Advanced atomistic models for radiation damage in Fe-based alloys: Contributions and future perspectives from artificial neural networks
- DOI
- 10.1016/j.commatsci.2018.02.025
- Published
- 2018-06
- Container
- Computational Materials Science
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.commatsci.2018.02.025,
title = {Advanced atomistic models for radiation damage in Fe-based alloys: Contributions and future perspectives from artificial neural networks},
author = {N. Castin and M.I. Pascuet and L. Messina and C. Domain and P. Olsson and R.C. Pasianot and L. Malerba},
year = {2018},
journal = {Computational Materials Science},
doi = {10.1016/j.commatsci.2018.02.025},
url = {https://doi.org/10.1016/j.commatsci.2018.02.025}
}RIS
TY - JOUR TI - Advanced atomistic models for radiation damage in Fe-based alloys: Contributions and future perspectives from artificial neural networks AU - N. Castin AU - M.I. Pascuet AU - L. Messina AU - C. Domain AU - P. Olsson AU - R.C. Pasianot AU - L. Malerba PY - 2018 JO - Computational Materials Science DO - 10.1016/j.commatsci.2018.02.025 UR - https://doi.org/10.1016/j.commatsci.2018.02.025 ER -
APA
Castin, N., Pascuet, M., Messina, L., Domain, C., Olsson, P., Pasianot, R., & Malerba, L. (2018). Advanced atomistic models for radiation damage in Fe-based alloys: Contributions and future perspectives from artificial neural networks. Computational Materials Science. https://doi.org/10.1016/j.commatsci.2018.02.025
Source records
- crossref · retrieved 2026-11-10T10:57:01.305Z