Flow Boiling Heat Transfer in a Silicon Microchannel Heat Sink Using Liquid Crystal Thermography
Bibliographic record
Abstract
The present study focuses on the experimental investigation of boiling heat transfer characteristics and pressure drop in a silicon microchannel heat sink. The microchannel heat sink consists of a rectangular silicon chip in which 45 rectangular microchannels were chemically etched with a depth of 295 μm, width of 254 μm, and a length of 16 mm. Un-encapsulated Thermochromic liquid Crystals (TLC) are used in the present work to enable nonintrusive and high spatial resolution temperature measurements. This measuring technique is used to provide accurate full and local surface-temperature and heat transfer coefficient measurements. Experiments are carried out for mass velocities ranging between 290 to 457 kg/m2.s and heat fluxes from 6.04 to 13.06 W/cm2 using FC-72 as the working fluid. Experimental results show that the pressure drop increases as the exit quality and the flow rate increase. High values of heat transfer coefficient can be obtained at low exit quality (xe < 0.2). However, the heat transfer coefficient decreases sharply and remains almost constant as the quality increases for an exit quality higher than 0.2.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".