Experimental characterization of a hybrid impinging microjet-microchannel heat sink fabricated using high-volume metal additive manufacturing
Bibliographic record
Abstract
A high-performance water-cooled micro heat sink for the thermal management of high heat flux microelectronics was designed, fabricated, and tested. The heat sink design leverages a multi- metal electrodeposition additive manufacturing process to produce complex flow which are impossible to fabricate with traditional processes. A previous study employed simulation-driven design to develop and optimize micro heat sinks and is a hybrid of microchannels with an array of integrated microjets. In the present investigation, a prototype heat sink was fabricated and tested at heat fluxes up to and exceeding 1000 W/cm2. The results demonstrate reasonable agreement between the numerical predictions and experimental results, considering the complex geometry flow and conjugate heat transfer within the device. From a thermal–hydraulic performance standpoint, the heat exchanger achieved an estimated overall thermal conductance of ~330 kW/m2K with a pressure drop of 160 kPa (23 psi) for a flow rate of 0.5 L/min. For inlet water at 20 °C, this corresponded to a measured base temperature of 54 °C at an applied heat flux of 1000 W/cm2. The hybrid microchannel–microjet heat sink further exhibited an enhancement ratio of 6 when compared with a microchannel heat exchanger of commensurate design. To the extent of our knowledge, this microfluidic heat exchanger has achieved one of the highest effective thermal conductance levels reported in the literature and has done so at moderate pressure drop and flow rate.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".