How Hydrophobic Hydration Destabilizes Surfactant Micelles at Low

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Interface Components: Nanoparticles, Colloids, Emulsions, Surfactants, Proteins, Polymers

How Hydrophobic Hydration Destabilizes Surfactant Micelle at Low Temperature: A Coarse-grained Simulation Study Gregory S Custer, Hongcheng Xu, Silvina Matysiak, and Payel Das Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.8b01994 • Publication Date (Web): 24 Sep 2018 Downloaded from http://pubs.acs.org on September 25, 2018

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How Hydrophobic Hydration Destabilizes Surfactant Micelle at Low Temperature: A Coarse-grained Simulation Study Gregory S. Custer,† Hongcheng Xu,‡ Silvina Matysiak,∗,†,‡ and Payel Das∗,¶,§ Fischell Department of Bioengineering, University of Maryland, College Park, Maryland 20742, United States, Biophysics Program, Institute of Physical Science and Technology, University of Maryland, College Park, Maryland 20742, United States, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598, United States, and Department of Applied Physics and Applied Mathematics, Columbia University, NY 10027 E-mail: [email protected]; [email protected]

Abstract Micelles are self-assembled aggregates of amphiphilic surfactant molecules that are important in a variety of applications, including drug delivery, detergency, and catalysis. It is known that the micellization process is driven by the same physiochemical forces that drive protein folding, aggregation, and biological membrane self-assembly. Nevertheless, the molecular details of how micelle stability changes in water at low temperature are not fully clear. We develop and use a coarse-grained model to investigate how the interplay between non-ionic surfactants and the surrounding water at ∗

To whom correspondence should be addressed UMD-BIOE ‡ UMD-IPST ¶ IBM § Columbia †

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the nano-scale affects the stability of micelles at high and low temperatures. Simulations of pre-formed C12 E5 micelles in explicit water at a range of temperatures reveal the existence of two distinct surfactant conformations within the micelle, a bent structure and an extended structure, the latter being more prevalent at low temperature. Favorable interactions of the surfactant with more ordered solvation water stabilizes the extended configuration, allowing nano-scale wetting of the dry, hydrophobic core of the micelle, leading to the micelle breaking. Taken together, our coarse-grained simulations unravel how energetic and structural changes of surfactant and the surrounding water destabilize micelles at low temperature, which is a direct consequence of the weakened hydrophobicity. Our approach thus provides an effective mean for extracting the molecular level changes during hydrophobicity-driven destabilization of molecular self-assembly, which is important in a wide range of fields, including biology, polymer science, and nanotechnology.

Introduction Micellization of surfactants is a critical process with many biological, industrial, and medical uses. 1–4 Micelles are one of many microstructures that can be formed from surfactants, depending on the thermodynamic conditions, surfactant concentration, and other properties of the solution. 5,6 In a polar solvent, micelles are organized surfactant aggregates with a hydrophobic core and a hydrophilic shell. Their ability to carry nonpolar solutes through a polar solvent makes micelles useful as detergents, dispersants, emulsifiers, and drug-delivery vehicles. 1–4,7 A primary driving force behind surfactant self-assembly into micelles is the hydrophobicity. 8–10 Solvation of the hydrophobic tails of surfactant is minimized by their placement at the core of the micelle. Micelles and their formation have been studied using experimental techniques including NMR, 11–14 calorimetry, 10,15 light scattering, 16,17 small angle neutron scattering, 18 sedimentation equilibrium, 19 and HPLC. 20,21 Experimental studies have characterized the critical

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micelle concentration (CMC) of many surfactants, the concentration above which surfactants spontaneously aggregate into micelles, as well as other physical properties, such as aggregation number, size, and shape. 5,6,10,19,22–24 The CMC of surfactants varies with temperature, with the CMC-temperature relationship typically appearing parabolic for nonionic surfactants, with a minimum in CMC occurring at an optimal temperature for micelle formation. When temperature is increased or decreased from this optimal temperature, the CMC increases and a higher surfactant concentration is required for micelle formation. 10,22,23 Thus, at a given surfactant concentration it is possible to observe micelle destabilization at both low and high temperatures. Solvation is thought to play a key role in determining micelle stability and has also been studied experimentally. Evidence indicates that, while a micelle has a dry inner core, the polar shell of a micelle is highly solvated and a considerable portion of the hydrophobic surface is in contact with water. 20,21,25,26 Experiments have also identified a dehydration of micelles that occurs with increasing temperature. 20,21,25 While both the CMC increase and enhanced hydration of the micelle at low temperature are known, the molecular details of micelle destabilization at low temperatures have not been characterized. In particular, it is difficult to capture the detailed solvation profile of the micelle experimentally or characterize changes in organization of individual surfactants. Experiments are also limited in examining the transient micelle structures, during their formation or destabilization. Molecular dynamics simulations served as a useful tool for providing a more detailed view of the physical properties of micelles. 27–40 Both formation of non-ionic micelles and destabilization are slow processes, and can require simulations that are longer or equal to 1µs to study. 34,41 The large system size required to study the dilute concentrations at which micelles form, combined with the lengthy simulation, make all-atom simulations of micelles in explicit water computationally challenging. As water typically represents the bulk of the computational costs in simulation, one approach to study aggregation is to treat water implicitly. Several models utilizing implicit solvent have been developed for studying micellization and properties of micelles. 38,42,43 While these models have provided valuable

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insight into the properties of micelles, the lack of explicit solvent interactions makes them unsuitable for examining the role of solvation in micelle stability. An alternative to reducing the computational burden of treating the solvent explicitly is to group multiple water beads into a single interaction site. 29,34,36,44 However, in these models the inability to represent the effects of hydrogen bonding makes it difficult to accurately capture the water phase diagram, and thus to model changes in solvation with varying temperature. In this study, we have developed an off-lattice coarse-grained model of non-ionic surfactants designed for studying the interplay between intersurfactant interactions and solvation as a function of temperature, which allows us to underpin the molecular details of micelle stability. Using this model we study the aggregation of n-alkyl polyethylene glycol surfactants (Cn Em ), a common nonionic surfactant frequently used in medicine, industry, experiments, and simulations. 45 To reduce computational costs, while preserving the unique structural properties of water, we employ the single particle mW water model. 46 This model employs the three-body Stillinger–Weber (SW) potential 47 to emulate the hydrogen bond network found in water, by enforcing a tetrahedral angle between neighboring water beads. Without any explicit accounting of electrostatic interactions, this model is able to accurately capture the phase diagram of water. 46 We have previously developed homopolymer, heteropolymer, and protein models which we used in combination with the mW water model to study the role of solvation in protein folding. 48–50 The work presented here adopts a similar approach to study the solvation and stability of non-ionic C12 E5 micelles across a range of temperatures. In the present model, the SW potential is also used to represent polar interactions that involve surfactants, i.e, inter-surfactant and surfactant-water interactions. Each heavy atom in the surfactant is represented by a single bead, with four bead types used to represent the different carbon and oxygen atoms within the surfactant. We characterize C12 E5 micelle structures in water and evaluate how changes in the structure and solvation of the micelle contribute to its destabilization at low and high temperatures.

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Experimental Model In the study presented here, we have represented each heavy atom and its bonded hydrogen atoms as a single CG bead. Four different bead types, shown in Figure 1, are used to represent the non-ionic surfactant pentaethylene glycol monododecyl ether (C12 E5 ). The beads differ by the element type and the hydrophobicity of the domain. The terms “head” and “tail” are used here to refer to ether domain (first 17 atoms of the molecule) and alkyl domain (last 11 carbon atoms of the molecule), respectively. The Ch bead represents the tail-domain carbons, while Cp represents the head-domain carbons. Ether oxygens are represented by the O bead, while the terminal hydroxyl group is represented by the OH bead. The model incorporates the mW model to represent water. 46 Due to their similar chemical nature, OH and water beads are treated identically. Mass for each bead is based on its atomic counterpart, including hydrogen where appropriate. The mW and OH beads have a mass of 18.015 g/mol, 46 the Ch and Cp beads have a mass of 14.01 g/mol (carbon with two hydrogen atoms), and the O bead has a mass of 16 g/mol. Parametrization of this CG model was performed by comparing and matching the properties of the CG system to all-atom simulations of surfactant molecules. The all-atom (AA) force-field AMBER99, which has been validated extensively against experimental observations, was used to model the surfactants. 51 The water was modeled using the SPC/E 52 water model and the GROMACS 53–56 simulator was used. In those simulations, two randomly distributed surfactants were immersed in explicit water. Both AA and CG simulations were performed at temperatures of 275, 300, and 350 K and the results were compared. Parameters within the CG model were adjusted so that intra-surfactant and surfactant-water interactions match closely to what was observed in AA simulations. Full details of this parametrization procedure are available in the supplementary material. In the derived CG model, bonds and angles between surfactant beads are represented by

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simple harmonic potentials. Parameters used for all bond and angle potentials in our system can be found in Table 1. As all heavy atoms are represented explicitly, bond lengths and angles between atoms were taken directly from the AMBER99 force field. 51

Figure 1: Line and CPK representations of C12 E5 . Atoms in line representation color-coded by CG bead type.

Table 1: Bonded parameters Bonds Bead types r0 (˚ A) K (kcal/˚ A2 ) C-C 1.526 248 C-O 1.410 256 Angles Bead types θ0 (◦ ) K (kcal/rad2 ) C-C-C 109.5 12 C-C-O 109.5 12 C-O-C 109.5 12

Non-bonded interactions involving nonpolar beads (Ch and Cp) were represented by a 9-6 Lennard-Jones potential, with parameters for interactions between all pairs of beads described in Table 2. The Stillinger-Weber (SW) potential was used to represent non-bonded interactions between polar beads (O and OH/mW). Again, due to their similarity, the model treats OH and mW beads identically. The three-body angular penalty component of the SW potential was used to enforce the tetrahedral hydrogen bond network found in water. 46 The SW potential has been used in the past to account for hydrogen bonding in water, polymerwater, and peptide-water systems. 46,48–50 Here we use this potential to emulate water-water, water-surfactant, and surfactant-surfactant hydrogen bonding. For the interactions represented by the SW potential, initial parameters in the potential were set as found in Molinero 6


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and Moore. 46 Parameters controlling the potential well depth(), bead size (σ), and strength of the three-body interaction (λ) were modified for each interaction type involving surfactant beads (shown in Table 2). Since ether oxygens are unable to act as hydrogen bond donors, strength of the three-body interaction was reduced by a factor of 1/6 for all interactions that involve one O bead and two mW beads, and by 1/3 for all interactions involving two O beads and one mW beads. The three-body interaction was not considered for interactions involving only O beads, as they cannot form hydrogen bonds. Full details of the parametrization can be found in the supplementary material. Table 2: Non-bonded parameters Lennard-Jones Bead types (kcal/mol) σ (˚ A) Ch-Ch 0.204 4.0 Ch-Cp 0.224 4.0 Cp-Cp 0.204 4.0 Ch-O 0.255 3.55 Ch-OH/mW 0.30 3.7 Cp-O 0.289 3.55 Cp-OH/mW 0.40 3.7 Stillinger-Weber Bead types (kcal/mol) σ (˚ A) a mW/OH-mW/OH-mW/OH 6.189 2.3925 mW/OH-mW/OH-O 5.250 2.25 mW/OH-O-O 5.250 2.25 O-O-O 0.6375 2.1 a Parameters for mW bead taken from Molinero, et

λ 23.15 19.29 15.43 0.0 al. 46

Simulation Setup CG simulations of the C12 E5 surfactant were performed using the LAMMPS molecular dynamics package. 57 Surfactants were placed in a cubic box and solvated with CG water. Surfactant concentration in simulations was set to 16mM (approximately 0.65% by weight). This concentration was chosen as it is above the experimental critical micelle concentration at 300K and 1 atm (0.062 mM), 58 but below the concentration needed to reach more complex 7


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mesophases (as high as 30 wt%). 5,6 Initial test simulations indicated that this concentration is high enough (above CMC) that we can observe micelle formation on a feasible timescale, while it is still lower than what is needed for the transition to more complex mesophases. Integration was performed using the Verlet integrator with a timestep of 8 fs. 59 Velocities were initialized using a Boltzmann distribution at the appropriate temperature. Temperature and pressure were regulated using the Nosé-Hoover thermostat/barostat, 60,61 with temperature of the water and surfactant maintained independently. Pressure was set to 1 atm, with temperature varying depending on the simulation. Damping time was 100 fs for temperature coupling and 1 ps for pressure coupling. Two initial CG simulations of micelle formation were performed at a temperature of 350 K to generate micelles for use in further simulations. Simulations of micelle formation had a system size of 160 surfactants in water at a concentration of 16 mM. The systems initial system configuration was comprised of surfactants randomly distributed within the simulation box. Next, 543160 water beads were added to solvate the surfactants. A large, stable micelle formed in each simulation. To compare the window of stability for micelle formation, CG simulations of micelle formation were also performed at 275, 300, and 500 K. CG simulations of micelle breakdown were initialized from pre-formed micelles containing 50 surfactants, as obtained from the simulations of micelle formation at 350 K. For each simulation, a single micelle was placed in a cubic box, such that the overall surfactant concentration was 16 mM. Approximately 172360 water beads were added to solvate the micelle. Two simulations were performed at each temperature, each starting from a different initial micelle configuration, shown in Figures 2A and 2B. Based on the micelle sizes observed for these simulations (Supplementary Figure S3A), micelles containing 50 surfactant appear to be stable at 350 K. Thus micelles of size 50 were used as the initial structures for simulation of pre-formed micelles. The size of our preformed micelles is similar to that observed by others, as computational studies have indicated an average micelle size of 55-56 for C12 E5 at similar concentrations. 34,62 We observe roughly spherical micelles with an average radius of

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approximately 27 ˚ A for a micelle size of 50 (Supplementary S3B), while experiments have reported formation of both spherical and cylindrical micelles for similar surfactants, which have an average radius of approximately 25-27 ˚ A. 63 Thus, despite the coarse-grained nature of the model, our simulations closely match with experiments and can, therefore, be used to capture qualitative changes in micellization with temperature. Simulations of micelle breakdown were performed at temperatures of 275, 300, 350, and 500 K. Simulations were extended until a consistent trend of micelle stability was apparent (either the micelle was completely dissipated in the solution or the micelle was stable). Simulations of a single CG surfactant in water were performed at temperatures of 275, 350, and 500 K. The surfactant was placed in a cubic box and solvated with 5203 water beads. Each simulation was run for 10 ns. Simulations were also performed of pure CG water for calculation of bulk water properties. A cubic box with edge lengths of 30 ˚ A was filled with 895 water beads. Simulations were performed at 275, 300, 350, and 500 K. Each simulation was run for 20 ns. Surfactant pulling simulations were set up to calculate the free energy to extract surfactant from the micelle. The pulling simulations were performed at 275K and 350K. The initial conformations for the pulling simulations were taken from 180ns of micelle breakdown simulations. In the pulling simulation, one surfactant in the micelle was pulled toward the opposite direction from micelle center of mass using “fix smd” command in LAMMPS. The pulling rate was set to 1/ns. The pulling simulation time was 50ns. Surfactants that were not pulled in the simulation were constrained in place at the 11th bead from hydrophobic side. For each temperature (350K and 275K), 4 pulling simulations were set up to extract one randomly selected surfactants at a time. The potentials of mean force were then averaged among 4 pulling simulations at each temperature for comparison.

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Graphics and Visualization Images of molecular structures in this work were generated using VMD. 64 Unless otherwise noted, red colors have been used for beads belonging to the head groups of the surfactant and blue colors for the tails.

Identification of Micelles Micelles were identified using a modified version of the GROMACS tool g clustsize. 53–56 Surfactants were grouped such that all surfactants within a cluster have a minimum number of contacts, N, to other surfactants within that cluster. Surfactants are considered to be in contact when the distance between any beads belonging to the surfactants is lower than a cutoff, Rcut . Both N and Rcut were optimized to identify clusters in a robust manner. The optimal value we identified for N was 7 contacts. Rcut was found to be optimal at 4.5 ˚ A. Micelle size in this work refers to the number of surfactants within a micelle, as estimated by the clustering algorithm described above. As many micelle properties vary with size, a minimum micelle size of 35 and maximum micelle size of 50 was chosen for analysis. Micelle properties studied showed little variance with size across this range. Additionally, this range in micelle size was represented at each temperature. In addition to identifying micelles, we must also identify surfactants participating in the core of a micelle. As the core of a micelle is predominantly made up of interacting hydrophobic domains, interactions between the Ch beads of surfactants were used to identify the core. To define these clusters of Ch beads which make up the core, the clustering was performed using only Ch beads, again with N=7 contacts and Rcut =4.5˚ A.

Micelle Radius Mean radii of micelle structrues were calculated using the convex hull of the micelle. A convex hull was calculated using all surfactants in the micelle, and the mean radius of the

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micelle was taken to be the average distance between the center of mass of the micelle and the surfactant beads on the surface of the convex hull.

Classification of Positions within Micelle Positions of beads within the micelle were defined with respect to the center of mass of the micelle and were then normalized. Normalization of distances to the center of the micelle was based on an ellipsoid model for the micelle. Axes of the ellipsoid were set to the principal axes of the micelle, with the length of each axis of the ellipsoid set equal to the radius of gyration of the micelle around each of the principal axes. For each bead, i, the normalized distance to the center would be calculated as following: |ri | 2 3 P ri ·Rg,n

rnorm,i = s

n=1

(1)

|ri |

where Rg,n is the radius of gyration around the nth principal axis and ri is the vector extending from the center of mass of the micelle to the ith bead. Thus, the normalization factor for each distance to a bead is the radius of the ellipsoid which passes through that bead.

Water Tetrahedral Order Parameter The orientation of water beads in bulk and in the solvation shell around surfactant was characterized by using the order parameter, q, calculated as: 65,66 2 3 4 3X X 1 q =1− cosψjk + 8 j=1 k=j+1 3

(2)

where ψjk is the angle between vectors extending from the given water bead to two of its four nearest neighbors, j and k. This order parameter scales between 0 for an ideal gas and

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1 for a perfect tetrahedral network. 65,66

Water energy Total potential energy for bulk and solvation water represents the total pairwise interaction energy for each water bead, as calculated within the simulation. Solvation water includes all water beads within 4 ˚ A of each surfactant bead.

Contact disruption as surfactant leaves micelle Contacts between surfactants transitioning out from the micelle to solvent and surfactants that remain within the micelle were quantified. For this analysis, we first identified surfactants that were originally part of the micelle and moved completely to the solvent. A surfactant was considered to transition out from micelle to bulk at a time t0 if: 1) The micelle was made up of at least 35 surfactants; 2) at time t0 the surfactant was completely out of the micelle; 3) the surfactant was part of the micelle’s core for at least 1.6 ns of the 2 ns before t0 ; 4) the surfactant was not classified as part of the micelle’s core for at least 1.6 ns of the 2 ns after t0 ; 5) within 4 ns of time = (t0 + 2 ns), the surfactant spent 1.6 ns of a 2 ns time period completely out of the micelle. If all of these conditions were met at a time point, t0 , then the surfactant was considered to have transitioned from the micelle to the solvent at time t0 . The requirements were carefully chosen to explicitly include transitions during which the surfactant, originally part of the miclle, fully transitions out of the micelle and to make this analysis insensitive to transient contacts between a leaving surfactant and the micelle. After identifying surfactants which leave the micelle and the transition time (t0 ), contacts between transitioning surfactants and the micelle were counted. Contacts were classified based on the contacting domain (head and tail). For example, any contact between head group of surfactant and tail domain of micelle is counted as head-tail contact. A contact was considered to be formed when the distance between two beads was less than or equal 12


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to 4.5 ˚ A. The evolution of contacts were estimated during a 4 ns window centered at t0 for each transition. The results shown in this paper are averages of all such transitions, in which the number of contacts (N) is normalized with respect to the maximum N at 350 K for that specific contact type.

Results and Discussion Initial structures for the pre-formed micelles at 350 K used in simulation are shown in Figures 2A and 2B. At other temperatures (275, 300, and 500 K), micelle formation was not observed within 150 ns. A window of thermal stability is observed from the maximum cluster size time series (Figures 2C- 2D). Maximum stability is observed at 350 K, while high temperature destabilization is observed at 500 K and low temperature destabilization occurs at 275 and 300 K. It is also apparent that destabilization occurs more rapidly at 500 K compared to that at low temperature (275 and 300 K). At 275 K, the micelle breaks apart slowly but steadily. As temperature increases to 300 K, the micelle takes longer to break apart, but remains unstable. We observe the same window of thermal stability for simulation of micelle formation from randomly distributed surfactant, with micelle formation not occurring at 275, 300, or 500 K (Supplementary Figure S3A). High temperature destabilization is an entropic effect, as a micelle is an ordered structure. 10 At low temperatures micelle breakdown is not as intuitive, but might be expected to occur due to changes in water properties and the associated impact on surfactant hydration, similar to cold denaturation of proteins. 67–69 A CMC increase at low temperature has been experimentally reported for a number of surfactants, indicating that cold destabilization does occur for micelles. 10,22,23 To our knowledge, simulations of cold destabilization of micelles have not been previously reported. Since cold destabilization is driven by changes in surfactant solvation, it requires a water model, such as the mW water model, that accurately captures the water phase diagram. 46 To investigate the molecular factors underlying the micelle destabilization at lower tem-

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Figure 2: A and B) Structures of the two initial micelles used for simulation of micelle breakdown. Nonpolar domains are shown in blue, polar in red. C and D) Maximum cluster size vs time for simulation of micelle breakdown at 275, 300, 350, and 500 K.

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peratures, we first examined structural properties of individual surfactants and of the micelle. The distribution of radius of gyration (Rg) at each temperature for monomeric surfactant is shown in Figure 3A. As temperature increases, a second peak with decreased Rg becomes

Figure 3: Properties of surfactant and micelles at varying temperatures. A) Distribution of radius of gyration for monomer surfactant. Example of surfactants with Rg of 5 and 8 ˚ A, shown with nonpolar domain in blue and polar domain in red. B) Distribution of angles between the polar domain of surfactants in the micelle shell and a line between the center of the polar domain and the center of the micelle. C) Average density at varying positions within the micelle for the polar domain (solid line) and nonpolar domain (dashed line) beads. D) Example micelle structures from 275 K and 350 K simulations. Color scheme of B-C is the same as used in A. accessible, with the surfactants folding into a hairpin-like structure in which the hydrophobic tail is in contact with the polar head. This folding is also manifested by the angular distribution between the head group of a surfactant within the micelle and a vector between the center of the micelle and that same head group (Figure 3B). At lower temperatures (275 and 15


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300 K), surfactants within the micelle remain extended, with a peak at low angles between the polar head and a vector to the micelle center, while at higher temperatures (350 and 500 K) the distribution shifts to larger angles. Thus, we observe folding of polar head groups for individual surfactants against the micelle as temperature increases. This may contribute to the increased stability of the micelle by both reducing the overall envelope of the micelle and reducing the portion of the hydrophobic core accessible to solvent. Changes in the distribution of tail and head group beads within the micelle at different temperatures are also investigated. Figure 3C gives the density of beads belonging to the head and tails of surfactants within the micelle as a function of position within the micelle. As expected, beads from the nonpolar tails are found primarily in the core of the micelle, and polar heads found primarily in the outer shell of the micelle. We will refer to the inner portion of the micelle primarily composed of tail beads as the core, stretching out to a normalized distance of approximately 1.0 units from the center of the micelle. The region with a higher head group density is referred to as the shell of the micelle, covering the region from 1.0 to the micelle edge at approximately 1.8-2.0 units from the center of the micelle. In the interface between the core and shell of the micelle, from 0.75-1.25 units, we find both tail and head group beads. At high temperatures, the micelle becomes more disordered, with the density of the polar head groups in the micelle core increasing. As temperatures decreases below 350 K, we observe a drop in density of the head groups in the outer shell of the micelle. This is consistent with the polar domains remaining extended. To further examine the orientation of the polar head groups, we calculated the angle between a line fit to the beads of the polar head group of a surfactant and a line from the center of mass of that same polar head group (point b in the inset schematic of Figure 3B to the center of mass of the micelle (point a in the inset schematic). The distribution of these angles, shown in Figure 3B, indicates that the polar head groups fold against the surface of the micelle at higher temeperature, increasing their density near the micelle core. We also observe an increase in the density of the nonpolar core of the micelle at temperatures below 350 K.

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Taken together, these structural properties provide us with an overall picture individual surfactant organization within the micelle. At 275 K, the radius of gyration indicates an extended conformation for individual surfactants. The alignment of the polar head groups with the radius of the micelle and the decreased density of polar head groups in the outer shell of the micelle indicates that those surfactants extend straight out from the center of the micelle, which leaves much of the hydrophobic core exposed. Figure 3D shows typical micelle structures formed at 275 and 350 K, which also illustrate the difference in surfactant organization. While there are still some extended surfactants in the micelle at 350 K, the folding of polar head groups against the surface reduces exposure of the micelle core, leaving a smoother surface than observed at 275 K. Additionally, the reduction in contacts between surfactants in the outer shell of the micelle at 275 K will decrease the energetic penalty for individual surfactants to leave the micelle. To investigate the micelle destabilization kinetics, we quantify the time an individual surfactant takes to leave the micelle, as estimated from the number of contacts between the micelle and surfactants. Evolution of mean contacts during a transition from the micelle to bulk solvent is shown in Figure 4. These time series are centered around the time when the surfactant leaves the micelle. We classify contacts based on the contact type, with contacts between the head of the transitioning surfactant and heads of the micelle (head-head) shown in Figure 4A, and between the head of the transitioning surfactant and tails of the micelle (head-tail) shown in Figure 4B. For clarity, only data from 275 and 350 K is shown. The 300 K profile can be found in the Supplementary Material. Results for transitions at 500 K are not provided due to the short-lived nature of the micelle at that temperature. Prior to a surfactant leaving the micelle, head-head contacts (Figure 4A) are reduced at 275 K relative to 350 K. These contacts start to break rapidly at all temperatures just before the surfactant leaves the micelle, and are significantly fewer at 275 K than 350 K during the transition. Even before the head-head contacts begin to drop, around time 0 ps, they are less abundant at 275 K relative to 350 K. This is an effect of reduced density of the head groups in the outer shell

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Figure 4: Time series for contacts between surfactants leaving the micelle and surfactants within the micelle. Contacts between A) polar head of leaving surfactant and polar heads in micelle and B) polar head and nonpolar tails. Inset images illustrate example contacts with micelle tail in blue, leaving surfactant tail in cyan, micelle head in red, leaving surfactant head in pink, and example contacts indicated by yellow dashed lines. Values normalized based on the maximum observed at 350 K. All data smoothed using a 500 ps window. 95% confidence intervals shown as shaded areas.

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of the micelle, observed in Figure 3C. We also observe a large difference in the time series of head-tail contacts. At 275 K these contacts drop almost to their minimum value before the surfactant is considered as having left the micelle, while at 350 K many of these contacts are still present during the transition. Again, these contacts are reduced at 275 K relative to 350 K even before the transition. As the tails of surfactants are in the micelle core and head groups primarily in the outer shell, contacts with the head groups prior to the transition are increased at 350 K due to the folding of the head groups against the core at 350 K, as shown in Figure 3B. Time series for tail-tail and tail-head contacts, found in Supplmentary Figure S4, show little difference between 275 and 350 K. Tail-tail contacts would be expected to break first as the surfactant transitions, so it is no surprise that they change similarly at each temperature during a transition. Contacts between the transitioning surfactant tail and micelle heads would be expected to be found primarily as surfactant passes through the shell of the micelle to the bulk solvent at the end of a transition. Thus, it appears that at both the beginning and end of the transition there is little difference with temperature. The differences in head-head and head-tail contacts explain stability lowering as tempertature drops. More favorable head-head contacts need to be broken for the micelle to escape at 350 K. At 275 K the fast disassociation of the head-tail contacts would be expected if the surfactant moves straight out of the micelle during a transition. The lingering head-tail contacts at 350 K indicate that the contacts between the head groups folded against the micelle and the core of the micelle are retained for some time during the transition, and the surfactant does not necessarily move straight away from the micelle. This increases the time a surfactant remains with the micelle instead of transitioning out. Next, the effects of temperature on micelle solvation are investigated by comparing the density of water at varying positions within the micelle for each temperature, as shown in Figure 5A. The inner core of the micelle, stretching out to a normalized distance of approximately 0.8-1.0 units, is essentially dry, with solvation beginning around the edge of the micelle. Extending out from micelle’s core, water density increases with distance until

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Figure 5: A) Average water density at varying positions within the micelle. B) Number distribution of water contacts per surfactant with the polar domain of surfactants which are participating in the micelle core. Contacts were defined using a cutoff distance of 4 ˚ A. Number of water contacts normalized by the maximum number of contacts observed.

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it reaches approximately bulk density at the outer edge of the micelle. This density profile is consistent with published experimental and computational results. 20,21,25,70 We observe a shift in solvation at a normalized distance of 1.0-1.6 from the center of the micelle, with the highest hydration observed in this region at low temperatures and a decrease in water density accompanying an increase in temperature. Dehydration of micelles with an increase in temperature has been observed both experimentally and computationally. 20,21,25,70 Our observations here agree with these results, as we observe a steady change in hydration with temperature, with the dehydration effects appearing largest near the interface between the nonpolar tails and polar head groups. To further characterize hydration in the micelle’s shell region, we quantified the number of water contacts with the head group of each surfactant in the micelle. The distribution of these contacts at each temperature is shown in Figure 5B. At higher temperatures (350 and 500 K) we find a single peak at corresponding to a relatively dry state, while at low temperatures, an additional wet state of the head group emerges. The wet state seen at 275 K corresponds to a fully extended head group oriented away from the micelle core, while the dry state corresponds to head groups which are laying against the surface of the micelle. As shown in Figure 3B, at higher temperature (350 and 500 K) the angular distribution of the head groups with the micelle radius is increased. Thus, a decrease in solvation of the head group results in the increased folding of the head group against the micelle surface. Deeper insights into surfactant solvation as a function of temperature can be obtained from analysis of the tetrahedral order parameter and total potential energy of solvation water (Figure 6). The total potential energy of water here refers to the summation of all pairwise interaction energy involving a particular water bead. To remove any potential effect from nearby surfactants, the total potential energy and the order parameter of water in the first solvation shell around a monomer surfactant were calculated using simulations of a single surfactant in water, at 275 and 350 K. For the same reason, we calculated bulk values from simulations of pure water at 275 and 350 K. At

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Figure 6: Comparison of water energy and structure at 275K and 350K. A) Distribution of total potential energy for water beads in first solvation shell of surfactant (solid line) and bulk water (dashed line). B) Tetrahedral order parameter for water in first solvation shell around single surfactant (solid line) and bulk water (dashed line).

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Figure 7: Average free energy to extract a surfactant molecule from micelle at 275K (blue line) and 350K (red line). 350 K, we find higher total potential energy, shown in Figure 6A, for solvation water than bulk water, as we might expect since the introduction of a solute will disrupt hydrogen bonding between water molecules. At 275 K, however, the total potential energy is very similar for solvation and bulk water. The tetrahedral order parameter of water in the first solvation shell around a single surfactant, shown in Figure 6B, was compared to the order parameter for bulk water and used to measure the effect of solvating surfactant on the order of water. At 350 K solvation water is significantly less ordered than bulk water. With the decrease in temperature to 275 K, both bulk and solvation water become more ordered. However, the order difference between bulk and solvation water is less at 275 K than at 350 K, indicating that an increase in order relative to bulk for solvation water at low temperature. Accompanying this structural order increase is a decrease in the total potential energy of solvation water relative to bulk. The increase in water tetrahedral order around monomer surfactant at low temperature indicates that solvation of the surfactant is less favorable entropically at low temperature, while the increase in total potential energy for solvation water indicates that solvation is more favorable enthalpically at low temperature.

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Favored hydration at low temperature prevents surfactants from folding against the surface of the micelle in addition to reducing interactions between head groups, thus allowing water insertion into the micelle core. Thus, the destabilization of the micelle at low temperature is aided by the enthalpic gain associated with surfactant solvation, which, in turn, originates from reduced hydrophobicity. This is in agreement with thermodynamic properties of micelle formation determined experimentally, which indicate increased entropy and enthalpy for micelle formation at low temperature, leading to an overall increase in the free energy of formation for micelles at low temperature. 71,72 The observed shift in enthalpy and entropy as a consequence of weakened hydrophobicity is also observed in the cold denaturation of proteins. 67,68,73 While it is not trivial to estimate surfactant-water pairwise interaction energy directly due to the use of three-body interaction potential, the surfactant conformation and hydration indirectly provide information about surfactant solvation energy. Further surfactant pulling simulations were performed to calculate the free energy to extract a single surfactant molecule from the equilibrated micelle at 275 K and 350 K, as shown in Figure 7. The free energy changes for extracting a single surfactant molecule at 350 K is 3 kcal/mol higher than at 275 K. This indicates a more stable micelle formation at 350 K and is in agreement with previous findings that micelle destablization is favored at lower temperature. Taken together, our results suggest stronger micelle-water interaction at low temperature due to weakened hydrophobicity, resulting into a loose micelle comprised of more extended surfactants. As a result, less work needs to be done to extract a surfactant from the micelle at low temperature.

Conclusions In conclusion, we have developed a coarse-grained model of nonionic surfactant in water and employed this model to characterize the destabilization of pre-formed micelles at extreme temperatures. Our model is capable of simulating both micelle formation and destabiliza-

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tion. Our simulations indicate the same temperature of maximum stability for micelles during formation and breaking. The generated micelles have the expected dry hydrophobic core surrounded by a solvated polar shell. At high temperatures we observe a rapid disordering and destabilization of the micelle. At low temperatures we note changes in both the overall structure of the micelle as well as the individual surfactants constituting the micelle. At 350 K the polar head groups of surfactant fold against the surface of the micelle, thus protecting the hydrophobic core from water. In contrast, at low temperature surfactants within the micelle remain extended due to favored hydrophobic hydration, resulting in enhanced wetting of the micelle shell. While leaving the micelle and moving to bulk, surfactants at 350 K have lingering head-head and head-tail contacts, which likely contribute to the retention of surfactants within the micelle. By contrast, surfactants that transition out from micelle to solvent at 275 K surfactants undergo a sharper transition, during which they rapidly lose head-head and head-tail contacts with the micelle. Micelle destabilization at low temperature is driven by reduced hydrophobicity, which leads to favorable interactions betweeen surfactants and the more ordered solvation water. Taken together, our coarse-grained simulation reveal how structural and energetic changes of the surfactant and surrounding solvation water destabilize a non-ionic micelle at low temperatures, which, in turn, is driven by reduced hydrophobicity at those conditions. Our approach thus can be useful for providing insight into the molecular level changes during hydrophobicity-driven destabilization of molecular self-assembly, which is important in a wide range of fields, including biology, polymer science, and nanotechnology. Similar to non-ionic surfactant micellization, protein folding, aggregation, and ionic surfactant micelle formation are also driven by the same physiochemical forces, i.e. hydrophobic interactions, intra and inter-polymer and polymer-water dispersion interactions. Head-group repulsion additionally plays a major role in determining the CMC in the case of ionic surfactants. Nevertheless, the observed trend in the temperature-dependent stability has been reported in those soft matter systems as well, including ionic micelles, i.e.CMC decreased to a certain minimum and then increased with the temperature, displaying a U-shaped be-

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havior. 10,22,23,67,68,73–75 In the case of ionic surfactants, the temperature corresponding to the lowest CMC shifts due to presence of counter-ions. Few exceptions to this general trend have been reported, e.g. cold denaturation of yeast frataxin in presence of alcohol, which is likely arising from the co-solute interference. 76,77 In its current form, the model presented here is easily extensible to any surfactants of the form Cn Em . In principle the model could be extended to any nonionic surfactant, though surfactants of another form may require additional parametrization. Additionally, the lack of representation for the directionality of hydrogen bonds means that the model is not capable of capturing a dipole moment. Future work will involve extension to charged residues and simulations of more complex mesophases and environments, such as mixed solvents and crowding.

Supporting Information Available Details on parametrization of the model, time series of micelle formation, and additional time series for contacts involving surfactants leaving the micelle.

Acknowledgements Authors acknowledge the donors of The American Chemical Society Petroleum Research Fund for partial support of this research (S.M., G.S.C.) and the IBM Blue Gene Science Program (P.D.).

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References (1) Drummond, C. J.; Fong, C. Curr. Opin. Colloid In. 1999, 4, 449 – 456. (2) Patist, A.; Kanicky, J. R.; Shukla, P. K.; Shah, D. O. J. Colloid Interf. Sci. 2002, 245, 1 – 15. (3) Schramm, L. L.; Stasiuk, E. N.; Marangoni, D. G. Annu. Rep. Prog. Chem., Sect. C: Phys. Chem. 2003, 99, 3–48. (4) Singh, A.; Hamme, J. D. V.; Ward, O. P. Biotechnol. Adv. 2007, 25, 99 – 121. (5) Mitchell, D. J.; Tiddy, G. J. T.; Waring, L.; Bostock, T.; McDonald, M. P. J. Chem. Soc., Faraday Trans. 1 1983, 79, 975–1000. (6) Strey, R.; Schomacker, R.; Roux, D.; Nallet, F.; Olsson, U. J. Chem. Soc., Faraday Trans. 1990, 86, 2253–2261. (7) Wang, J.; Mao, W.; Lock, L. L.; Tang, J.; Sui, M.; Sun, W.; Cui, H.; Xu, D.; Shen, Y. ACS Nano 2015, 9, 7195–7206, PMID: 26149286. (8) Puvvada, S.; Blankschtein, D. J. Chem. Phys. 1990, 92, 3710–3724. (9) Lee, D. J. Colloid Polym. Sci. 1995, 273, 539–543. (10) Paula, S.; Sues, W.; Tuchtenhagen, J.; Blume, A. J. Phys. Chem-US. 1995, 99, 11742– 11751. (11) Söderman, O.; Walderhaug, H.; Henriksson, U.; Stilbs, P. J. Phys. Chem-US. 1985, 89, 3693–3701. (12) Wennerstroem, H.; Lindman, B.; Soederman, O.; Drakenberg, T.; Rosenholm, J. B. J. Am. Chem. Soc. 1979, 101, 6860–6864. (13) Söderman, O.; Stilbs, P.; Price, W. S. Concept. Magn. Reso. A 2004, 23A, 121–135. 27


Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(14) Nilsson, P. G.; Lindman, B. J. Phys. Chem-US. 1984, 88, 5391–5397. (15) Olofsson, G. J. Phys. Chem-US. 1985, 89, 1473–1477. (16) Lesemann, M.; Martin, A.; Belkoura, L.; Woermann, D.; Hoinkis, E. Berich. Bunsen. Gesell. 1997, 101, 228–235. (17) Brunner-Popela, J.; Mittelbach, R.; Strey, R.; Schubert, K.-V.; Kaler, E. W.; Glatter, O. J. Chem. Phys. 1999, 110, 10623–10632. (18) Bendedouch, D.; Chen, S. H.; Koehler, W. C. J. Phys. Chem-US. 1983, 87, 153–159. (19) Tanford, C.; Nozaki, Y.; Rohde, M. F. J. Phys. Chem-US. 1977, 81, 1555–1560. (20) Romsted, L. S.; Yao, J. Langmuir 1996, 12, 2425–2432. (21) Romsted, L. S.; Yao, J. Langmuir 1999, 15, 326–336. (22) Chen, L.-J.; Lin, S.-Y.; Huang, C.-C.; Chen, E.-M. Colloid. Surface. A 1998, 135, 175 – 181. (23) Aoudia, M.; Zana, R. J. Colloid Interf. Sci. 1998, 206, 158 – 167. (24) Mehta, S.; Bhasin, K.; Chauhan, R.; Dham, S. Colloid. Surface. A 2005, 255, 153 – 157. (25) Jonströmer, M.; Jönsson, B.; Lindman, B. J. Phys. Chem-US. 1991, 95, 3293–3300. (26) Long, J. A.; Rankin, B. M.; Ben-Amotz, D. J. Am. Chem. Soc. 2015, 137, 10809–10815, PMID: 26222042. (27) Marrink, S. J.; Tieleman, D. P.; Mark, A. E. J. Phys. Chem. B. 2000, 104, 12165– 12173. (28) Bond, P. J.; Cuthbertson, J. M.; Deol, S. S.; Sansom, M. S. P. J. Am. Chem. Soc. 2004, 126, 15948–15949, PMID: 15584713. 28


Page 28 of 33

Page 29 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Langmuir

(29) Shinoda, W.; DeVane, R.; Klein, M. L. Mol. Simulat. 2007, 33, 27–36. (30) Shinoda, W.; DeVane, R.; Klein, M. L. Soft Matter 2008, 4, 2454–2462. (31) Garde, S.; Yang, L.; Dordick, J. S.; Paulaitis, M. E. Mol. Phys. 2002, 100, 2299–2306. (32) Lsal, M.; Hall, C. K.; Gubbins, K. E.; Panagiotopoulos, A. Z. J. Chem. Phys. 2002, 116, 1171–1184. (33) Woodhead, J. L.; Hall, C. K. Langmuir 2010, 26, 15135–15141, PMID: 20825214. (34) Velinova, M.; Sengupta, D.; Tadjer, A. V.; Marrink, S.-J. Langmuir 2011, 27, 14071– 14077, PMID: 21981373. (35) Mondal, J.; Mahanthappa, M.; Yethiraj, A. J. Phys. Chem. B. 2013, 117, 4254–4262, PMID: 22967267. (36) Dhakal, S.; Sureshkumar, R. J. Chem. Phys. 2015, 143, 024905. (37) Johnston, M. A.; Swope, W. C.; Jordan, K. E.; Warren, P. B.; Noro, M. G.; Bray, D. J.; Anderson, R. L. J. Phys. Chem. B. 2016, 120, 6337–6351, PMID: 27096611. (38) Santos, A. P.; Panagiotopoulos, A. Z. J. Chem. Phys. 2016, 144, 044709. (39) Deshmukh, S. A.; Solomon, L. A.; Kamath, G.; Fry, H. C.; Sankaranarayanan, S. K. R. S. Nature Communications 2016, 7, 12367. (40) Faramarzi, S.; Bonnett, B.; Scaggs, C. A.; Hoffmaster, A.; Grodi, D.; Harvey, E.; Mertz, B. Langmuir 2017, 33, 9934–9943, PMID: 28836794. (41) Yuan, F.; Wang, S.; Larson, R. G. Langmuir 2015, 31, 1336–1343, PMID: 25560633. (42) Lazaridis, T.; Mallik, B.; Chen, Y. J. Phys. Chem. B. 2005, 109, 15098–15106, PMID: 16852911.

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(43) Jusufi, A.; Hynninen, A.-P.; Panagiotopoulos, A. Z. J. Phys. Chem. B. 2008, 112, 13783–13792, PMID: 18844395. (44) Yesylevskyy, S. O.; Schäfer, L. V.; Sengupta, D.; Marrink, S. J. PLoS. Comput. Biol. 2010, 6, e1000810. (45) Schrdle, S.; Hefter, G.; Kunz, W.; ; Buchner, R. Langmuir 2006, 22, 924–932, PMID: 16430250. (46) Molinero, V.; Moore, E. B. J. Phys. Chem. B. 2009, 113, 4008–4016. (47) Stillinger, F. H.; Weber, T. A. Phys. Rev. B 1985, 31, 5262–5271. (48) Das, P.; Matysiak, S. J. Phys. Chem. B. 2012, 116, 5342–5348. (49) Matysiak, S.; Das, P. Phys. Rev. Lett. 2013, 111, 058103. (50) Custer, G. S.; Das, P.; Matysiak, S. J. Phys. Chem. B. 2017, 121, 2731–2738, PMID: 28282142. (51) Lindorff-Larsen, K.; Piana, S.; Palmo, K.; Maragakis, P.; Klepeis, J. L.; Dror, R. O.; Shaw, D. E. Proteins 2010, 78, 1950–1958. (52) Berendsen, H. J. C.; Grigera, J. R.; Straatsma, T. P. J. Phys. Chem-US. 1987, 91, 6269–6271. (53) Spoel, D. V. D.; Lindahl, E.; Hess, B.; Groenhof, G.; Mark, A. E.; Berendsen, H. J. C. J Comput Chem 2005, 26, 1701–1718. (54) Hess, B.; Kutzner, C.; van der Spoel, D.; Lindahl, E. J. Chem. Theory Comput. 2008, 4, 435–447. (55) Berendsen, H.; van der Spoel, D.; van Drunen, R. Comput. Phys. Commun. 1995, 91, 43–56.

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Page 30 of 33

Page 31 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Langmuir

(56) Lindahl, E.; Hess, B.; van der Spoel, D. Molecular Modeling Annual 2001, 7, 306–317. (57) Plimpton, S. Journal of Computational Physics 1995, 117, 1 – 19. (58) Shick, M. Nonionic Surfactants; Surfactant Science Series; Physical Chemistry: New York, 1987; Vol. 23. (59) Verlet, L. Phys. Rev. 1967, 159, 98–103. (60) Nosé, S. J. Chem. Phys. 1984, 81, 511–519. (61) Hoover, W. G. Phys. Rev. A 1985, 31, 1695–1697. (62) Al-Anber, Z. A.; Bonet i Avalos, J.; Floriano, M. A.; Mackie, A. D. J. Chem. Phys. 2003, 118, 3816–3826. (63) Glatter, O.; Fritz, G.; Lindner, H.; Brunner-Popela, J.; Mittelbach, R.; Strey, R.; Egelhaaf, S. U. Langmuir 2000, 16, 8692–8701. (64) Humphrey, W.; Dalke, A.; Schulten, K. J. Mol. Graphics 1996, 14, 33–38. (65) Chau, P.-L.; Hardwick, A. Mol. Phys. 1998, 93, 511–518. (66) Errington, J. R.; Debenedetti, P. G. Nature 2001, 409, 318. (67) Privalov, P. L. Crit. Rev. Biochem. Mol. 1990, 25, 281–306. (68) Dias, C. L.; Ala-Nissila, T.; Wong-ekkabut, J.; Vattulainen, I.; Grant, M.; Karttunen, M. Cryobiology 2010, 60, 91–99. (69) Chatterjee, P.; Sengupta, N. Mol. BioSyst. 2016, 12, 1139–1150. (70) Sterpone, F.; Pierleoni, C.; Briganti, G.; Marchi, M. Langmuir 2004, 20, 4311–4314, PMID: 15969130. (71) Chen, L.-J.; Lin, S.-Y.; Huang, C.-C. J. Phys. Chem. B. 1998, 102, 4350–4356. 31


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(72) Sugihara, G.; Hisatomi, M. J. Colloid Interf. Sci. 1999, 219, 31 – 36. (73) Privalov, P. L.; YuV, G.; SYu, V.; Kutyshenko, V. P. J Mol Biol 1986, 190, 487–498. (74) Kumar, S.; Parikh, K. Journal of Applied Solution Chemistry and Modeling 2012, 1, 65–73. (75) Tennouga, L.; Mansri, A.; Medjahed, K.; Chetouani, A.; Warad, I. Journal of Materials and Enviromental Science 2015, 6, 2711–2716. (76) Martin, S. R.; Esposito, V.; De Los Rios, P.; Pastore, A.; Temussi, P. A. Journal of the American Chemical Society 2008, 130, 9963–9970. (77) Chatterjee, P.; Bagchi, S.; Sengupta, N. The Journal of Chemical Physics 2014, 141, 11B615 1.

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How Hydrophobic Hydration Destabilizes Surfactant Micelles at Low

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