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Record W2891338872 · doi:10.1080/1478422x.2018.1517468

An investigation of the corrosion behaviour of a FeNiCoAlTa shape memory alloy in 3.5 wt-% NaCl solution

2018· article· en· W2891338872 on OpenAlexaff
Hanan Farhat, Russell Griffin, I. N. A. Oguocha, Richard W. Evitts

Bibliographic record

VenueCorrosion Engineering Science and Technology The International Journal of Corrosion Processes and Corrosion Control · 2018
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMaterials sciencePassivationCorrosionAlloyMetallurgyGrain boundaryIntergranular corrosionDissolutionPitting corrosionSaturated calomel electrodeElectrochemistryMicrostructureElectrodeReference electrodeComposite materialChemical engineeringChemistryLayer (electronics)

Abstract

fetched live from OpenAlex

In this study, the corrosion behaviour of an FeNiCoAlTa (NCAT) shape memory alloy in 3.5% (w w−1) NaCl solution was evaluated. Linear polarisation resistance and potentiodynamic polarisation tests were conducted at 25°C. An open circuit potential (OCP) of −381 mV (vs. saturated calomel reference electrode) and a corrosion rate (CR) of 0.0174 mm y−1 were obtained. The NCAT alloy did not show any passivation in the 3.5% (w w−1) NaCl solution. Its corrosion behaviour was very similar to that of G10180 (AISI 1018) carbon steel with the NCAT showing a lower CR and a less active OCP. Its corrosion in the solution was a combination of general dissolution and localised attack (pitting). Aging heat treatment caused β-Ni3Al phase, and tantalum to precipitate on the grain boundaries, resulting in chemical species segregation between the grain boundaries and the grains. The chemical segregation caused intergranular corrosion of the alloy.

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 score0.007

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)0.0000.000

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 head0.008
GPT teacher head0.237
Teacher spread0.228 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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Same venueCorrosion Engineering Science and Technology The International Journal of Corrosion Processes and Corrosion ControlSame topicShape Memory Alloy TransformationsFrench-language works237,207