Hollow cone dark field imaging: automatic acquisition, and its contrast for magnesium
| dc.contributor.author | Parsa, Farhang | |
| dc.contributor.examiningcommittee | Liang, Xihui (Mechanical Engineering) | |
| dc.contributor.examiningcommittee | Guyot, Meghan (Mechanical Engineering) | |
| dc.contributor.supervisor | Zhu, Guozhen | |
| dc.date.accessioned | 2025-06-02T17:02:19Z | |
| dc.date.available | 2025-06-02T17:02:19Z | |
| dc.date.issued | 2025-05-27 | |
| dc.date.submitted | 2025-05-27T19:15:10Z | en_US |
| dc.degree.discipline | Mechanical Engineering | |
| dc.degree.level | Master of Science (M.Sc.) | |
| dc.description.abstract | Hollow Cone Dark Field (HCDF) imaging is a powerful technique, yet it remains under-used for contrast-orientation studies—particularly when rapid, well-timed illumination adjustments are required and, up to the present time of authoring this thesis, no dedicated simulation protocols exist. The key obstacle is software fragmentation: conical-illumination simulation, beam-tilt control, automatic acquisition, and quantitative validation reside in separate programs. Researchers must therefore stitch together ad-hoc scripts and file conversions, hampering usability, reproducibility, and high-throughput studies. This study addresses the challenge by presenting a single, automated framework that unifies the entire HCDF workflow. A common scripting layer (i) generates orientation grids and supercells, (ii) performs multi-slice simulations, (iii) drives the microscope through continuous hollow-cone tilts while capturing images autonomously, and (iv) overlays experimental and simulated patterns with full parameter logging—eliminating manual data hand-offs at every stage. Demonstrated on magnesium crystals, the system simulates several hundred HCDF images, with experimental contrast matching simulation closely enough to validate both model and instrument settings. By fusing simulation, real-time acquisition, and validation into one cohesive environment, the framework transforms HCDF from a specialist method into a practical, high-throughput technique helpful for routine orientation mapping and in-situ deformation studies in both academic and industrial contexts. | |
| dc.description.note | October 2025 | |
| dc.identifier.uri | http://hdl.handle.net/1993/39096 | |
| dc.language.iso | eng | |
| dc.subject | Hollow Cone Dark Field Imaging | |
| dc.subject | Automatic Acquisition | |
| dc.subject | Multislice simulation framework | |
| dc.subject | Magnesium | |
| dc.subject | Contrast | |
| dc.title | Hollow cone dark field imaging: automatic acquisition, and its contrast for magnesium | |
| local.subject.manitoba | no |