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Record W2066405912 · doi:10.1063/1.4811234

Magnetic interaction and conical self-reorganization of aligned tin oxide nanowire array under field emission conditions

2013· article· en· W2066405912 on OpenAlexaff
Samad Bazargan, Joseph P. Thomas, K. T. Leung

Bibliographic record

VenueJournal of Applied Physics · 2013
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNanowireMaterials scienceField electron emissionTinMagnetic fieldOptoelectronicsConical surfaceChemical vapor depositionEpitaxyPulsed laser depositionRADIUSNanotechnologyTin oxideSapphireVapor–liquid–solid methodNanolithographyCurrent densityLaserLayer (electronics)Thin filmOpticsComposite materialMetallurgyElectron

Abstract

fetched live from OpenAlex

Magnetic interactions are induced between non-magnetic, vertically aligned tin dioxide nanowires under field-emission conditions. Vertically aligned nanowires of tin dioxide are synthesized along the [100] direction by pulsed laser deposition of an epitaxial (200) seed layer on c-cut sapphire substrates followed by vapor-liquid-solid growth using catalyst-assisted pulsed laser deposition method. Due to the dense arrangement of the vertically aligned ultra-long nanowires deposited in this study, magnetic interactions between the nanowires carrying parallel currents become significant within 1 μm radius and lead to their self-reorganization into conical tipi structures under field emission conditions. Optimization of the aerial density of the emission tips and reduction in the field screening effects upon self-reorganization of the nanowire array can account for the large field enhancement factor of 2.6 × 104 at low turn-on field of 3 V/μm.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.006
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.233
Teacher spread0.223 · 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.

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

Citations1
Published2013
Admission routes1
Has abstractyes

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