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The effect of cooling rate on critical current density and microstructure of single grain bulk YBa<sub>2</sub>Cu<sub>3</sub>O<sub>y</sub> superconductors grown by IG process

2018· article· en· W2883346908 on OpenAlexaff
M.S. Santosh, S. Pavan Kumar Naik, M. Murakami

Bibliographic record

VenueJournal of Physics Conference Series · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicrostructureMaterials scienceCritical currentSuperconductivityTexture (cosmology)Scanning electron microscopeAnalytical Chemistry (journal)DiffractionGrain sizeGrain boundaryComposite materialCondensed matter physicsChemistryOpticsChromatography

Abstract

fetched live from OpenAlex

In the recent years, top-seeded infiltration-growth (TS-IG) process of YBa2Cu3Oy (YBCO) had shown crucial and promising strengths as compared to melt growth process. The IG process lucidly clarified that a supply of liquid phase is more than essential for further growing large grains. Further, this experimentation aimed to enhance the performance of bulk YBCO superconducting materials, which were processed by IG process. The homemade Yb-123 and Y-211 were utilized in order to produce YBa2Cu3Oy samples with the means of Yb-123+liquid (1:1) as a liquid source under a varied cooling rate. Moreover, single grain YBCO bulks were fabricated employing TS-IG process consisted of numerous varied cooling rates of 0.16 °C/h, 0.25 °C/h and 0.5 °C/h, respectively. In essence, all samples were oxygenated for 100 h with a constant pressure of 300 mL/min. Therefore, all samples' texture was determined by means of X-ray diffraction measurements. Microstructure analysis was performed by scanning electron microscopy for correlation of critical current density of TS-IG processed single grain YBCO bulks.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.048
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.246
Teacher spread0.234 · 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 teacher head, not a consensus.

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

Citations2
Published2018
Admission routes1
Has abstractyes

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