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)
Ram, F.; Zaefferer, S.: Plastic strain derivation and Kikuchi band localization by applying the Kikuchi bandlet method to electron backscatter Kikuchi Diffraction patterns. 17th ICOTOM, Dresden; Germany (2014)
Zaefferer, S.: SEM and TEM based orientation microscopy for investigation of recrystallization processes. CNRS summer school on recrystallization, Frejus, France (2014)
Herbig, M.; Raabe, D.; Li, Y. J.; Choi, P.; Zaefferer, S.; Goto, S.: Quantification of Grain Boundary Segregation in Nanocrystalline Material. Seminar at Department Microstructure Physics and Alloy Design, MPI für Eisenforschung, Düsseldorf, Germany (2013)
Zaefferer, S.; Elhami, N. N.: Electron Channelling Contrast Imaging under controlled diffraction conditions, cECCI - Theory and Applications. CEMEF, Sofia-Antipolis, France (2013)
Zaefferer, S.; Kleindiek, S.; Schock, K.; Volbert, B.: Combined Application of EBSD and ECCI Using a Versatile 5-Axes Goniometer in an SEM. Microscopy and Microanalysis 2013, Indianapolis, IN, USA (2013)
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)
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
A novel design with independent tip and sample heating is developed to characterize materials at high temperatures. This design is realized by modifying a displacement controlled room temperature micro straining rig with addition of two miniature hot stages.
Many important phenomena occurring in polycrystalline materials under large plastic strain, like microstructure, deformation localization and in-grain texture evolution can be predicted by high-resolution modeling of crystals. Unfortunately, the simulation mesh gets distorted during the deformation because of the heterogeneity of the plastic…
In this project we developed a phase-field model capable of describing multi-component and multi-sublattice ordered phases, by directly incorporating the compound energy CALPHAD formalism based on chemical potentials. We investigated the complex compositional pathway for the formation of the η-phase in Al-Zn-Mg-Cu alloys during commercial…
The project HyWay aims to promote the design of advanced materials that maintain outstanding mechanical properties while mitigating the impact of hydrogen by developing flexible, efficient tools for multiscale material modelling and characterization. These efficient material assessment suites integrate data-driven approaches, advanced…
The Atom Probe Tomography group in the Microstructure Physics and Alloy Design department is developing integrated protocols for ultra-high vacuum cryogenic specimen transfer between platforms without exposure to atmospheric contamination.
Here, we aim to develop machine-learning enhanced atom probe tomography approaches to reveal chemical short/long-range order (S/LRO) in a series of metallic materials.