Koster, D.; Žeradjanin, A. R.; Battistel, A.; La Mantia, F.: Extracting the kinetic parameters of the hydrogen evolution reaction at Pt in acidic media by means of dynamic multi-frequency analysis. Electrochimica Acta 308, pp. 328 - 336 (2019)
Žeradjanin, A. R.: Frequent Pitfalls in the Characterization of Electrodes Designed for Electrochemical Energy Conversion and Storage. ChemSusChem 11 (8), pp. 1278 - 1284 (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
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.