Computational modeling and experimental research are used in a synergistic manner to develop and understand advanced materials in Professor Paul Leu's lab at the University of Pittsburgh Swanson School of Engineering. In collaboration with SigOpt and NETL, his team created a nanostructure glass that takes inspiration from the wings of the glasswing butterfly to create a new type of glass that is not only very clear across a wide variety of wavelengths and angles, but is also antifogging. Glass for technologies like displays, tablets, laptops, smartphones, and solar cells need to pass light through, but could benefit from a surface that repels water, dirt, oil, and other liquids.
The team recently published a paper detailing their findings: “Creating Glasswing-Butterfly Inspired Durable Antifogging Omniphobic Supertransmissive, Superclear Nanostructured Glass Through Bayesian Learning and Optimization” in Materials Horizons. “Something significant about the nanostructured glass research, in particular, is that we partnered with SigOpt to use machine learning to reach our final product,” says Dr. Leu. “When you create something like this, you don’t start with a lot of data, and each trial takes a great deal of time. We used machine learning to suggest variables to change, and it took us fewer tries to create this material as a result.”