Inertial particle separation in helical channels: A calibrated numerical analysis
Bibliographic record
Abstract
Inertial microfluidics has been used in recent years to separate particles by size, with most efforts focusing on spiral channels with rectangular cross sections. Typically, particles of different sizes have been separated by ensuring that they occupy different equilibrium positions near the inner wall. Trapezoidal cross sections have been shown to improve separation efficiency by entraining one size of particles in Dean vortices near the outer wall and inertially focusing larger particles near the inner wall. Recently, this principle was applied to a helical channel to develop a small-footprint microfluidic device for size-based particle separation and sorting. Despite the promise of these helical devices, the effects of channel geometry and other process parameters on separation efficiency remain unexplored. In this paper, a simplified numerical model was used to estimate the effect of various geometric parameters such as channel pitch, diameter, taper angle, depth, and width on the propensity for particle separation. This study can be used to aid in the design of microfluidic devices for optimal size-based inertial particle separation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".