Wireless microfluidic control with integrated shape-memory-alloy actuators operated by field frequency modulation
Bibliographic record
Abstract
This paper reports wireless microfluidic control enabled by the selective operation of multiple bulk-micromachined shape-memory-alloy actuators using external radiofrequency magnetic fields. Each shape-memory-alloy actuator is driven by a wireless resonant heater which generates heat only when the field frequency is tuned to the resonant frequency of the heater. Multiple actuators coupled with the heater circuits that are designed to have different resonant frequencies in the range of 135–295 MHz are selectively and simultaneously controlled by modulating the field frequency to the resonant frequencies of the corresponding heaters. A wireless microsyringe device that has three actuator–heater components and a flexible parylene reservoir is developed. The 5 µl reservoir is squeezed by the 5 mm long cantilever-type actuators to eject controlled amount of liquid from the reservoir. Using the device with an acidic solution loaded in the reservoir, sequential modifications of the pH level in the liquid are experimentally demonstrated through the selective control of the three actuators. The thermal characterization of the actuator using infrared imaging shows a temperature increase of 50 °C in 4 s and the full activation of the actuator in 8 s with 300 mW field output power.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".