Dataset
aC_JCP_2023_train
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| Name | aC_JCP_2023_train |
|---|---|
| Extended ID | aC_JCP_2023_train__Minamitani-Obayashi-Shimizu-Watanabe__DS_20h8o5d0ltx1_0 |
| Description | Test split from the 216-atom amorphous portion of the aC_JCP_2023 dataset. The amorphous carbon dataset was generated using ab initio calculations with VASP software. We utilized the LDA exchange-correlation functional and the PAW potential for carbon. Melt-quench simulations were performed to create amorphous and liquid-state structures. A simple cubic lattice of 216 carbon atoms was chosen as the initial state. Simulations were conducted at densities of 1.5, 1.7, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0, 3.2, 3.4, and 3.5 g/cm3 to produce a variety of structures. The NVT ensemble was employed for all melt-quench simulations, and the density was adjusted by modifying the size of the simulation cell. A time step of 1 fs was used for the simulations. For all densities, only the Γ points were sampled in the k-space. To increase structural diversity, six independent simulations were performed.In the melt-quench simulations, the temperature was raised from 300 K to 9000 K over 2 ps to melt carbon. Equilibrium molecular dynamics (MD) was conducted at 9000 K for 3 ps to create a liquid state, followed by a decrease in temperature to 5000 K over 2 ps, with the system equilibrating at that temperature for 2 ps. Finally, the temperature was lowered from 5000 K to 300 K over 2 ps to generate an amorphous structure.During the melt-quench simulation, 30 snapshots were taken from the equilibrium MD trajectory at 9000 K, 100 from the cooling process between 9000 and 5000 K, 25 from the equilibrium MD trajectory at 5000 K, and 100 from the cooling process between 5000 and 300 K. This yielded a total of 16,830 data points.Data for diamond structures containing 216 atoms at densities of 2.4, 2.6, 2.8, 3.0, 3.2, 3.4, and 3.5 g/cm3 were also prepared. Further data on the diamond structure were obtained from 80 snapshots taken from the 2 ps equilibrium MD trajectory at 300 K, resulting in 560 data points.To validate predictions for larger structures, we generated data for 512-atom systems using the same procedure as for the 216-atom systems. A single simulation was conducted for each density. The number of data points was 2,805 for amorphous and liquid states |
| Authors |
Emi Minamitani Ippei Obayashi Koji Shimizu Satoshi Watanabe |
| DOI |
10.60732/ee630a62
https://commons.datacite.org/doi.org/10.60732/ee630a62 https://doi.datacite.org/dois/10.60732%2Fee630a62 https://doi.org/10.60732/ee630a62 Cite as: Minamitani, E., Obayashi, I., Shimizu, K., and Watanabe, S. "aC JCP 2023 train." ColabFit, 2023. https://doi.org/10.60732/ee630a62. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
C (100.0%) |
| Number of Configurations | 13,464 |
| Number of Atoms | 2,908,224 |
| Links |
https://doi.org/10.5281/zenodo.7905585 https://doi.org/10.1063/5.0159349 |
| Configuration Sets by Name | (None) |
| Configuration Sets by ID | (None) |
| Calculated Properties | |
| ColabFit ID | DS_20h8o5d0ltx1_0 |
| Files | colabfitspec.json |
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