Cereceda, D.; Diehl, M.; Roters, F.; Raabe, D.; Perlado, J. M.; Marian, J.: An atomistically-informed crystal plasticity model to predict the temperature dependence of the yield strength of single-crystal tungsten. XXV International Workshop on Computational Micromechanics of Materials, Bochum, Germany (2015)
Roters, F.; Zhang, S.; Shantraj, P.: Including damage modelling into crystal plasticity simulation. XXV International Workshop on Computational Micromechanics of Materials, Bochum, Germany (2015)
Wong, S. L.; Roters, F.: Multiscale micromechanical modelling for advanced high strength steels including both the TRIP and TWIP effect. XXV International Workshop on Computational Micromechanics of Materials, Bochum, Germany (2015)
Diehl, M.; Eisenlohr, P.; Roters, F.; Shanthraj, P.; Reuber, J. C.; Raabe, D.: DAMASK: The Düsseldorf Advanced Material Simulation Kit for studying crystal plasticity using an FE based or a spectral numerical solver. Seminar of the Centro Nacional de Investigaciones Metalúrgicas (CENIM) del CSIC , Madrid, Spain (2015)
Roters, F.: Multi-scale Micromechanics and Damage: From Model Development to Real Systems. IEK-Kolloquium „Simulation von Energiematerialien“
, Jülich, Germany (2015)
Wong, S. L.; Roters, F.: A crystal plasticity model for advanced high strength steels including both TRIP and TWIP effect. 12th International Conference on the Mechanical Behavior of Materials ICM 12
, 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
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…
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…
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…
Advanced microscopy and spectroscopy offer unique opportunities to study the structure, composition, and bonding state of individual atoms from within complex, engineering materials. Such information can be collected at a spatial resolution of as small as 0.1 nm with the help of aberration correction.