A perspective-conditioned RAG architecture is proposed for AI-assisted LCA interpretation, using scenario anchors, micro-queries, and neutral synthesis, demonstrated on a hydrogen diesel reduction case in Italian apple production.
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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.
citing papers explorer
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LCAi: Life Cycle Assessment with big data fusion and retrieval-augmented generation-assisted interpretation
A perspective-conditioned RAG architecture is proposed for AI-assisted LCA interpretation, using scenario anchors, micro-queries, and neutral synthesis, demonstrated on a hydrogen diesel reduction case in Italian apple production.
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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.