An Energy Tranfer Study of the Interface Thickness in Blends of Poly(butyl methacrylate) and Poly(2-ethylhexyl methacrylate)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We propose a model to describe energy transfer between donors and acceptors chemically attached to the two different components of a polymer blend. The model describes the case of one polymer dispersed as spheres of identical diameter in a continuous matrix of the second polymer. The model takes explicit account of the segment distribution of the two polymers in the interface region. We used this model to characterize the interface between poly(butyl methacrylate) (PBMA) and poly(2-ethylhexyl methacrylate) (PEHMA) domains in a binary blend. The blend was prepared by casting films onto a solid substrate from mixed aqueous latex dispersions of the two polymers. The dispersions were prepared by emulsion polymerization under conditions in which both components were formed as spherical particles with a very narrow size distribution. By using a 14:1 particle ratio of PEHMA to PBMA, we obtained films in which the 120 nm PBMA particles were surrounded by the PEHMA matrix. For the ion-exchanged latex blend, the interface thickness in the film freshly prepared at room temperature was δ = 21 ± 2 nm and upon annealing broadened to δ = 25 ± 2 nm. Because of the low degrees of polymerization for the samples, it is difficult to have confidence in the value of the Flory−Huggins parameter χ calculated from the experimental value of δ, because the correction for the finite length of the component is larger than the term that depends on the interface width. Keeping in mind the limitations of this calculation, we estimate that χ is approximately equal to 0.02−0.03.
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.
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 | 0.000 | 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 it