Jägle, E. A.: Impact of the process gas atmosphere in Laser Additive Manufacturing – desired and undesired effects. Alloys for Additive Manufacturing Symposium 2018, Sheffield, UK (2018)
Kürnsteiner, P.; Wilms, M. B.; Weisheit, A.; Jägle, E. A.; Raabe, D.: Preventing the Coarsening of Al3Sc Precipitates by the Formation of a Zr-rich Shell During Laser Metal Deposition. TMS2018 Annual Meeting & Exhibition, Phoenix, AZ, USA (2018)
Jägle, E. A.: Ex-situ and in-situ heat treatment of alloys during Laser Additive Manufacturing. AWT Kolloquium, Institut für Werkstofftechnik, Bremen, Germany (2017)
Jägle, E. A.: Additive Manufacturing and 3D Printing - What’s beyond the hype? Institute Lecture at Indian Institute of Technology Roorkee, Roorkee, India (2017)
Jägle, E. A.: Alloys for Additive Manufacturing, Alloys by Additive Manufacturing. Plenary presentation, Advances in Materials & Processing: Challenges and Opportunities, Indian Institute of Technology Roorkee, Roorkee, India (2017)
Jägle, E. A.: Exploiting the Intrinsic Heat Treatment during Laser Additive Manufacturing to trigger Precipitation Reactions. International Mechanical Engineering Congress & Exposition (IMECE), Tampa, FL, USA (2017)
Kürnsteiner, P.; Wilms, M. B.; Weisheit, A.; Jägle, E. A.; Raabe, D.: In-process precipitation strengthening in Al–Sc during Laser Metal Deposition by exploiting the Intrinsic Heat Treatment. Alloys for Additive Manufacturing Symposium, Zürich, Switzerland (2017)
Jägle, E. A.: Alloys for Additive Manufacturing, Alloys by Additive Manufacturing. Seminar talk at Culham Center for Fusion Energy, Oxford, Oxford, UK (2017)
Jägle, E. A.: Alloys for Additive Manufacturing, Alloys by Additive Manufacturing. Laser-Kolloquium at Fraunhofer Institut für Lasertechnik, Aachen, Aachen, Germany (2017)
Jägle, E. A.: Alloys for Additive Manufacturing, Alloys by Additive Manufacturing. Seminar talk at Institut für Umformtechnik und Leichtbau, TU Dortmund, Dortmund, Germany (2017)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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
The project focuses on development and design of workflows, which enable advanced processing and analyses of various data obtained from different field ion emission microscope techniques such as field ion microscope (FIM), atom probe tomography (APT), electronic FIM (e-FIM) and time of flight enabled FIM (tof-FIM).
This project will aim at addressing the specific knowledge gap of experimental data on the mechanical behavior of microscale samples at ultra-short-time scales by the development of testing platforms capable of conducting quantitative micromechanical testing under extreme strain rates upto 10000/s and beyond.
The development of pyiron started in 2011 in the CM department to foster the implementation, rapid prototyping and application of the highly advanced fully ab initio simulation techniques developed by the department. The pyiron platform bundles the different steps occurring in a typical simulation life cycle in a single software platform and…
The project Hydrogen Embrittlement Protection Coating (HEPCO) addresses the critical aspects of hydrogen permeation and embrittlement by developing novel strategies for coating and characterizing hydrogen permeation barrier layers for valves and pumps used for hydrogen storage and transport applications.
This work led so far to several high impact publications: for the first time nanobeam diffraction (NBD) orientation mapping was used on atom probe tips, thereby enabling the high throughput characterization of grain boundary segregation as well as the crystallographic identification of phases.
Smaller is stronger” is well known in micromechanics, but the properties far from the quasi-static regime and the nominal temperatures remain unexplored. This research will bridge this gap on how materials behave under the extreme conditions of strain rate and temperature, to enhance fundamental understanding of their deformation mechanisms. The…
The prediction of materials properties with ab initio based methods is a highly successful strategy in materials science. While the working horse density functional theory (DFT) was originally designed to describe the performance of materials in the ground state, the extension of these methods to finite temperatures has seen remarkable…