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Name discrepencies_and_error_metrics_NPJ_2023_vacancy_enhanced_training_set
Extended ID discrepencies_and_error_metrics_NPJ_2023_vacancy_enhanced_training_set_LiuHeMo__DS_qxd7wv9yabtp_0
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

Cite as: Liu, Y., He, X., and Mo, Y. "discrepencies and error metrics NPJ 2023 vacancy enhanced training set." ColabFit, 2023.
For other citation formats, see the DataCite Fabrica page for this dataset.
Elements Si (100.0%)
Number of Data Objects 218
Number of Configurations 218
Number of Atoms 13,389
Configuration Sets by Name (None)
Configuration Sets by ID (None)
Data Objects
ColabFit ID DS_qxd7wv9yabtp_0
Files colabfitspec.json

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