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.

Binary salt structure classification with convolutional neural networks: Application to crystal nucleation and melting point calculations.

Convolutional neural networks are constructed and validated for the crystal structure classification of simple binary salts such as the alkali halides. The inputs of the neural network classifiers are the local bond orientational order parameters of Steinhardt, Nelson, and Ronchetti [Phys. Rev. B 28, 784 (1983)], which are derived solely from the relative positions of atoms surrounding a central reference atom. This choice of input gives classifiers that are invariant to density, increasing their transferability. The neural networks are trained and validated on millions of data points generated from a large set of molecular dynamics (MD) simulations of model alkali halides in nine bulk phases (liquid, rock salt, wurtzite, CsCl, 5-5, sphalerite, NiAs, AntiNiAs, and ß-BeO) across a range of temperatures. One-dimensional time convolution is employed to filter out short-lived structural fluctuations. The trained neural networks perform extremely well, with accuracy up to 99.99% on a balanced validation dataset constructed from millions of labeled bulk phase structures. A typical analysis using the neural networks, including neighbor list generation, order parameter calculation, and class inference, is computationally inexpensive compared to MD simulations. As a demonstration of their accuracy and utility, the neural network classifiers are employed to follow the nucleation and crystal growth of two model alkali halide systems, crystallizing into distinct structures from the melt. We further demonstrate the classifiers by implementing them in automated MD melting point calculations. Melting points for model alkali halides using the most commonly employed rigid-ion interaction potentials are reported and discussed.

Influence of pH on Ice Nucleation by Kaolinite: Experiments and Molecular Simulations.

In mixed-phase or ice clouds, ice can be formed through heterogeneous nucleation. A major type of ice-nucleating particle (INP) in the atmosphere are mineral dust particles. For mixed-phase clouds, the pH of water droplets can vary widely and influence ice nucleation by altering the surface of some INPs, including mineral dust. Kaolinite is a commonly occurring clay mineral, and laboratory experiments, as well as molecular dynamics (MD) simulations, have demonstrated its ice-nucleating efficiency at neutral pH. We examine the influence of pH on the ice-nucleating efficiency of kaolinite, in the immersion freezing mode, through both droplet freezing experiments and MD simulations. Droplet freezing experiments using KGa-1b kaolinite samples are reported under both acidic (HNO3 solutions) and basic (NaOH solutions) conditions, covering the measured pH range 0.18-13.26. These experiments show that the ice-nucleating efficiency of kaolinite is not significantly influenced by the presence of acid but is reduced in extremely basic conditions. We report MD simulations aimed at gaining a microscopic understanding of the pH dependence of ice nucleation by kaolinite. The Al(001), Si(001), and three edge surfaces of kaolinite are considered, but ice nucleation was observed only for the Al(001) surface. The hydroxy groups exposed on the Al(001) surface can be deprotonated in a basic solution or dual-protonated in an acidic solution, which can influence ice nucleation efficiency. The protonation state of the Al(001) surface for a particular pH can be estimated using previously measured pKa values. We find that the monoprotonated Al(001) surface expected to be stable at near-neutral pH is the most effective ice-nucleating surface. In MD simulations, the ice nucleation efficiency persists for dual-protonation but decreases significantly with increasing deprotonation, qualitatively consistent with the experimental observations. Taken together, our experimental and MD results for a wide range of pH values support the suggestion that the Al(001) surface may be important for ice nucleation by kaolinite. Additionally, the deprotonation of hydroxy groups on INP surfaces can have a significant effect on their ice-nucleating ability.

Analysis of the relative stability of lithium halide crystal structures: Density functional theory and classical models.

All lithium halides exist in the rock salt crystal structure under ambient conditions. In contrast, common lithium halide classical force fields more often predict wurtzite as the stable structure. This failure of classical models severely limits their range of application in molecular simulations of crystal nucleation and growth. Employing high accuracy density functional theory (DFT) together with classical models, we examine the relative stability of seven candidate crystal structures for lithium halides. We give a detailed examination of the influence of DFT inputs, including the exchange-correlation functional, basis set, and dispersion correction. We show that a high-accuracy basis set, along with an accurate description of dispersion, is necessary to ensure prediction of the correct rock salt structure, with lattice energies in good agreement with the experiment. We also find excellent agreement between the DFT-calculated rock salt lattice parameters and experiment when using the TMTPSS-rVV10 exchange-correlation functional and a large basis set. Detailed analysis shows that dispersion interactions play a key role in the stability of rock salt over closely competing structures. Hartree-Fock calculations, where dispersion interactions are absent, predict the rock salt structure only for LiF, while LiCl, LiBr, and LiI are more stable as wurtzite crystals, consistent with radius ratio rules. Anion-anion second shell dispersion interactions overcome the radius ratio rules to tip the structural balance to rock salt. We show that classical models can be made qualitatively correct in their structural predictions by simply scaling up the pairwise additive dispersion terms, indicating a pathway toward better lithium halide force fields.

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.

Simulations of water structure and the possibility of ice nucleation on selected crystal planes of K-feldspar.

Molecular dynamics simulations are employed to investigate the structure of supercooled water (230 K) in contact with the (001), (010), and (100) surfaces of potassium feldspar (K-feldspar) in the microcline phase. Experimentally, K-feldspar and other feldspar minerals are known to be good ice-nucleating agents, which play a significant role in atmospheric science. Therefore, a principal purpose of this work is to evaluate the possibility that the K-feldspar surfaces considered could serve as likely sites for ice nucleation. The (001) and (010) surfaces were selected for study because they are perfect cleavage planes of feldspar, with (001) also being an easy cleavage plane. The (100) surface is considered because some experiments have suggested that it is involved in ice nucleation. Feldspar is modeled with the widely used CLAYFF force field, and the TIP4P/Ice model is employed for water. We do not observe ice nucleation on any of the K-feldspar surfaces considered; moreover, the density profiles and the structure of water near these surfaces do not exhibit any particularly icelike features. Our simulations indicate that these surfaces of K-feldspar are likely not responsible for its excellent ice nucleating ability. This suggests that one must look elsewhere, possibly at water-induced surface rearrangements or some other "defect" structure, for an explanation of ice nucleation by K-feldspar.

Structural behavior of aqueous t-butanol solutions from large-scale molecular dynamics simulations.

Large-scale molecular dynamics simulations are reported for aqueous t-butanol (TBA) solutions. The CHARMM generalized force field (CGenFF) for TBA is combined with the TIP4P/2005 model for water. Unlike many other common TBA models, the CGenFF model is miscible with water in all proportions at 300 K. The main purpose of this work is to investigate the existence and nature of a microheterogeneous structure in aqueous TBA solutions. Our simulations of large systems (128 000 and 256 000 particles) at TBA mole fractions of 0.06 and 0.1 clearly reveal the existence of long-range correlations (>10 nm) that show significant variations on long time scales (∼50 ns). We associate these long-range slowly varying correlations with the existence of supramolecular domainlike structures that consist of TBA-rich and water-rich regions. This structure is always present but continually changing in time, giving rise to long-range slowly varying pair correlation functions. We find that this behavior appears to have little influence on the single particle dynamics; the diffusion coefficients of both TBA and water molecules lie in the usual liquid state regime, and mean square displacements provide no indication of anomalous diffusion. Using our large system simulations, we are able to reliably calculate small angle x-ray scattering and small angle neutron scattering spectra, except at a very low wave vector, and the results agree well with recent experiments. However, this paper shows that simulation of the relatively simple TBA/water system remains challenging. This is particularly true if one wishes to obtain properties such as Kirkwood-Buff factors, or scattering functions at a low wave vector, which strongly depend on the long-range behavior of the pair correlations.

The influence of ion hydration on nucleation and growth of LiF crystals in aqueous solution.

Molecular dynamics (MD) simulations are employed to investigate crystal nucleation and growth in oversaturated aqueous LiF solutions. Results obtained for a range of temperatures provide evidence that the rate of crystal growth is determined by a substantial energy barrier (∼49 kJ mol-1) related to the loss of water from the ion hydration shells. Employing direct MD simulations, we do not observe spontaneous nucleation of LiF crystals at 300 K, but nucleation is easily observable in NVT simulations at 500 K. This contrasts with the NaCl case, where crystal nucleation is directly observed in similar simulations at 300 K. Based on these observations, together with a detailed analysis of ion clustering in metastable LiF solutions, we argue that the ion dehydration barrier also plays a key role in crystal nucleation. The hydration of the relatively small Li+ and F- ions strongly influences the probability of forming large, crystal-like ion clusters, which are a necessary precursor to nucleation. This important factor is not accounted for in classical nucleation theory.

Mechanism of Urea Crystal Dissolution in Water from Molecular Dynamics Simulation.

Molecular dynamics simulations are used to determine the mechanism of urea crystal dissolution in water under sink conditions. Crystals of cubic and tablet shapes are considered, and results are reported for four commonly used water models. The dissolution rates for different water models can differ considerably, but the overall dissolution mechanism remains the same. Urea dissolution occurs in three stages: a relatively fast initial stage, a slower intermediate stage, and a final stage. We show that the long intermediate stage is well described by classical rate laws, which assume that the dissolution rate is proportional to the active surface area. By carrying out simulations at different temperatures, we show that urea dissolution is an activated process, with an activation energy of ∼32 kJ mol-1. Our simulations give no indication of a significant diffusion layer, and we conclude that the detachment of molecules from the crystal is the rate-determining step for dissolution. The results we report for urea are consistent with earlier observations for the dissolution of NaCl crystals. This suggests that the three-stage mechanism and classical rate laws might apply to the dissolution of other ionic and molecular crystals.

Comparison of simulation and experimental results for a model aqueous tert-butanol solution.

Molecular dynamics simulations are used to investigate the behavior of aqueous tert-butanol (TBA) solutions for a range of temperatures, using the CHARMM generalized force field (CGenFF) to model TBA and the TIP4P/2005 or TIP4P-Ew water model. Simulation results for the density, isothermal compressibility, constant pressure heat capacity, and self-diffusion coefficients are in good accord with experimental measurements. Agreement with the experiment is particularly good at low TBA concentration, where experiments have revealed anomalies in a number of thermodynamic properties. Importantly, the CGenFF model does not exhibit liquid-liquid demixing at temperatures between 290 and 320 K (for systems of 32 000 molecules), in contrast with the situation for several other common TBA models [R. Gupta and G. N. Patey, J. Chem. Phys. 137, 034509 (2012)]. However, whereas real water and TBA are miscible at all temperatures where the liquid is stable, we observe some evidence of demixing at 340 K and above. To evaluate the structural properties at low concentrations, we compare with both neutron scattering and recent spectroscopic measurements. This reveals that while the CGenFF model is a definite improvement over other models that have been considered, the TBA molecules still exhibit a tendency to associate at low concentrations that is somewhat stronger than that indicated by experiments. Finally, we discuss the range and decay times of the long-range correlations, providing an indication of the system size and simulation times that are necessary in order to obtain reliable results for certain properties.

Crystal structures of model lithium halides in bulk phase and in clusters.

We employ lattice energy calculations and molecular dynamics simulations to compare the stability of wurtzite and rock salt crystal structures of four lithium halides (LiF, LiCl, LiBr, and LiI) modeled using the Tosi-Fumi and Joung-Cheatham potentials, which are models frequently used in simulation studies. Both infinite crystals and finite clusters are considered. For the Tosi-Fumi model, we find that all four salts prefer the wurtzite structure both at 0 K and at finite temperatures, in disagreement with experiments, where rock salt is the stable structure and wurtzite exists as a metastable state. For Joung-Cheatham potentials, rock salt is more stable for LiF and LiCl, but the wurtzite structure is preferred by LiBr and LiI. It is clear that the available lithium halide force fields need improvement to bring them into better accord with the experiment. Finite-size clusters that are more stable as rock salt in the bulk phase tend to solidify as small rock salt crystals. However, small clusters of salts that prefer the wurtzite structure as bulk crystals tend to form structures that have hexagonal motifs, but are not finite-size wurtzite crystals. We show that small wurtzite structures are unstable due to the presence of a dipole and rearrange into more stable, size-dependent structures. We also show that entropic contributions can act in favor of the wurtzite structure at higher temperatures. The possible relevance of our results for simulation studies of crystal nucleation from melts and/or aqueous solutions is discussed.

A molecular dynamics investigation of the influence of water structure on ion conduction through a carbon nanotube.

Molecular dynamics simulations are employed to investigate pressure-driven water and ion transport through a (9,9) carbon nanotube (CNT). We consider NaCl solutions modeled with both the TIP3P and TIP4P/2005 water models. Concentrations range from 0.25 to 2.8 mol l-1 and temperatures from 260 to 320 K are considered. We discuss the influences on flow rates of continuum hydrodynamic considerations and molecular structural effects. We show that the flow rate of water, sodium, and chloride ions through the CNT is strongly model dependent, consistent with earlier simulations of pure water conduction. To remove the effects of different water flow rates, and clearly expose the influence of other factors on ion flow, we calculate ion transport efficiencies. Ion transport efficiencies are much smaller for TIP4P/2005 solutions than for those using the TIP3P model. Particularly at lower temperatures, the ion transport efficiencies for the TIP4P/2005 model are small, despite the fact that the nanotube conducts water at a significant rate. We trace the origin of small ion transport efficiencies to the presence of ring-like water structures within the CNT. Such structures occur commonly for the TIP4P/2005 model, but less frequently for TIP3P. The water structure acts to reduce ion "solvation" within the CNT, posing an additional barrier to ion entry and transport. Our results demonstrate that increasing the water structure within the CNT by decreasing the temperature strongly inhibits ion conduction, while still permitting significant water transport.

Birth of NaCl Crystals: Insights from Molecular Simulations.

Molecular dynamics simulations are used to investigate the factors that influence the nucleation of NaCl crystals in a supersaturated aqueous solution. We describe a methodology for detecting solidlike NaCl clusters (potential nuclei) and following their evolution in time until they achieve nucleation (which is very rare) or dissolve back into solution. Through an analysis of cluster lifetimes and multiple nucleation events, we demonstrate that cluster size is not the only property that influences cluster stability and the probability of achieving nucleation. We introduce a parameter called cluster crystallinity, which is a measure of the solidlike order in a particular cluster. We show that cluster order (as measured by this parameter) has a strong influence on the lifetime and nucleation probability of clusters of equal sizes, with the lifetime and probability of nucleation increasing with increasing crystallinity. These observations remain true for clusters as small as six ions, showing that the structural factors are important even at the earliest stages of crystal birth.

Simulated conduction rates of water through a (6,6) carbon nanotube strongly depend on bulk properties of the model employed.

We investigate pressure driven flow rates of water through a (6,6) carbon nanotube (CNT) for the TIP3P, SPC/E, and TIP4P/2005 water models. The flow rates are shown to be strongly model dependent, differing by factors that range from ∼6 to ∼2 as the temperature varies from 260 to 320 K, with TIP3P showing the fastest flow and TIP4P/2005 the slowest. For the (6,6) CNT, the size constraint allows only single-file conduction for all three water models. Hence, unlike the situation for the larger [(8,8) and (9,9)] CNTs considered in our earlier work [L. Liu and G. N. Patey, J. Chem. Phys. 141, 18C518 (2014)], the different flow rates cannot be attributed to different model-dependent water structures within the nanotubes. By carefully examining activation energies, we trace the origin of the model discrepancies for the (6,6) CNT to differing rates of entry into the nanotube, and these in turn are related to differing bulk mobilities of the water models. Over the temperature range considered, the self-diffusion coefficients of the TIP3P model are much larger than those of TIP4P/2005 and those of real water. Additionally, we show that the entry rates are approximately inversely proportional to the shear viscosity of the bulk liquid, in agreement with the prediction of continuum hydrodynamics. For purposes of comparison, we also consider the larger (9,9) CNT. In the (9,9) case, the flow rates for the TIP3P model still appear to be mainly controlled by the entry rates. However, for the SPC/E and TIP4P/2005 models, entry is no longer the rate determining step for flow. For these models, the activation energies controlling flow are considerably larger than the energetic barriers to entry, due in all likelihood to the ring-like water clusters that form within the larger nanotube.

Simulations of Ice Nucleation by Model AgI Disks and Plates.

Silver iodide is one of the most effective ice nuclei known. We use molecular dynamics simulations to investigate ice nucleation by AgI disks and plates with radii ranging from 1.15 to 2.99 nm. It is shown that disks and plates in this size range are effective ice nuclei, nucleating bulk ice at temperatures as warm as 14 K below the equilibrium freezing temperature, on simulation time scales (up to a few hundred nanoseconds). Ice nucleated on the Ag exposed surface of AgI disks and plates. Shortly after supercooling an ice cluster forms on the AgI surface. The AgI-stabilized ice cluster fluctuates in size as time progresses, but, once formed, it is constantly present. Eventually, depending on the disk or plate size and the degree of supercooling, a cluster fluctuation achieves critical size, and ice nucleates and rapidly grows to fill the simulation cell. Larger AgI disks and plates support larger ice clusters and hence can nucleate ice at warmer temperatures. This work may be useful for understanding the mechanism of ice nucleation on nanoparticles and active sites of larger atmospheric particles.

Simulations of Ice Nucleation by Kaolinite (001) with Rigid and Flexible Surfaces.

Nucleation of ice by airborne particles is a process vital to weather and climate, yet our understanding of the mechanisms underlying this process is limited. Kaolinite is a clay that is a significant component of airborne particles and is an effective ice nucleus. Despite receiving considerable attention, the microscopic mechanism(s) by which kaolinite nucleates ice is not known. We report molecular dynamics simulations of heterogeneous ice nucleation by kaolinite (001) surfaces. Both the Al-surface and the Si-surface nucleate ice. For the Al-surface, reorientation of the surface hydroxyl groups is essential for ice nucleation. This flexibility allows the Al-surface to adopt a structure which is compatible with hexagonal ice, Ih, at the atomic level. On the rigid Si-surface, ice nucleates via an unusual structure that consists of an ordered arrangement of hexagonal and cubic ice layers, joined at their basal planes where the interfacial energy cost is low. This ice structure provides a good match to the atomistic structure of the Si-surface. This example is important and may have far-reaching implications because it demonstrates that potential ice nuclei need not be good atomic-level matches to particular planes of ice Ih or cubic ice, Ic. It suggests that surfaces can act as effective ice nuclei by matching one of the much larger set of planes that can be constructed by regular arrangements of hexagonal and cubic ice.

Fluctuations and local ice structure in model supercooled water.

Large-scale simulations (up to 32,000 molecules) are used to analyze local structures and fluctuations for the TIP4P/2005 and TIP5P water models, under deeply supercooled conditions, near previously proposed liquid-liquid critical points. Bulk freezing does not occur in our simulations, but correlations between molecules with local ice-like structure (ice-like molecules) are strong and long ranged (∼4 nm), exceeding the shortest dimension of smaller simulation cells at the lowest temperatures considered. Correlations between ice-like molecules decay slowly at low temperature, on the order of a hundred nanoseconds. Local ice-like structure is strongly correlated with highly tetrahedral liquid structure at all times, both structures contribute to density fluctuations, and to the associated anomalous scattering. For the TIP4P/2005 and TIP5P models, we show that the apparent spontaneous liquid-liquid phase separations, recently reported [T. Yagasaki, M. Matsumoto, and H. Tanaka, Phys. Rev. E 89, 020301 (2014)] for small rectangular simulation cells below the proposed critical points, exhibit strong system size dependence and do not occur at all in the largest systems we consider. Furthermore, in the smaller rectangular systems where layers of different densities do occur, we find that the appearance of a region of low density is always accompanied simultaneously by an excess of local ice density, with no separation in time. Our results suggest that the density differences observed in direct simulations for the two models considered here are likely due to long-range correlations between ice-like molecules and do not provide strong evidence of liquid-liquid phase separation.

Melting point trends and solid phase behaviors of model salts with ion size asymmetry and distributed cation charge.

The melting point trends of model salts composed of coarse grain ions are examined using NPT molecular dynamics simulations. The model salts incorporate ion size asymmetry and distributed cation charge, which are two common features in ionic liquids. A series of single-phase and two-phase simulations are done at set temperatures with 50 K intervals for each salt, and the normal melting point is estimated within 50 K. The melting point trends are then established relative to a charge-centered, size symmetric salt with a normal melting point between 1250 K and 1300 K. We consider two sets of size asymmetric salts with size ratios up to 3:1; the melting point trends are different in each set. The lowest melting point we find is between 450 K and 500 K, which is a reduction of over 60% from the charge-centered, size symmetric case. In both sets, we find diversity in the solid phase structures. For all size ratios with small cation charge displacements, the salts crystallize with orientationally disordered cations. When the partial cation charge is far enough off-center in salts with ion size ratios near 1:1, the salts can become trapped in glassy states and have underlying crystal structures that are orientationally ordered. At ion size ratios near 3:1, the salts with large cation charge displacements show premelting transitions at temperatures as low as 300 K. After the premelting transition, these salts exist either as fast ion conductors, where the smaller anions move through a face centered cubic (fcc) cation lattice, or as plastic crystals, where ion pairs rotate on a fcc lattice.

Molecular dynamics simulation of NaCl dissolution.

Molecular dynamics simulations are used to investigate the dissolution of NaCl nanocrystals (containing ∼2400 ions) in water. We focus on systems under sink conditions at 300 K, but the influences of concentration and temperature are also investigated. Cubical, spherical, tablet-shaped, and rod-shaped nanocrystals are considered, and it is shown that the initial shape can influence the dissolution process. Dissolution is observed to occur in three stages: an initial period where the most exposed ions are removed from the crystal surface, and the crystal takes on a solution-annealed shape which persists throughout the second stage of dissolution; a second long intermediate stage where dissolution roughly follows a fixed rate law; and a final stage where the small residual crystal (≲200 ions) dissolves at an ever increasing rate until it disappears. The second stage of dissolution which applies for most of the dissolution process is well described by classical rate equations which simply assume that the dissolution rate is proportional to an active surface area from which ions are most easily detached from the crystal. The active area depends on the initial crystal shape. We show that for our model NaCl nanocrystals the rate-determining step for dissolution under sink conditions is ion detachment from the crystal, and that diffusion layers do not exist for these systems.

Simulations of water transport through carbon nanotubes: how different water models influence the conduction rate.

The conduction rate of water through (8,8) and (9,9) carbon nanotubes at 300 K and a pressure difference of 220 MPa is investigated using molecular dynamics simulations. The TIP3P, SPC/E, and TIP4P/2005 water models are considered. The pressure-driven flow rate is found to be strongly model dependent for both nanotubes. The fastest model (TIP3P) has a flow rate that is approximately five times faster than the slowest (TIP4P/2005). It is shown that the flow rate is significantly influenced by the structure taken on by the water molecules confined in the nanotube channels. The slower models, TIP4P/2005 and SPC/E, tend to favor stacked ring arrangements, with the molecules of a ring moving together through the nanotube, in what we term a "cluster-by-cluster" conduction mode. Confined TIP3P water has a much weaker tendency to form ring structures, and those that do form are fragile and break apart under flow conditions. This creates a much faster "diffusive" conduction mode where the water molecules mainly move through the tube as individual particles, rather than as components of a larger cluster. Our results demonstrate that water models developed to describe the properties of bulk water can behave very differently in confined situations.