Unravelling the Composition-Dependent Anomalies of Pair

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B: Liquids, Chemical and Dynamical Processes in Solution, Spectroscopy in Solution

Unravelling the Composition Dependent Anomalies of Pair Hydrophobicity in Water-Ethanol Binary Mixtures Ritaban Halder, and Biman Jana J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.8b02528 • Publication Date (Web): 05 Jun 2018 Downloaded from http://pubs.acs.org on June 5, 2018

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The Journal of Physical Chemistry

Unravelling the Composition Dependent Anomalies of Pair Hydrophobicity in WaterEthanol Binary Mixtures Ritaban Halder and Biman Jana* Department of Physical Chemistry, Indian Association for the cultivation of Science, Jadavpur, Kolkata 700032, India Abstract: Aqueous binary mixtures have received immense attention in recent years because of their extensive application in several biological and industrial processes. Water-ethanol binary mixture serves as a unique system because it exhibits composition dependent alteration of dynamic and thermodynamic properties. Our present work demonstrates how different compositions of water-ethanol binary mixtures affect the pair hydrophobicity of different hydrophobes. Pair hydrophobicity is measured by the depth of the first minimum (contact minima) of potential of mean force (PMF) profile between two hydrophobes. The pair hydrophobicity is found to be increased with addition of ethanol to water up to mole fraction of 0.10 and decreased with further addition of ethanol. This observation is shown to be true for three different pairs of hydrophobes. Decomposition of PMF into enthalpic and entropic contribution indicates a switch from entropic to enthalpic stabilization of the contact minimum upon addition of ethanol to water. The gain in mixing enthalpy of the binary solvent system upon association of two hydrophobes is found to be the determining factor for the stabilization of contact minimum. Several static/dynamics quantities (average composition fluctuations, diffusion coefficients, fluctuations in total dipole moment, propensity of ethyl-ethyl association, etc) of the ethanol-water binary mixture also show irregularities around xEtOH =0.10-0.15. We have also discovered that the hydrogen bonding pattern of ethanol rather than water reveals a change in trend near the similar composition 1 ACS Paragon Plus Environment

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range. As the anomalous behaviour of the physical/dynamical properties along with the pair hydrophobicity in aqueous binary mixture of amphiphilic solutes is common phenomena, our results may provide a general viewpoint on these aspects. 1. Introduction: Water is highly abundant in cellular system. It plays a crucial role in number of complex biological processes1-11. Aqueous binary mixtures (water-ethanol, water-DMSO etc)

12-13

are

also chemically and biologically important systems that are yet to be understood fully due to their complex nature. The widespread applicability of aqueous amphiphilic binary mixtures in diverse fields has made them a topic of special interest. It has been found that such binary mixtures can alter the extent of hydrophobic interaction in protein to a considerable extent1419

. Since, hydrophobic interactions play a crucial role behind protein folding20-22, protein

folding/stability is also markedly influenced in these binary mixtures. Among different other aqueous binary mixtures, water-ethanol binary mixtures have garnered a special attention in recent times14-17, 23-25. Ever since the pioneering work by Frank and Evans26 in 1945, water-ethanol binary mixtures have gained a marked recognition because of their several anomalous behaviour compared to the pure solvents. Since, there are multiple competing interactions in water-ethanol binary systems, it is expected that such interaction will vary at different ethanol compositions. In an experimental study, Nishi and co workers27 have explored the change in local structure at lower ethanol concentration. Koga and co workers28 have shown how microheterogeneity plays an important role in determining physical properties of aqueous ethanol solution. Another recent study by Pozar et.al29 has also indicated how clustering and micro heterogeneity is pivotal in understanding different aspects of aqueous ethanol solution. In a sequence of experimental studies, Biswas and coworkers30,31, using spectroscopic techniques, have reported that water-alcohol binary

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mixtures such as water-ethanol and water-tertiary butanol (TBA) exhibit striking dynamic anomalies at low concentration of alcohol. The structural and dynamic anomalous behaviour are prominent at 10% mole fraction of ethanol and 4% mole fraction of TBA. Biswas and co workers have assigned such anomalies due to a structural transition at those concentrations; however the particular nature of aforementioned structural transition was left unresolved. On the other hand, many computational32-39 and experimental40-48 studies have been performed regarding the impact of aqueous binary mixture on the structure of proteins, polymers and several other systems. By using Fluorescence correlation spectroscopy and molecular dynamics simulation, Bhattacharyya and co-workers14, 23 have manifested that the structure and function of a protein can be altered to a significant extent by regulating the concentration of ethanol in water-ethanol binary mixtures. A decent number of simulation studies have been performed to explain the nature of wateralcohol binary mixtures. Previous simulation studies regarding the aqueous binary mixtures are mostly involved to find out the effect of cosolvents on the structure of proteins14-17 and to understand some aspects of hydrophobic hydration49-50. Fidler and Roger51 used molecular dynamics simulation to analyze the structure of water around ethanol. Bagchi and coworkers16-17, 33 have carried out extensive research on the binary mixture induced structural transformation of polymers, proteins etc. They have studied several aqueous binary mixtures, such as water-ethanol, water-TBA, water-DMSO etc. Their analysis indicates how DMSO composition in the water-DMSO binary mixture affects the pair hydrophobicity of a pair of methane hydrophobe32. Another study by Bagchi and co-workers about the water-ethanol binary mixtures revealed that there is an emergence of a bi-continuous phase at low ethanol concentration (xETOH=0.10) which is attributed to a percolation-like transition33. They have also showed that a linear polymer gets a surprising stability at low ethanol concentration (xETOH=0.05). Therefore, although there are large numbers of studies on the exploration of 3 ACS Paragon Plus Environment


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physical properties of water-ethanol binary mixtures and their effect on protein stability, a quantitative understanding about the effect of water-ethanol binary mixture on the pair hydrophobicity of different hydrophobes is still missing. Hydrophobicity defines the tendency of aggregation of non polar molecules in water. By doing so, they tend to avoid interaction with water or polar substances. More the tendency of aggregation between non polar molecules more is the hydrophobicity. Hydrophobic interaction is generally attractive in nature. One can think about the classic example of oil in water. Oil and water do not mix because hydrophobic oil part forms aggregate between them rather than interacting with water. That is why a clear phase separation between oil and water is observed when we put them together. Often potential of mean force (PMF) is calculated between a pair of hydrophobic molecules to explore the extent of hydrophobic interaction between them. It measures the free energy cost of bringing two solvated hydrophobic molecules from infinity to a particular distance. In such calculations, one frequently encounters a deep minimum in free energy profile when two hydrophobes are in close contact. This minimum is referred as contact minima. Stabilisation of contact minima of PMF profile indicates strengthening of hydrophobic interaction. In the present study, by using molecular dynamics simulation, we report how the pair hydrophobcity of different hydrophobes is altered by various compositions of water-ethanol binary mixtures. The PMFs of a pair of methane-methane, isobutane-isobutane and toluene-toluene hydrophobes have been considered in the present study. The pair hydrophobicity is found to be increased initially upon addition of ethanol up to a certain extent. It undergoes a transition around xETOH=0.10-0.12 and then the pair hydrophobicity starts to decrease. These observations are found to be general for all the three pair hydrophobes considered in this study. The decomposition of the PMF into ethalpic and entropic components demonstrates that, with the addition of ethanol, hydrophobic association between a pair of hydrophobes becomes 4 ACS Paragon Plus Environment

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predominantly enthalpic in nature as opposed to entropic in pure water. We have also shown that several structural, physical and dynamical quantities of the water-ethanol binary mixture reveal irregular trends near the same concentration range. We have found that it is the change in hydrogen bonding pattern around ethanol rather than water bears the signature of the observed anomalous behaviour. Finally, we have revealed that the preferential binding of ethanol around the hydrophobe implies the enhanced hydrophobicity at xETOH=0.10 which further strengthen our PMF results. 2. Details of Simulation: All the simulations have been performed at 300 K temperature and 1 bar pressure. The extended simple point charge (SPC/E)

52

model of water has been used here. Earlier

SPC/E water model was extensively used in studies such as pair hydrophobicity32, polymer chain collapse33 etc. We have carried out all the simulations by using GROMACS (version 4.6.5)53software. Here Gromos53a6 force field54 has been used with united atom description to construct all the hydrophobic molecules and ethanol. For PMF calculation, the simulation boxes were constructed with two hydrophobes (methane-methane or isobutane-isobutane or toluene-toluene) and corresponding solvent molecules. We have used the steepest descent method to minimise the energy of the system. Subsequently, the energy minimized systems were equilibrated under NPT ensemble. The temperature and pressure of the system were maintained by means of Nose-Hoover thermostat55-56 and Parrinello-Rahman barostat57. Periodic boundary conditions were implemented for the non bonded force calculation, we have applied a grid system for neighbour searching. The neighbour list generation has been performed after every 10 steps. We used a cut off radius of 1nm for both neighbour searching and Van der Waal interaction.

Electrostatic interactions were handled by means of the

particle mesh ewald (PME) 58 method with a grid spacing of 0.16 nm and interpolation order of 4. 5 ACS Paragon Plus Environment


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2.1. Potential of mean force (PMF) between two hydrophobes. We have used umbrella sampling method59 for the calculation of Potential of mean force. Here the PMF between the hydrophobes in water as well as different composition of water-ethanol mixtures have been calculated by varying the distance between them. Two hydrophobes with a distance of 0.3 nm configuration was solvated by water/ethanol binary mixture. In order to obtain different hydrophobe-hydrophobe distances, we have gradually varied the distance between two hydrophobes from 0.3 nm to 2.0 nm using steered molecular dynamics simulations. We then chose configurations ranging from 0.3 nm to 2.0 nm at an interval of 0.1 nm for umbrella sampling calculations. We choose such small interval in order to ensure sufficient overlap between each window with its neighbour. The particular distance at every window was maintained by means of a harmonic potential with a force constant of 1000 kJ mol-1 nm-2. We have found nice overlap between each window with its neighbour which ensures efficient sampling of all distances. We have performed 4 ns long umbrella simulation at every window. By using individual histogram of distances at every window, weighed histogram analysis method (wham) 60 has been used to obtain a free energy profile. The PMF profile has been calculated from the free energy profile after the entropy correction. 2.2. Decompositions of potential of mean force (PMF) into enthalpic and entropic part. We have utilised the finite difference method61 to calculate the entropy of association with the help of temperature derivative of free energy. Details regarding the protocols of these calculations have been followed from earlier studies 61-62 3. Results and Discussions:


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3.1. Potential of mean force (PMF) of different hydrophobes in various composition of water-ethanol binary mixture: We have calculated potential of mean force (PMF) between pair of different hydrophobes at varying composition of ethanol in water-ethanol binary mixtures. Methane-methane, isobutene-isobutane and toluene-toluene pairs of hydrophobes have been considered in this purpose. Figure 1 shows the plot of PMF of those three mentioned hydrophobes with varying concentration of ethanol (xEtOH). In case of methane-methane association we have found the contact minima at 0.39 nm whereas the contact minima of isobutane-isobuatne and toluenetoluene association appear around 0.54-0.56 nm. We have found a significant change in the depth of contact minima of all the hydrophobes at various ethanol concentrations as evident from Figure 1. As the depth of the contact minima increases, the hydrophobic association becomes more favourable. Here, nonmonotonicity is observed in the depth of the contact minima with increasing ethanol composition (xEtOH). The depth of the contact minima increases initially up to xEtOH = 0.10 and then it starts to decrease with increasing xEtOH. It is interesting to note that the pair hydrophobicity for all the three hydrophobes is highest at xEtOH = 0.10 and the trends of pair hydrophobicity is also similar for all of them i.e., for all the hydrophobes with addition of little ethanol to water results in increasing pair hydrophobicity up to a certain extent and then with the addition of more ethanol to water results in subsequent decrease of pair hydrophobicity



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Figure 1. Potential of mean force (PMF) of different hydrophobes in various water ethanol compositions. Along x axis distance between two hydrophobe and along y axis PMF is plotted. xEtOH represents the mole fraction of ethanol in ethanol water binary mixture. The error bars are shown in each plot have been calculated using boot-strapping analysis. (a) Methane-Methane PMF, (b) Isobutane-Isobutane PMF and (c) Toluene-Toluene PMF. It is interesting to note that for all hydrophobes, there is an enhanced pair hydrophobicity around xEtOH=0.10. The structure of the hydrophobes at their respective contact minima is shown inside each plot. The increased pair hydrophobicity for all hydrophobes at xEtOH = 0.10 is noteworthy from Figure 2. Here the contact minima of the hydrophobes have been plotted against wide range of ethanol water composition. The plot indicates there exist two distinct region before and after xEtOH =0.10. Upto xEtOH=0.10, the contact minima between two hydrophobes stabilizes gradually and after xEtOH=0.10 the contact minima between two hydrophobes destabilizes monotonically.


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Figure 2. Minima of the (a) methane-methane, (b) isobutene-isobutane and (c) toluenetoluene PMF in various water ethanol compositions. XEtOH represents the mole fraction of ethanol in ethanol water binary mixture. The minima were obtained from PMF plots in Figure 1. Note that the depth is the highest at xEtOH=0.10 for all the hydrophobes. 3.2. PMF of toluene pair of hydrophobes at different temperature in water and in several ethanol-water compositions: To get a comprehensive understanding behind the hydrophobic association in water and in different water-ethanol compositions, it is better to decompose the free energy profile into enthalpic and entropic contributions. Here, the decomposition of PMF profile of toluene pair has been considered. The enthalpy and entropy at 300K can be calculated from the knowledge of PMF at another temperature, closed to 300K. Therefore, we have computed the PMF at 320K in water and different compositions of water-ethanol binary mixtures. The results are shown in Figure 3. The PMF at 300K and 320K were plotted in the same figure for each system. Figure 3(a) shows the PMF in water. One can note that in water, the well depth for the contact pair is larger at 320K compared to 300K. This result is in agreement with recent studies61,62. This scenario is found to be true in case of smallest hydrophobe like



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methane-methane association as well as in case of rod like bigger hydrophobes62. On the contrary, when we considered the pair hydrophobicity in ethanol-water binary mixtures, reverse phenomena have been observed. The PMF profiles for the toluene-toluene association at 300K and 320K in 3%, 10% and 40% ethanol-water binary mixture have been shown in Figure 3(b), 3(c) and 3(d) respectively. The contact pair formation is found to be preferable at 300K rather than 320K.

Figure 3. The PMF profile of toluene pair of hydrophobes in water and in water-ethanol binary mixtures at 300K and at 320K. (a) PMF in pure water. (b) PMF in 3% ethanol. (c) PMF in 10% ethanol and (d) PMF in 40% ethanol. Note that at 320K the contact minimum is more stable in water compare to 300K whereas for aqueous mixtures, a contact minimum is more stable at 300K rather than 320K. 10 ACS Paragon Plus Environment

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3.3. Decomposition of the PMF of toluene molecules into enthalpic and entropic components: The decomposition of free energy into enthalpic and entropic components is needed to elucidate the contribution from enthalpy and entropy factor for the stability of contact pair. Here all the decompositions were performed at 300K. Figure 4 shows enthalpy and entropy components corresponding to PMFs in water and in different compositions of water-ethanol mixtures. One can note that, at the contact minima in water (i.e., xeth= 0.0), both enthalpy and entropy are positive. It indicates that, contact formation is favoured entropically (-TS) but disfavoured enthalpically (H). The magnitude of H and –TS at contact minima are 7.4 and 10.0 kJ/mol respectively (Figure 4(a)). Previous studies have also suggested that hydrophobic association in pure water is driven by an increase of entropy60. Next, we have decomposed the PMF of toluene in water-ethanol binary mixtures. With addition of ethanol, the scenario changes drastically. At 3% ethanol, the contact formation is preferred marginally by enthalpy rather than entropy (Figure 4(b)). The magnitude of –TS and H are 2.4 and -6.0 kJ/mol respectively. At 10% ethanol, contact formation is highly favourable by enthalpic contribution rather than entropy. The magnitudes of –TS and H are large here, 16.5 and -25 kJ/mol respectively (Figure 4(c)). Further increase of ethanol concentration to 40% (Figure 4(d)) reveals that contact formation is still driven by enthalpy but the magnitude is less compared to that of xeth= 0.10. The magnitudes of –TS and H are 2.6 and -5 kJ/mol respectively in xeth= 0.40.



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Figure 4. The decomposition of the PMF profile into enthalpic and entropic contribution for toluene pair of hydrophobes in water and in water-ethanol binary mixtures at 300K (a) in pure water, (b) in 3% ethanol, (c) in 10% ethanol and (d) in 40% ethanol. In water, the contact minimum is entropically driven whereas in mixtures it is enthalpically driven. The corresponding PMF profiles are also shown in each plot. Next, we have calculated the enthalpic component of the solvent contribution (Hsolv) in case of xeth=0.10. This arises from the toluene-water interaction, water-water interaction, waterethanol interaction, ethanol-ethanol interaction and the mechanical pressure-volume work (P∆V). Hsolv is calculated by subtracting the toluene-toluene interaction energy from the total enthalphy (H) at different separation distances. The interaction energy between toluene and solvent was calculated at different toluene-toluene separation. At large separation, this value is shifted to zero. In this way, the toluene-solvent enthalpy contribution (HM-solv) is computed. Now, by subtracting HM-solv from the total solvent enthalpic contribution (Hsolv), we obtained the remaining enthalpy of solvent part (Hrem). Hrem consists water-water, water-ethanol and 12 ACS Paragon Plus Environment

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ethanol-ethanol interactions and the mechanical work (P∆V) term. Figure 5 depicts how different components of solvent enthalpy changes with separation distance at xeth= 0.10 at 300K. It is noticeable from the figure that solvent enthalpy is mostly governed by Hrem part rather than HM-solv part. The magnitude of Hsolv at contact minima is -26.0 kJ/mol. The value of Hrem at contact minima is -30.0 kJ/mol which is closer to Hsolv whereas the magnitude of HM-solv is only 5.0 kJ/mol. Therefore, the stabilisation of the contact minima of toluenetoluene association at xeth= 0.10 is predominantly due to the gain in mixing enthalpy as a results of the transfer of solvent from confined space between two hydrophobes to the bulk.

Figure 5. Decomposition of solvent enthalpy contribution (Hsolv, black) into enthalpy change due to solvent solvent interaction and mechanical work (Hrem, red) and to the toluene-solvent interaction (HM-solv, blue) at 300K. Most of the solvent contribution arises due to the solvent solvent interaction. 3.4. Analysis of water-ethanol binary mixture at various compositions: In the previous section, we have discussed about the thermodynamic origin for the observed nonmonotonicity of pair hydrophobicity in water-ethanol binary mixture. In order to correlate this phenomenon to the properties of water-ethanol binary mixture, we have calculated a host of physical properties of water-ethanol binary mixtures at various compositions. We have



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calculated relative average composition fluctuation of the components of the system, mean square fluctuation of total dipole moment of the system and diffusion coefficient of water and ethanol in various water-ethanol compositions. It has been noticed that certain anomalous behaviour of the calculated quantities appears near/around 10% composition range. A. Exploring structural and dynamical aspects of water ethanol binary mixture at different composition: To gain insight into the structural features at various compositions of ethanol water binary mixtures, we have calculated relative average composition fluctuation (χ) of both ethanol and water within 0.6 nm at the contact minima of the hydrophobes. We chose toluene pair of hydrophobes for this analysis. The plots of relative average composition fluctuation (χ) of ethanol and water with varying concentration of ethanol (xEtOH) are shown in Figure 6(a) and 6(b), respectively. The relative average composition fluctuation of ethanol χ EtOH

χH

2O

and water

can be calculated as:-

N H 2 0i N EtOH i i X ; = H2O N EtOH i + N H 2 0i N EtOH i + N H 2 0i

X EtOH i =

χ EtOH i = X EtOH i − X EtOH ; χ H O i = X H 2

χ EtOH =

1 N step

Nstep

∑ ( χ EtOH i ); χ H O = 2

i =1

i 20

− X H2 0

1 N step

Nstep

∑ (χ

i H2 0

)

i =1

Here N EtOH i is the number of ethanol molecule and N H 2 0i is the number of water molecule at i-th step within a cut off distance from the hydrophobes. X EtOH and X H 2 0 is the average composition of ethanol and water molecules. χ EtOH represents relative average composition fluctuation of ethanol and χ H 2 O is relative average composition fluctuation of water. 14 ACS Paragon Plus Environment

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It has been noticed from Figure 6(a) that is significantly high around xEtOH = 0.07 region. It suddenly decreases to a considerable extent at xEtOH= 0.10-0.12 region and then it increases slightly at xEtOH= 0.15 before decreasing continuously with the increase of xEtOH. The variation of χH2O with xEtOH is also non linear as observed from Figure 6(b). χH2O also shows irregular trends around xEtOH=0.10-0.12.

Figure 6. Relative average composition fluctuation χ of (a) ethanol and (b) water in different composition of ethanol-water mixture. xEtOH indicates the mole fraction of ethanol in ethanol water binary mixture. Note the irregular trends in both the quantities around xEtOH =0.10-0.12 range. Next, we calculated the diffusion coefficient of ethanol and water at various xEtOH as shown in Figure 7(a) and 7(b). Diffusion co-efficient (D) were calculated from the slope of mean square displacement at longer time according to Einstein’s relation. The diffusion coefficient of ethanol (DEtOH) initially decreases steadily with increasing ethanol concentration upto xEtOH=0.10, then increases slightly at xEtOH= 0.15. Beyond xEtOH= 0.15 diffusion of ethanol



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molecules decreases with increasing ethanol concentration. The diffusion coefficient of water (Dwater) has been shown in Figure 7(b). It indicates water diffusion also shows irregularity at that particular composition range.

Figure 7. (a) Diffusion coefficient of ethanol in different composition of ethanol-water mixture. The anomalous region has been circled in the plot. (b) Diffusion coefficient of water in different composition of ethanol-water mixture. Here also, the marked region indicates the irregular trend. xEtOH represents the mole fraction of ethanol in ethanol water binary mixture. Next, we have calculated root mean square fluctuation of the total dipole moment of the system at various water-ethanol compositions. The fluctuation of total dipole moment can be calculated as:-

δ Mi = Mi − M The mean square fluctuation can be obtained as:

(δ M )

2

=

1 N step

∑ (δ M )

2

i

i


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Here Mi is the total dipole moment of the system at the i-th step. We have shown the variation of root mean square fluctuation of the dipole moment at various composition of the waterethanol binary mixture in Figure 8. Initially the mean square fluctuation of total dipole moment decreases till xEtOH =0.10 and then it increases at xEtOH =0.15. Beyond this range, it decreases with further increasing in xEtOH . So, we have seen that around xEtOH =0.10-0.15 ethanol composition, water-ethanol binary mixture exhibits many anomalous behaviour such as anomaly in the average composition fluctuation, diffusion of ethanol and water and that mean square fluctuation of total dipole moment around xEtOH =0.10-0.15. All these analyses indicates some kind of structural/dynamical changes of the system around xEtOH =0.10-0.15.

Figure 8. Mean square fluctuation of total dipole moment () at different composition of ethanol-water mixture. Here xEtOH represents the mole fraction of ethanol in the ethanol water binary mixture. Note that around 10-15% ethanol concentration, there is a significant deviation from linearity. We have also calculated radial distribution function, g(r), of ethyl groups of ethanol molecules. The plot is shown below in Figure 9(a) for xETOH of 0.10 and 0.40. The larger peak value at xETOH=0.10 as compared to xETOH=0.40 indicates comparatively more



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association through hydrophobic interactions. We have also determined average number of ethyl groups around each ethyl group within a cut-off of 0.7 nm (this cut off was obtained from the g(r) plot as shown by blue dotted line) and the results are shown in Figure 9(b). One can note that with increase of ethanol concentration, this number increases steadily up to xEtOH = 0.10-0.12 and after that point steepness of the slope changes significantly.

Figure 9. (a) Represents the radial distribution function of ethyl groups of ethanol at two different concentrations. Note that the peaks appear in the similar region. The first minima of the plot are denoted by blue dots. (b) indicates the variation of average number of ethyl groups around each ethyl group within a cut off distance of 0.7 nm. Here xEtOH represents the mole fraction of ethanol in ethanol water binary mixture.

B. Hydrogen bond analysis at different composition: We have calculated the average number of ethanol-ethanol and ethanol-water hydrogen bond per ethanol molecule in different compositions of water-ethanol binary mixture. The results have been presented in Figure 10(a). It is clear from the analysis that average number of ethanol-ethanol hydrogen bond increases with increasing concentration of ethanol (xEtOH)


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whereas the reverse phenomena has been observed in case of average number of ethanolwater hydrogen bond. It is interesting to note from Figure 10(a) that the linearity of the plot breaks after xEtOH ~ 0.15. This composition dependent anomaly of number of hydrogen bond per ethanol molecule is true for both ethanol-ethanol and ethanol-water hydrogen bond pattern. We have also checked the average number of water-water and ethanol-water hydrogen bond pattern per water molecule at different composition. The results are displayed in Figure 10(b). It can be noted that unlike 10(a), here both for water-water and ethanol-water hydrogen bond pattern, the linearity holds. These results indicate that the change in different type of hydrogen bond pattern of ethanol molecule correlates with the observed anomalous behaviour of pair hydrophobicity and physical properties.

Figure 10. (a) Average number of ethanol-ethanol and ethanol-water hydrogen bond per ethanol molecule is shown as a function of ethanol concentration (xEtOH). Note that with increase of ethanol concentration water-ethanol H-bonds decreases whereas ethanol-ethanol H-bond increases. (b) Average number of water-water and ethanol-water hydrogen bond per water molecule is shown as a function of ethanol concentration (xEtOH). Note that, here with increase of ethanol concentration, the linearity of the plot remains intact.



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C. Preferential organisation of ethanol around hydrophobes: To probe the organisation of ethanol around the toluene pair of hydrophobes, we have introduced an experimentally relevant parameter referred as preferential binding coefficient, Γ E , which can be defined as:-

Γ E = nE −

N E tot − nE ⋅ nw NW tot − nW

Here nE is the number of ethanol around the hydrophobe and N E tot is the total number of ethanol in the system. nW is the number of water around the hydrophobe and NW tot is the total number of water present in system. Γ E reports that the excess cosolutes (here ethanol) present around the hydrophobes compare

to the overall concentration of cosolutes in the solution. We have calculated this parameter in two conditions—when the two hydrophobes are in close contact and also in case where they were far apart from each other. Γ E was calculated at xEtOH = 0.10 and at xEtOH = 0.40. The distance dependences of Γ E are shown in Figure 11. In all the conditions, Γ E values are generally higher than zero within the first solvation shell (~ 0.57 nm). This indicates a preferential binding of ethanol around the hydrophobes. However, at xEtOH = 0.10, Γ E value at contact condition is higher than when hydrophobes are well separated. This result implies that at xEtOH = 0.10 the hydrophobes prefer to stay as collapsed. On the other hand, at xEtOH = 0.40, situation is completely reversed. Here Γ E value at contact condition is smaller than when hydrophobes are well separated. This indicates that the hydrophobes tend to stay apart 20 ACS Paragon Plus Environment

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from each other. This result also correlates well with the results obtained from the PMF calculations.

Figure 11. Wyman-Tanford preferential binding coefficient of ethanol ( Γ E ) for (a) xEtOH = 0.10 and for (b) xEtOH = 0.40. Here Γ E is plotted against the distance from hydrophobes in contact condition and in separated state. Note that in case of xEtOH = 0.10, Γ E is higher when two hydrophobes are in close contact but in case of xEtOH = 0.40, Γ E is higher when the hydrophobes are separated from each other. Vertical blue dotted line indicates the first solvation shell. Blue arrows indicate the difference in Γ E in different cases.

4. Conclusion: This work manifests how different composition of water-ethanol binary mixture influences the pair hydrophobicity of several hydrophobes. We have noticed that pair hydrophobicity increases initially up to xEtOH ~0.10 for all the hydrophobes. Then it starts to decrease with increasing ethanol concentration. The increased pair hydrophobicity upon addition of ethanol in water has been attributed to the gain in mixing enthalpy upon association. In order to 21 ACS Paragon Plus Environment


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pinpoint the origin of such composition dependent anomaly, we have analysed the relative average composition fluctuation, diffusion coefficients of the constituents of binary mixtures, mean square fluctuation of total dipole moment and association propensity of ethyl sidechains at various composition range. The results indicate certain anomalies around that particular composition range of xEtOH ~0.10-0.15. Interestingly, the hydrogen bonding analysis show that hydrogen bonding pattern of ethanol rather than water reveals a change in trend near the similar composition range. Finally, the calculation of preferential binding coefficient calculation of ethanol at different composition further strengthens our PMF observations. Similar type of enhanced pair hydrophobicity is also observed in case of other aqueous amphiphilic binary mixtures in earlier studies. Further insightful investigations are required to verify the possibility of the presence of enthalpic contribution in the hydrophobic association in other aqueous binary mixtures.

AUTHOR INFORMATION CORRESPONDING AUTHOR E-mail: [email protected]. Phone: +913324734971. Fax: +913234732805

Notes: The authors declare no competing financial interest.

Acknowledgments: The authors gratefully acknowledge the central supercomputing facility (CRAY) at Indian Association for the Cultivation of Science, Kolkata for providing computational resources. R.H. is thankful to CSIR for providing the fellowship.


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Unravelling the Composition-Dependent Anomalies of Pair

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