MétaCan
Menu
Back to cohort

Synthesis of Cobalt Nanowires on Porous Anodic Alumina Template Using Electrochemical Deposition

2016· article· en· W2230199585 on OpenAlexvenueno aff
C.K. Chung, Shao-Shuo Wu, Ciao-Yang Hsu, Chia-Hung Dylan Tsai, I.C. Chung

Bibliographic record

VenueJournal of Coating Science and Technology · 2016
Typearticle
Languageen
FieldMaterials Science
TopicAnodic Oxide Films and Nanostructures
Canadian institutionsnot available
Fundersnot available
KeywordsNanowireMaterials scienceCobaltElectrolyteElectrochemistryChemical engineeringScanning electron microscopePorosityNanostructureDeposition (geology)NanotechnologyAnodeElectrodeMetallurgyChemistryComposite material

Abstract

fetched live from OpenAlex

Electrochemical deposition has been widely used for synthesis of metal nanowires (NWs) on the porous template. In this paper, the effect of potential and electrolyte concentration on cobalt (Co) NWs formation through porous anodic alumina template has been investigated using direct-current electrodepostion at 0.75~2 V together with the high 0.5 M and low 0.1 M cobalt sulfurate based electrolyte. Scanning electron microscopy and grazing incidence X-ray diffraction were used to examine the nanostructure, morphology and phase of Co NWs. The current vs time curve was recorded for understanding the growth behavior. Too low potential of 0.75 V is not favored for Co NWs formation due to insufficient driving force while too high potential of 2 V ruins the NWs growth owing to hydrogen generation in reduction reaction. The uniform crystalline Co NWs can be obtained by the proper potential of 1V and concentration of 0.5 M at an average growth rate of 964 nm/min.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.008
GPT teacher head0.245
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Coating Science and TechnologySame topicAnodic Oxide Films and NanostructuresFrench-language works237,207