This paper proposes and designs a dynamic radiative cooling smart window based on a metal-dielectric multilayer structure. An improved genetic algorithm is employed to optimize the number of layers, their thickness, and material type to achieve different target visible transmittance levels (from 30 to 60%). The optimal structure identified is a 10-layer stack of VO 2 and BaF 2 on a 1-μm-thick BaF 2 substrate, achieving an average visible transmittance of 50%. This design provides significant spectral control capabilities. Below its phase-transition temperature, the window is in an insulating state with a high near-infrared (NIR, 0.78–2.5 μm) transmittance of 80.8% and a low mid-infrared (MIR, 8–13 μm) emissivity of 6.7%, facilitating passive solar heating. Above the phase-transition temperature, it switches to a metallic state with a low NIR transmittance of 10.6% and a high MIR emissivity of 88.3%, enabling effective radiative cooling. The window exhibits substantial modulation abilities, with | Δ T NIR | and Δ ε values of 0.70 and 0.82, respectively. This energy-free, self-adaptive technology, which dynamically regulates thermal radiation in response to ambient temperature, is ideally suited for enhancing energy efficiency in green buildings and smart windows under varying weather conditions.
Liu et al. (Fri,) studied this question.