ADOPTING TRANSMISSION KIKUCHI DIFFRACTION TO CHARACTERIZE GRAIN STRUCTURE AND TEXTURE OF ZR-2.5NB CANDU PRESSURE TUBES
Bibliographic record
Abstract
The microstructure and texture of Zr-2.5Nb pressure tubes is greatly influenced by the manufacturing route. Although the general nature of the microstructure remains consistent between different manufacturing routes, subtle differences in the relative size and aspect ratios of the elongated α-Zr grains differ with pressure tubes of different pedigree. These differences have been shown to correlate well with in-reactor deformation; however, the ability to consistently and efficiently characterize the microstructures hinders an understanding of the fundamental degradation mechanisms. This paper outlines a new approach to characterize Zr-2.5Nb pressure tubes using thin foils characterized with both diffraction contrast in a conventional transmission electron microscope (TEM) and transmission Kikuchi diffraction (TKD) in a scanning electron microscope (SEM). The combined approaches enable a characterization of the same region of material with both techniques and capitalize on the advantages of each approach. In addition to obtaining general microscopy from SEM-TKD, the localized texture is obtained and compared to texture from X-ray diffraction, which provides higher confidence that the grains examined in the TEM foils are representative of the bulk material.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".