Designing radiative cooling metamaterials for passive thermal management by particle swarm optimization

The passive radiative cooling technology shows a great potential application on reducing the enormous global energy consumption. The multilayer metamaterials could enhance the radiative cooling performance. However, it is a challenge to design the radiative cooler. In this work, based on the particle swarm optimization (PSO) evolutionary algorithm, we develop an intelligent workflow in designing photonic radiative cooling metamaterials. Specifically, we design two 10-layer SiO 2 radiative coolers doped by cylindrical MgF 2 or air impurities, possessing high emissivity within the selective (8–13 μm) and broadband (8–25 μm) atmospheric transparency windows, respectively. Our two kinds of coolers demonstrate power density as high as 119 W/m 2 and 132 W/m 2 at the room temperature (300 K). Our scheme does not rely on the usage of special materials, forming high-performing metamaterials with conventional poor-performing components. This significant improvement of the emission spectra proves the effectiveness of our inverse design algorithm in boosting the discovery of high-performing functional metamaterials.