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Record W2071084951 · doi:10.1063/1.1914954

Electrical performance of contaminated rough surfaces in contact

2005· article· en· W2071084951 on OpenAlexaff
Lior Kogut

Bibliographic record

VenueJournal of Applied Physics · 2005
Typearticle
Languageen
FieldEngineering
TopicElectrical Contact Performance and Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsMaterials scienceElectrical contactsContact resistanceElectrical resistance and conductanceComposite materialQuantum tunnellingAsperity (geotechnical engineering)Electrical resistivity and conductivityElectrical conductorContact areaMetalThin filmOptoelectronicsNanotechnologyMetallurgyElectrical engineeringLayer (electronics)

Abstract

fetched live from OpenAlex

The inevitable presence of thin insulating films at the contact interface of electrical contacts has an adverse effect on their performances. An attempt is made to study the electrical performance of degraded electrical contacts where insulating films reside at the contact interface of conductive rough surfaces. The degradation mechanism is based on gradual growth of an insulating film and the characteristics of the insulating film are assumed to be known without considering details regarding the physical and chemical origins of the growth mechanisms. The present study relies on recently developed theories for electrical contact resistance of clean and fully contaminated rough surfaces, thus bridging the gap between these two extreme cases. For thick insulating films no current flow occurs across contaminated asperity contacts, whereas for thin insulating films tunneling currents are taken into account. A relationship is obtained between the degraded electrical contact resistance and the metallic conductance area. The effect of tunneling currents on the performance of partially contaminated surfaces is negligible due to the considerable current flow across the metallic asperity contacts. The electrical performance of fully contaminated surfaces is sensitive to the thickness and integrity of the insulating films and, therefore, can be exploited to study the durability of thin insulating films.

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)0.002
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.202
Teacher spread0.196 · 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

Citations38
Published2005
Admission routes1
Has abstractyes

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