Data publication: Machine Learning-Driven Structure Prediction for Iron Hydrides

Dataset

DOI

Here, we provide the training datasets and the resulting neural network potential for exploring the potential energy surfaces of the FeH system using the minima hopping method. Additionally, data for the minima structures identified in this work are included.

Identifier
DOI	https://doi.org/10.14278/rodare.2778
Related Identifier	https://www.hzdr.de/publications/Publ-38894
Related Identifier	https://www.hzdr.de/publications/Publ-37800
Related Identifier	https://doi.org/10.14278/rodare.2777
Related Identifier	https://rodare.hzdr.de/communities/rodare
Metadata Access	https://rodare.hzdr.de/oai2d?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:rodare.hzdr.de:2778

Provenance
Creator	Tahmasbi, Hossein ; Ramakrishna, Kushal ; Lokamani, Mani ; Cangi, Attila (ORCID: 0000-0001-9162-262X)
Publisher	Rodare
Publication Year	2024
Rights	Creative Commons Attribution 4.0 International; Open Access; https://creativecommons.org/licenses/by/4.0/legalcode; info:eu-repo/semantics/openAccess
OpenAccess	true
Contact	https://rodare.hzdr.de/support

Representation
Resource Type	Dataset
Discipline	Life Sciences; Natural Sciences; Engineering Sciences