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Application of Population Balance Models in Particle-Stabilized Dispersions.

Susanne Röhl1, Lena Hohl1, Sebastian Stock2

  • 1Department of Chemical and Process Engineering, Technische Universität Berlin, 10623 Berlin, Germany.

Nanomaterials (Basel, Switzerland)
|February 25, 2023
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Summary
This summary is machine-generated.

This study introduces a new model for drop size in nanoparticle-stabilized liquid systems. It accounts for nanoparticle effects on droplet coalescence, improving predictions for these complex dispersions.

Keywords:
Pickering emulsioncoalescence efficiencyinterface coverage degreestirred tank

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Area of Science:

  • Chemical Engineering
  • Colloid and Interface Science
  • Computational Modeling

Background:

  • Modeling liquid/liquid systems stabilized by nanoparticles is crucial for understanding dispersion behavior.
  • Existing coalescence efficiency models do not adequately capture the steric hindrance effect of interfacial nanoparticles.

Purpose of the Study:

  • To develop a novel population balance model for predicting drop size distributions in agitated nanoparticle-stabilized liquid/liquid systems.
  • To incorporate a modified coalescence efficiency submodel that accounts for nanoparticle steric hindrance and interfacial coverage.

Main Methods:

  • Developed a modified coalescence efficiency submodel based on film drainage, including desorption energy as an energy barrier against coalescence.
  • Implemented a function to calculate the time-dependent interface coverage rate by nanoparticles within the population balance framework.
  • Validated the model using experimental data from agitated water-in-oil dispersions stabilized by silica nanoparticles.

Main Results:

  • The modified submodel successfully predicts the effect of nanoparticle steric hindrance on coalescence.
  • The model accounts for the transient changes in interface coverage by nanoparticles.
  • Validation with experimental data confirmed the model's predictive capability for nanoparticle-stabilized dispersions.

Conclusions:

  • The developed population balance model provides a first step toward accurately predicting time-resolved drop size distributions in nanoparticle-stabilized systems.
  • The novel submodel enhances the understanding of coalescence mechanisms in systems with interfacial nanoparticles.
  • This approach offers a more robust tool for designing and optimizing nanoparticle-stabilized emulsions and dispersions.