Klemm, S. O.; Topalov, A. A.; Laska, C. A.; Mayrhofer, K. J. J.: Coupling of a high throughput microelectrochemical cell with online multielemental trace analysis by ICP-MS. Electrochemistry Communications 13 (12), pp. 1533 - 1535 (2011)
Laska, C. A.; Rossrucker, L.; Klemm, S. O.; Pust, S. E.; Hüpkes, J.; Mayrhofer, K. J. J.: Die Kopplung von Elektrochemie mit zeitaufgelöster Elementanalytik am Beispiel der chemischen und elektrochemischen Oberflächentexturierung von ZnO-Dünnschichten. In: Tagungsband zur Jahrestagung der Gesellschaft für Korrosionsschutz e.V. 2013, pp. 118 - 128. Jahrestagung der Gesellschaft für Korrosionsschutz e.V. , Frankfurt am Main, Germany, November 12, 2013 - November 13, 2013. (2013)
Laska, C. A.: Development of a Scanning Flow Cell system with Dynamic Electrolyte Change for Fully Automated Parameter Screening. Dissertation, Ruhr-Universität Bochum, Bochum, Germany (2015)
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
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.
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…