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Record W2370023764

Low temperature sintering-bonding through in-situ formation of Ag nanoparticles using micro-scaled Ag_2O composite paste

2013· article· en· W2370023764 on OpenAlexaff
Fengwen Mu, Guisheng Zou, Zhenyu Zhao, Aiping Wu, Jiuchun Yan, Y. Zhou

Bibliographic record

VenueTransactions of the China Welding Institution · 2013
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSinteringMaterials scienceNanoparticleMicrostructureComposite numberComposite materialShear strength (soil)Particle (ecology)Nanotechnology
DOInot available

Abstract

fetched live from OpenAlex

In order to reduce the cost of using Ag nanoparticle paste as bonding materials in electronic packaging, micro-scaled Ag2O powders were mixed with triethylene glycol (TEG) to form a paste to replace the Ag particle paste. The reaction mechanism of in-situ formation of Ag nanoparticles, the sintering characteristics of micro-Ag2O paste at low temperature, and the bonding of Ag-coated Cu bulks using this paste were investigated. The results reveal that the Ag2O particles in the paste were more easily transformed into Ag nanoparticles than microAg2O itself, and with increasing the sintering temperature, more Ag nanoparticles formed and grew larger by sintering, accompanied with some gaseous products which could escape easily. The effect of sintering-bonding time on the strength of joints fabricated at 250 ℃ under a pressure of 2 MPa was analyzed. The average shear strength of the joints increased with sintering-bonding time and reached about 24 MPa when the sintering-bonding time was 5 min. And the microstructure of the fractured surface and the crosssection of typical joints made at 250 ℃ under 2 MPa were also examined.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.249
Threshold uncertainty score0.473

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 communication0.0000.001
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 head0.010
GPT teacher head0.214
Teacher spread0.204 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

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