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The course Theoretical Methods in Chemistry provides an overview of basic techniques that are common in different fields of theoretical chemistry (such as quantum and computational chemistry, statistical thermodynamics, molecular modeling, chemoinformatics, …). After explaining the theoretical background (such as electronic structure of atoms and molecules, ensembles in statistical thermodynamics, …) the course describes how the resulting equations can be solved using numerical methods on a computer. The course is supplemented by a practical workshop.
Poslední úprava: Uhlík Filip, prof. RNDr., Ph.D. (21.12.2025)
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- P. W. Atkins, J. de Paula, J. Keeler: Atkins’ Physical Chemistry, Oxford University Press, 2018, ISBN 0198769865. Poslední úprava: Uhlík Filip, prof. RNDr., Ph.D. (21.12.2025)
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Final mark is based on the final exam (66%) and credit derived from class participation during course (33%). Final exam is comprised equally of a (1 hr) written exam and oral exam, to cover the concepts discussed within the course materials. Poslední úprava: Heard Christopher James, Ph.D. (05.09.2024)
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Lecture 1: Introduction to theoretical chemistry History of chemical theory, development of theoeretical methods in chemistry (quantum chemistry). Development of computational techniques. Introduction to electronic structure theory Concepts in modelling (accuracy/precision) Overview of course structure Lecture 2: Potential Energy Surfaces Concept of PES, harmonic approximation, Born-Oppenheimer Approximation, Normal Mode analysis. Critical points on the PES, algorithms for locating minima/transition states Searching the PES (global optimization and statistical methods for characterising the PES) Classification/visualization of PES Failure of BOA and implications to chemistry/physics/biology Lecture 3: Wavefunction methods in quantum chemistry Single electron methods (Hartree Fock) Variational principle LCAO, slater determinants and basis sets Approximations, derivations and application of HF. Restricted/unrestricted HF Accuracy and limitations - implications Lecture 4: Density methods in quantum chemistry Density-based methods (Thomas-Fermi -> density functional theory) Accuracy and limitations exchange and correlation Linear response Applications Lecture 5: Semi-Empirical methods Force-field methods (LJ, metallic fields, biological/protein FF) Introduction to fitted forcefields (training and testing) Approximate solutions to HF (INDO/MINDO) Huckel theory for conjugated organic molcules Coarse graining for polymers Lecture 6: Post-HF wavefunction methods Correlation methods (CI, perturbation theory, CCSD) Lecture 7: Symmetry and spectroscopy group theory in chemistry Application of symmetry to analysis of bonding, structure and spectral properties Lecture 8: Excited states Failures of BOA, conical intersections, avoided crossings Time-dependent DFT for calculation of optical response, UV-VIS spectra, photoelectron spectra Non-adiabatic dynamics Lecture 9 + Lecture 10: Statistical thermodynamics and molecular simulations (additional materials at https://11c.cz/st) Statistical mechanics Ensembles Partition functions Monte Carlo methods Molecular dynamics (Learning outcomes: Students will be able to describe basic postulates and ideas of statistical thermodynamics, work with partition functions and derive expressions for thermodynamic quantities, will be able to use and understand Monte Carlo calculations for calculation of integrals and sampling of arbitrary distributions, will be able to use and understand molecular dynamics methods for calculation of time averages) Lecture 11 + Lecture 12: Machine Learning Methods Supervised and unsupervised learning Clustering and characterisation (SVM) Multivariate regression (LASSO, KRR) chemoinformatics/materials - LLMs, QSAR Machine Learned Potentials (Featurization, training, active learning, delta learning, error estimation) interpretable AI ML integration into tools (surrogate methods) Poslední úprava: Uhlík Filip, prof. RNDr., Ph.D. (09.01.2026)
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