Surface modification of a polycarbonate-urethane using a vitamin-E-derivatized fluoroalkyl surface modifier
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
Fluorinated surface-modifying macromolecules (SMMs) have been previously reported on and shown to limit the hydrolytic degradation of polyurethanes. The SMM molecules achieve this effect by allowing for the selective migration of terminal fluorinated groups to the polymer's surface, which may then shield more hydrolytically-sensitive groups in the base polyurethane backbone. A further extension of the SMM concept would be to utilize the migration of the fluorine tails to simultaneously deliver biologically active moieties to the surface. This study explored the synthesis and characterization of a vitamin-E (natural anti-oxidant) coupled surface modifier, as a model for the bioactive SMM concept. The SMM was synthesized using lysine diisocyanate (LDI), polycarbonate diol (PCN), and a fluoroalcohol. By derivatizing the LDI pendant ester, vitamin E was coupled to the SMM. The vitamin-E SMM was physically characterized using gel-permeation chromatography (GPC) and its anti-oxidant activity was assessed in the presence of 0.1 mM NaOCl. Polymer degradation experiments were carried out using 10 mM NaOCl incubation solutions, and the relative material breakdown was assessed using GPC and scanning electron microscopy (SEM). The results indicate that while the fluoro-component reduced damage of the PU, the bioactive component achieved a further deactivating effect. A similar action may also be effective against superoxide anions generated by human macrophages.
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 | 0.001 | 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) | 0.000 | 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 it