sGDML -- ColabFit
Collection
Datasets from sGDML (www.sgdml.org) in ColabFit format • 11 items • Updated
Datasets:
property_id string | property_hash string | last_modified timestamp[us] | dataset_id string | multiplicity int32 | software string | method string | energy float64 | atomic_forces list | cauchy_stress list | cauchy_stress_volume_normalized bool | electronic_band_gap float64 | electronic_band_gap_type string | formation_energy float64 | adsorption_energy float64 | atomization_energy float64 | max_force_norm float64 | mean_force_norm float64 | energy_above_hull float64 | configuration_id string | configuration_hash string | structure_hash string | cell list | positions list | pbc list | chemical_formula_hill string | chemical_formula_reduced string | chemical_formula_anonymous string | elements list | elements_ratios list | atomic_numbers list | nsites int32 | nelements int32 | nperiodic_dimensions int32 | dimension_types list | names list | labels list | property_metadata_path string | configuration_metadata_path string | hash string | configuration_metadata string | property_metadata string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
PO_1000817086747790263943186 | 10008170867477902639431865701309334078266872767308482838038521902086186034827121240461744373771836573301339247408562319453875264138706552846036646661709520 | 2025-04-16T21:22:14 | DS_q9y1aat05u42_0 | 1 | FHI-aims | DFT-PBE+TS | -6,308.809026 | [
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"benzene2018_dft_FHI-aims_6038"
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PO_1000850556462114098772001 | 10008505564621140987720010891759786927746619515152585052698521242638714758975046248166144748517025512020156608718150614917949088822144515020123347570337179 | 2025-04-17T18:06:06 | DS_q9y1aat05u42_0 | 1 | FHI-aims | DFT-PBE+TS | -6,308.552045 | [
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"benzene2018_dft_FHI-aims_42239"
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PO_1000829961100717588987195 | 10008299611007175889871957674218400324677937260170403104863827363723511250292653258046366008128351264840795461113119236944511225325109310936002820578353974 | 2025-04-17T18:48:22 | DS_q9y1aat05u42_0 | 1 | FHI-aims | DFT-PBE+TS | -6,308.879982 | [
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"benzene2018_dft_FHI-aims_2856"
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PO_1000910916823101333629099 | 10009109168231013336290995034889805532009055593023141694091804015155753437945284803790406169479613727265915186117649108376709125751212574133158389321906654 | 2025-04-16T16:28:45 | DS_q9y1aat05u42_0 | 1 | FHI-aims | DFT-PBE+TS | -6,308.838409 | [
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1.203670818976518... | [] | null | null | null | null | null | null | 4.031048 | 1.883175 | null | CO_5292042102787637598794643 | 5292042102787637598794643773282130442613108860391759881405864580108632094376637447916453920671094268714490674938161715440913652928891853361861371878611606 | 1055150061844086457556939610005070206991884665709167335154293436897037485619474067571005275787036613737860913976714663173449638929693337275502763582400799 | [
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"benzene2018_dft_FHI-aims_30111"
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PO_1000927813079053914576518 | 10009278130790539145765185440988577393716496725551001101626272636963439242829687877134651264412911674496838809009153090215971511816457820104127650041017604 | 2025-04-16T20:43:06 | DS_q9y1aat05u42_0 | 1 | FHI-aims | DFT-PBE+TS | -6,308.882835 | [
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"benzene2018_dft_FHI-aims_37641"
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PO_1000952065466973733757009 | 10009520654669737337570092541850611728425354672104944919209399235340672612176656961232510313297263897110771219034442335911311667292307575239975167410585882 | 2025-04-16T18:44:30 | DS_q9y1aat05u42_0 | 1 | FHI-aims | DFT-PBE+TS | -6,309.001951 | [
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PO_1000962732047920466507468 | 10009627320479204665074684389212120098819747872743307165790309142030965353660516826125319891439845250294808013107195432780926242144132528150631987120668361 | 2025-04-16T17:18:32 | DS_q9y1aat05u42_0 | 1 | FHI-aims | DFT-PBE+TS | -6,308.560681 | [
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PO_1000990383166460480830818 | 10009903831664604808308181998798517203947325031851147601606711410121764844948967765933660999529500753754740630523576872802698749827320125745645650435754652 | 2025-04-16T18:48:00 | DS_q9y1aat05u42_0 | 1 | FHI-aims | DFT-PBE+TS | -6,309.124195 | [
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End of preview. Expand in Data Studio
Cite this dataset
Chmiela, S., Sauceda, H. E., Müller, K., and Tkatchenko, A. sGDML Benzene DFT NC2018. ColabFit, 2023. https://doi.org/10.60732/18404d62
Cite this dataset
Chmiela, S., Sauceda, H. E., Müller, K., and Tkatchenko, A. sGDML Benzene DFT NC2018. ColabFit, 2023. https://doi.org/10.60732/18404d62This 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_q9y1aat05u42_0
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Dataset Name
sGDML Benzene DFT NC2018
Description
The data used for training the DFT models were created running ab initio MD in the NVT ensemble using the Nosé-Hoover thermostat at 500 K during a 200 ps simulation with a resolution of 0.5 fs. Forces and energies were computed using all-electrons at the generalized gradient approximation level of theory with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional, treating van der Waals interactions with the Tkatchenko-Scheffler (TS) method. All calculations were performed with FHI-aims. The final training data was generated by subsampling the full trajectory under preservation of the Maxwell-Boltzmann distribution for the energies.
Dataset authors
Stefan Chmiela, Huziel E. Sauceda, Klaus-Robert Müller, Alexandre Tkatchenko
Publication
https://doi.org/10.1126/sciadv.1603015
Original data link
License
MIT
Number of unique molecular configurations
49862
Number of atoms
598344
Elements included
C, H
Properties included
energy, atomic forces
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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