Pool Boiling Experiment of Dielectric Liquids and Numerical Study for Cooling a Microprocessor
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Two-phase liquid immersion cooling has not yet reached its full potential because of two technological issues. The first issue is the boiling crisis and the second is the reliability risk caused by the immersed components, which are designed to work in air cooling applications. Experimental and numerical studies were performed to find the heat transfer limits of immersion cooling of microprocessor and new heat transfer design parameters are proposed. Pool boiling experiments were performed on bare copper surfaces for two dielectric fluids, Novec 649 and Novec 7100, and the critical heat fluxes were found to be 19.5 W/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and 23.8 W/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , respectively. Three-dimensional conduction models of a microprocessor were built to predict the junction temperature and junction-to-ambient thermal resistance. Effect of the integrated heatsink (IHS) thickness at different heat transfer coefficients have been investigated and the optimal thickness for the IHS is predicted to be around 4 mm while the heat transfer coefficient is less than 20 000 W/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> K on the IHS. Boiling directly on the silicon die has been studied, in order to examine the effect of a decreased thermal resistance by removing the thermal interface material and IHS. In this case, the heat transfer coefficient is predicted to be more than 20 000 W/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> K and to have better heat dissipation.
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.
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 it