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Record W1998797981 · doi:10.2495/mc070031

Effect of fly ash reinforcement on the corrosion behaviour of cast Al-Mg alloy A535 in 3.5 wt% NaC1 solution

2007· article· en· W1998797981 on OpenAlexafffund
I. N. A. Oguocha, Richard W. Evitts

Bibliographic record

VenueWIT transactions on engineering sciences · 2007
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFly ashMaterials scienceCorrosionAlloyMetallurgyImmersion (mathematics)Pitting corrosionElectrochemistryPorosityComposite materialElectrodeChemistry

Abstract

fetched live from OpenAlex

The effect of fly ash reinforcement on the room temperature corrosion behaviour an immersion corrosion test, electrochemical tests and optical microscopy. The materials studied were A535 and its metal matrix composites (MMCs) containing 10wt% fly ash, 15wt% fly ash, and a hybrid reinforcement (5wt% fly ash+5wt% SiC). The immersion corrosion test results showed that the corrosion rate of the MMCs increased with increasing fly ash content while the electrochemical test results indicated that their corrosion potential (E corr ) and critical pitting (breakdown) potential (E p ) decreased with increasing fly ash content. The repassivation potentials of the MMCs were found to be more positive than that of the matrix alloy. The corrosion of the MMCs, which was accompanied by loosening of fly ash particles, was also affected by porosity and the presence of several reaction products.

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 score0.004
Threshold uncertainty score0.008

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 head0.216
Teacher spread0.208 · 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

Citations3
Published2007
Admission routes2
Has abstractyes

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Same venueWIT transactions on engineering sciencesSame topicAluminum Alloy Microstructure PropertiesFrench-language works237,207