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Record W2149603305 · doi:10.1115/ipack2007-33026

Thermal Conductivity and Contact Resistance Measurements for Adhesives

2007· article· en· W2149603305 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

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsThermal conductivityMaterials scienceAdhesiveComposite materialThermal contact conductanceThermal resistanceContact resistanceThermal contactThermal conductivity measurementCeramicThermal conductionInterfacial thermal resistanceThermal

Abstract

fetched live from OpenAlex

Thermal adhesives that contain large concentrations of high thermal conductivity filler materials, such as ceramics or metals, are widely used by the electronics industries in a variety of applications. The thermal properties of these materials, such as the thermal contact resistance across a bonded joint and the thermal conductivity of the bulk material, are critical to the selection of the “best” material. A method is presented for the measurement of these thermal properties using a steady-state, guarded heat flux meter test apparatus based on the well-documented and familiar ASTM test standard D-5470. Five different adhesive materials are tested and a linear fit of the resulting resistance versus thickness data are used to determine the bulk thermal conductivity and contact resistance values. Four of the five materials tested had conductivity values of less than 1 W/mK, and the data demonstrates that a small but significant thermal contact resistance exists between the adhesive and the substrate for each of the adhesives.

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)0.002
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 score0.010
Threshold uncertainty score0.804

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.076
GPT teacher head0.285
Teacher spread0.209 · 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

Quick stats

Citations43
Published2007
Admission routes1
Has abstractyes

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