AI designs new material to cool your home and slash energy bills
SciTechDaily
Scientists from the University of Texas at Austin, along with collaborators from Shanghai Jiao Tong University, the National University of Singapore, and Umea University in Sweden, designed a machine learning method to engineer complex, three-dimensional thermal meta-emitters.
With this framework, they generated over 1,500 unique materials capable of selectively emitting heat in controlled ways, offering greater precision in heating and cooling for improved energy efficiency.
“Our machine learning framework represents a significant leap forward in the design of thermal meta-emitters,” said Yuebing Zheng, professor in the Cockrell School of Engineering’s Walker Department of Mechanical Engineering and co-leader of the study published in Nature.
“By automating the process and expanding the design space, we can create materials with superior performance that were previously unimaginable.”