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Project AMASE aims to improve materials innovation by developing new phase diagrams that account for defects in microstructures. It combines simulations and machine learning to create predictive tools for understanding material behaviors and enhancing industrial applications.
Phase diagrams are “treasure maps” in materials innovation.
However, they traditionally assume defect-free materials, whereas real-world microstructures are often dominated by defects––such as grain boundaries, phase boundaries, dislocations, and stacking faults––that have their own phase behaviours and distinct rules for evolving, interacting, and co-existing.
This discrepancy significantly ties materials innovation to slow, trial-and-error approaches.
Project AMASE is envisioned to deliver “ro…
BUNDESANSTALT FUER MATERIALFORSCHUNG UND -PRUEFUNG
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