Structure and Dynamics of N, N-Diethyl-N-methylammonium Triflate

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Structure and Dynamics of N,N-Diethyl-N-methylammonium Triflate Ionic Liquid, Neat and with Water, from Molecular Dynamics Simulations T. M. Chang,†,‡ Liem X. Dang,† R. Devanathan,† and M. Dupuis*,† Chemical and Materials Sciences DiVision, Pacific Northwest National Laboratory, Richland, Washington 99352, United States, and Department of Chemistry, UniVersity of WisconsinsParkside, Kenosha, Wisconsin 53141, United States ReceiVed: August 28, 2010; ReVised Manuscript ReceiVed: October 21, 2010

We investigated by means of molecular dynamics simulations the properties (structure, thermodynamics, ion transport, and dynamics) of the protic ionic liquid N,N-diethyl-N-methylammonium triflate (dema:Tfl) and of selected aqueous mixtures of dema:Tfl. This ionic liquid, a good candidate for a water-free proton exchange membrane, is shown to exhibit high ion mobility and conductivity. The radial distribution functions reveal a significant long-range structural correlation. The ammonium cations [dema]+ are found to diffuse slightly faster than the triflate anions [Tfl]-, and both types of ions exhibit enhanced mobility at higher temperatures, leading to higher ionic conductivity. Analysis of the dynamics of ion pairing clearly points to the existence of long-lived contact ion pairs. We also examined the effects of water through characterization of properties of dema:Tfl-water mixtures. Water molecules replace counterions in the coordination shell of both ions, thus weakening their association. As water concentration increases, water molecules start to connect with each other and then form a large network that percolates through the system. Water influences ion dynamics in the mixtures. As the concentration of water increases, both translational and rotational motions of [dema]+ and [Tfl]- are significantly enhanced. As a result, higher vehicular ionic conductivity is observed with increased hydration level. I. Introduction Room temperature ionic liquids (ILs) have attracted significant attention in recent years.1-6 The term “room temperature ionic liquids” refers to molten salts, generally consisting of large organic cations and inorganic anions, that are liquids near room temperature. The interest in this class of materials stems from their unique chemical and physical properties. Typically, ILs are nonflammable, have low vapor pressure, high ionic conductivity, and high chemical and electrochemical stability over a considerable temperature range. Because of their nonvolatile nature, ILs are widely used in many chemical processes while regarded as environmentally friendly. Given the broad range of anion-cation combinations, ILs have great potential to be tailored for specific applications and they are already used in many areas, including synthesis and catalysis, electrochemistry, carbon sequestration, and liquid-liquid extraction.7-13 A recently investigated potential application of ILs includes proton exchange membranes (PEMs).14-16 Bronsted acid-base ILs based on alkyl-substituted amines are being considered as potential water-free PEMs for low temperature fuel cells.17-19 In this context we are interested in understanding the proton transport ability and characteristics of this type of ILs. Proton transport in ILs is an intriguing proposal given the accepted belief that proton transport is critically dependent on the level of hydration of a molecular environment.20 In the case of ILs, at least of the type considered here, recent experimental studies suggest that the proton conductivity is mainly due to vehicular diffusion of the protonated amine ions.21-23 * To whom correspondence should be addressed, [email protected]. † Pacific Northwest National Laboratory. ‡ University of WisconsinsParkside.

Because of their promising properties and potential applications in fuel cells, protic ionic liquids have been studied extensively.15,17,18,24-36 Experimental techniques include spectroscopy, calorimetry, voltammetry, and neutron diffraction methods. Phase behavior, diffusivity, conductivity, and transport properties have been measured over a wide range of temperatures.12,37-41 These experimental studies contribute significantly to our understanding of ILs. However, because many experimental measurements are not able to directly probe molecular details, description of most ILs at the molecular level is still limited. Molecular modeling, on the other hand, provides an alternative approach to study ionic liquid systems.30,42-61 Both molecular dynamics (MD) and Monte Carlo methods are able to provide molecular information from an ensemble of molecular configurations, which can be linked to macroscopic thermodynamic or dynamic properties.54,62-69 A molecular level understanding of the structure, thermodynamics, and electrochemical properties of protic ILs may aid the development of electrolytes for fuel cell applications. The simple protic IL obtained from the combination of diethylmethylamine (dema) and trifluoromethanesulfonic acid (TfOH) (also called triflic acid Tfl) exhibited very good properties as a fuel cell electrolyte under nonhumidifying conditions, with a high and stable open-circuit potential and high thermal stability, over a wide liquid temperature range.17,21 This is one in a class of protic ILs consisting of combinations of Brønsted acids and bases that retain physical properties typical of ILs, such as thermal stability, low volatility, electrochemical stability, and high ionic conductivity. In these protic ILs, the Brønsted bases act as acceptors of the protons from the Brønsted acids and serve as proton carriers in the liquid. Recently, they have been shown to support high H2 oxidation and O2 reduction currents at Pt electrodes under nonhumidifying conditions at

10.1021/jp108189z  2010 American Chemical Society Published on Web 11/10/2010

Study of Room Temperature Ionic Liquids temperatures higher than 100 °C, a very desirable property for use as membranes in PEM fuel cells.14,15,17 Water is a product of the oxygen reduction reaction at the cathode of a fuel cell. It is thus desirable to understand the effect of water mixtures on the IL, how water affects its structure and dynamics and in particular proton diffusion. We report here on the structure, conductivity, and dynamics of dema:Tfl from MD simulations with the goal of obtaining a molecular level characterization of these properties. We also report on the same properties for dema:Tfl-water mixtures. In neat dema:Tfl, NMR data point to proton diffusion being vehicular by diffusion of the ammonium ion. This observation validates our use of a classical MD simulation model able to describe diffusion but not proton hopping. Water facilitates structural diffusion of proton conductivity in ammonia-based systems.70-72 Our focus here when considering the effect of water in these IL-water mixtures is to understand how water affects the ion pairing inherent to ILs and whether water (and then at what hydration level) percolates into the IL. We are not interested in accurately describing the combined vehicular/ structural diffusion of protons in IL-water mixtures per se, as experimentally, ILs as proton membranes involve nonhumidifying conditions. Thus we keep our focus on vehicular diffusion even in IL-water mixtures, a property well addressed by MD. Finally we note that diffusion has traditionally been a challenge to MD simulations when wanting highly accurate calculated diffusion constants. Calculated diffusion constants can be easily off by 1 order of magnitude and yet reproduce trends.73-77 Our calculated diffusion constants are off only by a factor of 2-3 because of our attention to the assignment of the force field parameters, an accuracy sufficient to extract semiquantitative understanding.49 The paper is organized as follows: in section II we give the computational details of the simulations. In section III we analyze the structure and dynamics of neat dema:Tfl. In section IV we describe our findings for mixtures of dema:Tfl with water. We summarize our findings in section V. II. Computational Details In this work we used the method of classical MD. In MD, the energy of a molecular system, i.e., an IL here, is described by a sum of Lennard-Jones, Coulombic, and intramolecular (bond, angle, and torsion) interactions. The [dema]+ and [Tfl]ion potentials were based on an all-atom framework, with fixed partial charges and Lennard-Jones parameters assigned to each atom. The partial charges of the [Tfl]- anions were taken from the DREIDING force field with modification,78 and those of the protonated amine cations were determined by fitting the electrostatic potential created at long range by a cation and calculated via quantum chemical calculations with the NWChem computational package.79,80 The intramolecular potential functions and potential parameters, i.e., bond distances, bond angles, and dihedral angles, were taken from the AMBER force fields.81 The Lennard-Jones parameters were also taken from the AMBER force fields.81 All these parameters were then slightly adjusted in order to reproduce the experimental density of [dema]+[Tfl]- at 303 K. The final potential parameters are given as Supporting Information. The SPC/E model was employed to describe water interactions.82 The cross Lennard-Jones interaction terms between unlike atoms are obtained using the Lorentz-Berthelot combining rules. The force fields described above and used in this study are classical pairwise additive force fields in contrast to more elaborate force fields, including polarizable force fields. Thermodynamic and structural properties are generally not very

J. Phys. Chem. A, Vol. 114, No. 48, 2010 12765 sensitive to the details of the potential models, and additive force fields are known to be capable of capturing polarization effects in an effective manner. Nonetheless polarizable force fields often give a better description of induced polarization. However, previous simulations on ILs with nonpolarizable force fields have been successful in providing useful insight into their properties even if the calculated absolute values of properties of ionic solutions in general depend on the force field parameters.83 Diffusion is notoriously difficult to obtain very accurately. In the present work we fine-tuned the potential parameters (the Lennard-Jones parameters) to obtain a density in good accord with experiment. As we will see below, the present set of parameters performed satisfactorily well, even for diffusion, in fact significantly better than other similar work on ILs.83 All all-atom computer simulations were carried out using the simulation package AMBER.84 MD simulations were performed on bulk melts of [dema]+[Tfl]- in the temperature range of 303-453K. All systems contained 256 ion pairs in a simulation cell of linear dimensions approximately equal to 43 × 43 × 43 Å. Periodic boundary conditions were applied in all three spatial directions. A molecular cutoff distance of 12 Å was used for Lennard-Jones interactions. The particle mesh Ewald method was employed to handle the long-range Coulombic interations.85,86 The simulations were initially equilibrated under an isothermalisobaric condition (NPT) at 1 atm for 1 ns, followed by 5 ns production runs to obtain liquid densities. The systems were then adjusted to maintain the average densities and further equilibrated in a constant volume-temperature (NVT) ensemble for 5 ns. Trajectories of 10 ns following equilibration were used for dynamical analysis. The temperature of the systems was maintained at the desired temperature using the Langevin dynamics thermostat.87,88 The SHAKE algorithm was used to constrain all the bonds involving hydrogen atoms. A time step of 2 fs was used to integrate the equations of motion. Seven different aqueous-ionic liquid mixtures were studied. Six mixtures contained 256 ion pairs with 16, 32, 64, 128, 256, and 512 water molecules, corresponding to water mole fractions of 0.059, 0.11, 0.20, 0.33, 0.50, and 0.67, respectively. The highest water fraction mixture of 0.80 was simulated with 200 ion pairs and 800 water molecules. The higher fraction mixtures corresponded to very large water contents, probably not relevant to the nonhumidifying PEM membrane conditions, yet it was informative to characterize them to assess the percolation behavior of water in this IL. Each system was equilibrated using the same protocol as described for the neat liquids, followed by a 10 ns trajectory for data analysis. All simulations were carried out under a constant temperature of 303 K. III. Neat Ionic Liquids A. Thermodynamics. As mentioned earlier, the potential parameters of [dema]+ and [Tfl]- were modified slightly to obtain the experimental density at 303 K. The same set of parameters was used to determine the melt properties at other temperatures. The predicted liquid densities are plotted in Figure 1, together with the enthalpies of vaporization of the ionic liquid, which can be evaluated by the following relation

∆Hvap ) Evap - Eliq + RT

(1)

where Evap and Eliq are the total potential energies of ion pairs in the vapor and liquid phases, respectively. These values are much higher than those of ordinary molecular solvents due to

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Figure 3. The decomposed atomic pair correlation functions between the [dema]+ and [Tfl]-. The data points correspond to N of cation-O of anion (circles), N of cation-F of anion (squares), H (attached to N) of cation-O of anion (diamonds), H of cation-F of anion (triangles), respectively. Figure 1. The computed liquid density of neat dema:Tfl as a function of temperature. The inset shows the enthalpy of vaporization as a function of temperature.

Figure 2. The calculated radial distribution functions of the center of mass of [dema]+[dema]+, [dema]+[Tfl]-, [Tfl]-[Tfl]- at temperatures of (a) 303 and (b) 453 K.

the strong electrostatic ionic interactions. The computed enthalpies of vaporization of neat [dema]+[Tfl]- are comparable to those of other ionic liquids.89,90 In the temperature range of 303-453 K, both liquid density and enthalpy of vaporization are observed to decrease roughly linearly with increasing temperature. B. Structural Properties. The local structural arrangements between ions were examined via radial distribution functions (RDFs). The RDFs of the cation-cation, cation-anion, and anion-anion distances are depicted in Figure 2 at 303 and 453 K. In this discussion, the center-of-mass of anions and cations was used in calculating the RDFs. There are distinct oscillations readily visible in these RDFs, indicating long-range spatial

correlations between ions. The most dominant feature in these RDFs is the sharp first peak between the cations and anions at ∼5 Å, evidence of a highly favored anion-cation association due to strong electrostatic attraction. The second and the third weaker peaks are also visible in the cation-anion RDFs, which suggests that the structural correlation is long-ranged. On the other hand, the first peaks of the cation-cation and anion-anion RDFs are much weaker and positioned at larger separations. Out-of-phase oscillations are observed between the cation-anion and cation-cation/anion-anion RDFs, which we attribute to alternating layers of cations and anions in the IL from the preferential ionic pairing, as will be discussed later. Interestingly, the first peak of anion-anion RDF is much broader than the cation-cation RDF, which may be caused by the orientational correlation between the anions. The features of charge layering in the RDF are broadly consistent with the structural details obtained in a previous MD study of ether-derivatized imidazolium-based room-temperature ILs.91 However, qualitative differences exist between these two systems. For example, the cation-cation RDFs are less pronounced than the anion-anion RDFs in ether-derivatized ILs. These results clearly suggest that the structure of ILs depends strongly on their chemical composition. As the temperature increases from 303 to 453 K, the major characteristics of the center-of-mass RDFs remain similar. The only noticeable difference is that peaks in the RDFs become broader and shift to larger separations. This clearly indicates that thermal fluctuations weaken the coordination structures in the IL. Shown in Figure 3 are the atomic RDFs decomposed between the N and acidic H (attached to N) atoms of [dema]+ and the F and O atoms of the [Tfl]- at 303 K. These RDFs exhibit complex features that we assign to the molecular orientational correlations. The most striking characteristic is the dominant first peak between the acidic cationic H atoms and the O atom of the anions at ∼2 Å. On the other hand, the first peak between cationic-H and anionic-F RDF is much weaker and occurs at much larger separation. Clearly, the acidic H of [dema]+ has a strong preference for coordination to the O atoms over F atoms of [Tfl]- and this is due to the negative charges attached to the sulfonate groups, yielding interactions that are stronger than the interactions with electrophilic fluorines. These RDFs demonstrate that there is a preferred cation-anion local structural arrangement with the acidic H atom hydrogen bonded to the sulfonate group. C. Dynamical/Transport Properties. The self-diffusion constants of [dema]+ and [Tfl]- were estimated from their mean-

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Figure 4. The self-diffusion coefficients of [dema]+ (circles) and [Tfl](squares) in neat dema:Tfl as a function of inverse temperature.

square displacements (MSD), 〈∆r2(t)〉, based on the Einstein relation

1 1 2〉 D ) lim 〈 | b(t) r - b(0)| r ) lim 〈∆b(t) r 2〉 tf∞ 6t tf∞ 6t

(2)

where b r (t) is the center-of-mass coordinate of the ion at time t, and 〈...〉 denotes an ensemble average. Because of the strong interionic forces, ILs exhibit slow translational motion when compared to other common molecular liquids. Therefore, long trajectories are required to observe the correct diffusive behavior of these ionic liquids.49,92 In a recent study Tsuzuki et al. showed that 3 ns simulations are adequate to extract reliably estimates of diffusion coefficients from MSD.74 Here we used 10 ns trajectories to extract the diffusion coefficients. The computed self-diffusion constants from MD simulations are plotted as a function of inverse temperature in Figure 4a. These calculated values are smaller than the experimental values by a factor between 2 and 3.21 This finding is consistent with the observation in the literature that nonpolarizable force fields typically yield diffusion coefficients too small, albeit results may be improved by including terms in the molecular force field that describe induced polarization.49 The accuracy reported here is sufficient for semiquantitative analysis. In fact we note that Tsuzuki et al.74 reported calculated self-diffusion constants about 1 order of magnitude smaller than experiment, consistently across a series of ILs, but that the trends were correctly reproduced. Not surprisingly, both ions display faster translational motion as temperature increases, with the self-diffusion coefficients going up faster at higher temperatures. The data in Figure 4a can be approximated by a linear curve, indicating that diffusion in these ionic liquids is an activated process. At low temperatures, despite the difference in ion size, the cation and anion mobility are very similar. This result is attributed to the strong ionic association as will be discussed later. For the temperature range studied, the cations diffuse slightly faster than the anions, in agreement with recent experimental observation.21 On the basis of experimental data, vehicular cation diffusion is thought to be the main mechanism for proton transport in a [dema]+[Tfl-] electrolyte.21,22 It is interesting to note that the ionic mobility is larger at higher temperatures, making [dema]+[Tfl-] useful in fuel cell application at moderate operating temperatures.

Figure 5. The self-diffusion coefficients of the N-H and C-H protons of [dema]+ and C-F fluorine of [Tfl]- in neat dema:Tfl as a function of inverse temperature.

In order to make direct comparison to the recently reported experimental diffusion on dema:Tfl21 we extracted the selfdiffusion coefficients of N-H and C-H protons of [dema]+ and the C-F fluorine of [Tfl]-. They are shown as a function of temperature in Figure 5. The values were extracted from the MSD of the specific atoms in the simulations. The experimental self-diffusion constants were determined from the PGSE-NMR measurements. As already mentioned, the diffusion constants obtained from simulations are smaller than the experimentally measured values. However, a general trend emerged in both experiments and simulationssthe atomic diffusion coefficient increases as temperature goes up and the [dema]+ protons diffuse faster than the C-F fluorine of [Tfl]- anion. To characterize the nature of the diffusion mechanism and to differentiate between vehicular diffusion and potential structural diffusion in the IL studied here, it is informative to examine the diffusivity of the N-H protons and of the C-H protons. Diffusivity of N-H protons might come from both vehicular and structural diffusion while diffusivity of C-H proton can only occur through the vehicular mechanism.21 In the NMR experiments, Watanabe and co-workers found the diffusion constants of the N-H and C-H protons to be very similar, indicating that the mechanism of proton transport in this dema:Tfl IL is mainly associated with vehicular proton transport. This observation validated our use of classical MD to describe the dema:Tfl system as there was no need to attempt to describe structural diffusion that would require vastly more complex simulation models. We evaluated also the transference number of the cation by dividing the N-H diffusion constant by the sum of the diffusion constants of C-H and C-F.21 The predicted values are in the range of 0.48-0.58, in reasonable agreement with the experimental results of 0.5-0.6. The transference number of the cation appears to increase with temperature, contrary to the experimental observation. A more definite assessment would require more accurate calculated diffusion constants. High ionic conductivity is one of the characteristics of protic ILs that make them attractive in fuel cell applications. To understand its temperature dependence, the ionic conductivity, Λ, of these systems was evaluated via the Einstein relation as

e2 Λ ) lim tf∞ 6tVkBT

N

∑ zizj〈[br i(t) - br i(0)][br j(t) - br j(0)]〉 ij

(3)

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Figure 6. The computed ionic conductivity Λ in dema:Tfl as a function of temperature. ΛNE is the conductivity obtained from Nernst-Einstein equation (see text).

where b ri (t) and zi are the center-of-mass coordinate at time t and the charge of the ith species, respectively. Here, N is the number of ions, 〈...〉 denotes an ensemble average, e is the electron charge, kB is the Boltzmann constant, T is the temperature, and V is the simulation volume. Shown in Figure 6 are the computed ionic conductivities, Λ, as a function of temperature. The computed values are smaller than the experimentally measured values of 53 mS/cm at 150 °C and 10 mS/ cm at room temperature.21 This result is consistent with the simulations underestimating the ionic mobility by a factor of 2-3, as pointed out earlier. In both simulations and experiments, the trend is clear that the ionic conductivity increases as temperature goes up, correlated with the faster ionic motions at higher temperatures. When the motion of cations and anions are uncorrelated, the ionic conductivity is directly related to the ionic diffusivity based on the Nernst-Einstein (NE) equation, which can be written as

ΛNE )

Ne2 + (D + D-) VkBT

(4)

Here, D+ and D- are the diffusion coefficients of the cation and anion, respectively. However, due to the strong electrostatic interactions, the ions may be strongly associated and this gives rise to correlated ionic motions. The degree of the ion association, ∆, can be evaluated as ∆ ) 1 - Λ/ΛΝE from MD simulations. The calculated values from our simulations are in the range of 0.45-0.10 and decrease as temperature goes up. Borodin and Smith have observed that the ionic conductivity of N-methyl-N-propylpyrrolidinium bis(trifluoromethanesulfonyl) imide was lowered by correlated ionic motion and that the ionic dynamics was slowed by strong electrostatic interactions.93 D. Dynamics of Ion Pairing. Part of the reason for the similar cationic and anionic translational motion in ionic liquids may come from the ion pairing; thus it is desirable to understand such behavior. The dynamics of ion pairing can be examined via the time autocorrelation function, which is defined as30,94-96 NC

R(t) )

NA

∑ ∑ 〈θ(rij, 0)θ(rij, t)〉

1 1 NC NA i)1

(5)

j)1

In eq 5, θ(r,t) is the Heavyside step function, which has a value of 1 when the particular ion pair, i and j, is associated and is

Figure 7. Time correlation functions for the ion pair association at different temperatures. The solid and dashed curves correspond to the continuous and intermittent autocorrelation functions, respectively.

zero when the two ions depart. NC is the number of [dema]+ ions, NA is the number of [Tfl]- ions that are bound to [dema]+, and t is the time. Here, we define the ions being paired if the acidic H(N) of the cation is within the first coordination shell of an oxygen atom of the [Tfl]- as established by the first minimum in the H-O atomic RDF. The time scale associated with ion pairing can then be estimated from these quantities. The time autocorrelation functions, R(t), are shown in Figure 7. Two types of R(t) are determined in the simulations. RC(t) refers to a continuous ion pair formation and does not allow for temporary dissociation in the interim of the interval. RI(t) corresponds to the correlation functions that allow for the breaking and re-forming of ion pairs. By examining the behavior of RC(t) and RI(t), it is clear that ion pair recombination is prevalent in this IL. It is also found that the time scale for ion pair dissociation can exceed tens or even hundreds of picoseconds. For example, only about half of the ion pairs break up for the first time after 80 ps at 303 K and many of them recombine. In addition, cluster formation of these ions is also feasible and has been observed in some ILs.97-99 The long lifetime associated with ion pairs or clusters may partially explain the similarity in the diffusive motion of the cations and anions near room temperature. A carefully chosen IL with shorter-lived ion pairs may increase the diffusivity and eventually lead to a better conducting electrolyte. Temperature is found to exhibit significant influence on the dynamics of ion pairing. As temperature increases, the autocorrelation functions decay appreciably faster, leading to a much shorter lifetime of the contact ion pair. At 453 K, half of the ion pairs start to dissociate after only about 18 ps, which is 4 times shorter than that at 303 K. The probability of recombination also decreases with rising temperatures. IV. Aqueous Mixtures A. Thermodynamics. Seven different aqueous-ionic liquid mixtures were studied, corresponding to water mole fraction of xW ) 0.059, 0.11, 0.20, 0.33, 0.50, 0.67 (16, 32, 64, 128, 256, 512 water molecules for 256 ion pairs in the simulation respectivelyssee above), and 0.80 (200 ion pairs with 800 water molecules). The computed densities of these aqueous mixtures are shown in Figure 8, together with the excess molar volume of mixing as a function of water mole fraction. At low water concentrations, the solution density varies only slightly, because



Figure 8. The calculated solution density of dema:Tfl-water mixtures as a function of water mole fraction, xw. Displayed in the inset are the excess molar volumes.

of the small mole fraction. Under the circumstances water is in the form of water monomers or dimers intercalated between anions and cations. As the water mole fraction increases, the density decreases rapidly to the bulk water density. Clearly, this nonlinear behavior demonstrates the nonideality of these mixtures. The nonideality of the ionic liquid-water solutions can be further characterized by the excess molar properties. The excess molar volumes of mixing show negative deviations from the ideal behavior over the range of water fraction. This result may be attributed to the attractive interactions between the IL and water. Nonetheless, these excess volumes are small compared to the bulk molar volumes. Both negative and positive deviations in excess molar volumes of mixing have been observed from simulations of aqueous IL solutions.56,100 B. Structural Properties. To study the effects of water on the dema:Tfl liquid structure, the cation-cation, cation-anion, and anion-anion center-of-mass radial distribution functions (RDFs) were calculated for several water compositions and are shown in Figure 9. Two points are noted from these figures. First, well-defined features are observed in these RDFs even at high water concentrations, suggesting the persistence of longrange spatial correlations between these ions. Second, as water percentage increases, the broadening of the peaks and the shifts in the peak positions of these RDFs clearly demonstrate that water molecules indeed play a significant role in altering the IL structure. In addition, water is found to have a different effect on the cation-cation structure than on the anion-anion structure. By introducing water molecules into the ionic liquid, the first peak of the cation-cation RDF (panel a, Figure 9) shifts to larger distances and eventually merges with the second peak, while the first peak of the anion-anion RDF (panel c, Figure 9) broadens and shifts to smaller separations. This behavior indicates that water molecules have reduced the cation-cation correlations. There is also a broadening of the anion-cation RDF (panel b, Figure 9), suggesting that the strong cation-anion association is weakened by the presence of water molecules. Snapshots from the simulation for three mole fractions (low, medium, high) are shown in Figure 10. At low mole fraction the water molecules are shown to be in the form of monomers (Figure 10a) intercalated between anions and cations (Figure 10b), and in the form of dimers also intercalated (Figure 10c), then in the form of small clusters (Figure 10d), until a water network starts to develop at medium mole fraction, with a percolated water network at high mole fraction (Figure 10e).

Figure 9. The (a) cation-cation, (b) cation-anion, and (c) anion-anion radial distribution function at 303 K. The fours curves correspond to the different water mole fraction, xW ) 0.059 (circles), 0.20 (squares), 0.50 (diamonds), and 0.80 (triangles), respectively.

Figure 11 gives a close-up view of the low mole fraction xW ) 0.20 configuration. The layered structure character of the IL stands out in this picture. The spatial correlation between water and ions was also investigated. Displayed in Figure 12 are the radial distribution functions between O of water and acidic H (attached to N) of [dema]+ as well as between H of water and S of the [Tfl]-. These atomic RDFs exhibit distinct features, representative of the presence of well-defined solvation structures. In particular, the pronounced first peaks of the O(w)-H(N) and H(w)-O(S) RDFs at ∼2 Å are due to direct interactions between water and ions. The heights of these peaks are found to decrease significantly with increasing water concentration, again indicative of strong water-ion interactions in dilute situations. This observation clearly points to the tendency of water to replace the counterions in the first coordination shell of the [dema]+ and [Tfl]- ions. C. Ion-Water Structure and Interactions. To gain insight to the effects of hydration level on the proton transport in this IL, we examined the ion-water bonding patterns (hydrogen bonds) and the cluster formation by water molecules in the IL-water mixtures, which can play an important role in protic ionic liquids.101 Here, a geometric criterion was used to define “hydrogen bond”. Two species are considered hydrogen bonded when the intermolecular O-O distance is less than 3.5 Å, the O-H distance is less than 2.6 Å, and the O-H-O angle is

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Figure 10. Snapshots of dema:Tfl-water mixtures for mole fractions (a) xW ) 0.059, (d) xW ) 0.20, and (e) xW ) 0.50. A water monomer and a water dimer intercalated between [dema]+ and [Tfl]- are shown in panels b and c. In addition to showing the structure (dispersed or percolated) of the water network, the snapshots reveal the layered structure of the IL with blue regions representing the [Tfl]- ions separated by green regions representing the [dema]+ cations.

Figure 11. Close-up snapshot of a configuration of dema:Tfl-water mixture for mole fraction xW ) 0.20. The dispersed water molecules can be seen; the layered structure stands out, with pink layers of [Tfl]and green layers of [dema]+.

greater than 125°. The probability distributions of finding an ion that is hydrogen bonded to a varying number of water molecules is displayed in Figure 13 at xW ) 0.059, 0.20, 0.50, and 0.80 for the [dema]+ and [Tfl]- ions, respectively (16, 64, 256 water molecules in the simulation for 256 ion pairs, and 800 water molecules for 200 ion pairs in the last xW). As the water concentration increases, the ions are found to include more water molecules in their coordination shell. This trend is most noticeable for anions. Even at the lowest water concentration

Chang et al.

Figure 12. The atomic pair correlation functions between the [dema]+-H2O and [Tfl]--H2O. The RDFs are between (a) O of water and H (attached to N) of cations and (b) H of water and O of anions. The fours curves correspond to the different water mole fractions, xW ) 0.059 (circles), 0.20 (squares), 0.50 (diamonds), and 0.80 (triangles), respectively.

of xW ) 0.059, 10% of [Tfl]- are hydrogen bonded to at least one water molecule. At the highest water mole fraction (xW ) 0.80), less than 2% of [Tfl]- are free of hydrogen bonds with water. These results clearly demonstrate the strong affinity of water to [Tfl]- ions owing to the ability of [Tfl]- to form multiple hydrogen bonds with water. In addition to the ion-water interactions, we also studied the cluster formation of water molecules in these solutions. Two water molecules are considered to be in the same cluster when their O-O distance is less than 3.5 Å. Figure 14 gives the probability of finding water molecules participating in clusters of various sizes. When the hydration level is low (less than xW ) 0.50), most water molecules are isolated from each other and do not form large clusters. As water concentrations increase, the water molecules start to connect with each other and form clusters of finite sizes. For mole fraction xW ) 0.50 solution, only about 20% of water molecules are isolated. At the highest level of mole fraction (xW ) 0.80), it is found that most of the water molecules belong to one percolating cluster and only 2% of water molecules are completely isolated from the rest of water molecules. The water network developing with increasing water mole fraction is found to have a significant impact on the ion mobility, as will be discussed below. D. Dynamical/Transport Properties. To understand the effect of water on the dynamics of [dema]+ and [Tfl]- ions, we analyzed the self-diffusion coefficients and orientational autocorrelation functions of [dema]+ and [Tfl]- ions in the IL-water mixtures. Figure 15 shows the self-diffusion coefficients of [dema]+, [Tfl]-, and water as a function of water mole fraction. These diffusion constants were extracted from mean-square displacements. In general, both ions show similar diffusivity



Figure 15. The self-diffusion coefficients of [dema]+ (circles), and [Tfl]- (×), and water (diamonds) in the aqueous dema:Tfl mixtures as a function of water mole fraction xW.

Figure 13. Probability of (a) [dema]+ and (b) [Tfl]- that are hydrogen bonded to different number of water molecules plotted against the number of hydrogen bonds per ion.

the composition of xW ) 0.50 is also when the water molecules start to form large clusters that percolate through the system. The impact on the dynamics of the contact ion pair formation by water was examined via the time correlation function, R(t). At low mole fraction (xW < 0.11) (data not shown), water does not play a significant role in the ion pairing process. At the same time, the enhancement of the ionic diffusivity is limited. As the hydration level increases, the contact ion pair is weakened, which leads to shorter time scale for ion dissociation. As mentioned earlier, about 50% of contact ion pairs start to break up after 80 ps in the neat IL. In contrast, in the case of the highest water concentration (xW ) 0.80), it takes only 19 ps for the same percentage of ion pairssclearly demonstrating a substantial influence of water on the ionic association process. In a recent study, Spohr and Patey examined the physical reason for water’s impact on transport properties in ionic liquids.69 They found that the influence depends on the type of ionic liquid and the dominant effect of water is dynamical in origin. As water molecules are introduced into the ionic liquids, they replace the heavier counterion from the solvation shell and reduce the effects of caging, leading to increased mobility. Our results corroborate their conclusions. We also studied how the rotational motion of [dema]+ and [Tfl]- ions is affected by the presence of water. The reorientation of [dema]+ and [Tfl]- in aqueous solution was examined via the orientational autocorrelation functions

Cl(t) ) 〈Pl[u b(0) · b u (t)]〉

Figure 14. Probability of water molecules to belong to clusters of different size as a function of cluster size.

over the water concentration range, indicative of the correlated motion of the ions and of their pairing, even at high water mole fraction.102,103 Similar behavior has also been observed for other IL-water systems.100 Water facilitates the translational motion of both ions as determined by the larger diffusion constants with higher level of hydration. Water molecules shield the electrostatic attractions between ions and weaken the structural organization of these IL-water mixtures. The increase in the ion mobility is small at low water concentrations but goes up more quickly around xW ) 0.70. A similar trend is observed for the translational motion of the water molecules with the sharp increase occurring at a mole fraction of xW ) 0.50. Interestingly,

(6)

u (t) is the Here, Pl denotes the lth Legendre polynomial, and b body-fixed unit vector along any specified axis at time t. The averaged orientational autocorrelation functions, Cl(t), from the N-H bond vector of [dema]+ and C-S bond vector of [Tfl]are computed and shown in Figure 16 at several water fractions. In general, these correlation functions can be approximated by exponential decay functions after an initial inertial behavior that occurs within 1 ps. Slow decay of these correlation functions are noticed here. This result is expected because of the strong intermolecular attraction in these IL-water mixtures that hinders the rotational motion of these ions. The rotational diffusion constants can be estimated from the asymptotic decay of these C1(t) curves at long times and are found to range from ∼2.5 ns in the neat ionic liquid to ∼0.3 ns in the xW ) 0.80 solution. These rotational time scales are slightly larger than those reported for imidazolium based ionic liquids.45,54,61 This result

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Chang et al. under humid conditions. We note that under such conditions, proton transport would not be limited to vehicular diffusion since water catalyzes proton exchange in ammonia-based liquids. Structural diffusion would come into play that would require a more complex treatment of diffusion at the molecular level (ability to break/form N-H and H-O bonds).72 V. Conclusions

Figure 16. The normalized rotational autocorrelation functions of (a) the N-H vector of [dema]+ and (b) O-C vector of [Tfl]- in dema: Tfl-water mixtures.

Figure 17. The computed ionic conductivity of dema:Tfl-water mixtures as a function of water mole fraction.

demonstrates that the presence of water molecules has substantial impact on the rotational motion of ions. By replacing the heavier counterions in the solvation shell, ions experience a diminished caging effect and may be able to rotate more freely. For comparison, the orientation autocorrelation functions for the molecular C2V axis and O-O bond vector of water molecules were also computed (data not shown). In general, water rotates much faster than the ions, which is expected due to its much smaller steric hindrance. The computed ionic conductivity as a function of water concentration is shown in Figure 17. It is apparent that the conductivity of the system increases with the increasing hydration level, which is due to the enhanced (vehicular) ion mobility. In addition, the degree of ion correlation is found to decrease as water concentration goes up. These results may indicate the feasibility of using dema:Tfl for PEM membrane

Using classical MD simulation techniques, we investigated the Bronsted acid-base ionic liquid of dema:Tfl. We examined the structures, thermodynamics, and dynamical and transport properties of the neat IL. In addition, we carried out a series of simulations to study aqueous mixtures of this IL to understand the influence of water on the diffusion dynamics of ammonium and triflate ions. In the bulk liquids, we observed that the bulk liquid density and enthalpy of vaporization decrease roughly linearly with increasing temperature in the range of 303-453 K. The calculated partial radial distribution functions exhibited welldefined structures, suggesting that there is a preferred long-range structural correlation between these ions resulting from charge ordering. We also examined the dynamical properties of the ions as a function of temperature. We computed the ion selfdiffusion constants from the mean-square displacements of the center-of-mass of ions. We found that the ammonium cations diffuse slightly faster than the triflate anions. At higher temperatures, both ions exhibited enhanced mobility, in accord with experiment. The higher ionic diffusivity leads to an increased conductivity of bulk dema:Tfl melts. We also found long-lived contact ion pair in the neat liquids. For the IL-water mixtures, we studied several mixtures corresponding to various mole fractions. As expected, the IL and water form nonideal solutions. From the radial distribution functions, we observed that the water molecules form a distinct solvation shell around the cations and anions and weaken their mutual association. The analysis of hydrogen bonding patterns revealed that the number of water hydrogen bonds per ion increases with increasing water concentrations. At low water content, water molecules were observed to be isolated from each other while bound strongly to the ions through hydrogen bonds. As water percentage increases, the water molecules started to cluster with each other to eventually form a large network that percolates through the system. This behavior was accompanied by a notable change in the ion dynamics. To study the effects of water on the transport properties in these mixtures, the selfdiffusion constants were also calculated. As the proportion of water increases, the translational motion of both ions is enhanced and the time scale for the ion pair dissociation decreases. We also evaluated the orientational autocorrelation function of the [dema]+ and [Tfl]- and determined that the rotational motion of both ions becomes faster with increased hydration level. As a result, the conductivity of the dema:Tfl-water mixtures increases at higher water compositions. Acknowledgment. This work was supported by the U.S. Department of Energy’s (DOE) Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences under Contract DE-AC05-76RL01830. It was performed in part using the Molecular Science Computing Facility (MSCF) in the EMSL, a national scientific user facility sponsored by DOE’s Office of Biological and Environmental Research located at Pacific Northwest National Laboratory (PNNL). PNNL is operated by Battelle for DOE. This work benefited also from resources of the National Energy Research Scientific Computing

Study of Room Temperature Ionic Liquids Center, which is supported by the Office of Science of DOE under Contract No. DE-AC02-05CH1123. Supporting Information Available: A figure of partial charges and atom types for the molecular models used in this work and table of potential parameters for the molecular models used in this work. This material is available free of charge via the Internet at http://pubs.acs.org. References and Notes (1) Rogers, R. D.; Seddon, K. R. Science 2003, 302, 792. (2) Wasserscheid, P. Nature 2006, 439, 797. (3) Welton, T. Chem. ReV. 1999, 99, 2071. (4) Dupont, J.; de Souza, R. F.; Suarez, P. A. Z. Chem. ReV. 2002, 102, 3667. (5) Wishart, J. F.; Castner, E. W. J. Phys. Chem. B 2007, 111, 4639. (6) Hermann, W. Angew. Chem., Int. Ed. 2008, 47, 654. (7) Wang, P.; Zakeeruddin, S. M.; Comte, P.; Exnar, I.; Gratzel, M. J. Am. Chem. Soc. 2003, 125, 1166. (8) Martins, M. A. P.; Frizzo, C. P.; Moreira, D. N.; Zanatta, N.; Bonacorso, H. G. Chem. ReV. 2008, 108, 2015. (9) Huddleston, J. G.; Willauer, H. D.; Swatloski, R. P.; Visser, A. E.; Rogers, R. D. Chem. Commun. 1998, 1765. (10) Pennline, H. W.; Granite, E. J.; Luebke, D. R.; Kitchin, J. R.; Landon, J.; Weiland, L. M. Fuel , 89, 1307. (11) Wilkes, J. S.; Levisky, J. A.; Wilson, R. A.; Hussey, C. L. Inorg. Chem. 1982, 21, 1263. (12) Buzzeo, M. C.; Evans, R. G.; Compton, R. G. ChemPhysChem 2004, 5, 1106. (13) Chiappe, C.; Pieraccini, D. J. Phys. Org. Chem. 2005, 18, 275. (14) Sekhon, S. S.; Krishnan, P.; Singh, B.; Yamada, K.; Kim, C. S. Electrochim. Acta 2006, 52, 1639. (15) Nakamoto, H.; Noda, A.; Hayamizu, K.; Hayashi, S.; Hamaguchi, H.; Watanabe, M. J. Phys. Chem. C 2007, 111, 1541. (16) MacFarlane, D. R.; Seddon, K. R. Aust. J. Chem. 2007, 60, 3. (17) Nakamoto, H.; Watanabe, M. Chem. Commun. 2007, 2539. (18) Belieres, J. P.; Gervasio, D.; Angell, C. A. Chem. Commun. 2006, 4799. (19) Mitsushima, S.; Shinohara, Y.; Matsuzawa, K.; Ota, K. Electrochim. Acta, in press. (20) Devanathan, R.; Venkatnathan, A.; Dupuis, M. J. Phys. Chem. B 2007, 111, 8069. (21) Lee, S.-Y.; Ogawa, A.; Kanno, M.; Nakamoto, H.; Yasuda, T.; Watanabe, M. J. Am. Chem. Soc. 2010, 9764. (22) Fernicola, A.; Panero, S.; Scrosati, B.; Tamada, M.; Ohno, H. ChemPhysChem 2007, 8, 1103. (23) Mori, K.; Hashimoto, S.; Yuzuri, T.; Sakakibara, K. Bull. Chem. Soc. Jpn. 2010, 83, 328. (24) Noda, A.; Susan, A. B.; Kudo, K.; Mitsushima, S.; Hayamizu, K.; Watanabe, M. J. Phys. Chem. B 2003, 107, 4024. (25) Susan, M.; Noda, A.; Mitsushima, S.; Watanabe, M. Chem. Commun. 2003, 938. (26) Kanzaki, R.; Song, X. D.; Umebayashi, Y.; Ishiguro, S. Chem. Lett. 2010, 39, 578. (27) Martinelli, A.; Matic, A.; Jacobsson, P.; Borjesson, L.; Fernicola, A.; Panero, S.; Scrosati, B.; Ohno, H. J. Phys. Chem. B 2007, 111, 12462. (28) Anouti, M.; Caillon-Caravanier, M.; Dridi, Y.; Jacquemin, J.; Hardacre, C.; Lemordant, D. J. Chem. Thermodyn. 2009, 41, 799. (29) Yasuda, T.; Ogawa, A.; Kanno, M.; Mori, K.; Sakakibara, K.; Watanabe, M. Chem. Lett. 2009, 38, 692. (30) Zahn, S.; Thar, J.; Kirchner, B. J. Chem. Phys. 2010, 132. (31) Anouti, M.; Vigeant, A.; Jacquemin, J.; Brigouleix, C.; Lemordant, D. J. Chem. Thermodyn. , 42, 834. (32) Seki, S.; Ohno, Y.; Miyashiro, H.; Kobayashi, Y.; Usami, A.; Mita, Y.; Terada, N.; Hayamizu, K.; Tsuzuki, S.; Watanabe, M. J. Electrochem. Soc. 2008, 155, A421. (33) Yoshizawa, M.; Xu, W.; Angell, C. A. J. Am. Chem. Soc. 2003, 125, 15411. (34) Bautista-Martinez, J. A.; Tang, L.; Belieres, J. P.; Zeller, R.; Angell, C. A.; Friesen, C. J. Phys. Chem. C 2009, 113, 12586. (35) Belieres, J. P.; Angell, C. A. J. Phys. Chem. B 2007, 111, 4926. (36) Angell, C. A.; Byrne, N.; Belieres, J. P. Acc. Chem. Res. 2007, 40, 1228. (37) Doyle, M.; Choi, S. K.; Proulx, G. J. Electrochem. Soc. 2000, 147, 34. (38) Kreuer, K. D.; Paddison, S. J.; Spohr, E.; Schuster, M. Chem. ReV. 2004, 104, 4637. (39) Greaves, T. L.; Drummond, C. J. Chem. ReV. 2008, 108, 206. (40) Jeon, Y.; Sung, J.; Seo, C.; Lim, H.; Cheong, H.; Kang, M.; Moon, B.; Ouchi, Y.; Kim, D. J. Phys. Chem. B 2008, 112, 4735.

J. Phys. Chem. A, Vol. 114, No. 48, 2010 12773 (41) Iimori, T.; Iwahashi, T.; Ishii, H.; Seki, K.; Ouchi, Y.; Ozawa, R.; Hamaguchi, H.; Kim, D. Chem. Phys. Lett. 2004, 389, 321. (42) Rivera-Rubero, S.; Baldelli, S. J. Am. Chem. Soc. 2004, 126, 11788. (43) Schroder, C.; Steinhauser, O. J. Chem. Phys. 2008, 128. (44) Raabe, G.; Koehler, J. J. Chem. Phys. 2008, 128. (45) Qiao, B.; Krekeler, C.; Berger, R.; Delle Site, L.; Holm, C. J. Phys. Chem. B 2008, 112, 1743. (46) Lynden-Bell, R. M.; Del Popolo, M. G.; Youngs, T. G. A.; Kohanoff, J.; Hanke, C. G.; Harper, J. B.; Pinilla, C. C. Acc. Chem. Res. 2007, 40, 1138. (47) Urahata, S. M.; Ribeiro, M. C. C. J. Chem. Phys. 2004, 120, 1855. (48) Bhargava, B. L.; Balasubramanian, S. J. Chem. Phys. 2006, 125, 219901. (49) Yan, T. Y.; Burnham, C. J.; Del Popolo, M. G.; Voth, G. A. J. Phys. Chem. B 2004, 108, 11877. (50) Wu, X. P.; Liu, Z. P.; Huang, S. P.; Wang, W. C. Phys. Chem. Chem. Phys. 2005, 7, 2771. (51) Wang, Y.; Jiang, W.; Yan, T.; Voth, G. A. Acc. Chem. Res. 2007, 40, 1193. (52) Liu, Z. P.; Huang, S. P.; Wang, W. C. J. Phys. Chem. B 2004, 108, 12978. (53) Lee, S. U.; Jung, J.; Han, Y.-K. Chem. Phys. Lett. 2005, 406, 332. (54) Kelkar, M. S.; Maginn, E. J. J. Phys. Chem. B 2007, 111, 4867. (55) Hunt, P. A. Molec. Simul. 2006, 32, 1. (56) Hanke, C. G.; Lynden-Bell, R. M. J. Phys. Chem. B 2003, 107, 10873. (57) Ghatee, M. H.; Ansari, Y. J. Chem. Phys. 2007, 126. (58) Del Popolo, M. G.; Lynden-Bell, R. M.; Kohanoff, J. J. Phys. Chem. B 2005, 109, 5895. (59) de Andrade, J.; Boes, E. S.; Stassen, H. J. Phys. Chem. B 2002, 106, 13344. (60) Buhl, M.; Chaumont, A.; Schurhammer, R.; Wipff, G. J. Phys. Chem. B 2005, 109, 18591. (61) Chang, T. M.; Dang, L. X. J. Phys. Chem. A 2009, 113, 2127. (62) Lopes, J. N. C.; Deschamps, J.; Padua, A. A. H. J. Phys. Chem. B 2004, 108, 2038. (63) Lopes, J. N. C.; Padua, A. A. H. J. Phys. Chem. B 2006, 110, 19586. (64) Maginn, E. J. Acc. Chem. Res. 2007, 40, 1200. (65) Margulis, C. J.; Stern, H. A.; Berne, B. J. J. Phys. Chem. B 2002, 106, 12017. (66) Cadena, C.; Anthony, J. L.; Shah, J. K.; Morrow, T. I.; Brennecke, J. F.; Maginn, E. J. J. Am. Chem. Soc. 2004, 126, 5300. (67) Castner, E. W.; Wishart, J. F.; Shirota, H. Acc. Chem. Res. 2007, 40, 1217. (68) Sieffert, N.; Wipff, G. J. Phys. Chem. B 2007, 111, 4951. (69) Spohr, H. V.; Patey, G. N. J. Chem. Phys. 2010, 132. (70) Luz, Z.; Meiboom, S. J. Chem. Phys. 1963, 39, 366. (71) Clutter, D. R.; Swift, T. J. J. Am. Chem. Soc. 1968, 90, 601. (72) Lagodzinskaya, G. V.; Yunda, N. G.; Manelis, G. B. Chem. Phys. 2002, 282, 51. (73) Del Popolo, M. G.; Voth, G. A. J. Phys. Chem. B 2004, 108, 1744. (74) Tsuzuki, S.; Shinoda, W.; Saito, H.; Mikami, M.; Tokuda, H.; Watanabe, M. J. Phys. Chem. B 2009, 113, 10641. (75) Bhargava, B. L.; Balasubramanian, S. J. Chem. Phys. 2005, 123. (76) Urahata, S. M.; Ribeiro, M. C. C. J. Chem. Phys. 2005, 122. (77) Hanke, C. G.; Price, S. L.; Lynden-Bell, R. M. Mol. Phys. 2001, 99, 801. (78) Mayo, S. L.; Olafson, B. D.; Goddard, W. A. J. Phys. Chem. 1990, 94, 8897. (79) Kendall, R. A.; Apra, E.; Bernholdt, D. E.; Bylaska, E. J.; Dupuis, M.; Fann, G. I.; Harrison, R. J.; Ju, J. L.; Nichols, J. A.; Nieplocha, J.; Straatsma, T. P.; Windus, T. L.; Wong, A. T. Comput. Phys. Commun. 2000, 128, 260. (80) Bylaska, E. J.; de Jong, W. A.; Govind, N.; Kowalski, K.; Straatsma, T. P.; Valiev, M.; Wang, D.; Apra, E.; Windus, T. L.; Hammond, J.; Nichols, P.; Hirata, S.; Hackler, M. T.; Zhao, Y.; Fan, P.-D.; Harrison, R. J.; Dupuis, M.; Smith, D. M. A.; Nieplocha, J.; Tipparaju, V.; Krishnan, M.; Wu, Q.; Van Voorhis, T.; Auer, A. A.; Nooijen, M.; Brown, E.; Cisneros, G.; Fann, G. I.; Fruchtl, H.; Garza, J.; Hirao, K.; Kendall, R.; Nichols, J. A.; Tsemekhman, K.; Wolinski, K.; Anchell, J.; Bernholdt, D.; Borowski, P.; Clark, T.; Clerc, D.; Dachsel, H.; Deegan, M.; Dyall, K.; Elwood, D.; Glendening, E.; Gutowski, M.; Hess, A.; Jaffe, J.; Johnson, B.; Ju, J.; Kobayashi, R.; Kutteh, R.; Lin, Z.; Littlefield, R.; Long, X.; Meng, B.; Nakajima, T.; Niu, S.; Pollack, L.; Rosing, M.; Sandrone, G.; Stave, M.; Taylor, H.; Thomas, G.; van Lenthe, J.; Wong, A.; , Zhang, Z. NWChem, A Computational Chemistry Package for Parallel Computers, Version 5.1; Pacific Northwest National Laboratory, Richland, WA, 2007.

12774


(81) Cornell, W. D.; Cieplak, P.; Bayly, C. I.; Gould, I. R.; Merz, K. M.; Ferguson, D. M.; Spellmeyer, D. C.; Fox, T.; Caldwell, J. W.; Kollman, P. A. J. Am. Chem. Soc. 1995, 117, 5179. (82) Berendsen, H. J. C.; Grigera, J. R.; Straatsma, T. P. J. Phys. Chem. 1987, 91, 6269. (83) Kalcher, I.; Dzubiella, J. J. Chem. Phys. 2009, 130, 12. (84) Case, D. A.; Darden, T. A.; Cheatham, I., T.E.; Simmerling, C. L.; Wang, J.; Duke, R. E.; Luo, R.; Merz, K. M.; Pearlman, D. A.; Crowley, M.; Walker, R. C.; Zhang, W.; Wang, B.; Hayik, S.; Roitberg, A.; Seabra, G.; Wong, K. F.; Paesani, F.; Wu, X.; Brozell, S.; Tsui, V.; Gohlke, H.; Yang, L.; Tan, C.; Mongan, J.; LHornak, V.; Cui, G.; Beroza, P.; Mathews, D. H.; Schafmeister, C.; Ross, W. S.; Kollman, P. A. AMBER 9; University of California, San Francisco, 2006. (85) Darden, T.; York, D.; Pedersen, L. J. Chem. Phys. 1993, 98, 10089. (86) Essmann, U.; Perera, L.; Berkowitz, M. L.; Darden, T.; Lee, H.; Pedersen, L. G. J. Chem. Phys. 1995, 103, 8577. (87) Pastor, R. W.; Brooks, B. R.; Szabo, A. Mol. Phys. 1988, 65, 1409. (88) Izaguirre, J. A.; Catarello, D. P.; Wozniak, J. M.; Skeel, R. D. J. Chem. Phys. 2001, 114, 2090. (89) Koddermann, T.; Paschek, D.; Ludwig, R. ChemPhysChem 2008, 9, 549. (90) Fumino, K.; Wulf, A.; Verevkin, S. P.; Heintz, A.; Ludwig, R. ChemPhysChem 2010, 11, 1623.

Chang et al. (91) Smith, G. D.; Borodin, O.; Li, L. Y.; Kim, H.; Liu, Q.; Bara, J. E.; Gin, D. L.; Nobel, R. Phys. Chem. Chem. Phys. 2008, 10, 6301. (92) Bagno, A.; D’Amico, F.; Saielli, G. J. Mol. Liq. 2007, 131, 17. (93) Borodin, O.; Smith, G. D. J. Phys. Chem. B 2006, 110, 11481. (94) Garcia, A. E.; Stiller, L. J. Comput. Chem. 1993, 14, 1396. (95) Impey, R. W.; Madden, P. A.; McDonald, I. R. J. Phys. Chem. 1983, 87, 5071. (96) Luzar, A.; Chandler, D. Nature 1996, 379, 55. (97) Kennedy, D. F.; Drummond, C. J. J. Phys. Chem. B 2009, 113, 5690. (98) Ludwig, R. J. Phys. Chem. B 2009, 113, 15419. (99) Triolo, A.; Russina, O.; Bleif, H. J.; Di Cola, E. J. Phys. Chem. B 2007, 111, 4641. (100) Moreno, M.; Castiglione, F.; Mele, A.; Pasqui, C.; Raos, G. J. Phys. Chem. B 2008, 112, 7826. (101) Fumino, K.; Wulf, A.; Ludwig, R. Phys. Chem. Chem. Phys. 2009, 11, 8790. (102) Rollet, A. L.; Porion, P.; Vaultier, M.; Billard, I.; Deschamps, M.; Bessada, C.; Jouvensal, L. J. Phys. Chem. B 2007, 111, 11888. (103) Fraser, K. J.; Izgorodina, E. I.; Forsyth, M.; Scott, J. L.; MacFarlane, D. R. Chem. Commun. 2007, 3817.

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