Fabritius, H.-O.; Enax, J.; Wu, X.; Epple, M.; Raabe, D.: Structure-property relations in biological composite materials: An inspiration source for synthetic materials. 79th Annual Meeting of the DPG and DPG Spring Meeting 2015, Berlin, Germany (2015)
Fabritius, H.-O.: Alternative Präparationsmethoden für nichtmetallische Werkstoffe. Fachtagung Mikroskopie und Präparation (mikpräp) der Gesellschaft für Materialografie Rhein Ruhr e.V. (gmr2), Solingen, Germany (2015)
Fabritius, H.-O.: Structure-property relations in biological composite materials – The arthropod exoskeleton. Chemical Engineering and Materials Science Seminar, Michigan State University, East Lensing, MI, USA (2014)
Enax, J.; Fabritius, H.-O.; Roters, F.; Raabe, D.; Epple, M.: Synthetic dental composite materials inspired by the hierarchical organization of shark tooth enameloid. Third winter school within the DFG priority programme 1420 "Biomimetic Materials Research: Functionality by Hierarchical Structuring of Materials", Potsdam, Germany (2014)
Huber, J.; Fabritius, H.-O.; Griesshaber, E.; Schmahl, W. W.; Ziegler, A. S.: Varying mechanical properties within the incisive cuticle of the terrestrial isopod Porcellio scaber resulting from region-dependent ultrastructure, elemental distribution and arrangement of calcite crystals. DGM Bio-inspired Materials: International Conference on Biological Material Science, Potsdam, Germany (2014)
Fabritius, H.-O.: Structure-property relations in biological composite materials. Seminar, Department of Earth- and Environmental Sciences, LMU Munich, München, Germany (2014)
Fabritius, H.-O.; Hennig, S.; Hild, S.; Soor, C.; Ziegler, A. S.: Influence of Near-Physiological Salines and Organic Matrix Proteins from Sternal ACC-Deposits of Porcellio scaber on CaCO3 Precipitation. 12th International Symposium on Biomineralization, Freiberg, Germany (2013)
Fabritius, H.-O.: Structure-property relations in biological materials – Opportunities and challenges. Summer School of the SPP1420 at the University of Ulm, Ulm, Germany (2013)
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.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…