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Prospective Students Current Students Faculty & Staff Alumni Industry Start your application today Undergraduate Admissions Graduate Admissions Dual Degree Program Graduate applicants: Attend an info session and skip the application fee Search Trending Searches graduate admissions academic programs financial aid academic calendar maps & directions summer school Home News & Events New metallic glass research brings in artificial intelligence New metallic glass research brings in artificial intelligence Katharine Flores will use federal funding to use artificial intelligence-based algorithms to identify which metal alloys are best to form metallic glasses Beth Miller   08.11.2020 An atomic structure of a simulated liquid consisting of 65% copper (Cu) atoms and 35% Zirconium (Zr) atoms. Share Share on Facebook Share on Twitter Share on Linkedin Email Metallic glasses are a unique group of metal alloys with a disordered atomic structure, similar to the liquid state. Although the differences are at the level of atoms, they result in very different properties for the end materials, including increased strength, better resistance to corrosion, and the ability to be molded into complex shapes. Katharine Flores, professor of mechanical engineering & materials science, has received a three-year, $379,392 grant from the National Science Foundation to use artificial intelligence-based algorithms to identify which metal alloys are best to form metallic glasses. Flores and her team will use artificial intelligence to identify liquid compositions that could be good candidates to form metallic glasses, then create compact material libraries using an advanced 3D-printing method to study their mechanical behavior. The work is expected to speed discovery of new high-performance metallic materials that could be used as structural materials. In addition, Flores,&＃160;also director of the Institute of Materials Science and Engineering,&＃160;will train graduate students in her lab on these processes and hold workshops for middle-and high-school teachers from diverse school districts. 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