Semi-analytical technique for the design of disordered coatings with tailored optical properties

Optical properties of particle dispersed coatings with gradient distribution

Particle dispersed coatings with gradient distributions, resulting from either gravity or artificial control, are frequently encountered in practical applications. However, most current studies investigating the optical properties of coatings use the uniform model (uniform single layer assumption), overlooking the gradient distribution effects. Given the pervasiveness of gradient distributions and the widespread use of the uniform model, it is imperative to evaluate applicability conditions of the uniform model in practical applications. In this work, we comprehensively investigate the quantitative performance of the uniform model in predicting the infrared optical properties of coatings with gradient distributions of particle volume fraction using the superposition T-matrix method. The results show that the gradient distribution of particle volume fraction has a limited impact on the emissivity properties of T i O 2-PDMS coatings in the midwavelength-infrared (MWIR) and long-wavelength-infrared (LWIR) bands, which validates the uniform model for the gradient coatings with weakly scattering dielectric particles. However, the uniform model can yield significant inaccuracies in estimating the emissivity properties of Al-PDMS coatings with gradient distributions in the MWIR and LWIR bands. To accurately estimate the emissivity of such gradient coatings with the scattering metallic particles, meticulous modeling of the particle volume fraction distribution is essential.

Prediction of Optical Properties in Particulate Media Using Double Optimization of Dependent Scattering and Particle Distribution

The prediction of optical properties dominated by light scattering in particulate media composed of high-concentration and polydisperse particles is greatly important in various optical applications. However, the accuracy and efficiency of light propagation simulations are still limited by the huge computational burden and complex interactions between dense and polydisperse particles. Here, we proposed a new optimization strategy that can effectively and accurately predict optical properties based on Monte Carlo simulation with particle size and dependent scattering corrections. Both the scattering parameters of particles and the experimental reflectance spectrum are fully examined for verification. Furthermore, using the weighted solar reflectance of particulate media as a representative optical property, both numerical simulations and experiments confirm the superiority and universality of the proposed optimization approach in a variety of materials systems. Moreover, our work can guide the design of particulate media with specific optical features insightfully and will be applicable in many fields involving multiparticle scattering.