A Differential Scanning Calorimetry (DSC) Study of Phase Changes in an As-Received Zr-2.5Nb Pressure Tube Material during Continuous Heating and Cooling
Bibliographic record
Abstract
Differential scanning calorimetry (DSC) has been used to study the phase changes in samples of as-received Zr-2.5Nb pressure tube material by continuous heating and cooling. Two different heating rates (5 and 20°C/min) were used to heat the sample up to 1050°C. After a short time hold at 1050°C, all the samples were continuously cooled to 300°C at a rate of 20°C/min. On continuous heating, the DSC signals obtained showed two endothermic transitions. The low-temperature transition, occurring between about 500 and 650°C, is attributed to a thermal decomposition of metastable niobium-stabilized β-phase. The highertemperature transition, occurring between 600 and 950°C, is due to phase transformations of hcp α-Zr to bcc β-Zr, as previously confirmed in a companion study on the same pressure-tube material that was examined in-situ by neutron diffraction. The neutron diffraction results provided a positive identification of the two phases and also a quantification of the β-phase present in the sample at different heating temperatures, and thus provided a guide to extract the volume fraction of β-phase from the DSC signals obtained in this study. The DSC signals revealed only one exothermic transition which is correlated to the reverse transformation of β-Zr to α-Zr, as previously identified in the companion neutron diffraction study of the same pressure tube 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".