Dataset Viewer
chemical_formula_hill
string | chemical_formula_reduced
string | chemical_formula_anonymous
string | atomic_numbers
sequence | elements
sequence | elements_ratios
sequence | nelements
int32 | nsites
int32 | cell
sequence | positions
sequence | pbc
sequence | dimension_types
sequence | nperiodic_dimensions
int32 | structure_hash
string | multiplicity
int32 | software
string | method
string | adsorption_energy
float64 | atomic_forces
string | atomization_energy
float64 | cauchy_stress
string | cauchy_stress_volume_normalized
bool | electronic_band_gap
float64 | electronic_band_gap_type
string | energy
float64 | formation_energy
float64 | max_force_norm
float64 | mean_force_norm
float64 | property_object_metadata
string | property_object_metadata_id
string | property_object_last_modified
timestamp[ns] | property_object_hash
string | property_object_id
string | configuration_metadata
string | configuration_metadata_id
string | configuration_labels
sequence | configuration_names
sequence | configuration_dataset_ids
sequence | configuration_last_modified
timestamp[ns] | configuration_hash
string | configuration_id
string | dataset_name
string | dataset_authors
sequence | dataset_description
string | dataset_elements
sequence | dataset_nelements
int32 | dataset_nproperty_objects
int64 | dataset_nconfigurations
int32 | dataset_nsites
int64 | dataset_adsorption_energy_count
int64 | dataset_atomic_forces_count
int64 | dataset_atomization_energy_count
int64 | dataset_cauchy_stress_count
int64 | dataset_electronic_band_gap_count
int64 | dataset_energy_count
int64 | dataset_energy_mean
float64 | dataset_energy_variance
float64 | dataset_formation_energy_count
int64 | dataset_last_modified
timestamp[ns] | dataset_dimension_types
sequence | dataset_nperiodic_dimensions
sequence | dataset_publication_year
string | dataset_total_elements_ratios
sequence | dataset_license
string | dataset_links
string | dataset_doi
string | dataset_hash
string | dataset_id
string | dataset_extended_id
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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| 2023-12-03T20:50:07 | 10004266641630177058199427278436605386904600738067115831223844022337847072837422437125012790801932452359676242687074470176932764737450302564374396645381443 | CO_1000426664163017705819942 | AFF_JCP_2022 | [
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"Musen Zhou",
"Jessalyn Sebastian",
"Jianzhong Wu",
"Mengyang Gu"
]
| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 4 | 143,759 | 143,770 | 1,911,240 | 0 | 143,759 | 0 | 143,759 | 0 | 143,759 | -11,733.030015 | 2,780,065.958849 | 0 | 2023-12-01T18:15:41 | [
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| 2023-12-03T20:49:56 | 10008226035012561012616018073222126618744122063508166349823484810783879037265625971706561884234581833633328962727398256629122946533591945332483759974581222 | CO_1000822603501256101261601 | AFF_JCP_2022 | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-03T20:50:02 | 10010618980870935607148283930402514919023859423160183834511573555341381959549148683543454745216287751441793350722546677265428520252305328556842731101704399 | CO_1001061898087093560714828 | AFF_JCP_2022 | [
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"Musen Zhou",
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"Jianzhong Wu",
"Mengyang Gu"
]
| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 4 | 143,759 | 143,770 | 1,911,240 | 0 | 143,759 | 0 | 143,759 | 0 | 143,759 | -11,733.030015 | 2,780,065.958849 | 0 | 2023-12-01T18:15:41 | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-03T20:50:05 | 10015604560363802866690383643112156412201849626123880221409795497946573777768407497899621745075676967377013040967351614180974799436463141092813717917260121 | CO_1001560456036380286669038 | AFF_JCP_2022 | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-01T23:06:14 | 10016056445029224090507133642259743907575249321285966406139762658319127367743145694632119658009610135450940333181582306266441595341041391292482648227316913 | CO_1001605644502922409050713 | AFF_JCP_2022 | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-03T20:50:10 | 10022731244915203063697041117732256968161331921211029745768870117641950904039596759193282528711421758299407391208955576348038045628473278451333094253672156 | CO_1002273124491520306369704 | AFF_JCP_2022 | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-03T20:50:12 | 10026199594451780826893919076092680280795123425734682335770479977684272940831664862742705286842563522735215912974495419613876909714345903517856090065423546 | CO_1002619959445178082689391 | AFF_JCP_2022 | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-01T23:06:20 | 10029495370163621401634136443328712899280924881690518891335060629353213086505871108889231480155345640320058596358764545366632924122272846807133256727282843 | CO_1002949537016362140163413 | AFF_JCP_2022 | [
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"Jianzhong Wu",
"Mengyang Gu"
]
| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| [
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| 2023-12-03T20:50:02 | 1003150587853083957533834485041471238640151457419140628733133715754985962991556736611282325126361273246946057955070992560834255659984039718154776257057829 | CO_1003150587853083957533834 | AFF_JCP_2022 | [
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"Jianzhong Wu",
"Mengyang Gu"
]
| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-01T23:06:18 | 10039153281567621018429508401230855814238804315092590118727911285262949328844314488233675970949581495907715333401302339714245408492630939707522346489984921 | CO_1003915328156762101842950 | AFF_JCP_2022 | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-01T23:06:21 | 10045495938634441852263468479673292408051882678955809793027751170478655695602015232278002638039370912114841879048538626447806764001587954912828441239034455 | CO_1004549593863444185226346 | AFF_JCP_2022 | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-03T20:50:11 | 10046616063919138556988143620987100548212077720295854837814026211508358817351552057931731625997261809481621192777409071075623318659607107719453693264886248 | CO_1004661606391913855698814 | AFF_JCP_2022 | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| [
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| 2023-12-03T20:49:48 | 1004802494866640714218526408033099696790000009068478095182885383726620118347949188428160876593012353395081156856225296739925847327835764445796988424800840 | CO_1004802494866640714218526 | AFF_JCP_2022 | [
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]
| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-03T20:49:52 | 10049289319917443416078551699239771408087185442403519448788048280006793308991496720191898920917408196424809535600625636616312018024016780148014225186066736 | CO_1004928931991744341607855 | AFF_JCP_2022 | [
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]
| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-01T23:06:19 | 10052982569240886933166077912868971309808420157920511995077306836327774124825849308958034407207256724228802238544876076792346719472509345180841098830010184 | CO_1005298256924088693316607 | AFF_JCP_2022 | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-03T20:49:58 | 1005338102293682438081187230227515613904655665381820631916801713758669679922994176562710009604492061490954516323309657715144220761728474560578503131801630 | CO_1005338102293682438081187 | AFF_JCP_2022 | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-01T23:06:19 | 10053973965948496523623920041892206903652167029527795945596029334239395046414102207454442985825200705669001105398044641236543683404092027078800600582234402 | CO_1005397396594849652362392 | AFF_JCP_2022 | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 2023-12-01T23:06:21 | 10061381726500762820772217826634461547002822050484849039445946541808579837749310393514253271751529993024017875342055499507309709710866240254435766077125688 | CO_1006138172650076282077221 | AFF_JCP_2022 | [
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| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 4 | 143,759 | 143,770 | 1,911,240 | 0 | 143,759 | 0 | 143,759 | 0 | 143,759 | -11,733.030015 | 2,780,065.958849 | 0 | 2023-12-01T18:15:41 | [
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| [
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| 2023-12-01T23:06:20 | 10063394576735387450947940665615181380525401527021066401310073531960774369146770418879269094923655962699609748911374834886240540176167155340913986415899532 | CO_1006339457673538745094794 | AFF_JCP_2022 | [
"Hao Li",
"Musen Zhou",
"Jessalyn Sebastian",
"Jianzhong Wu",
"Mengyang Gu"
]
| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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| 4 | 143,759 | 143,770 | 1,911,240 | 0 | 143,759 | 0 | 143,759 | 0 | 143,759 | -11,733.030015 | 2,780,065.958849 | 0 | 2023-12-01T18:15:41 | [
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| 0 | 5155195918861077916950781145502213483117389164081049466234631877120660819252473705310354572900839065908981999529134470727009281551786133789634287223603211 | 1 | Q-Chem | DFT-PBE-TS-vdW | null | [[-0.33448216124547603, 0.5270297747408692, 0.2852154289076184], [0.6648997148254767, -0.16742068436053642, -0.5712863759141683], [-0.888369669032326, -2.598788222341976, 0.18367221826765787], [-1.7724244312514172, -1.8946040343930792, 1.430564231718867], [-0.2649040522941064, 1.4959476115820733, 0.13493285995440316], [0.8187093210061176, 0.27327894325051666, -1.4909657004401982], [1.0870175797973594, 1.0104584166871355, -0.7094444374227665], [-0.44689897051321936, -0.45440153126205834, 0.0785992204555844], [-1.0929097460131563, 0.6107309616947505, 0.3392127312585393], [1.2013563193760837, 1.8610786088355051, -0.4199434467169375], [0.8284175239767915, -0.5441501422165864, 0.3358088469836373], [0.1995885713688728, -0.11915970221761403, 0.4036344229444637]] | null | [] | null | null | null | -11,279.384711 | null | 2.962689 | 1.491093 | {"basis-set": "6-31G(d,p)", "hash": "10281099371018203456003102773601362980884329820874994457383260713691322565993615090250794496181420958323621469068106291087205959450951985948219652092436410", "id": "MD_1028109937101820345600310"} | MD_1028109937101820345600310 | 2025-04-16T20:43:24 | 2329487313829519576432889565836642531875692980000649826997029406113551458372412156519736270705818121677768321966517346588078076131730687110376870421936610 | PO_2329487313829519576432889 | null | null | null | [
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| [
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]
| 2023-12-01T23:06:12 | 10068496883102783142403255984994358925015619869426972798543402526931040857916617420364201844053560537736602501737781016619520607870564679841083178595155995 | CO_1006849688310278314240325 | AFF_JCP_2022 | [
"Hao Li",
"Musen Zhou",
"Jessalyn Sebastian",
"Jianzhong Wu",
"Mengyang Gu"
]
| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
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]
| 4 | 143,759 | 143,770 | 1,911,240 | 0 | 143,759 | 0 | 143,759 | 0 | 143,759 | -11,733.030015 | 2,780,065.958849 | 0 | 2023-12-01T18:15:41 | [
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| 0 | 4328727501086887823018511924510156137882754512156370865718317367765345417837057722285698876534336713749276534640899724817480058738364034221460390523369133 | 1 | Q-Chem | DFT-PBE-TS-vdW | null | [[-0.12431492771529239, 0.9671264985218704, 0.3362797433321964], [-0.2546027104605321, -0.5287573087420707, -0.5316636138985302], [1.493807742156468, 0.4731502554015822, -0.47541926551029645], [-4.237504063217568, -0.7117437600521966, 2.8212357763438587], [0.818615402350568, -4.109804497264113, -0.7646905010699617], [3.0465939765129257, 3.108869878889077, -0.9576446922581984], [2.3572450138785523, 1.4680713631267683, -1.268489778321904], [0.09990835124309086, -1.0763663820258893, 0.4057085051859631], [0.46350423919192996, -1.015584700869324, 0.0319272907177621], [-0.029295960475078354, -0.17343726080006155, 0.10989164029858571], [-1.9812474539329226, 1.5416753578721056, 0.2291906600509233], [-1.6527096095454423, 0.05680055594325214, 0.06367423512990196]] | null | [] | null | null | null | -11,279.396511 | null | 5.140272 | 2.252109 | {"basis-set": "6-31G(d,p)", "hash": "10281099371018203456003102773601362980884329820874994457383260713691322565993615090250794496181420958323621469068106291087205959450951985948219652092436410", "id": "MD_1028109937101820345600310"} | MD_1028109937101820345600310 | 2025-04-17T01:13:01 | 5066248760597738930717831896989215987261807503911723911830875769894640476372142151257860581993457073303884422763794567890632401596770005493636592423669635 | PO_5066248760597738930717831 | {"MD17-index": 108754, "hash": "12328164662113567305028069879278458162813903192873480418983205821245556894934534324877558200737946576595268891362739525849507069630412296022803229179749960", "id": "MD_1232816466211356730502806"} | MD_1232816466211356730502806 | null | [
"uracil",
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]
| [
"DS_8rafgy0ly6bt_0",
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]
| 2023-12-03T20:49:41 | 1007043869443784657155414675307928986790873426817750620794050906066933026977025158622108890654928207278085446919966879675228918130049543709302396414588022 | CO_1007043869443784657155414 | AFF_JCP_2022 | [
"Hao Li",
"Musen Zhou",
"Jessalyn Sebastian",
"Jianzhong Wu",
"Mengyang Gu"
]
| Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model. | [
"C",
"H",
"N",
"O"
]
| 4 | 143,759 | 143,770 | 1,911,240 | 0 | 143,759 | 0 | 143,759 | 0 | 143,759 | -11,733.030015 | 2,780,065.958849 | 0 | 2023-12-01T18:15:41 | [
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| GPL-3.0 | {'source-publication': 'https://doi.org/10.1063/5.0088017', 'source-data': 'https://github.com/UncertaintyQuantification/AFF/tree/master', 'other': None} | 10.60732/82344f5c | 2624306582934449196169509044487398365042855554175348711065880230814991427079279209270935699646365573789681942692381037331435777443121943060558353371641282 | DS_5lhmgnxhuia3_0 | AFF_JCP_2022__Li-Zhou-Sebastian-Wu-Gu__DS_5lhmgnxhuia3_0 |
End of preview. Expand
in Data Studio
Cite this dataset
Li, H., Zhou, M., Sebastian, J., Wu, J., and Gu, M. AFF JCP 2022. ColabFit, 2023. https://doi.org/10.60732/82344f5c
View on the ColabFit Exchange
https://materials.colabfit.org/id/DS_5lhmgnxhuia3_0
Dataset Name
AFF JCP 2022
Description
Approximately 145,000 configurations of alkane, aspirin, alpha-glucose and uracil, partly taken from the MD-17 dataset, used in training an 'Atomic Neural Net' model.
Additional details stored in dataset columns prepended with "dataset_".
Dataset authors
Hao Li, Musen Zhou, Jessalyn Sebastian, Jianzhong Wu, Mengyang Gu
Publication
https://doi.org/10.1063/5.0088017
Original data link
https://github.com/UncertaintyQuantification/AFF/tree/master
License
GPL-3.0
Number of unique molecular configurations
143770
Number of atoms
1911240
Elements included
C, H, N, O
Properties included
energy, atomic forces, cauchy stress
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