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


  • Accurate knowledge of the size, density, and composition of nanoparticles (NPs) is vital for their practical applications.
  • Analytical ultracentrifugation (AUC) provides detailed insights into NP properties, but the interpretation becomes complicated when considering NPs as core-shell systems, where the stabilizing shell affects the overall hydrodynamics of the NPs.
  • The current state-of-the-art data evaluation methods encounter difficulties when characterizing polydisperse and widely distributed NPs due to either inadequate resolution or inability to accurately account for the core-shell properties.
  • Most particle production methods yield polydisperse particle size distributions (PSDs), posing challenges to high-resolution algorithms because of the reduced experimental signal from each species.
  • Modern tools for simultaneous size and effective density analysis have not been adequately applied to polydisperse and multimodal NPs, which represent most systems in nanotechnology.


  • The study initiated by investigating the performance of existing data evaluation models using simulated data.
  • A new methodology was proposed, based on the parametrically constrained spectrum analysis (PCSA), to specifically address the core-shell properties of NPs.
  • The PCSA method allows for detailed modeling of systems where a systematic change in two hydrodynamic parameters describes heterogeneity. It's specially designed for core-shell NPs, capable of analyzing broad PSDs with high resolution while simultaneously offering insights into the core-shell characteristics.
  • The proposed PCSA method can even potentially address varying shell thicknesses with NP size.
  • The effectiveness of this new methodology was confirmed through experiments using ZnO and CuInS2 quantum dots, both representing typical polydisperse core–shell NPs.


  • The study explored algorithms for sedimentation data from polydisperse Particle Size Distributions (PSDs). Previous methods couldn't adequately address the core-shell properties of nanoparticles (NPs). Current 2D analyses have resolution limitations and are unsuitable for large datasets.
  • However, the new PCSA with a 2nd order power law provides high resolution for core-shell properties in NPs. Tested on specific NPs, it yielded accurate results.
  • These advancements broaden the applications of AUC, and the PCSA tool is available in UltraScan3.
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Comparability Studies
Material Science (metal nanoparticles, synthetic polymers, drug compounds)

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