You Peng, Li Xiong, Huang Yijia, Ma Xiaoliang, Pu Mingbo, Guo Yinghui, Luo Xiangang
State Key Laboratory of Optical Technologies on Nano-Fabrication and Micro-Engineering, Institute of Optics and Electronics, Chinese Academy of Sciences, P.O. Box 350, Chengdu 610209, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Materials (Basel). 2020 Jun 27;13(13):2885. doi: 10.3390/ma13132885.
Despite their great potential for energy-saving applications, it is still challenging to design passive radiative cooling (RC) materials with simultaneous high performance and simple structures based on traditional design philosophy. To solve the contradiction between optimization speed and corresponding performance, we present a flexible hybrid optimization strategy based on a genetic algorithm (GA) in conjunction with the transfer matrix method and introducing the calculation of radiative cooling power density in the evaluation function of the GA. As a demonstration, an optimized coating with 1.5-μm-overlapping MgF and SiN layers on top of a silver film was numerically designed. Based on a detailed analysis of the material's electromagnetic properties and cooling performance, this coating achieved a radiative cooling power density of 62 W/m and a temperature reduction of 6.8 °C at an ambient temperature of 300 K. Our optimization strategy may have special significance in the design of high-performance RC materials or other multi-spectral engineering materials with simple structures.
尽管被动辐射冷却(RC)材料在节能应用方面具有巨大潜力,但基于传统设计理念设计出同时具备高性能和简单结构的被动辐射冷却材料仍然具有挑战性。为了解决优化速度与相应性能之间的矛盾,我们提出了一种基于遗传算法(GA)并结合传输矩阵法的灵活混合优化策略,并在遗传算法的评估函数中引入辐射冷却功率密度的计算。作为示例,通过数值设计了一种在银膜顶部具有1.5μm重叠的MgF和SiN层的优化涂层。基于对该材料电磁特性和冷却性能的详细分析,该涂层在300K的环境温度下实现了62W/m的辐射冷却功率密度和6.8°C的降温。我们的优化策略在设计具有简单结构的高性能RC材料或其他多光谱工程材料方面可能具有特殊意义。