Grafted polymers inside cylindrical tubes: Chain stretching vs layer thickness
Bibliographic record
Abstract
We present a study of the detailed structure of grafted polymer chains and the layers they form inside cylindrical tubes, using the finitely extensible nonlinear elastic chain model and numerical self-consistent field theory. For very large tube radius, the chain stretching and layer thicknesses are the same as for polymers grafted to a planar surface. For decreasing radius, our calculations indicate that the layer almost always gets thinner, although there can be situations where it is very slightly thicker. However, we find that this thinning is not necessarily due to changes to the polymers: in fact, the root-mean-squared layer thickness would decrease even if the polymers themselves are completely unchanged. Furthermore, we find that the polymer stretching can increase at the same time that the layer thickness decreases. These apparent paradoxes are resolved by analyzing and distinguishing between the volume fraction profiles and monomer number distributions in these systems, including how they change and why. We also find that, in a given system, parts of each polymer move towards the curved surface and parts away from it, and that these differences are key to understanding the behavior.
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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".