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chemical_formula_hill
string
chemical_formula_reduced
string
chemical_formula_anonymous
string
atomic_numbers
sequence
elements
sequence
elements_ratios
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nelements
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adsorption_energy
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atomic_forces
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atomization_energy
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cauchy_stress
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cauchy_stress_volume_normalized
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electronic_band_gap
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energy
float64
formation_energy
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mean_force_norm
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property_object_metadata
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dataset_nproperty_objects
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dataset_nconfigurations
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dataset_formation_energy_count
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dataset_total_elements_ratios
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C9H10N2
C9H10N2
A10B9C2
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MD_1328053828533783752466151
2025-04-16T19:18:43
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PO_9295662773964911042808346
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MD_1043808056618074144570631
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:47
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CO_1000046619274603555202245
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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{'source-publication': 'https://doi.org/10.1038/s41597-023-01998-3', 'source-data': 'https://doi.org/10.5281/zenodo.7032333', 'other': None}
10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
C9H10N2
C9H10N2
A10B9C2
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MD_1328053828533783752466151
2025-04-16T23:57:32
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PO_1134427283603509681093992
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MD_7975106739289527369595006
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:50
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CO_1000800519324877304791505
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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{'source-publication': 'https://doi.org/10.1038/s41597-023-01998-3', 'source-data': 'https://doi.org/10.5281/zenodo.7032333', 'other': None}
10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
C9H10N2
C9H10N2
A10B9C2
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null
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MD_1328053828533783752466151
2025-04-16T23:57:47
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PO_7176367707409720136934397
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MD_7495954197639547381477038
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:49
10013846578547869474165472474122579436692433257295949618583253241860483165903950571311012024953707412649425142916528262976353697390312932124588721022995421
CO_1001384657854786947416547
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
C9H10N2
C9H10N2
A10B9C2
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MD_1328053828533783752466151
2025-04-16T19:23:03
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MD_4424238249825026633325265
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:47
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CO_1001484788582513711235778
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
C9H10N2
C9H10N2
A10B9C2
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MD_1328053828533783752466151
2025-04-16T22:11:35
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MD_1070234805983685223997729
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:54
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CO_1001497670497352483037985
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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{'source-publication': 'https://doi.org/10.1038/s41597-023-01998-3', 'source-data': 'https://doi.org/10.5281/zenodo.7032333', 'other': None}
10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
C9H10N2
C9H10N2
A10B9C2
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MD_1328053828533783752466151
2025-04-16T22:10:42
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MD_8600488593349887809300788
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:44
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CO_1001891134132942080945972
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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2023-12-02T02:24:29
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null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:55
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WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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MD_1328053828533783752466151
2025-04-16T22:52:13
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MD_7768319876058844555353216
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:56
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CO_1005762752089754609037910
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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10.60732/ad4e82a6
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2025-04-16T19:18:29
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MD_5098325739635037003049332
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:46
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CO_1006219240395819632700771
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
C9H10N2
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MD_1328053828533783752466151
2025-04-16T19:41:31
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MD_4302056321418499753159953
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:49
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CO_1006530892804025105077313
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
C9H10N2
C9H10N2
A10B9C2
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MD_1328053828533783752466151
2025-04-16T19:18:43
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MD_1084055311621778290261441
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:52
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CO_1006585394641391702319202
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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{'source-publication': 'https://doi.org/10.1038/s41597-023-01998-3', 'source-data': 'https://doi.org/10.5281/zenodo.7032333', 'other': None}
10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
C9H10N2
C9H10N2
A10B9C2
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MD_1328053828533783752466151
2025-04-16T19:18:37
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MD_1244737906811287830856682
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:51
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CO_1006769619536025274551307
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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{'source-publication': 'https://doi.org/10.1038/s41597-023-01998-3', 'source-data': 'https://doi.org/10.5281/zenodo.7032333', 'other': None}
10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
C9H10N2
C9H10N2
A10B9C2
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2025-04-17T00:30:11
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MD_8117801457048642602483000
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:51
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CO_1008724730138348587828247
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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MD_1328053828533783752466151
2025-04-16T19:40:19
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MD_1132001780633096075505393
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:47
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CO_1008753886362614117717003
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
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MD_1328053828533783752466151
2025-04-16T19:18:29
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MD_3199868762221634458926246
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:51
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CO_1009336938560741038098921
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
C9H10N2
C9H10N2
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2025-04-16T19:41:03
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null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:48
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CO_1009599379552890865213611
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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C9H10N2
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MD_1328053828533783752466151
2025-04-16T19:14:03
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MD_8314951243118100382777382
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:53
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CO_1009902430914980157937290
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
C9H10N2
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MD_1328053828533783752466151
2025-04-16T22:57:04
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MD_5859289296505985536705543
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:44
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CO_1011670625919885536940388
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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{'source-publication': 'https://doi.org/10.1038/s41597-023-01998-3', 'source-data': 'https://doi.org/10.5281/zenodo.7032333', 'other': None}
10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
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C9H10N2
A10B9C2
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[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:51
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CO_1012130051514517416321916
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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MD_1328053828533783752466151
2025-04-16T22:55:36
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MD_1382825768428540940531496
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:44
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CO_1012250635212110975109413
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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10.60732/ad4e82a6
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WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
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MD_1328053828533783752466151
2025-04-16T23:57:46
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MD_9976644066029470201948815
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:55
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CO_1012358546256661522124211
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
C9H10N2
C9H10N2
A10B9C2
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2025-04-16T19:18:29
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MD_1186228453456635435613997
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:46
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WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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MD_1328053828533783752466151
2025-04-16T19:40:54
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MD_1165158734973508929410711
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:49
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CO_1013181452406447544700049
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
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C9H10N2
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MD_1328053828533783752466151
2025-04-16T19:18:43
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MD_3121094122277210238223053
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:52
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CO_1013494032976585555245888
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
C9H10N2
C9H10N2
A10B9C2
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2025-04-16T19:09:29
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2023-12-02T07:14:51
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WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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2025-04-17T00:24:05
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[ "ws22_dmabn_i" ]
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2023-12-02T07:14:48
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CO_1013685771337774941806353
WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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2025-04-16T22:09:37
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MD_6164495975213465691137004
null
[ "ws22_dmabn_i" ]
[ "DS_srva1ami36vs_0" ]
2023-12-02T07:14:54
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WS22_dmabn
[ "Max Pinheiro Jr", "Shuang Zhang", "Pavlo O. Dral", "Mario Barbatti" ]
Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.
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10.60732/ad4e82a6
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DS_srva1ami36vs_0
WS22_dmabn__Jr-Zhang-Dral-Barbatti__DS_srva1ami36vs_0
End of preview. Expand in Data Studio

Cite this dataset

Jr, M. P., Zhang, S., Dral, P. O., and Barbatti, M. WS22 dmabn. ColabFit, 2023. https://doi.org/10.60732/ad4e82a6

View on the ColabFit Exchange

https://materials.colabfit.org/id/DS_srva1ami36vs_0

Dataset Name

WS22 dmabn

Description

Configurations of dmabn from WS22. The WS22 database combines Wigner sampling with geometry interpolation to generate 1.18 million molecular geometries equally distributed into 10 independent datasets of flexible organic molecules with varying sizes and chemical complexity. In addition to the potential energy and forces required to construct potential energy surfaces, the WS22 database provides several other quantum chemical properties, all obtained via single-point calculations for each molecular geometry. All quantum chemical calculations were performed with the Gaussian 09 program.

Additional details stored in dataset columns prepended with "dataset_".

Dataset authors

Max Pinheiro Jr, Shuang Zhang, Pavlo O. Dral, Mario Barbatti

Publication

https://doi.org/10.1038/s41597-023-01998-3

Original data link

https://doi.org/10.5281/zenodo.7032333

License

CC-BY-4.0

Number of unique molecular configurations

120000

Number of atoms

2520000

Elements included

C, H, N

Properties included

energy, atomic forces, cauchy stress

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