Dataset

discrepencies_and_error_metrics_NPJ_2023_interstitial_re_testing_set


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Name :
discrepencies_and_error_metrics_NPJ_2023_interstitial_re_testing_set
Extended ID :
discrepencies_and_error_metrics_NPJ_2023_interstitial_re_testing_set__Liu-He-Mo__DS_dhe9aqs9q1wf_0
ColabFit ID :
DS_dhe9aqs9q1wf_0
Files :
colabfitspec.json
Description :
Structures from discrepencies_and_error_metrics_NPJ_2023 test set; these include an interstitial. 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 :
10.60732/81a7ca9e https://commons.datacite.org/doi.org/10.60732/81a7ca9e https://doi.datacite.org/dois/10.60732%2F81a7ca9e https://doi.org/10.60732/81a7ca9e Cite as: Liu, Y., He, X., and Mo, Y. "discrepencies and error metrics NPJ 2023 interstitial re testing set." ColabFit, 2023. https://doi.org/10.60732/81a7ca9e.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
100
Num. Atoms :
6,500
Downloads :
54
Calculated Property Types :
atomic_forces 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 :
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