Tasan, C. C.: Overcoming challenges in damage engineering: Design of reliable damage quantification methodologies and damage-resistant microstructures. TMS 2015, Orlando, FL, USA (2015)
Tasan, C. C.; Diehl, M.; Yan, D.; Raabe, D.: Coupled high-resolution experiments and crystal plasticity simulations to analyze stress and strain partitioning in multi-phase alloys. TMS2015, Orlando, FL, USA (2015)
Tasan, C. C.; Yan, D.; Raabe, D.: A novel, high-resolution approach for concurrent mapping of micro-strain and micro-structure evolution up to damage nucleation. TMS 2015, Orlando, FL, USA (2015)
Morsdorf, L.; Tasan, C. C.; Ponge, D.; Raabe, D.: Lath martensite transformation, µ-plasticity and tempering reactions: potential TEM aids. Seminar at Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany (2015)
Tasan, C. C.: Doing more, with less, for longer:Designing high-performance eco-friendly materials guided by in-situ experiments and simulations. Invited Seminar at the Dept. of Mat. Sci. and Eng. of MIT, Boston, MA, USA (2015)
Tasan, C. C.: Investigating Stress - Strain Partitioning in Nanostructured Multi-phase Alloys by Coupled Experiments and Simulations. 3rd World Congress on Integrated Computational Materials Engineering, Colorado Springs, CO, USA (2015)
Tasan, C. C.: Doing more, with less, for longer: Designing high-performance eco-friendly materials guided by in-situ experiments and simulations. Invited Seminar at the Dept. of Mat. Sci. and Eng. of MIT, Boston, MA, USA (2015)
Tasan, C. C.; Morsdorf, L.: In-situ characterization of martensite plasticity by high resolution microstructure and strain mapping. ICM12, Karlsruhe, Germany (2015)
Diehl, M.; Shanthraj, P.; Roters, F.; Tasan, C. C.; Raabe, D.: A Virtual Laboratory to Derive Mechanical Properties. M2i Conference "High Tech Materials: your world - our business"
, Sint Michielgestel, The Netherlands (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
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.
New product development in the steel industry nowadays requires faster development of the new alloys with increased complexity. Moreover, for these complex new steel grades, it is more challenging to control their properties during the process chain. This leads to more experimental testing, more plant trials and also higher rejections due to…