Entropic surface segregation from athermal polymer blends: Polymer flexibility vs bulkiness
Bibliographic record
Abstract
We examine athermal binary blends composed of conformationally asymmetric polymers of equal molecular volume next to a surface of width ξ. The self-consistent field theory (SCFT) of Gaussian chains predicts that the more compact polymer with the shorter average end-to-end length, R0, is entropically favored at the surface. Here, we extend the SCFT to worm-like chains with small persistence lengths, ℓp, relative to their contour lengths, ℓc, for which R0≈2ℓpℓc. In the limit of ℓp ≪ ξ, we recover the Gaussian-chain prediction where the segregation depends only on the product ℓpℓc, but for realistic polymer/air surfaces with ξ ∼ ℓp, the segregation depends separately on the two quantities. Although the surface continues to favor flexible polymers with smaller ℓp and bulky polymers with shorter ℓc, the effect of bulkiness is more pronounced. This imbalance can, under specific conditions, lead to anomalous surface segregation of the more extended polymer. For this to happen, the polymer must be bulkier and stiffer, with a stiffness that is sufficient to produce a larger R0 yet not so rigid as to reverse the surface affinity that favors bulky polymers.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".