Effect of hydrogen-bond strength on photoresponsive properties of polymer-azobenzene complexes
Bibliographic record
Abstract
Supramolecular complexation between photoresponsive azobenzene chromophores and a photopassive polymer host offers synthetic and design advantages compared with conventional covalent azo-containing polymers. In this context, it is important to understand the impact of the strength of the supramolecular interaction on the optical response. Herein, we study the effect of hydrogen-bonding strength between a photopassive polymer host [poly(4-vinylpyridine), or P4VP] and three azobenzene analogues capable of forming weaker (hydroxyl), stronger (carboxylic acid), or no H-bonding with P4VP. The hydroxyl-functionalized azo forms complete H-bonding complexation up to equimolar ratio with VP, whereas the COOH-functionalized azo reaches only up to 30% H-bond complexation due to competing acid dimerization that leads to partial phase separation and azo crystallization. We show that the stronger azo-polymer H-bonding nevertheless provides higher photoinduced orientation and better performance during optical surface patterning, in terms of grating depth and diffraction efficiency, when phase separation is either avoided altogether or is limited by using relatively low azo contents. These results demonstrate the importance of the H-bonding strength on the photoresponse of azopolymer complexes, as well as the need to consider the interplay between different intermolecular interactions that can affect complexation.
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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 | 0.001 |
| 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".