Table of Contents
Journal of Nanoparticles
Volume 2013 (2013), Article ID 936150, 9 pages
Research Article

A Cluster-Based Method for Improving Analysis of Polydisperse Particle Size Distributions Obtained by Nanoparticle Tracking

1Biomedical Imaging Group, Department of Informatics, Dortmund University of Applied Sciences and Arts, Emil-Figge-Straße 42, 44227 Dortmund, Germany
2Institute for Lung Health (IBE R&D gGmbH) Müenster, Mendelstraße 11, 48149 Münster, Germany
3Institute for Pathology, Ruhr University Bochum, Bürkle-de-la-Camp Platz 1, 44789 Bochum, Germany

Received 15 December 2012; Accepted 11 February 2013

Academic Editor: Frank Hubenthal

Copyright © 2013 Thorsten Wagner et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.