Machine Learning Speeds Discovery of New Materials

Metallurgists have long sought the Holy Grail of alloys, metallic glass that is strong and won't shatter. It is amorphous, with its atoms arranged every which way, much like the atoms of the glass in a window. Its glassy nature makes it stronger and lighter than today's best steel, plus it stands up better to corrosion and wear. Even though metallic glass would be useful as a protective coating or an alternative to steel, only a few thousand of the millions of possible combinations of ingredients have been evaluated over the past 50 years, and of those, only a handful developed to the point that they may become useful. Now a group led by scientists at the Department of Energy's SLAC National Accelerator Laboratory, the National Institute of Standards and Technology (NIST), and Northwestern University has reported a shortcut for discovering and improving metallic glass–and, by extension, other elusive materials–at a fraction of the time and cost.