chemical_formula_hill
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int32 | cell
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int32 | software
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list | cauchy_stress_volume_normalized
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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
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string | configuration_labels
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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
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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 | -1,994.461793 | null | 1.86079 | 14.938563 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:20:45 | 12984718569401748631391069813365286432758590962639915010473813943855810484622169102977697872861836294656073018509092847156087364502621043826350967417927902 | PO_1298471856940174863139106 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_1175"
]
| [
"DS_8frq3jczb0dt_0"
]
| 2024-01-12T23:00:30 | 5753909820991578208811715423529050291739484255324075673816554830790720904778557427006142866110479260408939853362342637977340423024691079199114290702786696 | CO_5753909820991578208811715 | 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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| 2024-01-12T23:00:29 | 5791982493991520827611357814750117700438452500677018105092293837524613553604338453258443140309477039809485743861285535794163385922977221470784140081734536 | CO_5791982493991520827611357 | 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 | 582973260671533717329308503512074179961021964504221526554066729617553177669697322120938984373025671569440099919378051946751407375025988409045823634480589 | CO_5829732606715337173293085 | 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 | 5899672507487411167700017667475861904591131785374579281000628668123426342260205165687501926322473249387426063554932237999780085949746558669587313246736631 | CO_5899672507487411167700017 | 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 | -1,252.120755 | null | 1.286024 | 15.975025 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:37:24 | 4804311447093770464018972857256251352511413418158914768515440018278146616194419743088863227417234690183145414253679495825786328618536923279392285047712266 | PO_4804311447093770464018972 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:29 | 5984353011895856643102935710463988370341090429329717664927075470697703107596727851217404406168557837438205913531773996542768412629086734866807119804700321 | CO_5984353011895856643102935 | 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 | -1,052.828115 | null | 1.449175 | 14.824667 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:22:09 | 7720244332497006308073053416307087076519921648538410999890993711644152631088881361599881272456206692570850837232171191882588480301003758918488722988032642 | PO_7720244332497006308073053 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:28 | 6010569050085809994309737746763897462664972248119921565894455705246123928390923680038660115078937512008372285124512394260029468082950111026320839261621389 | CO_6010569050085809994309737 | CGM-MLP_natcomm2023_Ti-C_deposition | [
"Di Zhang",
"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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| 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 | -1,912.731628 | null | 3.277175 | 56.389469 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:41:36 | 584931562447098603870337390940832161846571166242766781690890606686398927134935577562843847613341742335788336355905300815822965173344293455117624254593634 | PO_5849315624470986038703373 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:30 | 6023672437910441177698106014724447644545474001643925607822120397310805944999556104815571587089239218567630053802437047795074087331785781588468922110813245 | CO_6023672437910441177698106 | 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 | -2,049.500465 | null | 3.502197 | 29.60053 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:37:16 | 7686629803629826815558533701780265887015206451419615823309602615522377837376811014886004294765476551827499750399887357394499247179549998438352322274575714 | PO_7686629803629826815558533 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:31 | 6140142292187188158418714954573220748537448996687483837055266646571695050381819897279025165317647054307687954674559631791033183890270534411805323930194290 | CO_6140142292187188158418714 | 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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| 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 | -1,814.578898 | null | 1.539734 | 8.763483 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:14:29 | 4146911391188964196813156445328010207924053548061899044615216797628251977691788051700888058088980526675302245674136041534311701539460639168001356510574222 | PO_4146911391188964196813156 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_869"
]
| [
"DS_8frq3jczb0dt_0"
]
| 2024-01-12T23:00:29 | 6257128653461494013288761398440057552539896883600592361575950227227224046654014241108268058377757036636964446913972813904744058684361815462889909811441194 | CO_6257128653461494013288761 | 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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| 2024-01-12T23:00:28 | 6301197637716866936000841158576739839308572210211255857947894691052261652616833294565563729045921498430985713397191617335603100800772712825795121036276317 | CO_6301197637716866936000841 | 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 | -1,829.037879 | null | 2.955294 | 37.803641 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:37:17 | 10521152653373934491188818180857505135576828130488612229195463309601501255305154990132112189950512394057215843477039806463760492131981960411370808025123634 | PO_1052115265337393449118881 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_888"
]
| [
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]
| 2024-01-12T23:00:29 | 6335033748080809986204228579184883879082968861664698352592885107371405033003334363376722590792766571532523267022542810485198540507348839355324286348263751 | CO_6335033748080809986204228 | 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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| 2024-01-12T23:00:29 | 6361285888636762553851437567265174047830807726150792553088046921243856381233790680977143385639038547408121965876497526467153026272432543444987924184430976 | CO_6361285888636762553851437 | 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 | 6412456932526645243994680203963537854630759230930634452489177911656643974622356133018090613810003092720843448348224832782245470590360680193617086016514927 | CO_6412456932526645243994680 | 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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| 2024-01-12T23:00:29 | 6472484457727675153252043616423340779853370714605371107772702280481002120192962353992316685783127051721527778126569528100825493209443179461576842731929544 | CO_6472484457727675153252043 | 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 | 6531094826111322680723582765808129785354844309704786353518754375890498001237682114107628860780399806975611411645320884206805343508918996190312255000710643 | CO_6531094826111322680723582 | 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 | -2,056.446421 | null | 3.796041 | 42.314102 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:01:06 | 9285680459571855743475519055492712709863219112399463212881174503582008197916414419124442902721095829311707890013153149278851149981633595343305303892982930 | PO_9285680459571855743475519 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:31 | 6594145633297168200144275092045418912939954351185736956778280326364797254975523783289040428141318935079664194758441249580333395112107969630300161652146638 | CO_6594145633297168200144275 | 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 | 664839623319507625381696076950150618300376992815532053229620202797338030147776333149669135879653681350667679733903259506706926173964654153247948305250120 | CO_6648396233195076253816960 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
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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 | -1,445.947798 | null | 1.392956 | 5.53684 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:28:13 | 10250838252585144513580548883124225231377240822322547393340356103270705513426524066492018297376103406357602567575826463146679426707281895300526748362381603 | PO_1025083825258514451358054 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:30 | 6671490200251573743372692187515766426992575375323792471829613122532947720785720322249981783281627581857751751506689239362648500468693713007994884634616159 | CO_6671490200251573743372692 | 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 | -1,166.246884 | null | 1.102337 | 6.380429 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:39:55 | 12372995850676083664330821914995860264644564297497377188619775594894470365805355493543292369101731057784761826754405015108920546306531517199598582187338852 | PO_1237299585067608366433082 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 6876780774637204640958125832809478055092194928099477456040566397172083391707896170269163032815423044277887158659036495488583605295788436621095848079562669 | CO_6876780774637204640958125 | 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. | [
"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 | -1,535.962014 | null | 1.477449 | 8.75994 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:38:03 | 9649831083339719861639682356888441637757301126348193883877385873175264516665658355246377406568960006074538388577032922610902334305195670259919737653557813 | PO_9649831083339719861639682 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:28 | 6934241274718804896092320082210756121185170653789708801917943773517872983334621532257495573752796497707969884139972020520207983309926255792177779299775554 | CO_6934241274718804896092320 | 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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| 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 | 6997686713106529985819810816245940616821206937530705851430232223812129436645273758022063447316175870072123629523162893109288473927532216462299060444548653 | CO_6997686713106529985819810 | 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 | -1,177.97148 | null | 1.213153 | 8.103165 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:25:20 | 2864370767059806563556537060321378385262140142793499084664857913555431611422077577309895696508412272876302542524070561199138734850045511874280047881915275 | PO_2864370767059806563556537 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 7150903216034257110024898629356849869659755987995566835571703581788381609819373657461245750970079891813327446175496827464452641918196138629481715736075629 | CO_7150903216034257110024898 | 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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| 2024-01-12T23:00:29 | 722927364802943713509853452863869944133959227484658059293031678024800911050432296057275254490823415939353277111168777661051810395361357568831413829075794 | CO_7229273648029437135098534 | 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 | 7241804501447821548196552896165626402939558870604985657768694897831521172645561145354988714150604650401449520607902152080206448337847229438637185617033512 | CO_7241804501447821548196552 | 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 | -1,622.350564 | null | 1.271134 | 10.720794 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:23:42 | 6440021316042323178663254799231044905935333087658191961879877191728654555578519666334694371240319852863473632086552926341325300209840719905400584637062415 | PO_6440021316042323178663254 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:28 | 7296847608863463009379460856515875277376764071551150969712904796796361751233902152042603149304272728315661786302079862828973278233368567801766120877361534 | CO_7296847608863463009379460 | 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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| 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 | -2,036.456343 | null | 2.045443 | 20.720664 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:25:07 | 10235113525802821962172375416490635205632034305446688925702411612729465569707184785373882085188761902376914263976250276095339961103385998126282541919082958 | PO_1023511352580282196217237 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:30 | 7303979999975316015945486489632593079013434936080040412261765568185274805047649592330030776969238094151936356939349061552605933559700763003292993983650578 | CO_7303979999975316015945486 | 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 | -1,867.299213 | null | 1.625526 | 9.094519 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:57:23 | 6485925691645018655107602325351701976642987476988090714842063231510859035973578054022780580907555918079489065612926748609517570789143041396245299965320103 | PO_6485925691645018655107602 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_974"
]
| [
"DS_8frq3jczb0dt_0"
]
| 2024-01-12T23:00:29 | 7412626972704518893521339847469068756487570322681280306871120635929704021544185535033545113436456567566210906297757179802906304165306057646984306894815119 | CO_7412626972704518893521339 | 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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| 2024-01-12T23:00:29 | 7421403386818253898603565606298254134953777856202955491537903480897174480077854946390189471670367314521848238566639901315358839571949829544124388370362956 | CO_7421403386818253898603565 | 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 | -1,389.312257 | null | 1.228135 | 4.502164 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:33:49 | 10394218348929964430369387086807935462939091783609825050395675419722543817981096424004822311114462356080554036042862595381907649085885553117487719370216036 | PO_1039421834892996443036938 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 7434173814261626815745470557199746156158316420461450849247410122895793577286723604840595405642819508365817186660030029989598721036342123676857988028764724 | CO_7434173814261626815745470 | 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. | [
"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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| 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 | 7485481145220976447332996955989541886762372572244685239295900925431914557351307436278912186750485534360126388332126726790882063006719092989798099024302798 | CO_7485481145220976447332996 | 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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| 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 | -1,906.614243 | null | 2.809563 | 39.129645 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:41:50 | 6611416785865879372975945047722278840115698373474135816128687204548594747974856918707861826302433791269347581733277586009340218941159204818594520253063775 | PO_6611416785865879372975945 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_1123"
]
| [
"DS_8frq3jczb0dt_0"
]
| 2024-01-12T23:00:30 | 7578946656609139805046587410122110244344582293268349058816730272996175624045607332148053920381660363468015841804970506496880793232331319444035780806185031 | CO_7578946656609139805046587 | 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 | -1,758.164384 | null | 2.863157 | 52.403677 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:51:28 | 9266082513043440877559809068716723111640854306645291628353502602801740873111229644976060124785309969340912645358651444457148350783430738356922420704652181 | PO_9266082513043440877559809 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:28 | 771643003125144492764947687241325971923604040385947274661346810769180272744824994525917663298735379883727195487266901751656677199734690939951919130979182 | CO_7716430031251444927649476 | 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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"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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| 2024-01-12T23:00:29 | 7767630093819933275949165366445496328416888382620837097466569705953237022264994672514352799026509244030879581292543032314918946117312239391178505988709993 | CO_7767630093819933275949165 | 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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| true | null | null | -1,452.458527 | null | 1.33681 | 5.27369 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:23:06 | 11795603449694902908656591348599785848884533367328066377495753343870262941831867411382172571030485511993397135133827275201909657746998940928222041408805013 | PO_1179560344969490290865659 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:30 | 7801334271726923390297471598272710440782980071727275490450025302733610017785852375061387722386506938799939905802973383655219894045881201671525496586578446 | CO_7801334271726923390297471 | 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 | -1,847.161347 | null | 1.619461 | 19.327764 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:34:44 | 8782282331693632513112809975065827577464954831731091709446856971364017359524583064278137988211121398719922191596820873302986381222568212162991488504401428 | PO_8782282331693632513112809 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 784692444905893949439180891524888235224056392637476750108080745047225978736069073655658919306762853687175213294057420788603270134776491787937975667308677 | CO_7846924449058939494391808 | 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 | 7953907069260387617038171636694703604322228502478737555887451322077755164709007684278593831765593041919910406572092653563310856034641225426242557704495499 | CO_7953907069260387617038171 | 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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| true | null | null | -2,019.390178 | null | 3.124822 | 24.042702 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:27:16 | 12569578980162169394050054561364271328525312693279003150649898635591669211559298205802795099084320870558268813649745938944262595737150146838292890425987055 | PO_1256957898016216939405005 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:30 | 8021051917665351388740319584183011367215093916468459230721763051841787261507816426052688278783852335578948275865700365617290815555030898391553419265743659 | CO_8021051917665351388740319 | 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 | 8139986977521712834900324737995498580969806340647390724425304067225687707058023357433184175618889501096089772807182026308754873083097419173013306693814325 | CO_8139986977521712834900324 | 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 | -1,609.75016 | null | 2.0983 | 66.666209 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:22:02 | 11565329529725996302641714098862647851365345387303693308476752524870952364288366668303699265892618775922655374464198107351949646690496822676831942494154899 | PO_1156532952972599630264171 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:28 | 8240264167820457033264804052645228937800744963542022098938772128308530328973465690019505952108366970422534346817215493152390467789313456457213533733321539 | CO_8240264167820457033264804 | 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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| 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 | -1,063.914164 | null | 1.27812 | 19.68786 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:38:38 | 12556482152850839985447683103399358614539413167041770695764682513018518197138885394611504350669755218794569334317693583736428312557789137069465922270413562 | PO_1255648215285083998544768 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:28 | 8403739685748244261377091058656086844064708992428844731698426865016174954902671947582620316308538727573879870552188014880728534778276404141994575212079353 | CO_8403739685748244261377091 | 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 | 8468382928646083051662838513638849449729965041356919606792280971517328882092508479501188177680213605443448019095263024044428704218347834069839143262894965 | CO_8468382928646083051662838 | 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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| 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 | -1,067.376175 | null | 0.934888 | 3.581036 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:22:53 | 2274389180106776608910983953133267426959210569470612765210417709003786822191902186345343609737555478055741327665344121112840463073636129639750887323787841 | PO_2274389180106776608910983 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 8492336330338002331370383467782323345348660759993002320461370096853506785127026854224298930541655370305215689069535156116745215555825140170653546401934015 | CO_8492336330338002331370383 | 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 | -1,187.324899 | null | 1.12912 | 4.687917 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:23:24 | 7242128811818640910265584189922271707282547233247151466564464672577551337744877312419155719910242565315975670416552224612227145853575898423225855540470255 | PO_7242128811818640910265584 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_337"
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| [
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| 2024-01-12T23:00:29 | 8589799697110364068024709514318485828743150396606524885892087180633333966338758947974580095149295947857408070123358526347021691839197658427808331088673886 | CO_8589799697110364068024709 | 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 |
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| true | null | null | -1,252.288652 | null | 1.263003 | 13.843498 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:38:21 | 3998257878197915061576603910396545071149344427768248942389797983082064937693323056640761358583317747857182897747585873162085275138615506407337914363664270 | PO_3998257878197915061576603 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 8719283653199076214092415365610104077708768670166190963133583731051157517358580459698875069711479677457619823789033011841364874394345613764295353688178436 | CO_8719283653199076214092415 | 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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| 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 | -1,983.166869 | null | 2.122169 | 17.777033 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:44:12 | 10028787848364056802841449855791303847317545086292771729899791148255083027513575424270429505246029424007179401352313137350657604496180539182421521448156808 | PO_1002878784836405680284144 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:30 | 8804103969043709003454310231651195407882599914313634838029728356732840095858568457439130618146352448369341148347591179768448384005116298136250354661464513 | CO_8804103969043709003454310 | 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 | 881996527713260310212716023705828931925624300884081592132000825001266519411011029402428268961497003934639678816313143730600050784329816402810959802153014 | CO_8819965277132603102127160 | 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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| 2024-01-12T23:00:29 | 8824441924576394641595764043684142214186343947056925229979163607449771587392192333667133783895350207886301354207481311791126076965966142599532243941154926 | CO_8824441924576394641595764 | 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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| 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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| 2024-01-12T23:00:29 | 8851792083353828067969170049382672259364776947385247818198537157398460249588326218848071369481514794402605010465512265469543397224139951687810980772446626 | CO_8851792083353828067969170 | 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 | -1,367.483218 | null | 1.359784 | 6.170931 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:27:40 | 6358081206824567095507613998831586220539921260843987160310641371430862049723091006086570911674757170413693449466494866035944720273077312054245845763290190 | PO_6358081206824567095507613 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:29 | 8927842667574845328766829131304624107113372508658462456696497499011461729079546728878851048930621824547976052971621774087040979088243398563005974030330884 | CO_8927842667574845328766829 | 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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| 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 | -1,061.025965 | null | 0.936416 | 3.091184 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:44:25 | 2479337270624264564892198962935002077804660616685633560000398325447907122740213022013939554615101064774656934539149781306584344725814223722974264805167534 | PO_2479337270624264564892198 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 903660475748777168245433854098250645502973479540104031115528248242355475571345431489766673947431673871898725829317655630547890093637855766817789632956006 | CO_9036604757487771682454338 | 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 | 9083116254189100736006098231861408354602337411609825028204916167132027153226621535527130994048220439641079045917003410759596940005442774890400276554042900 | CO_9083116254189100736006098 | 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 | 9139832480877913782556909622985587420582081153813858935832911452382504040994406868976288582082656032074880785744060681530842726274187655749178066802756636 | CO_9139832480877913782556909 | 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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| 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 | -1,961.671691 | null | 3.609539 | 51.119187 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:26:50 | 4474811799125112871777441233277319784446883316755975621051437465780072596901028655092693050969352603386946704458458482633124917757688813473456566560381499 | PO_4474811799125112871777441 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_1108"
]
| [
"DS_8frq3jczb0dt_0"
]
| 2024-01-12T23:00:30 | 9193991125399246204469400607885389446684826877252709228005062032813783106820766988306901203992864136668748606019543741901488743030195684265033363068781111 | CO_9193991125399246204469400 | 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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| 2024-01-12T23:00:29 | 9358001216440330097371176724695394043545446958209804656245018026143345190429749404753046677209371001964889627174381106106933264576695289271465448129363340 | CO_9358001216440330097371176 | 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 | -1,072.92403 | null | 0.89864 | 3.910465 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:00:55 | 9273791425817726652333946461922601788357718489213453114677039205723868059671791330144591442068417842359406379293439198795138068994790534568000341294523865 | PO_9273791425817726652333946 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:28 | 9377631645770514894742184588212358258718491882356876445252330578326323500423323338161033271175999403959511807322747319109320100195368833261328091763496361 | CO_9377631645770514894742184 | 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 | -1,074.301837 | null | 1.255961 | 16.373194 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:29:10 | 6852504015481089079223523218090705160009906546756267328825638496653695643864675849148375159356381761989185814356057970438609659236591909832447696012839161 | PO_6852504015481089079223523 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_110"
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| [
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| 2024-01-12T23:00:28 | 9417591072556576899519131500904303707603385476420001650237608200288565298202012990525476514084516758296387081673680322858369605100189467039413548721016769 | CO_9417591072556576899519131 | 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 | -1,871.017485 | null | 1.861924 | 18.430086 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:00:33 | 11908329525743260422335130175096794121782149586748174726920437613594852368711508513197471326287322861055733368210277261207458314746554403072763118093035660 | PO_1190832952574326042233513 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:29 | 9491322316087505347596718811690095025070613671101745227579875327190783030248687015303855987678744030674207785494484345503645182889731179295435790764731459 | CO_9491322316087505347596718 | 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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| 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 | 953727879420219568010744676371141145963688027897794464020108842151682391865124852370337941790253096491400612204645936518644960389492609616987955731238882 | CO_9537278794202195680107446 | 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 | -1,348.482284 | null | 1.56156 | 13.634453 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:01:05 | 2950866814944577711802511362773464066083407809505077952909178973657942506800131767161389203930693839454744535155736630330797512259509376382310802742323566 | PO_2950866814944577711802511 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 9547743693224270690336769343199239143470035329410276222420742076702601058575909169857124931884608722503077744204450429756124246906352047426450032570609243 | CO_9547743693224270690336769 | 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 | -1,825.848774 | null | 1.364409 | 7.736215 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:31:44 | 12360773828203608119912329334813047368373175744804231624993575393187373570695334806171730123593387868663118425751633782860211653508745384990135856531006674 | PO_1236077382820360811991232 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 9554585431422598582370134881426767748476101608154197308827259264899170162636775476572851814428688795923739828063817779190460882083596743752986476948701559 | CO_9554585431422598582370134 | 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 | 9625048879775281514938044780113919059790610712914373979527928288557674949538604480957271692437399209774941228485993822990588857428018312833204273753055585 | CO_9625048879775281514938044 | CGM-MLP_natcomm2023_Ti-C_deposition | [
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| 2024-01-12T23:00:29 | 9706767827037929093537176847626816880706889412970981115518066451523721309261942876326546949747753194865185540771200752650365290699644838441804483195113616 | CO_9706767827037929093537176 | 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 | -1,399.421076 | null | 1.22361 | 5.554353 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:37:48 | 220643892755084444411688285770528345326299578983973206712607791430053207218361004554568025199014384829685296220666714516787504718005450519914887106047006 | PO_2206438927550844444116882 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:30 | 9710929558588310429266718604877618501047434090653206987560633240580704049004749574706319947330786722400853168631726209380556555174269187701156664006625952 | CO_9710929558588310429266718 | CGM-MLP_natcomm2023_Ti-C_deposition | [
"Di Zhang",
"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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| 2024-01-12T23:00:29 | 9797319893282609616806574621435755461657511607887953204051235528878187066217217103437895592475534697996170515828366902220403307830834981006144844411134336 | CO_9797319893282609616806574 | 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 | 9873037343057596928765791378800793078897576240005112234372180054990871873966123147604398352184055367278353268796437047754013237588104253509941826495487666 | CO_9873037343057596928765791 | 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 | 9916745039662783703016430969816357895536166726896682241287483260925699297483722773347961189488420130881013362399738538357781553240366016591610655999867932 | CO_9916745039662783703016430 | 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 | -1,848.237444 | null | 2.368449 | 47.600692 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:38:13 | 12766006229875312816716858191131047775833263152006170552711519253962935528652688879056328301097577333431904605798761982801087798638643628601584338789975020 | PO_1276600622987531281671685 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:29 | 9921453521162154618913142941899512404677749677278777061371011126883911840687692873843957506208199548708196497128394735242237591417865357429135218029951645 | CO_9921453521162154618913142 | 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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| true | null | null | -1,474.410778 | null | 1.425229 | 7.337877 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:17:20 | 713418226231405959537912018449586368233315201759173493867675788271057037096686310620540468738116439717450064077836112592353119960046496704721458981131718 | PO_7134182262314059595379120 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| 2024-01-12T23:00:30 | 10000090087995196352316501659326590220994557250083013221221000773365790051020714867953444682847628303342055174042314795564186085514365969245595808277981189 | CO_1000009008799519635231650 | 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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"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 | 10015467341426911302422674367708602582731265175059782220069449771301720050293059989456452509150676618220825970143306827220477044517789550530127748668409688 | CO_1001546734142691130242267 | 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 | 10017992669708624867343448690355100789383806278383036300365771010122510675274730730912379683858930630552092215604464745016154165664540087540291644280733587 | CO_1001799266970862486734344 | 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 | 10031475516017384964028602738258955844400119121718528966181853202027624767451826514350893794991680877999248668189417918808809864225591306866130528758111817 | CO_1003147551601738496402860 | 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 | -1,614.007416 | null | 1.500795 | 14.468285 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:26:45 | 171752852710295350032225018775371585084053872548662015822008043386458965315357489637763758044087164793108148010016278682231121667083176889079523298763556 | PO_1717528527102953500322250 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:28 | 100356836615915015553265064719209859919483170433034794344256887007225576477641689446044098984182145698860948006486553053455462865455336645486147788480641 | CO_1003568366159150155532650 | 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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| true | null | null | -1,967.277478 | null | 2.977109 | 39.459471 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T14:48:35 | 8889476902560699806257388049137887093876191747568931214400908462870219813876596322866621770752994112197054509887217008020332587383299883898924914647367444 | PO_8889476902560699806257388 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
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| [
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| 2024-01-12T23:00:30 | 10056930650457947203051855091885689898859843095675459382502797513904888827818047345902876296478280790438464068104874159876478397918839104821794068977279026 | CO_1005693065045794720305185 | 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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| null | [
[
0.052049,
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],
[
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],
[
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| true | null | null | -1,995.538834 | null | 3.393314 | 42.512573 | {"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_4178802015180711158523341"} | MD_4178802015180711158523341 | 2024-08-16T15:03:58 | 9110803862491358761555599229662991565351673598646448893035899744983616368461489204168249889787064576741720855742589221834451764050318010164655773125093626 | PO_9110803862491358761555599 | {"config_type": "default", "hash": "1404919777827893392269834943670411845301261407866846710153021606405314199411070807160658984221877463606755954368807568728599557946099287677348404211930695", "id": "MD_1404919777827893392269834"} | MD_1404919777827893392269834 | null | [
"C_G_M_-_M_L_P_-_T_i_-_C_Training_Dataset_deposition__default_1196"
]
| [
"DS_8frq3jczb0dt_0"
]
| 2024-01-12T23:00:30 | 10080757563792914022825382105804228891684553783704136632187119314862330542625837017182848477280650981130492800679972401660169305330524089727302280885210504 | CO_1008075756379291402282538 | 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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