0000000000309114
AUTHOR
T. Hjelt
Dynamical mean field theory: an efficient method to study surface diffusion coefficients
Abstract We test the accuracy of the dynamical mean field theory (DMF) developed recently for the collective and tracer diffusion coefficients D C and D T , respectively, by Monte Carlo simulations of two very strongly interacting model systems. The deviation of the DMF results from the true hydrodynamic diffusion coefficients is a measure of memory effects, which are not fully accounted for in DMF. In the cases studied here, DMF predicts the behavior of both D C and D T accurately, while the memory effects are found to be most pronounced at low temperatures, and at high coverages and stronger interactions. Nevertheless, the computational cost of DMF is just a fraction of what is needed for…
Memory expansion for diffusion coefficients
We present a memory expansion for macroscopic transport coefficients such as the collective and tracer diffusion coefficients ${D}_{C}$ and ${D}_{T},$ respectively. The successive terms in this expansion for ${D}_{C}$ describe rapidly decaying memory effects of the center-of-mass motion, leading to fast convergence when evaluated numerically. For ${D}_{T},$ one obtains an expansion of similar form that contains terms describing memory effects in single-particle motion. As an example we evaluate ${D}_{C}$ and ${D}_{T}$ for three strongly interacting surface systems through Monte Carlo simulations, and for a simple model diffusion system via molecular dynamics calculations. We show that the n…
A dynamical mean field theory for the study of surface diffusion constants
We present a combined analytical and numerical approach based on the Mori projection operator formalism and Monte Carlo simulations to study surface diffusion within the lattice-gas model. In the present theory, the average jump rate and the susceptibility factor appearing are evaluated through Monte Carlo simulations, while the memory functions are approximated by the known results for a Langmuir gas model. This leads to a dynamical mean field theory (DMF) for collective diffusion, while approximate correlation effects beyond DMF are included for tracer diffusion. We apply our formalism to three very different strongly interacting systems and compare the results of the new approach with th…