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Related Experiment Video

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Three-Dimensionally Printed Microfluidic Cross-flow System for Ultrafiltration/Nanofiltration Membrane Performance Testing
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Quantitative predictive modelling of ultrafiltration processes: colloidal science approaches.

W Richard Bowen1, Paul M Williams

  • 1Centre for Complex Fluids Processing, School of Engineering, University of Wales Swansea, Singleton Park, Swansea, SA2 8PP, UK.

Advances in Colloid and Interface Science
|June 2, 2007
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Summary

Predictive models for membrane ultrafiltration (UF) were developed using colloidal interactions and hydrodynamics. These models accurately predict UF performance, enabling process optimization and design based on fundamental principles.

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Published on: October 4, 2012

Area of Science:

  • Chemical Engineering
  • Colloid Science
  • Separation Processes

Background:

  • Membrane ultrafiltration (UF) is crucial for industrial separations.
  • Accurate predictive models are needed for UF process optimization.
  • Existing models require enhancement with detailed surface interaction physics.

Purpose of the Study:

  • To develop predictive methods for membrane ultrafiltration.
  • To incorporate fundamental colloidal interactions and hydrodynamics into UF models.
  • To improve the accuracy of ultrafiltration process simulations.

Main Methods:

  • Utilized cell-model for electrostatic interactions, London-van der Waals forces, and entropic pressure.
  • Calculated osmotic pressures and gradient diffusion coefficients.
  • Developed methods for local solution viscosity calculation.
  • Integrated calculated properties into mathematical models for frontal and cross-flow UF.

Main Results:

  • Models show excellent agreement with experimental ultrafiltration data.
  • Predictive calculations correlate well with observed ultrafiltration rates.
  • The approach allows predictions from fundamental properties like protein sequence.

Conclusions:

  • Developed robust predictive models for membrane ultrafiltration.
  • Fundamental colloidal and hydrodynamic interactions are key to accurate UF modeling.
  • These methods offer versatile tools for UF process design and optimization.