Non-equilibrium flow at gradient surfaces: multi-component fluids
| Project Leader: |
Privatdozent Dr. Peter Müller-Buschbaum
Technische Universität München
Department E 13: Lehrstuhl für Experimentalphysik IV
Garching |
| together with: |
Prof. Dr. Manfred Stamm
Leibniz-Institut für Polymerforschung Dresden e.V.
Dresden |
| and: |
Dr. Fathollah Varnik
Max-Planck-Institut für Eisenforschung GmbH
Düsseldorf |
| and: |
Prof. Dr.-Ing. Dierk Rolf Raabe
Max-Planck-Institut für Eisenforschung GmbH
Düsseldorf |
Summary
The use of wetting gradients is an interesting tool to drive liquid
flow along surfaces, micro or nano-channels. Separation processes of
liquid mixtures or polymer solutions are discussed mainly
phenomenologically until now and a basic understanding of the influence
of boundaries on those processes, which is essential for an improved
design of new microfluidic devices, is needed. The goal of the proposal
is to gain a fundamental understanding of separation processes on
gradient surfaces in confined geometries on the nano- and microscale.
The key idea of the project is a combination of newly developed
versatile experimental tools with a powerful theoretical approach in
order to investigate phenomena which are not at all understood until
now. Central part is the investigation is the demixing of
multi-component fluids during the flow. Different types of
multi-component fluids starting from simple liquids and ending with
polymer blend solutions will be focussed on. A gradual change of
surface properties is achieved by generating a gradient of the
geometrical structure ("roughness”) or by a variation of the
chemical composition of the surface. Wetting gradients will be prepared
by binary polymer brushes made of two largely different polymers
introducing a gradient of hydrophilicity/hydrophobicity or surface
charge via variations in the grafting density. The flux and
hydrodynamics of the fluid will be investigated as well as the spatial
variation of its composition due to changing boundary conditions. The
comparison of experimental results with computer simulation data will
result in a high level of understanding.