Machine learning on the largest curated alkali-activated slag dataset shows that average metal oxide dissociation energy serves as a compact, physically interpretable reactivity descriptor enabling strength prediction and low-emission design space exploration.
Aggarwal, Outlier analysis, Springer International Publishing, Cham, 2017
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Reactivity-Informed Machine Learning for Performance Prediction and Design Space Exploration of Alkali-Activated Slag
Machine learning on the largest curated alkali-activated slag dataset shows that average metal oxide dissociation energy serves as a compact, physically interpretable reactivity descriptor enabling strength prediction and low-emission design space exploration.