TEMPERATURE REGULATED NONLINEAR MICROVALVES FOR SELF-ADAPTIVE MEMS COOLING
Bibliographic record
Abstract
In this paper, thermal buckling of doubly clamped microfabricated nickel beams is implemented as a passive actuation mechanism to drive temperature-regulated nonlinear micro-valves for adaptive microcooling applications. The nonlinear buckling phenomenon is combined with the nonlinear change in flow rate through parallel plates with a variable spacing. The thermal buckling mechanism and parallel plate flow are modeled analytically, and nondimensional characteristic design curves have been generated. Passive flow-control microvalves were fabricated using deep reactive ion etching and a through-mold nickel electroplating process over a thin sacrificial layer. The model is validated with experimental results from the microfabricated temperature-regulated microvalves. Experimental characterization using an integrated micromachined heat exchanger with air as the working fluid shows the desired nonlinear valving behavior with mass flow rates of up to 5 mg/s for a temperature increase of 50degC, corresponding to 0.25 W of heat removal. It is shown that temperature-induced elastic instabilities in microfabricated structures can be modeled and manipulated to create a nonlinear adaptive valving mechanism. The modeling approach, microfabrication process, and full characterization of the microvalves are presented.
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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) | 0.001 | 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".