Jovičević-Klug, P.; Jovičević-Klug, M.; Tegg, L.; Hester, J. R.; Čapek, J.; Polatidis, E.; Cairney, J. M.; McCord, J.; Rohwerder, M.: Operando cryogenic processing effects on residual stress and magnetism of martensitic stainless steel for energy sector. Materials today advances 31, 100895 (2026)
Sudha, G.; Rohwerder, M.; Vijayshankar, D.: Towards establishing reliable approaches for measurement of hydrogen diffusion characteristics using the electrochemical permeation technique. Corrosion Science 259, 113449 (2026)
Vijayshankar, D.; Rohwerder, M.: Revealing the Role of Oxygen Reduction Rate and Degradation Time on the Buried Metal/Coating Interphase Delamination Behavior. Corrosion 81 (12), pp. 1145 - 1150 (2025)
Wang, L.; Sam, H. C.; Ao, M.; Rohwerder, M.; Dong, C.: The effect of austenite phase transformation on hydrogen distribution and embrittlement mechanisms of heterogeneous martensite stainless steel manufactured by laser powder bed fusion. Corrosion Science 256, 113195 (2025)
Keerthiga, G.; Singh, R. R. K.; Prasad, M. J. N. V.; Albinmousa, J.; Rohwerder, M.; Vijayshankar, D.: Understanding the corrosion behavior of poly(3-hydroxybutyrate) coated ZK60 Mg alloy under dynamic m-SBF electrolyte flow conditions. Electrochimica Acta 536, 146812 (2025)
Jovičević-Klug, M.; Brondin, C. A.; Caretta, A.; Bonnekoh, C.; Gossing, F.; Vogel, A.; Rieth, M.; McCord, J.; Rohwerder, M.; Jovičević-Klug, P.: Suppression of Cr nanoclusters and enrichments in Fe–Cr based alloys with cryogenic processing for future energy sector. Journal of Materials Research and Technology 36, pp. 9262 - 9273 (2025)
Khayatan, N.; Prabhakar, J. M.; Jalilian, E.; Madelat, N.; Terryn, H.; Rohwerder, M.: On the rate determining step of cathodic delamination of delamination-resistant organic coatings. Corrosion Science 239, 112396 (2024)
Azzam, W.; Subaihi, A.; Rohwerder, M.; Bashir, A.; Terfort, A.; Zharnikov, M.: Odd-even effects in aryl-substituted alkanethiolate SAMs: nonsymmetrical attachment of aryl unit and its impact on the SAM structure. Physical Chemistry Chemical Physics 26 (9), pp. 7563 - 7572 (2024)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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
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.