Beese-Vasbender, P. F.: From Microbially Induced Corrosion to Bioelectrical Energy Conversion - Electrochemical Characterization of Sulfate-Reducing Bacteria and Methanogenic Archaea. Dissertation, Fakultät für Chemie und Biochemie der Ruhr-Universität Bochum, Bochum, Germany (2014)
Schuppert, A. K.: Combinatorial screening of fuel cell catalysts for the oxygen reduction reaction. Dissertation, Fakultät für Chemie und Biochemie, Ruhr-Universität Bochum, Bochum, Germany (2014)
Meier, J. C.: Degradation phenomena and design principles for stable and active Pt/C fuel cell catalysts. Dissertation, Fakultät für Chemie und Biochemie, Ruhr-Universität Bochum, Bochum, Germany (2013)
Rabe, M.; Kasian, O.; Mayrhofer, K. J. J.; Erbe, A.: Schlussbericht zum Vorhaben: Mechanistische Untersuchungen der elektrochemischen Sauerstoffentwicklung auf Modellelektroden - Stabilität der Elektroden, Natur der Oxide und Intermediate - Teilvorhaben des Clusterprojekts "Mangan". Technische Informationsbibliothek (TIB) Hannover, Hannover, Germany (2019), 32 pp.
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’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.