材料科学
辐射冷却
热发射率
辐射传输
电介质
纳米颗粒
涂层
蒙特卡罗方法
光电子学
温度梯度
被动冷却
复合材料
光学
热的
纳米技术
气象学
物理
统计
梁(结构)
数学
作者
Yang Fu,Yidan An,Yunkun Xu,Jian‐Guo Dai,Dangyuan Lei
出处
期刊:EcoMat
[Wiley]
日期:2022-01-11
卷期号:4 (2)
被引量:45
摘要
Abstract Polymeric coatings with randomly distributed dielectric nanoparticles have attracted intensive attention in the passive daytime radiative cooling application. Here, we propose a modified Monte–Carlo method for investigating the spectral response and cooling performance of polymer coating with gradient‐dispersed nanoparticles. Using this method, we carry out a quantitative analysis on the solar reflectance, infrared emittance and cooling power of four categories of gradient structures. It is shown that the gradient profile of particle distribution at the near‐surface region has a significant influence on the overall performance of the coatings. Compared to a randomly distributed structure, the downward size‐gradient structure exhibits superiority in both solar reflectance and cooling power. The presented gradient design, also applicable to porous structures, provides an effective and universal strategy for significantly improving the cooling performance of radiative cooling coatings. image
科研通智能强力驱动
Strongly Powered by AbleSci AI