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Self-learning kinetic Monte Carlo model for arbitrary surface orientations

Published online by Cambridge University Press:  29 May 2013

Andreas Latz ,
Lothar Brendel  and
Dietrich E. Wolf
Andreas Latz
Affiliation:
Department of Physics and Center for Nanointegration Duisburg-Essen (CeNIDE), University of Duisburg-Essen, D-47057 Duisburg, Germany
Lothar Brendel
Affiliation:
Department of Physics and Center for Nanointegration Duisburg-Essen (CeNIDE), University of Duisburg-Essen, D-47057 Duisburg, Germany
Dietrich E. Wolf
Affiliation:
Department of Physics and Center for Nanointegration Duisburg-Essen (CeNIDE), University of Duisburg-Essen, D-47057 Duisburg, Germany
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Abstract

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.

Keywords

simulationdiffusionnanoscale
Type
Articles
Information
MRS Online Proceedings Library (OPL) , Volume 1559: Symposium AA – Advanced Interconnects for Micro- and Nanoelectronics—Materials, Processes and Reliability , 2013 , mrss13-1559-aa07-03
Copyright
Copyright © Materials Research Society 2013 

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References

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