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2026-06-22 11:03 |
[FZJ-2026-02803]
Dissertation / PhD Thesis
Govind, K. ; Sandfeld, S. ; Mayer, J.
Towards generalized machine learning models for dislocation image analysis: a parametric based synthetic data approach
RWTH Aachen University pages 1 Online-Ressource : Illustrationen (2025) [10.18154/RWTH-2025-08373]2025 = Dissertation, RWTH Aachen, 2026
Since the first observation of dislocations in the mid 1950s, when electron microscopy was used to visualize these defects, there have been significant advancements in microscopy techniques, allowing for the acquisition of high-quality, high-resolution dislocation image data. Today, it is even possible to perform in-situ mechanical testing, enabling the observation of dislocation microstructure evolution during the plastic deformation of materials. [...]
OpenAccess: PDF; External link: Fulltext
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2026-06-22 11:01 |
[FZJ-2026-02802]
Dissertation / PhD Thesis
Ihsan, A. Z. ; Sandfeld, S. ; Kerzel, U. B.
Enabling the digital transformation in materials science and engineering: leveraging ontologies for knowledge representation, provenance, and text mining
RWTH Aachen University pages 1 Online-Ressource : Illustrationen (2025) [10.18154/RWTH-2025-07969]2025 = Dissertation, RWTH Aachen, 2025
The digital transformation of Materials Science and Engineering (MSE) is essential for accelerating the development of novel materials and enhancing understanding of the materials life cycle, encompassing raw resources, functional materials, engineered components, and beyond. This transformation entails integrating computational methods, data science, and artificial intelligence (AI) to advance the field of MSE. [...]
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