Lai, M.; Li, T.; Raabe, D.: ω phase acts as a switch between dislocation channeling and joint twinning- and transformation-induced plasticity in a metastable β titanium alloy. Acta Materialia 151, pp. 67 - 77 (2018)
Baron, C.; Springer, H.; Raabe, D.: Development of high modulus steels based on the Fe – Cr – B system. Materials Science and Engineering A: Structural Materials Properties Microstructure and Processing 724, pp. 142 - 147 (2018)
Fujita, N.; Ishikawa, N.; Roters, F.; Tasan, C. C.; Raabe, D.: Experimental–numerical study on strain and stress partitioning in bainitic steels with martensite–austenite constituents. International Journal of Plasticity 104, pp. 39 - 53 (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)
Kwiatkowski da Silva, A.; Inden, G.; Kumar, A.; Ponge, D.; Gault, B.; Raabe, D.: Competition between formation of carbides and reversed austenite during tempering of a medium-manganese steel studied by thermodynamic-kinetic simulations and atom probe tomography. Acta Materialia 147, pp. 165 - 175 (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)
Breitbarth, E.; Zaefferer, S.; Archie, F. M. F.; Besel, M.; Raabe, D.; Requena, G.: Evolution of dislocation patterns inside the plastic zone introduced by fatigue in an aged aluminium alloy AA2024-T3. Materials Science and Engineering A: Structural Materials Properties Microstructure and Processing 718, pp. 345 - 349 (2018)
Svendsen, B.; Shanthraj, P.; Raabe, D.: Finite-deformation phase-field chemomechanics for multiphase, multicomponent solids. Journal of the Mechanics and Physics of Solids 112, pp. 619 - 636 (2018)
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…