Capillary instability of axisymmetric, active liquid crystal jets
Bibliographic record
Abstract
We study linear stability of an infinitely long, axisymmetric, cylindrical active liquid crystal (ALC) jet in a passive isotropic fluid matrix using a polar active liquid crystal (ALC) model. We identify three possible unstable modes (or mechanisms) as the result of the interaction between the flow and the active (or self-propelled) molecular motion. The first unstable mode is related to the polarity vector instability when coupled to the flow field in the presence of the molecular activity. It can be traced back to the inherent polarity vector instability in a bulk active liquid crystal flow. However, it can be grossly amplified in the ALC jet to encompass up to infinitely many unstable growth rates when the long range distortional elastic interaction is weak in certain parameter regimes; it can also be suppressed in other parameter regimes completely. The second unstable mode is related to the classical capillary or Rayleigh instability, which exists in a finite wave interval [0, k(cutoff)]. The new feature for this instability lies in the dependence of the cutoff wave number (k(cutoff)) on the activity of the active matter system. For ALC jets with sufficiently strong contractile activity, the instability can be completely suppressed though. The third unstable mode is due to the active viscous stress. This unstable mode can emerge in the intermediate wave number regime at a sufficiently strong active viscosity and even expand all the way to the zero wave number limit when the Rayleigh unstable mode is absent. It can also be suppressed in the regime of weak active viscous stress. At any given values of the model parameters, the three types of instabilities can show up either individually or in a certain combination, or be completely suppressed altogether. In this paper, we discuss the positive growth rates associated with the instabilities, windows of instability and their dependence on model parameters through extensive numerical computations aided by asymptotic analyses.
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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) | 0.002 | 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 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".