Enzyme-Initiated Devulcanization of Silicone–Gelatin Elastomers
Bibliographic record
Abstract
Silicone elastomers are valued for their resilience, particularly in stressful environments. Commercial cross-linking processes lead to covalent bonds based on Si–C or Si–O links, which, like all conventional rubbers, make degradation of the elastomer difficult at the end of life. We show that hydrated gelatin, a natural protein, can be covalently incorporated into silicone elastomers to produce hydrogels; the protein serves as both a diluent for silicone and a handle for devulcanization. Diacrylated cross-linkers based on poly(ethylene glycol) or triglycerol led to homo- and heteropolymer cross-linking between silicone and gelatin; the homogeneity of the elastomer products was dependent upon mixing prior to cure. Reactions occurred over a few hours at 80 °C to give hydrogels initially or, after drying, elastomers that exhibited the properties of both constituents. The cross-linked materials were stable during use, dry or after swelling in water, but very susceptible to enzymatic degradation to give silicone oils when treated with the enzymes bromelain and lipase.
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 | 0.001 |
| 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".