Dataset

discrepencies_and_error_metrics_NPJ_2023_vacancy_enhanced_training_set


Download Original Data Files 250.5 KB
Download Dataset Parquet Files 724.8 KB
Download Dataset XYZ Files 323.8 KB
Find on Hugging Face 🤗

Species content of dataset


Dataset viewer powered by Hugging Face

Name :
discrepencies_and_error_metrics_NPJ_2023_vacancy_enhanced_training_set
Extended ID :
discrepencies_and_error_metrics_NPJ_2023_vacancy_enhanced_training_set__Liu-He-Mo__DS_qxd7wv9yabtp_0
ColabFit ID :
DS_qxd7wv9yabtp_0
Files :
colabfitspec.json
Description :
Structures from discrepencies_and_error_metrics_NPJ_2023 training set; includes some structures with vacancies. The full discrepencies_and_error_metrics_NPJ_2023 dataset includes the original mlearn_Si_train dataset, modified with the purpose of developing models with better diffusivity scores by replacing ~54% of the data with structures containing migrating interstitials. The enhanced validation set contains 50 total structures, consisting of 20 structures randomly selected from the 120 replaced structures of the original training dataset, 11 snapshots with vacancy rare events (RE) from AIMD simulations, and 19 snapshots with interstitial RE from AIMD simulations. We also construct interstitial-RE and vacancy-RE testing sets, each consisting of 100 snapshots of atomic configurations with a single migrating vacancy or interstitial, respectively, from AIMD simulations at 1230 K.
Authors :
Yunsheng Liu, Xingfeng He, Yifei Mo
DOI :
10.60732/5a780a3a https://commons.datacite.org/doi.org/10.60732/5a780a3a https://doi.datacite.org/dois/10.60732%2F5a780a3a https://doi.org/10.60732/5a780a3a Cite as: Liu, Y., He, X., and Mo, Y. "discrepencies and error metrics NPJ 2023 vacancy enhanced training set." ColabFit, 2023. https://doi.org/10.60732/5a780a3a.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
218
Num. Atoms :
13,389
Downloads :
20
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
Si (100.0%)
Methods :
DFT-PBE
Software :
VASP 5.4.4
Publication Link :
https://doi.org/10.1038/s41524-023-01123-3
Data Source Link :
https://github.com/mogroupumd/Silicon_MLIP_datasets
Configuration Sets by Name :
Configuration Sets by ID :
Report an issue with this dataset

No uploaded content is transferred in ownership from the original creators to ColabFit. All content is distributed under the license specified by its contributor who has stated that he or she has the authority to share it under the specified license.