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Record W2363569720

Recent progress in microjoining and nanojoining

2011· article· en· W2363569720 on OpenAlexaff
Guisheng Zou, Jianfeng Yan, Fengwen Mu, Aiping Wu, Y. Zhou

Bibliographic record

VenueTransactions of the China Welding Institution · 2011
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBrazingMaterials scienceWeldingCold weldingDiffusion bondingSinteringPressingFabricationWire bondingElectronic packagingNanotechnologyMetallic bondingMetallurgyComposite materialLaser beam weldingMetalGas metal arc weldingAlloyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Micro-joining and nano-joining have been identified as the key technologies in the construct fabrication such as micro-and nano-mechanical,electronic and medical devices and systems,and their recent progresses are briefly reviewed in this article.For electronic packaging applications,the developed lead-free solders and the two-step loading procedure accompanied with a superimposed ultrasound for copper-wire-bonding were expounded.Typical joining methods including resistance micro-welding,laser micro-welding and brazing for similar and dissimilar wires or pieces used for medical devices were discussed,as well as one-step diffusion bonding with pressing at high temperature for Bi-Sr-Ca-Cu-O superconductive leads.Joining technologies were also introduced,including electron beam irradiating welding,strand wrapping bonding with Double-walled Carbon Nanotube Strands(DWNT) film and brazing,the welding technologies of metal nanoparticles realized through laser irradiation,and the novel process of low-temperature sintering bonding by using Ag,Cu,Ag-Cu and Ag2O micro/nano-particle pastes for electronic packaging applications.Based on the existing and new processes,the challenges and outlooks in micro-and nano-joining were pointed out.

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)0.000
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 score0.773
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

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 science0.0000.000
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 head0.019
GPT teacher head0.211
Teacher spread0.192 · 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

Citations3
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the China Welding InstitutionSame topicElectronic Packaging and Soldering TechnologiesFrench-language works237,207