The freezing of water affects the processes that determine Earth's climate. Therefore, accurate weather and climate forecasts hinge on good predictions of ice nucleation rates. Such rate predictions are based on extrapolations using classical nucleation theory, which assumes that the structure of nanometre-sized ice crystallites corresponds to that of hexagonal ice, the thermodynamically stable form of bulk ice. However, simulations with various water models find that ice nucleated and grown under atmospheric temperatures is at all sizes stacking-disordered, consisting of random sequences of cubic and hexagonal ice layers. This implies that stacking-disordered ice crystallites either are more stable than hexagonal ice crystallites or form because of non-equilibrium dynamical effects. Both scenarios challenge central tenets of classical nucleation theory. Here we use rare-event sampling and free energy calculations with the mW water model to show that the entropy of mixing cubic and hexagonal layers makes stacking-disordered ice the stable phase for crystallites up to a size of at least 100,000 molecules. We find that stacking-disordered critical crystallites at 230 kelvin are about 14 kilojoules per mole of crystallite more stable than hexagonal crystallites, making their ice nucleation rates more than three orders of magnitude higher than predicted by classical nucleation theory. This effect on nucleation rates is temperature dependent, being the most pronounced at the warmest conditions, and should affect the modelling of cloud formation and ice particle numbers, which are very sensitive to the temperature dependence of ice nucleation rates. We conclude that classical nucleation theory needs to be corrected to include the dependence of the crystallization driving force on the size of the ice crystallite when interpreting and extrapolating ice nucleation rates from experimental laboratory conditions to the temperatures that occur in clouds.

From a hypothetical perfect dividing surface, all trajectories commit to opposite basins in forward and backward time without recrossing, transition state theory is exact, the transmission coefficient is one, and the committor distribution is perfectly focused at 1/2. However, chemical reactions in solution and other real systems often have dynamical trajectories that recross the dividing surface. To separate true dynamical effects from effects of a nonoptimal dividing surface, the dividing surface and/or reaction coordinate should be optimized before computing transmission coefficients. For NaCl dissociation in TIP3P water, we show that recrossing persists even when the 1/2-committor surface itself is used as the dividing surface, providing evidence that recrossing cannot be fully eliminated from the dynamics for any configurational coordinate. Consistent with this finding, inertial likelihood maximization finds a combination of ion-pair distance and two solvent coordinates that improves the committor distribution and increases the transmission coefficient relative to those for ion-pair distance alone, but recrossing is not entirely eliminated. Free energy surfaces for the coordinates identified by inertial likelihood maximization show that the intrinsic recrossing stems from anharmonicity and shallow intermediates that remain after dimensionality reduction to the dynamically important variables.

Cassandra is an open source atomistic Monte Carlo software package that is effective in simulating the thermodynamic properties of fluids and solids. The different features and algorithms used in Cassandra are described, along with implementation details and theoretical underpinnings to various methods used. Benchmark and example calculations are shown, and information on how users can obtain the package and contribute to it are provided. © 2017 Wiley Periodicals, Inc.

Translating sticky biological molecules-such as mussel foot proteins (MFPs)-into synthetic, cost-effective underwater adhesives with adjustable nano-and macroscale characteristics requires an intimate understanding of the glue's molecular interactions. To help facilitate the next generation of aqueous adhesives, we performed a combination of surface forces apparatus (SFA) measurements and replicaexchange molecular dynamics (REMD) simulations on a synthetic, easy to prepare, Dopa-containing peptide (MFP-3s peptide), which adheres to organic surfaces just as effectively as its wild-type protein analog. Experiments and simulations both show significant differences in peptide adsorption on CH 3 -terminated (hydrophobic) and OH-terminated (hydrophilic) self-assembled monolayers (SAMs), where adsorption is strongest on hydrophobic SAMs because of orientationally specific interactions with Dopa. Additional umbrella-sampling simulations yield free-energy profiles that quantitatively agree with SFA measurements and are used to extract the adhesive properties of individual amino acids within the context of MFP-3s peptide adhesion, revealing a delicate balance between van der Waals, hydrophobic, and electrostatic forces.mussel foot proteins | self-assembled monolayers | protein folding | molecular dynamics simulations | surface forces apparatus D emand for biologically inspired underwater adhesives, such as those secreted by marine mussels to adhere to a wide variety of hard and soft surfaces (1), have seen tremendous growth over the past decade, with applications to bone sealing (2), dental and medical transplants (3), coronary artery coatings (4), cell encapsulants (5), and other systems. To facilitate the construction of nextgeneration underwater adhesives, we can mimic existing biological glues-such as those containing mussel foot proteins (MFPs)-and translate the glues' structures to create biologically inspired synthetic adhesives (6). Doing so requires detailed knowledge of the molecular interactions that take place, many of which occur on length and time scales that are, at present, too small to be accurately characterized by experiments. Therefore, more sophisticated studies that combine theoretical modeling with state-of-the-art experiments are necessary for advancing the development of novel underwater adhesives.Although the mussel's talent for wet adhesion has been known for centuries, the true molecular understanding of adhesion began in 1952 with Brown's hypothesis that the mussel's byssus thread and adhesive plaques are comprised of intrinsically disordered proteins rich in the catecholic amino acid dopa (Dopa) (7). With knowledge of Dopa's binding ability, an abundance of Dopa-containing polymers were synthesized that displayed impressive adhesive (8, 9), coating (1, 4), structural (10, 11), and selfhealing (12, 13) properties. The surface forces apparatus (SFA) has been used to measure the adhesion of MFP-containing glues (1, 6, 14-17); however, it remains difficult to unambiguously identify individual or ...

We propose a method for identifying accurate reaction coordinates among a set of trial coordinates. The method applies to special cases where motion along the reaction coordinate follows a one-dimensional Smoluchowski equation. In these cases the reaction coordinate can predict its own short-time dynamical evolution, i.e., the dynamics projected from multiple dimensions onto the reaction coordinate depend only on the reaction coordinate itself. To test whether this property holds, we project an ensemble of short trajectory swarms onto trial coordinates and compare projections of individual swarms to projections of the ensemble of swarms. The comparison, quantified by the Kullback-Leibler divergence, is numerically performed for each isosurface of each trial coordinate. The ensemble of short dynamical trajectories is generated only once by sampling along an initial order parameter. The initial order parameter should separate the reactants and products with a free energy barrier, and distributions on isosurfaces of the initial parameter should be unimodal. The method is illustrated for three model free energy landscapes with anisotropic diffusion. Where exact coordinates can be obtained from Kramers-Langer-Berezhkovskii-Szabo theory, results from the new method agree with the exact results. We also examine characteristics of systems where the proposed method fails. We show how dynamical self-consistency is related (through the ChapmanKolmogorov equation) to the earlier isocommittor criterion, which is based on longer paths.