Assessing flow alignment of nematic liquid crystals through linear viscoelasticity
Bibliographic record
Abstract
Shear alignment of rodlike nematic liquid crystals is found when the reactive parameter $\ensuremath{\lambda}>1$. Measurements of $\ensuremath{\lambda}$ usually require complex experiments. This paper presents a method based on the nematodynamic theory of Leslie and Ericksen that assesses flow alignment through small amplitude oscillatory flow. The method is based on the fact that the effect of $\ensuremath{\lambda}$ on the storage modulus ${G}^{\ensuremath{'}}$ of linear viscoelasticity, when the director is along the flow direction, is directly proportional to $\ensuremath{\lambda}\ensuremath{-}1$. Thus the alignment-nonalignment transition for increasing lambda is a reentrant viscoelastic transition: viscoelastic $(\ensuremath{\lambda}<1)$\ensuremath{\rightarrow}purely viscous $(\ensuremath{\lambda}=0)$\ensuremath{\rightarrow}viscoelastic $(\ensuremath{\lambda}>1)$ that is reflected in the storage modulus ${G}^{\ensuremath{'}}$ and in the ``loss angle'' $\ensuremath{\delta}={\mathrm{tan}}^{\ensuremath{-}1}({G}^{\ensuremath{''}}∕{G}^{\ensuremath{'}})$. The methodology is demonstrated by analyzing the Leslie-Ericksen equations for small-amplitude oscillatory Poiseuille flow of $(4\text{\ensuremath{-}}\mathrm{n}\text{\ensuremath{-}}\mathrm{\text{octyl}}\text{\ensuremath{-}}{4}^{\ensuremath{'}}\text{\ensuremath{-}}\mathrm{\text{cyanobiphenyl}})$ (8CB) using analytical and scaling methods. Since linear viscoelastic moduli are easily accessible, the proposed methodology is an additional useful and economical tool for nematodynamicists.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".