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Record W2166830789 · doi:10.1109/tcapt.2008.2004773

PCB-Integrated Heat Exchanger for Cooling Electronics Using Microchannels Fabricated With the Direct-Write Method

2008· article· en· W2166830789 on OpenAlexaff
Ramzi Bey Oueslati, Daniel Therriault, Sylvain Martel

Bibliographic record

VenueIEEE Transactions on Components and Packaging Technologies · 2008
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsHeat exchangerElectronicsPrinted circuit boardFabricationMicrofluidicsElectronic componentMechanical engineeringMicro heat exchangerMaterials scienceHeat sinkThermal management of electronic devices and systemsElectronics coolingIntegrated circuitElectronic packagingPlate fin heat exchangerHeat transferNanotechnologyEngineeringElectrical engineeringOptoelectronicsPlate heat exchangerMechanicsComposite material

Abstract

fetched live from OpenAlex

The electronic industry has a growing need for efficient heat dissipation mechanisms such as micro heat exchanger systems. This active cooling approach requires the integration of microfluidic components near the main heat sources of the electronic devices. Despite the investigation of several micro-cooling configurations, their commercial utilization by the electronic industry is rather limited due to complex fabrication and integration methods. Here, we present the integration of cylindrical microchannels fabricated by direct-write assembly in printed circuit board layouts for a micro heat exchanger application. The thermal performance of the manufactured prototype was characterized with respect to the fluid flow rate. The original fabrication and integration approaches presented here show high potential for efficient, compact, and low-cost micro heat exchangers for the electronic industry.

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)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.242
Teacher spread0.211 · 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

Citations36
Published2008
Admission routes1
Has abstractyes

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