Fluctuation stabilization of the <i>Fddd</i> network phase in diblock, triblock, and starblock copolymer melts
Bibliographic record
Abstract
The latest complex network phase to be discovered in diblock copolymer melts is the orthorhombic $F\phantom{\rule{0}{0ex}}d\phantom{\rule{0}{0ex}}d\phantom{\rule{0}{0ex}}d$ phase. Mean-field theory predicts it to be stable, but only at weak segregations where ordered phases are typically destroyed by thermal fluctuations. Indeed, Landau-Brazovskii theory confirmed this expectation, raising the question of how $F\phantom{\rule{0}{0ex}}d\phantom{\rule{0}{0ex}}d\phantom{\rule{0}{0ex}}d$ survives in experiments. However, this problem was recently resolved by accurate field-theoretic simulations, which found that $F\phantom{\rule{0}{0ex}}d\phantom{\rule{0}{0ex}}d\phantom{\rule{0}{0ex}}d$ is simply more resilient to fluctuations than other ordered phases. Here, the authors find that this is also true for the family of (AB)${}_{M}$ starblock copolymer architectures. This resilience may very well extend to numerous other architectures, and thus it would be prudent to keep our eyes open for $F\phantom{\rule{0}{0ex}}d\phantom{\rule{0}{0ex}}d\phantom{\rule{0}{0ex}}d$.
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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".