Rao, Z.; Han, L.; Zhang, H.; Raabe, D.: Active learning strategies for the sustainability of structural metals. Royal Society Discussion Meeting on Sustainable Metals: Science and Systems, London, UK (2024)
Zhou, X.; Wei, S.; Raabe, D.: Segregation-Driven Mechanics of White Gold at the Nanoscale: A Cursing or Blessing? Schöntal Symposium on Dislocation-based Plasticity 2024, Kloster Schöntal, Germany (2024)
Umate, K. S.; Bai, Y.; Svendsen, B.; Raabe, D.: Phase-field model for Hydrogen based direct reduction of iron oxides: Role of porosity. TMS - Algorithm Development in Materials Science and Engineering, Orlando, FL, USA (2024)
Raabe, D.: Transport and phase transformations phenomena in sustainable hydrogen-based steel production. 87th Spring Meeting of the German Physical Society, Berlin, Germany (2024)
Feng, S.; Gong, Y.; Neugebauer, J.; Raabe, D.; Liotti, E.; Grant, P. S.: Multi-technique investigation of Fe-rich intermetallic compounds for more impurity-tolerant Al alloys. Annual Meeting of DPG and DPG-Frühjahrstagung (DPG Spring Meeting) of the Condensed Matter Section (SKM) 2024, Berlin, Germany (2024)
Raabe, D.: Basic Materials Science Aspects of Green Metal Production. Royal Society Conference on Sustainable Metals: Science and Systems, London, UK (2024)
Raabe, D.: The Interplay of Lattice Defects and Chemistry at Atomic Scale and Why it Matters for the Properties of Materials. Van Horn Distinguished Lecturer Series, Cleveland, OH, USA (2023)
Wissenschaftler des Max-Planck-Instituts für Eisenforschung entwickeln ein neues maschinelles Lernmodell für korrosionsresistente Legierungen. Und veröffentlichen ihre Ergebnisse in der Fachzeitschrift Science Advances
Düsseldorfer Max-Planck-Wissenschaftler diskutieren den Einsatz künstlicher Intelligenz in der Materialwissenschaft und veröffentlichen Review-Artikel in der Fachzeitschrift Nature Computational Science