Efficient Parallel Algorithm for Statistical Ion Track Simulations in Crystalline Materials

We present an efficient parallel algorithm for statistical Molecular Dynamics simulations of ion tracks in solids. The method is based on the Rare Event Enhanced Domain following Molecular Dynamics (REED-MD) algorithm, which has been successfully applied to studies of, e.g., ion implantation into crystalline semiconductor wafers. We discuss the strategies for parallelizing the method, and we settle on a host-client type polling scheme in which a multiple of asynchronous processors are continuously fed to the host, which, in turn, distributes the resulting feed-back information to the clients. This real-time feed-back consists of, e.g., cumulative damage information or statistics updates necessary for the cloning in the rare event algorithm. We finally demonstrate the algorithm for radiation effects in a nuclear oxide fuel, and we show the balanced parallel approach with high parallel efficiency in multiple processor configurations.Comment: 17 pages, seven figures, four table

Simulation of ion track ranges in uranium oxide

Direct comparisons between statistically sound simulations of ion-tracks and published experimental measurements of range densities of iodine implants in uranium dioxide have been made with implant energies in the range of 100-800 keV. Our simulations are conducted with REED-MD (Rare Event Enhanced Domain-following Molecular Dynamics) in order to account for the materials structure in both single crystalline and polycrystalline experimental samples. We find near-perfect agreement between REED-MD results and experiments for polycrystalline target materials.Comment: Eleven pages, four figures