Dataset

SAIT_semiconductors_ACS_2023_SiN_raw


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Name :
SAIT_semiconductors_ACS_2023_SiN_raw
Extended ID :
SAIT_semiconductors_ACS_2023_SiN_raw__Kim-Na-Kim-Cho-Kang-Lee-Choi-Kim-Lee-Kim__DS_piuigd7monq9_0
ColabFit ID :
DS_piuigd7monq9_0
Files :
colabfitspec.json
Description :
Structures from the SAIT_semiconductors_ACS_2023_SiN dataset, separated into N-only, Si-only, SiN, and out-of-domain melt, quench and relax configuration sets. 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/ef14d3da https://commons.datacite.org/doi.org/10.60732/ef14d3da https://doi.datacite.org/dois/10.60732%2Fef14d3da https://doi.org/10.60732/ef14d3da 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 raw." ColabFit, 2024. https://doi.org/10.60732/ef14d3da.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
88,111
Num. Atoms :
5,201,559
Downloads :
29
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
N (51.08%) Si (48.92%)
Methods :
DFT-PBE
Software :
VASP
Publication Link :
https://openreview.net/forum?id=hr9Bd1A9Un
Data Source Link :
https://github.com/SAITPublic/MLFF-Framework
Configuration Sets by Name :
Configuration Sets by ID :
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