Copper crosslinked silicone elastomers in RGB colors: degradable on demand
Bibliographic record
Abstract
Increasing demand for fully recyclable polymers has prompted an interest in materials crosslinked via non-covalent interactions. Aggressive depolymerization can cleave backbone SiO bonds to generate linear oils or cyclic monomers from silicone rubbers, but one would rather recover the starting material oils simply by selectively breaking crosslinks. We demonstrate that ligand binding to metals can be used to reversibly crosslink silicone chains. Aminopropylsilicones were crosslinked via complexation with copper (II) acetate to form blue silicone oils. These oils slowly cured in air at room temperature to form soft, green elastomers over a month, or overnight at 50–55 °C in air to give robust, hard red elastomers. Potential explanations for the observed color changes are discussed. Elastomers prepared by either pathway underwent ready degradation by removal of the copper ions via competitive ligand binding using ethylenediamine, allowing for recovery of the unmodified silicone oil; the recovered amine could be reused with more copper to form a (softer) elastomer. This process provides a method for the synthesis of stable elastomeric silicones that are degradable on demand.
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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 | 0.001 |
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".