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Deposition of spherical particles onto cylindrical solid surfaces. I. Numerical simulations
1Faculty of Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2, Canada.
Journal of Colloid and Interface Science
|November 18, 2005
Summary
Particle deposition on cylindrical surfaces is governed by van der Waals (vdW) and electrical double-layer (EDL) forces. The EDL force primarily dictates the 1D deposition process, while vdW forces are necessary but have limited impact.
Area of Science:
- Colloid and Surface Science
- Mass Transfer Phenomena
- Computational Fluid Dynamics
Background:
- Particle deposition is crucial in various industrial and environmental processes.
- Understanding the interplay of colloidal forces is key to predicting deposition rates.
- Existing models often simplify the complex interactions involved.
Purpose of the Study:
- To provide analytical and numerical solutions for spherical particle deposition onto cylindrical surfaces.
- To investigate the influence of van der Waals (vdW) and electrical double-layer (EDL) forces on deposition.
- To examine the effects of gravity and external electrical forces on the deposition process.
Main Methods:
- Development of analytical and numerical solutions for a 1D mass transfer equation.
- Parametric study of vdW (adhesion number Ad) and EDL forces (EDL parameter Dl, reduced radius tau).
- Numerical solution of a 2D boundary value problem using the implicit Crank-Nicolson method for external forces.
Main Results:
- The attractive vdW force is essential for deposition but has a limited effect on mass transfer rate.
- The 1D deposition process is predominantly controlled by the EDL force, with tau being a critical factor.
- External forces like gravity and electrical fields introduce 2D effects, altering deposition dynamics.
Conclusions:
- The EDL force is the dominant factor in 1D particle deposition on cylindrical surfaces.
- The adhesion number (Ad) is necessary but not sufficient for significant deposition.
- Gravity and electrical forces introduce complexities requiring 2D modeling for accurate prediction.