Kinetic Monte Carlo

The authors investigate quantitatively the self-organization of step bunching instability during epitaxy of Si on vicinal Si(001). They show that growth instability evolution can be fitted by power laws L~tα and A~tβ (where L is the correlation length and A is the instability amplitude) with critical exponents α~0.3 and β~0.5 in good agreement with previous studies and well reproduced by kinetic Monte Carlo simulation. They demonstrate that the main phenomenon controlling step bunching is the anisotropy of surface diffusion. The microscopic origin of the instability is attributed to an easier adatom detachment from SA step, which can be interpreted as a pseudoinverse Ehrlich-Schwoebel barrier [J. Appl. Phys. 37, 3682 (1967); J. Chem. Phys. 44, 1039 (1966)].

Catalytic conversion of biomass-derived synthesis gas to ethanol and other C2+ oxygenates has received considerable attention recently due to the strong demands for alternative, renewable energy sources. Combining experimental measurements with first-principles-based kinetic modeling, we investigated the reaction kinetics of ethanol synthesis from CO hydrogenation over SiO2 -supported Rh/Mn alloy catalysts. We find that an Mn promoter can exist in

ABSTRACT An atomistic kinetic Monte Carlo (AKMC) method has been applied to study the stability and mobility of copper–vacancy clusters in Fe. This information, which cannot be obtained directly from experimental measurements, is needed to parameterise models describing the nanostructure evolution under irradiation of Fe alloys (e.g. model alloys for reactor pressure vessel steels). The physical reliability of the AKMC method has been improved by employing artificial intelligence techniques for the regression of the activation energies required by the model as input. These energies are calculated allowing for the effects of local chemistry and relaxation, using an interatomic potential fitted to reproduce them as accurately as possible and the nudged-elastic-band method. The model validation was based on comparison with available ab initio calculations for verification of the used cohesive model, as well as with other models and theories.

The surface diffusion of Cu adatoms in the presence of an adisland at FCC or HCP sites on Cu(111) is studied using the EAM potential derived by Mishin et al. (Phys. Rev. B 63 224106 (2001)). The diffusion rates along straight (with close-packed edges) steps with (100) and (111)-type microfacets (resp. step A and step B) are first investigated using

In studies of island nucleation and growth, the distribution of capture zones, essentially proximity cells, can give more insight than island-size distributions. In contrast to the complicated expressions, ad hoc or derived from rate equations, usually used, we find the capture-zone distribution can be described by a simple expression generalizing the Wigner surmise from random matrix theory that accounts for the distribution of spacings in a host of fluctuation phenomena. Furthermore, its single adjustable parameter can be simply related to the critical nucleus of growth models and the substrate dimensionality. We compare with extensive published kinetic Monte Carlo data and limited experimental data. A phenomenological theory sheds light on the result.