The nanostructured glass has random nanostructures, like the glasswing butterfly wing, that are smaller than the wavelengths of visible light.
This allows the glass to have a very high transparency of This high transparency can reduce the brightness and power demands on displays that could, for example, extend battery life. The glass is antireflective across higher angles, improving viewing angles. The glass also has low haze, less than 0. Finally, the nanostructured glass is durable from abrasion due to its self-healing properties -- abrading the surface with a rough sponge damages the coating, but heating it restores it to its original function.
Natural surfaces like lotus leaves, moth eyes and butterfly wings display omniphobic properties that make them self-cleaning, bacterial-resistant and water-repellant -- adaptations for survival that evolved over millions of years. Researchers have long sought inspiration from nature to replicate these properties in a synthetic material, and even to improve upon them.
While the team could not rely on evolution to achieve these results, they instead utilized machine learning. Leu holds secondary appointments in mechanical engineering and materials science and chemical engineering. We used machine learning to suggest variables to change, and it took us fewer tries to create this material as a result. Bolong Cheng, PhD, fellow research engineer at SigOpt, added, "Machine learning and AI strategies are only relevant when they solve real problems; we are excited to be able to collaborate with the University of Pittsburgh to bring the power of Bayesian active learning to a new application.
Department of Energy's National Energy Laboratory. Materials provided by University of Pittsburgh. Note: Content may be edited for style and length. Science News. Education in Chemistry. Open Access.
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