Breakthrough tool predicts properties of theoretical materials
Tuesday, July 11, 2017 - 16:02
in Physics & Chemistry
Scientists at the University of North Carolina at Chapel Hill and Duke University have created the first general-purpose method for using machine learning to predict the properties of new metals, ceramics and other crystalline materials and to find new uses for existing materials, a discovery that could save countless hours wasted in the trial-and-error process of creating new and better materials.