The hydrophobic effect, and fluctuations: The long and the short of it

A Janus membrane with electro-induced multi-affinity interfaces for high-efficiency water purification

Drinking water with micropollutants is a notable environmental concern worldwide. Membrane separation is one of the few methods capable of removing micropollutants from water. However, existing membranes face challenges in the simultaneous and efficient treatment of small-molecular and ionic contaminants because of their limited permselectivity. Here, we propose a high-efficiency water purification method using a low-pressure Janus membrane with electro-induced multi-affinity. By virtue of hydrophobic and electrostatic interactions between the functional interfaces and contaminants, the Janus membrane achieves simultaneous separation of diverse types of organics and heavy metals from water via single-pass filtration, with an approximately 100% removal efficiency, high water flux (>680 liters m-2 hour-1), and 98% lower energy consumption compared with commercial nanofiltration membranes. The electro-induced switching of interfacial affinity enables 100% regeneration of membrane performance; thus, our work paves a sustainable avenue for drinking water purification by regulating the interfacial affinity of membranes.

Relationships between Molecular Structural Order Parameters and Equilibrium Water Dynamics in Aqueous Mixtures

Water's unique thermophysical properties and how it mediates aqueous interactions between solutes have long been interpreted in terms of its collective molecular structure. The seminal work of Errington and Debenedetti [Nature 2001, 409, 318-321] revealed a striking hierarchy of relationships among the thermodynamic, dynamic, and structural properties of water, motivating many efforts to understand (1) what measures of water structure are connected to different experimentally accessible macroscopic responses and (2) how many such structural metrics are adequate to describe the collective structural behavior of water. Diffusivity constitutes a particularly interesting experimentally accessible equilibrium property to investigate such relationships because advanced NMR techniques allow the measurement of bulk and local water dynamics in nanometer proximity to molecules and interfaces, suggesting the enticing possibility of measuring local diffusivities that report on water structure. Here, we apply statistical learning methods to discover persistent structure-dynamic correlations across a variety of simulated aqueous mixtures, from alcohol-water to polypeptoid-water systems. We investigate a variety of molecular water structure metrics and find that an unsupervised statistical learning algorithm (namely, sequential feature selection) identifies only two or three independent structural metrics that are sufficient to predict water self-diffusivity accurately. Surprisingly, the translational diffusivity of water across all mixed systems studied here is strongly correlated with a measure of tetrahedral order given by water's triplet angle distribution. We also identify a separate small number of structural metrics that well predict an important thermodynamic property, the excess chemical potential of an idealized methane-sized hydrophobe in water. Ultimately, we offer a Bayesian method of inferring water structure by using only structure-dynamics linear regression models with experimental Overhauser dynamic nuclear polarization (ODNP) measurements of water self-diffusivity. This study thus quantifies the relationships among several distinct structural order parameters in water and, through statistical learning, reveals the potential to leverage molecular structure to predict fundamental thermophysical properties. In turn, these findings suggest a framework for solving the inverse problem of inferring water's molecular structure using experimental measurements such as ODNP studies that probe local water properties.

A critical review on the environmental application of lipopeptide micelles

The importance of lipopeptide micelles in environmental applications has been highlighted. These vessels exhibit various sizes, shapes, and surface properties under different environmental conditions. An in-depth understanding of the tunable assembling behavior of biosurfactant micelles is of great importance for their applications. However, a systematic review of such behaviors with assorted micro/nano micellar structures under given environmental conditions, particularly under low temperature and high salinity, remains untapped. Such impacts on their environmental applications have yet to be summarized. This review tried to fill the knowledge gaps by providing a comprehensive summary of the recent knowledge advancement in genetically regulated lipopeptides production, micelles associated decontamination mechanisms in low temperature and high salinity environments, and up-to-date environmental applications. This work is expected to deliver valuable insights to guide lipopeptide design and discovery. The mechanisms concluded in this study could inspire the forthcoming research efforts in the advanced environmental application of lipopeptide micelles.

Core-softened water-alcohol mixtures: the solute-size effects

Water is the most anomalous material on Earth, with a long list of thermodynamic, dynamic and structural behaviors that deviate from what is expected. Recent studies have indicated that these anomalies may be related to a competition between two liquids, which means that water has a potential liquid-liquid phase transition (LLPT) that ends at a liquid-liquid critical point (LLCP). In a recent study [J. Mol. Liq., 2020, 320, 114420], using molecular dynamics simulations and a core-softened potential approach, we have shown that adding a simple solute such as methanol can "kill" the density-anomalous behavior as the LLCP is suppressed by spontaneous crystallization in a hexagonal close packing (HCP) crystal near the LLPT. Now, we extend this work to realize how longer-chain alcohols will affect the complex behavior of water-alcohol mixtures in the supercooled regime. Besides core-softened (CS) methanol, ethanol and 1-propanol were added to a system of identical particles that interact through the continuous shouldered well (CSW) potential. We observed that the density anomaly gradually decreases its extension in phase diagrams until it disappears with the growth of the non-polar chain and the alcohol concentration, different from the liquid-liquid phase transition (and the LLCP), which remained present in all analyzed mixtures, according to Nature, 2001, 409, 692. For our model, the longer non-polar chains and higher concentrations gradually impact the competition between the scales in the CS potential, leading to a gradual disappearing of the anomalies until the TMD total disappearance is observed when the first coordination shell structure is also affected: short-range ordering is favored, leading to less competition between short- and long-range ordering and, consequently, to the extinction of anomalies. Also, the non-polar chain size and concentration have an effect on the solid phases, favoring the hexagonal close packed (HCP) solid and the amorphous solid phase over the body-centered cubic (BCC) crystal. These findings help to elucidate the behavior of water solutions in the supercooled regime and indicate that the LLCP can be observed in systems without density-anomalous behavior.

Characterizing the Interplay between Polymer Solvation and Conformation

Conformational transitions of flexible molecules, especially those driven by hydrophobic effects, tend to be hindered by desolvation barriers. For such transitions, it is thus important to characterize and understand the interplay between solvation and conformation. Using specialized molecular simulations, here we perform such a characterization for a hydrophobic polymer solvated in water. We find that an external potential, which unfavorably perturbs the polymer hydration waters, can trigger a coil-to-globule or collapse transition, and that the relative stabilities of the collapsed and extended states can be quantified by the strength of the requisite potential. Our results also provide mechanistic insights into the collapse transition, highlighting that the bottleneck to polymer collapse is the formation of a sufficiently large cluster, and the collective dewetting of such a cluster. We also study the collapse of the hydrophobic polymer in octane, a nonpolar solvent, and interestingly, we find that the mechanistic details of the transition are qualitatively similar to that in water.

Solvation Thermodynamics from the Perspective of Endpoints DFT

Solvation thermodynamics is concerned with the evaluation and physical interpretation of solvation free energies. Endpoints DFT provides a framework for computing solvation free energies by combining molecular simulations with a version of the classical density-functional theory of solutions which focuses on ω, the indirect (solvent-mediated) part of the solute-solvent potential of mean force (indirect PMF). The simulations are performed at the endpoints of a hypothetical charging process which transforms the solvent density from the pure liquid state to that of the solution state. The endpoints DFT expression for solvation free energy can be shown to be equivalent to the standard expression for which the key quantity is the direct correlation function, but it has the advantage that the indirect term ω is more focused on the change in solvent-solvent correlations with respect to the pure liquid as the solute is inserted into the solution. In this Perspective, we review recent developments of endpoints DFT, highlighting a series of papers we have written together beginning in 2017. We emphasize the importance of dimensionality reduction as the key to the evaluation of endpoints DFT expressions and present a recently developed, spatially resolved version of the theory. The role of interfacial water at certain positions which stabilize or destabilize a solute in solution can be analyzed with the spatially resolved version, and it is of considerable interest to investigate how changes in solvation affect protein-ligand binding and conformational landscapes from an endpoints DFT perspective. Endpoints DFT can also be employed in materials science; an example involving the rational design strategy for polymer membrane separation is described. The endpoints DFT method is a scheme to evaluate the solvation free energy by introducing approximations to integrate the classical density functional over a charging parameter. We have further proposed a new functional which captures the correct dependence of the indirect PMF ω at both endpoints of the charging process, and we review how it might be employed in future work.

100th Anniversary of Macromolecular Science Viewpoint: The Role of Hydrophobicity in Polymer Phenomena

The seemingly simple notion of the hydrophobic effect can be viewed from multiple angles involving theory, simulation, and experiments. This viewpoint examines five attributes of predictive models to enhance synthetic efforts as well as experimental methods to quantify hydrophobicity. In addition, we compare existing predictive models against experimental data for polymer surface tension, lower critical solution temperature, solution self-assembly morphology, and degradation behavior. Key conclusions suggest that both the Hildebrand solubility parameters (HSPs) and surface area-normalized Log P (Log P SA-1) values provide unique and complementary insights into polymer phenomena. In particular, HSPs appear to better describe bulk polymer phenomena for thermoplastics such as surface tension, while Log P SA-1 values are well-suited for describing and predicting the behavior of polymers in solution.

Cavity Particle in Aqueous Solution with a Hydrophobic Solute: Structure, Energetics, and Functionals

Endpoints density functional theory (DFT) provides a framework for calculating the excess chemical potential of a solute in solution using solvent distribution functions obtained from both physical endpoints of a hypothetical charging process which transforms the solvent density from that of the pure liquid to the solution state. In this work, the endpoints DFT equations are formulated in terms of the indirect (solvent-mediated) contribution ω(x) to the solute-solvent potential of mean force, and their connections are established with the conventional DFT expressions which are based on the use of direct correlation functions. ω actually corresponds to the free-energy cost to move a cavity particle (a tagged solvent molecule which interacts with the other solvent molecules but not the solute) from the bulk to the configuration x of a solvent molecule relative to the solute and is a suitable variable to describe the solvent effects on the solute-solvent interactions. HNC and PY type approximations are then used to integrate the DFT charging integral involved in the exact expression for the excess chemical potential. With these approximations, molecular simulations are to be performed at the two endpoints of solute insertion: pure solvent without the solute and the solution system with the fully coupled solute-solvent interaction. An endpoints method thus utilizes the ensembles of intermolecular configurations of physical interest, which are often readily accessible with MD simulations given the present computational power. To illustrate properties of the formulation, we perform simulations of model systems consisting of a cavity particle in an aqueous solution containing a spherical hydrophobic solute of three different sizes from which ω(x) and the solute chemical potential can be calculated using endpoints DFT expressions. These are compared with corresponding results obtained using the approximations needed in order to evaluate the endpoints DFT charging integral when cavity particle simulation data is not available. We analyze a new approximation (two-points quadratic HNC) to the DFT charging integral which captures the correct behavior of the cavity distributions at both endpoints of the solute insertion. The behavior of the cavity particle in simple and complex liquids plays an important role in various theoretical treatments of the solute chemical potential. For pure Lennard-Jones fluids, the free energy to bring a cavity particle from the bulk to the center of a fluid particle is negative. However, for solutes of varying size, this is not generally true for Lennard-Jones fluids or the systems studied in this work. We carry out energetic and structural analyses of the cavity particle in aqueous solution with hydrophobic solutes of varying size and discuss the results in the context of the hydrophobic effect.

Characterizing Solvent Density Fluctuations in Dynamical Observation Volumes

Hydrophobic effects drive diverse aqueous assemblies, such as micelle formation or protein folding, wherein the solvent plays an important role. Consequently, characterizing the free energetics of solvent density fluctuations can lead to important insights into these processes. Although techniques such as the indirect umbrella sampling (INDUS) method can be used to characterize solvent fluctuations in static observation volumes of various sizes and shapes, characterizing how the solvent mediates inherently dynamic processes, such as self-assembly or conformational change, remains a challenge. In this work, we generalize the INDUS method to facilitate the enhanced sampling of solvent fluctuations in dynamical observation volumes, whose positions and shapes can evolve. We illustrate the usefulness of this generalization by characterizing water density fluctuations in dynamical volumes pertaining to the hydration of flexible solutes, the assembly of small hydrophobes, and conformational transitions in a model peptide. We also use the method to probe the dynamics of hard spheres.

Hydrophobic Surface Enhances Electrostatic Interaction in Water

A high dielectric constant is one of the peculiar properties of liquid water, indicating that the electrostatic interaction between charged substances is largely reduced in water. We show by molecular dynamics simulation that the dielectric constant of water is decreased near the hydrophobic surface. We further show that the decrease in the dielectric constant is due to both the decreased water density and the reduced water dipole correlation in the direction perpendicular to the surface. We finally demonstrate that electrostatic interaction in water is actually strengthened near the hydrophobic surface.

How Water's Properties Are Encoded in Its Molecular Structure and Energies

How are water's material properties encoded within the structure of the water molecule? This is pertinent to understanding Earth's living systems, its materials, its geochemistry and geophysics, and a broad spectrum of its industrial chemistry. Water has distinctive liquid and solid properties: It is highly cohesive. It has volumetric anomalies-water's solid (ice) floats on its liquid; pressure can melt the solid rather than freezing the liquid; heating can shrink the liquid. It has more solid phases than other materials. Its supercooled liquid has divergent thermodynamic response functions. Its glassy state is neither fragile nor strong. Its component ions-hydroxide and protons-diffuse much faster than other ions. Aqueous solvation of ions or oils entails large entropies and heat capacities. We review how these properties are encoded within water's molecular structure and energies, as understood from theories, simulations, and experiments. Like simpler liquids, water molecules are nearly spherical and interact with each other through van der Waals forces. Unlike simpler liquids, water's orientation-dependent hydrogen bonding leads to open tetrahedral cage-like structuring that contributes to its remarkable volumetric and thermal properties.

The Dynamics of Water in Porous Two-Dimensional Crystals

Porous two-dimensional crystals offer many promises for water desalination applications. For computer simulation to play a predictive role in this area, however, one needs to have reliable methods for simulating an atomistic system with hydrodynamic currents and interpretative tools to relate microscopic interactions to emergent macroscopic dynamical quantities, such as friction, slip length, and permeability. In this article, we use Gaussian dynamics, a nonequilibrium molecular dynamics method that provides microscopic insights into the interactions that control the flows of both simple liquids and liquid water through atomically small channels. In simulations of aqueous transport, we mimic the effect of changing the membrane chemical composition by adjusting the attractive strength of the van der Waals interactions between the membrane atoms and water. We find that the wetting contact angle, a common measure of a membrane's hydrophobicity, does not predict the permeability of a membrane. Instead, the hydrophobic effect is subtle, with both static and dynamic effects that can both help and hinder water transport through these materials. The competition between the static and dynamical hydrophobicity balances an atomic membrane's tendency to wet against hydrodynamic friction, and determines an optimal contact angle for water passage through nonpolar membranes. To a reasonable approximation, the optimal contact angle depends only on the aspect ratio of the pore. We also find that water molecules pass through the most hydrophobic membranes in a punctuated series of bursts that are separated by long pauses. A continuous-time Markov model of these data provides evidence of a molecular analogue to the clogging transition, a phenomenon observed in driven granular flows.