What do you call a materials science discovery that was given a major boost by a lecture from a Nobel laureate in chemistry, used cryogenic electron microscopy (cryo-EM), and was pushed further along by a doctoral student’s thesis on machine learning?
Typical Cornell research.
The team’s paper, “Surfactant Micelle Self-Assembly Directed Highly Symmetric Ultrasmall Inorganic Cages,” was published June 20.
Other members of the team include postdoctoral researchers Kai Ma and Tangi Aubert from the Wiesner Group; Peter Doerschuk, professor in the Department of Electrical and Computer Engineering and in the Meinig School of Biomedical Engineering; and doctoral student Yunye Gong from the Doerschuk Group.
Techniques from Gong’s doctoral thesis, “Computing and Understanding Statistical Models for Heterogeneous Biological Nano-machines,” were used to determine the 3-D shape of the cage structures.
“People had suggested that these very complex nanostructures would be structural units of bulk materials,” Wiesner said, “but nobody had ever identified these cages as isolated building blocks.”
Image courtesy of news.cornell.edu