Ab initio and atomistic modelling
We develop methods bridging quantum mechanical description of electronic structure and bonding with atomic scale classical modelling, which can be used for large spatial and temporal scales in the statistical simulations of the thermodynamic and kinetic properties of materials. We apply these methods to study the properties of functional materials, used in clean energy applications (fuel cells, ion batteries, solar cells, electrochromic cells) and catalysis, as well as the properties of metals, alloys and nanostructures.
The list of developed codes includes: 1) a highly efficient EMTO-based LSGF method (ELSGF), which can be used for accurate calculations of electronic structure of multicomponent random alloys modelled by a super up to several thousand atoms with a finite degree of the atomic short-range order and in disordered magnetic state, including approximate account of longitudinal spin-fluctuations (Prof. A.Ruban); KKR-ASA- and EMTO-based codes for calculating effective chemical and magnetic interactions of different types of classical configurational Hamiltonians (Prof. A.Ruban); different types of Monte Carlo codes for statistical thermodynamic (Prof. A.Ruban); Kinetic Monte Carlo code (KMClib, https://github.com/leetmaa/KMCLib, Prof. N.Skorodumova); non-equilibrium Molecular Dynamics colour charge algorithm, which allows us to study ionic diffusion in solids with slow dynamics (Prof. N.Skorodumova)