A novel AC electrothermal micropump for biofluid transport using circular interdigitated microelectrode array
Bibliographic record
Abstract
Electrokinetic micropumps have been widely used in lab-on-a-chip devices. The AC electrothermal (ACET) effect is highly efficient for biofluidic micropumping, but is unable to generate high flow rates. Attempts to increase ACET flows, such as applying a wide range of actuation voltages, using asymmetric microelectrode arrays and using 3D microelectrodes have been reported. In this paper a novel idea of employing circular coplanar asymmetric microelectrodes placed on the perimeter of a microchannel is explored. An array of microelectrodes is simulated using COMSOL Multiphysics software. The micropump output shows relatively high flow rates compared to other ACET micropumps which have the same electrode dimensions. Moreover, the idea of using different micropumps with scaled dimensions is investigated. The results show that a highly efficient ACET micropump can be achieved if an appropriate electrode size-to-channel dimension ratio is selected. The results also show that a micropump with a scale of 0.2 can show negligible flow rate, but if the electrodes are used in a micropump with the scale of 1, a flow rate of 15 ×106 μm3/s can be generated. This new ACET pump design can be utilized for lab-on-a-chip applications, specifically in biofluid delivery systems.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".