A Comprehensive Study of Silicon Micropillar Based Biporous Evaporator
Bibliographic record
Abstract
Silicon micropillar based evaporators were proven to be good candidates in advanced vapor chambers, due to their high permeability, excellent capillary performance and ease of control over the fabrication process.In this paper, biporous silicon micropillar based evaporator with microchannels to shorten the fluid transportation distance was studied comprehensively.Semianalytical model in predicting the dryout heat flux of biporous evaporator was developed.Evaporator samples with different microchannel widths were fabricated and tested.Sample with geometries of d = 3.4 μm, h = 9.00 μm, l=6 μm, l i =101.0 μm, w = 58.5 μm was able to demonstrate a dryout heat flux q''= 55.9 W/cm 2. This has a difference of only 9.0 % compared to the model predicted dryout heat flux.The biporous evaporator was found to have a gentle drop of heat transfer coefficient after dryout, owing to the existence of microchannels that can shorten the fluid propagation distance.Samples with wider microchannels were found to have larger superheat values, due to the smaller thin film evaporation areas of these sample.This paper provided great insights into the investigation of biporous evaporators and can serve as important design guidance for biporous evaporator utilized in advanced vapor chamber.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".