Physical Properties and Hydrogen-Bonding Network of Water–Ethanol

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Physical Properties and Hydrogen-Bonding Network of WaterEthanol Mixtures from Molecular Dynamics Simulations Aziz Ghoufi, Franck Artzner, and Patrice Malfreyt J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.5b11776 • Publication Date (Web): 08 Jan 2016 Downloaded from http://pubs.acs.org on January 15, 2016

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Physical Properties and Hydrogen-Bonding Network of Water-Ethanol Mixtures from Molecular Dynamics Simulations A. Ghoufi ,∗,† F. Artzner ,† and P. Malfreyt‡ Institut de Physique de Rennes, UMR 6251 CNRS, Université de Rennes 1, 263 avenue Général Leclerc, 35042 Rennes, France., and Institut de Chimie de Clermont-Ferrand, ICCF, UMR CNRS 6296, BP 10448, F-63000 Clermont-Ferrand. E-mail: [email protected]



To whom correspondence should be addressed Institut de Physique de Rennes, UMR 6251 CNRS, Université de Rennes 1, 263 avenue Général Leclerc, 35042 Rennes, France. ‡ Institut de Chimie de Clermont-Ferrand, ICCF, UMR CNRS 6296, BP 10448, F-63000 ClermontFerrand. †

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Abstract While many numerical and experimental works were focused on water-ethanol mixtures at low ethanol concentration, this work reports predictions of a few physical properties (thermodynamical, interfacial, dynamical and dielectrical properties) of water-ethanol mixture at high alcohol concentrations by means of molecular dynamics simulations. By using a standard force field a good agreement was found between experiment and molecular simulation. This was allowed us to explore the dynamics, structure and the interplay between both hydrogen-bonding networks of water and ethanol.

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Introduction In several applications water-ethanol mixtures in low water concentration must be purified (ethylene hydration, brewing produces, fuel cell, ...). The ethanol must be of a high purity, and therefore a low water content is needed. The production methods of such a high purity ethanol require a large consumption of energy or the use of expensive separation agents. These explain why more economical production methods are needed to obtain fuel of a similar efficiency. 1 Selective adsorption through a nanoporous membrane as metal organics frameworks or hydrophilic zeolites membranes present the advantages of a high degree of dehydration, low energy consumption and the absence of harmful emissions to the environment. 2–4 In order to optimize the separation processes, a good knowledge of the microscopic structure of the water-ethanol mixtures and the hydration of water molecules at high alcohol concentration are needed. However, before to tackle the separation properties of water-ethanol mixtures in the confined phases the nanostructure in the bulk phase must be well understood.

Water-ethanol mixtures in bulk and in liquid-vapour phase at low ethanol concentration were extensively studied these past decades. 5–21 Additionally, ethanol was often considered as a model to explore the balance of hydrophobic interactions and hydrogen bonds in the hydration of protein, biological systems, stabilizing the nanostructure of DNA, folded proteins 22,23 and playing a major role in biological activity. 24 While many numerical and experimental works were focused on water-ethanol mixtures at low ethanol concentrations less works have been reported on the structure of water-ethanol mixtures at high alcohol concentrations. 11 Furthermore, these works focused on a few properties separately (dielectric permittivity, surface tension, diffusion, structure...). Let us note that up to now, less work has been gathered these properties. 11,15

From a structural viewpoint, at low ethanol concentration, several works clearly highlight the formation of the ethanol aggregates. Additionally, it has was evidenced that the water-water H-bonding is enhanced in the first hydration shell of the nonpolar group 3

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while the water-water H-bonding is depleted in the neighborhood of the hydroxyl group. Thus the balance between the hydrophobic and hydrogen bonds (HB) interactions is a main aspect of the cluster formation. The net effect from the entire first hydration shell is a reduction rather than an excess of water H-bond, and the dominant contribution arises from the structuring of water in the second hydration shell of ethanol. 11 At very high ethanol concentration (xEtOH =0.7, 0.8 and 0.9), the simulations indicate the presence of water clustering and reveal the existence of a transition between a fully percolating network of H-bonded water molecules at low ethanol concentration to a nonpercolating H-bonded network at high ethanol concentration. 11 More recently, Gereben and Pusztai have shown that the location of the second hydration shell shifted toward higher distances with increasing ethanol concentration which is an evidence that the ethanol molecule disrupts the water HB structure. 18 Interestingly, it has been shown that the three dimensional HB network is morphologically characterized by the ring structure 20 and lacunarity. 21 Thus, controlling how the HB association evolves with respect to the nature and the water content in the system is required for a deeper understanding of many chemical and biological processes. Therefore a detailed knowledge of the effect of a dilution of HBs on the structure is of fundamental interest.

Here, we propose i) to predict and to gather the main physical properties of liquid and liquid-vapour water-ethanol mixtures at high alcohol concentrations ii) to study the local organization around water and ethanol molecules i.e. the solvation of water in both phases and iii) to explore the nonpercolating H-bonded network at high ethanol concentration. The organization of the paper is as follow: we first describe computational details, force fields and methodology. Thereafter we report the physical properties and the structure. Finally we conclude by providing a brief summary of our main results.

Models and Computational Details Ethanol was modeled by the flexible non polarizable TRAPPE United Atoms (UA) force

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field 25 where the CH3 and the CH2 groups are considered as the UA particles while the OH group is considered explicitly. Recently, Graben and Pusztai have investigated the structures of ethanol-water mixtures by using a flexible all atoms model to describe ethanol molecule. It was shown that the AA description overestimated the excess mixing properties. 15 On the opposite Sink and coworkers have shown that the AA force fields underestimated the excess mixing properties. 26 Thus, UA description was considered to assess to ability of the TRAPPE force field to quantitatively reproduce the physical properties. Furthermore, we aim to study the nanoconfined ethanol-water mixtures into the polymeric membranes that needs to sample the high length and time scales leading to a high computational time which can be decreased by using a UA description. Water was represented from the rigid non-polarizable TIP4P/2005 model. 27 Indeed, recently Gereben and Pusztai have investigated the HB network of ethanol-water mixtures and they carried out molecular dynamics simulation of 0, 20, 40, 69, 80 and 100% ethanolin-water mixtures using all atoms force fields. 18 They have shown that the number of HB per water and ethanol molecules was strongly dependent on the force field. However, they showed that the TIP4P-2005 water model is the potential which provides the best agreement with experimental X-ray data. The intermolecular interactions are composed of the repulsion-dispersion and the electrostatic contributions that are represented by the Lennard-Jones (LJ) and Coulombic potentials. The electrostatic interactions were truncated at 12 Å and calculated by using the Ewald sum with a precision of 10−6 . Short range interactions were modeled by using the Lennard-Jones potential and a cutoff of 12 Å. Here, the interactions between unlike LJ sites of two molecules were determined by the Lorentz-Berthelot combining rule. The statistical errors for the calculated properties were estimated using the block averages method. Regarding the liquid phase the initial simulation box was a rectangular box of dimensions Lx =Ly =45 Å and Lz =90 Å. Periodic boundary conditions were applied in the three directions. MD simulations were performed in the NpT statistical ensemble. Molecular Dynamics (MD) simulations were performed at T=300K and p=1bar using a time step of 0.001 ps to sample 10 ns (acquisition & equilibration phases). All MD simulations have been carried out with the DL_POLY

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package 28 using a combination of the velocity-Verlet and QUATERNION algorithms and the Nose-Hoover thermostat and barostat. 29,30 The initial configuration was built by a random distribution of ethanol (EtOH) and water (H2 O) molecules. The number of molecules and the initial volume were chosen in order to build a dense bulk phase. Thus, 10 molar fraction in EtOH (xEtOH ) were investigated {0, 0.499, 0.834, 0.885, 0.913, 0.941, 0.957, 0.969, 0.996, 1}. Number of molecules, molar fraction and simulated density of mixtures are reported in Table 1. Table 1 Number of molecules (n−(EtOH) and n−(H2 O)), molar fraction (xEtOH ) and simulated density (ρsim. ) of both components.

n−(H2 O) 1807 904 300 207 157 107 77 57 7 0

n−(EtOH) 0 903 1507 1600 1650 1700 1730 1750 1800 1807

xEtOH 0 0.499 0.834 0.885 0.913 0.941 0.957 0.969 0.996 1

ρsim. (kg m−3 ) 997.1 852.7 800.5 793.7 790.2 786.7 784.4 783.1 779.4 778.6

Liquid-vapour (LV) interface was built by adding two vacuum slabs of 75 Å on both sides of the previous rectangular liquid phase along the z direction. Thus liquid-vapour interfaces are normal to the z direction. From this new configuration an equilibration phase of 10 ns in canonical ensemble was carried out to get the formation of two interfaces. Properties were managed during a production phase of 10 ns.

Methodology Binary excess properties were computed from

yE = y − x1 . y1 − x2 . y2 6

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(1)

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where yE represents the excess property, x the molar fraction and y the so-calculated property. The subscripts 1 and 2 corresponds to the pure substances.

The dielectric permittivity (ǫ) is defined from the total polarization (M) 31 related to the dipole density 31,32

ǫ=1+

N X 4π hM2 i with M = µi 3ǫ0 V kB T i

(2)

where V is the sample volume, < ... > denotes a statistical average over the different configurations, kB is the Boltzmann’s constant, ǫ0 the vacuum permittivity.

Surface tension (γ) was computed by means of the non-exponential test-area method, 33 TA2 34 based upon a thermodynamic route. This method expresses the surface tension as a change in the free energy for an infinitesimal change in the surface area performed in the constant-N V T ensemble. This infinitesimal change in the area is performed throughout a perturbation process for which the perturbed system (state A + ∆A ) is obtained from an infinitesimal change ∆A of the area A of the reference system. The box dimensions (Lx(A+∆A) , Ly(A+∆A) , L(A+∆A) ) in the perturbed systems are changed using the following z √ √ transformations LA+∆A = L(A) 1 + ξ, Ly(A+∆A) = L(A) 1 + ξ, L(A+∆A) = L(A) x x y z z /(1 + ξ) (A) where ξ → 0. The area (A + ∆A) of the perturbed state thus equals to L(A) x Ly (1 + ξ) (A) and ∆A is equal to L(A) x Ly ξ. These transformations conserve the volume of the box in

the perturbed state. This means that it is possible to express the surface tension as a difference between the perturbed and reference states. U (A) (rN ) and U (A+∆A) (r′ N ) are the configurational energies of the systems with an area A and a configurational space rN , and an area A + ∆A and a configurational space r′ N , respectively.

γ =

∂F ∂A

= lim

ξ→0

!

*

(3) N,V,T

(U (A+∆A) (r′ N ) − U (A) (rN )) ∆A 7

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< ... >0 indicates that the average is carried out over the reference state. Long range corrections were calculated from managing the energy of the reference and the perturbed states by means of the relations established by Guo and Lu. 35–37

Diffusion coefficient (D) was computed by means of the calculation of the mean square displacement (MSD) and the Einstein’s relation. For a diffusive regime (M SD ∼ Dt), where t is the time, D is calculated from

D = lim

t→∞

E D P P t0 N i=1 [rcom,i (t + t0 ) − rcom,i (t0 )]

2nN N0 t

= lim

t→∞

M SD 6N N0 t

(4)

with t0 the time origin, N the number of molecules, N0 the number of t0 and rcom,i the position vector of the center of mass of i molecule. n is the dimension of the system such as n = 3 in the three dimensional isotropic phase.

To investigate the local structure of water molecules the distribution of the tetrahedral order parameter (q) was computed. 38

q = 1 − 3/8

4 3 X X

cos(φij )

(5)

i=1 j=i+1

where φij is the angle between i and j molecules. For a tetrahedral structure q is close to 1. We considered water molecules that have an instantaneous coordination number of 4.

Results and Discussion Physical properties Density We report in Figure 1a the density of the liquid phase as a function of xEtOH . Pure liquids present a deviation less of 2 % with respect to experiments. 39 Additionally, as shown in Figure 1a the so-calculated density of the ethanol-water mixtures is in very 8

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good agreement with the experiment. 39 This concordance clearly contributes to validate the combination of the non polarizable UA-TRAPPE and TIP4P/2005 models by means of the mixing Lorentz-Berthelot rule. Furthermore, this result shows that the polarizabilities of water and ethanol do not impact on the simulated density of the liquid mixture. Let us note that, although the structure of water-ethanol mixtures was deeply investigated the prediction of the density was rarely undertaken at high alcohol concentrations. Additionally, we showed that the water-ethanol mixtures do not follow an ideal behavior and a maximum of deviation is observed to about xEtOH =0.5. We plot in Figure 1b the excess density of water-ethanol mixtures as a function of xEtOH . As depicted in Figure 1b the predicted minimum of the excess density (approximatively xEtOH =0.5) is well reproduced. The change in monotony of the excess density at xEtOH =0.5 could be imputed to a change in the structural topology. 11,19 Indeed, at xEtOH =0.5 a percolating-non-percolating transition could occurred. This will be discussed later. Dielectric permittivity We report in Figure 2 the dielectric permittivity of the water-ethanol mixtures. The dielectric permittivity of the pure TIP4P/2005 water model is 61.2 that is slightly higher than the usual value of 56 reported by Abascal and Vega. 27 As shown by Gereben and Pusztai this difference was imputed to the size effects and the box shape. 40 Indeed, a dielectric permittivity of 55.3 was found by modeling a liquid phase in a cubic box of 30 Å as length. Let us note that the dielectric constant of the pure ethanol is in good agreement with the experiment (a deviation less of 3 % was found). As shown in Figure 2a a monotone decrease in ǫ as a function of xEtOH is observed. This result is in qualitative agreement with experiment. 41 Thus the decrease in ǫ as a function of xEtOH is fairly reproduced from a non-polarizable force field in this range of ethanol concentration. Let us note that the dipolar moment of the ethanol remains independent of the water content (µ = 2.26D).

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Excess heat of mixing We manage in Figure 3 the excess heat of mixing (U +P V , where U is the configurational energy, P the pressure and V the volume) as a function of the ethanol molar fraction. We used the Equation 1 that we divided by the total molecules number (Ethanol+Water). 15 As shown in Figure 3 a reasonable concordance between predicted and experimental values is highlighted. This concordance allows us to validate from a thermodynamic viewpoint the combination of non polarizable force fields to model ethanol/water mixtures. At the opposite, by combining the TIP4P water model and the OPLS description for the ethanol molecule Wensink and coworkers found that excess energies are overestimated. 26 This result was attributed to the overestimated dipolar moment of both water and ethanol. In this work the dipolar moments are similar than those of Wensink et al. The difference between both works is probably due to the Lennard-Jones parameters and the mixing rules used. Surface tension We report in Figure 4a the surface tension of water-ethanol liquid vapor interface. As shown in Figure 4a a very good agreement between experiment and predicted values is observed with a maximum average deviation of 6.0% with experiment. Let us note that the long range corrections and reciprocal contribution of the electrostatic interactions of surface tension were considered in this calculation. 36 Long range corrections is about 3 mNm−1 whatever the concentrations i.e. 18% of surface tension of high alcohol concentrated mixtures. It is interesting to note that this correction was rarely considered. 9 At high ethanol concentration (xEtOH >0.8) the surface tension slowly decreases as function of the ethanol fraction. Indeed, from xEtOH =0.2 the surface tension is almost constant. As shown in Ref. 36 the strong decrease in surface tension between xEtOH =0 and xEtOH =0.2 is due to a breaking of the three dimensional (3D) hydrogen bonding network. Indeed, a H-bonding transition occurs from the three dimensional tetrahedral hydrogen water HB network to the two dimensional winding chains of ethanol. The addition of ethanol in water breaks the hydrogen bond network and causes the decrease of the interfacial ten10

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sion the water-ethanol mixture. The decrease of the surface tension of the water-alcohol mixture with the alcohol concentration was found to be predominantly correlated with the decrease of the water-water hydrogen bonds. 36 We display in Figure 5 the local surface tension (γ(z)) as a function of z. γ(z) can be assimilated to the profile of the difference between the normal an the tangential pressures along the normal axis of the surface. 34,42 Figure 5 shows that the local surface tension is quasi zero in the liquid phase which involves that the mechanical equilibrium in the liquid phase is well fulfilled. This involves that the liquid phase does not contribute to the total surface tension (γ =

P

γ(z)). Furthermore, Figure 5 shows that the tension

is well exerted at the interfacial regions. Interestingly, we observe a lower tension of the ethanol suggesting a less cohesive interface in line with the structural difference in hydrogen bonding network. Dynamical properties We report in Figure 6a the diffusion coefficient of ethanol, water and {water+ethanol} as a function of xEtOH . As shown in Figure 6a we fairly reproduced the experimental diffusion coefficient of both water and ethanol. Indeed, the diffusion coefficient was slightly overestimated for the high alcohol concentrations. As suggested by Graberen and Pusztai this difference can be due to the size effect. 43 This behavior was also observed by Zhong and Patel 15 who used a polarizable force field. These results are less quantitative than those of Hasse et al. which used the OPLS force field to model ethanol. 44 However, the evolution of the diffusion coefficient with respect to the ethanol fraction is in good qualitative agreement because the minimum of the diffusion coefficient at xEtOH =0.5 is well recovered. At higher concentrations of ethanol, the movement between water and ethanol molecules is highly correlated. Indeed, water molecules loss its hydrogen bond network structure and behave as single molecule bonded with ethanol molecules by hydration. 12 Additionally, we report in Figure 6b the excess of the total diffusion coefficient (water+ethanol) as a function of xEtOH . Interestingly, a similar minimum that the one observed from the excess surface tension and the excess heat of mixing 12

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is observed to about xEtOH =0.2. An additional simulation was carried out at low molar fraction to ascertain this minimum. This result shows that the deviation with respect to an ideal behavior is structural, thermodynamics and dynamics. The dipolar relaxation time was also managed by using the correlation function of the total dipolar moment. 45 The relaxation time was evaluated from an adjustment of the dipolar correlation function by means of the Kohlraush law. 45 As observed with the diffusion coefficient we found that from xEtOH =0.8 the dipolar relaxation time average of water and ethanol was sensibly similar (< τ >= 22.1 ps). Let us recall that both objectives of this work is to assess the ability of the combination of the UA(EtOH)-TIP4P-2005(H2O) models to quantitatively predict the physical properties and to get a structural vision of the HB structure, work is in progress to deeply investigate the dynamics and the interplay between dynamics and structure.

Structure and hydrogen bonding network We manage in Figure 7a and 7b the hydrogen bonds number (nHB) between water molecules (H2 O-H2 O), between ethanol molecules (EtOH-Et-OH) and between water and ethanol per water and ethanol molecules. Hydrogen bonds number was calculated by considering the definition of Luzar and Chandler. 46–48 Two molecules are chosen as being hydrogen bonded only if their inter-oxygen distance is less than 3.5 Å, and simultaneously the OHO angle is less than 30o . As shown by Gereben and Pusztai the angular constraint is superfluous. 18 Panel a) of Figure 7 shows that hydrogen bonds number of H2 O-H2 O and EtOH-EtOH decreases and increases as a function of xEtOH , respectively. This result shows a progressive dehydration of water molecules and a resolvation of ethanol with the increase in xEtOH . At the same time HB number of H2 O-EtOH per water molecules increases that suggests a possible compensation of the coordination number in the first hydration shell. These results are in good agreement with the works of Roux and coworkers 11 and Patel et al. 15 In panel b) of Figure 7 we report the total contribution of the HB number which is weakly sensitive to the HB water network dilution. Indeed, nHB per water molecule decreases from 3.8 to 3.3 while nHB of ethanol decreases from 2 to 12

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1.9. It seems that the loss of water-water HB number was partially compensated by the formation of HB between ethanol and water. Indeed, at high ethanol concentration water molecules form 3.2 HB number with ethanol. Thus, water molecules undergo a structural transition between a tetrahedral structure to a less cohesive trigonal environment. It seems that the water molecules lost their tetrahedral structure. Furthermore, as shown Figure 7a and 7b all contributions present a deviation with respect to the ideal behavior. To confirm this point we report in Figure 7c the HB number excess as a function of xEtOH . Figure 7c shows that water undergoes a stronger deviation with respect to a ideal behavior than the ethanol. To get a microscopic insight of the local structure around water we computed the radial distribution functions between the oxygen atoms of water and the atoms of the ethanol molecules. We provide in Figure 8 the radial distribution functions between two atoms a and b V 4πr2 Na Nb

DP

Na i

PN b

j6=i

E

δ(r − |rij (t)|) where Na and Nb are the atomic densities of a and b

respectively, V is the total volume, rij = rj −ri such that ri is the position of i. The brackets stands for a time average. We report in Figure 8a the radial distribution functions (RDF) between the oxygen atoms of water (OW) as a function of xEtOH , RDF (OW-OW). In inset of panel a) of Figure 8 we focus on the first hydration shell. Firstly, let us note that the location of the first and the second hydration shell is in good agreement with the recent results obtained by Gereben and Pusztai. 18 Moreover, amplitude of both peak is sensitively similar. This good agreement suggests that the UA force field is able to well described the local structure of ethanol-water mixtures. As shown in Figure 8a the amplitude of the first and second peaks of the RDF (OWOW) for the concentrated ethanol solution is larger than that of the corresponding peak for pure water, but the shapes and positions are very similar. This, is an obvious evidence of microheterogeneity and a partial mixing at the molecular scale. 10,45 Indeed the increase of the RDF peaks intensity implies a higher local water concentration, which stands for that the probability of finding OW atom at a distance r from OW atom does not scale with the decrease of the water number density, but it actually decays in a smaller extent. The second peak at approximatively 4.5 Å which is a signature of the hydrogen-bonded

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network present in pure water, is largely modified in amplitude and slightly shifted toward the concentrated alcohol mixture. Figure 8b represents the RDF between oxygen atoms of ethanol (OH). As previously, the location and the amplitude of two peaks are in line with the RDF calculated by Gereben and Pusztai. 18 At high concentration a slight impact was observed on the location and the amplitude of the second hydration shell. However the amplitude of the first shell is strongly modified. As shown in Figure 8c a similar trend is observed for the RDF between OH and OW atoms. This change in amplitude can be quantified from the integration of the radial distribution functions allowing the calculation of the coordination number. Thus, we report in Figure 8d the coordination number of water and ethanol in both first (S1) and second (S2) hydration shells. Figure 8d shows that the water-water coordination number (nOW−OW ) decreases as a function of xEtOH in both hydration shells while the number of ethanol molecules around ethanol (nOHOH) increases in S1 and S2. In the same time, number of ethanol molecules around water (nOW−OH ) increases and is higher than the OH-OH coordination number. This result is in line with the previous hydrogen bonds number calculation and suggests a high interactions between water and ethanol molecules. This is in good agreement with the difficulties to separate water/ethanol mixtures. However, the coordination number is lower than in the pure water phase that suggests the loss of the tetrahedral geometry. This result clearly contradicts early predictions of Soper et al. 10 who state that the water structure exists in a highly concentrated alcohol-water solution. Indeed, typical geometrical characteristics seems to be conserved (typical distances) while the coordination number and HB numbers are modified. This loss of the tetrahedral structure was corroborated by the calculation of the tetrahedral order parameter (q). Indeed, although the average coordination number is lower than 4 an instantaneous coordination number of 4 is allowed. As shown in Figure 8d for the pure water q is 0.81 while at high concentration q is 0.71. This result suggests that the water molecules with a coordination number of 4 are arranged in a modified tetrahedron. The energy of a water molecule (electrostatic+van der Waals) was then computed. We found that the energy per water molecules increases as the concentration in ethanol increases from -46 kJ mol−1 to -90 kJ mol−1 . This highlights

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favorable interactions between water and ethanol. This change in the total HB bonds number depicts a clear transition between both hydrogen bonding networks, 3 dimensional HB water to 2 dimensional HB ethanol. This can be appreciated through the clusters analysis. We report in Figure 9 the cluster size probability of water and ethanol clusters. It is well known that the liquid water is characterized by the existence of an extensive inter-connected network of HB that percolates throughout the entire phase. Indeed, we found that all water molecules are interconnected in the pure liquid water. From xEtOH =0.5 the three dimensional HB network begins to disconnect it to become nonpercolating. As shown in Figure 9a the transition from a percolating HB network to a non-percolating network occurs beyond xEtOH =0.5. Indeed, for 0.8340 ≤ xEtOH ≤ 0.97 we found a water cluster of 3.8 molecules while for xEtOH > 0.97 water molecules are fully dispersed in ethanol. Thus, the critical percolation point of the water network appears to approximatively xEtOH =0.5. This result is in line with the critical transition found by Soper and co-workers for the methanol-water mixtures (xMeOH 0.54). 10 Interestingly, as depicted in Figure 9b ethanol shows a different behavior with respect to methanol. Indeed, while none critical percolation point is evidenced a continue HB network evolution is observed. Contrary to the water, the HB network of the pure liquid ethanol does not percolate. Indeed, 50% of molecules are found interconnected that could suggest the formation of ethanol clusters and then micro-heterogeneity. 49,50 Thus, water molecules could associate with the ethanol molecules to form an additional HB network. However, the cluster etanol-water analysis shows that the ethanol and water molecules do not combine them to generate a new HB network. Indeed, from xEtOH =0.5 to xEtOH =0.99 we found that only 1% to 0.1% of water and ethanol molecules are interconnected. Therefore water and ethanol molecules are only locally connected that is in line with the previous HB number analysis. In panel c of Figure 9 we display the size distribution of linear cluster. We also analyzed the cyclic aggregates and we found that the linear ethanol clusters were most probable. Indeed, for xEtOH =0.5, 99% of clusters are linear and 0.1% are cyclic while for the pure ethanol 85% of clusters are linear and 15% are cyclic . From xEtOH =0.8854

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we found that the most probable size of the aggregate is a linear tetramer. Let us note that at xEtOH =0.5 the dimeric aggregates are preponderant. Thus the HB network of high ethanol concentration of water-ethanol mixture corresponds to a combination of an interconnected HB network and the ethanol clusters pocket. This organization clearly highlights a structural heterogeneity of the ethanol alcohol mixture already evidenced by Pereira et al. and Imre et al. 49,51 An illustration of the microstructure is shown in Figure 10. In order to get an energetic standpoint of the HB, H2 O-H2 O, EtOH-EtOH and H2 OEtOH binding energies were calculated. To be in line with the previous calculation of the HB number the same HB criterion was used to manage the pairwise energy. Energy was calculated by considering the electrostatic and van der Waals interactions. In Table 2 we report the three binding energies as a function of the ethanol concentrations. As shown in Table 2 the binding energy shows a weak dependance on the concentration for xEtOH > 0.4997. However at low concentrations the binding energy of H2 O-H2 O decreases from -15.1 kJ mol−1 for the pure water to -19.1 kJ mol−1 for xEtOH = 0.8340 i.e. a decrease of 4 kJ mol−1 . At the same time binding energy of EtOH-EtOH and H2 O-EtOH decrease of 1.5 and 1.4 kJ mol−1 , respectively. The so-calculated binding energy of H2 O-EtOH is in fair agreement with the results obtained by Gereben and Pusztai. 18 Interestingly, the calculated H2 O-H2 O, EtOH-EtOH and H2 O-EtOH binding energies obtained in this work from MD simulations are also in fair agreement with the quantum calculations. 52 Indeed, the difference between three binding energies is well reproduced that allows us to make confident to the combination of UA-TIP4P2005 models.

Concluding Remarks In this work the physical properties of water-ethanol mixtures at high alcohol concentrations were investigated. Namely, the thermodynamical, interfacial, dielectric and dynamical properties such as volume, density, enthalpies, surface tension, dielectric permittivity and diffusion coefficient that are standard access to the reliability of the simulation re-

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Table 2 Binding energies as a function of the ethanol concentration in kJ mol−1 . In average deviations are around 0.006 kJ mol−1 .

xEtOH 0.0 0.4997 0.8340 0.8854 0.9131 0.9408 0.9574 0.9685 0.9961 1.0

H2 O-H2 O -15.1 -17.9 -19.1 -19.4 -19.5 -19.7 -19.9 -19.9 -21.0

EtOH-EtOH

H2 O-EtOH

-21.2 -22.7 -23.0 -23.1 -23.2 -23.3 -23.4 -23.5 -23.5

-19.5 -20.9 -21.1 -21.3 -21.4 -21.5 -21.6 -21.7

sults showed very good agreement with the experimental results, indicating that the used non polarizable models are able to reproduce correctly the experiment. Furthermore, the analysis of the excess quantities, which directly explore the non-ideal contribution, indicate that, on this level, simulation models are well suited to predict the experimental properties. Structure of water-ethanol mixture was also investigated. At high ethanol concentration the loss of water-water HB number was compensated by the formation of HB between ethanol and water. Water molecules undergo a structural transition between a a tetrahedral structure to a less cohesive trigonal environment. Thus, the water molecule loses its tetrahedral structure. This change in the total HB bonds number depicts an obvious transition between both hydrogen bonding networks, three dimensional HB water to two dimensional HB ethanol. Furthermore, we have shown that the water undergoes a stronger deviation with respect to a ideal behavior than ethanol that highlights the partial mixing of both compounds. Radial distributions functions analysis showed that increase in the amplitude of first and second hydration shells which is correlated to an obvious evidence of microheterogeneity and a partial mixing at the molecular scale. Calculation of coordination number of water evidenced that the tetrahedral water structure did not exist in a highly con-

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centrated alcohol-water solution. Additionally, favorable interactions between water and ethanol have been established that could explain the so-difficulties of water separation at high ethanol concentration. From a concentration of xEtOH =0.5 the three dimensional HB network of water begins to disconnect it to became non-percolating and a transition between percolating HB network to a non-percolating network occurs. Contrary to the water, the HB network of the pure ethanol does not percolate. Indeed, 50% of molecules are found interconnected suggesting the formation of ethanol clusters and then a micro-heterogeneity. The cluster etanol-water analysis showed that the ethanol and water molecules do not form an additional HB network. We show that at high alcohol concentration water and ethanol clusters coexist. Eventually, for xEtOH =0.99 the water molecules were found fully dispersed and well hydrated by the ethanol. At low water content the energy per water molecules was higher than in the liquid water phase. This increase in water energy suggests the use of hydrophilic membranes in the pervaporation processes to overcome this energetics penalty. To check it we modeled, in prospective, the separation process of ethanol-water mixture through a hydrophilic polyamide membrane. Force field and computational construction of the membrane can be found in Ref. 53–55 Analysis of the density profiles of the coordination number of water shows that water molecules lost their hydration shell of ethanol molecules i.e. that are fully desolvated into the membrane. From our understanding in structure and interactions of water-ethanol mixtures we are going to plan to capture the microscopic insights driving the separation of water-ethanol mixtures through polymeric and inorganic hydrophilic membranes.

Competing Financial Interest The authors declare no competing financial interests.

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References (1) Hilmioglu, N. Bioethanol Recovery using the Pervaporation Separation Technique. Manage. Environ. Qual. 2009, 20, 165. (2) Kim, J.; Lee, K.; Kim, S. Pervaporation Separation of Sater from Ethanol through Polymide Composite Membranes. J. Membr. Sci. 2000, 169, 81. (3) He, Y.; Bagley, D.; Leung, K.; Liss, S.; Liao, B. Recent Advances in Membrane Technologies for Biorefining and Bioenergy Production. Biotechnol. Adv. 2012, 30, 817. (4) Kang, Q.; Huybrechts, J.; der Bruggen, B.-V.; Baeyens, J.; Tan, T.; Dewil, R. Hydrophilic Membranes to Replace Molecular Sieves in Dewatering the BioEthanol/Water Azeotropic Mixture. Separation and Purification Technology 2014, 136, 144. (5) Tarek, M.; Tobias, D.-J.; Klein, M.-L. Molecular Dynamics Investigation of an Ethanol-Water Solution. Physica A 1996, 231, 117. (6) Tarek, M.; Tobias, D.-J.; Klein, M.-L. Molecular Dynamics Investigation of the Surface/Bulk Equilibrium in an Ethanol-Water Solution. J. Chem. Soc. Faraday Trans. 1996, 92, 560. (7) Aratono, M.; Toyomasu, T.; Villeneuve, M.; Uchizono, Y.; Takiue, T.; Motomura, K.; Ikeda, N. Thermodynamic Study on the Surface Formation of the Mixture of Water and Ethanol. J. Coll. Int. Sci. 1997, 191, 146. (8) Dixit, S.; Crain, J.; Poon, W.; Finney, J.; Soper, A. K. Molecular Segregation Observed in a Concentrated Alcohol-Water Solution. Nature 2002, 416, 829. (9) Stewart, E.; Shields, R. L.; Taylor, R. S. Molecular Dynamics Simulations of the Liquid/Vapor Interface of Aqueous Ethanol Solutions as a Function of Concentration. J. Phys. Chem. B 2003, 107, 2333.

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(10) Dougan, L.; Bates, S. P.; Hargreaves, R.; Fox, J. P.; Crain, J.; Finney, J. L.; Réat, V.; ; Soper, A. K. Methanol-Water Solutions: A bi-Percolating Liquid Mixture. J. Chem. Phys. 2004, 121, 6456. (11) Noskov, S.; Lamoureux, G.; Roux, B. Molecular Dynamics Study of Hydration in Ethanol-Water Mixtures Using a Polarizable Force Field. J. Phys. Chem. B 2005, 109, 6705. (12) Zhang, C.; Yang, X. Molecular Dynamics Simulation of Ethanol/Water Mixtures for Structure and Diffusion Properties. Fluid Phase Equilibria 2005, 231, 1. (13) Andoh, Y.; Yasuoka, K. Hydrogen-Bonded Clusters on the Vapor/Ethanol-AqueousSolution Interface. J. Phys. Chem. B 2006, 110, 23264. (14) Stephenson, S.; Offeman, R.; Robertson, G.; Orts, W. Ethanol and Water Capacities of Alcohols: A Molecular Dynamics Study. Chem. Eng. Sci. 2006, 61, 5834. (15) Zhong, Y.; Patel, S. Electrostatic Polarization Effects and Hydrophobic Hydration in Ethanol-Water Solutions from Molecular Dynamics Simulations. J. Chem. Phys. 2009, 113, 767. (16) Vrhovsek, A.; Gereben, O.; Jamnik, A.; Pusztai, L. Hydrogen Bonding and Molecular Aggregates in Liquid Methanol, Ethanol, and 1-Propanol. J. Phys. Chem. B 2011, 115, 13473. (17) Juurinen, I.; Nakahara, K.; Ando, N.; Nishiumi, T.; Seta, H.; Yoshida, N.; Morinaga, T.; Itou, M.; Ninomiya, T.; Sakurai, Y.; Salonen, E.; Nordlund, K.; Hamalainen, K.; Hakala, M. Measurement of Two Solvation Regimes in WaterEthanol Mixtures Using X-Ray Compton Scattering. Phys. Rev. Lett. 2011, 107, 197401. (18) Gereben, O.; Pusztai, L. Investigation of the Structure of Ethanol-Water Mixtures by Molecular Dynamics Simulation I: Analyses Concerning the Hydrogen-Bonded Pairs. J. Phys. Chem. B 2015, 119, 3070. 20

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(19) Tan, M.-L.; Miller, B. T.; Te, J.; Cendagorta, J. R.; Brooks, B. R.; Ichiye, T. Hydrophobic Hydration and the Anomalous Partial Molar Volumes in EthanolWater Mixtures. J. Chem. Phys. 2015, 142, 064501. (20) Gereben, O. Lacunarity Analysis of Atomic Configurations: Application to EthanolWater Mixtures. Phys. Rev. E 2015, 92, 033305. (21) Gereben, O. Ring Structure Analysis of Ethanol-Water Mixtures. J. Mol. Liq. 2015, 812. (22) Beijer, F. H.; Kooijman, H.; Spek, A. L.; Sijbesma, R. P.; Meijer, E. W. SelfComplementarity Achieved through Quadruple Hydrogen Bonding. Angew. Chem. Int. Ed. 1998, 37, 75. (23) Stradner, A.; Sedgwick, H.; Cardinaux, F.; Poon, W. C. K.; Egelhaaf, S. U.; Schurtenberger, P. Equilibrium Cluster Formation in Concentrated Protein Solutions and Colloids. Nature 2004, 432, 492. (24) Pal, S. K.; Zewail, A. H. Dynamics of Water in Biological Recognition. Chem. Rev. 2004, 104, 2099. (25) Chen, B.; Potoff, J.-J.; Siepmann, J. Monte Carlo Calculations for Alcohols and Their Mixtures with Alkanes. Transferable Potentials for Phase Equilibria. 5. United-Atom Description of Primary, Secondary, and Tertiary Alcohols. J. Phys. Chem. B 2001, 105, 3093. (26) Wensink, E.; Hoffmann, A.; van Maaren, P.; van der Spoel, D. Dynamics Properties of Water/Alcohol Mixtures Studied by Computer Simulation. J. Chem. Phys. 2003, 119, 7308. (27) Abascal, J.; Vega, C. A General Purpose Model for the Condensed Phases of Water: TIP4P/2005. J. Chem. Phys. 2005, 123, 23505. (28) Todorov, I.; Smith, W.; Trachenko, K.; Dove, M. DLPOLY, CCP5 Program. J. Mater. Chem. 2006, 16, 1911. 21

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(29) Nose, S. A Unified Formulation of the Constant Temperature Molecular Dynamics Methods. J. Chem. Phys. 1984, 81, 511. (30) Hoover, W. Canonical Dynamics: Equilibrium Phase-Space Distributions. Phys. Rev. A 1985, 31, 1695. (31) Ballenegger, V.; Hansen, J.-P. Dielectric Permittivity Profiles of Confined Polar Fluids. J. Chem. Phys. 2005, 122, 114711. (32) Zhu, H.; Ghoufi, A.; Szymczyk, A.; Belannec, B.; Morineau, D. Anomalous Dielectric Behavior of Nanoconfined Electrolytic Solutions. Phys. Rev. Lett. 2012, 109, 107801. (33) Gloor, G. J.; Jackson, G.; Blas, F. J.; de Miguel, E. Test-Area Simulation Method for the Direct Determination of the Interfacial Tension of Systems with Continuous or Discontinuous Potentials. J. Chem. Phys. 2005, 123, 134703. (34) Ghoufi, A.; Malfreyt, P. Calculation of the Surface Tension and Pressure Components from a Non-Exponential Perturbation Method of the Thermodynamic Route. J. Chem. Phys. 2012, 136, 024104. (35) Guo, M.; Lu, B. C. Y. Long Range Corrections to Thermodynamic Properties of Inhomogeneous Systems with Planar Interfaces. J. Chem. Phys. 1997, 106, 3688. (36) Biscay, F.; Ghoufi, A.; malfreyt, P. Surface Tension of Water-Alcohol Mixtures from Monte Carlo Simulations. J. Chem. Phys. 2011, 134, 044709. (37) Biscay, F.; Ghoufi, A.; Lachet, V.; Malfreyt, P. Prediction of the Surface Tension of the Liquid-Vapor Interface of Alcohols from Monte Carlo Simulations. J. Phys. Chem. C 2011, 115, 8670. (38) Errington, J.; Debenedetti, P. Relationship Between Structural Order and the Anomalies of Liquid Water. Nature 2001, 409, 318. (39) Khattab, I.; Bandarkar, F.; Kakhree, M. A. A.; Jouyban, A. Density, Viscosity, and Surface Tension of Water+Ethanol Mixtures from 293 to 323 K. Korean J. Chem. Eng. 2012, 29, 812. 22

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(40) Gereben, O.; Pusztai, L. On the Accurate Calculation of the Dielectric Constant from Molecular Dynamics Simulations: The Case of SPC/E and SWM4-DP Water. Chem. Phys. Lett. 2011, 507, 80. (41) Wyman, J. The Dielectric Constant of Mixtures of Ethyl Alcohol and Water from -5 to o . J. Am. Chem. Soc. 1931, 53, 3292. (42) Ghoufi, A.; Malfreyt, P. Local Description of Surface Tension Through Thermodynamic and Mechanical Definitions. Mol. Sim. 2013, 39, 603. (43) Gereben, O.; Pusztai, L. System Size and Trajectory Length Dependence of the Static Structure Factor and the Diffusion Coefficient as Calculated from Molecular Dynamics Simulations: The case of SPC/E Water. J. Mol. Liq. 2011, 36, 161. (44) Guevara-Carrion, G.; Vrabec, J.; Hasse, H. Prediction of Self-Diffusion Coefficient and Shear Viscosity of Water and its Binary Mixtures with Methanol and Ethanol by Molecular Simulation. J. Chem. Phys. 2011, 134, 074508. (45) Hennous, L.; Hamid, A. A.; Lefort, R.; Morineau, D.; Malfreyt, P.; Ghoufi, A. Crossover in Structure and Dynamics of a Primary Alcohol Induced by HydrogenBonds Dilution. J. Chem. Phys. 2014, 141, 204503. (46) Luzar, A.; Chandler, D. Effect of Environment on Hydrogen Bond Dynamics in Liquid Water. Phys. Rev. Lett. 1996, 76, 928. (47) Soper, A. K.; Philips, M. G. A New Determination of the Structure of Water at 25o C. Chem. Phys. 1986, 107, 47. (48) Teixeira, J.; Bellisent-Funel, M. Dynamics of Water Studied by Neutron Scattering. J. Phys. Condens. Matter 1990, 2, SA105. (49) Perera, A.; Sokolíc, F.; Zoranić, L. Microstructure of Neat Alcohols. Phys. Rev. E 2007, 75, 060502R.

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(50) Ferrario, M.; Haughney, M.; McDonald, I.; Klein, M. Molecular-Dynamics Simulation of Aqueous Mixtures: Methanol, Acetone, and Ammonia. J. Chem. Phys. 1990, 93, 5156. (51) Bakó, I.; Megyes, T.; Bálint, S.; Grósz, T.; Chihaia, V. Water-Methanol Mixtures: Topology of Hydrogen Bonded Network. Phys. Chem. Chem. Phys. 2008, 10, 5004. (52) Fileti, E. E.; Chaudhurib, P.; Canuto, S. Relative Strength of Hydrogen Bond Interaction in Alcohol-Water Complexes. Chem. Phys. Letters 2004, 400, 494. (53) Ding, M.; Ghoufi, A.; Szymczyk, A. Molecular Simulations of Polyamide Reverse Osmosis Membranes. Desalination 2014, 16, 48. (54) Ding, M.; Szymczyk, A.; Goujon, F.; Soldera, A.; Ghoufi, A. Structure and Dynamics of Water Confined in a Polyamide Reverse-Osmosis Membrane: A MolecularSimulation Study. J. Membr. Sci. 2014, 458, 236. (55) Ding, M.; Szymczyk, A.; Ghoufi, A. On the Structure and Rejection of Ions by a Polyamide Membrane in Pressure-Driven Molecular Dynamics Simulations. Desalination 2015, 368, 76. (56) Boyne, J.; Williamson, A. Enthalpies of Mixing of Ethanol and Water of 25 o . J. Chem. Eng. Data 1967, 12, 318.

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Figure 1 Simulated and experimental (a) density and (b) excess density of water-ethanol mixtures as a function of xEtOH at 300K and 1bar. The incertitudes on the density are too small to be represented. The average deviation on the density is 3 kg m−3 . Experimental values were taken from Ref. 39

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Figure 2 Simulated and experimental dielectric permittivity of water-ethanol mixtures as a function of xEtOH at 300K and 1bar. Experimental values were taken from Ref. 41 The incertitudes on the dielectric permittivity are too small to be represented. The average deviation on ǫ is 2.

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Figure 3 Simulated (square) and experimental (circle) excess heat of mixing of water-ethanol mixtures as a function of xEtOH at 300K and 1bar. Experimental values were taken from Ref. 12,56 The incertitudes on the excess heat of mixing are too small to be represented. The average deviation is 10 kJ mol−1 .

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Figure 4 Simulated and experimental (a) surface tension and (b) excess surface tension of water-ethanol mixtures as a function of xEtOH at 300K and 1bar. Legend of b) is similar of a).

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Figure 5 Profile of the local surface tension as function of z for water and ethanol at 300K and 1bar for two concentrations.

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Figure 6 a) Diffusion coefficient of water, ethanol and the total component at 300K and 1bar as a function of xEtOH . b) Excess simulated diffusion coefficient of the ethanol+water as a function of xEtOH . Legend of b) is similar of a).

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Figure 7 a) decomposition of the HB number, b) total HB number of water and ethanol and c) total HB number excess as a function of xEtOH . Legend of c) is similar of b). Dashed lines represent the ideal behavior.

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Figure 8 Radial distribution functions between a) oxygen atoms of water, b) oxygen atoms of ethanol and c) oxygen atoms of water and ethanol. d) Coordination number of water and ethanol (left axis) and tetrahedral order parameter (right axis) as a function of xEtOH at 300K and 1bar. In panel a) the inset is an enlargement between 0 and 4 Å. S1 and S2 corresponds to the first and second shell coordination. For b) and c) the legend is similar than the one of panel a). in panel b) maroon dashed line corresponds to the RDF in pure ethanol. OW and OH are the oxygen atoms of water and ethanol, respectively. CH3 is the methyl group of the ethanol. In panels a) and b) the horizontal scales of the inset were removed for clarity.

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Figure 9 Cluster size distribution (P(n)) in log-log scale of a) water and b) ethanol as a function of xEtOH at 300K and 1bar. c) Cluster size distribution of linear aggregates of ethanol.

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Figure 10 Snapshot of an instantaneous configuration of water-ethanol mixture at xEtOH =0.5. Cyan, gray and red colors correspond to water molecules, CH3 -CH2 - and OH groups of ethanol, respectively.

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