RETRACTED ARTICLE: Significantly enhanced critical current density and pinning force in nanostructured, (RE)BCO-based, coated conductor
Post-publication record
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Bibliographic record
Abstract
High-temperature superconducting wires have many large-scale, niche applications such as commercial nuclear fusion as well as numerous other large-scale applications in the electric power industry and in the defense, medical and transportation industries. However, the price/performance metric of these coated conductor wires is not yet favorable to enable and realize most large-scale applications. Here we report on probing the limits of J c (H, T) possible via defect engineering in heteroepitaxially deposited high-temperature superconducting thin-films on coated conductor substrates used for long-length wire fabrication. We report record values of J c (H, T) and pinning force, F p (H, T) in (RE)BCO films with self-assembled BaZrO3 nanocolumns deposited on a coated conductor substrate. A J c of ~190 MA/cm2 at 4.2 K, self-field and ~90 MA/cm2, at 4.2 K, 7 T was measured. At 20 K, J c of over 150 MA/cm2 at self-field and over 60 MA/cm2 at 7 T was observed. A very high pinning force, F p, of ~6.4 TN/m3 and ~4.2 TN/m3 were observed at 7 T, 4.2 K and 7 T, 20 K respectively. We report on the highest values of J c and F p obtained to date for all fields and operating temperatures from 4.2 K to 77 K. These results demonstrate that significant performance enhancements and hence far more favorable price/performance metrics are possible in commercial high-temperature superconducting wires. In this work, authors demonstrate defect engineering in heteroepitaxially deposited high-temperature superconducting thin-films on coated conductor substrates achieving significant performance enhancement in the critical current density and pinning force achievable in coated conductors.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".