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Improvement of the corrosion resistance of acrylic electrocoating in the presence of acid-modified montmorillonite nano clay

2023· article· en· W4380258863 on OpenAlexaff
Mehdi Haghi, Hossein Kazemian, Zahra Ranjbar

Bibliographic record

VenueProgress in Organic Coatings · 2023
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsMontmorilloniteMaterials scienceNanocompositeDielectric spectroscopyCorrosionSalt spray testScanning electron microscopeNano-CoatingAcrylic acidComposite materialField emission microscopyChemical engineeringElectrochemistryPolymerCopolymer

Abstract

fetched live from OpenAlex

This study presents a novel approach to enhance the corrosion resistance of acrylic electrocoating by incorporating acid-modified montmorillonite nano clay particles at varying concentrations (0.0–0.5 wt%) into the coating matrix. The nanostructure and laminar shape of the nano clay particles were confirmed by field emission scanning electron microscopy (FE-SEM). XRD and FE-SEM/EDS analyses revealed successful modification of the nano clay and its uniform dispersion in the electrocoating film. The effect of the nano clay on the rheology of the coating was also investigated using rheometric methods. The anti-corrosion properties of the nanocomposite coatings were evaluated using salt spray and electrochemical impedance spectroscopy (EIS). The EIS results showed that the nanocomposite electrocoating containing 0.3 wt% of acid-modified montmorillonite nano clay exhibited remarkable improvement in anti-corrosion properties and corrosion resistance , with an impedance value of up to 10 Gohm after 21 days of immersion in NaCl 3.5 wt%.

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 score0.007
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.271
Teacher spread0.255 · 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

Citations13
Published2023
Admission routes1
Has abstractyes

Explore more

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