.png){kind=icon}
.png){kind=icon}
Return
High-Performance Transparent Radiative Cooler Designed by Quantum Computing
.png){kind=icon}
PRE
AI
DOI：10.1021/acsenergylett.2c01969.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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. However, it is difficult to achieve high visible transparency and radiative cooling performance simultaneously. Here, we design a visually transparent radiative cooler on the basis of layered photonic structures using a quantum computing-assisted active learning scheme, which combines active data production, machine learning, and quantum annealing in an iterative loop. We experimentally fabricate the designed cooler and demonstrate its cooling effect. This cooler may lead to an annual energy saving of up to 86.3 MJ/m(2) in hot climates compared with normal glass windows. The quantum annealing-assisted active learning scheme may be generalized for the design of other complex materials.
Keywords:
OPTICAL-PROPERTIES
OPTIMIZATION
WATER
Journal
IF:
18.2
Papers:
5.2K
Citations:
6.6W