Analytical Model for Light Scattering in Transparent Composites

TL;DR

This paper introduces an analytical model that predicts light scattering in transparent composites using a single microstructural metric, enabling efficient optical design and optimization.

Contribution

The work develops a novel, physically grounded analytical model based on the Average Interface Number (AIN) for accurate light scattering prediction in composites.

Findings

Model accurately predicts angular scattering in various composites.

EAIN enables rapid haze estimation considering refractive index mismatch.

DNN analysis confirms AIN as the key scattering feature.

Abstract

Transparent composites that combine optical transmittance with mechanical performance are increasingly important for applications in optical devices, sustainable building materials, and photonic engineering. However, predicting light scattering in such materials remains a challenge due to complex, multi-scale microstructural interactions. Here, we present a physically grounded and computationally efficient analytical model. It predicts angular light scattering in transparent composites based on the Average Interface Number (AIN), a single governing microstructural metric derived in this work from geometrical optics. The model accurately captures angular scattering behavior in both fiber- and particle-reinforced composites, as well as in transparent wood. We further introduce the Equivalent Average Interface Number (EAIN), combining AIN with refractive index mismatch into a unified parameter for fast haze prediction. Deep neural network (DNN) analyses confirm AIN as the dominant feature influencing optical scattering. The model predictions are supported by ray-tracing simulations and experimental trends from literature. Finally, we demonstrate the application of our model in fast image rendering simulations through transparent composites. This work provides a compact and practical toolbox for optical design and optimization of transparent structural materials.