Teaching computers to intelligently design 'billions' of possible materials

Discovering how atoms—such as a single layer of carbon atoms found in graphene, one of the world's strongest materials—work to create a solid material is currently a major research topic in the field of materials science, or the design and discovery of new materials. At the University of Missouri, researchers in the College of Engineering are applying one of the first uses of deep learning—the technology computers use to intelligently perform tasks such as recognizing language and driving autonomous vehicles—to the field of materials science.

"You can train a computer to do what it would take many years for people to otherwise do," said Yuan Dong, a research assistant professor of mechanical and aerospace engineering and lead researcher on the study. "This is a good starting point."

Dong worked with Jian Lin, an assistant professor of mechanical and aerospace engineering, to determine if there was a way to predict the billions of possibilities of material structures created when certain carbon atoms in graphene are replaced with non-carbon atoms.