Kirchlechner, C.; Malyar, N.; Dehm, G.: Insights into dislocation grain-boundary interaction by X-ray µLaue diffraction. Dislocations 2016, West Lafayette, IN, USA (2016)
Kirchlechner, C.: Synchrotron based µLaue diffraction to probe plasticity at interfaces. IRSP 2016, 14th International Conference Reliability and Stress-Related Phenomena in Nanoelectronics – Experiment and Simulation
, Dresden, Germany (2016)
Kirchlechner, C.; Malyar, N.; Imrich, P. J.; Dehm, G.: Dislocation twin boundary interaction and its dependence on loading direction. 62. Metallkunde-Kolloquium, Lech am Arlberg, Austria (2016)
Kirchlechner, C.; Malyar, N.; Imrich, P. J.: X-ray microdiffraction Laue experiments to understand plasticity at interfaces. 80th Annual Conference of the DPG and DPG Spring Meeting, Regensburg, Germany (2016)
Jaya, B. N.; Köhler, M.; Schnabel, V.; Raabe, D.; Schneider, J. M.; Kirchlechner, C.; Dehm, G.: Micro-scale fracture behavior of Co based metallic glass thin films. 2016 TMS Annual Meeting and Exhibition Symposium: In Operando Nano- and Micro-mechanical Characterization of Materials with Special Emphasis on In Situ Techniques, Nashville, TN, USA (2016)
Luo, W.; Kirchlechner, C.; Dehm, G.; Stein, F.: A New Method to Study the Composition Dependence of Mechanical Properties of Laves. MRS Fall Meeting 2016, Boston, MA, USA (2016)
Davydok, A.; Jaya, B. N.; Micha, J.-S.; Kirchlechner, C.: Can We Analyze the Full Strain Tensor During a micro-Compression Experiment? A µLaue case study on Germanium. CNRS GDRi mecano: General Meeting
, Marseille, France (2015)
Dehm, G.; Imrich, P. J.; Malyar, N.; Kirchlechner, C.: Differences in deformation behavior of bicrystalline Cu micropillars containing different grain boundaries. MS&T 2015 (Materials Science and Technology) meeting, symposium entitled "Deformation and Transitions at Grain Boundaries", Columbus, OH, USA (2015)
Davydok, A.; Jaya, B. N.; Micha, J.-S.; Kirchlechner, C.: Can We Analyze the Full Strain Tensor During a micro-Compression Experiment? A µLaue case study on Germanium. Size & Strain
, Oxford, UK (2015)
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.
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…