2D analysis of polydisperse core–shell nanoparticles using analytical ultracentrifugation

Accurate knowledge of the size, density and composition of nanoparticles (NPs) is of major importance for their applications. In this work the hydrodynamic characterization of polydisperse core–shell NPs by means of analytical ultracentrifugation (AUC) is addressed. AUC is one of the most accurate techniques for the characterization of NPs in the liquid phase because it can resolve particle size distributions (PSDs) with unrivaled resolution and detail. Small NPs have to be considered as core–shell systems when dispersed in a liquid since a solvation layer and a stabilizer shell will significantly contribute to the particle's hydrodynamic diameter and effective density. AUC measures the sedimentation and diffusion transport of the analytes, which are affected by the core–shell compositional properties. This work demonstrates that polydisperse and thus widely distributed NPs pose significant challenges for current state-of-the-art data evaluation methods. The existing methods either have insufficient resolution or do not correctly reproduce the core–shell properties. First, we investigate the performance of different data evaluation models by means of simulated data. Then, we propose a new methodology to address the core–shell properties of NPs. This method is based on the parametrically constrained spectrum analysis and offers complete access to the size and effective density of polydisperse NPs. Our study is complemented using experimental data derived for ZnO and CuInS2 NPs, which do not have a monodisperse PSD. For the first time, the size and effective density of such structures could be resolved with high resolution by means of a two-dimensional AUC analysis approach.