Difference between revisions of "Advanced Simulation Methods SS 2022"
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===== Worksheet =====
===== Worksheet =====
==== Literature ====
==== Literature ====
Latest revision as of 21:08, 24 June 2022
- Lecture and Tutorials (2 SWS in total)
- Prof. Dr. Christian Holm, aplProf. Dr. Maria Fyta, Dr. Alexander Schlaich
- 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.
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: Alexander Schlaich: Molecular modeling of electrode/electrolyte interfaces
First meeting: 13th of May, 22 in the Seminar Room
Final meeting and presentation: 10th of June, 22
If there are any questions regarding the exercise, contact Philipp Stärk.
Deadline for reports: 9th of June, 22. (For feedback, please hand in the first draft one week before!)
This module focuses on molecular modeling of electrode interfaces and confinement effects thereof. Such interfaces are highly relevant for numerous applications such as energy storage and catalysis. We will introduce simulation approaches to study the electrochemical double layer and capacitative performance of different materials. The corresponding approaches will be applied to study the performance of aqueous electrolyte supercapacitors.
Important Constant Potential References
- Siepmann, J. I.; Sprik, M. Influence of Surface Topology and Electrostatic Potential on Water/Electrode Systems. J. Chem. Phys. 1995, 102 (1), 511–524. https://doi.org/10.1063/1.469429.
- Scalfi, L.; T. Limmer, D.; Coretti, A.; Bonella, S.; A. Madden, P.; Salanne, M.; Rotenberg, B. Charge Fluctuations from Molecular Simulations in the Constant-Potential Ensemble. Physical Chemistry Chemical Physics 2020, 22 (19), 10480–10489. https://doi.org/10.1039/C9CP06285H.
- Gingrich, T. R.; Wilson, M. On the Ewald Summation of Gaussian Charges for the Simulation of Metallic Surfaces. Chemical Physics Letters 2010, 500 (1), 178–183. https://doi.org/10.1016/j.cplett.2010.10.010.
- Ahrens-Iwers, L. J. V.; Tee, S. R.; Meißner, R. H. ELECTRODE: An Electrochemistry Package for LAMMPS. arXiv:2203.15461 [physics] 2022.
Further References for Interfacial Physics and Related Methods
- Tyagi, S.; Süzen, M.; Sega, M.; Barbosa, M.; Kantorovich, S. S.; Holm, C. An Iterative, Fast, Linear-Scaling Method for Computing Induced Charges on Arbitrary Dielectric Boundaries. J. Chem. Phys. 2010, 132 (15), 154112. https://doi.org/10.1063/1.3376011.
- Loche, P.; Wolde-Kidan, A.; Schlaich, A.; Bonthuis, D. J.; Netz, R. R. Comment on ``Hydrophobic Surface Enhances Electrostatic Interaction in Water’’. Phys. Rev. Lett. 2019, 123 (4), 049601. https://doi.org/10.1103/PhysRevLett.123.049601.
- Kornyshev, A. A. On the Non-Local Electrostatic Theory of Hydration Force. Journal of electroanalytical chemistry and interfacial electrochemistry 1986, 204 (1–2), 79–84.
- Breitsprecher, K.; Szuttor, K.; Holm, C. Electrode Models for Ionic Liquid-Based Capacitors. J. Phys. Chem. C 2015, 119 (39), 22445–22451. https://doi.org/10.1021/acs.jpcc.5b06046.
- Bonthuis, D. J.; Gekle, S.; Netz, R. R. Profile of the Static Permittivity Tensor of Water at Interfaces: Consequences for Capacitance, Hydration Interaction and Ion Adsorption. Langmuir 2012, 28 (20), 7679–7694. https://doi.org/10.1021/la2051564.
Module 3: Christian Holm, Mariano Brito: Electrostatics, Lattice Boltzmann, and Electrokinetics
First meeting: Friday, June 24, 16:00 h.
Location: Final meeting and presentation in the ICP meeting room (Allmandring 3, 1st floor, room 1.095).
Tutorials: arrange with tutor.
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 Mariano Brito.
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.
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 charged 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.
Detailed worksheet (89 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 (98 KB)
Instructions and Literature
General part and part 5 of Media:04-lattice_boltzmann.pdf
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