As climate change intensifies summer heat, there is a growing demand for building cooling technologies. Researchers report in the journal ACS Energy Letters that they used advanced computing technology and artificial intelligence to create a transparent window coating that could lower the temperature inside buildings without using a single watt of energy.
According to studies, cooling accounts for about 15% of global energy consumption. This demand could be reduced by using a window coating that blocks ultraviolet and near-infrared light from the sun – the parts of the solar spectrum that typically pass through glass to heat an enclosed space. If the coating radiates heat from the window’s surface at a wavelength that passes through the atmosphere and into outer space, energy consumption could be reduced even further.
This computing method carries out optimization faster and better than conventional computers because it can efficiently test all possible combinations in a fraction of a second. This produced a coating design that, when fabricated, beat the performance of conventionally designed TRCs in addition to one of the best commercial heat-reduction glasses on the market.
However, it is difficult to design materials that can meet these criteria while also transmitting visible light, implying that they do not obstruct the view. Eungkyu Lee, Tengfei Luo, and colleagues set out to create a “transparent radiative cooler” (TRC) capable of doing exactly that.
The team constructed computer models of TRCs consisting of alternating thin layers of common materials like silicon dioxide, silicon nitride, aluminum oxide or titanium dioxide on a glass base, topped with a film of polydimethylsiloxane. They optimized the type, order, and combination of layers using an iterative approach guided by machine learning and quantum computing, which stores data using subatomic particles.
This computing method carries out optimization faster and better than conventional computers because it can efficiently test all possible combinations in a fraction of a second. This produced a coating design that, when fabricated, beat the performance of conventionally designed TRCs in addition to one of the best commercial heat-reduction glasses on the market.
In hot, dry cities, the researchers say, the optimized TRC could potentially reduce cooling energy consumption by 31% compared with conventional windows. They note their findings could be applied to other applications, since TRCs could also be used on car and truck windows. In addition, the group’s quantum computing-enabled optimization technique could be used to design other types of composite materials.
The authors acknowledge support from the National Research Foundation of Korea and the Notre Dame Center for Research Computing.
