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 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 Calculated Property Types: atomic_forces energy Elements: Si (100.0%) Methods: DFT-PBE Software: VASP 5.4.4 Number of Configurations: 100 Number of Atoms: 6,500 Publication Link: https://doi.org/10.1038/s41524-023-01123-3 Data Source Link: https://github.com/mogroupumd/Silicon_MLIP_datasets