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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, chemical kinetics, chemical and statistical thermodynamics, chemoinformatics, molecular modeling). After explaining the theoretical background of major topics (such as electronic structure of atoms and molecules, ensembles in statistical thermodynamics, reaction rates in chemical kinetics, …) the course describes how the resulting problems can be solved mostly using numerical methods on a computer. The course is supplemented by a practical workshop. Last update: Ušelová Kateřina, RNDr., Ph.D. (31.01.2022)
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Last update: Ušelová Kateřina, RNDr., Ph.D. (31.01.2022)
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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. Last update: 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: Kinetic and Dynamic Methods ·Statistical mechanics Monte Carlo (overview) Ensembles Partition functions Molecular dynamics Collision and transition state theory 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) Last update: Heard Christopher James, Ph.D. (05.09.2024)
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