Quantitative characterization of mixing in multicomponent nanoparticle aggregates
The application of nanosized multicomponent particles often requires tailored mixing characteristics. This involves mixing on primary particle level, on cluster level, or on aggregate level. This mixing is often evaluated qualitatively in 2D, based on image analyses. This work presents an approach to utilize the cluster size in combination with the heterogeneous coordination number as a quantitative measure for the mixing of clusters of more than three primary particles within nanosized aggregates in 3D. Therefore, nanoparticle aggregates formed by differently sized clusters are simulated and evaluated with respect to cluster size and coordination number. Subsequently, a method is introduced to generate 2D projections and mimic image analysis based on transmission electron microscopy images from flame-made nanoparticles. This also includes the evaluation of the necessary visible area for each particle to be identified in the 2D image analysis. This leads to a correlation of the 2D projections and 3D simulations including a calibration to experimental data and enables the determination of a 3D heterogeneous coordination number and cluster size from 2D image analysis.