Studying magnetic properties of materials

TMM researches phenomena driven by spin-orbit coupling in materials by using first-principles methods, like density functional theory (DFT), DFT+U and dynamical mean field theory (DMFT) methods. We also perform multi-scale simulations with the help of a highthroughput structure database. We develop methodologies to evaluate the properties of materials. Moreover we are applying machine learning methods on materials design, in particular inverse design.

The mission of the Theory of Magnetic Material group is

  • to design novel magnetic materials and stable/metal-stable new magnetic compounds
  • to perform multi-scale simulations in order to bridge intrinsic and experimental measurements

Three pillars of our research

Three pillars of TMM: HTP density functional theory (DFT) calculations, machine learning, and phase diagram optimisation based on the CALculation of PHAse Diagrams (CALPHAD) method.

Some ongoing studies

Our research areas in detail

High-throughput
High-throughput
Machine Learning
Machine Learning
CALPHAD
CALPHAD
Past Research