Algorithmic optimization and thermodynamic evaluation of PDMS-based multilayer radiative coolers for building energy efficiency

Abstract

Against the background of global warming and rapidly increasing building cooling demand, passive daytime radiative cooling offers substantial potential for zero-energy thermal management. Nevertheless, the design of multilayer radiative-cooling materials remains strongly constrained by empirical trial-and-error. In the large design space involving both discrete material selection and continuous film-thickness variation, conventional parameter sweeps are prone to local optima and generally fail to couple microscopic physical mechanisms with macroscopic techno-economic performance. To overcome this limitation, this study proposes a full-chain inverse-design computational framework that integrates the transfer matrix method, a steady-state heat-balance model, and hybrid-variable genetic algorithms. The dynamic competition between PDMS molecular characteristic absorption and parasitic heat gain is first quantified, establishing 100 μm as the single-layer physical ceiling, with a limiting net cooling power of 105.88 W/m2. A subsequent global evolutionary search identifies a composite metamaterial configuration with a limiting cooling power of 122.15 W/m2—the optimized metamaterial configuration (Ag/Al2O3/SiO2/PDMS). This study provides a rigorous theoretical basis and decision-making paradigm for the inverse design and engineering deployment of radiative-cooling materials.