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Miniature Liquid Cold-plate Enabled by Metal Spraying: A Thermal Management Solution for a Modular 1 kW Bi-directional GaN-based dc-ac Converter

2022· article· en· W4280516595 on OpenAlexafffund
Omri Tayyara, Joshua Palumbo, Nameer Khan, Miad Nasr, Carlos Da Silva, S. Chandra, Olivier Trescases, Cristina H. Amon

Bibliographic record

Venue2022 IEEE Applied Power Electronics Conference and Exposition (APEC) · 2022
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceThermal conductivityComposite materialThermalThermal management of electronic devices and systemsLiquid metalOptoelectronicsCopperJunction temperatureElectrical engineeringMechanical engineeringMetallurgyEngineering

Abstract

fetched live from OpenAlex

In recent years, power electronic systems have been consistently required to achieve higher power while also minimizing footprint. Addressing these demands has produced new electro-thermal challenges within these highly coupled systems. This work utilizes metal spraying techniques to fabricate a custom miniature liquid cold-plate to cool a 1 kW high-frequency bi-directional GaN-based dc-ac converter. A commercially sourced ‘off-the-shelf’ cold-plate, comprised of a serpentine copper tube embedded in an aluminum block and buried in low thermal conductivity epoxy is used as a baseline to compare the thermal performance of the proposed cold-plate. Experimental results show that the metal sprayed cold-plate yields lower junction temperatures at the same flow rate while also decreasing volume and mass when compared to the off-the-shelf system.

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 categoriesMeta-epidemiology (narrow)
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 score0.094
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.195
Teacher spread0.187 · 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

Citations8
Published2022
Admission routes2
Has abstractyes

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