Choi, W. S.; De Cooman, B. C.; Sandlöbes, S.; Raabe, D.: Size and orientation effects in partial dislocation-mediated deformation of twinning-induced plasticity steel micro-pillars. Acta Materialia 98, 12304, pp. 391 - 404 (2015)
Nellessen, J.; Sandlöbes, S.; Raabe, D.: Effects of strain amplitude, cycle number and orientation on low cycle fatigue microstructures in austenitic stainless steel studied by electron channelling contrast imaging. Acta Materialia 87, pp. 86 - 99 (2015)
Kim, J.-K.; Sandlöbes, S.; Raabe, D.: On the room temperature deformation mechanisms of a Mg–Y–Zn alloy with long period stacking ordered structures. Acta Materialia 82, pp. 414 - 423 (2015)
Yi, S. B.; Rayas, L.; Sandlöbes, S.; Zaefferer, S.; Letzig, D.; Kainer, K.: Influence of Rare Earth Addition on Texture Development during Static Recrystallization and Mechanical Behaviour of Magnesium Alloy Sheets. Materials Science Forum 702-703, pp. 651 - 654 (2012)
Sandlöbes, S.; Senk, D.; Sancho, L.; Diaz, A.: In-situ Measurement of CO- and CO2-Concentrations in BOF Off-Gas. Steel Research International 82 (6), pp. 632 - 637 (2011)
Sandlöbes, S.; Zaefferer, S.; Schestakow, I.; Yi, S.; Gonzales-Martinez, R.: On the role of non-basal deformation mechanisms for the ductility of Mg and Mg–Y alloys. Acta Materialia 59 (2), pp. 429 - 439 (2011)
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.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…