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Record W3145663142 · doi:10.1109/escinano.2010.5701024

Electrically conductive zinc oxide (ZnO) nanostructures prepared by solgel spin-coating

2010· article· en· W3145663142 on OpenAlexaff
Nor Diyana Md Sin, Mohamad Hafiz Mamat, M. Rusop, Zurita Zulkifli

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsSciencetech (Canada)
Fundersnot available
KeywordsMaterials scienceSpin coatingThin filmDopingAbsorbanceZincScanning electron microscopeAnalytical Chemistry (journal)Sol-gelField emission microscopyOptoelectronicsNanotechnologyOpticsComposite materialDiffractionMetallurgy

Abstract

fetched live from OpenAlex

The electrically conductive zinc oxide (ZnO) nanostructures prepared by sol-gel spin coating are presented. This project has been focused on electrical, optical and structural properties of Al doped ZnO thin film. The effects of Al doping concentration at 0∼5 at.% on the Al doped ZnO thin film properties have been investigated. This project involves 3 processes which are thin film preparation, deposition and characterization. The thin films were characterized using Current-Voltage (I–V) measurement and UV-Vis-NIR spectrophotometer for electrical properties and optical properties respectively. The surface morphology has been characterized using field emission scanning electron microscope (FESEM). The I-V measurement result indicated electrical properties of Al doped ZnO thin film improved with Al doping. The absorption coefficient spectra obtained from UV-Vis-NIR spectrophotometer measurement show all films have low absorbance in visible and near infrared (IR) region but have high UV absorption properties. The FESEM investigations shows that the nanoparticles size become smaller and denser as the doping concentration increase.

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 categoriesInsufficient payload (model declined to judge)
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 score0.010
Threshold uncertainty score1.000

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)0.0010.000

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 head0.248
Teacher spread0.238 · 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.

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

Citations4
Published2010
Admission routes1
Has abstractyes

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