Data sets and trained neural networks for Cu migration barriers
Jyri Kimari,
Ville Jansson,
Simon Vigonski,
Ekaterina Baibuz,
Roberto Domingos,
Vahur Zadin,
Flyura Djurabekova
Affiliations
Jyri Kimari
Helsinki Institute of Physics and Department of Physics, University of Helsinki, P.O. Box 43 (Pietari Kalmin katu 2), FI-00014, Finland; Corresponding author.
Ville Jansson
Helsinki Institute of Physics and Department of Physics, University of Helsinki, P.O. Box 43 (Pietari Kalmin katu 2), FI-00014, Finland
Simon Vigonski
Helsinki Institute of Physics and Department of Physics, University of Helsinki, P.O. Box 43 (Pietari Kalmin katu 2), FI-00014, Finland; Institute of Technology, University of Tartu, Nooruse 1, 50411 Tartu, Estonia
Ekaterina Baibuz
Helsinki Institute of Physics and Department of Physics, University of Helsinki, P.O. Box 43 (Pietari Kalmin katu 2), FI-00014, Finland
Roberto Domingos
Instituto Politécnico de Nova Friburgo – Universidade do Estado do Rio de Janeiro, Rua Sao Francisco Xavier, 524, 20550–900 Rio de Janeiro, RJ, Brazil
Vahur Zadin
Institute of Technology, University of Tartu, Nooruse 1, 50411 Tartu, Estonia
Flyura Djurabekova
Helsinki Institute of Physics and Department of Physics, University of Helsinki, P.O. Box 43 (Pietari Kalmin katu 2), FI-00014, Finland
Kinetic Monte Carlo (KMC) is an efficient method for studying diffusion. A limiting factor to the accuracy of KMC is the number of different migration events allowed in the simulation. Each event requires its own migration energy barrier. The calculation of these barriers may be unfeasibly expensive. In this article we present a data set of migration barriers on for nearest-neighbour jumps on the Cu surfaces, calculated with the nudged elastic band (NEB) method and the tethering force approach. We used the data to train artificial neural networks (ANN) in order to predict the migration barriers for arbitrary nearest-neighbour Cu jumps. The trained ANNs are also included in the article. The data is hosted by the CSC IDA storage service.
