Simulation Techniques for Soft Matter Sciences (SS 2008)
- Lecture (2 SWS) and Tutorials (2 SWS)
- PD Dr. Christian Holm (Lecture) and working group (Tutorials)
- Course language
- Time and Room
- Lecture: Thu special appointment, FIAS Room 200
Tutorials: Thu 16:00-18:00, Phys 1.120
Soft matter science is the science of "soft" materials, like polymers, liquid crystals, colloidal suspensions, ionic solutions, hydrogels and most biological matter. The phenomena that define the properties of these materials occur on mesoscopic length and time scales, where thermal fluctuations play a major role. These scales are hard to tackle both experimentally and theoretically. Instead, computer simulations and other computational techniques play a major role.
The course will give an introduction to the computational tools that are used in soft matter science, like Monte-Carlo (MC) and Molecular dynamics (MD) simulations (on- and off-lattice) and Poisson-Boltzmann theory (and extensions).
The course is intended for participants in the Master Program "Computational Science", but should also be useful for FIGSS students and for other interested science students.
We expect the participants to have basic knowledge in classical and statistical mechanics, thermodynamics, electrodynamics, and partial differential equations, as well as knowledge of a programming language (preferably C or C++).
Lecture and tutorials
The lecture is accompanied by hands-on-tutorials which will be held in the computer room (Physics, 1.120). They consist of practical excercises at the computer, like small programming tasks, simulations, visualisation and data analysis.
The tutorials build on each other, therefore continous attendance is expected.
The dates of the tutorials will be scheduled in the first lecture.
|10.4.||Monte-Carlo integration/simulation (Simple vs. Importance sampling)|
|17.4.||2D Random walks (RW) and Self-avoiding random walks (SAW)--Ising model I (Phase transitions, Critical phenomena, Finite size scaling)|
|24.4.||2D Ising model II (Reweighting, Cluster Algorithm)|
|08.5.|| Error Analysis (Binning, Jackknife, ...)
|15.5.||Molecular Dynamics I (Velocity Verlet algorithm, Reduced units, Langevin thermostat, Potentials, Forces, Atomistic force fields)|
|29.5.|| Molecular Dynamics II
|5.6.|| Long range interactions (Direct sum, Ewald summation, P3M, Fast Multipole method)
This pdf file long_range_lecture.pdf (216 KB) contains surely too many details, but I will walk you through in class. In case you like to have some more background material, here is a review article by A. Arnold and me about this topic (arnold05a.pdf (1.12 MB) )
|12.6.||Continuation of long range lecture, beginning of How to simulate Polymers and Polyelectrolytes.|
|19.6.||Continuation on How to simulate Polymers and Polyelectrolytes and background of Poisson-Boltzmann Theory.|
|26.6.|| Introduction to the Project work: charged infinite rods in ionic solution-comparison to PB theory. CompMethods.pdf (1.65 MB)
A good background reading is the thesis of M. Deserno thesis_deserno.pdf (3.57 MB)
|03.7.||Extended tutorial: project work|
Materials on the tutorials will be sent to students by tutors via mail!
|17.4.||Introductory tutorial, random walks||Nadezhda Gribova|
|24.4.||Monte Carlo: The Ising model I Ising I (90 KB)||Marcello Sega|
|8.5.||Monte Carlo: The Ising model II Ising II (28 KB)||Marcello Sega|
|15.5.||Error analysis||Joan Josep Cerdà|
|29.5.||Molecular Dynamics: Lennard-Jones liquid (687 KB)||Florian Dommert|
|5.6.|| Introduction to MD simulations with ESPResSo
Handout and sources (314 KB)
|12.6.||Long range interactions: Direct sum and Ewald summation: Long range interactions (40 KB)|| Kai Grass
|19.6.|| Simulation of polymers and polyeletrolytes; Project work
Handout and sources (138 KB)
Deserno Thesis (3.57 MB)
|26.6.||Visualisation of MD simulations with VMD||Olaf Lenz|