Stein, F.; Vogel, S. C.; Eumann, M.; Palm, M.: Determination of the crystal structure of the ε phase in the Fe–Al system by high-temperature neutron diffraction. Intermetallics 18 (1), pp. 150 - 156 (2010)
Krein, R.; Palm, M.; Heilmaier, M.: Characterization of microstructures, mechanical properties, and oxidation behavior of coherent A2 + L21 Fe–Al–Ti. Journal of Materials Research 24 (11), pp. 3412 - 3421 (2009)
Palm, M.: Phase equilibria in the Fe corner of the Fe–Al–Nb system between 800 and 1150°C. Journal of Alloys and Compounds 475 (1-2), pp. 173 - 177 (2009)
Palm, M.: Fe–Al materials for structural applications at high temperatures: Current research at MPIE. International Journal of Materials Research 100 (3), pp. 277 - 287 (2009)
Eumann, M.; Sauthoff, G.; Palm, M.: Phase equilibria in the Fe–Al–Mo system - Part II: Isothermal sections at 1000 and 1150 °C. Intermetallics 16 (6), pp. 834 - 846 (2008)
Krein, R.; Palm, M.: The influence of Cr and B additions on the mechanical properties and oxidation behaviour of L21-ordered Fe-Al-Ti-based alloys at high temperatures. Acta Materialia 56 (10), pp. 2400 - 2405 (2008)
Eumann, M.; Sauthoff, G.; Palm, M.: Phase equilibria in the Fe–Al–Mo system - Part I: Stability of the Laves phase Fe2Mo and isothermal section at 800 °C. Intermetallics 16 (5), pp. 706 - 716 (2008)
Stein, F.; Palm, M.: Re-determination of transition temperatures in the Fe–Al system by differential thermal analysis. International Journal of Materials Research 98 (7), pp. 580 - 588 (2007)
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
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…