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Record W4402438649 · doi:10.11159/mmme24.129

Green Channel Effect of Cu Nanotwin Enhanced Silver Sintered Die Bonding to Produce SiC Power Modules with Low Porosity and High Strength

2024· article· en· W4402438649 on OpenAlexvenueno aff
Tung‐Han Chuang, Yen‐Ting Chen, Devi Indrawati Syafei, Yin-Hsuan Chen, S. Y. Chang, James Chen

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsnot available
FundersHsinchu Science Park Bureau, Ministry of Science and Technology, TaiwanNational Taiwan University
KeywordsPorosityMaterials scienceDie (integrated circuit)Channel (broadcasting)Power (physics)Bonding strengthComposite materialMetallurgyElectrical engineeringNanotechnologyEngineering

Abstract

fetched live from OpenAlex

Silver sintered die bonding of SiC/Cr/nt-Cu chips with DBC ceramic substrates at 250 °C for 60 min with a pressure of 15 MPa achieved significantly reduction of porosity from 12.6 % to 4.4 % and increase of bonding strength from 24.3 MPa to 42.8 MPa under identical conditions in comparison to that of conventional SiC/Cr/coarse grained Cu metallized SiC chips.The sputtered nanotwinned Cu thin film possessed a high density (111) orientation of 91.2%, in contrast to a low proportion about 20% for the conventional coarse-grained Cu film.Interfacial cross-sectional analyses and fractography after shear tests reveal the beneficial effects of highly (111)-oriented nanotwinned Cu structure on Ag sintered die bonding, reducing delamination between interfaces compared to conventional Cu grain structures.

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 score0.004

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.175
Teacher spread0.172 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueProceedings of the World Congress on Mechanical, Chemical, and Material EngineeringSame topicAluminum Alloys Composites PropertiesFrench-language works237,207