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Using light scattering to evaluate the separation of polydisperse nanoparticles.

Anne A Galyean1, Wyatt N Vreeland2, James J Filliben3

  • 1Gillings School of Global Public Health, Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, NC 27599, USA.

Analytica Chimica Acta
|September 1, 2015
PubMed
Summary

A new method assesses particle separation accuracy for complex samples. It improves separation protocols by minimizing the measured average particle size, ensuring reliable analysis with light scattering detection.

Keywords:
Flow field flow fractionationMulti angle light scatteringNanoparticlePolydisperseQuasi-elastic light scatteringSeparation

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Area of Science:

  • Analytical Chemistry
  • Materials Science
  • Physical Chemistry

Background:

  • Analyzing complex samples with light scattering detection is challenging due to uncertainties in accuracy and precision.
  • Non-linear relationships between particle size and scattered light intensity can lead to overestimated average particle sizes in complex mixtures.
  • Effective separation is crucial for accurate particle size analysis, especially for heterogeneous samples.

Purpose of the Study:

  • To present a practical tool for assessing the relative accuracy of separation protocols in techniques using light scattering detection.
  • To establish a metric for improving separation efficiency and mitigating overestimation of average particle size.
  • To demonstrate the application of this metric in optimizing separation parameters for asymmetric flow field flow fractionation (AF(4)).

Main Methods:

  • Developed an assessment metric based on minimizing the average measured particle size obtained from separation protocols.
  • Applied the metric to optimize cross flow (V(x)) protocols in asymmetric flow field flow fractionation (AF(4)) coupled with quasi-elastic light scattering (QELS) detection.
  • Utilized mixtures of polystyrene beads with a wide size distribution to validate the protocol optimization.

Main Results:

  • The developed metric successfully guided the optimization of AF(4) V(x) protocols, leading to improved separation.
  • Optimized protocols resulted in measured average particle sizes that were in statistical agreement with calculated sizes.
  • The assessment metric demonstrated its utility in identifying superior separation protocols for complex mixtures.

Conclusions:

  • The proposed assessment metric provides a reliable approach to evaluate and enhance separation protocols for techniques employing light scattering detectors.
  • This method is broadly applicable to various separation parameters and techniques, including asymmetric flow field flow fractionation.
  • Accurate particle size analysis of complex samples is achievable through rigorous protocol optimization guided by this metric.