Keuter, P.: Design of materials with anomalous thermophysical properties and desorption-assisted phase formation of intermetallic thin films. Dissertation, RWTH Aachen University (2020)
Pei, R.: Microstructural Relationships of Strength and Ductility in a Newly Developed Mg–Al–Zn Alloy for Potential Automotive Applications. Dissertation, RWTH Aachen University (2020)
Pei, R.: Microstructural Relationships of Strength and Ductility in a Newly Developed Mg–Al–Zn Alloy for Po-tential Automotive Applications. Dissertation, RWTH Aachen University (2020)
Kürnsteiner, P.: Precipitation Reactions During the Intrinsic Heat Treatment of Laser Additive Manufacturing. Dissertation, RWTH Aachen University (2019)
Dutta, A.: Deformation behaviour and texture memory effect of multiphase nano-laminate medium manganese steels. Dissertation, RWTH Aachen University (2019)
Hariharan, A.: On the interfacial defect formation mechanism during laser additive manufac-turing of polycrystalline superalloys. Dissertation, Ruhr-Universität Bochum (2019)
Hariharan, A.: On the interfacial defect formation mechanism during laser additive manufacturing of polycrystalline superalloys. Dissertation, Ruhr-Universität Bochum (2019)
Chang, Y.: Challenges and opportunities associated to the characterization of H/D in Ti and its alloys with atom probe tomography. Dissertation, RWTH Aachen University (2019)
Archie, F. M. F.: Microstructural influence on micro-damage initiation in ferritic-martensitic DP-steels. Dissertation, RWTH Aachen, Aachen, Germany (2018)
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…