Binary Blends of Diblock Copolymers: An Efficient Route to Complex Spherical Packing Phases
Bibliographic record
Abstract
Abstract The phase behavior of binary blends composed of AB and AB diblock copolymers is systematically studied using the polymeric self‐consistent field theory, focusing on the formation and relative stability of various spherical packing phases. The results are summarized in a set of phase diagrams covering a large phase space of the system. Besides the commonly observed body‐centered‐cubic phase, complex spherical packing phases including the Frank–Kasper A15, and the Laves C14, C15 phases could be stabilized by the addition of longer AB‐copolymers to asymmetric AB‐copolymers. Stabilizing the complex spherical packing phases requires that the added AB‐copolymers have a longer A‐block and an overall chain length at least comparable to the host copolymer chains. A detailed analysis of the block distributions reveals the existence of inter‐ and intra‐domain segregation of different copolymers, which depends sensitively on the copolymer length ratio and composition. The predicted phase behaviours of the AB/AB diblock copolymer blends are in good agreement with previous experimental and theoretical results. The study demonstrates that binary blends of diblock copolymers provide an efficient route to regulate the emergence and stability of complex spherical packing 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 | 0.000 | 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".