Simulation Techniques for Soft Matter Sciences (SS 2007)

Overview

Type

Lecture (2 SWS) and Tutorials (2 SWS)

Lecturer

PD Dr. Christian Holm (Lecture) and working group (Tutorials)

Course language

English

Time and Room

Lecture: Thu 12:00 - 14:00, Phys 1.114
Tutorials: will be discussed in first lecture

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).

Prerequisites

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.

Lecture

Date	Subject
19.4.	Monte-Carlo integration/simulation (Simple vs. Importance sampling, Random walks (RW) and Self-avoiding random walks (SAW)) infos:
26.4.	2D 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)
21.6.	Simulations of Polymers and Polyelectrolytes
28.6.	Poisson-Boltzmann Theory
5.7.	Introduction to the Project work: charged infinite rods in ionic solution
12.7.	Extended tutorial I: project work
19.7.	Extended tutorial II: project work

Tutorials

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 Jose Cerdà
31.5.	Molecular Dynamics: Lennard-Jones liquid	Qiao Baofu
7.6.	Holiday
14.6.	Long range interactions: Direct sum and Ewald summation	Joan Jose Cerdà
21.6.	Introduction to MD simulations with ESPResSo	Mehmet Süzen
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

Recommended literature

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