Course will cover both classical and modern topics of computational methods in atomistic simulations of condensed matters. We will begin from classical representations of electric and heat transport in condensed matter and will finish with modern theories covering the molecular dynamics methods coupled with density functional theory and applications of machine learning. Practical part of the course will be devoted to hands-on sessions where students will apply these theories on practice by performing calculations of real materials. This will give an entire picture of applied computational methods allowing the solution of various tasks like calculations of mechanical properties of solid-state compounds, lattice dynamics, thermal conductivity etc.
The course provides a graduate level overview of selected topics of materials science related to formation of material and its stability. We will begin with the stability of materials by defining the energy contributions responsible for the stability including configuration, vibrational, and thermodynamic contributions to Gibbs free energy. Next, we will consider phase transitions and phase diagrams of materials with various dimensionality. One of the important factors responsible for stabilization is the formation of defects. Types of defects in bulk and 2D materials will be discussed. Considering all the above we will move to discussion of properties of surfaces and thin films which are the most important materials for sensing, energy storage, catalysis, and other applications.