Dielectric response of particles in flowing media: The effect of shear-induced rotation on the variation in particle polarizability
Bibliographic record
Abstract
When particles in liquid suspensions flow through channels and pipes in a laminar fashion, the resulting parabolic velocity profile gives rise to shear, which induces the particles to rotate. If flowing suspensions containing dielectric particles are immersed in an external electric field, the anisotropic polarization induced in rotating nonspherical particles will vary with the orientation of the particle with respect to the external field; what results is an uncertainty in experimental measurements that involve particle polarization. The present study establishes the limits of this uncertainty and shows that departure from spherical symmetry in individual particles can lead to a significant overlap in measurements attempting to discriminate between particle subpopulations in suspensions. For example, the uncertainty in signal amplitude for a population of activated T-lymphocytes can be as high as 20%. Such concerns arise in applications like field-flow fractionation, dielectrophoretic sorting of particles, flow impedance measurements and cytometry, and, most recently, isodielectric separation, all of which are used to separate particles in a flow based on their dielectric response. This paper considers axisymmetric particles as the first departure from the approximation of spherical symmetry, shows how to calculate an estimate of the size of the population overlap, and suggests possible strategies to minimize it.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".