Simulation Techniques for Soft Matter Sciences (SS 2007)

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Lecture (2 SWS) and Tutorials (2 SWS)
PD Dr. Christian Holm (Lecture) and working group (Tutorials)
Course language
Time and Room
Lecture: Thu 12:15 - 13:45, Phys 1.114
Tutorials: Thu 14:00-16:00, 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.


Date Subject
19.4. Monte-Carlo integration/simulation (Simple vs. Importance sampling)

Look at Zuse's Z3 computer from 1941: Z3 and read something about the first big US computer at Los Alamos Evolving from Calculators to Computers

26.4. 2D Random walks (RW) and Self-avoiding random walks (SAW)--Ising model I (Phase transitions, Critical phenomena, Finite size scaling)
3.5. 2D Ising model II (Reweighting, Cluster Algorithm)
10.5. Error Analysis (Binning, Jackknife, ...)
17.5. Holiday
24.5. Molecular Dynamics I (Velocity Verlet algorithm, Reduced units, Langevin thermostat, Potentials, Forces, Atomistic force fields)
31.5. Molecular Dynamics II
7.6. Holiday
14.6. Long range interactions (Direct sum, Ewald summation, P3M, Fast Multipole method)

This pdf file application_pdf.pnglong_range_lecture.pdf (216 KB)Info circle.png 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 (file does not exist!))

21.6. Continuation of long range lecture, beginning of How to simulate Polymers and Polyelectrolytes.
28.6. 12:15 Tutorial--14:30 Talk by Prof. Binder in Seminar room 2.116,

Afterwards we meet in the Computer room: Continuation on How to simulate Polymers and Polyelectrolytes and background of Poisson-Boltzmann Theory.

5.7. Introduction to the Project work: charged infinite rods in ionic solution-comparison to PB theory. application_pdf.pngCompMethods.pdf (1.65 MB)Info circle.png

A good background reading is the thesis of M. Deserno application_pdf.pngthesis_deserno.pdf (3.57 MB)Info circle.png

12.7. Extended tutorial I: project work
19.7. Extended tutorial II: project work
23.7. On this Monday from 10:00 on we will have the oral examination in my office 01.218! .


Materials on the tutorials can be found behind the links!

Date Subject Tutors
19.4. Introductory tutorial Kai Grass
26.4. Random walks Kai Grass
3.5. Monte Carlo: The Ising model I Marcello Sega
10.5. Monte Carlo: The Ising model II Marcello Sega
17.5. Holiday
24.5. Error analysis Joan Josep Cerdà
31.5. Molecular Dynamics: Lennard-Jones liquid Qiao Baofu
7.6. Holiday
14.6. Introduction to MD simulations with ESPResSo Mehmet Süzen
21.6. Long range interactions: Direct sum and Ewald summation Joan Josep Cerdà
28.6. Visualisation of MD simulations with VMD Olaf Lenz
5.7. Simulation of polymers and polyeletrolytes Qiao Baofu
12.7. Extended tutorial I: project work Olaf Lenz and Mehmet Süzen
19.7. Extended tutorial II: project work Olaf Lenz and Mehmet Süzen

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