Bibliographic record
Abstract
Micro-electromagnets hold great promise for integration into portable and handheld lab-on-a- chip systems applicable to point-of-care disease management. Two major requirements must be satisfied in order for such devices to be applicable into practical, miniaturized, and portable biomedical instrumentation: low power operation and low-cost fabrication. In this paper, we use numerical modeling combined with a lithography-free fabrication process to create micro-electromagnets on a polymer substrate. Numerical modeling reveals that active-passive devices—ferromagnetic layers coupled with current-controlled planar coils—are essential for generating a sufficient magnetic force for magnetic particle manipulation at low currents (<50 mA). In addition, it is shown that current carrying conductors created from micro/nanotextured materials further enhance the generated magnetic force at a given current. To combine low-cost fabrication with low-current operation, we developed a benchtop fabrication method based on craft cutting, polymer induced thin film wrinkling, and electrodeposition to create a multilevel arrangement of multi-scale materials essential for low-current operation. We demonstrate that the fabricated active-passive devices featuring wrinkled copper active layers and permalloy passive layers capture 2.8 μm magnetic particles upon the application of a 35 mA current.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.406 | 0.614 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".