chemical_formula_hill
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string | chemical_formula_anonymous
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int32 | cell
list | positions
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list | dimension_types
list | nperiodic_dimensions
int32 | structure_hash
string | multiplicity
int32 | software
string | method
string | adsorption_energy
float64 | atomic_forces
list | atomization_energy
float64 | cauchy_stress
list | cauchy_stress_volume_normalized
bool | electronic_band_gap
float64 | electronic_band_gap_type
string | energy
float64 | formation_energy
float64 | max_force_norm
float64 | mean_force_norm
float64 | property_object_metadata
string | property_object_metadata_id
string | property_object_last_modified
timestamp[ns] | property_object_hash
string | property_object_id
string | configuration_metadata
string | configuration_metadata_id
string | configuration_labels
list | configuration_names
list | configuration_dataset_ids
list | configuration_last_modified
timestamp[ns] | configuration_hash
string | configuration_id
string | dataset_name
string | dataset_authors
list | dataset_description
string | dataset_elements
list | dataset_nelements
int32 | dataset_nproperty_objects
int64 | dataset_nconfigurations
int32 | dataset_nsites
int64 | dataset_adsorption_energy_count
int64 | dataset_atomic_forces_count
int64 | dataset_atomization_energy_count
int64 | dataset_cauchy_stress_count
int64 | dataset_electronic_band_gap_count
int64 | dataset_energy_count
int64 | dataset_energy_mean
float64 | dataset_energy_variance
float64 | dataset_formation_energy_count
int64 | dataset_last_modified
timestamp[ns] | dataset_dimension_types
list | dataset_nperiodic_dimensions
list | dataset_publication_year
string | dataset_total_elements_ratios
list | dataset_license
string | dataset_links
string | dataset_doi
string | dataset_hash
string | dataset_id
string | dataset_extended_id
string |
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| 2023-12-01T23:04:56 | 10438574667465648757723052753854041861497482823707790861966130144799719447635814106005493354617225345562197728485233446042912180017916812957780976181921103 | CO_1043857466746564875772305 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| null | null | null | null | 9.108549 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T14:15:37 | 6787053239490694096349865368344818168736806561317825312489614664766949362496349207110571115326168236625437893067417942993434447484494198062161387264951653 | PO_6787053239490694096349865 | null | null | null | [
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| 2023-12-01T23:04:57 | 10441976165646839214612362764681637052646647253644309525056421821581965149528174441618179788690950643430646277590895914352872681882371557442173576242946010 | CO_1044197616564683921461236 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
"Alexander Lindmaa",
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"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
As2GaSbSi6 | As2GaSbSi6 | A6B2CD | [
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| [
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| 2023-12-01T23:04:56 | 10442727096666236829377940802804195230559599395978075992890123265680011682974325277979329036857517637759816781410676312894185376539527080582674428266689388 | CO_1044272709666623682937794 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
"Alexander Lindmaa",
"O. Anatole von Lilienfeld",
"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
OPSb2Si6 | OPSb2Si6 | A6B2CD | [
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| null | null | null | null | 4.466476 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T14:16:21 | 2163439792155062767805640858824437234222200125993460960382883130409547583836954939149493568792345491678418723304392987025712838416579478222755269816348921 | PO_2163439792155062767805640 | null | null | null | [
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| 2023-12-01T23:04:57 | 10442921867598235601569792827380590554324413235581960458262025843937803795866669076372666078623470940357876914455605059131576205256255845149859906507235690 | CO_1044292186759823560156979 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
"Alexander Lindmaa",
"O. Anatole von Lilienfeld",
"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 2023-12-01T23:04:57 | 10450124470816810728854016281798653336803578568835804940809123287083635495658517148277156305118131151689784032325706332292851452451511277926300293138535426 | CO_1045012447081681072885401 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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| 2023-12-01T23:04:57 | 10466479909597538780310500211376311585798493178376231990588095022831488938221607537052665604587225816204982640624624436986509706760077735633134561341743330 | CO_1046647990959753878031050 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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| 2023-12-01T23:04:57 | 10469527118786599624620155642896223424445059388884619243974093838311696658316142069866332550144386445184906138715613523461351508537042311048935458141203759 | CO_1046952711878659962462015 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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]
| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
As6OP2Sb | As6OP2Sb | A6B2CD | [
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| null | null | null | null | 9.818345 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T15:06:03 | 12512669242409085381625999796544773858112301852644855085494076679090626458687840543303874186476949870238862158566531396540363886997378876846364001980018194 | PO_1251266924240908538162599 | null | null | null | [
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| 2023-12-01T23:04:57 | 10478081219571503219908650391452888674021020403178135539236509428646889817133917041562531072232307100734292932813978901874810912111576581492000936761991752 | CO_1047808121957150321990865 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
NP6Sb2Sn | NP6Sb2Sn | A6B2CD | [
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| [
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| null | null | null | null | 9.282632 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T14:51:38 | 6923890110151405991349787180146026541483794015763913257196198121797856827430642327567212176635657203420048967359253539483281956829675707651884372909319143 | PO_6923890110151405991349787 | null | null | null | [
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| 2023-12-01T23:04:56 | 10480078495371732255893797689834998776374981375139375820193140247963670830337261884626686101831239753814585412544895742919821069017007910016239911655724953 | CO_1048007849537173225589379 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
AlGe6Si2Sn | AlGe6Si2Sn | A6B2CD | [
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| [
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| null | null | null | null | 10.149369 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T15:23:57 | 6486925818482084336300081144599558808028809846018476346708969991806776124732385505146540057739800472105590499458683742619250865384750003410728010047773909 | PO_6486925818482084336300081 | null | null | null | [
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| 2023-12-01T23:04:57 | 10480773093339662881651399418573195589475096641822399927197057451019167355016348368278159830826374171832522375978206711713855475448213515791380363327009614 | CO_1048077309333966288165139 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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"O. Anatole von Lilienfeld",
"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
CGaGe6N2 | CGaGe6N2 | A6B2CD | [
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| [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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| 2023-12-01T23:04:56 | 10533068456210223473961156558285367826485618597745597494220578561594840603762381310769532437352827164644928168501332659526261594186435898985714705701850615 | CO_1053306845621022347396115 | ABC2D6-16_PRL_2018 | [
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
C2GeSb6Sn | C2GeSb6Sn | A6B2CD | [
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| [
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| null | null | null | null | 20.644513 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T14:16:13 | 1652510253696389795170701367128758933630745114545301178780291559674844679321283557352100666780827432358371902714414143750237187438998869514956847677022434 | PO_1652510253696389795170701 | null | null | null | [
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| 2023-12-01T23:04:56 | 10538502414193946159886549027710160412672713223040235477629897876219254598711277408340029654009991778539611459373658145727883940952410075009012913585998629 | CO_1053850241419394615988654 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
Ba2Cl6RbSe | Ba2Cl6RbSe | A6B2CD | [
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| [
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| 2023-12-01T23:04:57 | 10541011886687643379386146564972551221112851151643675528240109210927197972653021680509782265000151055957404840640455020698712140066200655465208013084889878 | CO_1054101188668764337938614 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
Al2Ge6SSn | Al2Ge6SSn | A6B2CD | [
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13
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| null | null | null | null | 8.271444 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T15:29:02 | 6704663939439780095716727994533773008292243320155599419775249753885081539938539850578112486692341449897147174767952720318660732172107604723480252980459636 | PO_6704663939439780095716727 | null | null | null | [
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| 2023-12-01T23:04:56 | 10546186209276927875036423606533781973256006838607059909111595336728167630881888284930328231004355037823229360222666766421165497502635543859856320163614753 | CO_1054618620927692787503642 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
"Alexander Lindmaa",
"O. Anatole von Lilienfeld",
"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
ArBeBr2In6 | ArBeBr2In6 | A6B2CD | [
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| [
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| 2023-12-01T23:04:57 | 10554410073058318324591234136718319700856866207537517434738260571094255244717608347671273688926356378235158247635507555945758402092336259200983807241142922 | CO_1055441007305831832459123 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
Al6SbSi2Sn | Al6SbSi2Sn | A6B2CD | [
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13
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| [
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| null | null | null | null | 11.263346 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T15:19:15 | 2022799783693996634782808453457549868137048046985922766994359221076082990659694842980454450649885273040338063288827033860151545479442207120416790332422050 | PO_2022799783693996634782808 | null | null | null | [
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| 2023-12-01T23:04:56 | 10554695420451432109868929759952431481403711734934387849561596835959965527852864220898014188365750175436612283833580875101576304083956398153705620226107209 | CO_1055469542045143210986892 | ABC2D6-16_PRL_2018 | [
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
C6GaS2Sn | C6GaS2Sn | A6B2CD | [
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| [
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| 2023-12-01T23:04:57 | 10555040057390444225126905314565327645904103158171345764306163132398924726154899762462520090593953391270410829238302318261369764297555060688897645632595954 | CO_1055504005739044422512690 | ABC2D6-16_PRL_2018 | [
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
He2KrSe6Te | He2KrSe6Te | A6B2CD | [
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2
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| [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| 2023-12-01T23:04:56 | 10563378858642237996432037031935073445152517677572548948839845304590028000564565634126142538766607801431902209834168350947429082785790710499603743283818786 | CO_1056337885864223799643203 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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| 2023-12-01T23:04:57 | 10563676588963730413141031912567880449949439407146286384223884327977767623761486383608992174364554044933848535362177634236205380596892004144152479846010857 | CO_1056367658896373041314103 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| 2023-12-01T23:04:57 | 10569261203000476564582053368443099233175608234909458722705526625392870176889176764508623244553953203352033385045745708532871781655604316924988964012805047 | CO_1056926120300047656458205 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| 2023-12-01T23:04:57 | 10578975158743628725500747195461185994320838712351342211737058468603520561397907950119948591728167881550636352236471635674576039578514605910890460954142537 | CO_1057897515874362872550074 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 2023-12-01T23:04:57 | 10582445689238483062332291206625012998637202476632069886856103540108850751991963807345666977917351010603934389584123717247782533131296091282182627853737727 | CO_1058244568923848306233229 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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| 2023-12-01T23:04:57 | 10590260270698054690718249695962799838843647889869098434926156921024020355759358131911203132071975949642376532859388196406856170119838513866955488796210572 | CO_1059026027069805469071824 | ABC2D6-16_PRL_2018 | [
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 2023-12-01T23:04:56 | 10598576765463501252010564102077909348808253808512558948035162998307308711687654188790612730030774915404391595738332715962353059138047028692852850531484869 | CO_1059857676546350125201056 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
NO6S2Sb | NO6S2Sb | A6B2CD | [
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| 2023-12-01T23:04:56 | 10620779395940435459399424068771352837632264094897609831204633126012997821896436256244641530254957131050110459706994899317086882288714680444561353640114141 | CO_1062077939594043545939942 | ABC2D6-16_PRL_2018 | [
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
Al6Ga2GeN | Al6Ga2GeN | A6B2CD | [
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| [
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| null | null | null | null | 2.52173 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T15:22:11 | 501051304835944377529340760564644507573632783460344216761326536169513317425795643262906610647067639583150361889568507166093454002967484861002419917801701 | PO_5010513048359443775293407 | null | null | null | [
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| 2023-12-01T23:04:56 | 10630961452455974781566914938810212663867707015558469568431892326013942733942074378005842530245773549012700635816569485874039241851452585790824395906298468 | CO_1063096145245597478156691 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
Ca6CsS2Sb | Ca6CsS2Sb | A6B2CD | [
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16
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| [
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| 2023-12-01T23:04:57 | 10631244391617074430461664134794736526056889012154537500459011882407029164307687064320065444707869373521739512871814958594786450629769001504393273652263293 | CO_1063124439161707443046166 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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35
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| [
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| null | null | null | null | 4.025161 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T14:50:28 | 3586628714306181649592043612093980485276316700167986756517212786462405532374253541837847717168353806504545221108729880595106308426687894019167902436127708 | PO_3586628714306181649592043 | null | null | null | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 2023-12-01T23:04:56 | 10643783835086655019912162011513689193143432233840669771757931845045643177952175150665016158485894619093748659530848403444000132086896318381825660483655385 | CO_1064378383508665501991216 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 2023-12-01T23:04:57 | 10654412743433184262622914432642491658019398762862985049117759989073244653256171649089083922989281573723175265904207418265774539608843186056703690857852465 | CO_1065441274343318426262291 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| 2023-12-01T23:04:56 | 1065593619504215222146252657604578101166811731730002040587602631684291312764698608468353114224350390921789185353565113975890831437166534015776500322617521 | CO_1065593619504215222146252 | ABC2D6-16_PRL_2018 | [
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
H6Se2SnTl | H6Se2SnTl | A6B2CD | [
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| 2023-12-01T23:04:57 | 10657877689420180870910655134951956674523932483845163313961518714844301971822038503136545021546840789774545039793591215708766015448003352979339839975207080 | CO_1065787768942018087091065 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
ArF2Ge6Mg | ArF2Ge6Mg | A6B2CD | [
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| [
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| 2023-12-01T23:04:57 | 10665748841896466694360311205707470914128550536206377112437466143722177498343801809047967885290545622295142710248952967750796248245657136723021161287951950 | CO_1066574884189646669436031 | ABC2D6-16_PRL_2018 | [
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
As6GaSSi2 | As6GaSSi2 | A6B2CD | [
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| [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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54
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 2023-12-01T23:04:56 | 10724766824577420012708213934300446753520031880501657701507346458821388566228059504972619137333164980673136790435913127377219221636045338079732536850700279 | CO_1072476682457742001270821 | ABC2D6-16_PRL_2018 | [
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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CAlAs2Sn6 | AlAs2CSn6 | A6B2CD | [
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| 2023-12-01T23:04:57 | 10728511647267560840220822310630651246164941744408016630375855958030728453701172115980155757347852857588643364802538201787858848187497525696723090737172018 | CO_1072851164726756084022082 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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| 2023-12-01T23:04:57 | 1073302780921998993345282471801900671132496769269912046989093854009672710929741594234744343296036248153026710077944055878472024340637842872452800794241114 | CO_1073302780921998993345282 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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| null | null | null | null | 16.958581 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T15:23:34 | 8120300965977899222831075228025538517592497802477845557135710836802542283048664839777101689631448498698231177330937614371986180644931442572498452014405868 | PO_8120300965977899222831075 | null | null | null | [
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| 2023-12-01T23:04:56 | 10738428519183278636364586358606877838782470443209552818872359537559818661603171668516316485770100437730756557460033064417107065698338686914240908396674527 | CO_1073842851918327863636458 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| 2023-12-01T23:04:57 | 10752878920866369098032610116449990944112747105882204814847996237168353650073064837536077345733911779348800715262875160551610763479058613948652864533206217 | CO_1075287892086636909803261 | ABC2D6-16_PRL_2018 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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]
| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
AsN6SbSn2 | AsN6SbSn2 | A6B2CD | [
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7
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| null | null | null | null | 12.666851 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T14:17:44 | 11331566670224616353903062501640884740370968802255541044834298422542088366648491620328976959195620824231508191633165615136887608273343115950463802503998864 | PO_1133156667022461635390306 | null | null | null | [
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| 2023-12-01T23:04:57 | 10773427900524406407933400362186768047803442566086759537082078668732122719596229266415873942143462028404331043349728366130387001582920290910166285569972231 | CO_1077342790052440640793340 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
"Alexander Lindmaa",
"O. Anatole von Lilienfeld",
"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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]
| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
HBa2LiSe6 | Ba2HLiSe6 | A6B2CD | [
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3
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| [
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| [
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| 4 | 10 | [
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| null | null | null | null | -5.567051 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T14:38:40 | 3010412171775827666623729787520339410693396741950478633343257752684561435583452409224776356482939331164490908039323111138199424674879856017139901817025261 | PO_3010412171775827666623729 | null | null | null | [
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| 2023-12-01T23:04:57 | 10773859603016894042016642891315246639799679732633951249072748784592210354956666747932212902777657270404647658999259279063419524442959347652746367867459456 | CO_1077385960301689404201664 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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]
| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
[
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
AlBa6I2Na | AlBa6I2Na | A6B2CD | [
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13
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| [
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| null | null | null | null | -1.634546 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T14:36:56 | 7973676628474090348777552571088963597357370344865384388541899580221068117624335067786340516387130982916320599424904258106121182118471803528782949469968316 | PO_7973676628474090348777552 | null | null | null | [
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| 2023-12-01T23:04:57 | 10776401122620962083315183377628940710361332708282196490557625988240238194626095017925462429540383495266655113849460707624461569733549061099838112190048160 | CO_1077640112262096208331518 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
"Alexander Lindmaa",
"O. Anatole von Lilienfeld",
"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
Cs2KPb6Rb | Cs2KPb6Rb | A6B2CD | [
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82,
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82,
55,
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19,
37
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| [
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| [
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| 4 | 10 | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| null | null | null | null | 5.570944 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T15:16:32 | 3326372074295997083457498014705441174928608688142723223883750271069391910845621472672442619388514388674437322078166846945699051052344000078711100243174788 | PO_3326372074295997083457498 | null | null | null | [
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| 2023-12-01T23:04:57 | 10798407200280545759437761871469513812999297960525941907054540839187166349144219975512806548386091214065717445688834880785126046099162060544893750552303084 | CO_1079840720028054575943776 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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]
| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
HCs2Ga6Ne | Cs2Ga6HNe | A6B2CD | [
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31,
31,
31,
31,
31,
31
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| [
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| null | null | null | null | 1.906814 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T14:18:59 | 5882636888081329280180664766144349336903504001152856816598276395302843515786574707685839021401844001056951108923800773090900078474212176141533127620574489 | PO_5882636888081329280180664 | null | null | null | [
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| 2023-12-01T23:04:57 | 10799085442583072967933389763524547910119992783185783283159622403234401097219199871856190637671682083610302782422990458969546941668065642072232365023027480 | CO_1079908544258307296793338 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
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"O. Anatole von Lilienfeld",
"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
F2KrO6Rb | F2KrO6Rb | A6B2CD | [
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9
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| [
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| [
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| [
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| 2023-12-01T23:04:57 | 1080211095762107033697129684855805209699131235712043731889616664312205646933660737728397838012472095156732753843135230952461232815327967094561559229142199 | CO_1080211095762107033697129 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
"Alexander Lindmaa",
"O. Anatole von Lilienfeld",
"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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]
| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
[
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
H2Na6ORb | H2Na6ORb | A6B2CD | [
11,
11,
11,
11,
11,
11,
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37,
1,
1
]
| [
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| [
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| 4 | 10 | [
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| null | null | null | null | 1.040611 | null | null | {"input": {"encut": {"value": 600, "unit": "eV"}, "kpoints": "3 x 3 x 3"}, "hash": "3729522099721817188397416740516810902027432225271784584363856857132107150877135363641369004947328165181781344107197484170910728217675499016271602255113675", "id": "MD_3729522099721817188397416"} | MD_3729522099721817188397416 | 2024-08-16T14:57:04 | 542778201241490430750148855279902480285370636232307289857524430143006864078804515920541710816317048357865709414064331042744550782852621881679723565826034 | PO_5427782012414904307501488 | null | null | null | [
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| 2023-12-01T23:04:57 | 10803612751250702495558385586662847754517596594535029510436051506441097912197828895796663741131429300217531765802652334275367811509702742540514401573103108 | CO_1080361275125070249555838 | ABC2D6-16_PRL_2018 | [
"Felix Faber",
"Alexander Lindmaa",
"O. Anatole von Lilienfeld",
"Rickard Armiento"
]
| Dataset used to train a machine learning model to calculate density functional theory-quality formation energies of all ~2 x 106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). | [
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]
| 39 | 21,881 | 21,882 | 218,820 | 0 | 21,881 | 0 | 21,881 | 0 | 0 | null | null | 21,881 | 2023-12-01T18:05:52 | [
[
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| [
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| CC-BY-3.0 | {'source-publication': 'https://doi.org/10.1103/PhysRevLett.117.135502', 'source-data': 'https://qmml.org/datasets.html', 'other': None} | 10.60732/f87a64e4 | 12110994724639911956047482088690986156528073902140895356413132972271341337895444635192517682239989058361394442535062960949949218512917835653997173189061933 | DS_0ady7a8a8n6p_0 | ABC2D6-16_PRL_2018__Faber-Lindmaa-Lilienfeld-Armiento__DS_0ady7a8a8n6p_0 |
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