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Record W2081971110 · doi:10.5539/apr.v6n6p55

Growth and Characterization of Indium Oxide, Zinc Oxide and Cadmium Sulfide Nanowires by Vapor-Liquid-Solid Growth Technique

2014· article· en· W2081971110 on OpenAlex
Mojgan Mazouchi, Shripriya Poduri, Mitra Dutta

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueApplied Physics Research · 2014
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsNanowireMaterials scienceIndiumPhotoluminescenceZincVapor–liquid–solid methodCadmium sulfideOxideNanotechnologyCadmium oxideZinc sulfideChemical engineeringSulfideCadmiumOptoelectronicsMetallurgy

Abstract

fetched live from OpenAlex

In this study, the growth of three important semiconductor nanowires, Zinc Oxide, Indium Oxide and Cadmium Sulfide nanowires using the vapor–liquid–solid (VLS) method has been investigated. Different growth recipes with different growth parameters were incorporated to synthesize high quality and long NWs. It attempts to provide precise growth recipes which lead to high quality of nanowires. The effect of different growth conditions such as growth temperature, carrier gas flow, presence of metal catalyst and growth time has been investigated. Also, to evaluate the crystal quality of the nanowires, photoluminescence (PL) spectra of the as grown nanowires were investigated.

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)0.001
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 score0.038
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.261
Teacher spread0.248 · 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