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Record W2055700449 · doi:10.1115/icnmm2006-96148

Simulation and Analysis of Metal Microfluidic Heatsinks

2006· article· en· W2055700449 on OpenAlexaff
Alireza Motieifar, Cyrus Shafai, H.M. Soliman

Bibliographic record

VenueASME 4th International Conference on Nanochannels, Microchannels, and Minichannels, Parts A and B · 2006
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsHeat sinkMaterials scienceMicrofluidicsThermal resistanceSiliconCoolantWorking fluidSurface micromachiningHeat transferThermal conductivityFabricationComposite materialMechanical engineeringMechanicsOptoelectronicsNanotechnology

Abstract

fetched live from OpenAlex

Microfluidic heatsinks are usually fabricated in silicon substrates using micromachining methods. Fabrication of microfluidic heatsinks in metals is captivating due to the potential of higher heat conductance of many metals compared to silicon. In this work, metallic microfluidic structures fabricated of copper, silicon, and nickel are simulated and analyzed using the FEM method. The parametric dependence of the overall thermal resistance on the heatsink material, fluid velocity, and channel geometry is examined. Their performance is compared based on the shape and size of the microchannels, their separating distance from each other, and the flow rate. Simulations were done using FEMLAB v.3.2 (Comsol Multyphysics). The length of the microchannels considered is 1cm. Their cross section is rectangular. Simulated heatsinks are covered with 50 μm of the same material as the body and the total area of the heat sink is 1cm × 1cm. Water is used as the coolant with an input temperature of 300 K. These simulations show that most of the thermal resistance in the heatsink occurs in the fluid region. For the constant and uniform input heating power of 100 W/cm2 the performance of the structure is studied at steady state with the fluid velocity varied from 1 to 14m/s. Finally, experimental fabrication of an electroplated copper micro-channel system with rectangular channels is shown.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.026
GPT teacher head0.259
Teacher spread0.232 · 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 designSimulation or modeling
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

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueASME 4th International Conference on Nanochannels, Microchannels, and Minichannels, Parts A and BSame topicHeat Transfer and OptimizationFrench-language works237,207