Novel computational design of high refractive index nanocomposites and effective refractive index tuning based on nanoparticle morphology effect

This study introduces a method to predict the refractive index (RI) of nanocomposites with the Finite Elements Analysis (FEA) based on the Fabry-Perot interference. The efficacy was verified by comparing the estimated composites’ RI with the available data in the literature. In the experimental verification, the FEA-based prediction showed closer results with the measurement as compared to the effective medium approximation (EMA) approaches, which are prevalently used to predict the physical properties of nanocomposites. Due to the modeling capability, the FEA-method could investigate the effect of the nanoparticle morphology (particle size, shape, and orientation) and distribution. Large particle size, particle agglomeration in high electric-field amplitude region, and particle elongation along the light oscillating direction are found to be the major factors to enhance the RI of composites. The underlying mechanism of RI changing is attributed to the light scattering by embedded nanoparticles, which provides one potential real-time RI tuning schematic.