not appear to significantly alter the orientational ordering of the interfacial water molecules, it is possible that the specific surface absorbates have an effect on the overall spatial distribution of the water molecules near the surface. To examine the possibility of this effect, we examined the spatial distribution function (SDF) of water molecules at the three hydrophobic surfaces. The spatial pattern of water molecules has been observed by both STM34 and DFT.13 Water molecules in region I (∼ the first water layer) at the H−Si surface are preferentially ordered in a strong hexagonal SDF compared to those at the CH3− or CF3−Si surface as seen in the top panels of Figure 6. To

near the hydrophobic surfaces than the hydrophilic surface (region I). At the same time, the water diffusivity is seen to depend significantly on the atomistic details of the adsorbates even for the first layer as well. In region II, farther away from the surface, the dependence on the atomistic details of the surface adsorbates appears to be stronger than that on the overall hydrophobic/hydrophilic character of the surface. It is now apparent that water dynamics is not a simple function of the surface hydrophobicity alone, and atomistic details of the molecular adsorbates can play an important role as well. In the following sections, we discuss the origin of this behavior in terms of the different hydrophobic surfaces: H−Si, CH3−Si, and CF3−Si. Local and Spacial Water Distribution. The OH bond orientation was examined to probe the overall orientational ordering of the water molecules near the surface. The OH bond tilt angle is defined as the angle (θ) that each OH vector forms with the direction normal to the surface as shown schematically in the inset of Figure 5. The probability distribution of θ as a

Figure 6. Top: spatial distribution of water molecules near the three different hydrophobic surfaces. The distribution profiles are obtained by accumulating the spatial location of water molecules within 1 Å after the depletion region of each surface. Bottom: electrostatic potential contour map at the position right after the water depletion region of three surfaces.

Figure 5. Probability of finding different OH bond vector orientations as a function of the distance from the surface.

function of the angle and the distance from the surface is shown in Figure 5. For all three surfaces, water molecules show two preferential orientations in region I: one major peak in approximately a parallel direction and one minor peak that corresponds to OH bonds pointing toward the surface. At about 2.1 Å from the H−Si surface, the OH bonds show major (60°) and minor (160°) orientations corresponding to slightly pointing outward from the surface and pointing toward the surface. At about 3.1 Å, in contrast, the most likely OH orientations correspond to pointing slightly inward (120°) and outward (25°). In region II, the strong preference for parallel orientations begins to diminish and OH bond orientations exhibit a more uniform probability distribution over a wide range of angles (40−140°), indicating that the surface has less orientational ordering of water molecules in the region. Although the relative preferences of the OH orientation are

understand different SDFs of water molecules, we further investigate electrostatic potential profiles at the three hydrophobic surfaces. The electrostatic potential profiles indeed change significantly as shown in the bottom panels of Figure 6. On the H−Si surface, the locations of surface H atoms lead to a sharp drop in the electrostatic potential (red) while the rest of the surface shows a rather smooth potential (blue). In the restricted spaces of the high electrostatic potential, the water molecules at the H−Si surface are not able to form extensive hydrogen bond networks, and this is also evident in the ring statistics analysis discussed in the following section. On the other hand, the electrostatic potential pattern is less prominent for both CH3−Si and CF3−Si surfaces. CH3−Si and CF3−Si surfaces do not form the high-density water region restricted by 8511

dx.doi.org/10.1021/jp502850k | J. Phys. Chem. C 2014, 118, 8508−8513

The Journal of Physical Chemistry C

Article

closed loop of HBs. The size of each HB ring is determined by counting the number of HBs forming the closed circuit. We first calculated the ring statistics of HB networks centered in region I as shown in Figure 8. As can clearly be seen, the

the smooth electrostatic potential in the manner that the H−Si surface does. The electrostatic potential for the CF3−Si surface is more homogeneous compared to that for the CH3−Si surface (Figure 6), and therefore, water molecules are more randomly distributed at the surface. This results in the CH3−Si surface having relatively more of the adsorbate pattern in the water layer compared to the CF3−Si surface. Number of Hydrogen Bonds and Their Ring Network. We now look at the number of hydrogen bonds (HBs) at each surface to clarify the structural effect of water molecules on the overall HB formation. Figure 7 shows the number of HB

Figure 8. Enumeration of rings in (a) region I and (b) region II at H−, CH3−, and CF3−Si surfaces.

probability distribution depends strongly on the specific molecular adsorbates. Among different sizes of rings, 5-fold rings have the highest probability for CH3− and CF3−Si surfaces while the smaller 4-fold rings are more prevalent for the H−Si surface in region I. In bulk water, the ring size of the highest probability is 5. Because the restricted hexagonal SDF of water molecules at the H−Si surface limits the HB network ring formation, there is a smaller probability of forming larger sized rings in the case of the H−Si surface. Moreover, the number of HB networks formed at the H−Si surface is much smaller than at the other two surfaces for all the ring sizes. The trend of decreased HB ring network formation from CF3−Si to CH3−Si to H−Si surfaces in the ring statistics correlates well with the extent of the hexagonal SDF observed in region I for these surfaces. Furthermore, the effects of molecular adsorbates on the HB network formation (through the hexagonal SDF water distribution at the surface) are rather nonlocal, extending beyond the first layer of water and into region II. The observed trend in the ring statistics between the surfaces still exists even in region II, and it is prominent enough to influence the water diffusivity in region II as seen in Figure 4b. Water molecules near the CF3−Si surface show the slowest diffusivity because of the extensive HB network formed as indicated in the ring statistics, while water diffusivity at the H−Si surface is the fastest because of the suppressed HB network.

Figure 7. Average number of hydrogen bonds (HBs) for each water molecule along the direction perpendicular to the Si surface functionalized with three different molecules: (a) water−water HB donors, (b) water−water HB acceptors.

donors and acceptors between the water molecules as a function of the distance from the surface. The conventional geometric HB definition of an OHO angle larger than 140° and a 3.5 Å O−H distance cutoff is used.13 Within the framework of OA···H−OB, the HB donor represents an OB atom covalently bonded with the H atom while the HB acceptor is the neighboring OA atom interacting with the H atom via lone pair electrons; see the insets. There is a noticeable difference in the HB profiles close to the surface, depending on the adsorbate molecules (H, CH3, and CF3). However, the average numbers of HB donors formed in regions I and II are quite similar for all the hydrophobic surfaces as shown in Table 1; the hydrophilic surface with COOH is also shown for comparison. Overall, the total numbers of HB donors and acceptors are not significantly changed by different hydrophobic adsorbates and thus do not properly interpret the observed differences in the structural and dynamical behavior of the water molecules. The HB donors and acceptors represent a correlation between two water molecules and thus describe only a local feature of water. Since our analysis discussed above indicates that the main difference in water behavior near the three surfaces is related to the overall spatial distribution of the water molecules, we further investigated the probability of forming specific HB ring networks, which are more representative of the long-range arrangement of HBs. We calculate the number of HB network rings of different sizes by identifying the smallest

■

CONCLUSION In our first-principles MD simulations, we observed that the dynamical behavior of water molecules near nonpolar interfaces can be significantly influenced by the specific atomistic details of the molecular adsorbates as compared to the overall hydrophobic/hydrophilic character of the surface. In comparing H−, CH3−, CF3−, and COOH−Si surfaces, water diffusivity 8512

dx.doi.org/10.1021/jp502850k | J. Phys. Chem. C 2014, 118, 8508−8513

The Journal of Physical Chemistry C

Article

(2) Henderson, M. A. Surf. Sci. Rep. 2002, 46, 1−308. (3) Chandler, D. Nature 2005, 437, 640−647. (4) Eun, C. S.; Berkowitz, M. L. J. Phys. Chem. A 2011, 115, 6059− 6067. (5) Oleinikova, A.; Sasisanker, P.; Weingartner, H. J. Phys. Chem. B 2004, 108, 8467−8474. (6) Moilanen, D. E.; et al. J. Phys. Chem. B 2009, 113, 8560−8568. (7) Li, T. D.; et al. Phys. Rev. B 2007, 75, 115415. (8) Halle, B. Philos. Trans. R. Soc. London, Ser. B 2004, 359, 1207− 1223. (9) Bellissent-Funel, M. C., Ed. Experimental Hydration Processes in Biology: Theoretical and Experimental Approaches; NATO Science Series A: Life Sciences, Vol. 305; IOS Press: Amsterdam, 1999. (10) Svergun, D. I.; et al. Proc. Natl. Acad. Sci. U.S.A. 1998, 95, 2267− 2272. (11) Bagchi, B. Chem. Rev. 2005, 105, 3197−3219. (12) Grossman, J. C.; Schwegler, E.; Galli, G. J. Phys. Chem. B 2004, 108, 15865−15872. (13) Cicero, G.; et al. J. Am. Chem. Soc. 2008, 130, 1871−1878. (14) Mamontov, E.; Cole, D. R. Phys. Chem. Chem. Phys. 2006, 8, 4908−4914. (15) Modig, K.; et al. J. Am. Chem. Soc. 2004, 126, 102−114. (16) Douhal, A.; et al. J. Phys. Chem. B 2007, 111, 5487−5493. (17) Pal, S. K.; et al. J. Phys. Chem. B 2002, 106, 12376−12395. (18) Zhong, D. P.; Pal, S. K.; Zewail, A. H. Chem. Phys. Lett. 2011, 503, 1−11. (19) Joseph, S.; Aluru, N. R. Nano Lett. 2008, 8, 452−458. (20) Holt, J. K.; et al. Science 2006, 312, 1034−1037. (21) Majumder, M.; et al. Nature 2005, 438, 44−44. (22) Naguib, N.; et al. Nano Lett. 2004, 4, 2237−2243. (23) Liu, Y. C.; Wang, Q. Phys. Rev. B 2005, 72, 085420. (24) Major, R. C.; et al. Phys. Rev. Lett. 2006, 96, 177803. (25) Hummer, G.; Rasaiah, J. C.; Noworyta, J. P. Nature 2001, 414, 188−190. (26) Hirunsit, P.; Balbuena, P. B. J. Phys. Chem. C 2007, 111, 1709− 1715. (27) Kohn, W.; Sham, L. J. Phys. Rev. 1965, 140, A1133−A1138. (28) Perdew, J. P.; Burke, K.; Ernzerhof, M. Phys. Rev. Lett. 1996, 77, 3865−3868. (29) Vanderbilt, D. Phys. Rev. B 1990, 41, 7892−7895. (30) Car, R.; Parrinello, M. Phys. Rev. Lett. 1985, 55, 2471−2474. (31) Schwegler, E.; et al. J. Chem. Phys. 2004, 121, 5400−5409. (32) Cheng, L.; et al. Phys. Rev. Lett. 2001, 87, 156103. (33) Agmon, N. Acc. Chem. Res. 2012, 45, 63−73. (34) Carrasco, J.; Hodgson, A.; Michaelides, A. Nat. Mater. 2012, 11, 667−674. (35) Ho, T. A.; et al. Proc. Natl. Acad. Sci. U.S.A. 2011, 108, 16170− 16175.

was observed to vary significantly among hydrophobic surfaces, and this can be more significant than the difference deriving from the hydrophobicity. Employing an array of structural and dynamical analyses to understand the origin of the differences among the hydrophobic surfaces, it was shown that interfacial water dynamics is influenced strongly by atomistic details of the adsorbate molecules through spatial ordering that appears to alter the hydrogen bond ring network topology. In particular, water molecules diffuse significantly faster at the H−Si surface than at CH3− or CF3−Si surfaces because the hydrogen bond ring network formation is suppressed at those surfaces. The electrostatic potential generated by the adsorbate species appears to dictate the spatial water distribution in the first water layer. Such behavior is clearly noted for both metaland carbon-based surfaces in the literature.13,34 Interestingly, such a distinct long-range molecular behavior in the first water layer extends farther away (∼1 nm) because HB ring sizes are appreciable (4−5) in water. Our present study shows that longrange structural arrangements of water molecules are also important to dictate the dynamical behavior of water molecules at surfaces passivated by different hydrophobic molecules. The observed structural dependence on the dynamics of interfacial water is likely to be a universal character for a wide range of surfaces as a similar correlation between structural pattern and the water dynamics was also found for the hydrophilic surface.35 Therefore, the observed structure-dependent effects on water dynamics under confinement is likely to be generally important for designing nanoporous materials for a wide range of applications from nanofluidics to leaching.

■

ASSOCIATED CONTENT

S Supporting Information *

Figures showing the density and mean square displacement of water molecules at the Si surface passivated with CF 3 molecules, tilt angle distribution of the OH vector for the Hterminated surface and distribution of the OH vector 2.1 and 3.1 Å from the surface, probability of a specific orientation of water molecules in regions I and II, and tilt angle distribution of the OH vector at the CF3-terminated surface with two confining distances. This material is available free of charge via the Internet at http://pubs.acs.org.

■

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS D.L. and E.R. acknowledge support from the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering through FWP SCW1368. Y.K. gratefully acknowledges support by the donors of the Petroleum Research Fund, administered by the American Chemical Society, Grant 52494-DNI6 and National Energy Research Computing Center for computational resources. Part of the work was performed under the auspices of the U.S. Department of Energy at Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

■

REFERENCES

(1) Striolo, A. Adsorpt. Sci. Technol. 2011, 29, 211−258. 8513

dx.doi.org/10.1021/jp502850k | J. Phys. Chem. C 2014, 118, 8508−8513