Inertial particle separation in helical channels: A calibrated numerical analysis
Bibliographic record
Abstract
<p>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.</p>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".