RHEA database and tabGAP/NEP potential files

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Authors: Jesper Byggmästar
Cited by: 0

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