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)
Li, Z.; Sun, Y.; Lavernia, E. J.; Shan, A.: Mechanical Behavior of Ultrafine-Grained Ti–6Al–4V Alloy Produced by Severe Warm Rolling: The Influence of Starting Microstructure and Reduction Ratio. Metallurgical and Materials Transactions a-Physical Metallurgy and Materials Science 46 (11), pp. 5047 - 5057 (2015)
Liebscher, C.; Lu, W.; Dehm, G.; Raabe, D.; Li, Z.: Complex phase transformation pathways in high entropy alloys explored by in situ S/TEM. Third International Conference on High Entropy Materials, Berlin, Germany (2020)
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
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…
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.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.