Keywords: Alkali-activated materials

Alkali-activated materials (AAMs) are promising alternatives to ordinary Portland cement (OPC), but standardized mix design approaches are limited. This study introduces a machine learning-based framework for inverse mix design of AAMs, predicting optimal mixes based on target properties and sustainability. The model considers eight key factors, including precursor reactivity, activator properties, and liquid-to-binder ratio.