Langmuir and Langmuir–Blodgett Monolayer Studies of First-Generation Photoswitchable Donor–Acceptor Stenhouse Adduct Surfactants
Bibliographic record
Abstract
Donor–acceptor Stenhouse adducts (DASAs) are photoswitchable, solvatochromic organic molecules that can interconvert between a linear and cyclic form with visible light photoillumination. While applications of these species for phototherapy abound, their molecular packing into films and film deposition capacity remain poorly understood. In this work, the surface activity and film-forming ability of a synthetic “1 st generation” DASA, a photoswitchable, solvatochromic surfactant, have been investigated using Langmuir and Langmuir monolayer approaches. Unlike shorter tail chain variants, the 18-carbon long tail chain molecule, dubbed D18, formed stable monolayers at the air–water interface when D18 is in both the linear (“dark”) and cyclic (“illuminated”) forms, and to our knowledge, this is the first ever report of their monolayer properties. Packing, phase behavior, and micrometer-scale morphology of D18 films at the air–water interface were probed, and film characteristics were compared with closely related molecules in the literature; the systems share some common features with films formed from phospholipids and affiliated lipids. However, neither the linear nor the cyclic form transfers with good efficiency onto solid substrates as monolayers and tends to form complex multilayers with aggregates during deposition.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".