arXiv subjects

Adam André William Cretton

Publications and source records attributed to Adam André William Cretton.

3 recordsLinked to original sources

arXiv2026

Bridging powder and multi-crystal diffraction with basis-adaptive texture tomography

In spatially resolved X-ray diffraction experiments using narrow beams, diffraction patterns from polycrystalline materials often fall between two well-served regimes. Fine-grained, weakly textured microstructures produce smooth Debye-Scherrer rings suited to powder- and tensor-tomography methods, whereas coarse, weakly deformed grains produce isolated spots that can be indexed grain by grain. Many important polycrystalline materials, including plastically deformed metals, martensitic and ferroelastic materials containing complex twin microstructures, and geological aggregates with strong texture or heterogeneous grain size, produce spotty diffraction rings with broadened and overlapping peaks between these limits. Texture tomography addresses this regime by reconstructing spatial orientation distributions from diffraction data. Here, conventional texture tomography lacks the angular resolution needed for sharp distributions, while grain-by-grain indexing can introduce boundary artifacts and underestimate intragranular misorientation. This work introduces basis-adaptive texture tomography. Candidate orientations obtained from peak indexing replace the uniform orientation grid, achieving higher angular resolution. Like conventional texture tomography, it benefits from reconstructing a full orientation distribution function in each voxel, allowing voxels to retain contributions from multiple grains, subgrains or domains rather than being forced into a single orientation. Simulated aluminum polycrystals show improved delineation of grain and sub-grain boundaries accompanied by lower intragranular orientation errors compared with uniform-basis texture tomography and point-by-point scanning 3DXRD. An experimental demonstration on tensile-deformed aluminum shows that bulk grain and subgrain structures with orientation spreads of several degrees can be mapped.

cond-mat.mtrl-sci↗

arXiv2026

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

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.

cond-mat.mtrl-sci↗

arXiv2024

Observing formation and evolution of dislocation cells during plastic deformation

During plastic deformation of metals and alloys, dislocations self-organise in cells, which subsequently continuously decrease in size. How and when these processes take place has remained elusive, because observations of the structural dynamics in the bulk have not been feasible. We here present X-ray diffraction microscopy movies of the structural evolution during tensile deformation of a mm-sized aluminium (111) single crystal. The formation and subsequent development of 40,000 cells are visualised. We reveal that cells form in a stochastic and isotropic manner already at 1% strain. We show that the cell size and dislocation density distributions are log-normal and bi-modal Gaussian distributions, respectively, throughout. This insight leads to an interpretation of the formation and evolution steps in terms of universal stochastic multiplicative processes. This work will guide dislocation dynamics modelling, as it provides unique results on cell formation.

cond-mat.mtrl-sci↗