Scientists use machine learning and HiTp to speed discovery of metallic glasses by 200 times; approach applicable to other materials

Green Car Congress
By mmillikinApr 17, 2018, 8:15 am368 pts
Researchers at SLAC and their colleagues at Northwestern University and NIST have combined machine learning (ML) and high-throughput (HiTp) experiments to find a new system of metallic glasses in the Co-V-Zr ternary. In their approach, described in an open-access paper in Science Advances, the team trained a…

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