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The course covers the fundamentals of statistical thermodynamics of classical molecular systems and its applications in molecular modelling. The lecture includes general methods of mathematical statistics, which can be used in many other fields.
Last update: Pátková Vlasta (09.01.2018)
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Elaboration of an individual project. Comutational tests. Oral exam. Last update: Řehák Karel (02.03.2018)
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R:Malijevský A, Lekce ze statistické termodynamiky, VŠCHT, Praha, 2009, 978-80-7080-710-1 R:Nezbeda I.,Kolafa J.,Kotrla M., Úvod do počítačových simulací. Metody Monte Carlo a molekulární dynamiky, Karolinum, Praha, 2003, 80-246-0649-6 A: Atkins P.W., de Paula J., Physical Chemistry, Oxford University Press, 2010, 978-0-19-954337-3 A: Frenkel D.,Smit B, Understanding Molecular Simulation � From Algorithms to Applications, New York, 2002, Academic Press, 0-12-267351-4 A: Allen M. P.,Tildesley D. J., Computer Simulation of Liquids, Oxford, Clarendon Press, 2002, 0-19-855375-7 Last update: Pátková Vlasta (09.01.2018)
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1. Classical thermodynamics - a brief overview. Basic principles of statistical mechanics, ergodic hypothesis. Phase space. 2. Mathematical statistics - main distributions: binomial, Poisson, Gaussian. Mean and fluctuation. Stirling's formula (derivation). 3. Microcanonical ensemble. Entropy as a measure of chaos. A link between statistical mechanics and thermodynamics. 4. Virial and equipartition theorem. Calculation of energy and specific heats - examples. 5. Canonical and grand-canonical ensembles. Thermodynamic functions and their fluctuations. Partition function. 6. Ideal gas: from the partition function towards the equation of state. 7. Non-ideal systems. Molecular models. Correlation functions and structure factor. Virial expansion. 8. Application I: Calculation of equilibrium constant for the chemical reactions in the gas phase. 9. Application II: harmonic ideal crystal and black-body radiation. 10. Modeling in chemistry: forces between molecules, force field. Molecular mechanics. Boundary conditions, calculation of long-range forces. 11. Molecular dynamics: integrators, integrals of motion. Thermostat and barostat. 12. Monte Carlo: Markov Chain, Metropolis Algorithm. Random numbers. MC in different ensembles. Optimization. 13. Computer Experiment: design, measurement of quantities, analysis of uncertainties. 14. Kinetic quantities in equilibrium and non-equilibrium MD. Brownian dynamics and dissipative particle dynamics. Last update: Kolafa Jiří (08.02.2018)
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http://www.vscht.cz/fch/cz/pomucky/kolafa/N403027.html Last update: Pátková Vlasta (09.01.2018)
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The students will be able to: Understand fundamentals of (classical) molecular systems Apply statistical and simulation methods for stochastic processes Determine measurable (macroscopic) quantities from the molecular characteristics of matter Last update: Pátková Vlasta (09.01.2018)
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Physical chemistry I and II Last update: Pátková Vlasta (09.01.2018)
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Teaching methods | ||||
Activity | Credits | Hours | ||
Obhajoba individuálního projektu | 0.5 | 14 | ||
Účast na přednáškách | 1.5 | 42 | ||
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi | 1.5 | 42 | ||
Práce na individuálním projektu | 1 | 28 | ||
Příprava na zkoušku a její absolvování | 1 | 28 | ||
Účast na seminářích | 0.5 | 14 | ||
6 / 6 | 168 / 168 |
Coursework assessment | |
Form | Significance |
Defense of an individual project | 10 |
Report from individual projects | 20 |
Continuous assessment of study performance and course -credit tests | 50 |
Oral examination | 20 |