Critical Point of Symmetric Binary Homopolymer Blends
Bibliographic record
Abstract
Monte Carlo field-theoretic simulations (MC-FTS) are performed on structurally symmetric binary homopolymer blends for invariant polymerization indexes of N ≥ 10 3 . It is shown that the ultraviolet (UV) divergence that plagues MC-FTS at small N can be removed by an appropriate renormalization of the Flory–Huggins interaction parameter, χ, allowing one to extract meaningful results that are independent of the wavevector cutoff. Once the divergence is taken care of, the fluctuation corrections to mean-field theory are found to be exceptionally small. In particular, the disordered-state structure function, S ( k ), is virtually indistinguishable from the RPA prediction, and there is a slight shift in the critical point, ( χ N ) c, that roughly scales as N –1/2 . An implication of the small corrections is that previous experimental determinations of χ based on homopolymer blends should be relatively accurate.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".