Ta, Ti and Hf effects on Nb <sub>3</sub> Sn high-field performance: temperature-dependent dopant occupancy and failure of Kramer extrapolation
Bibliographic record
Abstract
Abstract The increasing demand for improving the high-field (16–22 T) performance of Nb 3 Sn conductors requires a better understanding of the properties of modern wires much closer to irreversibility field, H Irr . In this study we investigated the impact of Ta, Ti and Hf doping on the high-field pinning properties, the upper critical field, H c2 , and H Irr . We found that the pinning force curves of commercial Ti and Ta doped wires at different temperatures do not scale and that the Kramer extrapolation from low field data, typically used by magnet designers to estimate high-field critical current density and magnet operational margins, is not reliable and significantly overestimates the actual H Irr . In contrast, new laboratory scale conductors made with Nb–Ta–Hf alloy have improved high-field J c performance and, despite contributions by both grain boundary and point defect pinning mechanisms, have more predictable high-field behavior. Using Extended x-ray Absorption Fine Structure spectroscopy, EXAFS, we found that for the commercial Ta and Ti doped conductors, the Ta site occupancy in the A15 structure gradually changes with the heat treatment temperature whereas Ti is always located on the Nb site with clear consequences for H c2 . This work reveals the still limited understanding of what determines H c2 , H Irr and the high-field J c performance of Nb 3 Sn and the complexity of optimizing these conductors so that they can reach their full potential for high-field applications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".