Duarte, M. J.; Fang, X.; Rao, J.; Krieger, W.; Brinckmann, S.; Dehm, G.: In situ nanoindentation during electrochemical hydrogen charging: a comparison between front-side and a novel back-side charging approach. Journal of Materials Science 56 (14), pp. 8732 - 8744 (2021)
An, D.; Krieger, W.; Zaefferer, S.: Unravelling the effect of hydrogenon microstructure evolution under low-cycle fatigue in a high-manganese austenitic TWIP steel. International Journal of Plasticity 126, 102625 (2020)
Sun, B.; Krieger, W.; Rohwerder, M.; Ponge, D.; Raabe, D.: Dependence of hydrogen embrittlement mechanisms on microstructure-driven hydrogen distribution in medium Mn steels. Acta Materialia 183, pp. 313 - 328 (2020)
Wu, C.-H.; Krieger, W.; Rohwerder, M.: On the robustness of the Kelvin probe based potentiometric hydrogen electrode method and its application in characterizing effective hydrogen activity in metal: 5 wt. % Ni cold-rolled ferritic steel as an example. Science and Technology of Advanced Materials 20 (1), pp. 1073 - 1089 (2019)
Krieger, W.; Merzlikin, S. V.; Bashir, A.; Springer, H.; Rohwerder, M.: Influence of strengthening mechanisms and environmental conditions on the performance of ferritic steels. In: EUROCORR 2017 - The Annual Congress of the European Federation of Corrosion. Joint European Corrosion Congress 2017, EUROCORR 2017 and 20th International Corrosion Congress and Process Safety Congress 2017, Prague, Czech Republic, September 03, 2017 - September 07, 2017. (2017)
Altin, A.; Wohletz, S.; Krieger, W.; Groche, P.; Erbe, A.: Effect of surface condition on the bond strength between aluminum and steel joint in cold welding. CETAS 2015, Düsseldorf, Germany (2015)
Altin, A.; Wohletz, S.; Krieger, W.; Kostka, A.; Groche, P.; Erbe, A.: Nanoscale understanding of bond formation during cold welding of aluminum and steel. 6th International Conference on Tribology in Manufacturing Processes & Joining by Plastic Deformation, Darmstadt, Germany (2014)
Krieger, W.: Charakterisierung von Wasserstofffallen und deren Einfluss auf die Wasserstoffversprödung in ferritischen Stählen. Dissertation, Ruhr University Bochum, Bochum, Germany (2018)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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
The project HyWay aims to promote the design of advanced materials that maintain outstanding mechanical properties while mitigating the impact of hydrogen by developing flexible, efficient tools for multiscale material modelling and characterization. These efficient material assessment suites integrate data-driven approaches, advanced…
A novel design with independent tip and sample heating is developed to characterize materials at high temperatures. This design is realized by modifying a displacement controlled room temperature micro straining rig with addition of two miniature hot stages.
Many important phenomena occurring in polycrystalline materials under large plastic strain, like microstructure, deformation localization and in-grain texture evolution can be predicted by high-resolution modeling of crystals. Unfortunately, the simulation mesh gets distorted during the deformation because of the heterogeneity of the plastic…
In this project we developed a phase-field model capable of describing multi-component and multi-sublattice ordered phases, by directly incorporating the compound energy CALPHAD formalism based on chemical potentials. We investigated the complex compositional pathway for the formation of the η-phase in Al-Zn-Mg-Cu alloys during commercial…
The Atom Probe Tomography group in the Microstructure Physics and Alloy Design department is developing integrated protocols for ultra-high vacuum cryogenic specimen transfer between platforms without exposure to atmospheric contamination.
Here, we aim to develop machine-learning enhanced atom probe tomography approaches to reveal chemical short/long-range order (S/LRO) in a series of metallic materials.