Phase Behavior of Binary Blends of Diblock Copolymers
Bibliographic record
Abstract
The phase behavior of binary blends of a long symmetric AB diblock copolymer and a short asymmetric AB diblock copolymer is studied using the self-consistent mean-field theory. The investigation focuses on blends with different short diblocks by constructing phase diagrams over the whole blending compositions and a large segregation regime. The influences of the chain length ratio (R) of the long and short diblock copolymers on their miscibility and on the stability of various ordered structures are explored. The theoretical results reveal that the blends have a much more complex phase behavior than each constituent copolymer. With the increase of the volume fraction of the short diblocks in the blends, multiple transitions from a long-period lamellar phase to phases with nonzero interfacial curvatures including cylindrical and spherical phases, and finally to a short-period lamellar phase or disordered phase, are predicted. In particular, consistent with experiments, the theory predicts that the cylindrical phase is stabilized over a wide blending compositions region in the strong segregation region, even though the two constituent diblock copolymers are both lamella-forming. When the ratio R is large enough, macrophase separation occurs over a wide range of blending compositions in a relatively strong segregation regime. Various coexisting phases, including those of lamellar and disorder, lamellar and cylindrical, cylindrical and cylindrical, cylindrical and disorder, spherical and disorder, and cylindrical and spherical, are predicted. In addition, the density profiles of the typical ordered structures are presented in order to understand the self-organization of the different copolymer chains.
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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 | 0.000 |
| 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".