ML model using ideal entropy plus simulation features (energy above hull, heat capacity change, icosahedral fraction) predicts metallic glass critical cooling rates with R²=0.78 in leave-one-chemical-system-out cross-validation on 34 alloys.
Formation of Glasses from Liquids and Biopolymers,
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A review of topological defects in glasses, their theoretical foundations, and correlations with plasticity and shear-band formation in amorphous solids.
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Machine learning metallic glass critical cooling rates through elemental and molecular simulation based featurization
ML model using ideal entropy plus simulation features (energy above hull, heat capacity change, icosahedral fraction) predicts metallic glass critical cooling rates with R²=0.78 in leave-one-chemical-system-out cross-validation on 34 alloys.
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The Physics of Topological Defects in Glasses
A review of topological defects in glasses, their theoretical foundations, and correlations with plasticity and shear-band formation in amorphous solids.