Do we really need machine learning interatomic potentials for modeling amorphous metal oxides? Case study on amorphous alumina by recycling an existing ab initio database
- DOI
- 10.1088/1361-651x/ad39ff
- Published
- 2024-04-16
- Container
- Modelling and Simulation in Materials Science and Engineering
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1088/1361-651x/ad39ff,
title = {Do we really need machine learning interatomic potentials for modeling amorphous metal oxides? Case study on amorphous alumina by recycling an existing ab initio database},
author = {Simon Gramatte and Vladyslav Turlo and Olivier Politano},
year = {2024},
journal = {Modelling and Simulation in Materials Science and Engineering},
doi = {10.1088/1361-651x/ad39ff},
url = {https://doi.org/10.1088/1361-651x/ad39ff}
}RIS
TY - JOUR TI - Do we really need machine learning interatomic potentials for modeling amorphous metal oxides? Case study on amorphous alumina by recycling an existing ab initio database AU - Simon Gramatte AU - Vladyslav Turlo AU - Olivier Politano PY - 2024 JO - Modelling and Simulation in Materials Science and Engineering DO - 10.1088/1361-651x/ad39ff UR - https://doi.org/10.1088/1361-651x/ad39ff ER -
APA
Gramatte, S., Turlo, V., & Politano, O. (2024). Do we really need machine learning interatomic potentials for modeling amorphous metal oxides? Case study on amorphous alumina by recycling an existing ab initio database. Modelling and Simulation in Materials Science and Engineering. https://doi.org/10.1088/1361-651x/ad39ff
Source records
- hal · retrieved 2026-11-10T12:31:29.426Z