Abstract

The atomic-scale mechanisms driving thermally activated self-diffusion on silicon surfaces are investigated by atomic force microscopy. The evolution of surface topography is quantified over a large spatial bandwidth by means of the Power Spectral Density functions. We propose a parametric model, based on the Mullins-Herring (M-H) diffusion equation, to describe the evolution of the surface topography of silicon during thermal annealing. Usually, a stochastic term is introduced into the M-H model in order to describe intrinsic random fluctuations of the system. In this work, we add two stochastic terms describing the surface thermal fluctuations and the oxidation-evaporation phenomenon. Using this extended model, surface evolution during thermal annealing in reducing atmosphere can be predicted for temperatures above the roughening transition. A very good agreement between experimental and theoretical data describing roughness evolution and self-diffusion phenomenon is obtained. The physical origin and time-evolution of these stochastic terms are discussed. Finally, using this model, we explore the limitations of the smoothening of the silicon surfaces by rapid thermal annealing.

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