A trapping mechanism for propelled colloidal particles based on an inhomogeneous drive is presented and studied by means of computer simulations. In experiments this method can be realized using photophoretic Janus particles driven by a light source,
which shines through a shading mask and leads to an accumulation of the particles in the passive part. An equation for an accumulation parameter is derived using the effective inhomogeneous diffusion constant generated by the inhomogeneous drive. The impact of particle interaction on the trapping mechanism is studied, as well as the interplay between passivity-induced trapping and the emergent self-clustering of systems containing a high density of active particles. The combination of both effects makes the clusters more controllable for applications.
While the self-learning kinetic Monte Carlo (SLKMC) method enables the calculation of transition rates from a realistic potential, implementations of it were usually limited to one specific surface orientation. An example is the fcc (111) surface in
Latz et al. 2012, J. Phys.: Condens. Matter 24, 485005. This work provides an extension by means of detecting the local orientation, and thus allows for the accurate simulation of arbitrarily shaped surfaces. We applied the model to the diffusion of Ag monolayer islands and voids on a Ag(111) and Ag(001) surface, as well as the relaxation of a three-dimensional spherical particle.
A fully parallel version of the contact dynamics (CD) method is presented in this paper. For large enough systems, 100% efficiency has been demonstrated for up to 256 processors using a hierarchical domain decomposition with dynamic load balancing. T
he iterative scheme to calculate the contact forces is left domain-wise sequential, with data exchange after each iteration step, which ensures its stability. The number of additional iterations required for convergence by the partially parallel updates at the domain boundaries becomes negligible with increasing number of particles, which allows for an effective parallelization. Compared to the sequential implementation, we found no influence of the parallelization on simulation results.
Energy dissipation is studied for a hard magnetic tip that scans a soft magnetic substrate. The dynamics of the atomic moments are simulated by solving the Landau-Lifshitz-Gilbert (LLG) equation numerically. The local energy currents are analysed for
the case of a Heisenberg spin chain taken as substrate. This leads to an explanation for the velocity dependence of the friction force: The non-linear contribution for high velocities can be attributed to a spin wave front pushed by the tip along the substrate.
Cohesive powders tend to form porous aggregates which can be compacted by applying an external pressure. This process is modelled using the Contact Dynamics method supplemented with a cohesion law and rolling friction. Starting with ballistic deposit
s of varying density, we investigate how the porosity of the compacted sample depends on the cohesion strength and the friction coefficients. This allows to explain different pore stabilization mechanisms. The final porosity depends on the cohesion force scaled by the external pressure and on the lateral distance between branches of the ballistic deposit r_capt. Even if cohesion is switched off, pores can be stabilized by Coulomb friction alone. This effect is weak for round particles, as long as the friction coefficient is smaller than 1. However, for nonspherical particles the effect is much stronger.
The systematic errors due to the practical implementation of the Contact Dynamics method for simulation of dense granular media are examined. It is shown that, using the usual iterative solver to simulate a chain of rigid particles, effective elastic
ity and sound propagation with a finite velocity occur. The characteristics of these phenomena are investigated analytically and numerically in order to assess the limits of applicability of this simulation method and to compare it with soft particle molecular dynamics.
