Herbig, M.; Raabe, D.; Li, Y.; Choi, P.-P.; Zaefferer, S.; Goto, S.: Joint crystallographic and chemical characterization at the nanometer scale by correlative TEM and atom probe tomography. Workshop: White-etching layers in ball and roller bearings, Informatik-Zentrum Hörn, Aachen, Germany (2014)
Zaefferer, S.: Texture and microstructures of thin film solar cells. Autumn School on Microstructural Characterization and Modelling of Thin-Film Solar Cells, Potsdam, Germany (2014)
Haghighat, S. M. H.; Li, Z.; Zaefferer, S.; Reed, R. C.; Raabe, D.: Characterization and modeling of the propagation of creep dislocations from the interdendritic boundaries in single crystal Ni base superalloys. International Workshop on Modelling and Simulation of Superalloys, Bochum, Germany (2014)
Zaefferer, S.; Mandal, S.; Bozzolo, N.: Correlative Measurement of the 5-parameter Grain Boundary Character and its Physical and Chemical Properties. MSE 2014, Darmstadt, Germany (2014)
Schemmann, L.; Romano Triguero, P.; Zaefferer, S.: Eine Untersuchung zur ferritisch-bainitischen Umwandlung in einem Dualphasenstahl unter Verwendung von EBSD-basierten Misorientierungsmessungen. Arbeitskreistreffen: Mikrostrukturcharakterisierung im REM, Düsseldorf, Germany (2014)
Zaefferer, S.: Quantitative analysis of crystal defects by means of EBSD and related methods. Arbeitskreistreffen: Mikrostrukturcharakterisierung im REM, Düsseldorf, Germany (2014)
Zaefferer, S.: Application of EBSD and ECCI for the Investigation of Microstructures of Engineering Materials. MSA EBSD 2014, Pittsburgh, PA, USA (2014)
Zaefferer, S.: Application of diffraction techniques in the scanning electron microscope for the investigation of microstructures of engineering materials. Deutsche Versuchsanstalt für Luft und Raumfahrt (DLR), Köln, Germany (2014)
Herbig, M.; Raabe, D.; Li, Y.; Choi, P.; Zaefferer, S.; Goto, S.: High Throughput Quantification of Grain Boundary Segregation by Correlative TEM and APT. TMS 2014, Solid-State Interfaces III Symposium, San Diego, CA, USA (2014)
Herbig, M.; Raabe, D.; Li, Y.; Choi, P.-P.; Zaefferer, S.; Goto, S.: High Throughput Quantification of Grain Boundary Segregation by Correlative Transmission Electron Microscopy and Atom Probe Tomography. International Conference on Atom Probe Tomography & Microscopy 2014, Stuttgart, Germany (2014)
Konijnenberg, P. J.; Stechmann, G.; Zaefferer, S.; Raabe, D.: Advances in Analysis of 3D Orientation Data Sets Obtained by FIB-EBSD Tomography. 2nd International Congress on 3D Materials Science 2014, Annecy, France (2014)
Ram, F.; Khorashadizadeh, A.; Zaefferer, S.: Kikuchi Band Sharpness: A Measure for the Density of the Crystal Lattice Defects. MSE 2014, Darmstadt, Germany (2014)
Ram, F.; Zaefferer, S.: Accurate Kikuchi band localization and its application for diffraction geometry determination. HR-EBSD workshop, Imperial College, London, UK (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…