chemical_formula_hill
string | chemical_formula_reduced
string | chemical_formula_anonymous
string | atomic_numbers
list | elements
list | elements_ratios
list | nelements
int32 | nsites
int32 | cell
list | positions
list | pbc
list | dimension_types
list | nperiodic_dimensions
int32 | structure_hash
string | multiplicity
int32 | software
string | method
string | adsorption_energy
float64 | atomic_forces
list | atomization_energy
float64 | cauchy_stress
list | 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
list | configuration_names
list | configuration_dataset_ids
list | configuration_last_modified
timestamp[ns] | configuration_hash
string | configuration_id
string | dataset_name
string | dataset_authors
list | dataset_description
string | dataset_elements
list | 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
list | dataset_nperiodic_dimensions
list | dataset_publication_year
string | dataset_total_elements_ratios
list | dataset_license
string | dataset_links
string | dataset_doi
string | dataset_hash
string | dataset_id
string | dataset_extended_id
string |
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| true | null | null | -1,450.171012 | null | 1.465362 | 7.97348 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:48:14 | 7506933880169440154465471387777393570098799283197414444831461155300102027137407463497300899685452025058142119649751149050559320676544462909494492052841055 | PO_7506933880169440154465471 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:30 | 1773665436425151743236635371135143040923820937681838742161769183250996380406915821522125434648555352972255242206673353541154172228990109706584481810062701 | CO_1773665436425151743236635 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,922.813266 | null | 3.162078 | 28.958557 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:07:56 | 5325494661296365059934578502904439594273865151768832802557472180470050723307578840411032022034154740443509901211819372635759441022933293105489710419168555 | PO_5325494661296365059934578 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 1809516930601516171324484659852401836980524812637950863267702928465347798799027635458076377709444630364426033655455131272639215618546701020825286903883933 | CO_1809516930601516171324484 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,654.520688 | null | 1.457108 | 12.111493 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:07:03 | 9470187141727644804271484712613046243291822600501254959560685600600244483035332480759434311315852511215363920048022870856686903259926303267823869377092472 | PO_9470187141727644804271484 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:28 | 1847306522862676850101717093682421116958216735534196248126752589816123103278870114025916263613421231136841569514660392518002124060945611766131292268279539 | CO_1847306522862676850101717 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:28 | 1872494915094026847775517575929154065507673044854510591477599477459327556351293844260225573201352729678314025593534695743677202280096715884748799414802366 | CO_1872494915094026847775517 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2024-01-12T23:00:29 | 1872563645627209468077472727149710034289822911248686255410667576638763120602372794060376490204647300550045205331382784071260040076627704338055670988977934 | CO_1872563645627209468077472 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| true | null | null | -1,527.625067 | null | 1.414806 | 8.489328 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:35:49 | 6406144886323621613791613548350394388193870212450601971940611017902402035927149905288552620575652424404289170906130571881628468996773050137858875245439868 | PO_6406144886323621613791613 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:30 | 1952885302685826524124050279005056660298433544539843085215858083744689098813360262003220929257614804829092367822615224041094556253328061770375081819209386 | CO_1952885302685826524124050 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:29 | 1964573046774646849143207200468296087734917990796482468977461273751068285845572166536070776240765579967600386539076224944450240296662894624555420241146951 | CO_1964573046774646849143207 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| true | null | null | -1,530.038055 | null | 1.428467 | 9.408678 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:38:24 | 7118542807683395106156566713299646173506779547793694060683072181804304873561307743602289390356219085315546802738906380130669685073141174158646993714848305 | PO_7118542807683395106156566 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:30 | 2020033877372889255451797771877669100268448614494078982238581126963764606511722102099910524427393599154110904286420925441646358506007671845062234727280444 | CO_2020033877372889255451797 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,800.810605 | null | 2.86394 | 71.653897 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:12:13 | 9617974764873664870055086079361124922117103042071742265094546221806105146384540277117392836820766932667473778474146343545986974636301026977878549503928817 | PO_9617974764873664870055086 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:29 | 2022731748064424130901413649535594158606360160215399489706533745580474572735269970880768087715563968091776659894364291731191296985407741538671287903312573 | CO_2022731748064424130901413 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:30 | 2064940393907603780283881733978960984992983915744707883863881156353214406682506079614804101445504856725012730694995832241691747391932292826047975998251196 | CO_2064940393907603780283881 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| true | null | null | -1,666.187981 | null | 1.687052 | 20.31084 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:45:14 | 8590848922279141549710310160456284662674555353885559485982955144566911157140700564693035038968492989692494744503375890557754470175087404617260065017908286 | PO_8590848922279141549710310 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:28 | 2109290270396169112875497275268776724232143193417948679813477354601240982385893434385903270994809838268764359178401989067226203180693399832531521471709481 | CO_2109290270396169112875497 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,929.030166 | null | 1.744288 | 13.603209 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:47:23 | 3493107718090183442268291652261182346978224235875918528538522495000515854138361716836618592420883676050311108616979653536432750747667964510385624049589074 | PO_3493107718090183442268291 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 2205532888474741180748325827149813342753641651580199694890011398716421422862876250873112668706432455904817766921566531676836505497221001919128765063242301 | CO_2205532888474741180748325 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,925.960102 | null | 1.588381 | 11.01429 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:19:31 | 4702322152662304656900602456676607811903548866216784520047248786714107163389247980933265187126663418776757487605042395999620395464349395082300563957052691 | PO_4702322152662304656900602 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:30 | 2216634847307948911941741590685834275657932675320608449371682516935695564301125637423259229122494183807781093193284621492792576729548262187719816452138946 | CO_2216634847307948911941741 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:29 | 2303763018903461924805747522093695451023196235131129776919004686706455529988910931743771511152724012634712824554903114814182693903078610490422862305724399 | CO_2303763018903461924805747 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2024-01-12T23:00:28 | 2409071349943038469339758352805677660247102455551940223796862063506604468932983381637281638795384834603572285285925764655657771513979976573366865460328889 | CO_2409071349943038469339758 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:29 | 2462086192216894865445293224353640282659759335567883274492952499419224706862035983102613823722758072193239698892541978620416536950004809652115908903751185 | CO_2462086192216894865445293 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:28 | 2491948101116982921178022802647418824109267493534674922694303408313876089437451574980008615312361168747437797402566108621083728435284622990705265167273299 | CO_2491948101116982921178022 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| true | null | null | -1,006.994819 | null | 1.137394 | 16.348152 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:11:47 | 5867182834499639387995962175585316541354656965391695538109884120460102465834319510775530807196474175451422684087069867308905564492542222107553103554646672 | PO_5867182834499639387995962 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:28 | 25651572060640224992428279157785465335023898845784818574475548543464440440430988441285150568675535522063374428757051783218018368760665047389936933852738 | CO_2565157206064022499242827 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -2,069.955263 | null | 1.789925 | 16.414085 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:21:36 | 5939100158504136963032220803949901989986909074807827772926685666485747373817666088852057769528655393064757682955585540831572318551525589389645682812416071 | PO_5939100158504136963032220 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:30 | 2584507210579540027544757200770009928957909583622944980618132711110933426437221759497907113458788569124877079780143181230990867349950793418291881741005079 | CO_2584507210579540027544757 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:29 | 2585127650916001782768375344637209938437995819932766198948375192375062110525965554857282057570094997534473547993957625281803676024558955539974453211459130 | CO_2585127650916001782768375 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2024-01-12T23:00:29 | 2733346997759944580056335014789289464313645129730386599884971758355529755832914449466626037439422690065585221815594693267513819102998381460386110019109967 | CO_2733346997759944580056335 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2024-01-12T23:00:28 | 2734648803578638616823689266089013931751231210694179772240124183324445728969554362616001741532531879470685111537522321712170177261507381278271430383415027 | CO_2734648803578638616823689 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| true | null | null | -1,519.951058 | null | 1.714232 | 19.491719 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:49:39 | 1946242684664471411175450627092543218842904016874969375809341016004581263897622909841849286628712123372344953307776472184331154539401141713743409942875437 | PO_1946242684664471411175450 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:28 | 2807066441381666253060804972004970180191393103787222558434689390285489954442538632940431676191297229361219233705165947924037279916947950622916069286726252 | CO_2807066441381666253060804 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| 2024 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:30 | 2816978787640290250122661102121546558927324482326801935637102640364274823340970800911460665832073864313876717670755744245343983290743087301810503511486909 | CO_2816978787640290250122661 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2024-01-12T23:00:30 | 2917926125359006821451917877613614949925319440527243912740433589511948211689778365752691968344784765966234677249965511379137512065588540916265189252021802 | CO_2917926125359006821451917 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2024-01-12T23:00:28 | 3015550399783961149407961933726312196796910189250192269075641653094684600686938941314835358961887191521300483014159990063380596123887179196670915533954578 | CO_3015550399783961149407961 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,985.438835 | null | 1.72092 | 8.160761 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:32:18 | 7932937457136145479648378740595523516472051280692414747411105603255153039117992169941298332380572365797336370729922937817075935303730385682422361118716147 | PO_7932937457136145479648378 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_1039"
]
| [
"DS_8frq3jczb0dt_0"
]
| 2024-01-12T23:00:29 | 302513890346817181741341973465658787394474922895610868494391046699913118788975114657739160828904572103990516419480517280594732090326164254235115395137516 | CO_3025138903468171817413419 | CGM-MLP_natcomm2023_Ti-C_deposition | [
"Di Zhang",
"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
]
| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
"C",
"Ti"
]
| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
[
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| [
3
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| 2024 | [
0.27399898319185323,
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]
| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
C3Ti144 | CTi48 | A48B | [
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| 2024-01-12T23:00:28 | 3056021799422217036020394787635934486801029576546823215596782228135645880515546416619478235121461112416504004579995899986308028531717360324711048291497710 | CO_3056021799422217036020394 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2024-01-12T23:00:30 | 3087624297538875394265738225034456797031735777386988255372241714371429418659417204050067650062183830396652332209575825221403774081929763665858206970630833 | CO_3087624297538875394265738 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,972.455172 | null | 2.098863 | 22.036299 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:31:07 | 8182085383212230168257891984373708103561407709222661129351108360989751510410419250876573438242092840917508486551197885559304371744978275417694500921569416 | PO_8182085383212230168257891 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_1166"
]
| [
"DS_8frq3jczb0dt_0"
]
| 2024-01-12T23:00:30 | 3117339898573131696364232575006687908397333571419890696058013231480328404201543784370365902927237657760751641846318213764275950497191449391482129456449530 | CO_3117339898573131696364232 | CGM-MLP_natcomm2023_Ti-C_deposition | [
"Di Zhang",
"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
]
| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
"C",
"Ti"
]
| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| [
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| 2024 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
C6Ti144 | CTi24 | A24B | [
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| true | null | null | -1,262.23749 | null | 1.360677 | 9.35798 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:50:51 | 11424928962357608576687671050976845683156732805738691144320710738209764611246719224506133968630570149877907665941681541602890252161092587308280058769192989 | PO_1142492896235760857668767 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:29 | 3192743739614904818404848663022009173851252033111245549815982178063623624657133068657252654906120029749293481320721144643168903012764874206588873940281670 | CO_3192743739614904818404848 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:28 | 3200765698260430512131069358866520658339967558921095701444085409691569915932570116184323880044134893150228072514626455706736008111963220724037335230558073 | CO_3200765698260430512131069 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2024-01-12T23:00:29 | 325370149141746706999825062292353013852739888087791415305400420579471508083116934949677821659341165484196308291399497765967629773067975117587697903185703 | CO_3253701491417467069998250 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| 2024-01-12T23:00:28 | 3282276380952621144746819322505478878183255288614117199584029612352125299560500669173597209612386551734929547008939854590911796278321782461284158501057829 | CO_3282276380952621144746819 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2024-01-12T23:00:29 | 3291234617071913802513064475018715319394465152693931101595548262487236531923661822569513437836079280400775308031627420341066876198735110918865592363837894 | CO_3291234617071913802513064 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| true | null | null | -1,844.896203 | null | 3.203891 | 39.672689 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:12:06 | 2591156248015507001457829910053194818555829202694084983230920434859857043055174403445064721146421730722115358042045767447979837671621496939147925047475042 | PO_2591156248015507001457829 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_904"
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| [
"DS_8frq3jczb0dt_0"
]
| 2024-01-12T23:00:29 | 336393277269933311602105227390798946642872228088947230247034885570206452633392072178893092419231915357479406126655054534274381289553660523357888739647919 | CO_3363932772699333116021052 | CGM-MLP_natcomm2023_Ti-C_deposition | [
"Di Zhang",
"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
]
| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
"C",
"Ti"
]
| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| 2024 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,613.45273 | null | 1.603033 | 26.723615 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:11:56 | 7444917518980028688253174702070694428819672033948739670784006395129696507296392529585899648351121595060200018236438382216606728001276198106917083239598311 | PO_7444917518980028688253174 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:28 | 3434449073704208501086851802795843626781915768231743442135886690669017994874411650283945578538601565440407872518133360576479267906588674872842015506710704 | CO_3434449073704208501086851 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| 2024 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,775.486586 | null | 1.633985 | 11.569128 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:36:40 | 6625342235979682661918098092536856947076483085829822186480776139075654386124192955717531895900707357896636105510262555231567633678901915372544869638750640 | PO_6625342235979682661918098 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_852"
]
| [
"DS_8frq3jczb0dt_0"
]
| 2024-01-12T23:00:28 | 3555913819762009484251311993653640204855063755198548499863636469979607342477392279235878219833531468949198856661144982154333761230538450071876040687500855 | CO_3555913819762009484251311 | CGM-MLP_natcomm2023_Ti-C_deposition | [
"Di Zhang",
"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
]
| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
"C",
"Ti"
]
| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
[
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| [
3
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| 2024 | [
0.27399898319185323,
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,747.055402 | null | 1.562047 | 12.662857 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:00:44 | 8355496816063015053769990248004134886759185221655089079357701821630000824755949922264890663809882946392339384232777337471046478311538566258478471862645734 | PO_8355496816063015053769990 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:28 | 3615862281182533648587039183865554810820876720953442863079343158301686088686828111868265380286535454105553825393765441243606916090949651658582557382583656 | CO_3615862281182533648587039 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,926.05602 | null | 2.693625 | 33.886901 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:28:15 | 7675654625630054877283854980877063882130285388485973773773666281374185361324116567774298634837358037115806490359157311310941959129003160838945704277769370 | PO_7675654625630054877283854 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 3664543624398068232030833911501531441164469177854357061960691787912240813037670666381630764105388397585265251512271594796209022676236621399858570546573619 | CO_3664543624398068232030833 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,298.822698 | null | 1.274391 | 6.660677 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:19:28 | 3699495512987492719151516346342929110977282370444591757031300266416318676288632594838689013034895628110567114682534824663775856707591028364682188371812973 | PO_3699495512987492719151516 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:29 | 369531922812975608407144979356508677448950507258779217719388108419379933805996730954216535244990224322386775179892084893849365443500333957577039581969005 | CO_3695319228129756084071449 | CGM-MLP_natcomm2023_Ti-C_deposition | [
"Di Zhang",
"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
]
| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
"C",
"Ti"
]
| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
C91Ti144 | C91Ti144 | A144B91 | [
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| true | null | null | -1,895.214939 | null | 1.907124 | 19.265654 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:20:16 | 10988214788227210868009684415617444326641541730270961436081414720608249946743454716144032709744448873073110540937959513237453290624414137498669819991230070 | PO_1098821478822721086800968 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:29 | 3714349696709440171782941054189122685777496377405517784174462623743535093296653177431522675029570829110075590378347766905704390617121514792122733611971062 | CO_3714349696709440171782941 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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"Peiyun Yi",
"Xinmin Lai",
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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"Ti"
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| 2024 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:30 | 3730710275588704594239225826720982962444909676144068471178035894096112245525796905814662043548760691461294785946498180865040628265582332324307319238606516 | CO_3730710275588704594239225 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| true | null | null | -1,661.093908 | null | 1.549835 | 15.274428 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:17:43 | 11254417172875086670156755896406535820241203862412780251443268766704915930656925477328310174304048161414540622228505421598646348358412926234877731014209023 | PO_1125441717287508667015675 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:28 | 3921575492429319274072907207836711785567891352417656410140814409872910441968175062229840108169608664155972413571167655971058670660523481479318316048417501 | CO_3921575492429319274072907 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:28 | 397897937200888063146489905634990833001804118143179556423519943216299322030859702552379916958910655291855025476266034268877822932518181062097131210254263 | CO_3978979372008880631464899 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| 2024-01-12T23:00:28 | 4003004217101622542020909002593148127436562374302938716304000265433749328374956891374739786152857549964773448473014088589856345352427294587257789505874726 | CO_4003004217101622542020909 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| true | null | null | -1,828.017401 | null | 1.800814 | 20.928486 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:20:28 | 2432992971393853176570148264460283684157240554520597351950669009500468383129828816495306966411650245849926161233557086783628909384721065310739279562527385 | PO_2432992971393853176570148 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:29 | 4069217348073924154277795107350620188324621255691322951119848598926943881640658436531997371701865351663321653141433088213540227507735559007381022680941981 | CO_4069217348073924154277795 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:28 | 4083204737424045267967759936286805787466684886143752863386606453713531909656068240688609062478796214463550874980507281981137916478253054801064342894360077 | CO_4083204737424045267967759 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| true | null | null | -1,636.51939 | null | 1.700402 | 16.187051 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:15:03 | 8424707785448815080300792342386160899832166939201490990963847567950479597529397872663890337746236896134069979912487181847326411299262422828338008659266197 | PO_8424707785448815080300792 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:28 | 4145982618500453267096569426440599240129508667970796922273378859143265810263912356895205380023932105377375868342399543656608732466541522954172759612933815 | CO_4145982618500453267096569 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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"Peiyun Yi",
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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"Ti"
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| 2024 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:30 | 4159042762231398181939389267302299599380792061726362716915398975467850234582773326822285238460246013647904551758288102294165902972365654893975299857692483 | CO_4159042762231398181939389 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| true | null | null | -1,199.889831 | null | 1.111408 | 6.41586 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:19:21 | 10691243971696018996690009742781444689784283876508586952904842063945495121311947551018300802814161256105831423398078462765377255609911786032276185944363238 | PO_1069124397169601899669000 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:29 | 4207030810887709349633618172171470266263493426290727948441437230728461715739255290181211159087121719439681704506164755242217548070573890468525019182071073 | CO_4207030810887709349633618 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:30 | 4207303161747478254806218105759211760098237205398734669708216069443169605063037035285749954070409295289892029264769451225258011366581439851453699638346245 | CO_4207303161747478254806218 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,115.266049 | null | 0.953992 | 6.27435 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:17:27 | 8981581351537683448161498881796014062362584528935976622988791593572440770186401585874449106251273110919699112809364591399410429067075774758591831653963973 | PO_8981581351537683448161498 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:29 | 4236772413018340914643316653285494850768650233348449202105844926502990848571265114793377548466239858259173425125770056710313025880606282081997189133919395 | CO_4236772413018340914643316 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
"C",
"Ti"
]
| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:30 | 4266131828980338698233340043150835826303879076920840723784097099561844507086697778199137632127250189482245796427554204888410893035261567803247774616983906 | CO_4266131828980338698233340 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| true | null | null | -1,532.934384 | null | 1.611195 | 8.447637 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:05:36 | 7699045259285853895784810466666216747721077685296184979395055741472559574609617021612484626224442328143560963538026613257507861161981714565504578991879541 | PO_7699045259285853895784810 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:30 | 4426955642600595286524181262414045866880838170834656917563840756510854146847526933393090026908247354521915534281381006496816763221121834407653592604696600 | CO_4426955642600595286524181 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:28 | 4444868112563021860808258229161393159413038961142404045830891245769020438372851623742455050270753083667648907578725583348596289363967400536203894722385972 | CO_4444868112563021860808258 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:28 | 4485232232554977779760836900310212933653605470479656377256157354699511495933479130019460374958501847528909917989029203032993506278902585186493403057976163 | CO_4485232232554977779760836 | CGM-MLP_natcomm2023_Ti-C_deposition | [
"Di Zhang",
"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
]
| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
"C",
"Ti"
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| [
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| 2024 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| null | [
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| true | null | null | -2,030.762187 | null | 1.996636 | 19.486854 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:35:00 | 10670974531745907137291656673386986620464671953063661609010713294725132471113803525339016998345709284766291334398141476031782709278278317637839217751426348 | PO_1067097453174590713729165 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_1205"
]
| [
"DS_8frq3jczb0dt_0"
]
| 2024-01-12T23:00:30 | 4489885934736848310758378750678603080800127167428765026600154181214715579960547413442195295357234839202928355113651784087244512855175809015899250763199259 | CO_4489885934736848310758378 | CGM-MLP_natcomm2023_Ti-C_deposition | [
"Di Zhang",
"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
]
| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
"C",
"Ti"
]
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| 2024-01-12T23:00:28 | 4552099075394536089793582025030028597032139772564828365297865569872717228109417794968420437852213995284605445921172710745767847630084078751988978224440355 | CO_4552099075394536089793582 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2024-01-12T23:00:30 | 4602599596249608417787774106024057955304158226346706527516467014517722216026370951635926810552251143509360300743362354801763911282114158478797578852237732 | CO_4602599596249608417787774 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| true | null | null | -1,185.432491 | null | 1.184754 | 4.552988 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:30:21 | 3354635139167938647844900987759439044459313339809469177354379359653727516756391257166183305183155273457087057560750055642696812534791028891336303555601052 | PO_3354635139167938647844900 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 4664899367372002946883983258962278217815283915623878578602932980407496767808923335354384234259296036218414959424962792903805904432035411311732220499125067 | CO_4664899367372002946883983 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -2,000.059903 | null | 2.034856 | 17.704542 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:37:45 | 2347587493756364751687579108770951409447845552715174746712184500912653616430193569610745680061078718666092493534545946588324596204172763732208375141751678 | PO_2347587493756364751687579 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 4709205964993368628362141289536508827065336581154236236037156765952012692475821107450235361735374157393493640265236672346960197902070697164647069121231389 | CO_4709205964993368628362141 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -2,017.240659 | null | 1.840326 | 13.761734 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:34:04 | 7736718144591786482085174723921858843969217894235557668712947357646203963763753811354372243922141663739527787581186791464568814321722347034867589287586489 | PO_7736718144591786482085174 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:30 | 4733024894596898014927536373367928401031227331004838477117113842390229640561599913764801891736623408611708412031910532070378699017282854995564372381346897 | CO_4733024894596898014927536 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:28 | 4764352318421763275906719312133069409141499552578538885092125769264650097735255443679469502202386012373961264921616863419080731657343894352709354536856365 | CO_4764352318421763275906719 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| true | null | null | -1,943.643665 | null | 3.261146 | 59.981363 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:15:43 | 3600635421204966567944410248990620596618400900030482020836132038490214205984389229554658476236196279951663718110432815501633120185925357636897213543352357 | PO_3600635421204966567944410 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:29 | 4770862765757155522966502248975435280802151341768749731250832547452323130376895913256095078639807411858869955798130173133874695591336020561149160399291550 | CO_4770862765757155522966502 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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"Peiyun Yi",
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,923.533838 | null | 4.12278 | 38.255416 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:44:08 | 6122862358817969870491397091004644099663627089126189913711362499504810994262375412118548197017084148949972291038361814537964832576339042332112259851390798 | PO_6122862358817969870491397 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:30 | 4810207398929545373444108931144642415212935032025960767962034162921909922318123272247914482030858727585030140359804659658227655130862819889213144712718108 | CO_4810207398929545373444108 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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"Peiyun Yi",
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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"Ti"
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,090.863243 | null | 1.010722 | 4.978108 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:37:14 | 5456178515484213896692180912801313731604736528513361308045546132957836975986595463496065740865921611799298200266102634326565967069909474782938814460226802 | PO_5456178515484213896692180 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:29 | 4819562138537067230217406961117573977138879306639158226253364828016271900673446402153457446813443030906569923396809041258170180826207178418213866858771150 | CO_4819562138537067230217406 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
"C",
"Ti"
]
| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:28 | 495811795178767556805543425203589547648182062129260555389008233206125234935662828957455800841466368484885161257673134932787883002368342181056571215452602 | CO_4958117951787675568055434 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| true | null | null | -1,796.804066 | null | 2.118773 | 24.849842 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:15:33 | 2130735599647549263066320546600942543642831449766828271731074704676469548834028027797997611233812171786872248658990717875106010609715751892089155685648990 | PO_2130735599647549263066320 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:29 | 5046989829598535236561992943419767915102435223498815596694428015349164163658606304123050120076505102846331142493878166603942501268409578477669345851246812 | CO_5046989829598535236561992 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:28 | 5074478784343614927358246870133269363933106529734612321527259851548055897100677420974414597162164295560780049404608388241910871222565626885887253461042561 | CO_5074478784343614927358246 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| true | null | null | -1,869.001226 | null | 1.467807 | 9.705584 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:39:25 | 7528237120959344753298666604950634200388991407258980735616190040143497806109734184301004470392352510285121716839659971757160302489211887448257305625994812 | PO_7528237120959344753298666 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_981"
]
| [
"DS_8frq3jczb0dt_0"
]
| 2024-01-12T23:00:29 | 5226610626053007124229608546681493457398276426240173518085926433135662947750979935210427757153661516958566871622486632068975431174179235591022995616291882 | CO_5226610626053007124229608 | CGM-MLP_natcomm2023_Ti-C_deposition | [
"Di Zhang",
"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
]
| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
"C",
"Ti"
]
| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| [
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| 2024 | [
0.27399898319185323,
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:30 | 5258875235275798895336553095703789167509830387345617470942349477359898493621016385469029342656660607791381362267745547235725922937653448547650337580271947 | CO_5258875235275798895336553 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| true | null | null | -1,850.762049 | null | 1.474658 | 12.039582 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:40:04 | 2206344295021032680127340089619724918562832678655148386218894432061530275710525226782384736687451131856744869100420226952372218968446804858163396607059539 | PO_2206344295021032680127340 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_965"
]
| [
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]
| 2024-01-12T23:00:29 | 5365381947345655097957454021656915955586845800966930481805233946803990649313498181619259223492864474797713883132193303378912753073128940960063979832962503 | CO_5365381947345655097957454 | CGM-MLP_natcomm2023_Ti-C_deposition | [
"Di Zhang",
"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
]
| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
"C",
"Ti"
]
| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| true | null | null | -1,051.166809 | null | 1.07903 | 11.626293 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:42:18 | 9505059918512268197819840555500025088807915856749528605622405154383681102302907987825627134768521829292655153792082598676463539058870420343679347507922745 | PO_9505059918512268197819840 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:28 | 5407216550435117264615435826713397645242541057170708020260890409410356356229465503919045869768848178285420256049324388937483195607547457937624697130391991 | CO_5407216550435117264615435 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| true | null | null | -1,833.759453 | null | 1.750031 | 16.999872 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:19:10 | 4499543505539589201246283574721717946459636237344111513592510628564954520753631535225192543374300946018227280313073992240090811225938104650589321018698509 | PO_4499543505539589201246283 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 5449582369947051251390760737262868073020408527459622336935002421152542800031693172518979376728330507649142260068319928535308393855890513141173355878235588 | CO_5449582369947051251390760 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| true | null | null | -1,056.277624 | null | 1.590697 | 23.084764 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:09:43 | 3693923155557671311446629063477205390610124898835054263499381260216135881388006517677160515339519156476219113342897918060636122225440755563294902251957401 | PO_3693923155557671311446629 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:28 | 5468966328123269435103750249126029178525856701813887947902432774510866011956984787120645732501202578434941559383374736573967088196767497728334786449245509 | CO_5468966328123269435103750 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
"C",
"Ti"
]
| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:30 | 5502000127386510718027009180035042927720183997842706887655466981320928790366654724772935028404928462384331033830537451232594122793354933018915995880262069 | CO_5502000127386510718027009 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:28 | 553028930433928702425492334422556282555329360427512012676167633070472212618277138162794835996574616385684455743877104280108523298600515827598040053538294 | CO_5530289304339287024254923 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| true | null | null | -1,741.096044 | null | 1.741682 | 25.415746 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:20:08 | 12721961694720124199994357235379504197195911497588175432805694094382884018295785123595108681470828535825993327874965850889695108601008605106334726978475204 | PO_1272196169472012419999435 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:28 | 5631086230926130514123103665406272690580944618998977497620761651485503389794736758298519519318555764443001879630885742381755676962460316626768099589385070 | CO_5631086230926130514123103 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| 2024-01-12T23:00:30 | 5739654841513159296930874538888212557239835041510316853218747541700155370174051449357653868198927406246873542236513403251816490702835006416253242407231784 | CO_5739654841513159296930874 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
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| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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| null | [
[
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],
[
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[
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| true | null | null | -1,665.012785 | null | 3.350605 | 66.348303 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:40:29 | 10976453302729777823064386770678382313866869404108858323187325381559117210750639441963099779737811364315411467887800576047081142605164758996021797891410602 | PO_1097645330272977782306438 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_745"
]
| [
"DS_8frq3jczb0dt_0"
]
| 2024-01-12T23:00:28 | 5747289934862210423638975967031385871266468760513125358768578756006870407898874118764821014907923602251756761185935448517900409389291661988760997716867277 | CO_5747289934862210423638975 | CGM-MLP_natcomm2023_Ti-C_deposition | [
"Di Zhang",
"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
]
| Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Ti surface. This dataset was one of the datasets used in training during the process of producing an active learning dataset for the purposes of exploring substrate-catalyzed deposition on metal surfaces such as Cu(111), Cr(110), Ti(001), and oxygen-contaminated Cu(111) as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu, Cr and Ti surfaces. | [
"C",
"Ti"
]
| 2 | 1,309 | 1,309 | 259,636 | 0 | 1,309 | 0 | 1,309 | 0 | 1,309 | -1,531.380198 | 130,134.622308 | 0 | 2024-01-12T18:01:51 | [
[
1,
1,
1
]
]
| [
3
]
| 2024 | [
0.27399898319185323,
0.7260010168081468
]
| MIT | {'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None} | 10.60732/4e8857ac | 12664052871829008670308412807702479762634432401396325426514382084783273842987956036413329734434257492339920682671966491264318791537423533526344183663319918 | DS_8frq3jczb0dt_0 | CGM-MLP_natcomm2023_Ti-C_deposition__Zhang-Yi-Lai-Peng-Li__DS_8frq3jczb0dt_0 |
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