Li, Y.; Fang, X.; Zhang, S.; Feng, X.: Microstructure evolution of FeNiCr alloy induced by stress-oxidation coupling using high temperature nanoindentation. Corrosion Science 135, pp. 192 - 196 (2018)
Zhang, S.; Scheu, C.: Evaluation of EELS spectrum imaging data by spectral components and factors from multivariate analysis. Microscopy 67 (suppl_1), pp. i133 - i141 (2018)
Isotta, E.; Zhang, S.; Ghosh, S.; de Boor, J.; Balogun, O.; Snyder, G. J.; Scheu, C.: Thermal conductivity imaging to advance microstructure engineering in thermoelectrics. European Conference on Thermoelectrics 2025, Nancy, France (2025)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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.