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Record W4417147667 · doi:10.1016/j.rinma.2025.100841

Functionalized Cocos nucifera L shell particulate enhancement on the nanocrystalline and anticorrosion performance of Zn-Al2O3-CSP on mild steel for extended application

2025· article· en· W4417147667 on OpenAlexaff
O.S.I. Fayomi, Omaji Adakole, Ho Soonmin, K. M. Oluwasegun

Bibliographic record

VenueResults in Materials · 2025
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCorrosionNanocrystalline materialScanning electron microscopeCoatingPolarization (electrochemistry)IntermetallicNanocompositeIndentation hardness

Abstract

fetched live from OpenAlex

The degradation of mild steel in corrosive environments necessitates innovative, eco-friendly protective coatings. This study aims to enhance the corrosion resistance and mechanical properties of mild steel by developing a Zn-Al 2 O 3 nanocomposite coating reinforced with functionalized coconut shell particulates (CSP: 0, 2, 4, 6 g) constant-current electrodeposition (1.5 A/cm 2 ). The coatings were characterized for corrosion behavior in 3.65 % NaCl using linear polarization resistance (LPR) and open circuit potential (OCP), while hardness, microstructure, and phase composition were assessed via Brinell hardness testing, scanning electron microscopy (SEM), and X-ray diffraction (XRD). Results revealed that Zn-20Al 2 O 3 -6CSP significantly outperformed uncoated steel, with polarization resistance increasing from 23.5 Ω cm 2 to 97.2 Ω cm 2 and corrosion rate decreasing from 9.98 mm/year to 1.16 mm/year. Hardness improved by 92 % (to 261.8 kgf/mm 2 ) due to reduced voids and intermetallic phases (ZnO, Al 2 O 3 , MgO, FeO). These findings position CSP as a promising sustainable additive for advanced anti-corrosion coatings, warranting further exploration in marine applications.

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)0.001
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 score0.003
Threshold uncertainty score0.449

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 head0.022
GPT teacher head0.284
Teacher spread0.262 · 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.

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
Published2025
Admission routes1
Has abstractyes

Explore more

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