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Quantum-Assisted Coating Could Cool Indoor Spaces Without Using Energy

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To cool buildings more efficiently, researchers at the University of Notre Dame and Kyung Hee University in South Korea developed a high-performance, transparent radiative cooler (TRC) using quantum annealing (QA) combined with artificial intelligence. The transparent window coating that the researchers developed minimized optical heating by allowing visible light to pass through, and by reflecting the heat from ultraviolet (UV) and near-infrared (NIR) sunlight.

Transparent radiative coolers can be used as window materials to reduce cooling energy needs for buildings and automobiles, which may contribute significantly to addressing climate change challenges. Since light in the UV and NIR wavelengths accounts for about 50% of the total solar irradiance affecting an enclosed space, a TRC aiming for optimal efficiency would block these wavelengths while allowing visible photons to pass through with maximal transmission efficiency to allow a clear field of vision.

Such a TRC would also have high emission efficiency in the mid- and long-wavelength infrared regime so it could achieve optimal radiative cooling by passing heat through the atmospheric window.

However, it is difficult to achieve high visible transparency and radiative cooling performance simultaneously.

The researchers overcame this challenge by using a QA-assisted active machine learning scheme to design the TRC. The team constructed computer models of TRCs consisting of a planar multilayer (PML) photonic structure on a glass substrate with a polydimethylsiloxane (PDMS) top layer. They researchers optimized the type, order, and combination of layers using an iterative approach guided by machine learning and quantum computing.

Quantum annealing enabled the researchers to efficiently test all possible combinations in a fraction of a second. Using this approach, the team produced a coating design that, when experimentally fabricated, outperformed conventionally designed TRCs as well as one of the best commercial heat-reduction glasses on the market.
Developed by a research team at the University of Notre Dame, a window film (held in fingers at top left) keeps rooms bright and cool by allowing visible light to pass through, while reflecting invisible infrared and ultraviolet sunlight and radiating heat into outer space. Courtesy of ACS Energy Letters 2022, DOI: 10.1021/acsenergylett.2c01969.
Developed by a research team at the University of Notre Dame, a window film (held in fingers at top left) keeps rooms bright and cool by allowing visible light to pass through, while reflecting invisible infrared and ultraviolet sunlight and radiating heat into outer space. Courtesy of ACS Energy Letters 2022, DOI: 10.1021/acsenergylett.2c01969.
The PDMS layer enabled high radiative cooling performance, while the glass substrate provides mechanical support. The PML structure consisted of four common dielectric materials, which cover a refractive index range of 1.5 to 2.5 in the solar spectrum, so their combinations can potentially yield different optical properties — transmission and reflection — in different wavelength regimes.

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The researchers said that while the material combination of the PML could be optimized, and that, with an appropriate thickness, the PDMS top layer is transparent to the solar spectrum and can behave like an ideal blackbody in wavelength, greater than 4.5 μm, for optimal radiative cooling performance in the atmospheric window.

In simulations, the design showed the potential of the TRC to reduce the amount of energy used for cooling buildings both in the U.S. and worldwide.

Studies estimate that cooling accounts for about 15% of global energy consumption. As heat intensifies through climate change, demand for energy-independent technologies that can lower indoor temperatures, while keeping rooms sunny, will continue to grow.

The researchers estimate that in hot, dry cities, the optimized TRC could potentially reduce cooling energy consumption by 31% compared with conventional windows. Further, they said that their findings could be applied to other applications, since TRCs can also be used on car and truck windows.

The optimized PML structures in the TRC potentially can be scaled up for practical applications because they can be fabricated using state-of-the-art deposition techniques. The quantum computing-enabled optimization technique used to design the cooler could also could be used to design different types of composite materials, such as metamaterials for optical, thermal, and mechanical applications.

The research was published in ACS Energy Letters (www.doi.org/10.1021/acsenergylett.2c01969).

Published: November 2022
Glossary
annealing
The process of heating and slowly cooling a solid material, like glass or metal, to stabilize its thermal, electrical or optical properties or, as in semiconductor materials, to reverse lattice damage resulting from ion implantation of dopants.
machine learning
Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on the development of algorithms and statistical models that enable computers to improve their performance on a specific task through experience or training. Instead of being explicitly programmed to perform a task, a machine learning system learns from data and examples. The primary goal of machine learning is to develop models that can generalize patterns from data and make predictions or decisions without being...
quantum
The term quantum refers to the fundamental unit or discrete amount of a physical quantity involved in interactions at the atomic and subatomic scales. It originates from quantum theory, a branch of physics that emerged in the early 20th century to explain phenomena observed on very small scales, where classical physics fails to provide accurate explanations. In the context of quantum theory, several key concepts are associated with the term quantum: Quantum mechanics: This is the branch of...
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