Strondl, A.; Fischer, R.; Frommeyer, G.; Schneider, A.: Investigations of MX and γ'/γ'' precipitates in the nickel-based superalloy 718 produced by electron beam melting. Materials Science and Engineering A 480, pp. 138 - 147 (2008)
Deges, J.; Rablbauer, R.; Frommeyer, G.; Schneider, A.: Observation of boron enrichments in a heat treated quasibinary hypoeutectic NiAl-HfB2 alloy by means of atom probe field-ion microscopy (APFIM). Surface and Interface Analysis 39, pp. 251 - 156 (2007)
Bello-Rodriguez, B.; Schneider, A.; Hassel, A. W.: Preparation of Ultramicroelectrode Array of Gold Hemispheres on Nanostructured NiAl-Re. J. Electrochem. Soc. 153 (1), pp. C33 - C36 (2006)
Milenkovic, S.; Hassel, A. W.; Schneider, A.: Effect of the Growth Conditions on the Spatial Features of Re Nanowires Produced by Directional Solidification. Nano Letters 6 (4), pp. 794 - 799 (2006)
Stallybrass, C.; Schneider, A.; Sauthoff, G.: The strengthening effect of (Ni, Fe)Al precipitates on the mechanical properties at high temperatures of ferritic Fe–Al–Ni–Cr alloys. Intermetallics 13 (12), pp. 1263 - 1268 (2005)
Hassel, A. W.; Bello-Rodriguez, B.; Milenkovic, S.; Schneider, A.: Electrochemical Production of Nanopore Arrays into a Nickel Aluminium Alloy. Electrochimica Acta 50, pp. 3033 - 3039 (2005)
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…