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Record W7083592091 · doi:10.1016/j.hybadv.2025.100554

Development and evaluation of modified ZnCr-Shell particulates composite coatings: corrosion, structural, and microhardness properties

2025· article· en· W7083592091 on OpenAlexaff

Bibliographic record

VenueHybrid Advances · 2025
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsComposite numberCorrosionIndentation hardnessDurabilityPorosityMicrostructureReinforcementChloride

Abstract

fetched live from OpenAlex

Corrosion-induced surface degradation in ship hulls necessitates advanced protective solutions. This study develops sustainable composite coatings by electrodepositing coconut shell particles (CSP) into Zn-CrO 3 matrices. This work introduces the novel use of coconut shell waste as a synergistic reinforcement to enhance both the anti-corrosion and mechanical properties of Zn-CrO 3 coatings. Coatings with increasing CSP content (0-6 g/L) were evaluated, demonstrating exceptional performance: Zn-20CrO 3 -6CSP achieved 93.325 Ω polarization resistance (297% higher than uncoated steel), reduced corrosion rate by 75% to 2.285 mm/year, and increased hardness by 90% to 259.3 Kgf/mm 2 . Microstructural analysis revealed a novel, transformative evolution from porous scale-like formations to compact knot-like structures that physically impede chloride penetration. These enhancements derive from the novel finding of CSP's dual functionality as both a pore-blocking barrier and grain-refining agent. The findings establish CSP as an effective eco-friendly reinforcement for marine coatings, offering superior corrosion protection and mechanical durability through sustainable waste valorization.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.311

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)0.0000.000

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 head0.049
GPT teacher head0.352
Teacher spread0.303 · 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 designObservational
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

Citations1
Published2025
Admission routes1
Has abstractyes

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