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Record W7077181572

Manufacturing and Performance of Long-Length 2G High-Temperature Superconducting Tapes with Current Flow Diverter Architecture for Magnet Applications

2024· other· fr· W7077181572 on OpenAlexaboutno aff

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2024
Typeother
Languagefr
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsPower consumptionHigh-temperature superconductivitySolid-stateSemiconductor materials
DOInot available

Abstract

fetched live from OpenAlex

RÉSUMÉ: es rubans supraconducteurs d’oxydes de terres rares (REBCO) sont capables de générer des champs magnétiques intenses qui dépassent 20 T, et de conduire l’électricité sans aucune perte résistive à la température de l’azote liquide. Ces rubans sont caractérisés par une structure en couches minces déposées sur un substrat métallique, ce qui les rend aussi mécaniquement flexibles. Plusieurs recherches sont effectuées pour pouvoir utiliser ces matériaux dans les électro-aimants, les limiteurs de courant de défaut, et l’électrification des transports. Ces rubans sont aussi utilisés pour construire des aimants à forts champs magnétiques pour la fusion nucléaire, les accélérateurs des particules et l’imagerie médicale. Malgré les pro-grès réalisés au niveau de la fabrication et de la production des rubans REBCO sur des grandes longueurs, la couche supraconductrice possèdent des inhomogénéités au niveau du courant critique (lc) le long des rubans. Les zones qui possèdent un lc plus faible que la valeur moyenne, générent des points chauds quand le courant appliqué est proche de lc . De plus, ces points chauds se propagent le long du conducteur à une vitesse appelée vitesse de propagation de la zone normale (NZPV). Celle-ci est de l’ordre de quelques centimètres par seconde. La faible NZPV combinée avec les inhomogénéités du courant critique génère un gradient de température local qui peut endommager de façon permanente les dispositifs supraconducteurs. Ainsi, il est primordial d’avoir une méthode rapide et efficace pour la détection des points chauds. Actuellement, un effort considérable est déployé pour développer des méthodes de détection à la fois fiables, sensibles et rapides pour protéger les aimants à base de rubans REBCO contre l’emballement thermique. L’augmentation de la NZPV des rubans REBCO est une approche prometteuse pour limiter le risque de développement des points chauds et accélérer la détection de ceux-ci. Cette approche est réalisable en utilisant une architecture de ruban particulière qui agit sur la NZPV sans dégrader les propriétés supraconductrices des rubans, et qui est appelée «Current Flow Diverter» (CFD). Celle-ci consiste à intégrer une résistance d’interface non uniforme entre la couche de REBCO et la couche de stabilisateur (argent). Cependant, l’effet CFD a seulement été démontré sur des rubans d’une longueur de quelques centimètres. De plus, la complexité de la réalisation de cette architecture la rend inadéquate pour une production industrielle en grande longueur. ABSTRACT: Rare Earth Barium Copper Oxide (REBCO) High Temperature Superconductors (HTS) provide high current densities, high magnetic fields, and good mechanical flexibility. That’s why these conductors make attractive candidates to deliver powerful magnets capable of generating an intense magnetic field that exceeds 20 T. REBCO cables and magnets are currently the hot topics of many research areas such as fault current limitation, energy trans-mission, clean fusion energy, high energy physics, and high-resolution magnetic resonance imaging. Particularly, strong magnetic fields are needed in fusion magnets, particle acceler-ator magnets, and medicine (MRI). This requirement can be addressed by building robust REBCO-based high-field magnets. However, the performance of REBCO magnets is limited by the risk of local failures due to the high probability of nucleation of nonsuperconducting resistive zones, called hot spots. These hot spots expand along REBCO tapes at a certain speed called Normal Zone Propagation Velocity (NZPV). Unfortunately, the NZPV of RE-BCO tapes does not exceed a few centimeters per second (0.1-10 cm/s at 77 K). This low NZPV promotes a concentration of heat in a small region when a hot spot appears, leading to a localized thermal runaway. This localized heating requires a very sensitive and rapid quench detection system, as the local temperature increases rapidly. This makes supercon-ducting devices prone to catastrophic failures, which is costly and represents a threat to all superconducting devices based on REBCO tapes. In addition, REBCO tapes exhibit local millimeter-scale fluctuations in their critical current along their length. When the applied current oversteps the critical current of the defective zones, local superconducting-to-normal transitions, called a quench, occur generating local Joule heating. To overcome this issue, a promising solution is to increase the NZPV of REBCO tapes, and thus increase the quench voltage, which may facilitate quench detection before a thermal runaway occurs. This is now possible thanks to the Current Flow Diverter (CFD) concept, which consists in an innovative architecture of REBCO tapes, developed in Polytechnique Montréal, with a higher NZPV compared to regular (commercial) REBCO tapes. The CFD architecture requires patterning a high interfacial resistance between the stabilizer layer (silver) and the superconducting layer (REBCO). Although the efficiency of this architecture in increasing the NZPV was proved on centimeter-scale REBCO tapes, the complexity of its manufacturing process makes it unattractive for industrial production. Therefore the main objective of this work is to find a fabrication process for implementing the CFD architecture in long lengths and quantify their performance in quench situations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.206
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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