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Record W2495756689 · doi:10.1080/13621718.2016.1211583

Bonding mechanism and interface characterisation during dissimilar friction stir welding of an aluminium/polymer bi-material joint

2016· article· en· W2495756689 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.

Bibliographic record

VenueScience and Technology of Welding & Joining · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsUniversity of WaterlooNatural Resources Canada
Fundersnot available
KeywordsMaterials scienceFriction stir weldingWeldingJoint (building)AluminiumMechanism (biology)MetallurgyComposite materialFriction weldingInterface (matter)PolymerStructural engineeringWetting

Abstract

fetched live from OpenAlex

In the present study, detailed microstructural characterisation of a friction-stir-welded joint between AA5059 alloy and high-density polyethylene was carried out using field-emission scanning and high-resolution-transmission electron microscopy analysis. The structural features indicate large numbers of macro-, micro- and nano-mechanical interlocks between the Al-fragments and melted/re-solidified polymer matrix at the stir zone of the joint, with a 30-nm thick semi-crystalline aluminium structure layer elevated in levels of O, and traces of C at the interface. An ultrafine-grained structure with an average cell size of <100 nm was formed for the embedded Al-alloy fragments in the polymer matrix, as a result of low-temperature severe plastic deformation during friction-stir welding process. The interfacial chemical reactions assisted by generation of nano-scale pores inside the metal surface at the interface and secondary Van der Waals bonding are suggested as the main joining mechanisms, leading to significant improvements in the mechanical properties.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.231
Teacher spread0.223 · 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