Is Water at the Graphite Interface Vapor-like or Ice-like?

Comprehensive Molecular Dynamics Study of Oxygen Diffusion in Carbon Mesopores: Insights for Designing Fuel-Cell Catalyst Supports

Mesoporous carbon is often used as a support for platinum catalysts in polymer electrolyte fuel-cell catalyst layers. Mesopores in the carbon support improve the performance of fuel cells by inhibiting the adsorption of ionomer onto the catalyst particles. However, the mesopores may impair mass transport. Hence, understanding molecular behaviors in the pores is essential to optimizing the mesopore structures. Specifically, it is crucial to understand the oxygen transport in the high-current region. In this study, the diffusion coefficients of oxygen molecules in carbon mesopores were calculated for various pore lengths, pore diameters, filling rates, and water contents in the ionomer via molecular dynamics simulations. The results show that oxygen diffusion slows by 2 orders of magnitude because of pore occlusion, and it slows down by an additional 1 or 2 orders of magnitude if ionomers are present in the pores. The occlusion can be theoretically predicted by considering the surface free energy. This theory provides some insight into mesoporous carbon designs; for instance, the theory suggests that narrow pores should be shortened to prevent occlusion. Slow diffusion in the presence of ionomers was attributed to the localization of oxygen at the dense ionomer-carbon interface. Thus, to improve oxygen transport properties, carbon surfaces and ionomer structures may be designed in such a manner as to prevent densification at the interface.

Minimum in the pressure dependence of the interfacial free energy between ice Ih and water

Despite the importance of ice nucleation, this process has been barely explored at negative pressures. Here, we study homogeneous ice nucleation in stretched water by means of molecular dynamics seeding simulations using the TIP4P/Ice model. We observe that the critical nucleus size, interfacial free energy, free energy barrier, and nucleation rate barely change between isobars from -2600 to 500 bars when they are represented as a function of supercooling. This allows us to identify universal empirical expressions for homogeneous ice nucleation in the pressure range from -2600 to 500 bars. We show that this universal behavior arises from the pressure dependence of the interfacial free energy, which we compute by means of the mold integration technique, finding a shallow minimum around -2000 bars. Likewise, we show that the change in the interfacial free energy with pressure is proportional to the excess entropy and the slope of the melting line, exhibiting in the latter a reentrant behavior also at the same negative pressure. Finally, we estimate the excess internal energy and the excess entropy of the ice Ih-water interface.

Homogeneous ice nucleation in an ab initio machine-learning model of water

Molecular simulations have provided valuable insight into the microscopic mechanisms underlying homogeneous ice nucleation. While empirical models have been used extensively to study this phenomenon, simulations based on first-principles calculations have so far proven prohibitively expensive. Here, we circumvent this difficulty by using an efficient machine-learning model trained on density-functional theory energies and forces. We compute nucleation rates at atmospheric pressure, over a broad range of supercoolings, using the seeding technique and systems of up to hundreds of thousands of atoms simulated with ab initio accuracy. The key quantity provided by the seeding technique is the size of the critical cluster (i.e., a size such that the cluster has equal probabilities of growing or melting at the given supersaturation), which is used together with the equations of classical nucleation theory to compute nucleation rates. We find that nucleation rates for our model at moderate supercoolings are in good agreement with experimental measurements within the error of our calculation. We also study the impact of properties such as the thermodynamic driving force, interfacial free energy, and stacking disorder on the calculated rates.

Dielectric Profile and Electromelting of a Monolayer of Water Confined in Graphene Slit Pore

A monolayer of water confined between two parallel graphene sheets exists in many different phases and exhibits fascinating dielectric properties that have been studied in experiments. In this work, we use molecular dynamics simulations to study how the dielectric properties of a confined monolayer of water is affected by its structure. We consider six of the popular nonpolarizable water models-SPC/E, SPC/Fw, TIP3P, TIP3P_M (modified), TIP4P-2005, and TIP4P-2005f-and find that the in-plane structure of the water molecules at ambient temperature and pressure is strongly dependent on the water model: all the 3-point water models considered here show square ice formation, whereas no such structural ordering is observed for the 4-point water models. This allows us to investigate the role of the in-plane structure of the water monolayer on its dielectric profile. Our simulations show an anomalous perpendicular dielectric constant compared to the bulk, and the models that do not exhibit ice formation show very different dielectric response along the channel width compared to models that exhibit square ice formation. We also demonstrate the occurrence of electromelting of the in-plane ordered water under the application of a perpendicular electric field and find that the critical field for electromelting strongly depends on the water model. Together, we have shown the dependence of confined water properties on the different water structures that it may take when sandwiched between bilayer graphene. These remarkable properties of confined water can be exploited in various nanofluidic devices, artificial ion channels, and molecular sieving.

Is Ice Nucleation by Organic Crystals Nonclassical? An Assessment of the Monolayer Hypothesis of Ice Nucleation

Potent ice nucleating organic crystals display an increase in nucleation efficiency with pressure and memory effect after pressurization that set them apart from inorganic nucleants. These characteristics were proposed to arise from an ordered water monolayer at the organic-water interface. It was interpreted that ordering of the monolayer is the limiting step for ice nucleation on organic crystals, rendering their mechanism of nucleation nonclassical. Despite the importance of organics in atmospheric ice nucleation, that explanation has never been investigated. Here we elucidate the structure of interfacial water and its role in ice nucleation at ambient pressure on phloroglucinol dihydrate, the paradigmatic example of outstanding ice nucleating organic crystal, using molecular simulations. The simulations confirm the existence of an interfacial monolayer that orders on cooling and becomes fully ordered upon ice formation. The monolayer does not resemble any ice face but seamlessly connects the distinct hydrogen-bonding orders of ice and the organic surface. Although large ordered patches develop in the monolayer before ice nucleates, we find that the critical step is the formation of the ice crystallite, indicating that the mechanism is classical. We predict that the fully ordered, crystalline monolayer nucleates ice above -2 °C and could be responsible for the exceptional ice nucleation by the organic crystal at high pressures. The lifetime of the fully ordered monolayer around 0 °C, however, is too short to account for the memory effect reported in the experiments. The latter could arise from an increase in the melting temperature of ice confined by strongly ice-binding surfaces.

From a bulk to nanoconfined water chain: bridge water at the pore of the (6,6) carbon nanotube

Hydrophobic porous materials with nano-pores are critical in many processes such as water desalination and biological membrane transportation. Herein, we performed molecular dynamics (MD) simulations on a prototypical hydrophobic nanochannel consisting of a (6,6) carbon nanotube (CNT) of 4.12 Å in radius and 13.72 Å in length immersed in water. The simulation shows that there are two major filling numbers of water N = 5 and N = 6, with the former being the most stable one. The confined waters form a single-file water chain with two hydrogen bonds per water. An extending water chain is formed for N = 5, with a bridge water near the pore of the CNT linking the water confined inside the CNT and hydration layer around the pore of the CNT. The bridge water can be considered as intermediate water characterized by three hydrogen bonds that distinguish from the confined water and bulk water. On the other hand, the hydration layer is depleted from the pore when N = 6. The analyses of the correlation of the bond order for the adjacent hydrogen bond pair of the hydration layer around the pore of the CNT does not show apparent difference from that of bulk water, though the former is slightly ordered. van Hove analysis of the bridge water shows that it tends to move inside the CNT when N < 5, in order to maintain the chemical equilibrium between the confined water and bulk water. This study highlights the unique structure of water around the hydrophobic pore of a sub-nanometer nanochannel.

Selective nucleation of ice crystals depending on the inclination angle of nanostructures

Heterogeneous nucleation is decided by many factors, and surface morphology is one of the most important elements. This paper reports the selective ice nucleation and growth process on a series of nanorods with different inclinations, which were rarely mentioned in previous research studies. It is found that the nanorods with special inclinations can cause the selective nucleation of ice crystals because of the spatial geometry matching. On this basis, we can regulate the ice crystal types (mainly including cubic ice and hexagonal ice) accordingly and even improve the freezing efficiency via controlling the inclinations of surface nanorods. In particular, cubic ice occupies the dominant role in the ice crystal on the surface of 45°-inclination nanorods, yet 90°-inclination nanorods are more beneficial for the formation of hexagonal ice. The shape of the nanorods not only controls the type of ice crystal, but also changes the freezing efficiency because different ice crystals have an unequal nucleation energy barrier. There are no apparent differences in the freezing efficiency on nanostructures with 45°, 75° and 90° inclination nanorods, and 60°-inclination nanorods are more favorable for ice nucleation. Our studies can promote the understanding on the selective nucleation of ice crystals and provide a theoretical basis for achieving the regulation of freezing efficiency.

Machine learning coarse grained models for water

An accurate and computationally efficient molecular level description of mesoscopic behavior of ice-water systems remains a major challenge. Here, we introduce a set of machine-learned coarse-grained (CG) models (ML-BOP, ML-BOP_dih, and ML-mW) that accurately describe the structure and thermodynamic anomalies of both water and ice at mesoscopic scales, all at two orders of magnitude cheaper computational cost than existing atomistic models. In a significant departure from conventional force-field fitting, we use a multilevel evolutionary strategy that trains CG models against not just energetics from first-principles and experiments but also temperature-dependent properties inferred from on-the-fly molecular dynamics (~ 10's of milliseconds of overall trajectories). Our ML BOP models predict both the correct experimental melting point of ice and the temperature of maximum density of liquid water that remained elusive to-date. Our ML workflow navigates efficiently through the high-dimensional parameter space to even improve upon existing high-quality CG models (e.g. mW model).

Two-Step to One-Step Nucleation of a Zeolite through a Metastable Gyroid Mesophase

The importance of nonclassical nucleation pathways in the formation of complex crystals has become apparent in recent years. Nonclassical pathways were unraveled for, among others, the crystallization of proteins, colloids, and clathrates. In those cases, the formation of a metastable fluid with density close to the crystal decreases the crystallization barrier. Recent simulations indicate that mesophases can facilitate the nucleation of zeolites. Here, we use molecular simulations to investigate the role of a gyroid mesophase on the crystallization of a model zeolite from liquid. The nucleation pathway is always nonclassical. At warmer temperatures, the mechanism proceeds in two well-defined steps: nucleation of a metastable gyroid followed by its crystallization into a zeolite. At colder temperatures, the second barrier becomes negligible, and the crystallization occurs in one step. This second scenario is also nonclassical, as the critical nucleus for the crystallization has the structure of the gyroid and seamlessly transforms into a zeolite as it grows past its critical size. To our knowledge, this is the first report of a nonclassical mechanism of crystallization mediated by a mesophase.

Why Is It So Difficult to Identify the Onset of Ice Premelting?

Premelting of ice at temperatures below 0 °C is of fundamental importance for environmental processes. Various experimental techniques have been used to investigate the temperature at which liquid-like water first appears at the ice-vapor interface, reporting onset temperatures from -160 to -2 °C. The signals that identify liquid-like order at the ice-vapor interface in these studies, however, do not show a sharp initiation with temperature. That is at odds with the expected first-order nature of surface phase transitions, and consistent with recent large-scale molecular simulations that show the first premelted layer to be sparse and to develop continuously over a wide range of temperatures. Here we perform a thermodynamic analysis to elucidate the origin of the continuous formation of the first layer of liquid at the ice-vapor interface. We conclude that a negative value of the line tension of the ice-liquid-vapor three-phase contact line is responsible for the continuous character of the transition and the sparse nature of the liquid-like domains in the incomplete first layer.

Ice-Liquid Oscillations in Nanoconfined Water

Nanoscale confinement has a strong effect on the phase behavior of water. Studies in the last two decades have revealed a wealth of novel crystalline and quasicrystalline structures for water confined in nanoslits. Less is known, however, about the nature of ice-liquid coexistence in extremely nanoconfined systems. Here, we use molecular simulations to investigate the ice-liquid equilibrium for water confined between two nanoscopic disks. We find that the nature of ice-liquid phase coexistence in nanoconfined water is different from coexistence in both bulk water and extended nanoslits. In highly nanoconfined systems, liquid water and ice do not coexist in space because the two-phase states are unstable. The confined ice and liquid phases coexist in time, through oscillations between all-liquid and all-crystalline states. The avoidance of spatial coexistence of ice and liquid originates on the non-negligible cost of the interface between confined ice and liquid in a small system. It is the result of the small number of water molecules between the plates and has no analogue in bulk water.

Multiscale Simulation Method for Quantitative Prediction of Surface Wettability at the Atomistic Level

The solid-liquid interface is of great interest because of its highly heterogeneous character and its ubiquity in various applications. The most fundamental physical variable determining the strength of the solid-liquid interface is the solid-liquid interfacial tension, which is usually measured according to the contact angle. However, an accurate experimental measurement and a reliable theoretical prediction of the contact angle remain lacking because of many practical issues. Here, we propose a first-principles-based simulation approach to quantitatively predict the contact angle of an ideally clean surface using our recently developed multiscale simulation method of density functional theory in classical explicit solvents (DFT-CES). Using this approach, we simulate the surface wettability of a graphene and graphite surface, resulting in a reliable contact angle value that is comparable to the experimental data. From our simulation results, we find that the surface wettability is dominantly affected by the strength of the solid-liquid van der Waal's interaction. However, we further elucidate that there exists a secondary contribution from the change of water-water interaction, which is manifested by the change of liquid structure and dynamics of interfacial water layer. We expect that our proposed method can be used to quantitatively predict and understand the intriguing wetting phenomena at an atomistic level and can eventually be utilized to design a surface with a controlled hydrophobic(philic)ity.

What Controls the Limit of Supercooling and Superheating of Pinned Ice Surfaces?

Cold-adapted organisms produce antifreeze proteins and glycoproteins to control the growth, melting and recrystallization of ice. It has been proposed that these molecules pin the crystal surface, creating a curvature that arrests the growth and melting of the crystal. Here we use thermodynamic modeling and molecular simulations to demonstrate that the curvature of the superheated or supercooled surface depends on the temperature and distances between ice-binding molecules, but not the details of their interactions with ice. We perform simulations of ice pinned with the antifreeze protein TmAFP, polyvinyl alcohol with different degrees of polymerization, and model ice-binding molecules to determine the thermal hystereses on melting and freezing, i.e. the maximum curvature that can be attained before, respectively, ice melts or grows irreversibly over the ice-binding molecules. We find that the thermal hysteresis is controlled by the bulkiness of the ice-binding molecules and their footprint at the ice surface. We elucidate the origin of the asymmetry between freezing and melting hysteresis found in experiments and propose guidelines to design synthetic antifreeze molecules with potent thermal hysteresis activity.

Ice-Nucleating and Antifreeze Proteins Recognize Ice through a Diversity of Anchored Clathrate and Ice-like Motifs

Cold-adapted organisms produce antifreeze and ice-nucleating proteins to prevent and promote ice formation. The crystal structure of hyperactive bacterial antifreeze protein (AFP) MpAFP suggests that this protein binds ice through an anchored clathrate motif. It is not known whether other hyperactive AFPs and ice-nucleating proteins (INPs) use the same motif to recognize or nucleate ice. Here we use molecular simulations to elucidate the ice-binding motifs of hyperactive insect AFPs and a model INP of Pseudomonas syringae. We find that insect AFPs recognize ice through anchored clathrate motifs distinct from that of MpAFP. By performing simulations of ice nucleation by PsINP, we identify two distinct ice-binding sites on opposite sides of the β-helix. The ice-nucleating sequences identified in the simulations agree with those previously proposed for the closely related INP of Pseudomonas borealis based on the structure of the protein. The simulations indicate that these sites have comparable ice-nucleating efficiency, but distinct binding motifs, controlled by the amino acid sequence: one is an anchored clathrate and the other ice-like. We conclude that anchored clathrate and ice-like motifs can be equally effective for binding proteins to ice and promoting ice nucleation.