Our research interests are in the areas of superconductivity, magnetism, defects and thermoelectric materials. Structure prediction is the driven-force behind to accelerate the design of novel materials. We use theoretical tools (mostly at density-functional theory level) implemented in computational codes that efficiently calculate electronic band structure on complex structures. We are also interested in development algorithms to be exploited in high-throughput computational screening for new materials. Machine-learning started to make his on way in our research, currently one main project points towards this direction.


This figure illustrate the map of the different materials we specialize on, as well as the techniques or keywords for specific spectroscopy.