Use of computational intelligence for the prediction of vacancy migration energies in atomistic kinetic monte carlo simulations

DOI

10.2991/ijcis.2008.1.4.6How to use a DOI?

Keywords

Neural Networks, Fuzzy Logic, Cluster Expansion, Vacancy Migration Energy

Abstract

procedures for the calculation of point-defect migration energies in Atomistic Kinetic Monte Carlo (AKMC) simulations, as functions of the Local Atomic Configuration (LAC). Two approaches are considered: the Cluster Expansion (CE) and the Artificial Neural Network (ANN). The first is found to be unpromising because of its high computational complexity. On the contrary, the second provides very encouraging results and is found to be very well behaved.

Copyright

© 2009, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Nicolas Castin
AU  - Lorenzo Malerba
AU  - Roberto Pinheiro Domingos
PY  - 2008
DA  - 2008/12/01
TI  - Use of computational intelligence for the prediction of vacancy migration energies in atomistic kinetic monte carlo simulations
JO  - International Journal of Computational Intelligence Systems
SP  - 340
EP  - 352
VL  - 1
IS  - 4
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2008.1.4.6
DO  - 10.2991/ijcis.2008.1.4.6
ID  - Castin2008
ER  -