Theoretical Methods in Chemistry - MC260P146

• Title: Theoretical Methods in Chemistry
• Guaranteed by: Department of Physical and Macromolecular Chemistry (31-260)
• Faculty: Faculty of Science
• Actual: from 2023 to 2023
• Semester: winter
• E-Credits: 5
• Examination process: winter s.:
• Hours per week, examination: winter s.:2/2, C+Ex [HT]
• Capacity: unlimited
• Min. number of students: unlimited
• 4EU+: no
• Virtual mobility / capacity: no
• State of the course: not taught
• Language: English
• Note: enabled for web enrollment
• Guarantor: Christopher James Heard, Ph.D.

Annotation

Last update: RNDr. Kateřina Ušelová, Ph.D. (31.01.2022)

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.

Literature

Last update: RNDr. Kateřina Ušelová, Ph.D. (31.01.2022)

• P. W. Atkins, J. de Paula, J. Keeler: Atkins’ Physical Chemistry, Oxford University Press, 2018, ISBN 0198769865.

• D. A. McQuarrie, J. D. Simon: Physical Chemistry: A Molecular Approach, University Science Books, 1997, ISBN 0935702997.

• I. Levine: Quantum Chemistry, Pearson, 2013, ISBN 0321803450.

• P. W. Atkins, R. S. Friedman: Molecular Quantum Mechanics, Oxford University Press, 2010, ISBN 0199541426.

• M. E. Tuckerman: Statistical Mechanics: Theory and Molecular Simulation, Oxford University Press, 2010, ISBN 0198525265.

• S. M. Blinder, J. E. House: Mathematical Physics in Theoretical Chemistry, Elsevier, 2019, ISBN 0128136510.

Requirements to the exam

Last update: RNDr. Kateřina Ušelová, Ph.D. (31.01.2022)

Final mark is based on the oral examination (80%) and results of tests during the course (20%). Oral examination takes place during the examination period and students must first obtain a credit for the workshop. The credit for the workshop is based on the solution of take-home exercises.

Syllabus

Last update: RNDr. Kateřina Ušelová, Ph.D. (31.01.2022)

• Discrete problems (combinatorics, enumeration, lattice problems, prediction of NMR and EPR spectra)

• Continuous problems (root finding, minimization, integration, interpolation)

• Problems described by ordinary differential equations (chemical kinetics, molecular mechanics)

• Problems described by partial differential equations (Poisson-Boltzmann equation, diffusion, Schrödinger equation)

• Electronic structure of atoms and molecules (Hartree-Fock method, configurational interaction, density functional theory, quantum Monte Carlo methods)

• Group theory and symmetry (applications to electronic structure and spectroscopy)

• Statistical description of data and modeling (least squares methods and confidence limits, estimation of statistical parameters)

• Statistical thermodynamics (ensembles, Monte Carlo methods, molecular dynamics, free energy calculation)

• Chemoinformatics (quantitative structure-activity relationship, molecular descriptors)

• Machine learning in chemistry (supervised learning, linear models, kernels, feature sets, neural networks)

• Signal processing and discrete Fourier transform