Kontis, P.; Cormier, J.; Raabe, D.; Gault, B.: The Role of Chromium and Cobalt Segregation at Dislocations on the γ Dissolution in Nickel Based Superalloys. 18th International Conference on the Strength of Materials (ICSMA 18), Ohio State University, Columbus, OH, USA (2018)
Kontis, P.; Raabe, D.; Gault, B.: The role of systematic characterization on the development of new nickel-based superalloys. Industrial Colloquium - SFB/TR 103 „From Atoms to Turbine Blades“ , Fürth, Germany (2018)
Gault, B.; Kontis, P.; Cormier, J.; Raabe, D.: From systematic characterisation to the next generation of high performance materials. THERMEC 2018 , Paris, France (2018)
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.