Formation of dissipative structures in microscopic models of mixtures with species interconversion.

The separation of substances into different phases is ubiquitous in nature and important scientifically and technologically. This phenomenon may become drastically different if the species involved, whether molecules or supramolecular assemblies, interconvert. In the presence of an external force large enough to overcome energetic differences between the interconvertible species (forced interconversion), the two alternative species will be present in equal amounts, and the striking phenomenon of steady-state, restricted phase separation into mesoscales is observed. Such microphase separation is one of the simplest examples of dissipative structures in condensed matter. In this work, we investigate the formation of such mesoscale steady-state structures through Monte Carlo and molecular dynamics simulations of three physically distinct microscopic models of binary mixtures that exhibit both equilibrium (natural) interconversion and a nonequilibrium source of forced interconversion. We show that this source can be introduced through an internal imbalance of intermolecular forces or an external flux of energy that promotes molecular interconversion, possible manifestations of which could include the internal nonequilibrium environment of living cells or a flux of photons. The main trends and observations from the simulations are well captured by a nonequilibrium thermodynamic theory of phase transitions affected by interconversion. We show how a nonequilibrium bicontinuous microemulsion or a spatially modulated state may be generated depending on the interplay between diffusion, natural interconversion, and forced interconversion.

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

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

A first-principles machine-learning force field for heterogeneous ice nucleation on microcline feldspar.

The formation of ice in the atmosphere affects precipitation and cloud properties, and plays a key role in the climate of our planet. Although ice can form directly from liquid water under deeply supercooled conditions, the presence of foreign particles can aid ice formation at much warmer temperatures. Over the past decade, experiments have highlighted the remarkable efficiency of feldspar minerals as ice nuclei compared to other particles present in the atmosphere. However, the exact mechanism of ice formation on feldspar surfaces has yet to be fully understood. Here, we develop a first-principles machine-learning model for the potential energy surface aimed at studying ice nucleation at microcline feldspar surfaces. The model is able to reproduce with high-fidelity the energies and forces derived from density-functional theory (DFT) based on the SCAN exchange and correlation functional. Our training set includes configurations of bulk supercooled water, hexagonal and cubic ice, microcline, and fully-hydroxylated feldspar surfaces exposed to a vacuum, liquid water, and ice. We apply the machine-learning force field to study different fully-hydroxylated terminations of the (100), (010), and (001) surfaces of microcline exposed to a vacuum. Our calculations suggest that terminations that do not minimize the number of broken bonds are preferred in a vacuum. We also study the structure of supercooled liquid water in contact with microcline surfaces, and find that water density correlations extend up to around 10 Å from the surfaces. Finally, we show that the force field maintains a high accuracy during the simulation of ice formation at microcline surfaces, even for large systems of around 30 000 atoms. Future work will be directed towards the calculation of nucleation free-energy barriers and rates using the force field developed herein, and understanding the role of different microcline surfaces in ice nucleation.

Free-energy landscape and spinodals for the liquid-liquid transition of the TIP4P/2005 and TIP4P/Ice models of water.

Continued increases in computational power now make it possible to evaluate the free-energy landscape associated with the first-order liquid-liquid transition in realistic models of water for which an accurate estimate of the liquid-liquid critical point exists, and to explore its change with pressure near the coexistence line. We report the results of 50 µs-long NPT umbrella sampling simulations for two realistic models for water, TIP4P/2005 and TIP4P/ice, 3-9 K below their critical temperatures. The free energy profile at different pressures clearly shows the presence of two well-defined free energy basins and makes it possible to identify the liquid-liquid spinodal points, the limits of stability that define the (temperature dependent) pressure range within which two distinct free energy basins exist. The results show that for temperatures less than 10 K below the critical temperature, metastable states are possible across a very limited pressure interval, information that is relevant to the interpretation of experiments probing the metastable phase behavior of deeply supercooled water in the so-called no-man's land.

Melting curves of ice polymorphs in the vicinity of the liquid-liquid critical point.

The possible existence of a liquid-liquid critical point in deeply supercooled water has been a subject of debate due to the challenges associated with providing definitive experimental evidence. The pioneering work by Mishima and Stanley [Nature 392, 164-168 (1998)] sought to shed light on this problem by studying the melting curves of different ice polymorphs and their metastable continuation in the vicinity of the expected liquid-liquid transition and its associated critical point. Based on the continuous or discontinuous changes in the slope of the melting curves, Mishima [Phys. Rev. Lett. 85, 334 (2000)] suggested that the liquid-liquid critical point lies between the melting curves of ice III and ice V. We explore this conjecture using molecular dynamics simulations with a machine learning model based on ab initio quantum-mechanical calculations. We study the melting curves of ices III, IV, V, VI, and XIII and find that all of them are supercritical and do not intersect the liquid-liquid transition locus. We also find a pronounced, yet continuous, change in the slope of the melting lines upon crossing of the liquid locus of maximum compressibility. Finally, we analyze the literature in light of our findings and conclude that the scenario in which the melting curves are supercritical is favored by the most recent computational and experimental evidence. Although the preponderance of evidence is consistent with the existence of a second critical point in water, the behavior of ice polymorph melting lines does not provide strong evidence in support of this viewpoint, according to our calculations.

Critical behavior in a chiral molecular model.

Understanding the condensed-phase behavior of chiral molecules is important in biology as well as in a range of technological applications, such as the manufacture of pharmaceuticals. Here, we use molecular dynamics simulations to study a chiral four-site molecular model that exhibits a second-order symmetry-breaking phase transition from a supercritical racemic liquid into subcritical D-rich and L-rich liquids. We determine the infinite-size critical temperature using the fourth-order Binder cumulant, and we show that the finite-size scaling behavior of the order parameter is compatible with the 3D Ising universality class. We also study the spontaneous D-rich to L-rich transition at a slightly subcritical temperature of T = 0.985Tc, and our findings indicate that the free energy barrier for this transformation increases with system size as N2/3, where N is the number of molecules, consistent with a surface-dominated phenomenon. The critical behavior observed herein suggests a mechanism for chirality selection in which a liquid of chiral molecules spontaneously forms a phase enriched in one of the two enantiomers as the temperature is lowered below the critical point. Furthermore, the increasing free energy barrier with system size indicates that fluctuations between the L-rich and D-rich phases are suppressed as the size of the system increases, trapping it in one of the two enantiomerically enriched phases. Such a process could provide the basis for an alternative explanation for the origin of biological homochirality. We also conjecture the possibility of observing nucleation at subcritical temperatures under the action of a suitable chiral external field.

Signatures of a liquid-liquid transition in an ab initio deep neural network model for water.

The possible existence of a metastable liquid-liquid transition (LLT) and a corresponding liquid-liquid critical point (LLCP) in supercooled liquid water remains a topic of much debate. An LLT has been rigorously proved in three empirically parametrized molecular models of water, and evidence consistent with an LLT has been reported for several other such models. In contrast, experimental proof of this phenomenon has been elusive due to rapid ice nucleation under deeply supercooled conditions. In this work, we combined density functional theory (DFT), machine learning, and molecular simulations to shed additional light on the possible existence of an LLT in water. We trained a deep neural network (DNN) model to represent the ab initio potential energy surface of water from DFT calculations using the Strongly Constrained and Appropriately Normed (SCAN) functional. We then used advanced sampling simulations in the multithermal-multibaric ensemble to efficiently explore the thermophysical properties of the DNN model. The simulation results are consistent with the existence of an LLCP, although they do not constitute a rigorous proof thereof. We fit the simulation data to a two-state equation of state to provide an estimate of the LLCP's location. These combined results-obtained from a purely first-principles approach with no empirical parameters-are strongly suggestive of the existence of an LLT, bolstering the hypothesis that water can separate into two distinct liquid forms.

Liquid-Liquid Transition in Water from First Principles.

A long-standing question in water research is the possibility that supercooled liquid water can undergo a liquid-liquid phase transition (LLT) into high- and low-density liquids. We used several complementary molecular simulation techniques to evaluate the possibility of an LLT in an ab initio neural network model of water trained on density functional theory calculations with the SCAN exchange correlation functional. We conclusively show the existence of a first-order LLT and an associated critical point in the SCAN description of water, representing the first definitive computational evidence for an LLT in water from first principles.

Fluid-fluid phase transitions in a chiral molecular model.

Molecular chirality is a fundamental phenomenon, underlying both life as we know it and industrial pharmaceutical syntheses. Understanding the symmetry breaking phase transitions exhibited by many chiral molecular substances provides basic insights for topics ranging from the origin of life to the rational design of drug manufacturing processes. In this work, we have performed molecular dynamics simulations to investigate the fluid-fluid phase transitions of a flexible three-dimensional four-site chiral molecular model developed by Latinwo et al. [J. Chem. Phys. 145, 154503 (2016)] and Petsev et al. [J. Chem. Phys. 155, 084105 (2021)]. By introducing a bias favoring local homochiral vs heterochiral interactions, the system exhibits a phase transition from a single achiral phase to a single chiral phase that undergoes infrequent interconversion between the two thermodynamically identical chiral states: the L-rich and D-rich phases. According to the phase rule, this reactive binary system has two independent degrees of freedom and exhibits a density-dependent critical locus. Below the liquid-liquid critical locus, there exists a first-order vapor-liquid coexistence region with a single independent degree of freedom. Our results provide basic thermodynamic and kinetic insights for understanding many-body chiral symmetry breaking phenomena.

Liquid-liquid criticality in the WAIL water model.

The hypothesis that the anomalous behavior of liquid water is related to the existence of a second critical point in deeply supercooled states has long been the subject of intense debate. Recent, sophisticated experiments designed to observe the transformation between the two subcritical liquids on nano- and microsecond time scales, along with demanding numerical simulations based on classical (rigid) models parameterized to reproduce thermodynamic properties of water, have provided support to this hypothesis. A stronger numerical proof requires demonstrating that the critical point, which occurs at temperatures and pressures far from those at which the models were optimized, is robust with respect to model parameterization, specifically with respect to incorporating additional physical effects. Here, we show that a liquid-liquid critical point can be rigorously located also in the WAIL model of water [Pinnick et al., J. Chem. Phys. 137, 014510 (2012)], a model parameterized using ab initio calculations only. The model incorporates two features not present in many previously studied water models: It is both flexible and polarizable, properties which can significantly influence the phase behavior of water. The observation of the critical point in a model in which the water-water interaction is estimated using only quantum ab initio calculations provides strong support to the viewpoint according to which the existence of two distinct liquids is a robust feature in the free energy landscape of supercooled water.

Thermodynamics and kinetics of crystallization in deeply supercooled Stillinger-Weber silicon.

We study the kinetics of crystallization in deeply supercooled liquid silicon employing computer simulations and the Stillinger-Weber three-body potential. The free energy barriers to crystallization are computed using umbrella sampling Monte Carlo simulations and from unconstrained molecular dynamics simulations using a mean first passage time formulation. We focus on state points that have been described in earlier work [S. Sastry and C. A. Angell, Nat. Mater. 2, 739 (2003)] as straddling a liquid-liquid phase transition (LLPT) between two metastable liquid states. It was argued subsequently [Ricci et al., Mol. Phys. 117, 3254 (2019)] that the apparent transition is due to the loss of metastability of the liquid state with respect to the crystalline state. The presence of a barrier to crystallization for these state points is therefore of importance to ascertain, which we investigate, with due attention to ambiguities that may arise from the choice of order parameters. We find a well-defined free energy barrier to crystallization and demonstrate that both umbrella sampling and mean first passage time methods yield results that agree quantitatively. Our results thus provide strong evidence against the possibility that the liquids at state points close to the reported LLPT exhibit slow, spontaneous crystallization, but they do not address the existence of a LLPT (or lack thereof). We also compute the free energy barriers to crystallization at other state points over a broad range of temperatures and pressures and discuss the effect of changes in the microscopic structure of the metastable liquid on the free energy barrier heights.

Effect of configuration-dependent multi-body forces on interconversion kinetics of a chiral tetramer model.

We describe a reformulation of the four-site molecular model for chiral phenomena introduced by Latinwo et al. ["Molecular model for chirality phenomena," J. Chem. Phys. 145, 154503 (2016)]. The reformulation includes an additional eight-body force that arises from an explicit configuration-dependent term in the potential energy function, resulting in a coarse-grained energy-conserving force field for molecular dynamics simulations of chirality phenomena. In this model, the coarse-grained interaction energy between two tetramers depends on their respective chiralities and is controlled by a parameter λ, where λ < 0 favors local configurations involving tetramers of opposite chirality and λ > 0 gives energetic preference to configurations involving tetramers of the same chirality. We compute the autocorrelation function for a quantitative chirality metric and demonstrate that the multi-body force modifies the interconversion kinetics such that λ ≠ 0 increases the effective barrier for enantiomer inversion. Our simulations reveal that for λ > 0 and temperatures below a sharply defined threshold value, this effect is dramatic, giving rise to spontaneous chiral symmetry breaking and locking molecules into their chiral identity.

Interconversion-controlled liquid-liquid phase separation in a molecular chiral model.

Liquid-liquid phase separation of fluids exhibiting interconversion between alternative states has been proposed as an underlying mechanism for fluid polyamorphism and may be of relevance to the protein function and intracellular organization. However, molecular-level insight into the interplay between competing forces that can drive or restrict phase separation in interconverting fluids remains elusive. Here, we utilize an off-lattice model of enantiomers with tunable chiral interconversion and interaction properties to elucidate the physics underlying the stabilization and tunability of phase separation in fluids with interconverting states. We show that introducing an imbalance in the intermolecular forces between two enantiomers results in nonequilibrium, arrested phase separation into microdomains. We also find that in the equilibrium case, when all interaction forces are conservative, the growth of the phase domain is restricted only by the system size. In this case, we observe phase amplification, in which one of the two alternative phases grows at the expense of the other. These findings provide novel insights on how the interplay between dynamics and thermodynamics defines the equilibrium and steady-state morphologies of phase transitions in fluids with interconverting molecular or supramolecular states.

Combined molecular dynamics and neural network method for predicting protein antifreeze activity.

Antifreeze proteins (AFPs) are a diverse class of proteins that depress the kinetically observable freezing point of water. AFPs have been of scientific interest for decades, but the lack of an accurate model for predicting AFP activity has hindered the logical design of novel antifreeze systems. To address this, we perform molecular dynamics simulation for a collection of well-studied AFPs. By analyzing both the dynamic behavior of water near the protein surface and the geometric structure of the protein, we introduce a method that automatically detects the ice binding face of AFPs. From these data, we construct a simple neural network that is capable of quantitatively predicting experimentally observed thermal hysteresis from a trio of relevant physical variables. The model's accuracy is tested against data for 17 known AFPs and 5 non-AFP controls.

Advances in Computational Studies of the Liquid-Liquid Transition in Water and Water-Like Models.

There has been uninterrupted interest in supercooled water ever since the pioneering experiments of Speedy and Angell revealed sharp increases in this substance's response functions upon supercooling. One intriguing hypothesis that was formulated to explain this behavior involves the existence of a metastable liquid-liquid transition (LLT) at deeply supercooled conditions. The preponderance of experimental evidence is consistent with this hypothesis, although no definitive proof exists to date. Computational studies have played an important role in this area, because ice nucleation can in principle be controlled in silico. It has been claimed, controversially, that the LLT is a misinterpreted liquid-solid transition in all models of water. Recent studies disprove this viewpoint by providing unambiguous counter-examples of distinct liquid-liquid and liquid-crystal transitions in tetrahedral models. In one, state-of-the-art sampling methods were used to compute the free energy surface of a molecular model of water and revealed the existence of two liquid phases in metastable equilibrium with each other and a stable crystal phase, at the same, deeply supercooled thermodynamic conditions. Further studies showed that, by tuning the potential parameters of a model tetrahedral system, it is possible to make the LLT evolve continuously from metastability to being thermodynamically stable with respect to crystallization. Most recently, it has been shown that the simulation code used to challenge the hypothesis of an LLT contains conceptual errors that invalidate the results on which the challenge was based, definitively resolving the controversy. The debate has vastly expanded the range of fundamental questions being pursued about phase transitions in metastable systems and ushered the use of increasingly sophisticated computational methods to explore the possible existence of LLTs in model systems.

Metastable liquid-liquid transition in a molecular model of water.

Liquid water's isothermal compressibility and isobaric heat capacity, and the magnitude of its thermal expansion coefficient, increase sharply on cooling below the equilibrium freezing point. Many experimental, theoretical and computational studies have sought to understand the molecular origin and implications of this anomalous behaviour. Of the different theoretical scenarios put forward, one posits the existence of a first-order phase transition that involves two forms of liquid water and terminates at a critical point located at deeply supercooled conditions. Some experimental evidence is consistent with this hypothesis, but no definitive proof of a liquid-liquid transition in water has been obtained to date: rapid ice crystallization has so far prevented decisive measurements on deeply supercooled water, although this challenge has been overcome recently. Computer simulations are therefore crucial for exploring water's structure and behaviour in this regime, and have shown that some water models exhibit liquid-liquid transitions and others do not. However, recent work has argued that the liquid-liquid transition has been mistakenly interpreted, and is in fact a liquid-crystal transition in all atomistic models of water. Here we show, by studying the liquid-liquid transition in the ST2 model of water with the use of six advanced sampling methods to compute the free-energy surface, that two metastable liquid phases and a stable crystal phase exist at the same deeply supercooled thermodynamic condition, and that the transition between the two liquids satisfies the thermodynamic criteria of a first-order transition. We follow the rearrangement of water's coordination shell and topological ring structure along a thermodynamically reversible path from the low-density liquid to cubic ice. We also show that the system fluctuates freely between the two liquid phases rather than crystallizing. These findings provide unambiguous evidence for a liquid-liquid transition in the ST2 model of water, and point to the separation of time scales between crystallization and relaxation as being crucial for enabling it.

Computational investigation of surface freezing in a molecular model of water.

Water freezes in a wide variety of low-temperature environments, from meteors and atmospheric clouds to soil and biological cells. In nature, ice usually nucleates at or near interfaces, because homogenous nucleation in the bulk can only be observed at deep supercoolings. Although the effect of proximal surfaces on freezing has been extensively studied, major gaps in understanding remain regarding freezing near vapor-liquid interfaces, with earlier experimental studies being mostly inconclusive. The question of how a vapor-liquid interface affects freezing in its vicinity is therefore still a major open question in ice physics. Here, we address this question computationally by using the forward-flux sampling algorithm to compute the nucleation rate in a freestanding nanofilm of supercooled water. We use the TIP4P/ice force field, one of the best existing molecular models of water, and observe that the nucleation rate in the film increases by seven orders of magnitude with respect to bulk at the same temperature. By analyzing the nucleation pathway, we conclude that freezing in the film initiates not at the surface, but within an interior region where the formation of double-diamond cages (DDCs) is favored in comparison with the bulk. This, in turn, facilitates freezing by favoring the formation of nuclei rich in cubic ice, which, as demonstrated by us earlier, are more likely to grow and overcome the nucleation barrier. The films considered here are ultrathin because their interior regions are not truly bulk-like, due to their subtle structural differences with the bulk.

Effect of material flexibility on the thermodynamics and kinetics of hydrophobically induced evaporation of water.

The evaporation of water induced by confinement between hydrophobic surfaces has received much attention due to its suggested functional role in numerous biophysical phenomena and its importance as a general mechanism of hydrophobic self-assembly. Although much progress has been made in understanding the basic physics of hydrophobically induced evaporation, a comprehensive understanding of the substrate material features (e.g., geometry, chemistry, and mechanical properties) that promote or inhibit such transitions remains lacking. In particular, comparatively little research has explored the relationship between water's phase behavior in hydrophobic confinement and the mechanical properties of the confining material. Here, we report the results of extensive molecular simulations characterizing the rates, free energy barriers, and mechanism of water evaporation when confined between model hydrophobic materials with tunable flexibility. A single-order-of-magnitude reduction in the material's modulus results in up to a nine-orders-of-magnitude increase in the evaporation rate, with the corresponding characteristic time decreasing from tens of seconds to tens of nanoseconds. Such a modulus reduction results in a 24-orders-of-magnitude decrease in the reverse rate of condensation, with time scales increasing from nanoseconds to tens of millions of years. Free energy calculations provide the barriers to evaporation and confirm our previous theoretical predictions that making the material more flexible stabilizes the confined vapor with respect to liquid. The mechanism of evaporation involves surface bubbles growing/coalescing to form a subcritical gap-spanning tube, which then must grow to cross the barrier.

Effect of heterochiral inversions on the structure of a ß-hairpin peptide.

We study computationally a family of ß-hairpin peptides with systematically introduced chiral inversions, in explicit water, and we investigate the extent to which the backbone structure is able to fold in the presence of heterochiral perturbations. In contrast to the recently investigated case of a helical peptide, we do not find a monotonic change in secondary structure content as a function of the number of L- to D-inversions. The effects of L- to D-inversions are instead found to be highly position-specific. Additionally, in contrast to the helical peptide, some inversions increase the stability of the folded peptide: in such cases, we compute an increase in ß-sheet content in the aqueous solution equilibrium ensemble. However, the tertiary structures of the stable (folded) configurations for peptides for which inversions cause an increase in ß-sheet content show differences from one another, as well as from the native fold of the nonchirally perturbed ß-hairpin. Our results suggest that although some chiral perturbations can increase folding stability, chirally perturbed proteins may still underperform functionally, given the relationship between structure and function.

Low temperature protein refolding suggested by molecular simulation.

The function of critical biological materials, such as proteins, is intrinsically tied to their structure, and this structure is in turn heavily dependent on the properties of the solvent, most commonly water or dilute aqueous solutions. As water is known to exhibit anomalous properties, especially at supercooled temperatures, it is natural to ask how these properties might impact the thermodynamics of protein folding. To investigate this question, we use molecular simulation to explore the behavior of a model miniprotein, Trp-cage, as low as 70 K below the freezing point of the solvent at ambient pressure. Surprisingly, we find that while the expected cold denaturation of the protein is observed at moderate supercooling, further cooling to more than 55 K below the freezing point leads to cold refolding of the protein. Structural and hydrogen bonding analysis suggests that this refolding is driven by the desolvation of the protein's hydrophobic core, likely related to the pronounced decrease in density at this temperature. Beyond their intrinsic fundamental interest, these results have implications for cryomicroscopy and cryopreservation, where biological materials are often transiently subjected to these extreme conditions.