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Record W2313958863 · doi:10.1166/jnn.2011.3607

NbN and NbS<SUB>2</SUB> Nanobelt Arrays: <I>In-Situ</I> Conversion Preparation and Field-Emission Performance

2011· article· en· W2313958863 on OpenAlexaff
Yourong Tao, Qi-Xiu Gao, Xiaofang Wang, Xingcai Wu, Chang‐Jie Mao, Jun‐Jie Zhu

Bibliographic record

VenueJournal of Nanoscience and Nanotechnology · 2011
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsMinistry of Education and Child Care
Fundersnot available
KeywordsHigh-resolution transmission electron microscopyMaterials scienceField electron emissionTransmission electron microscopyMicrostructureIn situAnalytical Chemistry (journal)SpectroscopyCurrent densityNanotechnologyElectronPhysicsComposite material

Abstract

fetched live from OpenAlex

NbN nanobelt arrays were prepared by an in-situ conversion of aligned NbS3 nanobelts in the flowing NH3 at 950 degrees C, meanwhile, NbS2 nanobelt arrays were produced by a pyrolysis of aligned NbS3 nanobelts in the flowing argon atmosphere. The morphology and size of those nanobelts are close to the NbS3 nanobelt precursors, having a reactangular section of about 11 x 250 - 520 x 3100 nm2, and a length of about 120 microm. The microstructures were characterized by high-resolution transmission electron microscopy (HRTEM) and energy-dispersive X-ray spectroscopy (EDX). Magnetic measurements showed that the NbN nanobelts have superconductivity below 14.1 K. Field-emission experiments showed that the turn-on and threshold fields of the NbN nanobelt arrays (which are defined to be the macroscopic field to produce a current density of 10 microA/cm2 and 1 mA/cm2, respectively) are 0.61 and 2.3 V/microm, respectively, whereas the turn-on and threshold fields of the NbS2 nanobelt arrays are 0.61 and 3.5 V/microm, respectively, suggesting that they are decent field emitters.

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 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 score0.015
Threshold uncertainty score0.920

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.012
GPT teacher head0.202
Teacher spread0.191 · 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

Citations8
Published2011
Admission routes1
Has abstractyes

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