MétaCan
Menu
Back to cohort
Record W2081779515 · doi:10.1021/cg900313b

Hierarchical Al<sub>2</sub>O<sub>3</sub>Nanobelts and Nanowires: Morphology Control and Growth Mechanism

2009· article· en· W2081779515 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCrystal Growth & Design · 2009
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNanowireTransmission electron microscopyScanning electron microscopeNanotechnologyMaterials scienceFabricationVapor–liquid–solid methodNanostructureHigh-resolution transmission electron microscopySelected area diffractionChemical engineeringMorphology (biology)SpectroscopyEnergy-dispersive X-ray spectroscopyComposite material

Abstract

fetched live from OpenAlex

We report here a tunable synthesis of single crystalline hierarchical α-Al 2 O 3 nanobelts and nanowires by selectively applying a vapor−liquid−solid (VLS) and vapor−solid (VS) strategy in a chemical vapor process. The resultant nanostructures were characterized by scanning electron microscopy, transmission electron microscopy, high-resolution transmission electron microscopy, energy dispersive X-ray spectroscopy, and X-ray powder diffraction. The hierarchical nanobelts were generated by a noncatalytic oriented growth of Al 2 O 3 vertical to the {110} planes enclosed with {001} and {100} planes following a VS mode. The hierarchical nanowires were obtained through a catalytic growth in a VLS process. This well-controlled synthesis strategy is expected to be applicable to fabrication of other hierarchical nanobelts or nanowires.

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.

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 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 score0.215
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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 head0.008
GPT teacher head0.193
Teacher spread0.185 · 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