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)
Bajaj, P.; Gupta, A.; Jägle, E. A.; Raabe, D.: Precipitation kinetics during non-linear heat treatment in Laser Additive Manufacturing. International Conference on Advanced Materials and Processes, ‘ADMAT 2017’ SkyMat, Thiruvananthapuram, India (2017)
Jägle, E. A.: Microstructural Aspects of Additive Manufacturing. Lecture: Workshop “Microstructural Aspects of Additive Manufacturing”, Indian Institute of Technology Roorkee, 3,5h of lectures, Roorkee, India, December 02, 2017
Ackers, M.: Recommissioning of a metal powder atomisation system and investigation of its suitability to produce powders for additive Manufacturing processes. Master, Ruhr-Universität Bochum, Bochum, Germany (2017)
Qin, Y.: Effect of post-heat treatment on the microstructure and mechanical properties of SLM-produced IN738LC. Master, RWTH Aachen, Aachen, 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
This project will aim at developing MEMS based nanoforce sensors with capacitive sensing capabilities. The nanoforce sensors will be further incorporated with in situ SEM and TEM small scale testing systems, for allowing simultaneous visualization of the deformation process during mechanical tests
The utilization of Kelvin Probe (KP) techniques for spatially resolved high sensitivity measurement of hydrogen has been a major break-through for our work on hydrogen in materials. A relatively straight forward approach was hydrogen mapping for supporting research on hydrogen embrittlement that was successfully applied on different materials, and…
It is very challenging to simulate electron-transfer reactions under potential control within high-level electronic structure theory, e. g. to study electrochemical and electrocatalytic reaction mechanisms. We develop a novel method to sample the canonical NVTΦ or NpTΦ ensemble at constant electrode potential in ab initio molecular dynamics…
Photovoltaic materials have seen rapid development in the past decades, propelling the global transition towards a sustainable and CO2-free economy. Storing the day-time energy for night-time usage has become a major challenge to integrate sizeable solar farms into the electrical grid. Developing technologies to convert solar energy directly into…
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…