Ram, F.; Zaefferer, S.; Jäpel, T.; Raabe, D.: Error analysis of the crystal orientations and disorientations obtained by the classical electron backscatter diffraction technique. Journal of Applied Crystallography 48 (3), pp. 797 - 813 (2015)
Schäffer, A. K.; Jäpel, T.; Zaefferer, S.; Abart, R.; Rhede, D.: Lattice strain across Na–K interdiffusion fronts in alkali feldspar: An electron back-scatter diffraction study. Physics and Chemistry of Minerals 41 (10), pp. 795 - 804 (2014)
Zaefferer, S.; Elhami, N. N.; Konijnenberg, P. J.; Jäpel, T.: Quantitative Microstructure Characterization by Application of Advanced SEM-Based Electron Diffraction Techniques. Microscopy and Microanalysis 2013, Indianapolis, IN, USA (2013)
Jäpel, T.: Grundlagen der Kreuzkorrelationsmethode (delta-EBSD): Einführung in CrossCourt3 (CC3) und Erfahrungen in der praktischen Anwendung von CC3. Seminar Talk at Arbeitskreis EBSD in Garbsen, Garbsen, Germany (2012)
Kords, C.; Jäpel, T.; Eisenlohr, P.; Roters, F.: Residual stress prediction by considering dislocation density advection in 3D applied to single-crystal bending. Euromat 2011, Montpellier, France (2011)
Zaefferer, S.; Jäpel, T.; Tasan, C. C.; Konijnenberg, P.: Detailed observation of martensite transformation and twinning in TRIP and TWIP steels using advanced SEM diffraction techniques. ICOMAT 2011, Osaka, Japan (2011)
Kords, C.; Jäpel, T.; Eisenlohr, P.; Roters, F.: Residual stress prediction by considering dislocation density advection in 3D applied to single-crystal bending. 2nd International Conference on Material Modelling ICMM 2, Paris, France (2011)
Ram, F.; Zaefferer, S.; Jäpel, T.: Error Analysis of the Crystal Orientations and Misorientations obtained by the Classical Electron Backscatter Diffraction Method. RMS EBSD 2014, London, UK (2014)
Ram, F.; Zaefferer, S.; Jäpel, T.: On the accuracy and precision of orientations obtained by the conventional automated EBSD method. RMS EBSD 2014, London, UK (2014)
Jäpel, T.: Feasibility study on local elastic strain measurements with an EBSD pattern cross correlation method in elastic-plastically deforming material. Dissertation, RWTH Aachen, Aachen, Germany (2014)
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
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…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…