discrepencies and error metrics NPJ 2023 interstitial re testing set

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.

本数据集源自于《NPJ Computational Materials》2023年第5卷的discrepencies_and_error_metrics_NPJ_2023测试集，其中包含间隙结构。discrepencies_and_error_metrics_NPJ_2023完整数据集包括原始的mlearn_Si_train数据集，经过修改以开发具有更优扩散分数的模型，通过用含有迁移间隙结构的结构替换约54%的数据。增强验证集共计50个结构，其中包括从原始训练数据集的120个替换结构中随机选取的20个结构，11个来自AIMD模拟的空位稀事件（RE）快照，以及19个来自AIMD模拟的间隙稀事件快照。此外，我们构建了间隙-RE和空位-RE测试集，每个测试集均包含100个来自1230 K AIMD模拟的原子配置快照，分别对应单个迁移空位或间隙。