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THERMAL MANAGEMENT OF HIGH-HEAT-FLUX DEVICES EDIFICE: EMBEDDED DROPLET IMPINGEMENT FOR INTEGRATED COOLING OF ELECTRONICS

2000· article· en· W2174628321 on OpenAlexaff
Cristina H. Amon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHeat fluxMaterials scienceElectronicsComputer coolingCoolantElectronics coolingMechanical engineeringMicroelectromechanical systemsRadiative coolingJet (fluid)Heat pipeLatent heatActive coolingHeat sinkHeat transferOptoelectronicsAerospace engineeringWater coolingThermal management of electronic devices and systemsMechanicsElectrical engineeringEngineeringThermodynamicsPhysics

Abstract

fetched live from OpenAlex

This presentation will first explore recent research developments for thermal management of high-heat-flux devices. These include detachable heat storage units, jet impingement, droplets and sprays, and phase-change cooling, heat pipes, capillary- and gravity-pumped loops. Micro-manufacturing and MEMS (Micro Electro-Mechanical Systems) will be discussed as enabling technologies for some innovative cooling schemes recently proposed. In the second part of the presentation, the development of EDIFICE: Embedded Droplet Impingement For Integrated Cooling of Electronics will be discussed. The EDIFICE project seeks to develop an integrated droplet impingement cooling device for removing chip heat fluxes in the range 70-100 W/cm2, employing latent heat of vaporization of dielectric fluids (50-100 micron droplets) to achieve these high heat removal rates. A novel feature to enable adaptive on-demand cooling is MEMS sensing (on-chip temperature, remote IR temperature and ultrasonic dielectric film thickness) and MEMS actuation. EDIFICE will be integrated within the electronics package and fabricated using advanced micro-manufacturing technologies (e.g., deep RIE and CMOS CMU-MEMS). The development of EDIFICE involves modeling, CFD simulations, and physical experimentation on test beds. This presentation will then examine jet impingement cooling of EDIFICE with a dielectric coolant and the influence of several parameters such as impinging jet diameter, jet velocity, and latent heat effects.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.283
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 science0.0000.000
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 head0.008
GPT teacher head0.221
Teacher spread0.213 · 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 teacher head, not a consensus.

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

Citations5
Published2000
Admission routes1
Has abstractyes

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