Li, J.; Dehm, G.; Kirchlechner, C.: Differences in dislocation source activation stress in the grain interior and at twin boundaries using nanoindentation. Nanobruecken 2018, Erlangen, Germany (2018)
Duarte, M. J.; Harzer, T. P.; Dehm, G.: Towards ultra-strong alloys: thermal stability and diffusion kinetics of thin films by in-situ TEM. CALPHAD XLVII Conference, International Conference on Computer Coupling of Phase Diagrams and Thermochemistry, Querétaro, Mexico (2018)
Herbig, M.; Parra, C.D.; Lu, W.; Toji, Y.; Liebscher, C.; Li, Y.; Goto, S.; Dehm, G.; Raabe, D.: Where does the carbon atom go in steel? – Insights gained by correlative transmission electron microscopy and atom probe tomography. International Symposium on Steel Science 2017, Kyoto, Japan (2017)
Hieke, S. W.; Willinger, M. G.; Wang, Z.-J.; Richter, G.; Dehm, G.; Scheu, C.: Evolution of faceted voids and fingering instabilities in a model thin film system - Insights by in-situ environmental scanning electron microscopy. Symposium - In situ Microscopy with Electrons, X‐rays and Scanning Probes, Universität Erlangen‐Nürnberg, Erlangen, Germany (2017)
Brinckmann, S.; Kirchlechner, C.; Dehm, G.; Matoy, K.: Using simulations to investigate the apparent fracture toughness of microcantilevers. Nanomechanical Testing in Materials Research and Development VI, Dubrovnik, Croatia (2017)
Arigela, V. G.; Kirchlechner, C.; Dehm, G.: Setup of a microscale high temperature loading rig for micro-fracture mechanics. Euromat 2017, Thessaloniki, Greece (2017)
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…