Bibliographic record
Abstract
Abstract Most silicone elastomers are thermosets. As a response to the new paradigm of polymer recyclability, the development of silicone elastomers that can be reversibly and repeatedly cured and uncrosslinked using redox conditions is reported. Thiopropyl‐modified silicones are oxidized to elastomers with disulfide crosslinks using the organosoluble oxidant PhI(OAc)2. As with any elastomer, mechanical properties can be tuned by varying crosslink density. Thermal stabilities in air show that the products are comparable to traditional silicone thermosets, with degradation only starting over 300 °C. Uncrosslinking back to the same thiopropyl‐modified silicones involves reductive S–S bridge cleavage using a Piers–Rubinsztajn reaction with hydrosilanes catalyzed by B(C6F5)3; HSiMe2OSiMe3is identified as a convenient reducing agent. The initially formed silicone‐(CH2)3S‐SiMe2OSiMe3products need deprotection with water in isopropanol/water to completely regenerate the thiopropylsilicones. This oxidation/reduction crosslinking/uncrosslinking cycle is practiced thrice, with a yield of 89% per cycle, with essentially no change in the Young's moduli of the elastomers, or1H NMR spectra of the uncrosslinked fluids after reduction. Further oxidation of disulfide groups on the elastomer surface permanently and significantly improved water wettability.
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 | 0.000 |
| 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) | 0.002 | 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".