Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
This work led so far to several high impact publications: for the first time nanobeam diffraction (NBD) orientation mapping was used on atom probe tips, thereby enabling the high throughput characterization of grain boundary segregation as well as the crystallographic identification of phases.
We will investigate the electrothermomechanical response of individual metallic nanowires as a function of microstructural interfaces from the growth processes. This will be accomplished using in situ SEM 4-point probe-based electrical resistivity measurements and 2-point probe-based impedance measurements, as a function of mechanical strain and…
Photovoltaic materials have seen rapid development in the past decades, propelling the global transition towards a sustainable and CO2-free economy. Storing the day-time energy for night-time usage has become a major challenge to integrate sizeable solar farms into the electrical grid. Developing technologies to convert solar energy directly into…
In this project we developed a phase-field model capable of describing multi-component and multi-sublattice ordered phases, by directly incorporating the compound energy CALPHAD formalism based on chemical potentials. We investigated the complex compositional pathway for the formation of the η-phase in Al-Zn-Mg-Cu alloys during commercial…