DFT-Polymorphs -- ColabFit
Collection
Datasets from DFT-Polymorphs in ColabFit format
•
18 items
•
Updated
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_1000012972703100637159203
|
10000129727031006371592038768452856550345423693353399996877374661325349618554224385883643512881031315288680901024483424764681062697601888097307487150650297
| 2025-04-16T16:02:31
|
DS_b1n228x610dj_0
| 1
|
Quantum ESPRESSO v6.3
|
DFT-PBE-TS
| -23,196.57279
|
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[] | null | null | null | null | null | null | 6.292325
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| null |
CO_2160437058410475337223122
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true,
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C6H15N3O6
|
C2H5NO2
|
A5B2C2D
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| 4
| 3
|
[
1,
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[
"glycine_train_FPS_QE_PBE_TS",
"glycine_train_FPS_AIMS_PBE0_MBD"
] | null |
data/MD/3237/MD_1275013719955186013193237.json
| null | null | null |
{"input": {"encut": "100 Ry", "kpoints": "3x3x4"}, "hash": "12750137199551860131932377256894006068409205106908359450851272100841428753427414786661464189341615819360208507600567927025459385369978767392573986947112242", "id": "MD_1275013719955186013193237"}
|
PO_1000252656844829485821446
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| 2025-04-16T16:49:28
|
DS_b1n228x610dj_0
| 1
|
Quantum ESPRESSO v6.3
|
DFT-PBE-TS
| -23,200.685741
|
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| null | null | null | null | null | 5.297385
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C6H15N3O6
|
C2H5NO2
|
A5B2C2D
|
[
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[
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[
"glycine_train_FPS_QE_PBE_TS",
"glycine_train_FPS_AIMS_PBE0_MBD"
] | null |
data/MD/3358/MD_1253836397924609709183358.json
| null | null | null |
{"input": {"encut": "100 Ry", "kpoints": "4x2x4"}, "hash": "12538363979246097091833586420118042097224103726702180638478811883449722987643502399199118112955370205601235303336684897758604517956020966757613017737907519", "id": "MD_1253836397924609709183358"}
|
PO_1000106913726234341853710
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| 2025-04-16T17:12:24
|
DS_b1n228x610dj_0
| 1
|
Quantum ESPRESSO v6.3
|
DFT-PBE-TS
| -15,468.48907
|
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| null | null | null | null | null | 12.741118
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[
true,
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true
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C4H10N2O4
|
C2H5NO2
|
A5B2C2D
|
[
"C",
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[
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| 4
| 3
|
[
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[
"glycine_train_FPS_QE_PBE_TS",
"glycine_train_FPS_AIMS_PBE0_MBD"
] | null |
data/MD/3358/MD_1253836397924609709183358.json
| null | null | null |
{"input": {"encut": "100 Ry", "kpoints": "4x2x4"}, "hash": "12538363979246097091833586420118042097224103726702180638478811883449722987643502399199118112955370205601235303336684897758604517956020966757613017737907519", "id": "MD_1253836397924609709183358"}
|
PO_1000680131330231610526678
|
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| 2025-04-16T17:50:49
|
DS_b1n228x610dj_0
| 1
|
Quantum ESPRESSO v6.3
|
DFT-PBE-TS
| -15,469.845995
|
[
[
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C2H5NO2
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data/MD/3662/MD_9227642908899945704603662.json
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DS_b1n228x610dj_0
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Quantum ESPRESSO v6.3
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DFT-PBE-TS
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C8H20N4O8
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C2H5NO2
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data/MD/9937/MD_8804695634554787084129937.json
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DS_b1n228x610dj_0
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Quantum ESPRESSO v6.3
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DFT-PBE-TS
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C4H10N2O4
|
C2H5NO2
|
A5B2C2D
|
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data/MD/3237/MD_1275013719955186013193237.json
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|
End of preview. Expand
in Data Studio
Cite this dataset
Kapil, V., and Engel, E. A. DFT polymorphs PNAS 2022 PBE0 MBD glycine train. ColabFit, 2023. https://doi.org/10.60732/358cb5ee
Cite this dataset
Kapil, V., and Engel, E. A. DFT polymorphs PNAS 2022 PBE0 MBD glycine train. ColabFit, 2023. https://doi.org/10.60732/358cb5eeThis 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_b1n228x610dj_0
Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.
https://materials.colabfit.org
Dataset Name
DFT polymorphs PNAS 2022 PBE0 MBD glycine train
Description
Glycine training PBE0-MBD dataset from "Semi-local and hybrid functional DFT data for thermalised snapshots of polymorphs of benzene, succinic acid, and glycine". DFT reference energies and forces were calculated using Quantum Espresso v6.3. The calculations were performed with the semi-local PBE xc functional, Tkatchenko-Scheffler dispersion correction, optimised norm-conserving Vanderbilt pseudopotentials, a Monkhorst-Pack k-point grid with a maximum spacing of 0.06 x 2π A^-1, and a plane-wave energy cut-off of 100 Ry for the wavefunction.
Dataset authors
Venkat Kapil, Edgar A. Engel
Publication
https://doi.org/10.1073/pnas.2111769119
Original data link
https://doi.org/10.24435/materialscloud:vp-jf
License
CC-BY-4.0
Number of unique molecular configurations
3582
Number of atoms
109570
Elements included
C, H, N, O
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:
- Downloads last month
- 12
Size of downloaded dataset files:
5.53 MB
Size of the auto-converted Parquet files:
5.53 MB
Number of rows:
3,597