Dataset

SAIT_semiconductors_ACS_2023_SiN_train


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Name SAIT_semiconductors_ACS_2023_SiN_train
Extended ID SAIT_semiconductors_ACS_2023_SiN_train__Kim-Na-Kim-Cho-Kang-Lee-Choi-Kim-Lee-Kim__DS_5yfdgzb5zhgm_0
Description Training configurations from the SAIT_semiconductors_ACS_2023_SiN dataset. This dataset contains SiN, Si and N configurations from the SAIT semiconductors datasets. SAIT semiconductors datasets comprise two rich datasets for the important semiconductor thin film materials silicon nitride (SiN) and hafnium oxide (HfO), gathered for the development of MLFFs. DFT simulations were conducted under various conditions that include differing initial structures, stoichiometry, temperature, strain, and defects.
Authors Geonu Kim
Byunggook Na
Gunhee Kim
Hyuntae Cho
Seung-Jin Kang
Hee Sun Lee
Saerom Choi
Heejae Kim
Seungwon Lee
Yongdeok Kim
DOI 10.60732/dbe982a6
https://commons.datacite.org/doi.org/10.60732/dbe982a6
https://doi.datacite.org/dois/10.60732%2Fdbe982a6
https://doi.org/10.60732/dbe982a6

Cite as: Kim, G., Na, B., Kim, G., Cho, H., Kang, S., Lee, H. S., Choi, S., Kim, H., Lee, S., and Kim, Y. "SAIT semiconductors ACS 2023 SiN train." ColabFit, 2024. https://doi.org/10.60732/dbe982a6.
For other citation formats, see the DataCite Fabrica page for this dataset.
Calculated Property Types atomic_forces
cauchy_stress
energy
Elements N (50.59%)
Si (49.41%)
Number of Configurations 22,510
Number of Atoms 1,284,467
Links https://github.com/SAITPublic/MLFF-Framework
https://openreview.net/forum?id=hr9Bd1A9Un
Configuration Sets by Name (None)
Configuration Sets by ID (None)
Calculated Properties
ColabFit ID DS_5yfdgzb5zhgm_0
Files colabfitspec.json

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