Phototactic microswimmers in pulsatile flow: Toward a novel harvesting method
Bibliographic record
Abstract
Phototactic behavior is coupled with pulsatile flow features to reveal the advantages of pulsation for separating motile algae cells in a double Y-microchannel. The underlying mechanism is as follows: during half of the pulsation cycle, when the flow rate is low, the phototactic microswimmers are mainly redirected by the external stimulation (light); while, during the rest of the cycle, the flow effects become dominant and the microswimmers are driven toward the desired outlet. The results show that in the absence of light source, the pulsatile flow has no advantage over the steady flow for separation, and the microswimmers have no preference between the exit channels; the separation index (SI) is around 50%. However, when the light is on, SI increases to 65% and 75% in the steady and pulsatile flows, respectively. Although the experiments are conducted on the well-known model alga, Chlamydomonas reinhardtii, a numerical simulation based on a simple model demonstrates that the idea can be extended to other active particles stimulated by an attractive or repulsive external field. Thus, the potential applications can go beyond algae harvesting to the control and enhancement of separation processes without using any mechanical component or chemical substance.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".