Data for "Machine Learning the Energetics of Electrified Solid/Liquid Interfaces"

DOI

This Dataset contains the data required to reproduce the publication "Machine Learning the Energetics of Electrified Solid/Liquid Interfaces" (Phys. Rev. Lett. 135, 146201, DOI: https://doi.org/10.1103/lm64-m3bn, preprint: https://doi.org/10.48550/arXiv.2505.19745) It contains: Training structures for the Cu(100)-OH and H2O example Machine-Learned interatomic potentials (MLIPs); training files for the Cu(100)-OH and H2O examples; molecular dynamics trajectories, including the potential energies and work functions, from the Cu(100)-OH example in the publication.

Identifier
DOI https://doi.org/10.17617/3.OBN9BY
Metadata Access https://edmond.mpg.de/api/datasets/export?exporter=dataverse_json&persistentId=doi:10.17617/3.OBN9BY
Provenance
Creator Bergmann, Nicolas; Nicéphore Bonnet; Marzari, Nicola; Reuter, Karsten; Hörmann, Nicolas G.
Publisher Edmond
Publication Year 2025
OpenAccess true
Contact bergmann(at)fhi-berlin.mpg.de
Representation
Language English
Resource Type Dataset
Version 1
Discipline Other