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Record W2329192931 · doi:10.1021/jp2050096

Designed Growth and Characterization of Radially Aligned Ti<sub>5</sub>Si<sub>3</sub> Nanowire Architectures

2011· article· en· W2329192931 on OpenAlexaff
Yong Zhang, Dongsheng Geng, Hao Liu, Mohammad Norouzi Banis, Mihnea Ioan Ionescu, Ruying Li, Mei Cai, Xueliang Sun

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2011
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsWestern University
Fundersnot available
KeywordsNanowireMaterials scienceHigh-resolution transmission electron microscopyChemical vapor depositionVapor–liquid–solid methodNanotechnologyTransmission electron microscopyNanoshellScanning electron microscopeSiliconMicrofiberField electron emissionOptoelectronicsChemical engineeringAnalytical Chemistry (journal)Composite materialElectronChemistryNanoparticle

Abstract

fetched live from OpenAlex

Radially aligned and high-density Ti 5 Si 3 nanowire architectures have been designedly obtained on carbon microfibers through a self-assembly growth by atmospheric pressure chemical vapor deposition. The morphology, structure, and composition of obtained nanowires have been characterized using field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), and energy dispersive X-ray spectroscopy (EDX). The results indicate coaxial cable structure of the nanowires, featuring Ti 5 Si 3 nanocore and silicon oxide nanoshell. The growth mechanism of the nanowires has been proposed as a vapor–liquid–solid (VLS) mechanism. Cyclic voltammetry measurement of the nanowires demonstrates that the Ti 5 Si 3 nanowires show evident electrochemical capacitance characteristics, which may find many applications in producing electrochemical nanodevices, such as electrochemical capacitors.

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 score0.003
Threshold uncertainty score0.529

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 head0.005
GPT teacher head0.170
Teacher spread0.165 · 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

Citations10
Published2011
Admission routes1
Has abstractyes

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