Modeling Structural Colors from Disordered One-Component Colloidal Nanoparticle-based Supraballs using Combined Experimental and Simulation Techniques

TL;DR

This paper presents a combined experimental and computational method to predict and reverse engineer the structural colors of disordered nanoparticle assemblies, aiding the design of materials with specific optical properties.

Contribution

It introduces a novel approach that reconstructs nanoparticle structures from scattering data and predicts their colors using FDTD simulations, bridging experimental measurements and theoretical modeling.

Findings

Validated computational predictions against experimental reflectance data

Demonstrated ability to reverse engineer colloidal structures for desired colors

Provided a pathway for designing optical materials with tailored properties

Abstract

Bright, saturated structural colors in birds have inspired synthesis of self-assembled, disordered arrays of assembled nanoparticles with varied particle spacings and refractive indices. However, predicting colors of assembled nanoparticles, and thereby guiding their synthesis, remains challenging due to the effects of multiple scattering and strong absorption. Here, we use a computational approach to first reconstruct the nanoparticles' assembled structures from small-angle scattering measurements and then input the reconstructed structures to a finite-difference time-domain method to predict their color and reflectance. This computational approach is successfully validated by comparing its predictions against experimentally measured reflectance and provides a pathway for reverse engineering colloidal assemblies with desired optical and photothermal properties.