Direct Molecular Dynamics Simulation of Nucleation during Supersonic Expansion of Gas to a Vacuum

Novel barostat implementation for molecular dynamics

We propose a novel implementation of the extended-dynamics equations for isothermal-isobaric ensemble in molecular dynamics, as the Martyna-Tobias-Klein thermostat and barostat. This method is suitable for systems with constraints and the Verlet-family integrators. Instead of iterations or the Trotter-expansion-based methods, both velocities and box sizes (scaling of bond lengths) are predicted. The algorithm begins with force calculation, requiring neither quarter nor half time steps, and necessitating iterations only inside SHAKE. Several tests demonstrate that the quality is comparable to other implementations. It is found that the formula relating the extended barostat mass to the characteristic time of volume fluctuations is inaccurate for condensed systems, which has consequences for the parameter setup. Emphasis is also put on the verification of the precise isothermal-isobaric ensemble and finite-size effects.

Properties of water and argon clusters developed in supersonic expansions

Using adiabatic molecular dynamics coupled with the fluid dynamics equations, we model nucleation in an expanding beam of water vapor and argon on a microsecond scale. The size distribution of clusters, their temperature, and pickup cross sections in dependence on velocity are investigated and compared to the geometric cross sections and the experiment. The clusters are warmer than the expanding gas because of the time scale of relaxation processes. We also suggest that their translational and rotational kinetic energies are modified due to evaporative cooling. The pickup cross sections determined for the final clusters using molecules of the same kind increase with decreasing velocity, still obeying the (a+bN1/3)2 law.

Electron-induced fragmentation of water droplets: Simulation study

The transport of free electrons in a water environment is still poorly understood. We show that additional insight can be brought about by investigating fragmentation patterns of finite-size particles upon electron impact ionization. We have developed a composite protocol aiming to simulate fragmentation of water clusters by electrons with kinetic energies in the range of up to 100 eV. The ionization events for atomistically described molecular clusters are identified by a kinetic Monte Carlo procedure. We subsequently model the fragmentation with classical molecular dynamics simulations, calibrated by non-adiabatic quantum mechanics/molecular mechanics simulations of the ionization process. We consider one-electron ionizations, energy transfer via electronic excitation events, elastic scattering, and also the autoionization events through intermolecular Coulombic decay. The simulations reveal that larger water clusters are often ionized repeatedly, which is the cause of substantial fragmentation. After losing most of its energy, low-energy electrons further contribute to fragmentation by electronic excitations. The simultaneous measurement of cluster size distribution before and after the ionization represents a sensitive measure of the energy transferred into the system by an incident electron.

Molecular Dynamics of Heterogeneous Systems on GPUs and Their Application to Nucleation in Gas Expanding to a Vacuum

Expansion of water vapor through a small orifice to a vacuum produces liquid or frozen clusters which in the experiment serve as model particles for atmospheric aerosols. Yet, there are controversies about the shape of these clusters, suggesting that the nucleation process is not fully understood. Such questions can be answered by molecular dynamics simulations; however, they require microsecond-scale runs with thousands of molecules and accurate energy conservation. The available highly parallel codes typically utilize domain decomposition and are inefficient for heterogeneous systems as clusters in a dilute gas. In this work, we present an implementation of molecular dynamics on graphics processing units based on the Verlet list and apply it to several systems for which experimental data are available. We reproduce sufficiently sized clusters but not the experimentally observed clusters of irregular shape.