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Record W2498044997 · doi:10.1080/13621718.2016.1209625

Induction diffusion brazing of copper to aluminium

2016· article· en· W2498044997 on OpenAlexaff
X. G. Wang, Feng-Jie Yan, Xinghao Li, C. G. Wang

Bibliographic record

VenueScience and Technology of Welding & Joining · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsDalhousie University
FundersState Grid Corporation of China
KeywordsBrazingMaterials scienceAluminiumCopperIntermetallicMetallurgyWeldingDiffusion bondingJoint (building)Composite materialOxideUltimate tensile strengthDiffusionStructural engineering

Abstract

fetched live from OpenAlex

The aim of this research was to develop an induction diffusion brazing to obtain a sound joint between copper and aluminium. A foil interlayer was used to bond copper to aluminium at 600°C for 2 s under a bonding pressure of 9 MPa. The failure of tensile test is in the aluminium side and no failure occurs when the joint is bent to 180°. The electrical resistivity of joint is lower than that of aluminium. The interfacial intermetallic compounds layers are Cu 9 Al 4 and CuAl 2 with the total thickness of 2 μm. No voids and oxide scale are found in the joint. Heat treatment shows that induction diffusion brazing is superior to conventional flash welding to maintain electrical stability and mechanical integrity of copper to aluminium joint.

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 score0.001
Threshold uncertainty score0.005

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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.239
Teacher spread0.231 · 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

Citations26
Published2016
Admission routes1
Has abstractyes

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