Photo-crosslinked Diels–Alder and thiol–ene polymer networks
Bibliographic record
Abstract
= 0.08) was similarly crosslinked in single and dual crosslinked networks with BM : FMA of 0.1 and 0.2. Crosslinking efficiency was evaluated for both single and dual crosslinked networks with a BM : FMA = 0.1 by comparing thermal and UV curing methods, with UV curing proving more effective for dual-crosslinked systems, leading to increased gel content (71% with UV compared to 61% thermally) and improved material properties. FTIR and DSC results confirmed the formation of the DA adducts and the reversibility of the DA reaction. The terpolymers were further analyzed for adhesive applications through rheological testing. These studies demonstrated that the incorporation of thiol-ene crosslinking alongside Diels-Alder crosslinking offers a balanced combination of reversible and permanent bonds, resulting in materials with enhanced mechanical strength, thermal stability, and functional versatility that are suitable for applications such as recyclable adhesives.
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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) | 0.001 | 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".