Electrohydrodynamic Injection Micropump With Composite Gold and Single-Walled Carbon Nanotube Electrodes
Bibliographic record
Abstract
The presence of microfeatures/nanofeatures with sharp asperities on the emitter electrodes of ion drag electrohydrodynamic (EHD) micropumps is likely to enhance the local electric field and charge injection significantly, and thus the pressure generation and flow rates. The objective of this paper is to investigate the performance of EHD micropumps with single-walled carbon nanotubes (SWCNT) on the emitter electrodes. The micropumps had 100 pairs of planar electrodes where the width of the emitter and collector electrodes was 20 and 40 μm, respectively, with a cross-sectional domain of 100 μm × 5 mm. Two micropumps with interelectrode spacing of 120 and 40 μm were tested with a smooth emitter surface, and where SWCNT were electrophoretically deposited on the emitter electrodes using HFE7100 as the working fluid. The threshold voltage for charge injection lowered by a factor of 3 and 1.4 for the two pumps with SWCNT on the emitter electrodes compared with the smooth electrode case. The corresponding static pressure head increased by a factor 5, while the flow rate at no external back pressure increased by a factor 3 for the pump with interelectrode spacing of 120 μm. For the pump with interelectrode spacing of 40 μm, a maximum static pressure of 4.7 kPa was achieved at 900 V with SWCNT on the emitter electrode.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".