Two‐Photon Excitation of a Plasmonic Nanoswitch Monitored by Single‐Molecule Fluorescence Microscopy
Bibliographic record
Abstract
Visible-light excitation of the surface plasmon band of silver nanoplates can effectively localize and concentrate the incident electromagnetic field enhancing the photochemical performance of organic molecules. Herein, the first single-molecule study of the plasmon-assisted isomerization of a photochrome-fluorophore dyad, designed to switch between a nonfluorescent and a fluorescent state in response to the photochromic transformation, is reported. The photochemistry of the switchable assembly, consisting of a photochromic benzooxazine chemically conjugated to a coumarin moiety, is examined in real time with total internal reflection fluorescence microscopy in the presence of silver nanoplates excited with a 633 nm laser. The metallic nanostructures significantly enhance the visible light-induced performance of the photoconversion, which normally requires ultraviolet excitation. The resulting ring-open isomer is strongly fluorescent and can also be excited at 633 nm. These stochastic emission events are used to monitor photochromic activation and show quadratic dependence on incident power. The utilization of a single laser wavelength for both photochromic activation and excitation effectively mimics a pseudo two-colours system.
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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) | 0.000 | 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 | 0.001 |
| 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".