A strategy of hierarchical particle sizes in nanoparticle composite for enhancing solar reflection

A key requirement for achieving passive radiative cooling for an ideal emitter, in the sky window (8–13 µm), during daytime is a total solar reflection >85%, and every 1% above this threshold results in ∼10 W/m2 gain in cooling power. One promising, inexpensive, and scalable solution for achieving high total solar reflectance is a dielectric nanoparticle-polymer composite coating. Past works have widely used a single particle size. However, it is challenging to achieve solar reflectance significantly above 85%. Here, recognizing the broadband nature of the solar irradiation, we propose and test a new concept of enhancing solar reflection at a given particle volume concentration by using hierarchical particle sizes, which we hypothesize to scatter each band of the solar spectrum i.e. VIS, NIR, and UV effectively. The hypothesis is tested using a TiO2 nanoparticle-acrylic system. Using the Mie Theory, the scattering and absorption efficiencies and asymmetric parameter of nanoparticles with different sizes and combinations are calculated, then the Monte Carlo Method is used to solve the Radiative Transfer Equation. When validating our computational model to in-house experimental results it is found that a nanoparticle size distribution of d = 104 ± 37 nm creates an overall better fit to the experimental data and increases the total solar reflection when compared to the single size model of d = 104 nm. We then purposely design hierarchical combinations of particle sizes in the broader range of 50 nm to 800 nm, and we have achieved an overall total solar reflection of ≈91%, which is higher than the ≈78% and ≈88% for 100 nm and 400 nm single particle sizes, respectively. The results confirm our hypothesis that hierarchical particle sizes can scatter over a broad spectrum more effectively rather than any single particle size. Moreover, our findings could also cut the manufacturing cost since no precise control of particle size is necessary.