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Physics-Informed Machine Learning for Refractory Alloy Design

cond-mat.mtrl-sci · 2026-08-04 · reject · novelty 5.0

Quantile gradient boosting on 393 DFT alloys predicts refractory CCA elastic properties with R² 0.89-0.97, but reported 100% Born stability and Re-based design rules are undercut by internal inconsistencies and miscalibrated intervals.

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  • Physics-Informed Machine Learning for Refractory Alloy Design cond-mat.mtrl-sci · 2026-08-04 · reject · none · ref 4

    Quantile gradient boosting on 393 DFT alloys predicts refractory CCA elastic properties with R² 0.89-0.97, but reported 100% Born stability and Re-based design rules are undercut by internal inconsistencies and miscalibrated intervals.