Phase Behavior of Rod–Coil Diblock Copolymer and Homopolymer Blends from Self-Consistent Field Theory
Bibliographic record
Abstract
The phase behavior of binary blends of rod-coil diblock copolymers and coil or rod homopolymers is studied by the self-consistent field theory (SCFT). The rod blocks are modeled as wormlike chains and the corresponding SCFT equations are solved using a hybrid method, in which the orientation-dependent functions are discretized on a unit sphere, while the positional space-dependent functions are treated using a spectral method. Phase diagrams of the blends are constructed as a function of the homopolymer volume fraction and phase segregation strength. It is discovered that the phase behavior of the system depends on the flexibility of the homopolymers. The addition of coil-homopolymers stabilizes the smectic phases. Low-molecular weight coil-homopolymers tend to mix with the coil-blocks, whereas high-molecular weight coil-homopolymers are mostly localized at the center of the coil-domains. On the other hand, the addition of rod-homopolymers strongly affects the orientation ordering of the system, leading to transitions between monolayer smectic-C, monolayer smectic-A and bilayer smectic-A phases.
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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 | 0.001 | 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) | 0.001 | 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".