Inferring Dislocation Microstructures from X-ray Diffraction via Cross-Modal Contrastive Learning
Understanding and inferring dislocation microstructures from diffraction patterns remains an open challenge in materials characterization, as diffraction measurements provide only indirect information about the underlying dislocation structure. In this work, a cross-modal learning framework is developed to enable the prediction of 3D dislocation structures directly from diffraction data. Dislocation density fields generated from discrete dislocation dynamics simulations are paired with corresponding virtual X-ray diffraction patterns and embedded into a shared 2D latent space using contrastive learning. The alignment between structural and diffraction representations of dislocation struct...
| Authors | Benjamin Udofia, Nicolas Bertin, Markus Stricker |
|---|---|
| Primary category | cond-mat.mtrl-sci |
| Published | 11 September 2026 |
| Last updated at source | 11 September 2026 |
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.