Orientation-Adaptive Virtual Imaging of Defects using EBSD
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2025
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| author | della Ventura, Nicolò M. Lamb, James D. Lenthe, William C. Echlin, McLean P. Pürstl, Julia T. Trageser, Emily S. Quevedo, Alejandro M. Begley, Matthew R. Pollock, Tresa M. Gianola, Daniel S. De Graef, Marc |
| author_facet | della Ventura, Nicolò M. Lamb, James D. Lenthe, William C. Echlin, McLean P. Pürstl, Julia T. Trageser, Emily S. Quevedo, Alejandro M. Begley, Matthew R. Pollock, Tresa M. Gianola, Daniel S. De Graef, Marc |
| contents | EBSD is a foundational technique for characterizing crystallographic orientation, phase distribution, and lattice strain. Embedded within EBSD patterns lies latent information on dislocation structures, subtly encoded due to their deviation from perfect crystallinity - a feature often underutilized. Here, a novel framework termed orientation-adaptive virtual apertures (OAVA) is introduced. OAVAs enable the generation of virtual images tied to specific diffraction conditions, allowing the direct visualization of individual dislocations from a single EBSD map. By dynamically aligning virtual apertures in reciprocal space with the local crystallographic orientation, the method enhances contrast from defect-related strain fields, mirroring the principles of diffraction-contrast imaging in TEM, but without sample tilting. The approach capitalizes on the extensive diffraction space captured in a single high-quality EBSD scan, with its effectiveness enhanced by modern direct electron detectors that offer high-sensitivity at low accelerating voltages, reducing interaction volume and improving spatial resolution. We demonstrate that using OAVAs, identical imaging conditions can be applied across a polycrystalline field-of-view, enabling uniform contrast in differently oriented grains. Furthermore, in single-crystal GaN, threading dislocations are consistently resolved. Algorithms for the automated detection of dislocation contrast are presented, advancing defect characterization. By using OAVAs across a wide range of diffraction conditions in GaN, the visibility/invisibility of defects, owing to the anisotropy of the elastic strain field, is assessed and linked to candidate Burgers vectors. Altogether, OAVA offers a new and high-throughput pathway for orientation-specific defect characterization with the potential for automated, large-area defect analysis in single and polycrystalline materials. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_15523 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Orientation-Adaptive Virtual Imaging of Defects using EBSD della Ventura, Nicolò M. Lamb, James D. Lenthe, William C. Echlin, McLean P. Pürstl, Julia T. Trageser, Emily S. Quevedo, Alejandro M. Begley, Matthew R. Pollock, Tresa M. Gianola, Daniel S. De Graef, Marc Materials Science EBSD is a foundational technique for characterizing crystallographic orientation, phase distribution, and lattice strain. Embedded within EBSD patterns lies latent information on dislocation structures, subtly encoded due to their deviation from perfect crystallinity - a feature often underutilized. Here, a novel framework termed orientation-adaptive virtual apertures (OAVA) is introduced. OAVAs enable the generation of virtual images tied to specific diffraction conditions, allowing the direct visualization of individual dislocations from a single EBSD map. By dynamically aligning virtual apertures in reciprocal space with the local crystallographic orientation, the method enhances contrast from defect-related strain fields, mirroring the principles of diffraction-contrast imaging in TEM, but without sample tilting. The approach capitalizes on the extensive diffraction space captured in a single high-quality EBSD scan, with its effectiveness enhanced by modern direct electron detectors that offer high-sensitivity at low accelerating voltages, reducing interaction volume and improving spatial resolution. We demonstrate that using OAVAs, identical imaging conditions can be applied across a polycrystalline field-of-view, enabling uniform contrast in differently oriented grains. Furthermore, in single-crystal GaN, threading dislocations are consistently resolved. Algorithms for the automated detection of dislocation contrast are presented, advancing defect characterization. By using OAVAs across a wide range of diffraction conditions in GaN, the visibility/invisibility of defects, owing to the anisotropy of the elastic strain field, is assessed and linked to candidate Burgers vectors. Altogether, OAVA offers a new and high-throughput pathway for orientation-specific defect characterization with the potential for automated, large-area defect analysis in single and polycrystalline materials. |
| title | Orientation-Adaptive Virtual Imaging of Defects using EBSD |
| topic | Materials Science |
| url | https://arxiv.org/abs/2504.15523 |