A research team has deployed artificial intelligence to develop a groundbreaking yet practical tool that could keep your home comfortable while significantly reducing your cooling costs.
According to Energy Star, nearly half of a typical American home's energy bill goes to heating and cooling, equating to around $900 each year. When a home's appliances aren't energy efficient, those electric bills can be particularly expensive.
Scientists from the University of Texas at Austin, Shanghai Jiao Tong University, Singapore's National University, and Sweden's Umeå University believe they have found another way to boost household energy efficiency and reduce heat-trapping pollution generated when a grid relies on dirty fuels, as is still widely the case in many countries, including the U.S.
The team announced in a press release published by EurekAlert that it used machine learning and AI to create "complex" three-dimensional thermal meta-emitters — a "class of engineered materials capable of selectively emitting thermal radiation at highly specific wavelengths," as Bioengineer.org explains.
While the traditional process of designing thermal meta-emitters involves a combination of human intuition and troubleshooting, AI and machine learning helped bridge that gap.
"Our machine learning framework represents a significant leap forward in the design of thermal meta-emitters," Yuebing Zheng, professor in the Cockrell School of Engineering's Walker Department of Mechanical Engineering, said in the release.
"By automating the process and expanding the design space, we can create materials with superior performance that were previously unimaginable," he added.
All in all, the team developed 1,500 different materials. One of these special materials demonstrated an ability to keep a coated house 9 to 36 degrees Fahrenheit (5 to 20 degrees Celsius) cooler on average than houses with white and gray regular paint.
While that discovery was thrilling because it could save consumers money on heating and cooling if realized at scale while reducing strain on the electrical grid, Interesting Engineering lauded the materials as "more than energy savers."
In the press release, researchers revealed that they created seven classes of meta-emitters with a range of applications, including reflecting sunlight to reduce the heat island effect in urban areas and managing a spacecraft's temperature by bouncing off solar radiation.
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The upfront cost 💰 The team published its results in Nature. Now, it will continue fine-tuning its technology as part of broadening its applications.
"Machine learning may not be the solution to everything, but the unique spectral requirements of thermal management make it particularly suitable for designing high-performance thermal emitters," study co-author Kan Yao said in the release.
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