Simulation Techniques for Soft Matter Sciences (SS 2007)
Overview
- Type
- Lecture (2 SWS) and Tutorials (2 SWS)
- Lecturer
- PD Dr. Christian Holm (Lecture) and coworkers (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, 1.1??). 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)) |
| 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
- Introduction by Kai Grass
- Random walks by Kai Grass
- Monte Carlo: The Ising model I by Marcello Sega
- Monte Carlo: The Ising model II by Marcello Sega
- Error analysis by Joan Jose Cerdà
- Molecular Dynamics: The Lennard-Jones liquid by Qiao Baofu
- Long range forces: Direct sum vs. Ewald summation by Joan Jose Cerdà
- ESPResSo: A flexible Molecular Dynamics software package by Mehmet Suzen
- VMD: A tool for visualizing simulation data by Olaf Lenz
- Simulating polymers by Qiao Baofu
- Project: Charged systems by Olaf Lenz and Mehmet Suzen
Note: You will work on the project in the last two weeks of the semester.
Recommended literature
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