Influence of Entanglements on the Time Dependence of Mixing in Nonradiative Energy Transfer Studies of Polymer Diffusion in Latex Films
Bibliographic record
Abstract
We report energy transfer experiments on poly(butyl methacrylate) (PBMA) latex films prepared from a 1:1 mixture of donor- and acceptor-labeled latex particles. In one set of samples, the particles contain low molecular weight polymer ( M w = 34 000) comparable to the entanglement molecular weight ( M e ) of PBMA. For this sample, the extent of mixing f m (defined as the fractional increase in the energy transfer quantum yield) increased with time as t 1/2, consistent with diffusion that follows Fick's law. In the second set of experiments, involving polymer with M w = 380 000 ( M w > 10 M e ), we observe a change in the time dependence of f m . At early times, for values of f m < 0.2, f m scales as t 1/2 . There is a sharp crossover to a t 1/4 scaling relationship for values of f m > 0.2. The most likely explanation of the early-time behavior is Fickian diffusion of the lowest molecular weight components of the broadly disperse polymer ( M w / M n = 3). The scaling of f m with t 1/4 does not appear to be consistent with the predictions of the theory of polymer diffusion across interfaces. The parameter f m is a measure of the number of monomers crossing the interface N ( t ). For diffusion across a planar interface, N ( t ) is predicted to increase as t 3/4 if the chain ends are uniform and as t 1/2 if they are segregated to the interface.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 |
| 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".