Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Bach, Jakob

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Karlsruhe Institute of Technology

in Cooperation with on an Cooperation-Score of 37%

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  • 2020Data-driven exploration and continuum modeling of dislocation networks16citations

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Sudmanns, Markus
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Weygand, Daniel
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Schulz, Katrin
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2020

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  • Sudmanns, Markus
  • Weygand, Daniel
  • Schulz, Katrin
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article

Data-driven exploration and continuum modeling of dislocation networks

  • Sudmanns, Markus
  • Weygand, Daniel
  • Bach, Jakob
  • Schulz, Katrin
Abstract

The microstructural origin of strain hardening during plastic deformation in stage II deformation of face-centered cubic (fcc) metals can be attributed to the increase in dislocation density resulting in a formation of dislocation networks. Although this is a well known relation, the complexity of dislocation multiplication processes and details about the formation of dislocation networks have recently been revealed by discrete dislocation dynamics (DDD) simulations. It has been observed that dislocations, after being generated by multiplication mechanisms, show a limited expansion within their slip plane before they get trapped in the network by dislocation reactions. This mechanism involves multiple slip systems and results in a heterogeneous dislocation network, which is not reflected in most dislocation-based continuum models. We approach the continuum modeling of dislocation networks by using data science methods to provide a link between discrete dislocations and the continuum level. For this purpose, we identify relevant correlations that feed into a model for dislocation networks in a dislocation-based continuum theory of plasticity. As a key feature, the model combines the dislocation multiplication with the limitation of the travel distance of dislocations by formation of stable dislocation junctions. The effective mobility of the network is determined by a range of dislocation spacings which reproduces the scattering travel distances of generated dislocation as observed in DDD. The model is applied to a high-symmetry fcc loading case and compared to DDD simulations. The results show a physically meaningful microstructural evolution, where the generation of new dislocations by multiplication mechanisms is counteracted by a formation of a stable dislocation network. In conjunction with DDD, we observe a steady state interplay of the different mechanisms.

Topics
  • density
  • impedance spectroscopy
  • polymer
  • mobility
  • theory
  • simulation
  • dislocation
  • plasticity
  • informatics
  • dislocation dynamics