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Record W1972394143 · doi:10.1007/s11664-014-3478-6

Nanocopper Based Solder-Free Electronic Assembly

2014· article· en· W1972394143 on OpenAlexaff
K. Schnabl, Luke Wentlent, K. Mootoo, S. Khasawneh, Alfred A. Zinn, J. Beddow, E. Hauptfleisch, D. Blass, Peter Børgesen

Bibliographic record

VenueJournal of Electronic Materials · 2014
Typearticle
Languageen
FieldMaterials Science
TopicNanoporous metals and alloys
Canadian institutionsLockheed Martin (Canada)
FundersIntegrated Electronics Engineering Center, Binghamton UniversityBinghamton University
KeywordsSolderingSolder pasteMaterials scienceCopperPrinted circuit boardSurface-mount technologyScanning electron microscopeElectronicsComposite materialElectronic packagingPorosityReliability (semiconductor)Drop testNanocrystalline materialMetallurgyOptoelectronicsNanotechnologyElectrical engineeringStructural engineering

Abstract

fetched live from OpenAlex

CuantumFuse nano copper material has been used to assemble functional LED test boards and a small camera board with a 48 pad CMOS sensor quad-flat no-lead chip and a 10 in flexible electronics demo. Drop-in replacement of solder, by use of stencil printing and standard surface mount technology equipment, has been demonstrated. Applications in space and commercial systems are currently under consideration. The stable copper-nanoparticle paste has been examined and characterized by scanning electron microscopy and high-resolution transmission electron microscopy; this has shown that the joints are nanocrystalline but with substantial porosity. Assessment of reliability is expected to be complicated by this and by the effects of thermal and strain-enhanced coarsening of pores. Strength, creep, and fatigue properties were measured and results are discussed with reference to our understanding of solder reliability to assess the potential of this nano-copper based solder alternative.

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 score0.002
Threshold uncertainty score0.008

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.221
Teacher spread0.215 · 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

Citations33
Published2014
Admission routes1
Has abstractyes

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