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The course covers advanced methods of molecular and coarse-grained computer simulations with applications in biology, thermodynamics of solutions, and theory of phase transitions. The selection of applications will be tailored to the group of Ph.D. students.
Last update: Matějka Pavel (16.06.2019)
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Student will receive an overview of modern MC and MD simulation methods of molecular systems. Last update: Kolafa Jiří (28.05.2018)
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active participation in seminars (50 %) oral exam (50 %) Last update: Kolafa Jiří (28.05.2018)
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K. Binder and D. Heermann: Monte Carlo Simulation in Statistical Physics: An Introduction (Springer International, 6th Edition, 2019); Ch. Chipot and A. Pohorille: Free Energy Calculations Theory and Applications in Chemistry and Biology (Springer-Verlag 2007); D. Frenkel and B. Smit: Understanding Molecular Simulation (Academic Press, 1996, 2002); M.P. Allen and D.J. Tildesley: Computer Simulation of Liquids (Clarendon Press, Oxford 1986, 2002); U.R. Pedersen: Direct calculation of the solid-liquid Gibbs free energy difference in a single equilibrium simulation, J. Chem. Phys. 139, 104102 (2013); J.R. Espinosa, C. Vega, E. Sanz: The mold integration method for the calculation of the crystal-fluid interfacial free energy from simulations, J. Chem. Phys. 141, 134709 (2014); M. Dinpajooh, P. Bai, D.A. Allan, and J.I. Siepmann: Accurate and precise determination of critical properties from Gibbs ensemble Monte Carlo simulations, J. Chem. Phys. 143, 114113 (2015);
and selected articles Last update: Heyda Jan (06.09.2019)
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Lectures (50 %) and seminars (50 %) from hot topics. Last update: Kolafa Jiří (28.05.2018)
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1. Parallel tempering – Replica Exchange Molecular Dynamics. 2. Metadynamics – application of adjustable external potential. 3. Kinetics of rare events techniques – transition path sampling. 4. Generalized Monte Carlo methods – Wang-Landa algorithm. 5. Statistical thermodynamics of solutions – Kirkwood-Buff theory. 6. Free energy functional theory – mean-field theories, Flory-de-Gennes theory. 7. Langevin equation, fluctuation-dissipation theorem. Stochastic thermostats. 8. Brownian dynamics, dissipative particle dynamics. 9. Special ensembles in MC: from the grand canonical ensemble to Gibbs ensemble to reaction ensemble. Osmotic ensemble in MC and MD. 10. Phase equilibria. Slab geometry, chemical potential of liquids and crystals. 11. Surface tension and interfacial energy of crystals. 12. Critical point: how to beat critical slowing-down, finite-size scaling, renormalization group. 13. MD and MC simulations of polarizable molecules. 14. Kinetic quantities (viscosity, el. conductivity, diffusivity). EMD: Linear Response Theory, Green-Kubo formulas, Einstein relations. NEMD, SLODD. Last update: Kolafa Jiří (28.05.2018)
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http://old.vscht.cz/fch/en/tools/kolafa/S403027.html http://www.vscht.cz/fch/cz/pomucky/kolafa/molsim.pdf https://janheyda.wordpress.com/teaching/mdsimexp/ Last update: Heyda Jan (29.05.2018)
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Good knowledge of thermodynamics and statistical thermodynamics. Basic knowledge of simulation methods MC, MD. Last update: Kolafa Jiří (28.05.2018)
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