Lhadi, S.; Ahzi, S.; Rémond, Y.; Nikolov, S. D.; Fabritius, H.-O.: Effects of homogenization technique and introduction of interfaces in a multiscale approach to predict the elastic properties of arthropod cuticle. Journal of the Mechanical Behavior of Biomedical Materials 23, S. 103 - 116 (2013)
Fabritius, H.; Karsten, E. S.; Balasundaram, K.; Hild, S.; Huemer, K.; Raabe, D.: Correlation of structure, composition and local mechanical properties in the dorsal carapace of the edible crab Cancer pagurus. 11, S. 766 - 776 (2012)
Maniruzzaman, M.; Rahman, M. A.; Gafur, M. A.; Fabritius, H.; Raabe, D.: Modification of pineapple leaf fibers and graft copolymerization of acrylonitrile onto modified fibers. Journal of Composite Materials 46, S. 79 - 90 (2012)
Van Opdenbosch, D.; Johannes, M.; Wu, X.; Fabritius, H.; Zollfrank, C.: Fabrication of high-temperature resistant threedimensional photonic crystals with tunable photonic properties by biotemplating. 4, S. 516 - 522 (2012)
Fabritius, H.; Sachs, C.; Romano, P.; Raabe, D.: Influence of structural principles on the mechanics of a biological fiber-based composite material with hierarchical organization: The exoskeleton of the lobster Homarus americanus. Advanced Materials 21, S. 391 - 400 (2009)
Al-Sawalmih, A.; Li, C.; Siegel, S.; Fabritius, H.; Yi, S. B.; Raabe, D.; Fratzl, P.; Paris, O.: Microtexture and Chitin/Calcite Orientation Relationship in the Mineralized Exoskeleton of the American Lobster. Advanced Functional Materials 18 (20), S. 3307 - 3314 (2008)
Sachs, C.; Fabritius, H.; Raabe, D.: Influence of the microstructure on deformation anisotropy of mineralized cuticle from the lobster Homarus americanus. Journal of Structural Biology 161, S. 120 - 132 (2008)
Boßelmann, F.; Romano, P.; Fabritius, H.; Raabe, D.: The composition of the exoskeleton of two crustacea: The American lobster Homarus americanus and the edible crab Cancer pagurus. Thermochimica Acta 463 (1-2), S. 65 - 68 (2007)
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