Ab initio modelling of structural and magnetic phase transitions under pressure and doping for the iron based superconductors

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The goal of this project is a better understanding of the interplay between magnetism, structural transitions and superconductivity as a function of pressure and doping in the iron-based superconductors by a combination of ab initio density functional theory (DFT) calculations, Car- Parrinello molecular dynamics and dynamical mean field theory (DMFT). We will explore the nature of the structural, magnetic and superconducting phase transitions in these multiband systems i) by performing electronic structure calculations in the framework of first principles (Car- Parrinello) molecular dynamics. We will compare bandstructures with ARPES results. ii) by performing momentum-dependent and orbital-resolved susceptibility calculations at various pressures and dopings. For the latter we will implement the evaluation of the corresponding matrix elements within DFT. These calculations will allow us to quantify the amount of intra- and inter-band as well as intra- and inter-orbital nesting, which may be a key quantity for understanding the interplay between magnetism and superconductivity. iii) by performing a systematic investigation of the optical properties as a function of pressure and doping within DFT and DMFT. The possible correlated nature of these materials will be analyzed. iv) by calculating angle dependent de Haas-van Alphen (dHvA) frequencies and compare them to available measurements. These calculations will allow a better characterization of the evolution of Fermi surfaces under pressure and doping. v) by analyzing the spin dynamics in these systems under pressure in terms of susceptibility calculations as well as non-collinear calculations. In the iron chalcogenide (“11”) compounds, a non-collinear magnetic ground state was observed, which needs to be addressed by corresponding calculations. And finally we plan to search for adequate exchange-correlation functionals within DFT that allow a better prediction of structures and magnetic properties.