Advanced Simulation Methods SS 2022
- Lecture and Tutorials (2 SWS in total)
- Prof. Dr. Christian Holm, PD. Dr. Jens Smiatek, aplProf. Dr. Maria Fyta
- Course language
- English or German
- ICP, Allmandring 3; Room: ICP Meeting Room
- (see below)
The course will consist of three modules supervised by Prof. Dr. Christian Holm, PD. Dr. Jens Smiatek, and aplProf. Dr. Maria Fyta. It will contain exercises, presentations, discussion meetings, and written reports, worked out in groups. Each group will have to give a talk for all modules. The students can work in groups. All groups should write a report of about 10 pages on each module, which they should submit to the responsible person for each module by the deadline set for each module.
Module 1: Maria Fyta and Samuel Tovey: Machine-learned Interatomic Potentials
First meeting: Friday, April 23, 2021 at 10:00 (online or in person TBA) in the ICP meeting room (Allmandring 3, 1st floor, room 1.095).
Final meeting and presentation: Friday, May 22; time tba in the ICP meeting room (Allmandring 3, 1st floor, room 1.095).
Tutorials: Fridays 11:30-13:00 in the ICP CIP-Pool. The first tutorial will take place on tba
Deadline for reports: tba-->
This exercise introduces student to the process of developing an inter-atomic potential for liquid argon using machine learning methods. You will follow the process from start to finish, using ab-initio MD methods to construct training data before fitting a model and deploying it in scaled up simulations.
If you have any questions regarding the organization or content of this module please do not hesitate to contact Christian Holm. For practical guidance regarding the simulations Samuel Tovey.
Part 1 -- DFT Simulations
In the first part of the exercise, you will use the CP2K simulation software to perform ab-initio molecular dynamics simulations on a system of liquid argon, in the process experimenting with configuring the interactions between atoms and seeing the results.
Part 2 -- Fitting a Potential
In this part, students will use the data generated in part 1 to fit a Gaussian process regression based machine learned inter-atomic potential. This task will allow the students to develop a deeper understanding of how these potentials are fit and the different parameters that need to be optimised in the process.
In part 3, students use the machine-learned potential to perform scaled up molecular dynamics simulations using the LAMMPS simulation engine. These simulations are compared to the ab-initio data to demonstrate the retention of accuracy with the significantly improved performance.
- Bartók, A. P., Payne, M. C., Kondor, R. & Gábor, C. Gaussian approximation potentials: the accuracy of quantum mechanics, without the electrons. Phys. Rev. Lett. 104, 136403 (2010).
Further reading (if interested)
Module 2: Jens Smiatek: Molecular Theories of Solutions
First meeting: tba
Final meeting and presentation: tba.
Deadline for reports: tba
This module focuses on molecular theories of solution. I will outline the main principles of solvation processes and the corresponding interactions. As we will see, most mechanisms strongly differ from highly idealized assumptions such that more effective descriptions are needed. Such considerations are represented by the Kirkwood-Buff theory of solutions or in the framework of conceptual density functional theory. The corresponding theories will be applied for the study of water-ionic liquid mixtures.
Lecture Notes for Part: Molecular Theories of Solution
Lecture Notes for Part: Conceptual Density Functional Theory
If you have any questions regarding the organization or content of this module, please do not hesitate to contact ???.
Part 1: Molecular Theories of Solution
This part introduces the students to the field of solution research. An important theory to study solvation and binding behavior is given by the Kirkwood-Buff theory which can be well applied to computer simulations. The students should study the literature given below and present their findings. The presentation should at a minimum contain an introduction to Kirkwood-Buff theory in the context of the simulations.
- J. G. Kirkwood and F. P. Buff. "The statistical mechanical theory of solutions. I." J. Chem. Phys. 19, 774 (1951)
- V. Pierce, M. Kang, M. Aburi, S. Weerasinghe and P. E. Smith, "Recent applications of Kirkwood–Buff theory to biological systems", Cell Biochem. Biophys. 50, 1 (2008)
- J. Rösgen, B. M. Pettitt and D. W. Bolen, "Protein folding, stability, and solvation structure in osmolyte solutions", Biophys. J. 89, 2988 (2005)
- J. Smiatek, "Aqueous ionic liquids and their effects on protein structures: an overview on recent theoretical and experimental results", J. Phys. Condens. Matter 29, 233001 (2017)
- E. A. Oprzeska-Zingrebe and J. Smiatek, "Aqueous ionic liquids in comparison with standard co-solutes - Differences and common principles in their interaction with protein and DNA structures", Biophys. Rev. 10, 809 (2018)
- J. Smiatek, A. Heuer and M. Winter, "Properties of ion complexes and their impact on charge transport in organic solvent-based electrolyte solutions for lithium batteries: insights from a theoretical perspective", Batteries 4, 62 (2018)
- T. Kobayashi et al, "The properties of residual water molecules in ionic liquids: a comparison between direct and inverse Kirkwood–Buff approaches", Phys. Chem. Chem. Phys. 19, 18924 (2017)
Part 2: Simulations
This part is practical. The simulations will be conducted by the software package GROMACS . The students will perform the simulations of ionic liquids(IL)-water mixtures at different water concentration in combination with the SPC/E water model and OPLSAA force field for EMImBF4. To generate the initial configuration of the simulation boxes, the software package Packmol  will be used.
First the students simulate pure water and pure IL, and analyze the output data. Following properties will be calculated. The Kirkwood-Buff theory will be used to calculate the Kirkwood-Buff integrals. The student perform the different simulation box size to estimate the proper box size for calculating the properties.
- Kirkwood-Buff integrals
- diffusion coefficients
- mass densities
In addition to above, for water
- hydrogen bond life times and number of hydrogen bonds for water-water pairs
- water mean relaxation times
Next the student perform the IL-water mixtures at different water concentrations. After energy minimization and warm up, run 500 ns simulations with GROMACS for water mole fractions between X_H2O = 0 - 0.30.
In comparison to pure water/pure IL, the students will analyze several properties stated above and elucidate their water concentration dependent behavior. Interpret the corresponding results with regard to the findings in Phys.Chem.Chem.Phys. 19, 18924 (2017).
All the data needed for the exercise can be found in /group/sm/2019/Advsm_part2
Module 3: Christian Holm, Mariano Brito: Electrostatics, Lattice Boltzmann, and Electrokinetics
First meeting: tba
Final meeting and presentation:tba in the ICP meeting room (Allmandring 3, 1st floor, room 1.095).
Tutorials: tba in the ICP CIP-Pool.
Deadline for reports: tba
This module focuses on charged matter with electrostatic and hydrodynamic interactions. It should be taken in groups of three people. It consists of one lecture on electrostatic algorithms, simulations, theory, a presentation and a short report on the simulation results. You only have to give one common presentation and hand in one report. The Module 3 consists of three parts.
If you have any questions regarding the organisation or content of this module please do not hesitate to contact Christian Holm. For questions regarding the practical part of the module and technical help contact Alexander Reinauer.
Part 1: Electrostatics
This part is about the theory of electrostatic algorithms for molecular dynamics simulations. It is concerned with state of the art algorithms beyond the Ewald sum, especially mesh Ewald methods. To this end the students should read the referenced literature. Christian Holm will give an hour long lecture. Afterwards we will discuss the content and try to resolve open questions. The presentation should foster the students understanding of the P3M method as well as give them an overview of its performance compared to other modern electrostatics methods.
- C. Holm.
"Simulating Long range interactions".
Institute for Computational Physics, Universitat Stuttgart, 2018.
[PDF] (15.4 MB)
- C. Holm.
Markus Deserno, Christian Holm.
How to mesh up Ewald sums. I. A theoretical and numerical comparison of various particle mesh routines.
The Journal of Chemical Physics 109:7678, 1998.
[PDF] (307 KB) [DOI]
Axel Arnold, Florian Fahrenberger, Christian Holm, Olaf Lenz, Matthias Bolten, Holger Dachsel, Rene Halver, Ivo Kabadshow, Franz Gähler, Frederik Heber, Julian Iseringhausen, Michael Hofmann, Michael Pippig, Daniel Potts, Godehard Sutmann.
Comparison of scalable fast methods for long-range interactions.
Physical Review E 88(6):063308, 2013.
[PDF] (2.3 MB) [DOI]
Axel Arnold, Christian Holm.
Efficient methods to compute long range interactions for soft matter systems.
In Advanced Computer Simulation Approaches for Soft Matter Sciences II, pages 59–109. Edited by C. Holm, K. Kremer. Part of Advances in Polymer Science.
Springer, Berlin, 2005. ISBN: 9783540260912.
[PDF] (1.1 MB) [DOI]
Part 2: Electro-Osmotic Flow
This part is practical. It is concerned with the movement of ions in an charged slit pore. It is similar to the systems that are discussed in the Bachelors thesis of Georg Rempfer which is recommended reading. A slit pore consists of two infinite charge walls as shown in the figure to the right. In this exercise you should simulate such a system with ESPResSo. You are supposed to use a Lattice Boltzmann fluid coupled to explicit ions which are represented by charge Week-Chandler-Anderson spheres. In addition to the charge on the walls, the ions are also subject to an external electrical field parallel to the walls. Electrostatics should be handled by the P3M algorithm with ELC. A set of realistic parameters and an more in detail description of the system can be found in the thesis. You should measure the flow profile of the fluid and the density and velocity profiles of the ions. The case of the slit pore can be solved analytically either in the case of only counter ions (the so called salt free case) or in the high salt limit (Debye-Hueckel-Limit). Calculate the ion profiles in one or both of these cases and compare the results with the simulation.
Worksheet 2021 Detailed worksheet (94 KB)
Some ESPResSo tutorials can be helpful.
- Introductory tutorials, Intermediate tutorials: Lattice-Boltzmann and Charged systems Tutorials for ESPResSo 4.1.4
- The Part 2 of the charged systems tutorial to see how to setup proper electrostatics in quasi-2D geometry.
- Georg Rempfer, "Lattice-Boltzmann Simulations in Complex Geometries" (1.36 MB), 2010, Institute for Computational Physics, Stuttgart
Part 3: Electrophoresis of Polyelectrolytes
In this part you simulate the movement of a charged polymer under the influence of an external electrical field and hydrodynamic interactions. Set up a system consisting of a charged polymer, ions with the opposite charge to make the system neutral and an Lattice Boltzmann fluid coupled with the the ions and polymer. Apply an external field and measure the center of mass velocity of the polymer as a function of the length of the polymer for polymers of one to 20 monomers. Make sure the system is in equilibrium before you start the sampling. Compare your result to theory and experimental results (see literature).
Detailed worksheet (103 KB)
Instructions and Literature
General part and part 5 of Media:04-lattice_boltzmann.pdf
Kai Grass, Ute Böhme, Ulrich Scheler, Hervé Cottet, Christian Holm.
Importance of Hydrodynamic Shielding for the Dynamic Behavior of Short Polyelectrolyte Chains.
Physical Review Letters 100(9):096104, 2008.
[PDF] (115 KB) [DOI]
Kai Christian Grass.
Towards realistic modelling of free solution electrophoresis: a case study on charged macromolecules.
PhD thesis, Goethe-Universität Frankfurt am Main, 2008.
[PDF] (5.3 MB)
At the final meeting day of this module, one group will give a presentation about the learned and performed work. In addition, they write a report of about 5 pages containing and discussing the obtained results and hand it in together with the reports of the other modules at the end of the course (see above).
The final report is due electronically TBA