Unravelling the origins of ice nucleation on organic crystals

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.

Physics of Ice Nucleation and Antinucleation: Action of Ice-Binding Proteins

Ice-binding proteins are crucial for the adaptation of various organisms to low temperatures. Some of these, called antifreeze proteins, are usually thought to inhibit growth and/or recrystallization of ice crystals. However, prior to these events, ice must somehow appear in the organism, either coming from outside or forming inside it through the nucleation process. Unlike most other works, our paper is focused on ice nucleation and not on the behavior of the already-nucleated ice, its growth, etc. The nucleation kinetics is studied both theoretically and experimentally. In the theoretical section, special attention is paid to surfaces that bind ice stronger than water and thus can be "ice nucleators", potent or relatively weak; but without them, ice cannot be nucleated in any way in calm water at temperatures above -30 °C. For experimental studies, we used: (i) the ice-binding protein mIBP83, which is a previously constructed mutant of a spruce budworm Choristoneura fumiferana antifreeze protein, and (ii) a hyperactive ice-binding antifreeze protein, RmAFP1, from a longhorn beetle Rhagium mordax. We have shown that RmAFP1 (but not mIBP83) definitely decreased the ice nucleation temperature of water in test tubes (where ice originates at much higher temperatures than in bulk water and thus the process is affected by some ice-nucleating surfaces) and, most importantly, that both of the studied ice-binding proteins significantly decreased the ice nucleation temperature that had been significantly raised in the presence of potent ice nucleators (CuO powder and ice-nucleating bacteria Pseudomonas syringae). Additional experiments on human cells have shown that mIBP83 is concentrated in some cell regions of the cooled cells. Thus, the ice-binding protein interacts not only with ice, but also with other sites that act or potentially may act as ice nucleators. Such ice-preventing interaction may be the crucial biological task of ice-binding proteins.

Detecting dynamic domains and local fluctuations in complex molecular systems via timelapse neighbors shuffling

It is known that the behavior of many complex systems is controlled by local dynamic rearrangements or fluctuations occurring within them. Complex molecular systems, composed of many molecules interacting with each other in a Brownian storm, make no exception. Despite the rise of machine learning and of sophisticated structural descriptors, detecting local fluctuations and collective transitions in complex dynamic ensembles remains often difficult. Here, we show a machine learning framework based on a descriptor which we name Local Environments and Neighbors Shuffling (LENS), that allows identifying dynamic domains and detecting local fluctuations in a variety of systems in an abstract and efficient way. By tracking how much the microscopic surrounding of each molecular unit changes over time in terms of neighbor individuals, LENS allows characterizing the global (macroscopic) dynamics of molecular systems in phase transition, phases-coexistence, as well as intrinsically characterized by local fluctuations (e.g., defects). Statistical analysis of the LENS time series data extracted from molecular dynamics trajectories of, for example, liquid-like, solid-like, or dynamically diverse complex molecular systems allows tracking in an efficient way the presence of different dynamic domains and of local fluctuations emerging within them. The approach is found robust, versatile, and applicable independently of the features of the system and simply provided that a trajectory containing information on the relative motion of the interacting units is available. We envisage that "such a LENS" will constitute a precious basis for exploring the dynamic complexity of a variety of systems and, given its abstract definition, not necessarily of molecular ones.

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.

Engineered Compounds to Control Ice Nucleation and Recrystallization

One of the greatest concerns in the subzero storage of cells, tissues, and organs is the ability to control the nucleation or recrystallization of ice. In nature, evidence of these processes, which aid in sustaining internal temperatures below the physiologic freezing point for extended periods of time, is apparent in freeze-avoidant and freeze-tolerant organisms. After decades of studying these proteins, we now have easily accessible compounds and materials capable of recapitulating the mechanisms seen in nature for biopreser-vation applications. The output from this burgeoning area of research can interact synergistically with other novel developments in the field of cryobiology, making it an opportune time for a review on this topic.

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.

A highly active mineral-based ice nucleating agent supports in situ cell cryopreservation in a high throughput format

Cryopreservation of biological matter in microlitre scale volumes of liquid would be useful for a range of applications. At present, it is challenging because small volumes of water tend to supercool, and deep supercooling is known to lead to poor post-thaw cell viability. Here, we show that a mineral ice nucleator can almost eliminate supercooling in 100 µl liquid volumes during cryopreservation. This strategy of eliminating supercooling greatly enhances cell viability relative to cryopreservation protocols with uncontrolled ice nucleation. Using infrared thermography, we demonstrate a direct relationship between the extent of supercooling and post-thaw cell viability. Using a mineral nucleator delivery system, we open the door to the routine cryopreservation of mammalian cells in multiwell plates for applications such as high throughput toxicology testing of pharmaceutical products and regenerative medicine.

Ideal Conductor Model: An Analytical Finite-Size Correction for Nonequilibrium Molecular Dynamics Simulations of Ion Transport through Nanoporous Membranes

Modulating ion transport through nanoporous membranes is critical to many important chemical and biological separation processes. The corresponding transport timescales, however, are often too long to capture accurately using conventional molecular dynamics (MD). Recently, path sampling techniques, such as forward-flux sampling (FFS), have emerged as attractive alternatives for efficiently and accurately estimating arbitrarily long ionic passage times. Here, we use non-equilibrium MD and FFS to explore how the kinetics and mechanisms of pressure-driven chloride transport through a nanoporous graphitic membrane are affected by its lateral dimensions. We not only find ionic passage times and free energy barriers to decrease dramatically upon increasing the membrane surface area but also observe an abrupt and discontinuous change in the locus of the transition state. These strong finite size effects arise due to the cumulative effect of the periodic images of the leading ion entering the pore on the distribution of the induced excess charge at the membrane surface in the feed. By assuming that the feed is an ideal conductor, we analytically derive a finite size correction term that can be computed from the information obtained from a single simulation and successfully use it to obtain corrected free energy profiles with no dependence on the system size. We then estimate ionic passage times in the thermodynamic limit by assuming an Eyring-type dependence of rates on barriers with a size-independent prefactor. This approach constitutes a universal framework for removing finite size artifacts in molecular simulations of ion transport through nanoporous membranes and biological channel proteins.

Poly(vinyl alcohol) Molecular Bottlebrushes Nucleate Ice

Ice binding proteins (IBP) have evolved to limit the growth of ice but also to promote ice formation by ice-nucleating proteins (INPs). IBPs, which modulate these seemingly distinct processes, often have high sequence similarities, and molecular size/assembly is hypothesized to be a crucial determinant. There are only a few synthetic materials that reproduce INP function, and rational design of ice nucleators has not been achieved due to outstanding questions about the mechanisms of ice binding. Poly(vinyl alcohol) (PVA) is a water-soluble synthetic polymer well known to effectively block ice recrystallization, by binding to ice. Here, we report the synthesis of a polymeric ice nucleator, which mimics the dense assembly of IBPs, using confined ice-binding polymers in a high-molar-mass molecular bottlebrush. Poly(vinyl alcohol)-based molecular bottlebrushes with different side-chain densities were synthesized via a combination of ring-opening metathesis polymerization (ROMP) and reversible addition-fragmentation chain-transfer (RAFT) polymerization, using "grafting-to" and "grafting-through" approaches. The facile preparation of the PVA bottlebrushes was performed via selective hydrolysis of the acetate of the poly(vinyl acetate) (PVAc) side chains of the PVAc bottlebrush precursors. Ice-binding polymer side-chain density was shown to be crucial for nucleation activity, with less dense brushes resulting in colder nucleation than denser brushes. This bio-inspired approach provides a synthetic framework for probing heterogeneous ice nucleation and a route toward defined synthetic nucleators for biotechnological applications.

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.

Chemical approaches to cryopreservation

Cryopreservation of cells and biologics underpins all biomedical research from routine sample storage to emerging cell-based therapies, as well as ensuring cell banks provide authenticated, stable and consistent cell products. This field began with the discovery and wide adoption of glycerol and dimethyl sulfoxide as cryoprotectants over 60 years ago, but these tools do not work for all cells and are not ideal for all workflows. In this Review, we highlight and critically review the approaches to discover, and apply, new chemical tools for cryopreservation. We summarize the key (and complex) damage pathways during cellular cryopreservation and how each can be addressed. Bio-inspired approaches, such as those based on extremophiles, are also discussed. We describe both small-molecule-based and macromolecular-based strategies, including ice binders, ice nucleators, ice nucleation inhibitors and emerging materials whose exact mechanism has yet to be understood. Finally, looking towards the future of the field, the application of bottom-up molecular modelling, library-based discovery approaches and materials science tools, which are set to transform cryopreservation strategies, are also included.

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.

The seven deadly sins: When computing crystal nucleation rates, the devil is in the details

The formation of crystals has proven to be one of the most challenging phase transformations to quantitatively model-let alone to actually understand-be it by means of the latest experimental technique or the full arsenal of enhanced sampling approaches at our disposal. One of the most crucial quantities involved with the crystallization process is the nucleation rate, a single elusive number that is supposed to quantify the average probability for a nucleus of critical size to occur within a certain volume and time span. A substantial amount of effort has been devoted to attempt a connection between the crystal nucleation rates computed by means of atomistic simulations and their experimentally measured counterparts. Sadly, this endeavor almost invariably fails to some extent, with the venerable classical nucleation theory typically blamed as the main culprit. Here, we review some of the recent advances in the field, focusing on a number of perhaps more subtle details that are sometimes overlooked when computing nucleation rates. We believe it is important for the community to be aware of the full impact of aspects, such as finite size effects and slow dynamics, that often introduce inconspicuous and yet non-negligible sources of uncertainty into our simulations. In fact, it is key to obtain robust and reproducible trends to be leveraged so as to shed new light on the kinetics of a process, that of crystal nucleation, which is involved into countless practical applications, from the formulation of pharmaceutical drugs to the manufacturing of nano-electronic devices.

Effect of interfacial dipole on heterogeneous ice nucleation

In this work, we performed molecular dynamics simulations of ice nucleation on a rigid surface model of cubic zinc blende structure with different surface dipole strength and orientation. Our results show that, although substrates are excellently lattice-matched to cubic ice, ice nucleation merely occurred as the interfacial water molecules (IWs) show identical or similar orientations to that of water molecules in cubic ice. Free energy landscapes revealed that, as substrates have non-suitable dipole strength/orientation, there exist large free energy barriers for rotating dipole IWs to the right orientation to trigger ice formation. This study stresses that, beyond the traditional view of lattice match and the similarity of lattice length between the substrate and new-formed crystal, the similarity between molecular orientations of interfacial component and component in the specific new-formed crystalline face is also critical for promoting ice nucleation.

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.

The atomistic details of the ice recrystallisation inhibition activity of PVA

Understanding the ice recrystallisation inhibition (IRI) activity of antifreeze biomimetics is crucial to the development of the next generation of cryoprotectants. In this work, we bring together molecular dynamics simulations and quantitative experimental measurements to unravel the microscopic origins of the IRI activity of poly(vinyl)alcohol (PVA)-the most potent of biomimetic IRI agents. Contrary to the emerging consensus, we find that PVA does not require a "lattice matching" to ice in order to display IRI activity: instead, it is the effective volume of PVA and its contact area with the ice surface which dictates its IRI strength. We also find that entropic contributions may play a role in the ice-PVA interaction and we demonstrate that small block co-polymers (up to now thought to be IRI-inactive) might display significant IRI potential. This work clarifies the atomistic details of the IRI activity of PVA and provides novel guidelines for the rational design of cryoprotectants.

A comparison between superhydrophobic surfaces (SHS) and slippery liquid-infused porous surfaces (SLIPS) in application

Slippery liquid-infused porous surfaces inspired by the Nepenthes pitcher plant exhibit excellent performances and are known for their extremely low contact angle hysteresis (<5°) and smooth surface. In contrast, superhydrophobic surfaces (SHS) exhibit poor pressure stability, difficulty in self-healing, and difficulty in removing low surface tension liquids or organic solvents, which can affect the stable air layer. Thus, these issues can be avoided through the replacement of SHS with slippery liquid infused porous surfaces (SLIPS). In this review, the theoretical models of SHS and SLIPS are classified initially, and several design standards for the preparation of SLIPS are briefly described. Then, we focus on comparing the differences in the application of SHS and SLIPS, such as pressure stability, transparency, and droplet manipulation. However, there are still some problems that need to be improved during the preparation of SLIPS, such as the evaporation of the lubricant layer, the use of a lubricant layer of toxic perfluoropolyether and other substances, and easily lost nanostructured lubricant layer. Accordingly, several new improved methods are proposed in this review, and finally, the potential applications and development prospects of SLIPS are presented.

Disclosing crystal nucleation mechanism in lithium disilicate glass through molecular dynamics simulations and free-energy calculations

Unraveling detailed mechanism of crystal nucleation from amorphous materials is challenging for both experimental and theoretical approaches. In this study, we have examined two methods to understand the initial stage of crystal precipitation from lithium disilicate glasses using molecular dynamics simulations. One of the methods is a modified exploring method to find structurally similar crystalline clusters in the glass models, enabling us to find three different embryos, such as Li₂Si₂O₅ (LS₂), Li₂SiO₃ (LS) and Li₃PO₄ (LP), in the 33Li₂O·66SiO₂·1P₂O₅ glass (LS₂P1), in which P₂O₅ is added as a nucleating agent. Interestingly, LS₂ and LP crystals were found inside the LS₂P1 glass while LS crystal appeared on the glass surface, which agrees with experimental observations. The other method is free energy calculation using a subnano-scale spherical crystal embedded in the glass model. This method, which we called Free-Energy Seeding Method (FESM), allows us to evaluate free energy change as a function of crystal radius and to identify critical size of the crystal precipitation. The free energy profiles for LS and LS₂ crystal nuclei in the LS₂ glass models possess maximum energy at a critical radius as expected by classical nucleation theory. Furthermore, the critical radius and the energy barrier height agree well with recent experimental investigation, proving the applicability of this method to design glass–ceramics by atomistic modeling.

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.

Confronting the Challenge of Modeling Cloud and Precipitation Microphysics

In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth's atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle-based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next-generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process-level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle-based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.

Dimethyl sulfoxide-free cryopreservation for cell therapy: A review

Cell-based therapeutics promise to transform the treatment of a wide range of diseases including cancer, genetic and degenerative disorders, or severe injuries. Many of the commercial and clinical development of cell therapy products require cryopreservation and storage of cellular starting materials, intermediates and/or final products at cryogenic temperature. Dimethyl sulfoxide (Me₂SO) has been the cryoprotectant of choice in most biobanking situations due to its exceptional performance in mitigating freezing-related damages. However, there is concern over the toxicity of Me₂SO and its potential side effects after administration to patients. Therefore, there has been growing demand for robust Me₂SO-free cryopreservation methods that can improve product safety and maintain potency and efficacy. This article provides an overview of the recent advances in Me₂SO-free cryopreservation of cells having therapeutic potentials and discusses a number of key challenges and opportunities to motivate the continued innovation of cryopreservation for cell therapy.

Modifying Surfaces with the Primary and Secondary Faces of Cyclodextrins To Achieve a Distinct Anti-icing Capability

Heterogenous ice nucleation (HIN) induced by organic materials is a long-lasting issue in wide-ranging fields from cryobiology to atmospheric physics, but efforts for controlling HIN are still restricted by incomplete understanding of its mechanism. In this work, distinct anti-icing capabilities were achieved by experimentally investigating the HIN behavior on the surfaces modified with the primary face (PF) and secondary face (SF) of cyclodextrins (CDs) (i.e., α-1,4-linked d-(+)-glucopyranose with two relatively flat and hydroxylated faces). To achieve this, CDs were first immobilized to the surfaces through selectively binding the PF and SF of CDs onto the solid surfaces; as such, either PF or SF is exposed to liquid water. Interestingly, HIN temperature and delay time assays indicate that HIN is depressed when the PF of CDs (which matches with the ice lattice) is exposed to liquid water whereas the HIN is facilitated when the SF of CDs (which mismatches with the ice lattice) is exposed to liquid water. This deviates from the common thought that surfaces with a template of ice lattice match facilitate the HIN. Instead, ¹H NMR studies show that the resonances of hydroxyl (OH) in the SF of CDs are most deshielded due to the formation of intramolecular hydrogen bonds, in comparison to that of OH in the PF of CDs, which weakens the interaction between the OH groups on the SF and water molecules. Thus, the distinct anti-icing capabilities of the PF and SF of CDs can be achieved and established by the distinct interactions between OH groups on the two faces and water, which is of great potential for practical applications. The molecular-level interactions between surfaces and water molecules may be a more appropriate criterion for forecasting materials' HIN ability.

Metal-catechol complexes mediate ice nucleation

The capability of mediating ice nucleation is pertinent to a broad range of fields. Herein, inspired by metal-catechol coordination found in adhesive proteins in which catechol moieties can construct strong complexes with a diverse array of metal ions, we develop a platform for mediating ice nucleation based on metal-catechol complexes and demonstrate that ice nucleation can be successively mediated by varying the characteristics and valence of the metal in metal-catechol complexes.

Stabilization of AgI's polar surfaces by the aqueous environment, and its implications for ice formation

AgI is a potent inorganic ice nucleating particle, a feature often attributed to the lattice match between its {0001} surfaces and ice. Dissolved ions are found to be essential to the stability of these polar surfaces, and crucial to ice formation.