Ice Nucleation Efficiency of Hydroxylated Organic Surfaces Is Controlled by Their Structural Fluctuations and Mismatch to Ice

High-speed cryo-microscopy reveals that ice-nucleating proteins of Pseudomonas syringae trigger freezing at hydrophobic interfaces

Ice-nucleating proteins (INpro) trigger the freezing of supercooled water droplets relevant to atmospheric, biological, and technological applications. The high ice nucleation activity of INpro isolated from the bacteria Pseudomonas syringae could be linked to the aggregation of proteins at the bacterial membrane or at the air-water interface (AWI) of droplets. Here, we imaged freezing onsets, providing direct evidence of these proposed mechanisms. High-speed cryo-microscopy identified the onset location of freezing in droplets between two protein-repellent glass slides. INpro from sterilized P. syringae (Snomax) statistically favored nucleation at the AWI of the droplets. Removing cellular fragments by filtration or adding surfactants increased the frequency of nucleation events at the AWI. On the other hand, cultivated intact bacteria cells or lipid-free droplets nucleated ice without an affinity to the AWI. Overall, we provide visual evidence that INpro from P. syringae trigger freezing at hydrophobic interfaces, such as the AWI or the bacterial membrane, with important mechanistic implications for applications of INpro.

A universal and accurate LPMI method for calculating mismatch in heterogeneous ice nucleation

The interfacial correlation factor f(m,x), where m refers to the interaction among ice, water and the substrate and x refers to the ratio of the critical nucleation size to the surface topography characteristic size of the substrate, plays a crucial role in the classical theory of heterogeneous ice nucleation as it significantly impacts the energy of nucleation. Generally, a smaller value of f(m,x) indicates a higher propensity for ice nucleation. The degree of structural compatibility between ice and the substrate greatly influences f(m,x), particularly on specific substrates. Several approaches have been proposed to calculate the lattice matching based on this idea, which allows whether a surface is favorable for nucleation to be determined. However, none of these methods adequately correlates the mismatch index with ice growth phenomena. In this paper, we embarked on a new attempt to calculate the mismatch index by combining the lattice parameter and Miller index (LPMI). Droplet freezing experiments have been carried out on α-Al2O3 and silicon surfaces with different Miller indices to verify the rationality of the LPMI method. Furthermore, we validated the LPMI method extensively against other works and further demonstrated its readiness, accuracy and universality for freezing problems. The results consistently show that δd = 2|di - ds|/(di + ds) with interplanar spacing more accurately predicts heterogeneous ice nucleation rates across a wide range of substrates than δ1 = (ai - as)/ai with the lattice parameter of ice and the substrate and is more generally applicable than δ2D = (di - di)/di with the distances between two adjacent and congener atoms on the same plane. We believe that the proposed approach will aid in the selection of substrates for promoting or inhibiting heterogeneous nucleation on a specific substrate.

Effect of substrate mismatch, orientation, and flexibility on heterogeneous ice nucleation

Heterogeneous nucleation is the main path to ice formation on Earth. The ice nucleating ability of a certain substrate is mainly determined by both molecular interactions and the structural mismatch between the ice and the substrate lattices. We focus on the latter factor using molecular simulations of the mW model. Quantifying the effect of structural mismatch alone is challenging due to its coupling with molecular interactions. To disentangle both the factors, we use a substrate composed of water molecules in such a way that any variation on the nucleation temperature can be exclusively ascribed to the structural mismatch. We find that a 1% increase in structural mismatch leads to a decrease of ∼4 K in the nucleation temperature. We also analyze the effect of orientation of the substrate with respect to the liquid. The three main ice orientations (basal, primary prism, and secondary prism) have a similar ice nucleating ability. We finally assess the effect of lattice flexibility by comparing substrates where molecules are immobile to others where a certain freedom to fluctuate around the lattice positions is allowed. Interestingly, we find that the latter type of substrate is more efficient in nucleating ice because it can adapt its structure to that of ice.

Using machine learning with atomistic surface and local water features to predict heterogeneous ice nucleation

Heterogeneous ice nucleation (HIN) has applications in climate science, nanotechnology, and cryopreservation. Ice nucleation on the earth's surface or in the atmosphere usually occurs heterogeneously involving foreign substrates, known as ice nucleating particles (INPs). Experiments identify good INPs but lack sufficient microscopic resolution to answer the basic question: What makes a good INP? We employ molecular dynamics (MD) simulations in combination with machine learning (ML) to address this question. Often, the large amount of computational cost required to cross the nucleation barrier and observe HIN in MD simulations is a practical limitation. We use information obtained from short MD simulations of atomistic surface and water models to predict the likelihood of HIN. We consider 153 atomistic substrates with some surfaces differing in elemental composition and others only in terms of lattice parameters, surface morphology, or surface charges. A range of water features near the surface (local) are extracted from short MD simulations over a time interval (≤300 ns) where ice nucleation has not initiated. Three ML classification models, Random Forest (RF), support vector machine, and Gaussian process classification are considered, and the accuracies achieved by all three approaches lie within their statistical uncertainties. Including local water features is essential for accurate prediction. The accuracy of our best RF classification model obtained including both surface and local water features is 0.89 ± 0.05. A similar accuracy can be achieved including only local water features, suggesting that the important surface properties are largely captured by the local water features. Some important features identified by ML analysis are local icelike structures, water density and polarization profiles perpendicular to the surface, and the two-dimensional lattice match to ice. We expect that this work, with its strong focus on realistic surface models, will serve as a guide to the identification or design of substrates that can promote or discourage ice nucleation.

Does freezing induce self-assembly of polymers? A molecular dynamics study

This work investigates the freezing-induced self-assembly (FISA) of polyvinyl alcohol (PVA) and PVA-like polymers using molecular dynamics simulations. In particular, the effect of the degree of supercooling, degree of polymerization, polymer type, and initial local concentration on the FISA was studied. It was found that the preeminent factor responsible for FISA is not the diffusion of the polymers away from the nucleating ice front, but the increase in the polymer's local concentration upon freezing of the solvent (water). At a higher degree of supercooling, the polymers are engulfed by the growing ice front, impeding their diffusion into the supercooled solution and finally inhibiting their self-assembly. Conversely, at a relatively lower degree of supercooling, the rate of diffusion of the polymers into the supercooled solution is higher, which increases their local concentration and results in FISA. FISA was also observed to depend on the polymer-solvent interactions. Strongly favorable solute-solvent interactions hinder the self-assembly, whereas unfavorable solute-solvent interactions promote the self-assembly. The polymer and aggregate morphology were investigated using the radius of gyration, end-to-end distance, and asphericity analysis. This study brings molecular insights into the quintessential factors governing self-assembly via freezing of the solvent, which is a novel self-assembly technique especially suitable for biomedical applications.

Characterizing Surface Ice-Philicity Using Molecular Simulations and Enhanced Sampling

The formation of ice, which plays an important role in diverse contexts ranging from cryopreservation to atmospheric science, is often mediated by solid surfaces. Although surfaces that interact favorably with ice (relative to liquid water) can facilitate ice formation by lowering nucleation barriers, the molecular characteristics that confer icephilicity to a surface are complex and incompletely understood. To address this challenge, here we introduce a robust and computationally efficient method for characterizing surface ice-philicity that combines molecular simulations and enhanced sampling techniques to quantify the free energetic cost of increasing surface-ice contact at the expense of surface-water contact. Using this method to characterize the ice-philicity of a family of model surfaces that are lattice matched with ice but vary in their polarity, we find that the nonpolar surfaces are moderately ice-phobic, whereas the polar surfaces are highly ice-philic. In contrast, for surfaces that display no complementarity to the ice lattice, we find that ice-philicity is independent of surface polarity and that both nonpolar and polar surfaces are moderately ice-phobic. Our work thus provides a prescription for quantitatively characterizing surface ice-philicity and sheds light on how ice-philicity is influenced by lattice matching and polarity.

RSeeds: Rigid Seeding Method for Studying Heterogeneous Crystal Nucleation

Heterogeneous nucleation is the dominant form of liquid-to-solid transition in nature. Although molecular simulations are most uniquely suited to studying nucleation, the waiting time to observe even a single nucleation event can easily exceed the current computational capabilities. Therefore, there exists an imminent need for methods that enable computationally fast and feasible studies of heterogeneous nucleation. Seeding is a technique that has proven to be successful at dramatically expanding the range of computationally accessible nucleation rates in simulation studies of homogeneous crystal nucleation. In this article, we introduce a new seeding method for heterogeneous nucleation called Rigid Seeding (RSeeds). Crystalline seeds are treated as pseudorigid bodies and simulated on a surface with metastable liquid above its melting temperature. This allows the seeds to adapt to the surface and identify favorable seed-surface configurations, which is necessary for reliable predictions of crystal polymorphs that form and the corresponding heterogeneous nucleation rates. We demonstrate and validate RSeeds for heterogeneous ice nucleation on a flexible self-assembled monolayer surface, a mineral surface based on kaolinite, and two model surfaces. RSeeds predicts the correct ice polymorph, exposed crystal plane, and rotation on the surface. RSeeds is semiquantitative and can be used to estimate the critical nucleus size and nucleation rate when combined with classical nucleation theory. We demonstrate that RSeeds can be used to evaluate nucleation rates spanning many orders of magnitude.

On the Propensity of Excess Hydroxide Ions at the Alcohol Monolayer-Water Interface

Atomistic molecular dynamics simulations have been employed to study the self-ion (H⁺ and OH^-) distribution at the interface between long-chain C₁₆-OH alcohol (cetyl alcohol) monolayer and water. It is well known that the free air-water interface is acidic due to accumulation of the hydronium (H₃O⁺) ions at the interface. In the present study, we have observed that contrary to the air-water interface, at the long-chain alcohol monolayer-water interface, it is the hydroxide (OH^-) ion, not the hydronium ion (H₃O⁺) that gets accumulated. By calculating the potential of mean forces, it is confirmed that there is extra stabilization for the OH^- ions at the interface relative to the bulk, but no such stabilization is observed for the H₃O⁺ ions. By analyzing the interaction of the self-ions with other constituents in the medium, it is clearly shown that the favorable interaction of the OH^- ions with the alcoholic -OH groups stabilizes this ion at the interface. By calculating coordination numbers of the self-ions it is observed that around 50% water neighbors are substituted by alcoholic -OH in case of the hydroxide ion at the interface, whereas in the case of hydronium ions, only 15% water neighbors are substituted by the alcoholic -OH. The most interesting observation about the local structure and H-bonding pattern is that the hydroxide ion acts solely as the H-bond acceptor, but the hydronium ion acts only as the H-bond donor.

Quantitative Structure-Activity Relationship Studies on Alkane Chemistry Tuning Ice Nucleation

Understanding how surface chemistry influences ice nucleation is essential for both forecasting icing phenomena and designing surfaces with desired ice-control abilities. Although alkylating is one of the most common and simplest ways for surface chemical modification, the effect of alkane chemistry on ice nucleation remains ambiguous as a result of the usually accompanying interferences of substrate morphology or heat transfer. Here, we decouple the effect of alkane chemistry on ice nucleation by investigating the ice nucleation behaviors on alkane self-assembled monolayers (SAMs) with atomic-level roughness and (sub)nanoscale thickness. Our results indicate that the introduction of alkane chemistry leads to decreased ice nucleation activities, i.e., increased anti-icing abilities, and the longer alkyl chain endows the SAM surface with the more inert ability to promote ice nucleation. The alkyl-chain-length-dependent ice nucleation activities are found to be correlated with the surface polarity. This work sheds light on a long-standing question of how alkane chemistry influences ice nucleation and offers a useful strategy for tuning ice nucleation.

Influences of 1-Propanol and Methanol Additives on Crystallization of Thin Amorphous Solid Water Films

In general, randomly oriented ice crystallites are formed by heating amorphous solid water (ASW) films at ∼160 K via homogeneous nucleation. Here, we demonstrate that monolayers of methanol and 1-propanol additives incorporated in the multilayer ASW film lead to heterogeneous nucleation at the substrate interface of Pt(111), as evidenced by the occurrence of epitaxial ice growth. The mobility of water in direct contact with the Pt(111) substrate is decreased relative to that in the bulk, but it can be increased via interactions with hydrophobic moieties of alcohols that are segregated to the interfacial region. As a result, heterogeneous nucleation occurs at ca. 160 K along with homogeneous nucleation in the film interior. However, the template effect is quenched when the alcohols are in direct contact with the substrate. The methanol adspecies deposited onto the ASW film surface induces heterogeneous nucleation at a temperature as low as 145 K, but the 1-propanol adspecies has no such an effect. Their different ability of heterogeneous nucleation at the free ASW film surface, as well as their uptake behaviors in the near surface region, is associated with the hydrophobic hydration of the alcohols resulting from different lengths of the aliphatic moiety.

Orcinol and resorcinol induce local ordering of water molecules near the liquid-vapor interface

Resorcinol and orcinol are simple members of the family of phenolic compounds present in particulate matter in the atmosphere; they are amphiphilic in nature and thus surface active in aqueous solution. Here, we used X-ray photoelectron spectroscopy to probe the concentration of resorcinol (benzene-1,3-diol) and orcinol (5-methylbenzene-1,3-diol) at the liquid-vapor interface of aqueous solutions. Qualitatively consistent surface propensity and preferential orientation was obtained by molecular dynamics simulations. Auger electron yield near-edge X-ray absorption fine structure (NEXAFS) spectroscopy was used to probe the hydrogen bonding (HB) structure, indicating that the local structure of water molecules near the surface of the resorcinol and orcinol solutions tends towards a larger fraction of tetrahedrally coordinated molecules than observed at the liquid-vapor interface of pure water. The order parameter obtained from the molecular dynamics simulations confirm these observations. This effect is being discussed in terms of the formation of an ordered structure of these molecules at the surface leading to patterns of hydrated OH groups with distances among them that are relatively close to those in ice. These results suggest that the self-assembly of phenolic species at the aqueous solution-air interface could induce freezing similar to the case of fatty alcohol monolayers and, thus, be of relevance for ice nucleation in the atmosphere. We also attempted at looking at the changes of the O 1b₁, 3a₂ and 1b₂ molecular orbitals of liquid water, which are known to be sensitive to the HB structure as well, in response to the presence of resorcinol and orcinol. However, these changes remained negligible within uncertainty for both experimentally obtained valence spectra and theoretically calculated density of states.

Janus regulation of ice growth by hyperbranched polyglycerols generating dynamic hydrogen bonding

In this study, a new phenomenon describing the Janus effect on ice growth by hyperbranched polyglycerols, which can align the surrounding water molecules, has been identified. Even with an identical polyglycerol, we not only induced to inhibit ice growth and recrystallization, but also to promote the growth rate of ice that is more than twice that of pure water. By investigating the polymer architecture and population, we found that the stark difference in the generation of quasi-structured H₂O molecules at the ice/water interface played a crucial role in the outcome of these opposite effects. Inhibition activity was induced when polymers at nearly fixed loci formed steady hydrogen bonding with the ice surface. However, the formation-and-dissociation dynamics of the interfacial hydrogen bonds, originating from and maintained by migrating polymers, resulted in an enhanced quasi-liquid layer that facilitated ice growth. Such ice growth activity is a unique property unseen in natural antifreeze proteins or their mimetic materials.

Partition Constant of Binary Mixtures for the Equilibrium between a Bulk and a Confined Phase

It is well-known that the thermodynamic, kinetic and structural properties of fluids, and in particular of water and its solutions, can be drastically affected in nanospaces. A possible consequence of nanoscale confinement of a solution is the partial segregation of its components. Thereby, confinement in nanoporous materials (NPM) has been proposed as a means for the separation of mixtures. In fact, separation science can take great advantage of NPM due to the tunability of their properties as a function of nanostructure, morphology, pore size, and surface chemistry. Alcohol-water mixtures are in this context among the most relevant systems. However, a quantitative thermodynamic description allowing for the prediction of the segregation capabilities as a function of the material-solution characteristics is missing. In the present study we attempt to fill this vacancy, by contributing a thermodynamic treatment for the calculation of the partition coefficient in confinement. Combining the multilayer adsorption model for binary mixtures with the Young equation, we conclude that the liquid-vapor surface tension and the contact angle of the pure substances can be used to predict the separation ability of a particular material for a given mixture to a semiquantitative extent. Moreover, we develop a Kelvin-type equation that relates the partition coefficient to the radius of the pore, the contact angle, and the liquid-vapor surface tensions of the constituents. To assess the validity of our thermodynamic formulation, coarse grained molecular dynamics simulations were performed on models of alcohol-water mixtures confined in cylindrical pores. To this end, a coarse-grained amphiphilic molecule was parametrized to be used in conjunction with the mW potential for water. This amphiphilic model reproduces some of the properties of methanol such as enthalpy of vaporization and liquid-vapor surface tension, and the minimum of the excess enthalpy for the aqueous solution. The partition coefficient turns out to be highly dependent on the molar fraction, on the interaction between the components and the confining matrix, and on the radius of the pore. A remarkable agreement between the theory and the simulations is found for pores of radius larger than 15 Å.

Silica as a Model Ice-Nucleating Particle to Study the Effects of Crystallinity, Porosity, and Low-Density Surface Functional Groups on Immersion Freezing

Aerosol particles can facilitate heterogeneous ice formation in the troposphere and stratosphere by acting as ice-nucleating particles, modulating cloud formation/dissipation, precipitation, and their microphysical properties. Heterogeneous ice nucleation is driven by ice embryo formation on the particle surface, which can be influenced by features of the surface such as crystallinity, surface structure, lattice structure, defects, and functional groups. To characterize the effect of crystallinity, pores, and surface functional groups toward ice nucleation, samples of comparable silica systems, specifically, quartz, ordered and nonordered porous amorphous silica samples with a range of pore sizes (2-11 nm), and nonporous functionalized silica spheres, were used as models for mineral dust aerosol particles. The ice nucleation activity of these samples was investigated by using an immersion freezing chamber. The results suggest that crystallinity has a larger effect than porosity on ice nucleation activity, as all of the porous silica samples investigated had lower onset freezing temperatures and lower ice nucleation activities than quartz. Our findings also suggest that pores alone are not sufficient to serve as effective active sites and need some additional chemical or physical property, like crystallinity, to nucleate ice in immersion mode freezing. The addition of a low density of organic functional groups to nonporous samples showed little enhancement compared to the inherent nucleation activity of silica with native surface hydroxyl groups. The density of functional groups investigated in this work suggests that a different arrangement of surface groups may be needed for enhanced immersion mode ice nucleation activity. In summary, crystallinity dictates the ice nucleation activity of silica samples rather than porosity or low-density surface functional groups. This work has broader implications regarding the climate impacts resulting from ice cloud formation.

Accurate prediction of ice nucleation from room temperature water

Crystal nucleation is one of the most fundamental processes in the physical sciences and almost always occurs heterogeneously with the aid of a nucleating substrate. No example of nucleation is more ubiquitous and impactful than the formation of ice, vital to fields as diverse as geology, biology, aeronautics, and climate science. However, despite considerable effort, we still cannot predict a priori the efficacy of a nucleating agent. Here we utilize deep learning methods to accurately predict nucleation ability from images of room temperature liquid water-generated from molecular dynamics simulations-on a broad range of substrates. The resulting model, named IcePic, can rapidly and accurately infer nucleation ability, eliminating the requirement for either notoriously expensive simulations or direct experimental measurement. In an online poll, IcePic was found to significantly outperform humans in predicting the ice nucleating efficacy of materials. By analyzing the typical errors made by humans, as well as the application of reverse interpretation methods, physical insights into the role the water contact layer plays in ice nucleation have been obtained. Moving forward, we suggest that IcePic can be used as an easy, cheap, and rapid way to discern the nucleation ability of substrates, also with potential for learning other properties related to interfacial water.

Local Ice-like Structure at the Liquid Water Surface

Experiments and computer simulations have established that liquid water's surfaces can deviate in important ways from familiar bulk behavior. Even in the simplest case of an air-water interface, distinctive layering, orientational biases, and hydrogen bond arrangements have been reported, but an overarching picture of their origins and relationships has been incomplete. Here we show that a broad set of such observations can be understood through an analogy with the basal face of crystalline ice. Using simulations, we demonstrate a number of structural similarities between water and ice surfaces, suggesting the presence of domains at the air-water interface with ice-like features that persist over 2-3 molecular diameters. Most prominent is a shared characteristic layering of molecular density and orientation perpendicular to the interface. Lateral correlations of hydrogen bond network geometry point to structural similarities in the parallel direction as well. Our results bolster and significantly extend previous conceptions of ice-like structure at the liquid's boundary and suggest that the much-discussed quasi-liquid layer on ice evolves subtly above the melting point into a quasi-ice layer at the surface of liquid water.

Icephobic/anti-icing properties of superhydrophobic surfaces

In the winter, icing on solid surfaces is a typical occurrence that may create a slew of hassles and even tragedies. Anti-icing surfaces are one of the effective solutions for this kind of problem. The roughness of a superhydrophobic surface traps air and weakens the contact between the solid surface and liquid water, allowing water droplets to be removed before freezing. At present, the conventional anti-icing methods including mechanical or thermal technology are not only surface structure unfriendly but also have the obsessions of low efficiency, high energy consumption and high manufacturing costs. Hence, developing a way to remove ice by just modifying the surface shape or chemical composition with a low surface energy is extremely desirable. Numerous attempts have been made to investigate the evolution of ice nucleation and icing on superhydrophobic surfaces under the direction of the ice nucleation hypothesis. In this paper, the research progress of ice nucleation in recent years is reviewed from theoretical and application. The icephobic surfaces are described using the wettability and classical nucleation theories. The benefits and drawbacks of anti-icing superhydrophobic surface are summarized, as well as deicing methods. Finally, several applications of ice phobic materials are illustrated, and some problems and challenges in the research field are discussed. We believed that this review will be useful in guiding future water freezing initiatives.

The role of structural order in heterogeneous ice nucleation

The freezing of water into ice is a key process that is still not fully understood. It generally requires an impurity of some description to initiate the heterogeneous nucleation of the ice crystals. The molecular structure, as well as the extent of structural order within the impurity in question, both play an essential role in determining its effectiveness. However, disentangling these two contributions is a challenge for both experiments and simulations. In this work, we have systematically investigated the ice-nucleating ability of the very same compound, cholesterol, from the crystalline (and thus ordered) form to disordered self-assembled monolayers. Leveraging a combination of experiments and simulations, we identify a “sweet spot” in terms of the surface coverage of the monolayers, whereby cholesterol maximises its ability to nucleate ice (which remains inferior to that of crystalline cholesterol) by enhancing the structural order of the interfacial water molecules. These findings have practical implications for the rational design of synthetic ice-nucleating agents.

The freezing of water into ice is still not fully understood. Here, we investigate the role of structural disorder within the biologically relevant impurities that facilitate this fundamental phase transition.

Lipid bilayers as potential ice nucleating agents

Cellular damage is a key issue in the context of cryopreservation. Much of this damage is believed to be caused by extracellular ice formation at temperatures well above the homogeneous freezing point of pure water. Hence the question: what initiates ice nucleation during cryopreservation? In this paper, we assess whether cellular membranes could be responsible for facilitating the ice nucleation process, and what characteristics would make them good or bad ice nucleating agents. By means of molecular dynamics simulations, we investigate a number of phospholipids and lipopolysaccharide bilayers at the interface with supercooled liquid water. While these systems certainly appear to act as ice nucleating agents, it is likely that other impurities might also play a role in initiating extracellular ice nucleation. Furthermore, we elucidate the factors which affect a bilayer's ability to act as an ice nucleating agent; these are complex, with specific reference to both chemical and structural factors. These findings represent a first attempt to pinpoint the origin of extracellular ice nucleation, with important implications for the cryopreservation process.

Volcanic ash ice nucleation activity is variably reduced by aging in water and sulfuric acid: the effects of leaching, dissolution, and precipitation

Volcanic ash nucleates ice when immersed in supercooled water droplets, giving it the potential to influence weather and climate from local to global scales. This ice nucleation activity (INA) is likely derived from a subset of the crystalline mineral phases in the ash. The INA of other mineral-based dusts can change when exposed to various gaseous and aqueous chemical species, many of which also interact with volcanic ash in the eruption plume and atmosphere. However, the effects of aqueous chemical aging on the INA of volcanic ash have not been explored. We show that the INA of two mineralogically distinct ash samples from Fuego and Astroni volcanoes is variably reduced following immersion in water or aqueous sulfuric acid for minutes to days. Aging in water decreases the INA of both ash samples by up to two orders of magnitude, possibly due to a reduction in surface crystallinity and cation availability accompanying leaching. Aging in sulfuric acid leads to minimal loss of INA for Fuego ash, which is proposed to reflect a quasi-equilibrium between leaching that removes ice-active sites and dissolution that reveals or creates new sites on the pyroxene phases present. Conversely, exposure to sulfuric acid reduces the INA of Astroni ash by one to two orders of magnitude, potentially through selective dissolution of ice-active sites associated with surface microtextures on some K-feldspar phases. Analysis of dissolved element concentrations in the aged ash leachates shows supersaturation of certain mineral species which could have precipitated and altered the INA of the ash. These results highlight the key role that leaching, dissolution, and precipitation likely play in the aqueous aging of volcanic ash with respect to its INA. Finally, we discuss the implications for understanding the nature and reactivity of ice-active sites on volcanic ash and its role in influencing cloud properties in the atmosphere.

Effects of Stearyl Alcohol Monolayer on the Structure, Dynamics and Vibrational Sum Frequency Generation Spectroscopy of Interfacial Water

The structure, dynamics and vibrational spectroscopy of water surface covered by a monolayer of stearyl alcohol (STA) are investigated by means of molecular dynamics simulations and vibrational sum frequency generation...

Temperature-Dependent Liquid Water Structure for Individual Micron-Sized, Supercooled Aqueous Droplets with Inclusions

Herein, we measure the water structure for individual micron-sized droplets of water, salt water, and water containing biologically and marine relevant atmospheric inclusions as a function of temperature. Individual droplets, formed on a hydrophobic substrate, are analyzed with micro-Raman spectroscopy. Analysis of the Raman spectra in the O-H stretching region shows that the equilibrium of partially and fully hydrogen-bonding water interactions change as temperature decreases up until there is a phase transition to form ice. Using these temperature-dependent measurements, the thermodynamic parameters for the interchange between partially and fully hydrogen-bonded water (PHW ⇄ FHW) for different supercooled droplets (water, salt water, and water containing biologically and marine relevant atmospheric inclusions) have been determined.

Antifreeze proteins and their biomimetics for cell cryopreservation: Mechanism, function and application-A review

Cell-based therapy is a promising technology for intractable diseases and health care applications, in which cryopreservation has become an essential procedure to realize the production of therapeutic cells. Ice recrystallization is the major factor that affects the post-thaw viability of cells. As a typical series of biomacromolecules with ice recrystallization inhibition (IRI) activity, antifreeze proteins (AFPs) have been employed in cell cryopreservation. Meanwhile, synthesized materials with IRI activity have emerged in the name of biomimetics of AFPs to expand their availability and practicality. However, fabrication of AFPs mimetics is in a chaotic period. There remains little commonality among different AFPs mimetics, then it is difficult to set guidelines on their design. With no doubt, a comprehensive understanding on the antifreezing mechanism of AFPs in molecular level will enable us to rebuild the function of AFPs, and provide convenience to clarify the relationship between structure and function of these early stage biomimetics. In this review, we would discuss those previously reported biomimetics to summarize their structure characteristics concerning the IRI activity and attempt to develop a roadmap for guiding the design of novel AFPs mimetics.

Hydration and Hydrogen Bond Order of Octadecanoic Acid and Octadecanol Films on Water at 21 and 1 °C

The temperature-dependent hydration structure of long-chain fatty acids and alcohols at air-water interfaces has great significance in the fundamental interactions underlying ice nucleation in the atmosphere. We present an integrated theoretical and experimental study of the temperature-dependent vibrational structure and electric field character of the immediate hydration shells of fatty alcohol and acid headgroups. We use a combination of surface-sensitive infrared reflection-absorption spectroscopy (IRRAS), surface potentiometry, and ab initio molecular dynamics simulations to elucidate detailed molecular structures of the octadecanoic acid and octadecanol (stearic acid and stearyl alcohol) headgroup hydration shells at room temperature and near freezing. In experiments, the alcohol at high surface concentration exhibits the largest surface potential; yet we observe a strengthening of the hydrogen-bonding for the solvating water molecules near freezing for both the alcohol and the fatty acid IRRAS experiments. Results reveal that the hydration shells for both compounds screen their polar headgroup dipole moments reducing the surface potential at low surface coverages; at higher surface coverage, the polar headgroups become dehydrated, which reduces the screening, correlating to higher observed surface potential values. Lowering the temperature promotes tighter chain packing and an increase in surface potential. IRRAS reveals that the intra- and intermolecular vibrational coupling mechanisms are highly sensitive to changes in temperature. We find that intramolecular coupling dominates the vibrational relaxation pathways for interfacial water determined by comparing the H₂O and the HOD spectra. Using ab initio molecular dynamics (AIMD) calculations on cluster systems of propanol + 6H₂O and propionic acid + 10H₂O, a spectral decomposition scheme was used to correlate the OH stretching motion with the IRRAS spectral features, revealing the effects of intra- and intermolecular coupling on the spectra. Spectra calculated with AIMD reproduce the red shift and increase in intensity observed in experimental spectra corresponding to the OH stretching region of the first solvation shell. These findings suggest that intra- and intermolecular vibrational couplings strongly impact the OH stretching region at fatty acid and fatty alcohol water interfaces. Overall, results are consistent with ice templating behavior for both the fatty acid and the alcohol, yet the surface potential signature is strongest for the fatty alcohol. These findings develop a better understanding of the complex surface potential and spectral signatures involved in ice templating.

Proton Traffic Jam: Effect of Nanoconfinement and Acid Concentration on Proton Hopping Mechanism

The properties of the water network in concentrated HCl acid pools in nanometer-sized reverse non-ionic micelles were probed with TeraHertz absorption, dielectric relaxation spectroscopy, and reactive force field simulations capable of describing proton hopping mechanisms. We identify that only at a critical micelle size of W0=9 do solvated proton complexes form in the water pool, accompanied by a change in mechanism from Grotthuss forward shuttling to one that favors local oscillatory hopping. This is due to a preference for H+ and Cl- ions to adsorb to the micelle interface, together with an acid concentration effect that causes a "traffic jam" in which the short-circuiting of the hydrogen-bonding motif of the hydronium ion decreases the forward hopping rate throughout the water interior even as the micelle size increases. These findings have implications for atmospheric chemistry, biochemical and biophysical environments, and energy materials, as transport of protons vital to these processes can be suppressed due to confinement, aggregation, and/or concentration.

Recent Advances for Improving the Accuracy, Transferability, and Efficiency of Reactive Force Fields

Reactive force fields provide an affordable model for simulating chemical reactions at a fraction of the cost of quantum mechanical approaches. However, classically accounting for chemical reactivity often comes at the expense of accuracy and transferability, while computational cost is still large relative to nonreactive force fields. In this Perspective, we summarize recent efforts for improving the performance of reactive force fields in these three areas with a focus on the ReaxFF theoretical model. To improve accuracy, we describe recent reformulations of charge equilibration schemes to overcome unphysical long-range charge transfer, new ReaxFF models that account for explicit electrons, and corrections for energy conservation issues of the ReaxFF model. To enhance transferability we also highlight new advances to include explicit treatment of electrons in the ReaxFF and hybrid nonreactive/reactive simulations that make it possible to model charge transfer, redox chemistry, and large systems such as reverse micelles within the framework of a reactive force field. To address the computational cost, we review recent work in extended Lagrangian schemes and matrix preconditioners for accelerating the charge equilibration method component of ReaxFF and improvements in its software performance in LAMMPS.

Ice Nucleation Activity of Perfluorinated Organic Acids

Perfluorinated acids (PFAs) are widely used synthetic chemical compounds, highly resistant to environmental degradation. The widespread PFA contamination in remote regions such as the High Arctic implies currently not understood long-range atmospheric transport pathways. Here, we report that perfluorooctanoic acid (PFOA) initiates heterogeneous ice nucleation at temperatures as high as -16 °C. In contrast, the eight-carbon octanoic acid, perfluorooctanesulfonic acid, and deprotonated PFOA showed poor ice nucleating capabilities. The ice nucleation ability of PFOA correlates with the formation of a PFOA monolayer at the air-water interface, suggesting a mechanism in which the aligned hydroxyl groups of the carboxylic acid moieties provide a lattice matching to ice. The ice nucleation capabilities of fluorinated compounds like PFOA might be relevant for cloud glaciation in the atmosphere and the removal of these persistent pollutants by wet deposition.

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.

Ice nucleation activity of iron oxides via immersion freezing and an examination of the high ice nucleation activity of FeO

Heterogeneous ice nucleation is a common process in the atmosphere, but relatively little is known about the role of different surface characteristics on the promotion of ice nucleation. We have used a series of iron oxides as a model system to study the role of lattice mismatch and defects induced by milling on ice nucleation activity. The iron oxides include wüstite (FeO), hematite (Fe₂O₃), magnetite (Fe₃O₄), and goethite (FeOOH). The iron oxides were characterized by X-ray diffraction (XRD) and Brunauer-Emmett-Teller (BET) surface area measurements. The immersion freezing experiments were performed using an environmental chamber. Wüstite (FeO) had the highest ice nucleation activity, which we attribute to its low lattice mismatch with hexagonal ice and the exposure of Fe-OH after milling. A comparison study of MnO and wüstite (FeO) with milled and sieved samples for each suggests that physical defects alone result in only a slight increase in ice nucleation activity. Despite differences in the molecular formula and surface groups, hematite (Fe₂O₃), magnetite (Fe₃O₄), and goethite (FeOOH) had similar ice nucleation activities, which may be attributed to their high lattice mismatch to hexagonal ice. This study provides further insight into the characteristics of a good heterogeneous ice nucleus and, more generally, helps to elucidate the interactions between aerosol particles and ice particles in clouds.

Brief Overview of Ice Nucleation

The nucleation of ice is vital in cloud physics and impacts on a broad range of matters from the cryopreservation of food, tissues, organs, and stem cells to the prevention of icing on aircraft wings, bridge cables, wind turbines, and other structures. Ice nucleation thus has broad implications in medicine, food engineering, mineralogy, biology, and other fields. Nowadays, the growing threat of global warming has led to intense research activities on the feasibility of artificially modifying clouds to shift the Earth’s radiation balance. For these reasons, nucleation of ice has been extensively studied over many decades and rightfully so. It is thus not quite possible to cover the whole subject of ice nucleation in a single review. Rather, this feature article provides a brief overview of ice nucleation that focuses on several major outstanding fundamental issues. The author’s wish is to aid early researchers in ice nucleation and those who wish to get into the field of ice nucleation from other disciplines by concisely summarizing the outstanding issues in this important field. Two unresolved challenges stood out from the review, namely the lack of a molecular-level picture of ice nucleation at an interface and the limitations of classical nucleation theory.

Hydroxyl Group Separation Distances in Anti-Freeze Compounds and Their Effects on Ice Nucleation

Since the discovery of biological antifreeze glycoproteins (AFGPs), which can inhibit ice nucleation, there has been considerable interest in understanding their mechanisms and mimicking them in synthetic polymers. In this study, we used molecular dynamics simulations of modified polyvinyl alcohol (PVA) compounds to show that the hydroxyl (OH) group distance is a key factor in whether certain compounds promote or inhibit ice nucleation. A hydroxyl distance smaller than ~2.8 Å but greater than ~7.1 Å in modified PVA (MPVA) compounds was associated with the promotion of ice nucleation, while a hydroxyl group separation distance of approximately ~5.0 Å was correlated with a delay in ice nucleation, owing to changes in the energy of the system. Thus, these results may help explain some of the mechanisms of current known anti-freeze compounds and may have implications for designing new anti-freeze compounds in the future.

Relating Structure and Ice Nucleation of Mixed Surfactant Systems Relevant to Sea Spray Aerosol

Ice nucleating particles (INPs) influence weather and climate by their effect on cloud phase state. Fatty alcohols present within aerosol particles confer a potentially important source of ice nucleation activity to sea spray aerosol produced in oceanic regions. However, their interactions with other aerosol components and the influence on freezing were previously largely unknown. Here, we report quantitative measurements of fatty alcohols in model sea spray aerosol and examine the relationships between the composition and structure of the surfactants and subphase in the context of these measurements. Deposited mixtures of surfactants retain the ability to nucleate ice, even in fatty acid-dominant compositions. Strong refreezing effects are also observed, where previously frozen water-surfactant samples nucleate more efficiently. Structural sources of refreezing behavior are identified as either kinetically trapped film states or three-dimensional (3D) solid surfactant particles. Salt effects are especially important for surfactant INPs, where high salt concentrations suppress freezing. A simple water uptake model suggests that surfactant-containing aerosol requires either very low salt content or kinetic trapping as solid particles to act as INPs in the atmosphere. These types of INPs could be identified through comparison of different INP instrument responses.

Use of Ion Exchange To Regulate the Heterogeneous Ice Nucleation Efficiency of Mica

Heterogeneous ice nucleation (HIN) triggered by mineral surfaces typically exposed to various ions can have a significant impact on the regional atmosphere and climate. However, the dependence of HIN on the nature of the mineral surface ions is still largely unexplored due to the complexity of mineral surfaces. Because K⁺ on the atomically flat (001) surface of mica can be readily replaced by different cations through ion exchange, muscovite mica was selected; its simple nature provides a very straightforward system that can serve as the model for investigating the effects of mineral surface ions on HIN. Our experiments show that the surface (001) of H⁺-exchanged mica displays markedly higher HIN efficiencies than that of Na-/K-mica. Vibrational sum-frequency generation spectroscopy reveals that H-mica induces substantially less orientation ordering than Na-/K-mica within the contact water layer at the interface. Molecular dynamics simulations suggest that the HIN efficiency of mica depends on the positional arrangement and orientation of the interfacial water. The formation of the hexagonal ice Ih basal-type structure in the first water layer atop the mica surface facilitates HIN, which is determined by the size of the protruding ions atop the mica surface and by the surface adsorption energy. The orientational distribution is optimal for HIN when 25% of the water molecules in the first water layer atop the mica surface have one OH group pointing up and 25% have one OH group pointing down, which, in turn, is determined by the surface charge distribution.

Water Freezes at Near-Zero Temperatures Using Carbon Nanotube-Based Electrodes under Static Electric Fields

Although static electric fields have been effective in controlling ice nucleation, the highest freezing temperature (T_f) of water that can be achieved in an electric field (E) is still uncertain. We performed a systematic study of the effect of an electric field on water freezing by varying the thickness of a dielectric layer and the voltage across it in an electrowetting system. Results show that T_f first increases sharply with E and then reaches saturation at -3.5 °C after a critical value E of 6 × 10⁶ V/m. Using classical heterogeneous nucleation theory, it is revealed that this behavior is due to saturation in the contact angle of the ice embryo with the underlying substrate. Finally, we show that it is possible to overcome this freezing saturation by controlling the uniformity of the electric field using carbon nanotubes. We achieve a T_f of -0.6 °C using carbon nanotube-based electrodes with an E of 3 × 10⁷ V/m. This work sheds new light on the control of ice nucleation and has the potential to impact many applications ranging from food freezing to ice production.

Nucleation and growth of water ice on oxide surfaces: the influence of a precursor to water dissociation

We have investigated how nucleation and growth processes of ice are influenced by interfacial molecular interactions on some oxide surfaces, such as rutile TiO2(110), TiO2(100), MgO(100), and Al2O3(0001), based on the diffraction patterns of electrons transmitted through ice crystallites under the experimental configuration of reflection high energy electron diffraction (RHEED). The cubic ice Ic grows on the TiO2(110) surface with the epitaxial relationship of (110)Ic//(110)TiO2 and [001]Ic//[11[combining macron]0]TiO2. The epitaxial ice growth tends to be disturbed on the TiO2(110) surface under the presence of oxygen vacancies and adatoms. The result is not simply ascribable to small misfit values between TiO2 and ice Ic lattices (∼2%) because ice grains are formed randomly on TiO2(100). No template effects are identified during ice nucleation on the pristine MgO(100) and Al2O3(0001) surfaces either. The water molecules are chemisorbed weakly on these surfaces as a precursor to dissociation via the acid-base interaction. Such anchored water species act as an inhibitor of epitaxial ice growth because the orientation flexibility of physisorbed water during nucleation is hampered at the interface by the preferential formation of hydrogen bonds.

Predicting heterogeneous ice nucleation with a data-driven approach

Water in nature predominantly freezes with the help of foreign materials through a process known as heterogeneous ice nucleation. Although this effect was exploited more than seven decades ago in Vonnegut's pioneering cloud seeding experiments, it remains unclear what makes a material a good ice former. Here, we show through a machine learning analysis of nucleation simulations on a database of diverse model substrates that a set of physical descriptors for heterogeneous ice nucleation can be identified. Our results reveal that, beyond Vonnegut's connection with the lattice match to ice, three new microscopic factors help to predict the ice nucleating ability. These are: local ordering induced in liquid water, density reduction of liquid water near the surface and corrugation of the adsorption energy landscape felt by water. With this we take a step towards quantitative understanding of heterogeneous ice nucleation and the in silico design of materials to control ice formation.

Heterogeneous Electrofreezing Triggered by CO2 on Pyroelectric Crystals: Qualitatively Different Icing on Hydrophilic and Hydrophobic Surfaces

By performing icing experiments on hydrophilic and hydrophobic surfaces of pyroelectric amino acids and on the x-cut faces of LiTaO₃ , we discovered that the effect of electrofreezing of super cooled water is triggered by ions of carbonic acid. During the cooling of the hydrophilic pyroelectric crystals, a continuous water layer is created between the charged hemihedral faces, as confirmed by impedance measurements. As a result, a current of carbonic acid ions, produced by dissolved environmental CO₂ , flows through the wetted layer towards the hemihedral faces and elevates the icing temperature. This proposed mechanism is based on the following: (i) on hydrophilic surfaces, water with dissolved CO₂ (pH 4) freezes at higher temperatures than pure water of pH 7. (ii) In the absence of the ionic current, achieved by linking the two hemihedral faces of hydrophilic crystals by a conductive paint, water of the two pH levels freeze at the same temperature. (iii) On hydrophobic crystals with similar pyroelectric coefficients, where there is no continuous wetted layer, no electrofreezing effect is observed.

Effects of Inorganic Ions on Ice Nucleation by the Al Surface of Kaolinite Immersed in Water

Molecular dynamics simulations are employed to investigate the influence of inorganic salts on ice nucleation by the Al surface of kaolinite, terminated with hydroxyl groups. Seven salt solutions (LiI(Cl), NaI(Cl), KI(Cl), and NH₄I) are considered. Simulations were performed at 300 K to obtain equilibrium surface-ion and surface-water density profiles. These simulations show no specific ion adsorption at the kaolinite surface. There are weak surface-ion correlations, with cations preferring to be closer to the surface than the anions. At a supercooling of 26 K (taking account of freezing point depression), 1 M salt solutions slowed ice nucleation by a factor of 2-3 compared with pure water and significantly reduced the rate of ice growth after nucleation. All salt solutions had similar influences on ice nucleation, and no specific ion effects were identified. Ice nucleation simulations for 1 M NaI(Cl), KI(Cl), and LiI solutions were performed for a range of temperatures. In all cases, the supercooling required for ice nucleation was larger by ∼1-6 K, after accounting for freezing point depression, than that required for pure water. For 1 M LiI solution an earlier laboratory study using kaolin as ice nucleating particles (INP) reported that the supercooling required for ice nucleation was ∼11 K smaller than that required for pure water. Our simulation results are not consistent with this finding. In this paper, we report new laboratory results for 1 M LiI solution employing kaolinite as INP. In our experiments ice nucleation in the LiI solution required the same supercooling as pure water, which is more consistent with our simulations.

Surface phase transitions and crystal habits of ice in the atmosphere

With climate modeling predicting a raise of at least 2°C by year 2100, the fate of ice has become a serious concern, but we still do not understand how ice grows (or melts). In the atmosphere, crystal growth rates of basal and prism facets exhibit an enigmatic temperature dependence and crossover up to three times in a range between 0° and -40°. Here, we use large-scale computer simulations to characterize the ice surface and identify a sequence of previously unidentified phase transitions on the main facets of ice crystallites. Unexpectedly, we find that as temperature is increased, the crystal surface transforms from a disordered phase with proliferation of steps to a smooth phase with small step density. This causes the anomalous increase of step free energies and provides the long sought explanation for the enigmatic crossover of snow crystal growth rates found in the atmosphere.

Deep-supercooling for extended preservation of adipose-derived stem cells

Cell preservation is an enabling technology for widespread distribution and applications of mammalian cells. Traditional cryopreservation via slow-freezing or vitrification provides long-term storage but requires cytotoxic cryoprotectants (CPA) and tedious CPA loading/unloading, cooling, and recovering procedures. Hypothermic storage around 0-4 °C is an alternative method but only works for a short period due to its high storage temperatures. Here, we report on the deep-supercooling (DSC) preservation of human adipose-derived stem cells at deep subzero temperatures without freezing for extended storage. Enabled by surface sealing with an immiscible oil phase, cell suspension can be preserved in a liquid state at -13 °C and -16 °C for 7 days with high cell viability, retention of stemness, attachment, and multilineage differentiation capacities. These results demonstrate that DSC is an improved short-term preservation approach to provide off-the-shelf cell sources for booming cell-based medicine and bioengineering.

Hydrogen bonding structure of confined water templated by a metal-organic framework with open metal sites

Water in confinement exhibits properties significantly different from bulk water due to frustration in the hydrogen-bond network induced by interactions with the substrate. Here, we combine infrared spectroscopy and many-body molecular dynamics simulations to probe the structure and dynamics of confined water as a function of relative humidity within a metal-organic framework containing cylindrical pores lined with ordered cobalt open coordination sites. Building upon the agreement between experimental and theoretical spectra, we demonstrate that water at low relative humidity binds initially to open metal sites and subsequently forms disconnected one-dimensional chains of hydrogen-bonded water molecules bridging between cobalt atoms. With increasing relative humidity, these water chains nucleate pore filling, and water molecules occupy the entire pore interior before the relative humidity reaches 30%. Systematic analysis of rotational and translational dynamics indicates heterogeneity in this pore-confined water, with water molecules displaying variable mobility as a function of distance from the interface.

The properties of water under confinement are significantly altered with respect to the bulk phase. Here the authors use infrared spectroscopy and many-body molecular dynamics simulations to show the structure and dynamics of confined water as a function of relative humidity within a metal-organic framework.

A generalized deep learning approach for local structure identification in molecular simulations

Identifying local structure in molecular simulations is of utmost importance. The most common existing approach to identify local structure is to calculate some geometrical quantity referred to as an order parameter. In simple cases order parameters are physically intuitive and trivial to develop (e.g., ion-pair distance), however in most cases, order parameter development becomes a much more difficult endeavor (e.g., crystal structure identification). Using ideas from computer vision, we adapt a specific type of neural network called a PointNet to identify local structural environments in molecular simulations. A primary challenge in applying machine learning techniques to simulation is selecting the appropriate input features. This challenge is system-specific and requires significant human input and intuition. In contrast, our approach is a generic framework that requires no system-specific feature engineering and operates on the raw output of the simulations, i.e., atomic positions. We demonstrate the method on crystal structure identification in Lennard-Jones (four different phases), water (eight different phases), and mesophase (six different phases) systems. The method achieves as high as 99.5% accuracy in crystal structure identification. The method is applicable to heterogeneous nucleation and it can even predict the crystal phases of atoms near external interfaces. We demonstrate the versatility of our approach by using our method to identify surface hydrophobicity based solely upon positions and orientations of surrounding water molecules. Our results suggest the approach will be broadly applicable to many types of local structure in simulations.