Difference between revisions of "Hauptseminar Active Matter SS 2017/Finite Element Modeling of Active Particles"
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{{Seminartopic | {{Seminartopic | ||
|topic=Finite Element Modeling of Active Particles | |topic=Finite Element Modeling of Active Particles | ||
− | |speaker= | + | |speaker=Miftahussurur Hamidi Putra |
− | |date=2017- | + | |date=2017-05-31 |
− | |time= | + | |time=17:30 |
|tutor=[[Patrick Kreissl]] | |tutor=[[Patrick Kreissl]] | ||
+ | |handout=[https://www.icp.uni-stuttgart.de/~icp/html/teaching/2017-ss-hauptseminar/handout_miftahussurur_fem.pdf] | ||
}} | }} | ||
== Contents == | == Contents == | ||
− | + | The Finite Element Method (FEM) is a computational technique to solve systems of partial differential equations (PDEs) numerically — allowing also for treatment of nonlinear differential equations. In combination with its inherent ability to deal with complex geometries and to work on locally refined meshes, this makes the FEM a powerful tool for investigating not only self-diffusio- but also self-electrophoretic particle systems: The full (nonlinear) electrokinetic equations can be applied directly on an experimental length scale, while resolving critical regions on the scale of the double layer with the necessary high accuracy. | |
+ | The speaker will introduce the FEM, discuss its strengths and weaknesses when applied to the electrokinetic equations, and show how the method can be used to model both self-diffusiophoretic and self-electrophoretic active particles. | ||
== Literature == | == Literature == | ||
− | + | <bibentry>ehrhardt16a</bibentry> | |
− | + | <bibentry>rempfer16a</bibentry> | |
− | + | <bibentry>kreissl16a,brown17a,niu17a</bibentry> | |
− | |||
− | <bibentry>kreissl16a,niu17a</bibentry> |
Latest revision as of 10:16, 22 May 2017
- "{{{number}}}" is not a number.
- Date
- 2017-05-31
- Time
- 17:30
- Topic
- Finite Element Modeling of Active Particles
- Speaker
- Miftahussurur Hamidi Putra
- Tutor
- Patrick Kreissl
- Handout
- [1]
Contents
The Finite Element Method (FEM) is a computational technique to solve systems of partial differential equations (PDEs) numerically — allowing also for treatment of nonlinear differential equations. In combination with its inherent ability to deal with complex geometries and to work on locally refined meshes, this makes the FEM a powerful tool for investigating not only self-diffusio- but also self-electrophoretic particle systems: The full (nonlinear) electrokinetic equations can be applied directly on an experimental length scale, while resolving critical regions on the scale of the double layer with the necessary high accuracy.
The speaker will introduce the FEM, discuss its strengths and weaknesses when applied to the electrokinetic equations, and show how the method can be used to model both self-diffusiophoretic and self-electrophoretic active particles.
Literature
-
Sascha Ehrhardt.
Simulation of Electroosmotic Flow through Nanocapillaries using Finite-Element Methods.
Master's thesis, University of Stuttgart, 2016.
[PDF] (11 MB)
-
Georg Rempfer, Gary B. Davies, Christian Holm, Joost de Graaf.
Reducing spurious flow in simulations of electrokinetic phenomena.
The Journal of Chemical Physics 145(4):044901, 2016.
[PDF] (3.1 MB) [DOI]
-
Patrick Kreissl, Christian Holm, Joost de Graaf.
The efficiency of self-phoretic propulsion mechanisms with surface reaction heterogeneity.
The Journal of Chemical Physics 144(20):204902, 2016.
[PDF] (1.6 MB) [DOI] -
Aidan T. Brown, Wilson C. K. Poon, Christian Holm, Joost de Graaf.
Ionic screening and dissociation are crucial for understanding chemical self-propulsion in polar solvents.
Soft Matter 13(6):1200–1222, 2017.
[PDF] (4.1 MB) [DOI] -
Ran Niu, Patrick Kreissl, Aidan Thomas Brown, Georg Rempfer, Denis Botin, Christian Holm, Thomas Palberg, Joost de Graaf.
Microfluidic pumping by micromolar salt concentrations.
Soft Matter 13(7):1505–1518, 2017.
[PDF] (4.5 MB) [DOI]