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Data sets of migration barriers for atomistic Kinetic Monte Carlo simulations of Fe self-diffusion

Authors :
Ekaterina Baibuz
Simon Vigonski
Jyri Lahtinen
Junlei Zhao
Ville Jansson
Vahur Zadin
Flyura Djurabekova
Source :
Data in Brief, Vol 19, Iss , Pp 564-569 (2018)
Publication Year :
2018
Publisher :
Elsevier, 2018.

Abstract

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 calculated three data sets of migration barriers for Fe self-diffusion: barriers of first nearest neighbour jumps, second nearest neighbours hop-on jumps on the Fe {100} surface and a set of barriers of the diagonal exchange processes for various cases of the local atomic environments within the 2nn coordination shell. Keywords: Copper, Iron, Kinetic Monte Carlo, Surface diffusion, Rigid lattice, Migration barriers, Atomic jumps

Details

Language :
English
ISSN :
23523409
Volume :
19
Issue :
564-569
Database :
Directory of Open Access Journals
Journal :
Data in Brief
Publication Type :
Academic Journal
Accession number :
edsdoj.981540042af4ef1973d112670483f1f
Document Type :
article
Full Text :
https://doi.org/10.1016/j.dib.2018.04.060