Characterization of a bent Laue double-crystal beam-expanding monochromator
Bibliographic record
Abstract
A bent Laue double-crystal monochromator system has been designed for vertically expanding the X-ray beam at the Canadian Light Source's BioMedical Imaging and Therapy beamlines. Expansion by a factor of 12 has been achieved without deteriorating the transverse coherence of the beam, allowing phase-based imaging techniques to be performed with high flux and a large field of view. However, preliminary studies revealed a lack of uniformity in the beam, presumed to be caused by imperfect bending of the silicon crystal wafers used in the system. Results from finite-element analysis of the system predicted that the second crystal would be most severely affected and has been shown experimentally. It has been determined that the majority of the distortion occurs in the second crystal and is likely caused by an imperfection in the surface of the bending frame. Measurements were then taken to characterize the bending of the crystal using both mechanical and diffraction techniques. In particular, two techniques commonly used to map dislocations in crystal structures have been adapted to map local curvature of the bent crystals. One of these, a variation of Berg-Berrett topography, has been used to quantify the diffraction effects caused by the distortion of the crystal wafer. This technique produces a global mapping of the deviation of the diffraction angle relative to a perfect cylinder. This information is critical for improving bending and measuring tolerances of imperfections by correlating this mapping to areas of missing intensity in the beam.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".