Self-Assembly of Linear ABCBA Pentablock Terpolymers
Bibliographic record
Abstract
The phase behavior of linear ABCBA pentablock terpolymers is examined and compared with corresponding linear ABC triblock terpolymers by using the 3-D self-consistent field theory. In particular, phase diagrams of the melts are constructed and used to discuss how the self-assembled morphologies are influenced by the compositions of the three components and the block number per chain. Since the two free ends of A blocks in the ABCBA copolymers enable the macromolecules to relieve the packing frustration within the structures as well as more types of chain conformation, the ABCBA pentablocks exhibit diverse complex network structures and binary crystalline phases of cylinders and spheres. Compared with most linear diblock and triblock copolymers, for which the gyroid phase occupies a narrow region in the phase space, the ABCBA pentablocks tend to form a variety of continuous networks including diamond, hexagonally perforated lamellae, Fddd network, and gyroid. Moreover, the ABCBA pentablocks exhibit different packing orders of alternating A/C spheres and cylinders than ABC. By varying the length of the B-blocks and the ratio of compositions of A and C, a large number of binary metallic and ionic crystals, such as NaCl, CsCl, ZnS, CaF 2, Li 3 Bi, Nb 3 Sn (A15), and Cu 3 Au, and alternating A/C cylinders with coordination numbers of A/C equal to 4/4, 6/3, and 4/2, are obtained from the ABCBA pentablock terpolymers. As our simulated ABCBA pentablock terpolymers have synthetic advantages, the fascinating self-assembling results displayed in this study enable the ABCBA as being one of the most efficient routes to functional materials.
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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".