International Journal of Computational Intelligence Systems

Volume 1, Issue 4, December 2008, Pages 340 - 352

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

Authors
Nicolas Castin, Lorenzo Malerba, Roberto Pinheiro Domingos
Corresponding Author
Nicolas Castin
Available Online 2 January 2009.
DOI
https://doi.org/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.
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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
1 - 4
Pages
340 - 352
Publication Date
2009/01
ISSN
1875-6883
DOI
https://doi.org/10.2991/ijcis.2008.1.4.6How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Nicolas Castin
AU  - Lorenzo Malerba
AU  - Roberto Pinheiro Domingos
PY  - 2009
DA  - 2009/01
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  - https://doi.org/10.2991/ijcis.2008.1.4.6
ID  - Castin2009
ER  -