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Cite this dataset
Gebauer, N. W., Gastegger, M., Hessmann, S. S., Müller, K., and Schütt, K. T. cG-SchNet. ColabFit, 2023. https://doi.org/10.60732/de8af6a2
Cite this dataset
Gebauer, N. W., Gastegger, M., Hessmann, S. S., Müller, K., and Schütt, K. T. cG-SchNet. ColabFit, 2023. https://doi.org/10.60732/de8af6a2This 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_xzaglubh0trq_0
Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.
https://materials.colabfit.org
Dataset Name
cG-SchNet
Description
Configurations from a cG-SchNet trained on a subset of the QM9dataset. Model was trained with the intention of providing molecules withspecified functional groups or motifs, relying on sampling of molecularfingerprint data. Relaxation data for the generated molecules is computedusing ORCA software. Configuration sets include raw data fromcG-SchNet-generated configurations, with models trained on several differenttypes of target data and DFT relaxation data as a separate configurationset. Includes approximately 80,000 configurations.
Dataset authors
Niklas W.A. Gebauer, Michael Gastegger, Stefaan S.P. Hessmann, Klaus-Robert Müller, Kristof T. Schütt
Publication
https://doi.org/10.1038/s41467-022-28526-y
Original data link
https://github.com/atomistic-machine-learning/cG-SchNet/
License
MIT
Number of unique molecular configurations
23632
Number of atoms
418729
Elements included
C, F, H, N, O
Properties included
energy
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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