--- configs: - config_name: default data_files: "main/*.parquet" license: gpl-3.0 tags: - molecular dynamics - mlip - interatomic potential pretty_name: 23-Single-Element-DNPs RSCDD 2023-Pd --- # Dataset 23-Single-Element-DNPs RSCDD 2023-Pd ### Description Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
Additional details stored in dataset columns prepended with "dataset_". ### Dataset authors Christopher M. Andolina, Wissam A. Saidi ### Publication https://doi.org/10.1039/D3DD00046J ### Original data link https://github.com/saidigroup/23-Single-Element-DNPs ### License gpl-3.0 ### Number of unique molecular configurations 3478 ### Number of atoms 140196 ### Elements included Pd ### Properties included energy, atomic forces, cauchy stress ### Cite this dataset Andolina, C. M., and Saidi, W. A. _23-Single-Element-DNPs RSCDD 2023-Pd_. ColabFit, 2023. https://doi.org/10.60732/8d5bdb05