Koprek, A.; Cojocaru-Mirédin, O.; Freysoldt, C.; Würz, R.; Raabe, D.: Atomic scale investigation of the p-n Junction in CIGS based solar cells: correlation between cell efficiency and impurities. E-MRS 2014, Lille, France (2014)
Archie, F. M. F.; Zaefferer, S.; Raabe, D.: The influence of grain boundary character on dislocation densities and fracture toughness in AHSS. M2i Conference "High Tech Materials: your world - our business", Sint Michielgestel, The Netherlands (2014)
Diehl, M.; Shanthraj, P.; Roters, F.; Raabe, D.: From Crystal Plasticity to Forming Simulations: The "Virtual Laboratory". M2i Conference "High Tech Materials: your world - our business", Sint Michielgestel, The Netherlands (2014)
Diehl, M.; Yan, D.; Tasan, C. C.; Shanthraj, P.; Roters, F.; Raabe, D.: Stress and Strain Partitioning in Multiphase Alloys: An Integrated Experimental-Numerical Analysis. Winter School 2014, Research Training Group 1483,
Karlsruher Intitut f. Technologie (KIT), Karlsruhe, Germany (2014)
Djaziri, S.; Li, Y.; Goto, S.; Kirchlechner, C.; Raabe, D.; Dehm, G.: Microstructural characterization of cold-drawn pearlitic steel wires at the nanometer scale. The Thin Film & Small Scale Mechanical Behavior Gordon Research Conference, Waltham, MA, USA (2014)
Lai, M.; Tasan, C. C.; Zhang, J.; Grabowski, B.; Huang, L.; Springer, H.; Raabe, D.: ω phase accommodated nano-twinning mechanism in Gum Metal: An ab initio study. 3rd International Workshop on Physics Based Material Models and Experimental Observations: Plasticity and Creep, Cesme/Izmir, Turkey (2014)
Yan, D.; Tasan, C. C.; Raabe, D.: Graded, ultrafine-grained, ferrite/martensite dual phase steel: a case study for damage-resistant microstructure design. Physics based materials models and experimental observations, Cesme Turkey (2014)
Diehl, M.; Yan, D.; Tasan, C. C.; Shanthraj, P.; Roters, F.; Raabe, D.: Stress and Strain Partitioning in Multiphase Alloys: An Integrated Experimental-Numerical Analysis. Materials to Innovate Industry and Society, Noordwijkerhout, The Netherlands (2013)
Enax, J.; Fabritius, H.-O.; Prymak, O.; Raabe, D.; Epple, M.: Synthetische Fluorapatit/Polymer-Dentalkomposite, basierend auf dem Vorbild Haizahn-Enameloid. Jahrestagung der Deutschen Gesellschaft für Biomaterialien, Erlangen, Germany (2013)
Nellessen, J.; Sandlöbes, S.; Raabe, D.: Systematic and efficient investigation of the influences on the dislocation structures formed during low cycle fatigue in austenitic stainless steel. Euromat 2013, Sevilla, Spain (2013)
Haghighat, S. M. H.; Eggeler, G.; Raabe, D.: In-situ observation of dislocation evolutions in single crystal Ni base superalloys creep using discrete dislocation dynamics simulation. GDRi CNRS MECANO General Meeting on the Mechanics of Nano-Objects, MPIE, Düsseldorf, Germany (2013)
Wang, M.; Tasan, C. C.; Ponge, D.; Kostka, A.; Raabe, D.: Size effects on mechanical stability of metastable austenite. GDRi CNRS MECANO General Meeting on the Mechanics of Nano-Objects, MPIE, Düsseldorf, 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
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…
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.