Belde, M. M.; Springer, H.; Raabe, D.: Tailoring multi-phase microstructures by control of local chemical gradients, applied to austenite in martensitic steel. Icomat 2014
, Bilbao, Spain (2014)
Herbig, M.; Li, Y.; Morsdorf, L.; Goto, S.; Choi, P.-P.; Kirchheim, R.; Raabe, D.: Recent Advances in Understanding the Structures and Properties of Nanomaterials. Gordon Research Conference on Structural Nanomaterials, The Chinese University of Hong Kong, Hong Kong, China (2014)
Tasan, C. C.; Diehl, M.; Yan, D.; Zambaldi, C.; Shanthraj, P.; Roters, F.; Raabe, D.: Integrated experimental and simulation analysis of stress and strain partitioning in dual phase steel. IUTAM Symposium on Connecting Multiscale Mechanics to Complex Material Design, Evanston, IL, USA (2014)
Haghighat, S. M. H.; Eggeler, G. F.; Raabe, D.: Mesoscale modelling of the influence of loading conditions on the dislocation mobility and creep process in single crystal Ni base superalloys. KTH Stockholm-Sweden, Stockholm, Sweden (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)
Herbig, M.; Choi, P.; Raabe, D.: Atom Probe Tomography and Correlative TEM/APT at the MPIE. Inauguration of the Atom Probe at the Institute for Physics IA at the RWTH Aachen, Aachen, Germany (2014)
Herbig, M.; Raabe, D.; Li, Y.; Choi, P.; Zaefferer, S.; Goto, S.: High Throughput Quantification of Grain Boundary Segregation by Correlative TEM and APT. TMS 2014, Solid-State Interfaces III Symposium, San Diego, CA, USA (2014)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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
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…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…