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Record W2024439516 · doi:10.1088/1757-899x/60/1/012036

Effect of interlayer configurations on joint formation in TLP bonding of Ti-6Al-4V to Mg-AZ31

2014· article· en· W2024439516 on OpenAlexafffund
Anas M. Atieh, Tahir I. Khan

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2014
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaGerman-Jordanian University
KeywordsMaterials scienceIntermetallicJoint (building)Scanning electron microscopeMicrostructureMetallurgyComposite materialShear strength (soil)Phase (matter)Layer (electronics)NickelShear (geology)AlloyStructural engineering

Abstract

fetched live from OpenAlex

In this research work, the transient liquid phase (TLP) bonding process was utilized to fabricate joints using thin (20μm) nickel and copper foils placed between two bonding surfaces to help facilitate joint formation. Two joint configurations were investigated, first, Ti-6Al-4V/CuNi/Mg-AZ31 and second, Ti-6Al-4V/NiCu/Mg-AZ3L The effect of bonding time on microstructural developments across the joint and the changes in mechanical properties were studied as a function of bonding temperature and pressure. The bonded specimens were examined by metallographic analysis, scanning electron microscopy (SEM), and X-ray diffraction (XRD). In both cases, intermetallic phase of CuMg 2 and Mg 3 AlNi 2 was observed inside the joint region. The results show that joint shear strengths for the Ti-6Al-4V/CuNi/Mg-AZ31 setup produce joints with shear strength of 57 MPa compared to 27MPa for joints made using the Ti-6Al-4V/NiCu/Mg-AZ31 layer arrangement.

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)0.001
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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0040.000

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 head0.014
GPT teacher head0.227
Teacher spread0.213 · 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
Published2014
Admission routes2
Has abstractyes

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Same venueIOP Conference Series Materials Science and EngineeringSame topicMagnesium Alloys: Properties and ApplicationsFrench-language works237,207