Planar Microcoil Array Based Temperature-Controllable Lab-on-Chip Platform
Bibliographic record
Abstract
In this paper, we present the design and implementation of a planar microcoil array based temperature-controllable Lab-on-chip (LoC) platform for magnetic bead manipulation. Magnetic beads are used as the solid phase carriers of bioparticles and microcoil array acts as the scattered magnetic field source to manipulate the magnetic beads in microfluidics. Meanwhile, the Joule heat issue, which is inevitable and often considered a drawback of electromagnetic LoC applications, is analyzed and proved to be controllable using our proposed current supply method. With this method, microcoil can be used as a heat source to keep the temperature of microfluidic within the safe range for bioparticles, saving the external incubator. To verify the concept, a polyimide substrate LoC platform was fabricated and tested. Taking advantage of the commercially available process, it is standard and mass-producible. Experimental results show that both individual single bead and mass beads varying from 1$\mu{\rm m}$to 2$\mu{\rm m}$can be manipulated with acceptable current consumption, while temperature can be maintained in a safe range.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".