Phase behavior of triblock copolymer and homopolymer blends: Effect of copolymer topology
Bibliographic record
Abstract
Two distinct linear triblock copolymers with different block sequences, ABA or BAB, are obtained when two identical AB diblock copolymers are jointed at their B or A ends, respectively, resulting in three homologous, AB diblock, ABA, and BAB triblock copolymers with the same chemical composition but different topologies. We demonstrate that the topological effect on the phase behaviors of these copolymers is amplified when A homopolymers are added to the system. Specifically, the phase behaviors of binary blends composed of ABA or BAB linear triblock copolymers and A homopolymers are studied by using the random-phase approximation (RPA) and self-consistent field theory (SCFT). The RPA analysis predicts that the Lifshitz point for the ABA/A blends behaves like a second-order transition but that for the BAB/A blends behaves like a first-order transition. The Lifshitz point of the BAB/A mixtures is found to occur at a much lower homopolymer concentration than that of the ABA/A mixtures, indicating a poorer miscibility of the A homopolymers into the BAB than ABA triblocks, which is also confirmed by SCFT. For sphere-forming triblock copolymers mixed with homopolymers, the poorer miscibility and the more diffused distribution of the A homopolymers in the BAB/A blends result in a phase behavior drastically different from that of the ABA/A and AB/A blends. The ABA/A blends stabilize the Frank-Kasper (FK) phases similar to the AB/A blends, but the stability window of FK phases becomes negligibly small in the corresponding BAB/A blends. Our results demonstrate that the topological effect of block copolymers on the equilibrium phase behaviors can be more prominent in multicomponent systems and thus more attention should be paid to copolymer topologies in the design of polymeric blends. Published by the American Physical Society 2024
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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".