Beese-Vasbender, P. F.; Nayak, S.; Erbe, A.; Stratmann, M.; Mayrhofer, K. J. J.: Electrochemical characterization of direct electron uptake in electrical microbially influenced corrosion of iron by the lithoautotrophic SRB Desulfopila corrodens strain IS4. Electrochimica Acta 167, pp. 321 - 329 (2015)
Ettl, C.; Stratmann, M.: Editorial: Chemistry and the Max Planck Society: A Stable Bond Resonating into the Future. Angewandte Chemie International Edition 54 (20), pp. 5798 - 5799 (2015)
Ettl, C.; Stratmann, M.: Editorial: Die Chemie in der Max‐Planck‐Gesellschaft – Vergangenheit und Zukunft einer erfolgreichen Verbindung. Angewandte Chemie 127 (20), pp. 5892 - 5893 (2015)
Iqbal, D.; Sarfraz, A.; Stratmann, M.; Erbe, A.: Solvent-starved conditions in confinement cause chemical oscillations excited by passage of a cathodic delamination front. Chemical Communications 51 (89), pp. 16041 - 16044 (2015)
Nayak, S.; Biedermann, P. U.; Stratmann, M.; Erbe, A.: In situ infrared spectroscopic investigation of intermediates in the electrochemical oxygen reduction on n-Ge(100) in alkaline perchlorate and chloride electrolyte. Electrochimica Acta 106, pp. 472 - 482 (2013)
Nayak, S.; Biedermann, P. U.; Stratmann, M.; Erbe, A.: A mechanistic study of the electrochemical oxygen reduction on the model semiconductor n-Ge(100) by ATR-IR and DFT. Physical Chemistry Chemical Physics 15 (16), pp. 5771 - 5781 (2013)
Posner, R.; Jubb, A. M.; Frankel, G. S.; Stratmann, M.; Allen, H. C.: Simultaneous in-situ Kelvin Probe and Raman spectroscopy analysis of electrode potentials and molecular structures at polymer covered salt layers on steel. Electrochimica Acta 83, pp. 327 - 334 (2012)
Enning, D.; Venzlaff, H.; Garrelfs, J.; Dinh, H. T.; Meyer, V.; Mayrhofer, K. J. J.; Hassel, A. W.; Stratmann, M.; Widdel, F.: Marine sulfate-reducing bacteria cause serious corrosion of iron under electroconductive biogenic mineral crust. Environmental Microbiology 14 (7), pp. 1772 - 1787 (2012)
Senöz, C.; Borodin, S.; Stratmann, M.; Rohwerder, M.: In-situ detection of differences in the electrochemical activity of Al2Cu IMPs and investigation of their effect on FFC by scanning Kelvin probe force microscopy. Corrosion Science 58, pp. 307 - 314 (2012)
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
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 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…
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.