Multiresponsive Azobenzene End-Cap for Self-Immolative Polymers
Bibliographic record
Abstract
Azobenzene was introduced as a new multiresponsive end-cap for self-immolative polymers. Using small-molecule model compounds, it was demonstrated that reducing agents including hydrazine and dithiothreitol could reduce the azobenzene to the corresponding hydrazobenzene, resulting in a 1,6-elimination reaction with the potential to initiate the depolymerization of self-immolative polycarbamates. An activated azobenzene derivative was then prepared, allowing for its incorporation as an end-cap for polycarbamates based on alternating N, N’ -dimethylethylene diamine and 4-hydroxybenzyl alcohol. Upon treatment with hydrazine, depolymerization proceeded. To demonstrate the versatility of this end-cap, the chemistry was also applied to polycarbamates based on 4-aminobenzyl alcohol. In addition to allowing triggered depolymerization, the azobenzene end-cap also provides a visual signal upon triggering owing to the strong visible absorption of the azobenzene, which shifts to the UV range upon reduction. Furthermore, azobenzene is capable of undergoing trans–cis isomerization in response to UV light, providing multiple functions in a single end-cap.
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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".