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Record W1768809741 · doi:10.3390/ma8095314

Electrochemical Behavior of Al-B4C Metal Matrix Composites in NaCl Solution

2015· article· en· W1768809741 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMaterials · 2015
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsUniversité du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceCorrosionDielectric spectroscopyComposite materialComposite numberMetalGalvanic corrosionGalvanic cellPolarization (electrochemistry)ElectrochemistryMetal matrix compositeVolume fractionAluminiumPitting corrosionMetallurgyElectrodeChemistry

Abstract

fetched live from OpenAlex

Aluminum based metal matrix composites (MMCs) have received considerable attention in the automotive, aerospace and nuclear industries. One of the main challenges using Al-based MMCs is the influence of the reinforcement particles on the corrosion resistance. In the present study, the corrosion behavior of Al-B₄C MMCs in a 3.5 wt.% NaCl solution were investigated using potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS) techniques. Results indicated that the corrosion resistance of the composites decreased when increasing the B₄C volume fraction. Al-B₄C composite was susceptible to pitting corrosion and two types of pits were observed on the composite surface. The corrosion mechanism of the composite in the NaCl solution was primarily controlled by oxygen diffusion in the solution. In addition, the galvanic couples that formed between Al matrix and B₄C particles could also be responsible for the lower corrosion resistance of the composites.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.524

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 head0.017
GPT teacher head0.239
Teacher spread0.222 · 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