Kürnsteiner, P.; Wilms, M. B.; Weisheit, A.; Jägle, E. A.; Raabe, D.: Precipitation Reaction in a Maraging Steel during Laser Additive Manufacturing triggered by Intrinsic Heat Treatment. Materials Science and Engineering Congress, Darmstadt, Germany (2016)
Jägle, E. A.: Small variations in powder composition lead to strong differences in part properties. Alloys for Additive Manufacturing Workshop 2016, Düsseldorf, Germany (2016)
Jägle, E. A.: Alloys for Laser Additive Manufacturing: general considerations and precipitation reactions. Seminar at Institut für Werkstoff-Forschung, DLR Köln 2016, Köln, Germany (2016)
Jägle, E. A.: Precipitation Reactions in Age-Hardenable Alloys During Laser Additive Manufacturing. Seminar at EMPA (Eidgenössische Materialprüfungs- und Forschungsanstalt), Dübendorf, Switzerland (2016)
Jägle, E. A.: Alloys for and by Laser Additive Manufacturing – the basic research perspective. 2nd European Scientific Steel Panel – Metal Additive Manufacturing, Steel Institute VdEH, Düsseldorf, Germany (2015)
Jägle, E. A.: Maraging steel produced by LAM: Influence of processing on precipitation and austenite reversion. Phase Transformations in Inorganic Materials (PTM), Whistler, BC, Canada (2015)
Jägle, E. A.; Tytko, D.; Choi, P.-P.; Raabe, D.: Deformation-induced intermixing in a model multilayer system. Atom Probe Tomography & Microscopy 2014, Stuttgart, Germany (2014)
Jägle, E. A.: Atom Probe Tomography: Basics, data analysis and application to the analysis of phase transformations. Department of Materials Engineering house seminar, KU Leuven, Leuven, Belgium (2014)
Jägle, E.: Parameter finding for and accuracy of the Maximum Separation algorithm assessed by Atom Probe simulations. 2nd European APT Workshop at ETH Zürich, Zürich, Switzerland (2013)
Jägle, E.: Atom Probe Tomography: Basics, data analysis and application to the analysis of advanced steels. Symposium "Frontiers in Steelmaking and Steel Design", INM, Saarbrücken, Germany (2013)
Jägle, E.: Atom Probe Tomography: Basics, data analysis and application to the analysis of phase transformations. Kolloquium at Max-Planck-Institute for Intelligent Systems, Stuttgart, Germany (2013)
Hariharan, A.; Lu, L.; Risse, J.; Jägle, E. A.; Raabe, D.: Mechanisms Contributing to Solidification Cracking during laser powder bed fusion of Inconel-738LC. Alloys for Additive Manufacturing Symposium 2019 (AAMS2019), Chalmers University of Technology, Gothenburg, Sweden (2019)
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…
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…