Table 2. Validation Set and Model Predictions^a.

^aThe table includes materials kept out of the training set and labeled by the reactivity classifier trained in this work, together with their actual labels from AIMD calculations. The validation misclassification rate of 6/17 (35.3%) results from wrong outcomes from passivating predictions. Note that the training set and test set include only 50 and 17 materials, respectively, due to the computational cost of AIMD. Materials marked with ∗ are also predicted to be high ionic conductors (σ_Li > 10^–4 mS/cm) by Sendek et al.²³ These materials have an |ΔE_rxn| > 100 meV/atom with Li metal and hence were missed by the previous conductivity screening. See the data availability section for all stable and passivating predictions.