Microfluidic active mixers employing ultra-high aspect-ratio rare-earth magnetic nano-composite polymer artificial cilia
Bibliographic record
Abstract
We present a new micromixer based on highly magnetic, flexible, high aspect-ratio, artificial cilia that are fabricated as individual micromixer elements or in arrays for improved mixing performance. These new cilia enable high efficiency, fast mixing in a microchamber, and are controlled by small electromagnetic fields. The artificial cilia are fabricated using a new micromolding process for nano-composite polymers. Cilia fibers with aspect-ratios as high as 8:0.13 demonstrate the fabrication technique's capability in creating ultra-high aspect-ratio microstructures. Cilia, which are realized in polydimethylsiloxane doped with rare-earth magnetic powder, are magnetized to produce permanent magnetic structures with bidirectional deflection capabilities, making them highly suitable as mixers controlled by electromagnetic fields. Due to the high magnetization level of the polarized nano-composite polymer, we are able to use miniature electromagnets providing relatively small magnetic fields of 1.1 to 7 mT to actuate the cilia microstructures over a very wide motion range. Mixing performances of a single cilium, as well as different arrays of multiple cilia ranging from 2 to 8 per reaction chamber, are characterized and compared with passive diffusion mixing performance. The mixer cilia are actuated at different amplitudes and frequencies to optimize mixing performance. We demonstrate that more than 85% of the total volume of the reaction chamber is fully mixed after 3.5 min using a single cilium mixer at 7 mT compared with only 20% of the total volume mixed with passive diffusion. The time to achieve over 85% mixing is further reduced to 70 s using an array of eight cilia microstructures. The novel microfabrication technique and use of rare-earth permanently-magnetizable nano-composite polymers in mixer applications has not been reported elsewhere by other researchers. We further demonstrate improved mixing over other cilia micromixers as enabled by the high aspect-ratio, high flexibility, and magnetic properties of our cilia micromixer elements.
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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 | 0.000 | 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".