Böhm, D.; Beetz, M.; Kutz, C.; Zhang, S.; Scheu, C.; Bein, T.; Fattakhova-Rohlfing, D.: V(III)-Doped Nickel Oxide-Based Nanocatalysts for Electrochemical Water Splitting: Influence of Phase, Composition, and Doping on the Electrocatalytic Activity. Chemistry of Materials 32 (24), pp. 10394 - 10406 (2020)
Gänsler, T.; Hengge, K. A.; Beetz, M.; Pizzutilo, E.; Scheu, C.: Tracking the Degradation of Fuel Cell Catalyst Particles: 3D Reconstruction of Nanoscale Transmission Electron Micrographs. CINEMAX IV, "Best poster Award at the Summer School", Toreby, Denmark (2018)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…