Fink, N.; Klimow, G.; Stromberg, C.; Grundmeier, G.: Combination of Surface Gradient Chemistry and Kelvin Probe Studies of Thin Amorphous Conversion Films on Metals. 57th Annual Meeting of the International Society of Electrochemistry, Edinburgh, UK (2006)
Fink, N.; Wilson, B.; Stromberg, C.; Grundmeier, G.: Fundamental Investigations of Different Film Formation Kinetics of Amorphous Conversion Layers on Zinc Coated Steel due to Grain Orientation. 208th Meeting of the Electrochemical Society, Los Angeles, CA, USA (2005)
Stromberg, C.; Dornbusch, M.; Grundmeier, G.: A combined spectroscopic and electrochemical study of zirconium based conversion layers on zinc coated steel. 207th Meeting of the Electrochemical Society, Québec, Canada (2005)
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
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
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.