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Machine learning reveals 5-angstrom sweet spot behind metallic glass stability
- May 18, 2026 at 2:20 PM
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Using the second-nearest neighboring atoms to predict metallic glass stability can help researchers more accurately model the disordered solid with strong, elastic properties, according to a recent study led by University of Michigan Engineering researchers.
Originally published at Phys.org