AI RESEARCH
Multi-Label Phase Diagram Prediction in Complex Alloys via Physics-Informed Graph Attention Networks
arXiv CS.LG
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ArXi:2604.16468v1 Announce Type: new Accurate phase equilibria are foundational to alloy design because they encode the underlying thermodynamics governing stability, transformations, and processing windows. However, while the CALculation of Phase Diagrams (CALPHAD) provides a rigorous thermodynamic framework, exploring multicomponent composition-temperature space remains computationally expensive and is typically limited to sparse section.