Springer, H.; Tasan, C. C.; Raabe, D.: A novel roll-bonding methodology for the cross-scale analysis of phase properties and interactions in multiphase structural materials. International Journal of Materials Research 106 (1), pp. 3 - 14 (2015)
Tasan, C. C.; Hoefnagels, J. P.M.; Diehl, M.; Yan, D.; Roters, F.; Raabe, D.: Strain localization and damage in dual phase steels investigated by coupled in-situ deformation experiments and crystal plasticity simulations. International Journal of Plasticity 63, pp. 198 - 210 (2014)
Wang, M.; Tasan, C. C.; Ponge, D.; Kostka, A.; Raabe, D.: Smaller is less stable: Size effects on twinning vs. transformation of reverted austenite in TRIP-maraging steels. Acta Materialia 79, pp. 268 - 281 (2014)
Yao, M.; Pradeep, K. G.; Tasan, C. C.; Raabe, D.: A novel, single phase, non-equiatomic FeMnNiCoCr high-entropy alloy with exceptional phase stability and tensile ductility. Scripta Materialia 72–73, pp. 5 - 8 (2014)
Tasan, C. C.; Hoefnagels, J. P. M.; Dekkers, E. C. A.; Geers, M. G. D.: Multi-Axial Deformation Setup for Microscopic Testing of Sheet Metal to Fracture. Experimental Mechanics 52 (7), pp. 669 - 678 (2012)
Tasan, C. C.; Hoefnagels, J. P. M.; Geers, M.G. D.: Identification of the continuum damage parameter: An experimental challenge in modeling damage evolution. Acta Materialia 60 (8), pp. 3581 - 3589 (2012)
Tasan, C. C.; Hoefnagels, J. P. M.; Geers, M. G. D.: A micropillar compression methodology for ductile damage quantification. Metallurgical and Materials Transactions A 43 (3), pp. 796 - 801 (2012)
Tasan, C. C.; Hoefnagels, J.P.M.; Geers, M.G.D.: Microstructural Banding Effects Clarified Through Micrographic Digital Image Correlation. Scripta Materialia 62 (11), pp. 835 - 838 (2010)
Tasan, C. C.; Hoefnagels, J.P.M.; Geers, M.G.D.: A brittle-fracture methodology for three-dimensional visualization of ductile deformation micromechanisms. Scripta Materialia 61 (1), pp. 20 - 23 (2009)
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…