Table of Contents
Fetching ...

Unexpected Planar Dislocation Boundary Formation in FCC Metals Captured by Dark-Field X-ray Microscopy and Continuum Dislocation Dynamics

Adam André William Cretton, Khaled SharafEldin, Axel Henningsson, Felix Frankus, Can Yıldırım, Carsten Detlefs, Flemming Bjerg Grumsen, Albert Zelenika, Anter El-Azab, Grethe Winther, Henning Friis Poulsen

Abstract

Validating dislocation patterning models against in situ imaging experiments is a longstanding goal in materials physics. Here, we provide the first direct morphological comparison of such models. Using in situ Dark-Field X-ray Microscopy (DFXM), we map the local orientations in high-purity aluminium deformed along [100] and find unexpected planar dislocation boundaries aligned with {111} slip planes that form prior to the development of a conventional dislocation cell structure. To explain this behaviour, we generate synthetic DFXM contrast images from a continuum dislocation dynamics (CDD) simulation. This mesoscale model, using nickel as a high stacking fault energy (SFE) FCC analogue, independently predicts the formation of the same {111} planar boundary types. This correspondence demonstrates that state-of-the-art CDD and DFXM experimental data can be used synergistically - despite differences in strain rates and length scales - as a practical route for refining continuum theories of plasticity.

Unexpected Planar Dislocation Boundary Formation in FCC Metals Captured by Dark-Field X-ray Microscopy and Continuum Dislocation Dynamics

Abstract

Validating dislocation patterning models against in situ imaging experiments is a longstanding goal in materials physics. Here, we provide the first direct morphological comparison of such models. Using in situ Dark-Field X-ray Microscopy (DFXM), we map the local orientations in high-purity aluminium deformed along [100] and find unexpected planar dislocation boundaries aligned with {111} slip planes that form prior to the development of a conventional dislocation cell structure. To explain this behaviour, we generate synthetic DFXM contrast images from a continuum dislocation dynamics (CDD) simulation. This mesoscale model, using nickel as a high stacking fault energy (SFE) FCC analogue, independently predicts the formation of the same {111} planar boundary types. This correspondence demonstrates that state-of-the-art CDD and DFXM experimental data can be used synergistically - despite differences in strain rates and length scales - as a practical route for refining continuum theories of plasticity.
Paper Structure (1 section, 1 equation, 4 figures)

This paper contains 1 section, 1 equation, 4 figures.

Figures (4)

  • Figure 1: Summary of DFXM experiment. Evolution of lattice orientation during tensile deformation of Aluminium along the [100] axis is shown, visualised as orientation maps at 0.2%, 3.0%, 5.0% and 7.6% strain. Colour encodes the local lattice orientation. The illuminated layer was not tracked continuously across strain steps due to sample elongation.
  • Figure 2: Summary of CDD simulations for [100] tensile deformation of Ni. Top row: Forward-modelled DFXM orientation maps at successive strain levels (0.0%, 1.0%, 2.0%, 3.0% and 3.5%). Colour encodes the local lattice orientation. Bottom row: Corresponding kernel average misorientation (KAM) maps (log scale), highlighting local orientation differences, with dislocation cells nucleating highlighted with black arrows.
  • Figure 3: Comparison of planar dislocation boundary trace orientations observed in the CDD simulation (above) and experimentally (below) - for [100]-oriented deformation. In both cases, planar boundaries are visible. The traces align closely with the projected directions of $\{111\}$ slip planes. Dashed-line overlays indicate the calculated slip-trace directions.
  • Figure 4: Autocorrelation analysis of experimental rocking-direction orientation maps at 5.0% strain (above) and 7.6% strain (below). Red dashed arrows indicate the projected $\{111\}$ slip-trace directions $(0\ \overline{1}\ \overline{1})$, $(2\ 1\ 1)$ and $(2\ \overline{1}\ \overline{1})$. The middle panels show a contour plot highlighting anisotropic correlation features. The right panels show line profiles through the autocorrelation along the horizontal ($x$) and vertical ($y$) directions.