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Last update: Matějka Pavel prof. Dr. RNDr. (16.06.2019)
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Last update: Kolafa Jiří prof. RNDr. CSc. (08.08.2018)
Students will:
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Last update: Řehák Karel doc. Ing. CSc. (17.10.2018)
R: D. Frenkel a B. Smit: Understanding Molecular Simulation (Academic Press, 1996, 2002); A: M. P. Allen a D. J. Tildesley: Computer Simulation of Liquids (Clarendon Press, Oxford 1986, 2002); |
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Last update: Kubová Petra Ing. (12.04.2018)
http://old.vscht.cz/fch/en/tools/kolafa/S403027.html |
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Last update: Řehák Karel doc. Ing. CSc. (05.11.2018)
1. Introduction - What are simulations good for? 2. Repetition of statistical thermodynamics and less common ensembles (isobaric). 3. Atomistic and lattice models. Force field. 4. Molecular dynamics: Verlet's method, leap-frog. Fundamentals of Hamilton's mechanics, conservation laws. Symplecticity. 5. Other integrators (Gear, multiple timestep). Thermostats in MD. 6. Monte Carlo Methods - MC integration, Metropolis method. Random numbers. 7. Methodology of simulations and measurement of quantities, statistical errors. Boundary conditions. 8. Structural quantities: radial distribution functions, structure factor. 9. Entropic quantities: thermodynamic integration, non-Boltzmann sampling, integration of mean force, Widom's method. 10. Potential range, cutoff corrections. Coulomb's forces: Ewald summation, reaction field. 11. Other ensembles: isobaric, grandkanonical, Gibbs. Additional degrees of freedom in MD: Nose-Hoover, barostat. 12. Other MC methods: preferential sampling, molecules, polymers. Constraint dynamics (SHAKE). Optimization of simulations. 13. Brownian (Langevin) dynamics and DPD. Kinetic quantities: EMD vs. NEMD. 14. Optimization: simulated annealing, genetic algorithms. |
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Last update: Kolafa Jiří prof. RNDr. CSc. (08.08.2018)
Good knowledge of chemical and statistical thermodynamics. Basic knowledge of theoretical mechanics is recommended. |