RHEA database and tabGAP/NEP potential files
Abstract
Data for the RHEA training database and Cr-Hf-Mo-Nb-Ta-Ti-V-W-Zr machine-learned potentials (tabGAP and NEP). Potential files, training, testing and validation data, training and DFT input files, and cross-sampling examples.See README files in each folder for details.
Fields of Study & Subjects
Machine Learning in Materials Science
Advanced Chemical Physics Studies
Fusion materials and technologies
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 4 March 2026
- Language
- EN
- Document type
- Dataset