Dataset
discrepencies_and_error_metrics_NPJ_2023_enhanced_validation_set
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Name | discrepencies_and_error_metrics_NPJ_2023_enhanced_validation_set |
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Extended ID | discrepencies_and_error_metrics_NPJ_2023_enhanced_validation_set__Liu-He-Mo__DS_q6e3bvq4y67a_0 |
Description | Structures from discrepencies_and_error_metrics_NPJ_2023 validation set, enhanced by inclusion of rare events. 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 |
10.60732/9c77bb8c
https://commons.datacite.org/doi.org/10.60732/9c77bb8c https://doi.datacite.org/dois/10.60732%2F9c77bb8c https://doi.org/10.60732/9c77bb8c Cite as: Liu, Y., He, X., and Mo, Y. "discrepencies and error metrics NPJ 2023 enhanced validation set." ColabFit, 2023. https://doi.org/10.60732/9c77bb8c. For other citation formats, see the DataCite Fabrica page for this dataset. |
Property Types |
atomic_forces cauchy_stress energy |
Elements |
Si (100.0%) |
Number of Property Objects | 50 |
Number of Configurations | 50 |
Number of Atoms | 3,198 |
Links |
https://github.com/mogroupumd/Silicon_MLIP_datasets https://doi.org/10.1038/s41524-023-01123-3 |
Configuration Sets by Name | (None) |
Configuration Sets by ID | (None) |
Property Objects | |
ColabFit ID | DS_q6e3bvq4y67a_0 |
Files | colabfitspec.json |
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