Optical tracking methods are increasingly employed to characterize the size of nanoparticles in suspensions. However, the sufficient separation of different particle populations in polydisperse suspension is still difficult. In this work, Nanosight measurements of well-defined particle populations and Monte-Carlo simulations showed that the analysis of polydisperse particle dispersion could be improved with mathematical methods. Logarithmic transform of measured hydrodynamic diameters led to improved comparability between different modal values of multimodal size distributions. Furthermore, an automatic cluster analysis of transformed particle diameters could uncover otherwise hidden particle populations. In summary, the combination of logarithmically transformed hydrodynamic particle diameters with cluster analysis markedly improved the interpretability of multimodal particle size distributions as delivered by particle tracking measurements. 1. Introduction It has often been shown that the size of nanoparticles determines, among other factors, its biologic or even toxic effects [1]. However, the exact description of a nanoparticle suspension is a challenging issue, for example, during toxicological in vitro testing of nanoparticles [2–4]. During the past 5 years, the Nanoparticle Tracking Analysis (NTA) became increasingly important in nanotoxicology to describe the size distribution of nanoparticle suspensions [5]. As a basic principle, the Brownian motion of laser illuminated NPs is captured by a CCD camera mounted on a conventional light microscope and particle trajectories are tracked by image processing software. Particle size distribution is then obtained via the Stokes-Einstein relation [6]. The variance of the size distribution depends on duration of the observed particle tracks [7] and, in particular, on the mean particle size. Thus, a broadening of the size distribution is to be expected if mean diameter increases. Owing to this broadening effect the proportions of different particle populations are hard to assess by the modal values of a polydisperse suspension. From this consideration it, appears intuitively clear that the larger the broadening effect is, the more difficult it becomes to separate populations of particles with a small difference in size. The purpose of this paper is to demonstrate these features by means of Monte-Carlo simulations of polydisperse suspensions. We furthermore will show methods useful for the analysis and improved interpretation of polydisperse particle size distributions (PSDs). Therefore, different
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