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Record W4292507974 · doi:10.1016/s1003-6326(22)65938-7

Base material location dependence of corrosion response in friction-stir-welded dissimilar 2024-to-5083 aluminum alloy joints

2022· article· en· W4292507974 on OpenAlexaff
Pengliang Niu, Wen-ya LI, Yuhua Chen, Qipeng Liu, Dao-lun CHEN

Bibliographic record

VenueTransactions of Nonferrous Metals Society of China · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMaterials scienceMetallurgyElectron backscatter diffractionAlloyCorrosionIntergranular corrosionUltimate tensile strengthScanning electron microscopeFriction stir weldingWelding6111 aluminium alloyComposite materialMicrostructure

Abstract

fetched live from OpenAlex

The effects of the base material (BM) location on the mechanical properties and the exfoliation corrosion performance of friction-stir-welded (FSWed) dissimilar 2024-to-5083 aluminum alloy joints were investigated. Scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), transmission electron microscopy (TEM), tensile tests and electrochemical experiments were conducted. The results revealed that the BM location had little effect on the tensile properties of the joints. The grain orientation spread (GOS) value of 2024 alloy side was lower than that of 5083 alloy side. Intergranular corrosion occurred mainly on the 2024 alloy side, while the grain interior of the 5083 alloy side was corroded due to the higher GOS value and dislocation density. The FSWed dissimilar joints with a superior exfoliation corrosion resistance could be achieved when the 5083 aluminum alloy with better corrosion performance was positioned on the retreating side.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.249
Teacher spread0.235 · 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

Citations15
Published2022
Admission routes1
Has abstractyes

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