Kiener, D.; Grosinger, W.; Dehm, G.; Pippan, R.: A further step towards an understanding of size-dependent crystal plasticity: In situ tenison experiments of miniaturized single-crystal copper samples. Acta Materialia 56 (3), pp. 580 - 592 (2008)
Inkson, B. J.; Dehm, G.; Peng, Y.: Dynamical growth of Cu-Pt nanowires with a nanonecklace morphology. Nanotechnology 18 (41), 415601, pp. 1 - 5 (2007)
Oh, S. H.; Legros, M.; Kiener, D.; Gruber, P. A.; Dehm, G.: In situ TEM straining of single crystal Au films on polyimide: Change of deformation mechanisms at the nanoscale. Acta Materialia 55 (16), pp. 5558 - 5571 (2007)
Kiener, D.; Motz, C.; Rester, M.; Jenko, M.; Dehm, G.: FIB damage of Cu and possible consequences for miniaturized mechanical tests. Materials Science and Engineering A: Structural Materials Properties Microstructure and Processing 459 (1-2), pp. 262 - 272 (2007)
Kiener, D.; Motz, C.; Schöberl, T.; Jenko, M.; Dehm, G.: Determination of mechanical properties of copper at the micron scale. Advanced Engineering Materials 8 (11), pp. 1119 - 1125 (2006)
Riethmüller, J.; Dehm, G.; Affeldt, E. E.; Arzt, E.: Microstructure and mechanical behavior of Pt-modified NiAl diffusion coatings. International Journal of Materials Research 97 (6), pp. 689 - 698 (2006)
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…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.