Data sets of migration barriers for atomistic Kinetic Monte Carlo simulations of Cu self-diffusion via first nearest neighbour atomic jumps

Ekaterina Baibuz, Simon Vigonski, Jyri Kalevi Lahtinen, Junlei Zhao, Ville Bernt Christian Jansson, Vahur Zadin, Flyura Gatifovna Djurabekova

Forskningsoutput: TidskriftsbidragArtikelPeer review

Sammanfattning

Atomistic rigid lattice Kinetic Monte Carlo (KMC) is an efficient method for simulating nano-objects and surfaces at timescales much longer than those accessible by molecular dynamics. A laborious and non-trivial part of constructing any KMC model is, however, to calculate all migration barriers that are needed to give the probabilities for any atom jump event to occur in the simulations. We have calculated three data sets of migration barriers for Cu self-diffusion with two different methods. The data sets were specifically calculated for rigid lattice KMC simulations of copper self-diffusion on arbitrarily rough surfaces, but can be used for KMC simulations of bulk diffusion as well.
Originalspråkengelska
TidskriftData in Brief
Volym17
Sidor (från-till)739-743
Antal sidor5
ISSN2352-3409
DOI
StatusPublicerad - apr 2018
MoE-publikationstypA1 Tidskriftsartikel-refererad

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