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.
Elastic Properties of Model Porous Ceramics
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Identifies conditions and explicit constructions allowing polynomial-size quantum circuits to implement geometry oracles for pseudorandom textured materials, in contrast to Grover-hard unstructured cases.
Wet infiltration co-dopes 3YSZ with Sc, Mg, and Y, producing samples with varying tetragonal and cubic phases plus altered hardness and translucency compared to standard 3YSZ and 5YSZ.
citing papers explorer
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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.
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How to make quantum cheese: efficient geometry oracles for exponentially many pseudorandom microstructures
Identifies conditions and explicit constructions allowing polynomial-size quantum circuits to implement geometry oracles for pseudorandom textured materials, in contrast to Grover-hard unstructured cases.
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Structural effects of liquid infiltration of 3Y-Zirconia with Sc, Mg and Y
Wet infiltration co-dopes 3YSZ with Sc, Mg, and Y, producing samples with varying tetragonal and cubic phases plus altered hardness and translucency compared to standard 3YSZ and 5YSZ.
- Extraction of a structural short-range order descriptor from nanobeam electron diffraction patterns using a transfer learning approach