Variable Pumping Control for Low Power Microfluidic Chip Cooling
Bibliographic record
Abstract
As microelectronic modules increase in power density, liquid cooling has become increasingly required to maintain acceptable chip temperatures. Liquid cooling in microchannels offers low thermal resistance and can be integrated into modules given their small size and implementation by microfabrication methods [1]. Microchannel cooling is therefore particularly well suited for embedded or portable applications. Their performance and compact form factor come, however, to the cost of increased pressure drop compared to larger scale cold plates. Since energy is limited in portable applications, power consumption by the cooling system (product of pressure drop and flow rate) should be minimized. This can be done by reducing the pressure drop with optimal design [2] or by distributing the flow in parallel microchannels or cell arrays [3], [4]. This work focuses on reducing the flow rate by adapting the pumping conditions to only provide the minimal flow rate required to maintain the maximum chip temperature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".