The structure factor of a wormlike chain and the random-phase-approximation solution for the spinodal line of a diblock copolymer melt
Bibliographic record
Abstract
An efficient and convenient numerical approach to calculate the structure factor of a wormlike chain model is proposed by directly dealing with a formal solution of the Green's function. A precise numerical representation of the structure factor of the wormlike chain model is then obtained, for arbitrary chain rigidity. On one hand, in the flexible limit, the numerical results recover the well-known Debye function of the structure factor of a Gaussian chain and furthermore predict the correct large-k behavior that a Gaussian model fails to capture; on the other hand, in the rigid limit, the numerical results recover the well-known Neugebauer function of the structure factor of a rigid rod. Based on the calculated structure factor, the random phase approximation is employed to study the physical properties of the order-disorder transition for asymmetric wormlike diblock copolymers; particularly, the spinodal line of the disordered phase is calculated. For the case of symmetric diblock copolymer microphase separation, the present calculation reproduces the phase boundary previously determined by self-consistent field theories and yields the entire picture crossing over from the flexible-chain limit to the rigid-chain limit.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".