The kinetics of the ice-water interface from ab initio machine learning simulations.

Molecular simulations employing empirical force fields have provided valuable knowledge about the ice growth process in the past decade. The development of novel computational techniques allows us to study this process, which requires long simulations of relatively large systems, with ab initio accuracy. In this work, we use a neural-network potential for water trained on the revised Perdew-Burke-Ernzerhof functional to describe the kinetics of the ice-water interface. We study both ice melting and growth processes. Our results for the ice growth rate are in reasonable agreement with previous experiments and simulations. We find that the kinetics of ice melting presents a different behavior (monotonic) than that of ice growth (non-monotonic). In particular, a maximum ice growth rate of 6.5 Å/ns is found at 14 K of supercooling. The effect of the surface structure is explored by investigating the basal and primary and secondary prismatic facets. We use the Wilson-Frenkel relation to explain these results in terms of the mobility of molecules and the thermodynamic driving force. Moreover, we study the effect of pressure by complementing the standard isobar with simulations at a negative pressure (-1000 bar) and at a high pressure (2000 bar). We find that prismatic facets grow faster than the basal one and that pressure does not play an important role when the speed of the interface is considered as a function of the difference between the melting temperature and the actual one, i.e., to the degree of either supercooling or overheating.

Minimum in the pressure dependence of the interfacial free energy between ice Ih and water.

Despite the importance of ice nucleation, this process has been barely explored at negative pressures. Here, we study homogeneous ice nucleation in stretched water by means of molecular dynamics seeding simulations using the TIP4P/Ice model. We observe that the critical nucleus size, interfacial free energy, free energy barrier, and nucleation rate barely change between isobars from -2600 to 500 bars when they are represented as a function of supercooling. This allows us to identify universal empirical expressions for homogeneous ice nucleation in the pressure range from -2600 to 500 bars. We show that this universal behavior arises from the pressure dependence of the interfacial free energy, which we compute by means of the mold integration technique, finding a shallow minimum around -2000 bars. Likewise, we show that the change in the interfacial free energy with pressure is proportional to the excess entropy and the slope of the melting line, exhibiting in the latter a reentrant behavior also at the same negative pressure. Finally, we estimate the excess internal energy and the excess entropy of the ice Ih-water interface.

Escape dynamics of active particles in multistable potentials.

Rare transitions between long-lived metastable states underlie a great variety of physical, chemical and biological processes. Our quantitative understanding of reactive mechanisms has been driven forward by the insights of transition state theory and in particular by Kramers' dynamical framework. Its predictions, however, do not apply to systems that feature non-conservative forces or correlated noise histories. An important class of such systems are active particles, prominent in both biology and nanotechnology. Here, we study the active escape dynamics of a silica nanoparticle trapped in a bistable potential. We introduce activity by applying an engineered stochastic force that emulates self-propulsion. Our experiments, supported by a theoretical analysis, reveal the existence of an optimal correlation time that maximises the transition rate. We discuss the origins of this active turnover, reminiscent of the much celebrated Kramers turnover. Our work establishes a versatile experimental platform to study single particle dynamics in non-equilibrium settings.

Theoretical Prediction of Thermal Polarization.

We present a mean-field theory to explain the thermo-orientation effect in an off-center Stockmayer fluid. This effect is the underlying cause of thermally induced polarization and thermally induced monopoles, which have recently been predicted theoretically. Unlike previous theories that are based either on phenomenological equations or on scaling arguments, our approach does not require any fitting parameters. Given an equation of state and assuming local equilibrium, we construct an effective Hamiltonian for the computation of local Boltzmann averages. This simple theoretical treatment predicts molecular orientations that are in very good agreement with simulation results for the range of dipole strengths investigated. By decomposing the overall alignment into contributions from the temperature and density gradients, we shed further light on how the nonequilibrium result arises from the competition between the two gradients.

Pathways to self-organization: Crystallization via nucleation and growth.

Crystallization, a prototypical self-organization process during which a disordered state spontaneously transforms into a crystal characterized by a regular arrangement of its building blocks, usually proceeds by nucleation and growth. In the initial stages of the transformation, a localized nucleus of the new phase forms in the old one due to a random fluctuation. Most of these nuclei disappear after a short time, but rarely a crystalline embryo may reach a critical size after which further growth becomes thermodynamically favorable and the entire system is converted into the new phase. In this article, we will discuss several theoretical concepts and computational methods to study crystallization. More specifically, we will address the rare event problem arising in the simulation of nucleation processes and explain how to calculate nucleation rates accurately. Particular attention is directed towards discussing statistical tools to analyze crystallization trajectories and identify the transition mechanism.

Non-equilibrium simulations of thermally induced electric fields in water.

Using non-equilibrium molecular dynamics simulations, it has been recently demonstrated that water molecules align in response to an imposed temperature gradient, resulting in an effective electric field. Here, we investigate how thermally induced fields depend on the underlying treatment of long-ranged interactions. For the short-ranged Wolf method and Ewald summation, we find the peak strength of the field to range between 2 × 10(7) and 5 × 10(7) V/m for a temperature gradient of 5.2 K/Å. Our value for the Wolf method is therefore an order of magnitude lower than the literature value [J. A. Armstrong and F. Bresme, J. Chem. Phys. 139, 014504 (2013); J. Armstrong et al., J. Chem. Phys. 143, 036101 (2015)]. We show that this discrepancy can be traced back to the use of an incorrect kernel in the calculation of the electrostatic field. More seriously, we find that the Wolf method fails to predict correct molecular orientations, resulting in dipole densities with opposite sign to those computed using Ewald summation. By considering two different multipole expansions, we show that, for inhomogeneous polarisations, the quadrupole contribution can be significant and even outweigh the dipole contribution to the field. Finally, we propose a more accurate way of calculating the electrostatic potential and the field. In particular, we show that averaging the microscopic field analytically to obtain the macroscopic Maxwell field reduces the error bars by up to an order of magnitude. As a consequence, the simulation times required to reach a given statistical accuracy decrease by up to two orders of magnitude.

An enhanced version of the heat exchange algorithm with excellent energy conservation properties.

We propose a new algorithm for non-equilibrium molecular dynamics simulations of thermal gradients. The algorithm is an extension of the heat exchange algorithm developed by Hafskjold et al. [Mol. Phys. 80, 1389 (1993); 81, 251 (1994)], in which a certain amount of heat is added to one region and removed from another by rescaling velocities appropriately. Since the amount of added and removed heat is the same and the dynamics between velocity rescaling steps is Hamiltonian, the heat exchange algorithm is expected to conserve the energy. However, it has been reported previously that the original version of the heat exchange algorithm exhibits a pronounced drift in the total energy, the exact cause of which remained hitherto unclear. Here, we show that the energy drift is due to the truncation error arising from the operator splitting and suggest an additional coordinate integration step as a remedy. The new algorithm retains all the advantages of the original one whilst exhibiting excellent energy conservation as illustrated for a Lennard-Jones liquid and SPC/E water.

Dynamical phases of attractive particles sliding on a structured surface.

Inspired by experiments on quartz crystal microbalance setups, we study the mobility of a monolayer of Lennard-Jones particles driven over a hexagonal external potential. We pay special attention to the changes in the dynamical phases that arise when the lattice constant of the external substrate potential and the Lennard-Jones interaction are mismatched. We find that if the average particle separation is such that the particles repel each other, or interact harmonically, the qualitative behavior of the system is akin to that of a monolayer of purely repulsive Yukawa particles. On the other hand, if the particles typically attract each other, the ensuing dynamical states are determined entirely by the relative strength of the Lennard-Jones interaction with respect to that of the external potential.

A proof of Jarzynski's nonequilibrium work theorem for dynamical systems that conserve the canonical distribution.

We present a derivation of the Jarzynski [Phys. Rev. Lett. 78, 2690 (1997)] identity and the Crooks [J. Stat. Phys. 90, 1481 (1998)] fluctuation theorem for systems governed by deterministic dynamics that conserves the canonical distribution such as Hamiltonian dynamics, Nose-Hoover dynamics, Nose-Hoover chains, and Gaussian isokinetic dynamics. The proof is based on a relation between the heat absorbed by the system during the nonequilibrium process and the Jacobian of the phase flow generated by the dynamics.

Field-dependent collision frequency of the two-dimensional driven random Lorentz gas.

In the field-driven, thermostated Lorentz gas the collision frequency increases with the magnitude of the applied field due to long-time correlations. We study this effect with computer simulations and confirm the presence of nonanalytic terms in the field dependence of the collision rate as predicted by kinetic theory.

Autoionization in liquid water.

The dissociation of a water molecule in liquid water is the fundamental event in acid-base chemistry, determining the pH of water. Because of the short time scales and microscopic length scales involved, the dynamics of this autoionization have not been directly probed by experiment. Here, the autoionization mechanism is revealed by sampling and analyzing ab initio molecular dynamics trajectories. We identify the rare fluctuations in solvation energies that destabilize an oxygen-hydrogen bond. Through the transfer of protons along a hydrogen bond "wire," the nascent ions separate by three or more neighbors. If the hydrogen bond wire connecting the two ions is subsequently broken, a metastable charge-separated state is visited. The ions may then diffuse to large separations. If, however, the hydrogen bond wire remains unbroken, the ions recombine rapidly. Because of their concomitant large electric fields, the transient ionic species produced in this case may provide an experimentally detectable signal of the dynamics we report.

Finite-precision stationary states at and away from equilibrium

We study the precision dependence of equilibrium and nonequilibrium phase-space distribution functions for time-reversible dynamical systems simulated with finite, computational precision. The conservative and dissipative cases show different behavior, with substantially reduced period lengths in the dissipative case. The main effect of finite precision is to change the phase-space fraction occupied by the distributions. The convergence of thermodynamic averages is only slightly affected. We introduce and discuss a simple stochastic model which is nicely consistent with all of our numerical results. This model links the length of periodic orbits to the strange attractor's correlation dimension.

Reaction coordinates of biomolecular isomerization.

Transition path sampling has been applied to the molecular dynamics of the alanine dipeptide in vacuum and in aqueous solution. The analysis shows that more degrees of freedom than the traditional dihedral angles, phi and psi, are necessary to describe the reaction coordinates for isomerization of this molecule. In vacuum, an additional dihedral angle is identified as significant. In solution, solvent variables are shown to play a significant role, and this role appears to be more specific than can be captured by friction models. Implications for larger molecules are discussed.