Course title: Computational Chemistry and Materials Modeling

Class hours and location: Term 2, Mon/Wed/Fri 9:00-12:00, via Zoom (after 12:00 we switch to optional activities for interested students)

Course website:

Course LMS site: LMS, use it to

Course facilities: TBD (previously CMS Lab)

Educational: code MA06008, 8 weeks by 20 hours, 6 ECTS, graduate level (MSc/PhD), max 10 students per TA, core course in Computational Materials Science track, the follow-up course is Advanced Materials Modeling

Course address: online course

Course development: Sergei Tretiak and A.Z., Dmitry Aksenov since 2017, see list of lecturers here and TAs here

Instructor: Andriy Zhugayevych

Office: 0.118

Office hours: in Zoom class after 12:00, or by appointment in Zoom class before 9:00, or other time by Zoom-appointment

Phone: 478

E-mail:, student emails will usually be answered in class

Co-Instructors: Sergei Tretiak, Sergey Levchenko, Dmitry Aksenov


Lecturers: TBD

Description: The course provides a graduate level overview of modern atomistic computer simulations used to model, understand and predict properties of technologically important materials. The emphasis is on practical use of techniques, algorithms and programs to bridge theory and applications, from the discovery of materials to their use in real-world technologies. Several laboratories give students direct experience with simulation methods as well as practical knowledge on how to use computational modeling and how to present and interpret results of simulations. Bridges from atomic to complex systems demonstrate potential of different theories to applications relevant to multiple major industries in the future, including nanotechnology and energy.

Intended learning outcomes: At the end of the course, the students will be able to:

Assessment (see details here, see grading scheme):

Prerequisites: The course relies on strong undergraduate math/physics background, however no background in computational chemistry is assumed or required. The general background in materials science is provided by Survey of Materials course (Part I). See also Background literature and Required software. If you plan to improve your background beyond the required minimum see this list.


Course content (see details here):

  1. Basics of quantum chemistry: Schrodinger equation for electrons, Born-Oppenheimer approximation, basis set.
  2. The ab initio many-body problem:from Hartree-Fock to wavefunction techniques.
  3. Density Functional Theory (DFT): applications and performance.
  4. Electronically excited states and theoretical spectroscopy. Polarizabilities, normal modes, vibrational spectra.
  5. Computational chemistry of molecules.
  6. Computational chemistry of crystals.
  7. Tight-binding and semiempirical approaches (including DFTB).
  8. Classical molecular dynamics (force fields, empirical potentials).
  9. Materials data science: Exploring materials space.
  10. Special methods co-developed by lecturers: MLIP, FHI-aims, Abinit, NEXMD.