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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".