Compartmentalizing Donor–Acceptor Stenhouse Adducts for Structure–Property Relationship Analysis
Bibliographic record
Abstract
The development of photoswitches that absorb low energy light is of notable interest due to the growing demand for smart materials and therapeutics necessitating benign stimuli. Donor-acceptor Stenhouse adducts (DASAs) are molecular photoswitches that respond to light in the visible to near-infrared spectrum. As a result of their modular assembly, DASAs can be modified at the donor, acceptor, triene, and backbone heteroatom molecular compartments for the tuning of optical and photoswitching properties. This Perspective focuses on the electronic and steric contributions at each compartment and how they influence photophysical properties through the adjustment of the isomerization energetic landscape. An emphasis on current synthetic strategies and their limitations highlights opportunities for DASA architecture, and thus photophysical property expansion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".