Hickel, T.; Neugebauer, J.; McEniry, E.: Ab initio simulation of hydrogen-induced decohesion in cementite-containing microstructures. Acta Materialia 150, pp. 53 - 58 (2018)
Dutta, B.; Körmann, F.; Hickel, T.; Neugebauer, J.: Impact of Co and Fe doping on the martensitic transformation and the magnetic properties in Ni–Mn-based Heusler alloys. Physica Status Solidi B, 1700455 , pp. 1 - 7 (2017)
Schwarze, C.; Gupta, A.; Hickel, T.; Kamachali, R. D.: Phase-field study of ripening and rearrangement of precipitates under chemomechanical coupling. Physical Review B 95 (17), 174101 (2017)
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…