Ponge, D.: Arbeiten des MPI für Eisenforschung auf dem Gebiet der feinkörnigen Stähle. Lecture at the Sitzung des Arbeitsausschusses des Werkstoffausschusses, Stahlinstitut VDEh, Düsseldorf, Germany (2004)
Ponge, D.: Hochfeste Baustähle und deren schweißtechnische Verarbeitung. Berufsfortbildung Deutscher Verband für Schweißen und verwandte Verfahren e. V., Hamburg (2003)
Storojeva, L.; Kaspar, R.; Ponge, D.: Ferritic-Pearlitic Steel with Deformation Induced Spheroidized Cementite. Lecture at the International Conference on Processing & Manufacturing of Advanced Materials THERMEC'2003, Leganes, Madrid, Spain (2003)
Kwiatkowski da Silva, A.; Ponge, D.; Inden, G.; Gault, B.; Raabe, D.: Physical Metallurgy of segregation, austenite reversion, carbide precipitation and related phenomena in medium Mn steels. Gordon Research Conference: Physical Metallurgy, Biddeford, ME, USA (2017)
Neddermann, P.; Ponge, D.; Raabe, D.: Influence of Chromium on the Low Temperature Austenite Reversion through Local Equilibrium in Martensitic Stainless Steel. MSE 2014, Darmstadt, Germany (2014)
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)
Yan, D.; Tasan, C. C.; Ponge, D.; Diehl, M.; Roters, F.; Hartmaier, A.; Raabe, D.: Experimental-Numerical Analysis of Stress and Strain Partitioning in Dual Phase Steel. 10th Materials Day, Joint workshop of the Materials Research Department (MRD) and the IMPRS-SurMat, Bochum, Germany (2012)
Dmitrieva, O.; Ponge, D.; Millán, J.; Choi, P.; Raabe, D.: Study of local chemical gradients in advanced precipitation hardened TRIP steel. 52nd International Field Emission Symposium IFES 2010, Sydney, Australia (2010)
Calcagnotto, M.; Ponge, D.; Adachi, Y.; Raabe, D.: Effect of grain refinement on strength and toughness in dual-phase steels. 2nd International Symposium on Steel Science ISSS 2009, Kyoto, Japan (2009)
Herrera, C.; Ponge, D.; Raabe, D.: Microstructural evolution during hot working of 1.4362 duplex stainless steel. 2nd International Symposium on Steel Science (ISSS 2009), Kyoto, Japan (2009)
Calcagnotto, M.; Ponge, D.; Raabe, D.: Experimental study on orientation gradients and GNDs in ultrafine grained dual-phase steels. International Conference on Processing & Manufacturing of Advanced Materials (THERMEC 2009), Berlin, Germany (2009)
Nnamchi, P.; Ponge, D.; Raabe, D.; Barani, A.; Bruckner, G.; Krautschik, J.: Influence of the As-Cast Microstructure on the Evolution of the Hot Rolling Textures of Ferritic Stainless Steels with Different Compositions. 15th International Conference on the Textures of Materials (ICOTOM 15), Carnegie Mellon University Center, Pittsburgh, PA, USA (2008)
Calcagnotto, M.; Ponge, D.; Raabe, D.: Fabrication of Ultrafine Grained Ferrite/Martensite Dual Phase Steel by Large Strain Warm Deformation and Subsequent Intercritical Annealing. ISUGS 2007 (International Symposium on Ultrafine Grained Steels), Kitakyushu, Japan (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
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.
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…
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…
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…