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Updated: Oct 9, 2025
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Three-Dimensionally Printed Microfluidic Cross-flow System for Ultrafiltration/Nanofiltration Membrane Performance Testing
Published on: February 13, 2016
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Geometrical Influence on Particle Transport in Cross-Flow Ultrafiltration: Cylindrical and Flat Sheet Membranes
Gun Woo Park1, Gerhard Nägele1
1Institute of Biological Information Processing (IBI-4), Forschungszentrum Juelich GmbH, 52425 Jülich, Germany.
Membranes
|December 23, 2021
Summary
Cross-flow membrane ultrafiltration (UF) efficiency depends on membrane geometry. A new method shows process indicators are determined by just three dimensionless variables, simplifying UF design and scale-up.
Area of Science:
- Chemical Engineering
- Materials Science
- Fluid Dynamics
Background:
- Cross-flow membrane ultrafiltration (UF) is crucial for purifying particles and proteins.
- Understanding membrane geometry's impact on UF efficiency is vital for process optimization.
Purpose of the Study:
- To investigate how different membrane geometries affect particle transport and efficiency in inside-out cross-flow UF.
- To generalize the modified boundary layer approximation (mBLA) method for various membrane configurations.
Main Methods:
- Generalized the modified boundary layer approximation (mBLA) method for flat sheet and hollow cylindrical membranes.
- Analyzed particle transport and UF process indicators for Brownian hard spheres using the mBLA method.
- Varied operating parameters and membrane geometries to assess their influence on UF performance.
Main Results:
- Global UF process indicators (permeate flux, solvent recovery, concentration factor) are highly sensitive to membrane geometry.
- Particle transport and UF efficiency are significantly influenced by membrane configuration.
- A key finding is that UF performance is governed by only three independent dimensionless variables.
Conclusions:
- Membrane geometry is a critical factor in cross-flow UF performance.
- The generalized mBLA method provides an accurate and efficient tool for UF process analysis.
- The identification of three key dimensionless variables simplifies the design, optimization, and scale-up of UF processes.
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