(31j) Computational Reverse-Engineering Analysis for Scattering Experiments of Assembled Binary Colloidal Particle Mixtures

Directed and self-assembly of nanoparticle/colloidal mixtures is a proven route to precisely engineer organic/inorganic materials with controlled optical properties. During the design of such optically active materials, an important step is the structural characterization of the assembled colloid/particle mixture. In many cases, researchers use small angle neutron or X-ray scattering to conduct such structural characterization. The intensity profiles, I(q) vs. q, that are produced from scattering experiments are then interpreted to real space arrangement using off-the shelf analytical models that can sometimes be too approximate for the system at hand. In this talk, we will present our recent work in development of computational methods to analyze the structure of binary nanoparticles assembled into supraballs from the intensity profiles obtained by contrast-matched small angle neutron scattering (SANS). Given the contrast-matched scattering intensity profiles and information about the nanoparticle size and dispersity as inputs, our method utilizes a combination of a genetic algorithm and simulations to output the best structure of the self-assembled nanoparticles whose computed intensity profile matches the experimental intensity profile. This method provides nanoparticle level structural information in complex assembled geometries such as spherical confinements, without dependence on off-the-shelf analytical models.