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Lecturer(s)
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Kužela Tomáš, Ing.
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Ingr Marek, doc. RNDr. Ph.D.
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Kolaříková Alena, Ing.
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Kutálková Eva, RNDr. Ph.D.
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Course content
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- Basics of statistical thermodynamics - statistical ensembles, partition functions, calculations of thermodynamic state functions. - Classical simulations of thermodynamic systems using the molecular dynamics (MD) method, Newton's equations of motion, periodic boundary conditions, systems at constant temperature and pressure, force fields. Monte-Carlo (MC) method. - Distribution functions of particles of the system. Calculation of thermodynamic state functions using MD and MC, Gibbs and Helmholtz energies, solvation energy, stability of supramolecular complexes. - Rough molecular dynamics and mesoscale simulations - non-atomistic simulations of large systems. - Quantum chemistry - Hamiltonian operator, Schrödinger equation, solving eigenvalue and eigenfunction problems. - Multi-electron systems, Pauli principle, Slater determinant. Spin of electrons in multi electron systems, closed and open shell systems. - Variational principle, perturbation theory, molecular orbitals as linear combinations of atomic orbitals, bases. - Hartree-Fock self-consistent field (HF-SCF) method. Correlation energy. Slater-Condon rules. - Configurational interaction (CI), Moller-Plesset perturbation theory (MPx), coupled cluster (CC) method. Semiempirical methods. - Density functional theory (DFT) and TDDFT. Applications to multi-atom systems. - Geometry of molecules, Born-Oppenheimer approximation, potential energy hyperplane, vibrational spectra, calculations of molecular properties. Mechanisms of chemical reactions. - Calculations of excited states of molecules and optical spectra of molecules, multireference methods. - Dynamic methods combining classical and quantum approaches - ab initio MD, QM/MM method - simulation of enzyme reactions. - Quantum dynamics - nuclear wave function, propagation of time-dependent Schrödinger equation, MCTDH method.
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Learning activities and teaching methods
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Monologic (Exposition, lecture, briefing), Simple experiments, Practice exercises
- Preparation for examination
- 180 hours per semester
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| learning outcomes |
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| Knowledge |
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| explain the principle of variation and failure theory |
| explain the principle of variation and failure theory |
| explain the Born-Oppenheimer approximation |
| explain the Born-Oppenheimer approximation |
| explain dynamic methods combining classical and quantum approaches |
| explain dynamic methods combining classical and quantum approaches |
| describe the geometry of molecules |
| describe the geometry of molecules |
| discuss the Slater-Condon rules |
| discuss the Slater-Condon rules |
| Skills |
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| apply the Hartree-Fock self-consistent field method |
| apply the Hartree-Fock self-consistent field method |
| calculate the excited states of molecules |
| calculate the excited states of molecules |
| calculate the optical spectra of molecules |
| calculate the optical spectra of molecules |
| calculate molecular properties |
| calculate molecular properties |
| define configuration interactions |
| define configuration interactions |
| teaching methods |
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| Knowledge |
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| Monologic (Exposition, lecture, briefing) |
| Monologic (Exposition, lecture, briefing) |
| Dialogic (Discussion, conversation, brainstorming) |
| Dialogic (Discussion, conversation, brainstorming) |
| Skills |
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| Simple experiments |
| Simple experiments |
| Practice exercises |
| Practice exercises |
| assessment methods |
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| Knowledge |
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| Oral examination |
| Oral examination |
| Analysis of works made by the student (Technical products) |
| Analysis of works made by the student (Technical products) |
| Grade (Using a grade system) |
| Grade (Using a grade system) |
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Recommended literature
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CRAMER, C.J. Essentials of Computational Chemistry. 2nd Ed.. Chichester: John Wiley & Sons, 2016.
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JENSEN, M. Introduction to Computational Chemistry. 3rd Ed.. Chichester: John Wiley & Sons, 2017.
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LIWO, A. (Ed.). Computational Methods to Study the Structure and Dynamics of Biomolecules and Biomolecular Processes. Heidelberg: Springer, 2014.
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NEZBEDA, I., KOLAFA, J., KOTRLA, M. Úvod do počítačových simulací. Metody Monte Carlo a molekulární dynamiky. Praha: Karolinum, 2003.
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SLAVÍČEK, P., MUCHOVÁ, E. Kvantová chemie: První čtení. Praha: VŠCHT, 2019.
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WILLOCK, D.J. Molecular Symmetry. Chichester: John Wiley & Sons, 2009.
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