Domain-knowledge-oriented data pre-processing and machine learning of corrosion-resistant γ-U alloys with a small database

The present work proposed a characteristic-parameter-embedded machine learning (ML) model to predict and design body-centered-cubic (BCC) γ-U alloys with high corrosion-resistant lifetime in 343 °C boiling water in U-Mo-Nb-Ti-Zr systems. The characteristic parameters of cluster formula approach and Mo equivalence (Moeq) were implemented into the ML for a more accurate prediction, in which the former reflects the interactions among elements and...