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Cite this dataset
Andolina, C. M., and Saidi, W. A. 23-Single-Element-DNPs RSCDD 2023-Os. ColabFit, 2023. https://doi.org/10.60732/1ec0df98
Cite this dataset
Andolina, C. M., and Saidi, W. A. 23-Single-Element-DNPs RSCDD 2023-Os. ColabFit, 2023. https://doi.org/10.60732/1ec0df98This dataset has been curated and formatted for the ColabFit Exchange
This dataset is also available on the ColabFit Exchange:
https://materials.colabfit.org/id/DS_098x6q7kbeat_0
Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.
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Dataset Name
23-Single-Element-DNPs RSCDD 2023-Os
Description
Configurations of Os 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.
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-only
Number of unique molecular configurations
4624
Number of atoms
114840
Elements included
Os
Properties included
energy, atomic forces, cauchy stress
Usage
ds.parquet: Aggregated dataset information.co/directory: Configuration rows each include a structure, calculated properties, and metadata.cs/directory : Configuration sets are subsets of configurations grouped by some common characteristic. Ifcs/does not exist, no configurations sets have been defined for this dataset.cs_co_map/directory : The mapping of configurations to configuration sets (if defined).
ColabFit Exchange documentation includes descriptions of content and example code for parsing parquet files:
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