Publikationsrepositorium - Helmholtz-Zentrum Dresden-Rossendorf

Nanopatterning of surfaces and bulk materials is very important from molecular electronics to photovoltaics. But, in order to understand the underlying physics of self-organization, large scale atomistic simulations are crucial. Only stochastic models can bridge the gap from nano to micro, enabling simulations of micron-sized volumes, billions of atoms and study long-time evolution. Random site-selection is essential but can be harmed by domain decomposition in GPGPU. We present solutions by example of a dimer-model for KPZ surface growth.