Thermo-Fluids Considerations in the Development of a Silicon-based Micro-scale Direct Methanol Fuel Cell
Bibliographic record
Abstract
A silicon-based micro-scale Direct Methanol Fuel Cell (DMFC) system is under development at Carnegie Mellon University, as a substitute for lithium-ion batteries to power hand-held electronic devices. The DMFC is simple in design, operational in any orientation and environmentally benign. The air flow and the methanol circulation are both at a natural convection draft, while a passive gas bubble separator removes CO2 from the methanol chamber. The design and operation of the passive gas separator system, which has been successfully fabricated and tested, is described. Micro-scale Direct Methanol Fuel Cells have great potential for early applications in portable electronics due to their higher tolerance of power cost. However, challenges in system integration have to be overcome. A major issue is the development of micro-fluidics, which includes the micro pump for anode liquid re-circulation and for recycling the excess water from the cathode back to the anode, as well as the passive CO2 gas bubble separation from the anode side liquids. In addition, the seamless integration of various micro-fluidic components and the electronic control system has been an essential concern for system reliability and cost reduction. The DMFC is designed using MEMS technology. To achieve high energy density, the excess water at the cathode is collected and pumped back to the anode. This micro fuel cell contains several unique features. A silicon wafer with an array of etched holes selectively coated with a non-wetting agent is used at the cathode to collect the water effectively. A silicon membrane micro pump is developed for pumping the collected water back to the anode. Finally, a passive micro-scale CO2 bubble separator is developed to remove the gas bubbles from the anode stream. All of these silicon-based components are fabricated with a set of common processes on the same silicon wafer, such that interconnections are eliminated and fabrication cost is minimized. The resulting micro-scale fuel cell has an energy density four times larger than that of current lithium-ion batteries.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".