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Record W2145413915 · doi:10.1039/c1jm12108a

Preparation of PVP coated Cu NPs and the application for low-temperature bonding

2011· article· en· W2145413915 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Materials Chemistry · 2011
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsUniversity of Waterloo
FundersTsinghua Initiative Scientific Research ProgramTsinghua UniversityNational Natural Science Foundation of China
KeywordsPolyvinylpyrrolidoneMaterials scienceSinteringNanoparticleChemical engineeringCoatingElectrical resistivity and conductivityMetalCopperMetallic bondingInterconnectionDirect bondingMetallurgyNanotechnologyComposite materialSiliconPolymer chemistry

Abstract

fetched live from OpenAlex

There is an increasing interest in developing a low temperature interconnection process using nanoparticles. Some studies focus on bonding using Ag nanoparticles (Ag NPs). However, few studies investigate a bonding process using Cu nanoparticles (Cu NPs) due to the easy oxidation in air. Here we achieve a robust bonding of Cu wires to Cu pads with polyvinylpyrrolidone (PVP) coated Cu NPs at a low temperature of 170 °C. The PVP coating can effectively prevent the oxidation of Cu NPs when heated in air. The bonding is formed through the sintering of Cu NPs and direct metallic bonding between the sintered Cu particles and Cu pads. Electrical measurements of the Cu NPs demonstrate that Cu NPs have a low resistivity of 8.6 × 10−5 Ω cm after being sintered under pressure. This method has the potential to be used in the electrical packaging industry due to its economic cost, easy operation, and high conductivity.

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.

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 score0.001
Threshold uncertainty score0.170

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 head0.008
GPT teacher head0.231
Teacher spread0.222 · 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