Data for: Hydrogen diffusion in TiCr2Hx Laves phases: A combined ab initio and machine-learning-potential study

DOI

This dataset supports the development and validation of machine learning interatomic potentials (MLIPs) for modeling hydrogen diffusion in C14 (hexagonal) and C15 (cubic) TiCr₂-based Laves phases. It includes fitted moment tensor potentials (Level 16) and the corresponding training dataset. The data is organized into two directories: Training_db/, which contains DFT-calculated energies, forces, and stresses for training configurations, and Trained_MTPs/, which contains the final fitted MLIPs for both the C14 (C14.mtp) and C15 (C15.mtp) phases. The dataset is fully referenced in the accompanying manuscript and supplementary materials.

MLIP, 2

VASP, 6

Identifier
DOI https://doi.org/10.18419/DARUS-5544
Related Identifier IsSupplementTo https://doi.org/10.1016/j.actamat.2026.122048
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/DARUS-5544
Provenance
Creator Kumar, Pranav ORCID logo; Körmann, Fritz ORCID logo; Edalati, Kaveh ORCID logo; Grabowski, Blazej ORCID logo; Ikeda, Yuji ORCID logo
Publisher DaRUS
Contributor Grabowski, Blazej
Publication Year 2026
Funding Reference DFG 519607530 ; DFG 541649719 ; DFG 358283783 - SFB 1333 ; DFG 405998092 ; European Commission info:eu-repo/grantAgreement/EC/H2020/865855
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact Grabowski, Blazej (University of Stuttgart)
Representation
Resource Type Dataset
Format application/zip
Size 242965; 22079; 87030778
Version 1.0
Discipline Chemistry; Construction Engineering and Architecture; Design; Engineering; Engineering Sciences; Fine Arts, Music, Theatre and Media Studies; Humanities; Natural Sciences; Physics