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Record W1986794465 · doi:10.1109/tcpmt.2015.2419981

A Study on Measuring Contact Resistance of Ball Bonds on Thin Metallization

2015· article· en· W1986794465 on OpenAlexafffund
Ari Laor, Parker J. Herrell, M. Mayer

Bibliographic record

VenueIEEE Transactions on Components Packaging and Manufacturing Technology · 2015
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceContact resistanceComposite materialBall (mathematics)Sheet resistanceVoltage dropThin filmDrop (telecommunication)Current (fluid)Electrical engineeringNanotechnologyGeometryLayer (electronics)

Abstract

fetched live from OpenAlex

Contact resistance measurement configurations for the evaluation of ball bond reliability on thin metallizations are studied. Samples with symmetrical and asymmetrical four-wire probe configurations are analyzed and compared with a calibrated finite-element model. It is found that the measured contact resistance strongly depends on the geometric placement of the probe wires, and the value closest to the true value is obtained from a probe placement that is opposite and away from high-current-density regions on the metallization. Probes should also be placed as close as possible to the contact interface. Sheet resistance components contributed by intermediate thin metallizations are of the same order of magnitude as the unaged reported RC. Therefore, they are considered. Symmetrical current distributions yield a more homogeneous potential drop across the bond interface being probed, but also capture a larger component of metallization sheet resistance. Experimental samples were aged, and the contact resistance increase was measured. The impacts of various probe placements on the sensed RC were studied.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.039
GPT teacher head0.241
Teacher spread0.202 · 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

Citations21
Published2015
Admission routes2
Has abstractyes

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