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
- Nicolas Castin, Lorenzo Malerba, Roberto Pinheiro Domingos
- Corresponding Author
- Nicolas Castin
Available Online 2 January 2009.
- https://doi.org/10.2991/ijcis.2008.1.4.6How to use a DOI?
- Neural Networks, Fuzzy Logic, Cluster Expansion, Vacancy Migration Energy
- 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.
- 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 -