Kuzmina, M.; Herbig, M.; Ponge, D.; Choi, P.-P.; Stoffers, A.; Sandlöbes, S.; Raabe, D.: Segregation engineering enables nanostructured dual-phase laminates via solute decoration and phase transformation at lattice defects. Colloquium lecture at Department of Mechanical Engineering, Technische Universiteit Eindhoven, Eindhoven, The Netherlands (2015)
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)
Choi, P.-P.: Characterization of Ni- and Co-based superalloys using Atom Probe Tomography. International Workshop on Modelling and Simulation of Superalloys, Bochum, Germany (2014)
Jägle, E. A.; Tytko, D.; Choi, P.-P.; Raabe, D.: Deformation-induced intermixing in a model multilayer system. Atom Probe Tomography & Microscopy 2014, Stuttgart, Germany (2014)
Li, Y.; Ponge, D.; Choi, P.-P.; Raabe, D.: Segregation of boron at prior austenite grain boundaries in a quenched steel studied by atom probe tomography. Atom Probe Tomography & Microscopy 2014, Stuttgart, Germany (2014)
Herbig, M.; Li, Y.; Morsdorf, L.; Goto, S.; Choi, P.-P.; Kirchheim, R.; Raabe, D.: Recent Advances in Understanding the Structures and Properties of Nanomaterials. Gordon Research Conference on Structural Nanomaterials, The Chinese University of Hong Kong, Hong Kong, China (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
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.
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…
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.