Hüter, C.; Nguyen, C.-D.; Spatschek, R. P.; Neugebauer, J.: Scale bridging between atomistic and mesoscale modelling: Applications of amplitude equation descriptions. Modelling and Simulation in Materials Science and Engineering 22 (3), 034001 (2014)
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
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
Electron microscopes offer unique capabilities to probe materials with extremely high spatial resolution. Recent advancements in in situ platforms and electron detectors have opened novel pathways to explore local properties and the dynamic behaviour of materials.
In this project, we aim to design novel NiCoCr-based medium entropy alloys (MEAs) and further enhance their mechanical properties by tuning the multiscale heterogeneous composite structures. This is being achieved by alloying of varying elements in the NiCoCr matrix and appropriate thermal-mechanical processing.
Here, we aim to develop machine-learning enhanced atom probe tomography approaches to reveal chemical short/long-range order (S/LRO) in a series of metallic materials.