Energy Transfer in the Restricted Geometry of Lamellar Block Copolymer Interfaces
Bibliographic record
Abstract
We carried out simulations of energy transfer kinetics for lamellar block copolymer systems in which donor and acceptor dyes were attached to the block junctions. We considered blocks of homopolymers that were sufficiently immiscible and of sufficiently high molecular weight to employ the Helfand−Tagami distribution of block junctions. The morphology of such block copolymers has been frequently discussed in terms of an apparent dimension parameter, which is recovered from the analysis of fluorescence decay curves, using the Klafter−Blumen (KB) formalism. Here, we investigate how such apparent dimensions are influenced by the interface thickness between the two blocks (which is dependent on the Flory−Huggins χ parameter of the system). We also probe the dependence of this apparent dimension on the concentration of the dyes in labeled samples. This kind of dependence has been experimentally observed but never explained, perhaps because of the approximations inherent in using the KB model to analyze fluorescent decay curves for block copolymer systems. We have found that apparent dimensions approach three for reasonably broad interfaces, but decrease to near two for very narrow interfaces, in accordance with asymptotic formulas that we propose for strongly segregated, lamellar block copolymer melts. Global analysis of the decay curves, as well as weighted linear regression of the parameters obtained from individual analyses of the decays, suggest linear relationships between the apparent dimensions from KB analyses and acceptor concentrations. We discuss the dependence on interface thickness in terms of the basic (Förster) theory of direct energy transfer, and indicate why the KB model is a reasonable representation of lamellar block copolymers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".