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1.6084575468033153
]
] | false | null | null | null | null | null | 13.58471 | 2.846305 | null | CO_9367626997272099154157215 | 9367626997272099154157215390890828414287771542555141702387356957644533930938497018213337346929233177667783823394546703235359127939179853497012420923681415 | 11297421919990403842441731537794876221849295520028975277055339164928652859504183228178086809866590154428716409504353469675422781308557110015203823292623592 | [
[
6.91001,
0,
0
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[
-3.4550049999999985,
5.984244200404509,
0
],
[
0,
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5.43695
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[
4.97263,
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[
1.38594,
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[
0.36943,
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[
6.01223,
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[
2.78634,
4.56226,
1.7708
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[
1.57684,
0.124102,
3.64218
],
[
5.56945,
2.35604,
4... | [
true,
true,
true
] | C6H15N3O6 | C2H5NO2 | A5B2C2D | [
"C",
"H",
"N",
"O"
] | [
0.2,
0.5,
0.1,
0.2
] | [
8,
8,
8,
8,
8,
8,
6,
6,
6,
6,
6,
6,
7,
7,
7,
1,
1,
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1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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] | 30 | 4 | 3 | [
1,
1,
1
] | [
"glycine_test_QE_PBE_TS",
"glycine_train_FPS_QE_PBE_TS"
] | null | data/MD/3237/MD_1275013719955186013193237.json | null | null | null | {"input": {"encut": "100 Ry", "kpoints": "3x3x4"}, "hash": "12750137199551860131932377256894006068409205106908359450851272100841428753427414786661464189341615819360208507600567927025459385369978767392573986947112242", "id": "MD_1275013719955186013193237"} |
Cite this dataset
Kapil, V., and Engel, E. A. DFT polymorphs PNAS 2022 PBE TS glycine test. ColabFit, 2023. https://doi.org/10.60732/d68e42bc
Cite this dataset
Kapil, V., and Engel, E. A. DFT polymorphs PNAS 2022 PBE TS glycine test. ColabFit, 2023. https://doi.org/10.60732/d68e42bcThis 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_qx4h8j4luk70_0
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Dataset Name
DFT polymorphs PNAS 2022 PBE TS glycine test
Description
Glycine test PBE-TS 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
500
Number of atoms
17710
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:
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