Ou, P.; Li, Z.: Ordering of primary carbonitrides in an austenitic steel revealed by transmission electron microscopy and atom probe tomography. Materials 11 (11), 2321 (2018)
Li, Z.; Raabe, D.: Influence of compositional inhomogeneity on mechanical behavior of an interstitial dual-phase high-entropy alloy. Materials Chemistry and Physics 210, pp. 29 - 36 (2018)
Luo, H.; Li, Z.; Mingers, A. M.; Raabe, D.: Corrosion behavior of an equiatomic CoCrFeMnNi high-entropy alloy compared with 304 stainless steel in sulfuric acid solution. Corrosion Science 134, pp. 131 - 139 (2018)
Wang, M.; Li, Z.; Raabe, D.: In-situ SEM observation of phase transformation and twinning mechanisms in an interstitial high-entropy alloy. Acta Materialia 147, pp. 236 - 246 (2018)
Luo, H.; Li, Z.; Chen, Y.-H.; Ponge, D.; Rohwerder, M.; Raabe, D.: Hydrogen effects on microstructural evolution and passive film characteristics of a duplex stainless steel. Electrochemistry Communucations 79, pp. 28 - 32 (2017)
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
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…
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…
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.