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, pp. 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, pp. 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, pp. 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, pp. 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, pp. 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), pp. 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, pp. 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), pp. 65 - 68 (2007)
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
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…
Advanced microscopy and spectroscopy offer unique opportunities to study the structure, composition, and bonding state of individual atoms from within complex, engineering materials. Such information can be collected at a spatial resolution of as small as 0.1 nm with the help of aberration correction.
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
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.