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Au50Cu50Ni50Pd50Pt50
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AuCuNiPdPt
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ABCDE
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| 5
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[
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data/MD/9492/MD_8681479008172192160479492.json
| null | null | null |
{"input": "\nGGA = PE # Default is POTCAR\nENCUT = 600 # Default is POTCAR\nKSPACING = 0.2 # Default is 0.5\nKGAMMA = .TRUE. # This is the default\nNELM = 120 # Default is 60\nALGO = Normal # This is the default\nEDIFF = 1E-06 # Default is 1E-4\nSIGMA = 0.02 # Default is 0.2\nISMEAR = 0 # Default is 1\nPREC = Accurate # Default is Normal\nLREAL = A # Default is .FALSE.\n ", "keys": {"energy": "energy", "forces": "forces", "virial": "virial"}, "hash": "8681479008172192160479492036128153571152048554015375590208551917358267961043733431147510758264500467165048731533317130522701372096097842271105618107735160", "id": "MD_8681479008172192160479492"}
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PO_1000566754725796286102139
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| 2025-04-16T18:30:57
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DS_jyklsju4h580_0
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VASP
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DFT-PBE
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DS_jyklsju4h580_0
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VASP
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DFT-PBE
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Mo
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| 2025-04-16T16:45:25
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DS_jyklsju4h580_0
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VASP
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DFT-PBE
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W2
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W
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PO_4906316792832244933715893
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| 2025-04-16T21:22:14
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DS_jyklsju4h580_0
| 1
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VASP
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DFT-PBE
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Mg14MoZr
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Mg14MoZr
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A14BC
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data/MD/2225/MD_5823992481922259372942225.json
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PO_4908885069457449812224636
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| 2025-04-16T21:52:07
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DS_jyklsju4h580_0
| 1
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VASP
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DFT-PBE
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CO_1306680173799558294189791
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Al3NiZr2
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Al3NiZr2
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A3B2C
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data/MD/2225/MD_5823992481922259372942225.json
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PO_4913556992587033368927592
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| 2025-04-16T21:29:37
|
DS_jyklsju4h580_0
| 1
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VASP
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DFT-PBE
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DS_jyklsju4h580_0
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DS_jyklsju4h580_0
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VASP
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DS_jyklsju4h580_0
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DS_jyklsju4h580_0
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VASP
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DFT-PBE
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DS_jyklsju4h580_0
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End of preview. Expand
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Cite this dataset
Song, K., Zhao, R., Liu, J., Wang, Y., Lindgren, E., Wang, Y., Chen, S., Xu, K., Liang, T., Ying, P., Xu, N., Zhao, Z., Shi, J., Wang, J., Lyu, S., Zeng, Z., Liang, S., Dong, H., Sun, L., Chen, Y., Zhang, Z., Guo, W., Qian, P., Sun, J., Erhart, P., Ala-Nissila, T., Su, Y., and Fan, Z. UNEP v1 2023 test. ColabFit, 2023. https://doi.org/10.60732/b459b5f2
Cite this dataset
Song, K., Zhao, R., Liu, J., Wang, Y., Lindgren, E., Wang, Y., Chen, S., Xu, K., Liang, T., Ying, P., Xu, N., Zhao, Z., Shi, J., Wang, J., Lyu, S., Zeng, Z., Liang, S., Dong, H., Sun, L., Chen, Y., Zhang, Z., Guo, W., Qian, P., Sun, J., Erhart, P., Ala-Nissila, T., Su, Y., and Fan, Z. UNEP v1 2023 test. ColabFit, 2023. https://doi.org/10.60732/b459b5f2This dataset has been curated and formatted for the ColabFit Exchange
This dataset is also available on the ColabFit Exchange:
https://materials.colabfit.org/id/DS_jyklsju4h580_0
Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.
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Dataset Name
UNEP v1 2023 test
Description
The test set for UNEP-v1 (version 1 of Unified NeuroEvolution Potential), a model implemented in GPUMD.
Dataset authors
Keke Song, Rui Zhao, Jiahui Liu, Yanzhou Wang, Eric Lindgren, Yong Wang, Shunda Chen, Ke Xu, Ting Liang, Penghua Ying, Nan Xu, Zhiqiang Zhao, Jiuyang Shi, Junjie Wang, Shuang Lyu, Zezhu Zeng, Shirong Liang, Haikuan Dong, Ligang Sun, Yue Chen, Zhuhua Zhang, Wanlin Guo, Ping Qian, Jian Sun, Paul Erhart, Tapio Ala-Nissila, Yanjing Su, Zheyong Fan
Publication
https://doi.org/10.1038/s41467-024-54554-x
Original data link
https://zenodo.org/doi/10.5281/zenodo.10081676
License
CC-BY-4.0
Number of unique molecular configurations
4411
Number of atoms
318910
Elements included
Ag, Al, Au, Cr, Cu, Mg, Mo, Ni, Pb, Pd, Pt, Ta, Ti, V, W, Zr
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. Ifcs/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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