Grote, J.-P.; Žeradjanin, A. R.; Cherevko, S.; Mayrhofer, K. J. J.: Electrochemical CO2 reduction: A Combinatorial High-Throughput Approach for Catalytic Activity, Stability, and Selectivity Investigations. Electrochemistry 2014, Mainz, Germany (2014)
Grote, J.-P.; Žeradjanin, A. R.; Cherevko, S.; Mayrhofer, K. J. J.: Electrochemical CO2 reduction: A Combinatorial High-Throughput Approach for Catalytic Activity, Stability, and Selectivity Investigations. 247th ACS National Meeting, Dallas, TX, USA (2014)
Grote, J.-P.; Žeradjanin, A. R.; Cherevko, S.; Mayrhofer, K. J. J.: Electrochemical CO2 Reduction A Combinatorial High-Throughput Approach for Catalytic Activity, Stability and Selectivity Investigations. International Symposium on Electrocatalysis: Explorations of the Volcano Landscape, Whistler, BC, Canada (2014)
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
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.