Lab on a rod: Size-based particle separation and sorting in a helical channel
Bibliographic record
Abstract
<p>Size-based particle separation using inertial microfluidics in spiral channels has been well studied over the past decade. Though these devices can effectively separate particles, they require a relatively large device footprint with a typical outer channel radius of approximately 15 mm. In this paper, we describe a microfluidic device with a footprint diameter of 5.5 mm, containing a helical channel capable of inertial particle separation fabricated using abrasive jet micromachining. The separation of particles in several channel geometries was studied using wide-field fluorescence microscopy. A maximum separation efficiency of approximately 90% was achieved at a flow rate of 1.5 ml/min with a purity of approximately 95% at the outlet, where large particles were collected. An accompanying computational fluid dynamics model was developed to allow researchers to quickly assess the separation capability of their helical or spiral devices.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".