Utilizing a coil to realize 3D electrodes for dielectrophoresis-based particle concentration
Bibliographic record
Abstract
Abstract In this paper a novel technique is presented to fabricate a coil of insulated and uninsulated wires placed in a polydimethylsiloxane (PDMS) channel. The design introduces 3D dielectrophoresis-based particle concentration using a coil for the first time. The wires were wound around a 3D printed acrylonitrile butadiene styrene (ABS) rod and embedded in the PDMS. The ABS then dissolved in acetone to create the channel surrounded by wires. Electric field is attained by applying 180° phase-shifted electric potentials to the uninsulated wires, acting as electrodes. Hence, the insulated wires only serve as insulators between the electrodes to prevent them from electrical shorting. This configuration produces a gradient in the electric field with its maximum near the channel walls (electrodes) and its minimum at the centre of the channel. Thus, under proper electric field frequency, negative dielectrophoresis force focuses particles by pushing them to the central area of the channel while the fluid flow carries them to the outlet. Proof-of-concept simulations and experiments were conducted. Polystyrene particles, with a diameter of 6 µ m, were used in the experiments. To find the concentration performance under different conditions, the variations in the frequency and amplitude of the electric potential and the flow rate of the solution were examined. The results confirmed the capability of the coil to efficiently focus the polystyrene particles under optimum conditions. A comprehensive set of COMSOL simulations demonstrate the underlying principles. In addition, polystyrene particles with diameters of 6 µ m and 15 µ m were simulated under different conditions. Under the same conditions, the larger particles can be focused more efficient than the smaller particles.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".