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Register a new userA three-dimensional self-learning kinetic Monte Carlo model: application to Ag(111)
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The reliability of kinetic Monte Carlo (KMC) simulations depends on accurate transition rates. The self-learning KMC method (Trushin et al 2005 Phys. Rev. B 72 115401) combines the accuracy of rates calculated from a realistic potential with the efficiency of a rate catalog, using a pattern recognition scheme. This work expands the original two-dimensional method to three dimensions. The concomitant huge increase in the number of rate calculations on the fly needed can be avoided by setting up an initial database, containing exact activation energies calculated for processes gathered from a simpler KMC model. To provide two representative examples, the model is applied to the diffusion of Ag monolayer islands on Ag(111), and the homoepitaxial growth of Ag on Ag(111) at low temperatures.
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While the self-learning kinetic Monte Carlo (SLKMC) method enables the calculation of transition rates from a realistic potential, implementations of it were usually limited to one specific surface orientation. An example is the fcc (111) surface in Latz et al. 2012, J. Phys.: Condens. Matter 24, 485005. This work provides an extension by means of detecting the local orientation, and thus allows for the accurate simulation of arbitrarily shaped surfaces. We applied the model to the diffusion of Ag monolayer islands and voids on a Ag(111) and Ag(001) surface, as well as the relaxation of a three-dimensional spherical particle.
Cesium adsorption structures on Ag(111) were characterized in a low-temperature scanning tunneling microscopy experiment. At low coverages, atomic resolution of individual Cs atoms is occasionally suppressed in regions of an otherwise hexagonally ordered adsorbate film on terraces. Close to step edges Cs atoms appear as elongated protrusions along the step edge direction. At higher coverages, Cs superstructures with atomically resolved hexagonal lattices are observed. Kinetic Monte Carlo simulations model the observed adsorbate structures on a qualitative level.
A growth model and parameters obtained in our previous experimental (scanning tunneling microscopy, KMC) and theoretical (kinetic Monte Carlo simulations, KMC) studies of Ag/Si(111)-(7x7) heteroepitaxy were used to optimise growth conditions (temperature and deposition rate) for the most ordered self-organized growth of Ag island arrays on the (7x7) reconstructed surface. The conditions were estimated by means of KMC simulations using the preference in occupation of half unit cells (HUCs) of F-type as a criterion of island ordering. Morphology of experimentally prepared island structures was studied by STM. High degree of experimentally obtained island ordering is compared with the simulated data and results are discussed with respect to the model and parameters used at the KMC simulations.
We perform large-scale Monte Carlo simulations of the classical XY model on a three-dimensional $Ltimes L times L$ cubic lattice using the graphics processing unit (GPU). By the combination of Metropolis single-spin flip, over-relaxation and parallel-tempering methods, we simulate systems up to L=160. Performing the finite-size scaling analysis, we obtain estimates of the critical exponents for the three-dimensional XY universality class: $alpha=-0.01293(48)$ and $ u=0.67098(16)$. Our estimate for the correlation-length exponent $ u$, in contrast to previous theoretical estimates, agrees with the most recent experimental estimate $ u_{rm exp}=0.6709(1)$ at the superfluid transition of $^4$He in a microgravity environment.
To study epitaxial thin-film growth, a new model is introduced and extensive kinetic Monte Carlo simulations performed for a wide range of fluxes and temperatures. Varying the deposition conditions, a rich growth diagram is found. The model also reproduces several known regimes and in the limit of low particle mobility a new regime is defined. Finally, a relation is postulated between the temperatures of the kinetic and thermal roughening transitions.
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