Material databases offer avenues for identifying predictive descriptors, yet often rely on data that diverges from experimental results. Here, machine learning was used to capture expert intuition into quantifiable descriptors, revealing hypervalency as a key predictor for topological semimetals.
- Yanjun Liu
- Milena Jovanovic
- Eun-Ah Kim
