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Record W2016118684 · doi:10.1179/174327808x310024

Erosion–corrosion of aluminium alloys in ethylene glycol–water solutions in absence and presence of sand particles

2008· article· en· W2016118684 on OpenAlexaff
Lin Niu, Y. Frank Cheng

Bibliographic record

VenueCorrosion Engineering Science and Technology The International Journal of Corrosion Processes and Corrosion Control · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicErosion and Abrasive Machining
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMaterials scienceCorrosionErosion corrosionEthylene glycolAluminiumDielectric spectroscopyMetallurgyCoolantErosionElectrodeOxideElectrochemistryComposite materialChemical engineeringChemistry

Abstract

fetched live from OpenAlex

The erosion–corrosion of aluminium alloys in ethylene glycol–water solutions that simulated the automotive coolant was studied by a rotating cylinder electrode (RCE) through the measurements of potentiodynamic polarisation curves, electrochemical impedance spectroscopy and weight loss. In the absence of sand particles, the turbulent flow developed on RCE produces weakening effects and damage to the oxide film on the Al electrode, which becomes more active with the increasing fluid flow, as indicated by the negative shift of corrosion potential and the decreasing film resistance. In the presence of sand particles, both the turbulent flow of solution and the mechanical impingement of sand particles contribute to the weakening and damage to the oxide film. However, the interfacial reaction mechanism is not changed upon the sand addition. In the ethylene glycol–water–sand solution, weight loss of Al alloys is mainly due to the contribution of the mechanical erosion of sand particles. The corrosion induced weight loss is negligible.

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)0.001
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 score0.050
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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

Citations7
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueCorrosion Engineering Science and Technology The International Journal of Corrosion Processes and Corrosion ControlSame topicErosion and Abrasive MachiningFrench-language works237,207