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Record W3100632365 · doi:10.1021/acsomega.0c04948

Niobia Nanofiber-Reinforced Protective Niobium Oxide/Acrylate Nanocomposite Coatings

2020· article· en· W3100632365 on OpenAlexaff
Ubong Eduok

Bibliographic record

VenueACS Omega · 2020
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMaterials scienceNanocompositeCorrosionNanofiberNiobium oxideCoatingOxideAcrylatePolymerizationChemical engineeringNiobiumComposite materialPolymerMetallurgyMonomer

Abstract

fetched live from OpenAlex

In the present study, the corrosion resistance of a new niobium oxide/acrylate hybrid nanocomposite coating doped with niobia nanofibers is investigated. Nanofibers were initially synthesized from niobium(V) chloride precursor in a novel autoclave approach before fabricating the base coating from a two-step process involving the syntheses of acrylate resin via free radical polymerization and niobium oxide gel from niobium ethoxide via a sol-gel technique. Variants of the synthesized nanocomposite coating were incorporated with varying concentrations of niobia nanofibers before spin-coating on Q235 steel substrates to inhibit corrosive electrolytic ion percolation and further enhance corrosion resistance when treated with chloride-enriched corrosive media. The corrosion resistance of these nanocomposite coatings increased with nanofiber content up to an optimum concentration due to the corrosion-inhibiting and protective effects of niobium barrier layers within these coatings. The presence of the niobia nanofibers also promoted improved surface contact angle and toughened mechanical strengths.

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 score0.002
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.018
GPT teacher head0.240
Teacher spread0.221 · 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
Published2020
Admission routes1
Has abstractyes

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