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2025-04-16T18:07:29
DS_xzo1tvni8bay_0
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CCu144
CCu144
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[ "Carbon_Cluster_Training_Set_181", "C_G_M_-_M_L_P_-_C_u_-_C_Training_Dataset_deposition__deposition_241", "C_G_M_-_M_L_P_-_C_u_-_C_-_O_Training_Dataset_deposition__deposition_241" ]
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2025-04-16T16:10:12
DS_xzo1tvni8bay_0
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C18Cu144
CCu8
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2025-04-16T18:49:16
DS_xzo1tvni8bay_0
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C9Cu144
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2025-04-17T17:35:57
DS_xzo1tvni8bay_0
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C40Cu144
C5Cu18
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2025-04-16T18:44:29
DS_xzo1tvni8bay_0
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C9Cu144
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2025-04-16T17:26:05
DS_xzo1tvni8bay_0
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C42Cu144
C7Cu24
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2025-04-16T18:33:21
DS_xzo1tvni8bay_0
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2025-04-17T18:26:41
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C43Cu144
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2025-04-16T21:12:41
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2025-04-16T18:54:22
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C4Cu288
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2025-04-16T21:44:51
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C9Cu144
CCu16
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2025-04-16T21:51:00
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2025-04-16T16:24:43
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2025-04-16T18:33:37
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[ [ 0.032525, -0.267686, 0.579671 ], [ -1.192256, -0.334602, -1.327139 ], [ -0.776049, -0.000847, -0.228096 ], [ -0.466519, -1.129492, -0.162854 ], [ 1.59583, -0.944432, -0.610983 ], [ 0.40231, -0.632873, 1.936837 ], [ ...
[ [ 0.029637, 0.008374, 0.005167 ], [ 0.008374, 0.025177, 0.008538 ], [ 0.005167, 0.008538, 0.042265 ] ]
true
null
null
null
null
null
10.13739
1.616455
null
CO_1672936558368150221488245
1672936558368150221488245613834768221236311598222824607763904736283400737054274353961204160291659025109267768421883259712586935390497333948056459435299229
9900429637395173710954600428690913589916891654706713118120193873572019312442087368643472775655252227440619394559571483405236183774333072619788159755145927
[ [ 15.027817947043928, 0, 0 ], [ 0, 17.352620305820842, 0 ], [ 0, 0, 60 ] ]
[ [ 14.9126, 0.135141, 7.14651 ], [ 14.9598, 1.4713, 9.54504 ], [ 3.39957, 0.543087, 11.0366 ], [ 1.16713, 2.45636, 7.10481 ], [ 0.914799, 3.64049, 9.45785 ], [ 1.36136, 4.77667, 11.4162 ], [ 14.9958, 4.48717, ...
[ true, true, true ]
C34Cu144
C17Cu72
A72B17
[ "C", "Cu" ]
[ 0.19101123595505617, 0.8089887640449438 ]
[ 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, ...
178
2
3
[ 1, 1, 1 ]
[ "C_G_M_-_M_L_P_-_C_u_-_C_Training_Dataset_metal_surface__metal_surface_387", "C_G_M_-_M_L_P_-_C_u_-_C_-_O_Training_Dataset_deposition__metal_surface_1574" ]
null
data/MD/3341/MD_4178802015180711158523341.json
data/MD/8848/MD_8041769497871336756638848.json
null
{"config_type": "metal_surface", "hash": "8041769497871336756638848319743004227555484317990585045426020494630790487036267289371643695078154005944188700497279119886098681806582457831451980474337646", "id": "MD_8041769497871336756638848"}
{"input": {"cutoff-energy": {"value": 300, "units": "Ry"}, "relative-cutoff-energy": {"value": 60, "units": "Ry"}, "scheme": "QUICKSTEP"}, "hash": "4178802015180711158523341789665647106270915003175636797223149523631617352424712633254110378226507537845096425680076758458702686284378534857806338422045244", "id": "MD_41788...
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Cite this dataset Zhang, D., Yi, P., Lai, X., Peng, L., and Li, H. CGM-MLP natcomm2023 Cu-C-O deposition. ColabFit, 2024. https://doi.org/10.60732/ae9380c5

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Dataset Name

CGM-MLP natcomm2023 Cu-C-O deposition

Description

Training simulations from CGM-MLP_natcomm2023 of carbon deposition on a Cu surface. This appears similar to CGM-MLP_natcomm2023_CU-C_deposition, as there are no O atoms present in this set. 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.

Dataset authors

Di Zhang, Peiyun Yi, Xinmin Lai, Linfa Peng, Hao Li

Publication

https://doi.org/10.1038/s41467-023-44525-z

Original data link

https://github.com/sjtudizhang/CGM-MLP

License

MIT

Number of unique molecular configurations

1693

Number of atoms

326182

Elements included

C, Cu

Properties included

energy, atomic forces, cauchy stress


Usage

  • ds.parquet : Aggregated dataset information.
  • co/ directory: Configuration rows each include a structure, calculated properties, and metadata.
  • cs/ directory : Configuration sets are subsets of configurations grouped by some common characteristic. If cs/ does not exist, no configurations sets have been defined for this dataset.
  • cs_co_map/ directory : The mapping of configurations to configuration sets (if defined).

ColabFit Exchange documentation includes descriptions of content and example code for parsing parquet files:

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